WorldWideScience

Sample records for model metal-reducing microbial

  1. Development of a Model, Metal-reducing Microbial Community for a System Biology Level Assessment of Desulfovibrio vulgaris as part of a Community

    Energy Technology Data Exchange (ETDEWEB)

    Elias, Dwayne; Schadt, Christopher; Miller, Lance; Phelps, Tommy; Brown, S. D.; Arkin, Adam; Hazen, Terry; Drake, Megin; Yang, Z.K.; Podar, Mircea

    2010-05-17

    One of the largest experimental gaps is between the simplicity of pure cultures and the complexity of open environmental systems, particularly in metal-contaminated areas. These microbial communities form ecosystem foundations, drive biogeochemical processes, and are relevant for biotechnology and bioremediation. A model, metal-reducing microbial community was constructed as either syntrophic or competitive to study microbial cell to cell interactions, cell signaling and competition for resources. The microbial community was comprised of the metal-reducing Desulfovibrio vulgaris Hildenborough and Geobacter sulfurreducens PCA. Additionally, Methanococcus maripaludis S2 was added to study complete carbon reduction and maintain a low hydrogen partial pressure for syntrophism to occur. Further, considerable work has been published on D. vulgaris and the D. vulgaris/ Mc. maripaludis co-culture both with and without stress. We are extending this work by conducting the same stress conditions on the model community. Additionally, this comprehensive investigation includes physiological and metabolic analyses as well as specially designed mRNA microarrays with the genes for all three organisms on one slide so as to follow gene expression changes in the various cultivation conditions as well as being comparable to the co- and individual cultures. Further, state-of -the-art comprehensive AMT tag proteomics allows for these comparisons at the protein level for a systems biology assessment of a model, metal-reducing microbial community. Preliminary data revealed that lactate oxidation by D. vulgaris was sufficient to support both G. sulfurreducens and M. maripaludis via the excretion of H2 and acetate. Fumarate was utilized by G. sulfurreducens and reduced to succinate since neither of the other two organisms can reduce fumarate. Methane was quantified, suggesting acetate and H2 concentrations were sufficient for M. maripaludis. Steady state community cultivation will allow for

  2. Bacteriophage Infection of Model Metal Reducing Bacteria

    Science.gov (United States)

    Weber, K. A.; Bender, K. S.; Gandhi, K.; Coates, J. D.

    2008-12-01

    Microbially-mediated metal reduction plays a significant role controlling contaminant mobility in aqueous, soil, and sedimentary environments. From among environmentally relevant microorganisms mediating metal reduction, Geobacter spp. have been identified as predominant metal-reducing bacteria under acetate- oxidizing conditions. Due to the significance of these bacteria in environmental systems, it is necessary to understand factors influencing their metabolic physiology. Examination of the annotated finished genome sequence of G. sulfurreducens PCA, G. uraniumreducens Rf4, G. metallireduceans GS-15 as well as a draft genome sequence of Geobacter sp. FRC-32 have identified gene sequences of putative bacteriophage origin. Presence of these sequences indicates that these bacteria are susceptible to phage infection. Polymerase chain reaction (PCR) primer sets designed tested for the presence of 12 of 25 annotated phage-like sequences in G. sulfurreducens PCA and 9 of 17 phage-like sequences in FRC- 32. The following genes were successfully amplified in G. sulfurreducens PCA: prophage type transcription regulator, phage-induced endonuclease, phage tail sheath, 2 phage tail proteins, phage protein D, phage base plate protein, phage-related DNA polymerase, integrase, phage transcriptional regulator, and Cro-like transcription regulator. Nine of the following sequences were present in FRC-32: 4 separate phage- related proteins, phage-related tail component, viron core protein, phage Mu protein, phage base plate, and phage tail sheath. In addition to the bioinformatics evidence, incubation of G. sulfurreducens PCA with 1 μg mL-1 mytomycin C (mutagen stimulating prophage induction) during mid-log phase resulted in significant cell lysis relative to cultures that remained unamended. Cell lysis was concurrent with an increase in viral like particles enumerated using epifluorescent microscopy. In addition, samples collected following this lytic event (~44hours) were

  3. Microbial community succession during lactate amendment and electron acceptor limitation reveals a predominance of metal-reducing Pelosinus spp.

    Science.gov (United States)

    Mosher, Jennifer J; Phelps, Tommy J; Podar, Mircea; Hurt, Richard A; Campbell, James H; Drake, Meghan M; Moberly, James G; Schadt, Christopher W; Brown, Steven D; Hazen, Terry C; Arkin, Adam P; Palumbo, Anthony V; Faybishenko, Boris A; Elias, Dwayne A

    2012-04-01

    The determination of the success of in situ bioremediation strategies is complex. By using controlled laboratory conditions, the influence of individual variables, such as U(VI), Cr(VI), and electron donors and acceptors on community structure, dynamics, and the metal-reducing potential can be studied. Triplicate anaerobic, continuous-flow reactors were inoculated with Cr(VI)-contaminated groundwater from the Hanford, WA, 100-H area, amended with lactate, and incubated for 95 days to obtain stable, enriched communities. The reactors were kept anaerobic with N(2) gas (9 ml/min) flushing the headspace and were fed a defined medium amended with 30 mM lactate and 0.05 mM sulfate with a 48-h generation time. The resultant diversity decreased from 63 genera within 12 phyla to 11 bacterial genera (from 3 phyla) and 2 archaeal genera (from 1 phylum). Final communities were dominated by Pelosinus spp. and to a lesser degree, Acetobacterium spp., with low levels of other organisms, including methanogens. Four new strains of Pelosinus were isolated, with 3 strains being capable of Cr(VI) reduction while one also reduced U(VI). Under limited sulfate, it appeared that the sulfate reducers, including Desulfovibrio spp., were outcompeted. These results suggest that during times of electron acceptor limitation in situ, organisms such as Pelosinus spp. may outcompete the more-well-studied organisms while maintaining overall metal reduction rates and extents. Finally, lab-scale simulations can test new strategies on a smaller scale while facilitating community member isolation, so that a deeper understanding of community metabolism can be revealed.

  4. Modeling microbial growth and dynamics.

    Science.gov (United States)

    Esser, Daniel S; Leveau, Johan H J; Meyer, Katrin M

    2015-11-01

    Modeling has become an important tool for widening our understanding of microbial growth in the context of applied microbiology and related to such processes as safe food production, wastewater treatment, bioremediation, or microbe-mediated mining. Various modeling techniques, such as primary, secondary and tertiary mathematical models, phenomenological models, mechanistic or kinetic models, reactive transport models, Bayesian network models, artificial neural networks, as well as agent-, individual-, and particle-based models have been applied to model microbial growth and activity in many applied fields. In this mini-review, we summarize the basic concepts of these models using examples and applications from food safety and wastewater treatment systems. We further review recent developments in other applied fields focusing on models that explicitly include spatial relationships. Using these examples, we point out the conceptual similarities across fields of application and encourage the combined use of different modeling techniques in hybrid models as well as their cross-disciplinary exchange. For instance, pattern-oriented modeling has its origin in ecology but may be employed to parameterize microbial growth models when experimental data are scarce. Models could also be used as virtual laboratories to optimize experimental design analogous to the virtual ecologist approach. Future microbial growth models will likely become more complex to benefit from the rich toolbox that is now available to microbial growth modelers.

  5. Using proteomic data to assess a genome-scale "in silico" model of metal reducing bacteria in the simulation of field-scale uranium bioremediation

    Science.gov (United States)

    Yabusaki, S.; Fang, Y.; Wilkins, M. J.; Long, P.; Rifle IFRC Science Team

    2011-12-01

    A series of field experiments in a shallow alluvial aquifer at a former uranium mill tailings site have demonstrated that indigenous bacteria can be stimulated with acetate to catalyze the conversion of hexavalent uranium in a groundwater plume to immobile solid-associated uranium in the +4 oxidation state. While this bioreduction of uranium has been shown to lower groundwater concentrations below actionable standards, a viable remediation methodology will need a mechanistic, predictive and quantitative understanding of the microbially-mediated reactions that catalyze the reduction of uranium in the context of site-specific processes, properties, and conditions. At the Rifle IFRC site, we are investigating the impacts on uranium behavior of pulsed acetate amendment, acetate-oxidizing iron and sulfate reducing bacteria, seasonal water table variation, spatially-variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties. The simulation of three-dimensional, variably saturated flow and biogeochemical reactive transport during a uranium bioremediation field experiment includes a genome-scale in silico model of Geobacter sp. to represent the Fe(III) terminal electron accepting process (TEAP). The Geobacter in silico model of cell-scale physiological metabolic pathways is comprised of hundreds of intra-cellular and environmental exchange reactions. One advantage of this approach is that the TEAP reaction stoichiometry and rate are now functions of the metabolic status of the microorganism. The linkage of in silico model reactions to specific Geobacter proteins has enabled the use of groundwater proteomic analyses to assess the accuracy of the model under evolving hydrologic and biogeochemical conditions. In this case, the largest predicted fluxes through in silico model reactions generally correspond to high abundances of proteins linked to those reactions (e.g. the condensation reaction catalyzed by the protein

  6. MATHEMATICAL MODEL OF THE MICROBIAL FLOODING

    Institute of Scientific and Technical Information of China (English)

    Lei Guang-lun; Zhang Zhong-zhi; Chen Yue-ming

    2003-01-01

    On the basis of growth kinetics of microorganism and the principle of material balance, equations were derived to describe microbial growth, nutrient consumption, metabolites production and their transport in formation. The changes in porosity, permeability, oil viscosity and capillary force were also described as the main facturs of microbial flooding. For reservoirs with black oil properties, three-dimensional three-phase mathematical models with the cosidaration of multi-microbial components were established to depict microbial flooding oil. With this model, calculated results are in good agreement with experimental data.

  7. Mathematical modeling of microbial growth in milk

    Directory of Open Access Journals (Sweden)

    Jhony Tiago Teleken

    2011-12-01

    Full Text Available A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.

  8. Modeling Approaches for Describing Microbial Population Heterogeneity

    DEFF Research Database (Denmark)

    Lencastre Fernandes, Rita

    , ethanol and biomass throughout the reactor. This work has proven that the integration of CFD and population balance models, for describing the growth of a microbial population in a spatially heterogeneous reactor, is feasible, and that valuable insight on the interplay between flow and the dynamics......Although microbial populations are typically described by averaged properties, individual cells present a certain degree of variability. Indeed, initially clonal microbial populations develop into heterogeneous populations, even when growing in a homogeneous environment. A heterogeneous microbial......) to predict distributions of certain population properties including particle size, mass or volume, and molecular weight. Similarly, PBM allow for a mathematical description of distributed cell properties within microbial populations. Cell total protein content distributions (a measure of cell mass) have been...

  9. Multiscale Modeling of Microbial Communities

    Science.gov (United States)

    Blanchard, Andrew

    Although bacteria are single-celled organisms, they exist in nature primarily in the form of complex communities, participating in a vast array of social interactions through regulatory gene networks. The social interactions between individual cells drive the emergence of community structures, resulting in an intricate relationship across multiple spatiotemporal scales. Here, I present my work towards developing and applying the tools necessary to model the complex dynamics of bacterial communities. In Chapter 2, I utilize a reaction-diffusion model to determine the population dynamics for a population with two species. One species (CDI+) utilizes contact dependent inhibition to kill the other sensitive species (CDI-). The competition can produce diverse patterns, including extinction, coexistence, and localized aggregation. The emergence, relative abundance, and characteristic features of these patterns are collectively determined by the competitive benefit of CDI and its growth disadvantage for a given rate of population diffusion. The results provide a systematic and statistical view of CDI-based bacterial population competition, expanding the spectrum of our knowledge about CDI systems and possibly facilitating new experimental tests for a deeper understanding of bacterial interactions. In the following chapter, I present a systematic computational survey on the relationship between social interaction types and population structures for two-species communities by developing and utilizing a hybrid computational framework that combines discrete element techniques with reaction-diffusion equations. The impact of deleterious and beneficial interactions on the community are quantified. Deleterious interactions generate an increased variance in relative abundance, a drastic decrease in surviving lineages, and a rough expanding front. In contrast, beneficial interactions contribute to a reduced variance in relative abundance, an enhancement in lineage number, and a

  10. Microbial growth modelling with artificial neural networks.

    Science.gov (United States)

    Jeyamkonda, S; Jaya, D S; Holle, R A

    2001-03-20

    There is a growing interest in modelling microbial growth as an alternative to time-consuming, traditional, microbiological enumeration techniques. Several statistical models have been reported to describe the growth of different microorganisms, but there are accuracy problems. An alternate technique 'artificial neural networks' (ANN) for modelling microbial growth is explained and evaluated. Published data were used to build separate general regression neural network (GRNN) structures for modelling growth of Aeromonas hydrophila, Shigella flexneri, and Brochothrix thermosphacta. Both GRNN and published statistical model predictions were compared against the experimental data using six statistical indices. For training data sets, the GRNN predictions were far superior than the statistical model predictions, whereas the GRNN predictions were similar or slightly worse than statistical model predictions for test data sets for all the three data sets. GRNN predictions can be considered good, considering its performance for unseen data. Graphical plots, mean relative percentage residual, mean absolute relative residual, and root mean squared residual were identified as suitable indices for comparing competing models. ANN can now become a vehicle whereby predictive microbiology can be applied in food product development and food safety risk assessment.

  11. Simulation modeling for microbial risk assessment.

    Science.gov (United States)

    Cassin, M H; Paoli, G M; Lammerding, A M

    1998-11-01

    Quantitative microbial risk assessment implies an estimation of the probability and impact of adverse health outcomes due to microbial hazards. In the case of food safety, the probability of human illness is a complex function of the variability of many parameters that influence the microbial environment, from the production to the consumption of a food. The analytical integration required to estimate the probability of foodborne illness is intractable in all but the simplest of models. Monte Carlo simulation is an alternative to computing analytical solutions. In some cases, a risk assessment may be commissioned to serve a larger purpose than simply the estimation of risk. A Monte Carlo simulation can provide insights into complex processes that are invaluable, and otherwise unavailable, to those charged with the task of risk management. Using examples from a farm-to-fork model of the fate of Escherichia coli O157:H7 in ground beef hamburgers, this paper describes specifically how such goals as research prioritization, risk-based characterization of control points, and risk-based comparison of intervention strategies can be objectively achieved using Monte Carlo simulation.

  12. Microbial Growth Modeling and Simulation Based on Cellular Automata

    Directory of Open Access Journals (Sweden)

    Hong Men

    2013-07-01

    Full Text Available In order to simulate the micro-evolutionary process of the microbial growth, [Methods] in this study, we adopt two-dimensional cellular automata as its growth space. Based on evolutionary mechanism of microbial and cell-cell interactions, we adopt Moore neighborhood and make the transition rules. Finally, we construct the microbial growth model. [Results] It can describe the relationships among the cell growth, division and death. And also can effectively reflect spatial inhibition effect and substrate limitation effect. [Conclusions] The simulation results show that CA model is not only consistent with the classic microbial kinetic model, but also be able to simulate the microbial growth and evolution.

  13. An autocatalytic kinetic model for describing microbial growth during fermentation.

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    Ibarz, Albert; Augusto, Pedro E D

    2015-01-01

    The mathematical modelling of the behaviour of microbial growth is widely desired in order to control, predict and design food and bioproduct processing, stability and safety. This work develops and proposes a new semi-empirical mathematical model, based on an autocatalytic kinetic, to describe the microbial growth through its biomass concentration. The proposed model was successfully validated using 15 microbial growth patterns, covering the three most important types of microorganisms in food and biotechnological processing (bacteria, yeasts and moulds). Its main advantages and limitations are discussed, as well as the interpretation of its parameters. It is shown that the new model can be used to describe the behaviour of microbial growth.

  14. A bioenergetics-kinetics coupled modeling study on subsurface microbial metabolism in a field biostimulation experiment

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    Jin, Q.; Zheng, Z.; Zhu, C.

    2006-12-01

    Microorganisms in nature conserve energy by catalyzing various geochemical reactions. To build a quantitative relationship between geochemical conditions and metabolic rates, we propose a bioenergetics-kinetics coupled modeling approach. This approach describes microbial community as a metabolic network, i.e., fermenting microbes degrade organic substrates while aerobic respirer, nitrate reducer, metal reducer, sulfate reducer, and methanogen consume the fermentation products. It quantifies the control of substrate availability and biological energy conservation on the metabolic rates using thermodynamically consistent rate laws. We applied this simulation approach to study the progress of microbial metabolism during a field biostimulation experiment conducted in Oak Ridge, Tennessee. In the experiment, ethanol was injected into a monitoring well and groundwater was sampled to monitor changes in the chemistry. With time, concentrations of ethanol and SO42- decreased while those of NH4+, Fe2+, and Mn2+ increased. The simulation results fitted well to the observation, indicating simultaneous ethanol degradation and terminal electron accepting processes. The rates of aerobic respiration and denitrification were mainly controlled by substrate concentrations while those of ethanol degradation, sulfate reduction, and methanogenesis were controlled dominantly by the energy availability. The simulation results suggested two different microbial growth statuses in the subsurface. For the functional groups with significant growth, variations with time in substrate concentrations demonstrated a typical S curve. For the groups without significant growth, initial decreases in substrate concentrations were linear with time. Injecting substrates followed by monitoring environmental chemistry therefore provides a convenient approach to characterize microbial growth in the subsurface where methods for direct observation are currently unavailable. This research was funded by the

  15. Representing Microbial Dormancy in Soil Decomposition Models Improves Model Performance and Reveals Key Ecosystem Controls on Microbial Activity

    Science.gov (United States)

    He, Y.; Yang, J.; Zhuang, Q.; Wang, G.; Liu, Y.

    2014-12-01

    Climate feedbacks from soils can result from environmental change and subsequent responses of plant and microbial communities and nutrient cycling. Explicit consideration of microbial life history traits and strategy may be necessary to predict climate feedbacks due to microbial physiology and community changes and their associated effect on carbon cycling. In this study, we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of dormancy at six temperate forest sites with observed soil efflux ranged from 4 to 10 years across different forest types. We then extrapolated the model to all temperate forests in the Northern Hemisphere (25-50°N) to investigate spatial controls on microbial and soil C dynamics. Both models captured the observed soil heterotrophic respiration (RH), yet no-dormancy model consistently exhibited large seasonal amplitude and overestimation in microbial biomass. Spatially, the total RH from temperate forests based on dormancy model amounts to 6.88PgC/yr, and 7.99PgC/yr based on no-dormancy model. However, no-dormancy model notably overestimated the ratio of microbial biomass to SOC. Spatial correlation analysis revealed key controls of soil C:N ratio on the active proportion of microbial biomass, whereas local dormancy is primarily controlled by soil moisture and temperature, indicating scale-dependent environmental and biotic controls on microbial and SOC dynamics. These developments should provide essential support to modeling future soil carbon dynamics and enhance the avenue for collaboration between empirical soil experiment and modeling in the sense that more microbial physiological measurements are needed to better constrain and evaluate the models.

  16. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.

    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of

  17. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of new technologies

  18. Explicitly representing soil microbial processes in Earth system models

    Science.gov (United States)

    Wieder, William R.; Allison, Steven D.; Davidson, Eric A.; Georgiou, Katerina; Hararuk, Oleksandra; He, Yujie; Hopkins, Francesca; Luo, Yiqi; Smith, Matthew J.; Sulman, Benjamin; Todd-Brown, Katherine; Wang, Ying-Ping; Xia, Jianyang; Xu, Xiaofeng

    2015-10-01

    Microbes influence soil organic matter decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) will make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here we review the diversity, advantages, and pitfalls of simulating soil biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models, we suggest the following: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.

  19. Modeling adaptation of carbon use efficiency in microbial communities

    Directory of Open Access Journals (Sweden)

    Steven D Allison

    2014-10-01

    Full Text Available In new microbial-biogeochemical models, microbial carbon use efficiency (CUE is often assumed to decline with increasing temperature. Under this assumption, soil carbon losses under warming are small because microbial biomass declines. Yet there is also empirical evidence that CUE may adapt (i.e. become less sensitive to warming, thereby mitigating negative effects on microbial biomass. To analyze potential mechanisms of CUE adaptation, I used two theoretical models to implement a tradeoff between microbial uptake rate and CUE. This rate-yield tradeoff is based on thermodynamic principles and suggests that microbes with greater investment in resource acquisition should have lower CUE. Microbial communities or individuals could adapt to warming by reducing investment in enzymes and uptake machinery. Consistent with this idea, a simple analytical model predicted that adaptation can offset 50% of the warming-induced decline in CUE. To assess the ecosystem implications of the rate-yield tradeoff, I quantified CUE adaptation in a spatially-structured simulation model with 100 microbial taxa and 12 soil carbon substrates. This model predicted much lower CUE adaptation, likely due to additional physiological and ecological constraints on microbes. In particular, specific resource acquisition traits are needed to maintain stoichiometric balance, and taxa with high CUE and low enzyme investment rely on low-yield, high-enzyme neighbors to catalyze substrate degradation. In contrast to published microbial models, simulations with greater CUE adaptation also showed greater carbon storage under warming. This pattern occurred because microbial communities with stronger CUE adaptation produced fewer degradative enzymes, despite increases in biomass. Thus the rate-yield tradeoff prevents CUE adaptation from driving ecosystem carbon loss under climate warming.

  20. Modeling of Sustainable Base Production by Microbial Electrolysis Cell.

    Science.gov (United States)

    Blatter, Maxime; Sugnaux, Marc; Comninellis, Christos; Nealson, Kenneth; Fischer, Fabian

    2016-07-07

    A predictive model for the microbial/electrochemical base formation from wastewater was established and compared to experimental conditions within a microbial electrolysis cell. A Na2 SO4 /K2 SO4 anolyte showed that model prediction matched experimental results. Using Shewanella oneidensis MR-1, a strong base (pH≈13) was generated using applied voltages between 0.3 and 1.1 V. Due to the use of bicarbonate, the pH value in the anolyte remained unchanged, which is required to maintain microbial activity. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Design, Modeling, and Development of Microbial Cell Factories

    KAUST Repository

    Kodzius, Rimantas

    2014-03-26

    Using Metagenomic analysis, computational modeling, single cell and genome editing technologies, we will express desired microbial genes and their networks in suitable hosts for mass production of energy, food, and fine chemicals.

  2. Microbial Life in Soil - Linking Biophysical Models with Observations

    Science.gov (United States)

    Or, Dani; Tecon, Robin; Ebrahimi, Ali; Kleyer, Hannah; Ilie, Olga; Wang, Gang

    2015-04-01

    Microbial life in soil occurs within fragmented aquatic habitats formed in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools

  3. Measures of Microbial Biomass for Soil Carbon Decomposition Models

    Science.gov (United States)

    Mayes, M. A.; Dabbs, J.; Steinweg, J. M.; Schadt, C. W.; Kluber, L. A.; Wang, G.; Jagadamma, S.

    2014-12-01

    Explicit parameterization of the decomposition of plant inputs and soil organic matter by microbes is becoming more widely accepted in models of various complexity, ranging from detailed process models to global-scale earth system models. While there are multiple ways to measure microbial biomass, chloroform fumigation-extraction (CFE) is commonly used to parameterize models.. However CFE is labor- and time-intensive, requires toxic chemicals, and it provides no specific information about the composition or function of the microbial community. We investigated correlations between measures of: CFE; DNA extraction yield; QPCR base-gene copy numbers for Bacteria, Fungi and Archaea; phospholipid fatty acid analysis; and direct cell counts to determine the potential for use as proxies for microbial biomass. As our ultimate goal is to develop a reliable, more informative, and faster methods to predict microbial biomass for use in models, we also examined basic soil physiochemical characteristics including texture, organic matter content, pH, etc. to identify multi-factor predictive correlations with one or more measures of the microbial community. Our work will have application to both microbial ecology studies and the next generation of process and earth system models.

  4. Accounting for microbial habitats in modeling soil organic matter dynamics

    Science.gov (United States)

    Chenu, Claire; Garnier, Patricia; Nunan, Naoise; Pot, Valérie; Raynaud, Xavier; Vieublé, Laure; Otten, Wilfred; Falconer, Ruth; Monga, Olivier

    2017-04-01

    The extreme heterogeneity of soils constituents, architecture and inhabitants at the microscopic scale is increasingly recognized. Microbial communities exist and are active in a complex 3-D physical framework of mineral and organic particles defining pores of various sizes, more or less inter-connected. This results in a frequent spatial disconnection between soil carbon, energy sources and the decomposer organisms and a variety of microhabitats that are more or less suitable for microbial growth and activity. However, current biogeochemical models account for C dynamics at the macroscale (cm, m) and consider time- and spatially averaged relationships between microbial activity and soil characteristics. Different modelling approaches have intended to account for this microscale heterogeneity, based either on considering aggregates as surrogates for microbial habitats, or pores. Innovative modelling approaches are based on an explicit representation of soil structure at the fine scale, i.e. at µm to mm scales: pore architecture and their saturation with water, localization of organic resources and of microorganisms. Three recent models are presented here, that describe the heterotrophic activity of either bacteria or fungi and are based upon different strategies to represent the complex soil pore system (Mosaic, LBios and µFun). These models allow to hierarchize factors of microbial activity in soil's heterogeneous architecture. Present limits of these approaches and challenges are presented, regarding the extensive information required on soils at the microscale and to up-scale microbial functioning from the pore to the core scale.

  5. Models of microbiome evolution incorporating host and microbial selection.

    Science.gov (United States)

    Zeng, Qinglong; Wu, Steven; Sukumaran, Jeet; Rodrigo, Allen

    2017-09-25

    Numerous empirical studies suggest that hosts and microbes exert reciprocal selective effects on their ecological partners. Nonetheless, we still lack an explicit framework to model the dynamics of both hosts and microbes under selection. In a previous study, we developed an agent-based forward-time computational framework to simulate the neutral evolution of host-associated microbial communities in a constant-sized, unstructured population of hosts. These neutral models allowed offspring to sample microbes randomly from parents and/or from the environment. Additionally, the environmental pool of available microbes was constituted by fixed and persistent microbial OTUs and by contributions from host individuals in the preceding generation. In this paper, we extend our neutral models to allow selection to operate on both hosts and microbes. We do this by constructing a phenome for each microbial OTU consisting of a sample of traits that influence host and microbial fitnesses independently. Microbial traits can influence the fitness of hosts ("host selection") and the fitness of microbes ("trait-mediated microbial selection"). Additionally, the fitness effects of traits on microbes can be modified by their hosts ("host-mediated microbial selection"). We simulate the effects of these three types of selection, individually or in combination, on microbiome diversities and the fitnesses of hosts and microbes over several thousand generations of hosts. We show that microbiome diversity is strongly influenced by selection acting on microbes. Selection acting on hosts only influences microbiome diversity when there is near-complete direct or indirect parental contribution to the microbiomes of offspring. Unsurprisingly, microbial fitness increases under microbial selection. Interestingly, when host selection operates, host fitness only increases under two conditions: (1) when there is a strong parental contribution to microbial communities or (2) in the absence of a strong

  6. Enhancing Extracellular Electron Transfer of Shewanella oneidensis MR-1 through Coupling Improved Flavin Synthesis and Metal-Reducing Conduit for Pollutant Degradation.

    Science.gov (United States)

    Min, Di; Cheng, Lei; Zhang, Feng; Huang, Xue-Na; Li, Dao-Bo; Liu, Dong-Feng; Lau, Tai-Chu; Mu, Yang; Yu, Han-Qing

    2017-05-02

    Dissimilatory metal reducing bacteria (DMRB) are capable of extracellular electron transfer (EET) to insoluble metal oxides, which are used as external electron acceptors by DMRB for their anaerobic respiration. The EET process has important contribution to environmental remediation mineral cycling, and bioelectrochemical systems. However, the low EET efficiency remains to be one of the major bottlenecks for its practical applications for pollutant degradation. In this work, Shewanella oneidensis MR-1, a model DMRB, was used to examine the feasibility of enhancing the EET and its biodegradation capacity through genetic engineering. A flavin biosynthesis gene cluster ribD-ribC-ribBA-ribE and metal-reducing conduit biosynthesis gene cluster mtrC-mtrA-mtrB were coexpressed in S. oneidensis MR-1. Compared to the control strain, the engineered strain was found to exhibit an improved EET capacity in microbial fuel cells and potentiostat-controlled electrochemical cells, with an increase in maximum current density by approximate 110% and 87%, respectively. The electrochemical impedance spectroscopy (EIS) analysis showed that the current increase correlated with the lower interfacial charge-transfer resistance of the engineered strain. Meanwhile, a three times more rapid removal rate of methyl orange by the engineered strain confirmed the improvement of its EET and biodegradation ability. Our results demonstrate that coupling of improved synthesis of mediators and metal-reducing conduits could be an efficient strategy to enhance EET in S. oneidensis MR-1, which is essential to the applications of DMRB for environmental remediation, wastewater treatment, and bioenergy recovery from wastes.

  7. Dental Biofilm and Laboratory Microbial Culture Models for Cariology Research

    Directory of Open Access Journals (Sweden)

    Ollie Yiru Yu

    2017-06-01

    Full Text Available Dental caries form through a complex interaction over time among dental plaque, fermentable carbohydrate, and host factors (including teeth and saliva. As a key factor, dental plaque or biofilm substantially influence the characteristic of the carious lesions. Laboratory microbial culture models are often used because they provide a controllable and constant environment for cariology research. Moreover, they do not have ethical problems associated with clinical studies. The design of the microbial culture model varies from simple to sophisticated according to the purpose of the investigation. Each model is a compromise between the reality of the oral cavity and the simplification of the model. Researchers, however, can still obtain meaningful and useful results from the models they select. Laboratory microbial culture models can be categorized into a closed system and an open system. Models in the closed system have a finite supply of nutrients, and are also simple and cost-effective. Models in the open system enabled the supply of a fresh culture medium and the removal of metabolites and spent culture liquid simultaneously. They provide better regulation of the biofilm growth rate than the models in the closed system. This review paper gives an overview of the dental plaque biofilm and laboratory microbial culture models used for cariology research.

  8. Representing Microbial Processes in Environmental Reactive Transport Models

    Science.gov (United States)

    van Cappellen, P.

    2009-04-01

    Microorganisms play a key role in the biogeochemical functioning of the earth's surface and shallow subsurface. In the context of reactive transport modeling, a major challenge is to derive, parameterize, calibrate and verify mathematical expressions for microbially-mediated reactions in the environmental. This is best achieved by combining field observations, laboratory experiments, theoretical principles and modeling. Here, I will illustrate such an integrated approach for the case of microbial respiration processes in aquatic sediments. Important issues that will be covered include experimental design, model consistency and performance, as well as the bioenergetics and transient behavior of geomicrobial reaction systems.

  9. Simulated Carbon Cycling in a Model Microbial Mat.

    Science.gov (United States)

    Decker, K. L.; Potter, C. S.

    2006-12-01

    We present here the novel addition of detailed organic carbon cycling to our model of a hypersaline microbial mat ecosystem. This ecosystem model, MBGC (Microbial BioGeoChemistry), simulates carbon fixation through oxygenic and anoxygenic photosynthesis, and the release of C and electrons for microbial heterotrophs via cyanobacterial exudates and also via a pool of dead cells. Previously in MBGC, the organic portion of the carbon cycle was simplified into a black-box rate of accumulation of simple and complex organic compounds based on photosynthesis and mortality rates. We will discuss the novel inclusion of fermentation as a source of carbon and electrons for use in methanogenesis and sulfate reduction, and the influence of photorespiration on labile carbon exudation rates in cyanobacteria. We will also discuss the modeling of decomposition of dead cells and the ultimate release of inorganic carbon. The detailed modeling of organic carbon cycling is important to the accurate representation of inorganic carbon flux through the mat, as well as to accurate representation of growth models of the heterotrophs under different environmental conditions. Because the model ecosystem is an analog of ancient microbial mats that had huge impacts on the atmosphere of early earth, this MBGC can be useful as a biological component to either early earth models or models of other planets that potentially harbor life.

  10. Modeling microbial processes in porous media

    Science.gov (United States)

    Murphy, Ellyn M.; Ginn, Timothy R.

    The incorporation of microbial processes into reactive transport models has generally proceeded along two separate lines of investigation: (1) transport of bacteria as inert colloids in porous media, and (2) the biodegradation of dissolved contaminants by a stationary phase of bacteria. Research over the last decade has indicated that these processes are closely linked. This linkage may occur when a change in metabolic activity alters the attachment/detachment rates of bacteria to surfaces, either promoting or retarding bacterial transport in a groundwater-contaminant plume. Changes in metabolic activity, in turn, are controlled by the time of exposure of the microbes to electron acceptors/donor and other components affecting activity. Similarly, metabolic activity can affect the reversibility of attachment, depending on the residence time of active microbes. Thus, improvements in quantitative analysis of active subsurface biota necessitate direct linkages between substrate availability, metabolic activity, growth, and attachment/detachment rates. This linkage requires both a detailed understanding of the biological processes and robust quantitative representations of these processes that can be tested experimentally. This paper presents an overview of current approaches used to represent physicochemical and biological processes in porous media, along with new conceptual approaches that link metabolic activity with partitioning of the microorganism between the aqueous and solid phases. Résumé L'introduction des processus microbiologiques dans des modèles de transport réactif a généralement suivi deux voies différentes de recherches: (1) le transport de bactéries sous forme de colloïdes inertes en milieu poreux, et (2) la biodégradation de polluants dissous par une phase stationnaire de bactéries. Les recherches conduites au cours des dix dernières années indiquent que ces processus sont intimement liés. Cette liaison peut intervenir lorsqu

  11. Modeling Logistic Performance in Quantitative Microbial Risk Assessment

    NARCIS (Netherlands)

    Rijgersberg, H.; Tromp, S.O.; Jacxsens, L.; Uyttendaele, M.

    2010-01-01

    In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage ti

  12. A Multiple Reaction Modelling Framework for Microbial Electrochemical Technologies

    Science.gov (United States)

    Oyetunde, Tolutola; Sarma, Priyangshu M.; Ahmad, Farrukh; Rodríguez, Jorge

    2017-01-01

    A mathematical model for the theoretical evaluation of microbial electrochemical technologies (METs) is presented that incorporates a detailed physico-chemical framework, includes multiple reactions (both at the electrodes and in the bulk phase) and involves a variety of microbial functional groups. The model is applied to two theoretical case studies: (i) A microbial electrolysis cell (MEC) for continuous anodic volatile fatty acids (VFA) oxidation and cathodic VFA reduction to alcohols, for which the theoretical system response to changes in applied voltage and VFA feed ratio (anode-to-cathode) as well as membrane type are investigated. This case involves multiple parallel electrode reactions in both anode and cathode compartments; (ii) A microbial fuel cell (MFC) for cathodic perchlorate reduction, in which the theoretical impact of feed flow rates and concentrations on the overall system performance are investigated. This case involves multiple electrode reactions in series in the cathode compartment. The model structure captures interactions between important system variables based on first principles and provides a platform for the dynamic description of METs involving electrode reactions both in parallel and in series and in both MFC and MEC configurations. Such a theoretical modelling approach, largely based on first principles, appears promising in the development and testing of MET control and optimization strategies. PMID:28054959

  13. Stochiometry, Microbial community composition and decomposition, a modelling analysis

    Science.gov (United States)

    Berninger, Frank; Zhou, Xuan; Aaltonen, Heidi; Köster, Kajar; Heinonsalo, Jussi; Pumpanen, Jukka

    2017-04-01

    Enzyme activity based litter decomposition models describe the decomposition of soil organic matter as a function of microbial biomass and its activity. In these models, decomposition depends largely on microbial and litter stoïchiometry. We, used the model of Schimel and Weintraub (Soil Biology & Biochemistry 35 (2003) 549-563 largely relying on the modification of Waring B et al. Ecology Letters, (2013) 16: 887-894) and we modified the model to include bacteria, fungi and mycorrizal fungi as decomposer groups assuming different stochiometries. The model was tested against previously published data from a fire chronosequence from northern Finland. The model reconstructed well the development of soil organic matter, microbial biomasses, enzyme actitivies with time after fire. In a theoretical model analysis we tried to understand how the exchange of carbon and nitrogen between mycorrhiza and the plant as different litter stoïchiometries interact. The results indicate that if a high percentage of fungal N uptake is transferred to the plant mycorrhizal biomass will decrease drastically and does decrease, due to low mycorrhizal biomasses, the N uptake of plants. If a lower proportion of the fungal N uptake is transferred to the plant the N uptake of the plants is reasonable stable while the proportion of mycorrhiza of the total fungal biomass varies. The model is also able to simulate priming of soil organic matter decomposition.

  14. Kinetic Modelling of Pesticidal Degradation and Microbial Growth in Soil

    Institute of Scientific and Technical Information of China (English)

    LIUDUO-SEN; WANGZONG-SHENG; 等

    1994-01-01

    This paper discusses such models for the degradation kinetics of pesticides in soil as the model expressing the degradation rate as a function of two varables:the pesticide concentration and the number of pesticide degrading microorganisms,the model expressing the pesticide concentration as explicit or implicit function of time ,and the model exprssing the pesticide loss rate constants as functions of temperature,These models may interpret the degradation curves with an inflection point.A Kinetic model describing the growth processes of microbial populations in a closed system is reported as well.

  15. Biologically-motivated system identification: application to microbial growth modeling.

    Science.gov (United States)

    Yan, Jinyao; Deller, J R

    2014-01-01

    This paper presents a new method for identification of system models that are linear in parametric structure, but arbitrarily nonlinear in signal operations. The strategy blends traditional system identification methods with three modeling strategies that are not commonly employed in signal processing: linear-time-invariant-in-parameters models, set-based parameter identification, and evolutionary selection of the model structure. This paper reports recent advances in the theoretical foundation of the methods, then focuses on the operation and performance of the approach, particularly the evolutionary model determination. The method is applied to the modeling of microbial growth by Monod Kinetics.

  16. Probabilistic models to describe the dynamics of migrating microbial communities.

    Directory of Open Access Journals (Sweden)

    Joanna L Schroeder

    Full Text Available In all but the most sterile environments bacteria will reside in fluid being transported through conduits and some of these will attach and grow as biofilms on the conduit walls. The concentration and diversity of bacteria in the fluid at the point of delivery will be a mix of those when it entered the conduit and those that have become entrained into the flow due to seeding from biofilms. Examples include fluids through conduits such as drinking water pipe networks, endotracheal tubes, catheters and ventilation systems. Here we present two probabilistic models to describe changes in the composition of bulk fluid microbial communities as they are transported through a conduit whilst exposed to biofilm communities. The first (discrete model simulates absolute numbers of individual cells, whereas the other (continuous model simulates the relative abundance of taxa in the bulk fluid. The discrete model is founded on a birth-death process whereby the community changes one individual at a time and the numbers of cells in the system can vary. The continuous model is a stochastic differential equation derived from the discrete model and can also accommodate changes in the carrying capacity of the bulk fluid. These models provide a novel Lagrangian framework to investigate and predict the dynamics of migrating microbial communities. In this paper we compare the two models, discuss their merits, possible applications and present simulation results in the context of drinking water distribution systems. Our results provide novel insight into the effects of stochastic dynamics on the composition of non-stationary microbial communities that are exposed to biofilms and provides a new avenue for modelling microbial dynamics in systems where fluids are being transported.

  17. Minimal models of growth and decline of microbial populations.

    Science.gov (United States)

    Juška, Alfonsas

    2011-01-21

    Dynamics of growth and decline of microbial populations were analysed and respective models were developed in this investigation. Analysis of the dynamics was based on general considerations concerning the main properties of microorganisms and their interactions with the environment which was supposed to be affected by the activity of the population. Those considerations were expressed mathematically by differential equations or systems of the equations containing minimal sets of parameters characterizing those properties. It has been found that: (1) the factors leading to the decline of the population have to be considered separately, namely, accumulation of metabolites (toxins) in the medium and the exhaustion of resources; the latter have to be separated again into renewable ('building materials') and non-renewable (sources of energy); (2) decline of the population is caused by the exhaustion of sources of energy but no decline is predicted by the model because of the exhaustion of renewable resources; (3) the model determined by the accumulation of metabolites (toxins) in the medium does not suggest the existence of a separate 'stationary phase'; (4) in the model determined by the exhaustion of energy resources the 'stationary' and 'decline' phases are quite discernible; and (5) there is no symmetry in microbial population dynamics, the decline being slower than the rise. Mathematical models are expected to be useful in getting insight into the process of control of the dynamics of microbial populations. The models are in agreement with the experimental data.

  18. Multi-population model of a microbial electrolysis cell.

    Science.gov (United States)

    Pinto, R P; Srinivasan, B; Escapa, A; Tartakovsky, B

    2011-06-01

    This work presents a multi-population dynamic model of a microbial electrolysis cell (MEC). The model describes the growth and metabolic activity of fermentative, electricigenic, methanogenic acetoclastic, and methanogenic hydrogenophilic microorganisms and is capable of simulating hydrogen production in a MEC fed with complex organic matter, such as wastewater. The model parameters were estimated with the experimental results obtained in continuous flow MECs fed with acetate or synthetic wastewater. Following successful model validation with an independent data set, the model was used to analyze and discuss the influence of applied voltage and organic load on hydrogen production and COD removal.

  19. Diverse metal reduction and nano- mineral formation by metal-reducing bacteria enriched from inter-tidal flat sediments

    Science.gov (United States)

    Kim, Y.; Park, B.; Seo, H.; Roh, Y.

    2009-12-01

    Dissimilatory metal-reducing bacteria utilize diverse metal oxides as electron acceptors and couple this microbial metal reduciton to growth. However, the microbe-metal interactions playing important roles in the metal geochemistry and organic matter degradation in the tidal flat sediments have not been uncovered enough to employ in various environmental and industrial applications. The objective of this study was to examine biomineralization and bioremediation by the facultative metal-reducing bacteria isolated from the inter-tidal flat sediments in southwestern of Korea. 16S-rRNA analysis showed bacterial consortium mainly consists of genus of Clostridium sp. The enriched bacteria were capable of reducing diverse metals such as iron oxide, maganese oxide, Cr(VI) and Se(VI) during glucose fermentation process at room temperature. The bacteria reduced highly toxic and reactive elements such as Cr(VI) and Se(VI) to Cr(III) and Se(0). The results showed that microbial processes induced transformation from toxic states of heavy metals to less toxic and mobile states in natural environments. Andthe bacteria also reduced iron oxyhydroxide such as ferrihydrite and akaganeite (β-FeOOH) and formed nanometer-sized magnetite (Fe3O4). This study indicates microbial processes not only can be used for bioremediation of inorganic contaminants existing in the marine environments, but also form the magnetite nanoparticles which are exhibit superparamagnetic properties that can be useful for relevant medical and industrial applications.

  20. Explicitly representing soil microbial processes in Earth system models: Soil microbes in earth system models

    Energy Technology Data Exchange (ETDEWEB)

    Wieder, William R. [Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder Colorado USA; Allison, Steven D. [Department of Ecology and Evolutionary Biology, University of California, Irvine California USA; Department of Earth System Science, University of California, Irvine California USA; Davidson, Eric A. [Appalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg Maryland USA; Georgiou, Katerina [Department of Chemical and Biomolecular Engineering, University of California, Berkeley California USA; Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley California USA; Hararuk, Oleksandra [Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre, Victoria British Columbia Canada; He, Yujie [Department of Earth System Science, University of California, Irvine California USA; Department of Earth, Atmospheric and Planetary Sciences, Purdue University, West Lafayette Indiana USA; Hopkins, Francesca [Department of Earth System Science, University of California, Irvine California USA; Jet Propulsion Laboratory, California Institute of Technology, Pasadena California USA; Luo, Yiqi [Department of Microbiology & Plant Biology, University of Oklahoma, Norman Oklahoma USA; Smith, Matthew J. [Computational Science Laboratory, Microsoft Research, Cambridge UK; Sulman, Benjamin [Department of Biology, Indiana University, Bloomington Indiana USA; Todd-Brown, Katherine [Department of Microbiology & Plant Biology, University of Oklahoma, Norman Oklahoma USA; Pacific Northwest National Laboratory, Richland Washington USA; Wang, Ying-Ping [CSIRO Ocean and Atmosphere Flagship, Aspendale Victoria Australia; Xia, Jianyang [Department of Microbiology & Plant Biology, University of Oklahoma, Norman Oklahoma USA; Tiantong National Forest Ecosystem Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai China; Xu, Xiaofeng [Department of Biological Sciences, University of Texas at El Paso, Texas USA

    2015-10-01

    Microbes influence soil organic matter (SOM) decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) may make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here, we review the diversity, advantages, and pitfalls of simulating soil biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models we suggest: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.

  1. Integrating microbial physiology and enzyme traits in the quality model

    Science.gov (United States)

    Sainte-Marie, Julien; Barrandon, Matthieu; Martin, Francis; Saint-André, Laurent; Derrien, Delphine

    2017-04-01

    Microbe activity plays an undisputable role in soil carbon storage and there have been many calls to integrate microbial ecology in soil carbon (C) models. With regard to this challenge, a few trait-based microbial models of C dynamics have emerged during the past decade. They parameterize specific traits related to decomposer physiology (substrate use efficiency, growth and mortality rates...) and enzyme properties (enzyme production rate, catalytic properties of enzymes…). But these models are built on the premise that organic matter (OM) can be represented as one single entity or are divided into a few pools, while organic matter exists as a continuum of many different compounds spanning from intact plant molecules to highly oxidised microbial metabolites. In addition, a given molecule may also exist in different forms, depending on its stage of polymerization or on its interactions with other organic compounds or mineral phases of the soil. Here we develop a general theoretical model relating the evolution of soil organic matter, as a continuum of progressively decomposing compounds, with decomposer activity and enzyme traits. The model is based on the notion of quality developed by Agren and Bosatta (1998), which is a measure of molecule accessibility to degradation. The model integrates three major processes: OM depolymerisation by enzyme action, OM assimilation and OM biotransformation. For any enzyme, the model reports the quality range where this enzyme selectively operates and how the initial quality distribution of the OM subset evolves into another distribution of qualities under the enzyme action. The model also defines the quality range where the OM can be uptaken and assimilated by microbes. It finally describes how the quality of the assimilated molecules is transformed into another quality distribution, corresponding to the decomposer metabolites signature. Upon decomposer death, these metabolites return to the substrate. We explore here the how

  2. A GPU Reaction Diffusion Soil-Microbial Model

    Science.gov (United States)

    Falconer, Ruth; Houston, Alasdair; Schmidt, Sonja; Otten, Wilfred

    2014-05-01

    Parallelised algorithms are frequent in bioinformatics as a consequence of the close link to informatics - however in the field of soil science and ecology they are less prevalent. A current challenge in soil ecology is to link habitat structure to microbial dynamics. Soil science is therefore entering the 'big data' paradigm as a consequence of integrating data pertinent to the physical soil environment obtained via imaging and theoretical models describing growth and development of microbial dynamics permitting accurate analyses of spatio-temporal properties of different soil microenvironments. The microenvironment is often captured by 3D imaging (CT tomography) which yields large datasets and when used in computational studies the physical sizes of the samples that are amenable to computation are less than 1 cm3. Today's commodity graphics cards are programmable and possess a data parallel architecture that in many cases is capable of out-performing the CPU in terms of computational rates. The programmable aspect is achieved via a low-level parallel programming language (CUDA, OpenCL and DirectX). We ported a Soil-Microbial Model onto the GPU using the DirectX Compute API. We noted a significant computational speed up as well as an increase in the physical size that can be simulated. Some of the drawbacks of such an approach were concerned with numerical precision and the steep learning curve associated with GPGPU technologies.

  3. Predicting the microbial exposure risks in urban floods using GIS, building simulation, and microbial models.

    Science.gov (United States)

    Taylor, Jonathon; Biddulph, Phillip; Davies, Michael; Lai, Ka man

    2013-01-01

    London is expected to experience more frequent periods of intense rainfall and tidal surges, leading to an increase in the risk of flooding. Damp and flooded dwellings can support microbial growth, including mould, bacteria, and protozoa, as well as persistence of flood-borne microorganisms. The amount of time flooded dwellings remain damp will depend on the duration and height of the flood, the contents of the flood water, the drying conditions, and the building construction, leading to particular properties and property types being prone to lingering damp and human pathogen growth or persistence. The impact of flooding on buildings can be simulated using Heat Air and Moisture (HAM) models of varying complexity in order to understand how water can be absorbed and dry out of the building structure. This paper describes the simulation of the drying of building archetypes representative of the English building stock using the EnergyPlus based tool 'UCL-HAMT' in order to determine the drying rates of different abandoned structures flooded to different heights and during different seasons. The results are mapped out using GIS in order to estimate the spatial risk across London in terms of comparative flood vulnerability, as well as for specific flood events. Areas of South and East London were found to be particularly vulnerable to long-term microbial exposure following major flood events.

  4. Microbially Mediated Kinetic Sulfur Isotope Fractionation: Reactive Transport Modeling Benchmark

    Science.gov (United States)

    Wanner, C.; Druhan, J. L.; Cheng, Y.; Amos, R. T.; Steefel, C. I.; Ajo Franklin, J. B.

    2014-12-01

    Microbially mediated sulfate reduction is a ubiquitous process in many subsurface systems. Isotopic fractionation is characteristic of this anaerobic process, since sulfate reducing bacteria (SRB) favor the reduction of the lighter sulfate isotopologue (S32O42-) over the heavier isotopologue (S34O42-). Detection of isotopic shifts have been utilized as a proxy for the onset of sulfate reduction in subsurface systems such as oil reservoirs and aquifers undergoing uranium bioremediation. Reactive transport modeling (RTM) of kinetic sulfur isotope fractionation has been applied to field and laboratory studies. These RTM approaches employ different mathematical formulations in the representation of kinetic sulfur isotope fractionation. In order to test the various formulations, we propose a benchmark problem set for the simulation of kinetic sulfur isotope fractionation during microbially mediated sulfate reduction. The benchmark problem set is comprised of four problem levels and is based on a recent laboratory column experimental study of sulfur isotope fractionation. Pertinent processes impacting sulfur isotopic composition such as microbial sulfate reduction and dispersion are included in the problem set. To date, participating RTM codes are: CRUNCHTOPE, TOUGHREACT, MIN3P and THE GEOCHEMIST'S WORKBENCH. Preliminary results from various codes show reasonable agreement for the problem levels simulating sulfur isotope fractionation in 1D.

  5. Biostimulation of Metal-Reducing Microbes at a Former Uranium Mill Tailings Site

    Science.gov (United States)

    Peacock, A. D.; Anderson, R. T.; Chang, J.; Long, P. E.; White, D. C.

    2002-12-01

    In situ biological treatment strategies are currently being used or considered to address groundwater contamination at hundreds and perhaps thousands of sites in the United States. A key to demonstrating the effectiveness of biological treatment strategies at a site is establishing cause and effect relationships, which provide evidence that the desired bioprocesses are occurring, or are likely to occur. These methods involve directly measuring various biochemical constituents of the bacteria themselves (i.e. "biomarkers"), which are indicative of their metabolic processes, and therefore provide direct, relevant information regarding the environment in which they are growing. These biomarkers include the presence and viability of biomass, the ability of the organisms to degrade or transform target contaminant(s), the presence of nutrients to promote bacterial growth and activity, and the oxidation/reduction (redox) status of the system. Using these tools we monitored an in situ biostimulation test at the field scale at the Old Rifle Uranium Mill Tailings Remedial Action (UMTRA) Project site, a former uranium ore processing facility located approximately 0.3 mile east of the city of Rifle in Garfield County, Colorado. The purpose of the study was to investigate if the addition of low concentrations of acetate (approx. 1 millimolar) as an electron donor into the subsurface would create anaerobic conditions that would stimulate growth of metal reducing bacteria capable of reducing soluble U(VI) to insoluble U(IV). Phospholipid fatty acid (PLFA), respiratory quinone, and DNA data showed that addition of acetate into the subsurface increased the microbial biomass and altered the microbial community structure to one that contained more anaerobic microorganisms (i.e. Geobacter sp.) capable of the reduction of U(VI).

  6. Simulating microbial denitrification with EPIC: Model description and initial testing

    Energy Technology Data Exchange (ETDEWEB)

    Izaurralde, Roberto C.; Mcgill, William B.; Williams, Jimmy R.; Jones, Curtis D.; Link, Robert P.; Manowitz, D.; Schwab, D. E.; Zhang, Xuesong; Robertson, G. P.; Milar, Neville

    2017-09-01

    Microbial denitrification occurs in anaerobic soil microsites and aquatic environments leading to production of N2O and N2 gases, which eventually escape to the atmosphere. Atmospheric concentrations of N2O have been on the rise since the beginning of the industrial revolution due to large-scale manipulations of the N cycle in managed ecosystems, especially the use of synthetic nitrogenous fertilizer. Here we document and test a microbial denitrification model identified as IMWJ and implemented as a submodel in the EPIC terrestrial ecosystem model. The IMWJ model is resolved on an hourly time step using the concept that C oxidation releases electrons that drive a demand for electron acceptors such as O2 and oxides of N (NO3-, NO2-, and N2O). A spherical diffusion approach is used to describe O2 transport to microbial surfaces while a cylindrical diffusion method is employed to depict O2 transport to root surfaces. Oxygen uptake by microbes and roots is described with Michaelis-Menten kinetic equations. If insufficient O2 is present to accept all electrons generated, the deficit for electron acceptors may be met by oxides of nitrogen, if available. The movement of O2, CO2 and N2O through the soil profile is modeled using the gas transport equation solved on hourly or sub-hourly time steps. Bubbling equations also move N2O and N2 through the liquid phase to the soil surface under highly anaerobic conditions. We used results from a 2-yr field experiment conducted in 2007 and 2008 at a field site in southwest Michigan to test the ability of EPIC, with the IMWJ option, to capture the non-linear response of N2O fluxes as a function of increasing rates of N application to maize [Zea mays L.]. Nitrous oxide flux, soil inorganic N, and ancillary data from 2007 were used for EPIC calibration while 2008 data were used for independent model validation. Overall, EPIC reproduced well the timing and magnitude of N2O fluxes and NO3- mass in surficial soil layers after N

  7. Probabilistic model of microbial cell growth, division, and mortality.

    Science.gov (United States)

    Horowitz, Joseph; Normand, Mark D; Corradini, Maria G; Peleg, Micha

    2010-01-01

    After a short time interval of length deltat during microbial growth, an individual cell can be found to be divided with probability Pd(t)deltat, dead with probability Pm(t)deltat, or alive but undivided with the probability 1-[Pd(t)+Pm(t)]deltat, where t is time, Pd(t) expresses the probability of division for an individual cell per unit of time, and Pm(t) expresses the probability of mortality per unit of time. These probabilities may change with the state of the population and the habitat's properties and are therefore functions of time. This scenario translates into a model that is presented in stochastic and deterministic versions. The first, a stochastic process model, monitors the fates of individual cells and determines cell numbers. It is particularly suitable for small populations such as those that may exist in the case of casual contamination of a food by a pathogen. The second, which can be regarded as a large-population limit of the stochastic model, is a continuous mathematical expression that describes the population's size as a function of time. It is suitable for large microbial populations such as those present in unprocessed foods. Exponential or logistic growth with or without lag, inactivation with or without a "shoulder," and transitions between growth and inactivation are all manifestations of the underlying probability structure of the model. With temperature-dependent parameters, the model can be used to simulate nonisothermal growth and inactivation patterns. The same concept applies to other factors that promote or inhibit microorganisms, such as pH and the presence of antimicrobials, etc. With Pd(t) and Pm(t) in the form of logistic functions, the model can simulate all commonly observed growth/mortality patterns. Estimates of the changing probability parameters can be obtained with both the stochastic and deterministic versions of the model, as demonstrated with simulated data.

  8. Species Coexistence in Nitrifying Chemostats: A Model of Microbial Interactions

    Directory of Open Access Journals (Sweden)

    Maxime Dumont

    2016-12-01

    Full Text Available In a previous study, the two nitrifying functions (ammonia oxidizing bacteria (AOB or nitrite-oxidizing bacteria (NOB of a nitrification reactor—operated continuously over 525 days with varying inputs—were assigned using a mathematical modeling approach together with the monitoring of bacterial phylotypes. Based on these theoretical identifications, we develop here a chemostat model that does not explicitly include only the resources’ dynamics (different forms of soluble nitrogen but also explicitly takes into account microbial inter- and intra-species interactions for the four dominant phylotypes detected in the chemostat. A comparison of the models obtained with and without interactions has shown that such interactions permit the coexistence of two competing ammonium-oxidizing bacteria and two competing nitrite-oxidizing bacteria in competition for ammonium and nitrite, respectively. These interactions are analyzed and discussed.

  9. Monitoring and modeling of microbial and biological water quality

    Science.gov (United States)

    Microbial and biological water quality informs on the health of water systems and their suitability for uses in irrigation, recreation, aquaculture, and other activities. Indicators of microbial and biological water quality demonstrate high spatial and temporal variability. Therefore, monitoring str...

  10. Dirichlet multinomial mixtures: generative models for microbial metagenomics.

    Science.gov (United States)

    Holmes, Ian; Harris, Keith; Quince, Christopher

    2012-01-01

    We introduce Dirichlet multinomial mixtures (DMM) for the probabilistic modelling of microbial metagenomics data. This data can be represented as a frequency matrix giving the number of times each taxa is observed in each sample. The samples have different size, and the matrix is sparse, as communities are diverse and skewed to rare taxa. Most methods used previously to classify or cluster samples have ignored these features. We describe each community by a vector of taxa probabilities. These vectors are generated from one of a finite number of Dirichlet mixture components each with different hyperparameters. Observed samples are generated through multinomial sampling. The mixture components cluster communities into distinct 'metacommunities', and, hence, determine envirotypes or enterotypes, groups of communities with a similar composition. The model can also deduce the impact of a treatment and be used for classification. We wrote software for the fitting of DMM models using the 'evidence framework' (http://code.google.com/p/microbedmm/). This includes the Laplace approximation of the model evidence. We applied the DMM model to human gut microbe genera frequencies from Obese and Lean twins. From the model evidence four clusters fit this data best. Two clusters were dominated by Bacteroides and were homogenous; two had a more variable community composition. We could not find a significant impact of body mass on community structure. However, Obese twins were more likely to derive from the high variance clusters. We propose that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype. This is an example of the 'Anna Karenina principle (AKP)' applied to microbial communities: disturbed states having many more configurations than undisturbed. We verify this by showing that in a study of inflammatory bowel disease (IBD) phenotypes, ileal Crohn's disease (ICD) is associated with a more variable

  11. Dirichlet multinomial mixtures: generative models for microbial metagenomics.

    Directory of Open Access Journals (Sweden)

    Ian Holmes

    Full Text Available We introduce Dirichlet multinomial mixtures (DMM for the probabilistic modelling of microbial metagenomics data. This data can be represented as a frequency matrix giving the number of times each taxa is observed in each sample. The samples have different size, and the matrix is sparse, as communities are diverse and skewed to rare taxa. Most methods used previously to classify or cluster samples have ignored these features. We describe each community by a vector of taxa probabilities. These vectors are generated from one of a finite number of Dirichlet mixture components each with different hyperparameters. Observed samples are generated through multinomial sampling. The mixture components cluster communities into distinct 'metacommunities', and, hence, determine envirotypes or enterotypes, groups of communities with a similar composition. The model can also deduce the impact of a treatment and be used for classification. We wrote software for the fitting of DMM models using the 'evidence framework' (http://code.google.com/p/microbedmm/. This includes the Laplace approximation of the model evidence. We applied the DMM model to human gut microbe genera frequencies from Obese and Lean twins. From the model evidence four clusters fit this data best. Two clusters were dominated by Bacteroides and were homogenous; two had a more variable community composition. We could not find a significant impact of body mass on community structure. However, Obese twins were more likely to derive from the high variance clusters. We propose that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype. This is an example of the 'Anna Karenina principle (AKP' applied to microbial communities: disturbed states having many more configurations than undisturbed. We verify this by showing that in a study of inflammatory bowel disease (IBD phenotypes, ileal Crohn's disease (ICD is associated with

  12. Methodology for modeling the microbial contamination of air filters.

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    Yun Haeng Joe

    Full Text Available In this paper, we propose a theoretical model to simulate microbial growth on contaminated air filters and entrainment of bioaerosols from the filters to an indoor environment. Air filter filtration and antimicrobial efficiencies, and effects of dust particles on these efficiencies, were evaluated. The number of bioaerosols downstream of the filter could be characterized according to three phases: initial, transitional, and stationary. In the initial phase, the number was determined by filtration efficiency, the concentration of dust particles entering the filter, and the flow rate. During the transitional phase, the number of bioaerosols gradually increased up to the stationary phase, at which point no further increase was observed. The antimicrobial efficiency and flow rate were the dominant parameters affecting the number of bioaerosols downstream of the filter in the transitional and stationary phase, respectively. It was found that the nutrient fraction of dust particles entering the filter caused a significant change in the number of bioaerosols in both the transitional and stationary phases. The proposed model would be a solution for predicting the air filter life cycle in terms of microbiological activity by simulating the microbial contamination of the filter.

  13. Metabolic modelling of polyhydroxyalkanoate copolymers production by mixed microbial cultures

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    Reis Maria AM

    2008-07-01

    Full Text Available Abstract Background This paper presents a metabolic model describing the production of polyhydroxyalkanoate (PHA copolymers in mixed microbial cultures, using mixtures of acetic and propionic acid as carbon source material. Material and energetic balances were established on the basis of previously elucidated metabolic pathways. Equations were derived for the theoretical yields for cell growth and PHA production on mixtures of acetic and propionic acid as functions of the oxidative phosphorylation efficiency, P/O ratio. The oxidative phosphorylation efficiency was estimated from rate measurements, which in turn allowed the estimation of the theoretical yield coefficients. Results The model was validated with experimental data collected in a sequencing batch reactor (SBR operated under varying feeding conditions: feeding of acetic and propionic acid separately (control experiments, and the feeding of acetic and propionic acid simultaneously. Two different feast and famine culture enrichment strategies were studied: (i either with acetate or (ii with propionate as carbon source material. Metabolic flux analysis (MFA was performed for the different feeding conditions and culture enrichment strategies. Flux balance analysis (FBA was used to calculate optimal feeding scenarios for high quality PHA polymers production, where it was found that a suitable polymer would be obtained when acetate is fed in excess and the feeding rate of propionate is limited to ~0.17 C-mol/(C-mol.h. The results were compared with published pure culture metabolic studies. Conclusion Acetate was more conducive toward the enrichment of a microbial culture with higher PHA storage fluxes and yields as compared to propionate. The P/O ratio was not only influenced by the selected microbial culture, but also by the carbon substrate fed to each culture, where higher P/O ratio values were consistently observed for acetate than propionate. MFA studies suggest that when mixtures of

  14. The vineyard yeast microbiome, a mixed model microbial map.

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    Mathabatha Evodia Setati

    Full Text Available Vineyards harbour a wide variety of microorganisms that play a pivotal role in pre- and post-harvest grape quality and will contribute significantly to the final aromatic properties of wine. The aim of the current study was to investigate the spatial distribution of microbial communities within and between individual vineyard management units. For the first time in such a study, we applied the Theory of Sampling (TOS to sample gapes from adjacent and well established commercial vineyards within the same terroir unit and from several sampling points within each individual vineyard. Cultivation-based and molecular data sets were generated to capture the spatial heterogeneity in microbial populations within and between vineyards and analysed with novel mixed-model networks, which combine sample correlations and microbial community distribution probabilities. The data demonstrate that farming systems have a significant impact on fungal diversity but more importantly that there is significant species heterogeneity between samples in the same vineyard. Cultivation-based methods confirmed that while the same oxidative yeast species dominated in all vineyards, the least treated vineyard displayed significantly higher species richness, including many yeasts with biocontrol potential. The cultivatable yeast population was not fully representative of the more complex populations seen with molecular methods, and only the molecular data allowed discrimination amongst farming practices with multivariate and network analysis methods. Importantly, yeast species distribution is subject to significant intra-vineyard spatial fluctuations and the frequently reported heterogeneity of tank samples of grapes harvested from single vineyards at the same stage of ripeness might therefore, at least in part, be due to the differing microbiota in different sections of the vineyard.

  15. The vineyard yeast microbiome, a mixed model microbial map.

    Science.gov (United States)

    Setati, Mathabatha Evodia; Jacobson, Daniel; Andong, Ursula-Claire; Bauer, Florian Franz; Bauer, Florian

    2012-01-01

    Vineyards harbour a wide variety of microorganisms that play a pivotal role in pre- and post-harvest grape quality and will contribute significantly to the final aromatic properties of wine. The aim of the current study was to investigate the spatial distribution of microbial communities within and between individual vineyard management units. For the first time in such a study, we applied the Theory of Sampling (TOS) to sample gapes from adjacent and well established commercial vineyards within the same terroir unit and from several sampling points within each individual vineyard. Cultivation-based and molecular data sets were generated to capture the spatial heterogeneity in microbial populations within and between vineyards and analysed with novel mixed-model networks, which combine sample correlations and microbial community distribution probabilities. The data demonstrate that farming systems have a significant impact on fungal diversity but more importantly that there is significant species heterogeneity between samples in the same vineyard. Cultivation-based methods confirmed that while the same oxidative yeast species dominated in all vineyards, the least treated vineyard displayed significantly higher species richness, including many yeasts with biocontrol potential. The cultivatable yeast population was not fully representative of the more complex populations seen with molecular methods, and only the molecular data allowed discrimination amongst farming practices with multivariate and network analysis methods. Importantly, yeast species distribution is subject to significant intra-vineyard spatial fluctuations and the frequently reported heterogeneity of tank samples of grapes harvested from single vineyards at the same stage of ripeness might therefore, at least in part, be due to the differing microbiota in different sections of the vineyard.

  16. Modeling logistic performance in quantitative microbial risk assessment.

    Science.gov (United States)

    Rijgersberg, Hajo; Tromp, Seth; Jacxsens, Liesbeth; Uyttendaele, Mieke

    2010-01-01

    In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage times, temperatures, gas conditions, and their distributions) are determined. However, the logistic chain with its queues (storages, shelves) and mechanisms for ordering products is usually not taken into account. As a consequence, storage times-mutually dependent in successive steps in the chain-cannot be described adequately. This may have a great impact on the tails of risk distributions. Because food safety risks are generally very small, it is crucial to model the tails of (underlying) distributions as accurately as possible. Logistic performance can be modeled by describing the underlying planning and scheduling mechanisms in discrete-event modeling. This is common practice in operations research, specifically in supply chain management. In this article, we present the application of discrete-event modeling in the context of a QMRA for Listeria monocytogenes in fresh-cut iceberg lettuce. We show the potential value of discrete-event modeling in QMRA by calculating logistic interventions (modifications in the logistic chain) and determining their significance with respect to food safety.

  17. Microcosm Experiments and Modeling of Microbial Movement Under Unsaturated Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Brockman, F.J.; Kapadia, N.; Williams, G.; Rockhold, M.

    2006-04-05

    Colonization of bacteria in porous media has been studied primarily in saturated systems. In this study we examine how microbial colonization in unsaturated porous media is controlled by water content and particle size. This is important for understanding the feasibility and success of bioremediation via nutrient delivery when contaminant degraders are at low densities and when total microbial populations are sparse and spatially discontinuous. The study design used 4 different sand sizes, each at 4 different water contents; experiments were run with and without acetate as the sole carbon source. All experiments were run in duplicate columns and used the motile organism Pseudomonas stutzeri strain KC, a carbon tetrachloride degrader. At a given sand size, bacteria traveled further with increasing volumetric water content. At a given volumetric water content, bacteria generally traveled further with increasing sand size. Water redistribution, solute transport, gas diffusion, and bacterial colonization dynamics were simulated using a numerical finite-difference model. Solute and bacterial transport were modeled using advection-dispersion equations, with reaction rate source/sink terms to account for bacterial growth and substrate utilization, represented using dual Monod-type kinetics. Oxygen transport and diffusion was modeled accounting for equilibrium partitioning between the aqueous and gas phases. The movement of bacteria in the aqueous phase was modeled using a linear impedance model in which the term D{sub m} is a coefficient, as used by Barton and Ford (1995), representing random motility. The unsaturated random motility coefficients we obtained (1.4 x 10{sup -6} to 2.8 x 10{sup -5} cm{sup 2}/sec) are in the same range as those found by others for saturated systems (3.5 x 10{sup -6} to 3.5 x 10{sup -5} cm{sup 2}/sec). The results show that some bacteria can rapidly migrate in well sorted unsaturated sands (and perhaps in relatively high porosity, poorly

  18. Microbial turnover times in the deep seabed studied by amino acid racemization modelling.

    Science.gov (United States)

    Braun, Stefan; Mhatre, Snehit S; Jaussi, Marion; Røy, Hans; Kjeldsen, Kasper U; Pearce, Christof; Seidenkrantz, Marit-Solveig; Jørgensen, Bo Barker; Lomstein, Bente Aa

    2017-07-18

    The study of active microbial populations in deep, energy-limited marine sediments has extended our knowledge of the limits of life on Earth. Typically, microbial activity in the deep biosphere is calculated by transport-reaction modelling of pore water solutes or from experimental measurements involving radiotracers. Here we modelled microbial activity from the degree of D:L-aspartic acid racemization in microbial necromass (remains of dead microbial biomass) in sediments up to ten million years old. This recently developed approach (D:L-amino acid modelling) does not require incubation experiments and is highly sensitive in stable, low-activity environments. We applied for the first time newly established constraints on several important input parameters of the D:L-amino acid model, such as a higher aspartic acid racemization rate constant and a lower cell-specific carbon content of sub-seafloor microorganisms. Our model results show that the pool of necromass amino acids is turned over by microbial activity every few thousand years, while the turnover times of vegetative cells are in the order of years to decades. Notably, microbial turnover times in million-year-old sediment from the Peru Margin are up to 100-fold shorter than previous estimates, highlighting the influence of microbial activities on element cycling over geologic time scales.

  19. Development of a program to fit data to a new logistic model for microbial growth.

    Science.gov (United States)

    Fujikawa, Hiroshi; Kano, Yoshihiro

    2009-06-01

    Recently we developed a mathematical model for microbial growth in food. The model successfully predicted microbial growth at various patterns of temperature. In this study, we developed a program to fit data to the model with a spread sheet program, Microsoft Excel. Users can instantly get curves fitted to the model by inputting growth data and choosing the slope portion of a curve. The program also could estimate growth parameters including the rate constant of growth and the lag period. This program would be a useful tool for analyzing growth data and further predicting microbial growth.

  20. Modeling Central Carbon Metabolic Processes in Soil Microbial Communities: Comparing Measured With Modeled

    Science.gov (United States)

    Dijkstra, P.; Fairbanks, D.; Miller, E.; Salpas, E.; Hagerty, S.

    2013-12-01

    Understanding the mechanisms regulating C cycling is hindered by our inability to directly observe and measure the biochemical processes of glycolysis, pentose phosphate pathway, and TCA cycle in intact and complex microbial communities. Position-specific 13C labeled metabolic tracer probing is proposed as a new way to study microbial community energy production, biosynthesis, C use efficiency (the proportion of substrate incorporated into microbial biomass), and enables the quantification of C fluxes through the central C metabolic network processes (Dijkstra et al 2011a,b). We determined the 13CO2 production from U-13C, 1-13C, 2-13C, 3-13C, 4-13C, 5-13C, and 6-13C labeled glucose and 1-13C and 2,3-13C pyruvate in parallel incubations in three soils along an elevation gradient. Qualitative and quantitative interpretation of the results indicate a high pentose phosphate pathway activity in soils. Agreement between modeled and measured CO2 production rates for the six C-atoms of 13C-labeled glucose indicate that the metabolic model used is appropriate for soil community processes, but that improvements can be made. These labeling and modeling techniques may improve our ability to analyze the biochemistry and (eco)physiology of intact microbial communities. Dijkstra, P., Blankinship, J.C., Selmants, P.C., Hart, S.C., Koch, G.W., Schwartz, E., Hungate, B.A., 2011a. Probing C flux patterns of soil microbial metabolic networks using parallel position-specific tracer labeling. Soil Biology & Biochemistry 43, 126-132. Dijkstra, P., Dalder, J.J., Selmants, P.C., Hart, S.C., Koch, G.W., Schwartz, E., Hungate, B.A., 2011b. Modeling soil metabolic processes using isotopologue pairs of position-specific 13C-labeled glucose and pyruvate. Soil Biology & Biochemistry 43, 1848-1857.

  1. Biotic Interactions in Microbial Communities as Modulators of Biogeochemical Processes: Methanotrophy as a Model System.

    Science.gov (United States)

    Ho, Adrian; Angel, Roey; Veraart, Annelies J; Daebeler, Anne; Jia, Zhongjun; Kim, Sang Yoon; Kerckhof, Frederiek-Maarten; Boon, Nico; Bodelier, Paul L E

    2016-01-01

    Microbial interaction is an integral component of microbial ecology studies, yet the role, extent, and relevance of microbial interaction in community functioning remains unclear, particularly in the context of global biogeochemical cycles. While many studies have shed light on the physico-chemical cues affecting specific processes, (micro)biotic controls and interactions potentially steering microbial communities leading to altered functioning are less known. Yet, recent accumulating evidence suggests that the concerted actions of a community can be significantly different from the combined effects of individual microorganisms, giving rise to emergent properties. Here, we exemplify the importance of microbial interaction for ecosystem processes by analysis of a reasonably well-understood microbial guild, namely, aerobic methane-oxidizing bacteria (MOB). We reviewed the literature which provided compelling evidence for the relevance of microbial interaction in modulating methane oxidation. Support for microbial associations within methane-fed communities is sought by a re-analysis of literature data derived from stable isotope probing studies of various complex environmental settings. Putative positive interactions between active MOB and other microbes were assessed by a correlation network-based analysis with datasets covering diverse environments where closely interacting members of a consortium can potentially alter the methane oxidation activity. Although, methanotrophy is used as a model system, the fundamentals of our postulations may be applicable to other microbial guilds mediating other biogeochemical processes.

  2. Modelling microbial metabolic rewiring during growth in a complex medium.

    Science.gov (United States)

    Fondi, Marco; Bosi, Emanuele; Presta, Luana; Natoli, Diletta; Fani, Renato

    2016-11-24

    In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of

  3. Using integrated environmental modeling to automate a process-based Quantitative Microbial Risk Assessment

    Science.gov (United States)

    Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, and human health effect...

  4. Microbial dynamics in a High Arctic glacier forefield: a combined field, laboratory, and modelling approach

    Science.gov (United States)

    Bradley, James A.; Arndt, Sandra; Šabacká, Marie; Benning, Liane G.; Barker, Gary L.; Blacker, Joshua J.; Yallop, Marian L.; Wright, Katherine E.; Bellas, Christopher M.; Telling, Jonathan; Tranter, Martyn; Anesio, Alexandre M.

    2016-10-01

    Modelling the development of soils in glacier forefields is necessary in order to assess how microbial and geochemical processes interact and shape soil development in response to glacier retreat. Furthermore, such models can help us predict microbial growth and the fate of Arctic soils in an increasingly ice-free future. Here, for the first time, we combined field sampling with laboratory analyses and numerical modelling to investigate microbial community dynamics in oligotrophic proglacial soils in Svalbard. We measured low bacterial growth rates and growth efficiencies (relative to estimates from Alpine glacier forefields) and high sensitivity of bacterial growth rates to soil temperature (relative to temperate soils). We used these laboratory measurements to inform parameter values in a new numerical model and significantly refined predictions of microbial and biogeochemical dynamics of soil development over a period of roughly 120 years. The model predicted the observed accumulation of autotrophic and heterotrophic biomass. Genomic data indicated that initial microbial communities were dominated by bacteria derived from the glacial environment, whereas older soils hosted a mixed community of autotrophic and heterotrophic bacteria. This finding was simulated by the numerical model, which showed that active microbial communities play key roles in fixing and recycling carbon and nutrients. We also demonstrated the role of allochthonous carbon and microbial necromass in sustaining a pool of organic material, despite high heterotrophic activity in older soils. This combined field, laboratory, and modelling approach demonstrates the value of integrated model-data studies to understand and quantify the functioning of the microbial community in an emerging High Arctic soil ecosystem.

  5. Proteomics of Porphyromonas gingivalis within a model oral microbial community

    Directory of Open Access Journals (Sweden)

    Wang Tiansong

    2009-05-01

    Full Text Available Abstract Background Porphyromonas gingivalis is a periodontal pathogen that resides in a complex multispecies microbial biofilm community known as dental plaque. Confocal laser scanning microscopy showed that P. gingivalis can assemble into communities in vitro with Streptococcus gordonii and Fusobacterium nucleatum, common constituents of dental plaque. Whole cell quantitative proteomics, along with mutant construction and analysis, were conducted to investigate how P. gingivalis adapts to this three species community. Results 1156 P. gingivalis proteins were detected qualitatively during comparison of the three species model community with P. gingivalis incubated alone under the same conditions. Integration of spectral counting and summed signal intensity analyses of the dataset showed that 403 proteins were down-regulated and 89 proteins up-regulated. The proteomics results were inspected manually and an ontology analysis conducted using DAVID. Significant decreases were seen in proteins involved in cell shape and the formation of the cell envelope, as well as thiamine, cobalamin, and pyrimidine synthesis and DNA repair. An overall increase was seen in proteins involved in protein synthesis. HmuR, a TonB dependent outer membrane receptor, was up-regulated in the community and an hmuR deficient mutant was deficient in three species community formation, but was unimpaired in its ability to form mono- or dual-species biofilms. Conclusion Collectively, these results indicate that P. gingivalis can assemble into a heterotypic community with F. nucleatum and S. gordonii, and that a community lifestyle provides physiologic support for P. gingivalis. Proteins such as HmuR, that are up-regulated, can be necessary for community structure.

  6. A Thermodynamically-Based Model For Predicting Microbial Growth And Community Composition Coupled To System Geochemistry

    Science.gov (United States)

    Istok, J. D.

    2007-12-01

    We present an approach that couples thermodynamic descriptions for microbial growth and geochemical reactions to provide quantitative predictions for the effects of substrate addition or other enviornmental perturbations on microbial community composition. A synthetic microbial community is defined as a collection of defined microbial groups; each with a growth equation derived from bioenergetic principles. The growth equations and standard-state free energy yields are appended to a thermodynamic database for geochemical reactions and the combined equations are solved simultaneously to predict coupled changes in microbial biomass, community composition, and system geochemistry. This approach, with a single set of thermodynamic parameters (one for each growth equation), was used to predict the results of laboratory and field experiments at three geochemically diverse research sites. Predicted effects of ethanol or acetate addition on radionuclide and heavy metal solubility, major ion geochemistry, mineralogy, microbial biomass and community composition were in general agreement with experimental observations although the available experimental data precluded rigorous model testing. Model simulations provide insight into the long-standing difficulty in transferring experimental results from the laboratory to the field and from one site to the next, especially if the form, concentration, or delivery of growth substrate is varied from one experiment to the next. Although originally developed for use in better understanding bioimmobilization of radionuclides and heavy metals via reductive precipitation, the modeling approach is potentially useful for exploring the coupling of microbial growth and geochemical reactions in a variety of basic and applied biotechnology research settings.

  7. Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems

    Science.gov (United States)

    Perez-Garcia, Octavio; Lear, Gavin; Singhal, Naresh

    2016-01-01

    We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN) models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms, and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA), experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e., (i) lumped networks, (ii) compartment per guild networks, (iii) bi-level optimization simulations, and (iv) dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach) are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial interactions can

  8. Metabolic network modeling of microbial interactions in natural and engineered environmental systems

    Directory of Open Access Journals (Sweden)

    Octavio ePerez-Garcia

    2016-05-01

    Full Text Available We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA, experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e. i lumped networks, ii compartment per guild networks, iii bi-level optimization simulations and iv dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial

  9. Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems.

    Science.gov (United States)

    Perez-Garcia, Octavio; Lear, Gavin; Singhal, Naresh

    2016-01-01

    We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN) models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms, and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA), experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e., (i) lumped networks, (ii) compartment per guild networks, (iii) bi-level optimization simulations, and (iv) dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach) are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial interactions can

  10. Prediction of microbial growth in mixed culture with a competition model.

    Science.gov (United States)

    Fujikawa, Hiroshi; Sakha, Mohammad Z

    2014-01-01

    Prediction of microbial growth in mixed culture was studied with a competition model that we had developed recently. The model, which is composed of the new logistic model and the Lotka-Volterra model, is shown to successfully describe the microbial growth of two species in mixed culture using Staphylococcus aureus, Escherichia coli, and Salmonella. With the parameter values of the model obtained from the experimental data on monoculture and mixed culture with two species, it then succeeded in predicting the simultaneous growth of the three species in mixed culture inoculated with various cell concentrations. To our knowledge, it is the first time for a prediction model for multiple (three) microbial species to be reported. The model, which is not built on any premise for specific microorganisms, may become a basic competition model for microorganisms in food and food materials.

  11. Effects of different vegetation restoration models on soil microbial biomass in eroded hilly Loess Plateau, China

    Institute of Scientific and Technical Information of China (English)

    XUE Sha; LIU Guobin; DAI Quanhou; LAN Xue; YU Na

    2007-01-01

    Vegetation restoration is a key measure to improve the eco-environment in Loess Plateau,China.In order to find the effect of soil microbial biomass under different vegetation restoration models in this region,six trial sites located in Zhifanggou watershed were selected in this study.Results showed that soil microbial biomass,microbial respiration and physical and chemical properties increased apparently.After 30 years of vegetation restoration,soil microbial biomass C,N,P(SMBC,SMBN,SMBP)and microbial respiration,increased by 109.01%-144.22%,34.17%-117.09%,31.79%-79.94% and 26.78%-87.59% respectively,as compared with the farmland.However,metabolic quotient declined dramatically by 57.45%-77.49%.Effects of different models of vegetation restoration are different on improving the properties of soil.In general,mixed stands of Pinus tabulaeformisAmorpha fruticosa and Robinia pseudoacacia-A,fruticosa had the most remarkable effect,followed by R.pseudoacacia and Caragana korshinkii,fallow land and P.tabulaeformis was the lowest.Restoration of mixed forest had greater effective than pure forest in eroded Hilly Loess Plateau.The significant relationships were observed among SMBC,SMBP,microbial respiration,and physical and chemical properties of soil.It was concluded that microbial biomass can be used as indicators of soil quality.

  12. Statistical evaluation of mathematical models for microbial growth

    NARCIS (Netherlands)

    Lopez, S.; Prieto, M.; Dijkstra, J.; Dhanoa, M.S.; France, J.

    2004-01-01

    The aim of this study was to evaluate the suitability of several mathematical functions for describing microbial growth curves. The nonlinear functions used were: three-phase linear, logistic, Gompertz, Von Bertalanffy, Richards, Morgan, Weibull, France and Baranyi. Two data sets were used, one comp

  13. GENOME-BASED MODELING AND DESIGN OF METABOLIC INTERACTIONS IN MICROBIAL COMMUNITIES

    Directory of Open Access Journals (Sweden)

    Radhakrishnan Mahadevan

    2012-10-01

    With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

  14. A fermented meat model system for studies of microbial aroma formation

    DEFF Research Database (Denmark)

    Tjener, Karsten; Stahnke, Louise Heller; Andersen, L.

    2003-01-01

    A fermented meat model system was developed, by which microbial formation of volatiles could be examined The model was evaluated against dry, fermented sausages with respect to microbial growth, pH and volatile profiles. Fast and slowly acidified sausages and models were produced using the starter......H, microbial growth and volatile profiles was similar to sausage production. Based on these findings, the model system was considered valid for studies of aroma formation of meat cultures for fermented sausage....... for multivariate data analysis. Growth of lactic acid bacteria was comparable for model and sausages, whereas survival of S. xylosus was better in the model. Multivariate analysis of volatiles showed that differences between fast and slowly acidified samples were identical for model and sausage. For both sausage...

  15. Effects of Microbial Metabolic Lag in Contaminant Transport and Biodegradation Modeling

    Science.gov (United States)

    Wood, Brian D.; Ginn, Timothy R.; Dawson, Clint N.

    1995-03-01

    A model is introduced for microbial kinetics in porous media that includes effects of transients in the metabolic activity of subsurface microorganisms. The model represents the microbial metabolic activity as a functional of the history of aqueous phase substrates; this dependence is represented as a temporally nonlocal convolution integral. Conceptually, this convolution represents the activity of a microbial component as a fraction of its maximum activity, and it is conventionally known as the metabolic potential. The metabolic potential is used to scale the kinetic expressions to account for the metabolic state of the organisms and allows the representation of delayed response in the microbial kinetic equations. Calculation of the convolution requires the definition of a memory (or kernel) function that upon integration over the substrate history represents the microbial metabolic response. A simple piecewise-linear metabolic potential functional is developed here; however, the approach can be generalized to fit the observed behavior of specific systems of interest. The convolution that results from the general form of this model is nonlinear; these nonlinearities are handled by using two separate memory functions and by scaling the domains of the convolution integrals. The model is applied to describe the aerobic degradation of benzene in saturated porous media. Comparative simulations show that metabolic lag can be used to consistently describe observations and that a convolution form can effectively represent microbial lag for this system. Simulations also show that disregarding metabolic lag when it exists can lead to overestimation of the amount of substrate degraded.

  16. Quantitative Modeling of Microbial Population Responses to Chronic Irradiation Combined with Other Stressors

    OpenAIRE

    Igor Shuryak; Ekaterina Dadachova

    2016-01-01

    Microbial population responses to combined effects of chronic irradiation and other stressors (chemical contaminants, other sub-optimal conditions) are important for ecosystem functioning and bioremediation in radionuclide-contaminated areas. Quantitative mathematical modeling can improve our understanding of these phenomena. To identify general patterns of microbial responses to multiple stressors in radioactive environments, we analyzed three data sets on: (1) bacteria isolated from soil co...

  17. A fermented meat model system for studies of microbial aroma formation

    DEFF Research Database (Denmark)

    Tjener, Karsten; Stahnke, Louise Heller; Andersen, L.

    2003-01-01

    A fermented meat model system was developed, by which microbial formation of volatiles could be examined The model was evaluated against dry, fermented sausages with respect to microbial growth, pH and volatile profiles. Fast and slowly acidified sausages and models were produced using the starte......H, microbial growth and volatile profiles was similar to sausage production. Based on these findings, the model system was considered valid for studies of aroma formation of meat cultures for fermented sausage.......A fermented meat model system was developed, by which microbial formation of volatiles could be examined The model was evaluated against dry, fermented sausages with respect to microbial growth, pH and volatile profiles. Fast and slowly acidified sausages and models were produced using the starter...... cultures Pediococcus pentosaceus and Staphylococcus xylosus. Volatiles were collected and analysed by dynamic headspace sampling and GC MS. The analysis was primarily focused on volatiles arising from amino acid degradation and a total of 24 compounds, of which 19 were quantified, were used...

  18. Mechanisms of Electron Transfer in Two Decaheme Cytochromes from a Metal-Reducing Bacterium

    Energy Technology Data Exchange (ETDEWEB)

    Wigginton, Nicholas S.; Rosso, Kevin M.; Hochella, Michael F.

    2007-11-08

    Single-molecule current-voltage (I–V) spectra were collected using a scanning tunneling microscope for two decaheme c-type cytochromes, OmcA and MtrC, which are outer-membrane proteins from the dissimilatory metal-reducing bacterium Shewanella oneidensis. Although the two cytochromes are similar in heme count, charge-carrying amino-acid content, and molecular mass, their I–V spectra are significantly different. The I–V spectra for OmcA show smoothly varying symmetric exponential behavior. These spectra are well fit by a coherent tunneling model that is based on a simple square barrier description of the tunneling junction. In contrast, the I–V spectra for MtrC have pronounced breaks in slope in the positive tip bias range. Two large peaks in the normalized differential conductance spectra of MtrC were fit to a tunneling model that accounts for the possibility of transient population of empty states stabilized by vibrational relaxation. Reorganization energies deduced for the two features are similar to those normally assigned to metal centers in other metalloproteins. Work function measurements of the cytochrome films were used to convert the energies of these two spectral features to the normal hydrogen electrode scale for comparison with the midpoint potential measured using protein film voltammetry, which showed good correspondence. We conclude that MtrC mediates tunneling current by heme orbital participation. The difference in tunneling behavior between OmcA and MtrC suggests distinct physiological functions for the two cytochromes; in contrast to OmcA, MtrC appears to be tuned to a specific operating potential.

  19. Tracer experiment and model evidence for macrofaunal shaping of microbial nitrogen functions along rocky shores

    Science.gov (United States)

    Pfister, Catherine A.; Altabet, Mark A.; Pather, Santhiska; Dwyer, Greg

    2016-06-01

    Seawater microbes as well as those associated with macrobiota are increasingly recognized as a key feature affecting nutrient cycling. Tidepools are ideal natural mesocosms to test macrofauna and microbe interactions, and we quantified rates of microbial nitrogen processing using tracer enrichment of ammonium (15NNH4) or nitrate (15NNO3) when tidepools were isolated from the ocean during low intertidal periods. Experiments were conducted during both day and night as well as in control tidepools and those from which mussels had been removed, allowing us to determine the role of both mussels and daylight in microbial nitrogen processing. We paired time series observations of 15N enrichment in NH4+, NO2- and NO3- with a differential equation model to quantify multiple, simultaneous nitrogen transformations. Mussel presence and daylight increased remineralization and photosynthetic nitrogen uptake. When we compared ammonium gain or loss that was attributed to any tidepool microbes vs. photosynthetic uptake, microbes accounted for 32 % of this ammonium flux on average. Microbial transformations averaged 61 % of total nitrate use; thus, microbial activity was almost 3 times that of photosynthetic nitrate uptake. Because it accounted for processes that diluted our tracer, our differential equation model assigned higher rates of nitrogen processing compared to prior source-product models. Our in situ experiments showed that animals alone elevate microbial nitrogen transformations by 2 orders of magnitude, suggesting that coastal macrobiota are key players in complex microbial nitrogen transformations.

  20. Modeling microbial ethanol production by E. coli under aerobic/anaerobic conditions: applicability to real postmortem cases and to postmortem blood derived microbial cultures.

    Science.gov (United States)

    Boumba, Vassiliki A; Kourkoumelis, Nikolaos; Gousia, Panagiota; Economou, Vangelis; Papadopoulou, Chrissanthy; Vougiouklakis, Theodore

    2013-10-10

    The mathematical modeling of the microbial ethanol production under strict anaerobic experimental conditions for some bacterial species has been proposed by our research group as the first approximation to the quantification of the microbial ethanol production in cases where other alcohols were produced simultaneously with ethanol. The present study aims to: (i) study the microbial ethanol production by Escherichia coli under controlled aerobic/anaerobic conditions; (ii) model the correlation between the microbial produced ethanol and the other higher alcohols; and (iii) test their applicability in: (a) real postmortem cases that had positive BACs (>0.10 g/L) and co-detection of higher alcohols and 1-butanol during the original ethanol analysis and (b) postmortem blood derived microbial cultures under aerobic/anaerobic controlled experimental conditions. The statistical evaluation of the results revealed that the formulated models were presumably correlated to 1-propanol and 1-butanol which were recognized as the most significant descriptors of the modeling process. The significance of 1-propanol and 1-butanol as descriptors was so powerful that they could be used as the only independent variables to create a simple and satisfactory model. The current models showed a potential for application to estimate microbial ethanol - within an acceptable standard error - in various tested cases where ethanol and other alcohols have been produced from different microbes.

  1. Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions.

    Science.gov (United States)

    Momeni, Babak; Xie, Li; Shou, Wenying

    2017-03-28

    Pairwise models are commonly used to describe many-species communities. In these models, an individual receives additive fitness effects from pairwise interactions with each species in the community ('additivity assumption'). All pairwise interactions are typically represented by a single equation where parameters reflect signs and strengths of fitness effects ('universality assumption'). Here, we show that a single equation fails to qualitatively capture diverse pairwise microbial interactions. We build mechanistic reference models for two microbial species engaging in commonly-found chemical-mediated interactions, and attempt to derive pairwise models. Different equations are appropriate depending on whether a mediator is consumable or reusable, whether an interaction is mediated by one or more mediators, and sometimes even on quantitative details of the community (e.g. relative fitness of the two species, initial conditions). Our results, combined with potential violation of the additivity assumption in many-species communities, suggest that pairwise modeling will often fail to predict microbial dynamics.

  2. Application of the new logistic model to microbial growth prediction in food.

    Science.gov (United States)

    Fujikawa, Hiroshi

    2011-06-01

    Recently a microbial growth model, the new logistic model, which could precisely describe and predict microbial growth at various patterns of temperature, was developed by the author (Biocontrol Science, 15, 75-80, 2010). The author shows several software programs developed with the model in this review. First, a program that analyzes microbial growth data and generates growth curves fitted to the model was developed. Second, a growth prediction program for Escherichia coli, Staphylococcus aureus, and Vibrio paraheamolyticus [corrected] exposed at various patterns of temperature was made based on experimental data. For V. paraheamolyticus [corrected] a program for bacterial growth under environmental conditions including temperature, salt concentration, and pH was developed. These programs are available free at the Japan Food Industry Center. Furthermore, a method to estimate the temperature at various points on or inside a food exposed to a given temperature was developed by using the measured temperatures of two points on the surface of the food and the heat conduction law. Combining this method with the growth model, a system that predicts microbial growth in a food exposed to various temperature patterns was made. This system could be a prototype of an alert system for microbial food safety.

  3. A conceptual ecosystem model of microbial communities in enhanced biological phosphorus removal plants.

    Science.gov (United States)

    Nielsen, Per Halkjaer; Mielczarek, Artur Tomasz; Kragelund, Caroline; Nielsen, Jeppe Lund; Saunders, Aaron Marc; Kong, Yunhong; Hansen, Aviaja Anna; Vollertsen, Jes

    2010-09-01

    The microbial populations in 25 full-scale activated sludge wastewater treatment plants with enhanced biological phosphorus removal (EBPR plants) have been intensively studied over several years. Most of the important bacterial groups involved in nitrification, denitrification, biological P removal, fermentation, and hydrolysis have been identified and quantified using quantitative culture-independent molecular methods. Surprisingly, a limited number of core species was present in all plants, constituting on average approx. 80% of the entire communities in the plants, showing that the microbial populations in EBPR plants are rather similar and not very diverse, as sometimes suggested. By focusing on these organisms it is possible to make a comprehensive ecosystem model, where many important aspects in relation to microbial ecosystems and wastewater treatment can be investigated. We have reviewed the current knowledge about these microorganisms with focus on key ecophysiological factors and combined this into a conceptual ecosystem model for EBPR plants. It includes the major pathways of carbon flow with specific organic substances, the dominant populations involved in the transformations, interspecies interactions, and the key factors controlling their presence and activity. We believe that the EBPR process is a perfect model system for studies of microbial ecology in water engineering systems and that this conceptual model can be used for proposing and testing theories based on microbial ecosystem theories, for the development of new and improved quantitative ecosystem models and is beneficial for future design and management of wastewater treatment systems. Copyright © 2010 Elsevier Ltd. All rights reserved.

  4. Representing life in the Earth system with soil microbial functional traits in the MIMICS model

    Science.gov (United States)

    Wieder, W. R.; Grandy, A. S.; Kallenbach, C. M.; Taylor, P. G.; Bonan, G. B.

    2015-06-01

    Projecting biogeochemical responses to global environmental change requires multi-scaled perspectives that consider organismal diversity, ecosystem processes, and global fluxes. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon (C) cycle-climate feedbacks. We used a microbial trait-based soil C model with two physiologically distinct microbial communities, and evaluate how this model represents soil C storage and response to perturbations. Drawing from the application of functional traits used to model other ecosystems, we incorporate copiotrophic and oligotrophic microbial functional groups in the MIcrobial-MIneral Carbon Stabilization (MIMICS) model; these functional groups are akin to "gleaner" vs. "opportunist" plankton in the ocean, or r- vs. K-strategists in plant and animal communities. Here we compare MIMICS to a conventional soil C model, DAYCENT (the daily time-step version of the CENTURY model), in cross-site comparisons of nitrogen (N) enrichment effects on soil C dynamics. MIMICS more accurately simulates C responses to N enrichment; moreover, it raises important hypotheses involving the roles of substrate availability, community-level enzyme induction, and microbial physiological responses in explaining various soil biogeochemical responses to N enrichment. In global-scale analyses, we show that MIMICS projects much slower rates of soil C accumulation than a conventional soil biogeochemistry in response to increasing C inputs with elevated carbon dioxide (CO2) - a finding that would reduce the size of the land C sink estimated by the Earth system. Our findings illustrate that tradeoffs between theory and utility can be overcome to develop soil biogeochemistry models that evaluate and advance our theoretical understanding of microbial dynamics and soil biogeochemical responses to environmental change.

  5. Data-Driven Microbial Modeling for Soil Carbon Decomposition and Stabilization

    Science.gov (United States)

    Luo, Yiqi; Chen, Ji; Chen, Yizhao; Feng, Wenting

    2017-04-01

    Microorganisms have long been known to catalyze almost all the soil organic carbon (SOC) transformation processes (e.g., decomposition, stabilization, and mineralization). Representing microbial processes in Earth system models (ESMs) has the potential to improve projections of SOC dynamics. We have recently examined (1) relationships of microbial functions with environmental factors and (2) microbial regulations of decomposition and other key soil processes. According to three lines of evidence, we have developed a data-driven enzyme (DENZY) model to simulate soil microbial decomposition and stabilization. First, our meta-analysis of 64 published field studies showed that field experimental warming significantly increased soil microbial communities abundance, which is negatively correlated with the mean annual temperature. The negative correlation indicates that warming had stronger effects in colder than warmer regions. Second, we found that the SOC decomposition, especially the transfer between labile SOC and protected SOC, is nonlinearly regulated by soil texture parameters, such as sand and silt contents. Third, we conducted a global analysis of the C-degrading enzyme activities, soil respiration, and SOC content under N addition. Our results show that N addition has contrasting effects on cellulase (hydrolytic C-degrading enzymes) and ligninase (oxidative C-degrading enzymes) activities. N-enhanced cellulase activity contributes to the minor stimulation of soil respiration whereas N-induced repression on ligninase activity drives soil C sequestration. Our analysis links the microbial extracellular C-degrading enzymes to the SOC dynamics at ecosystem scales across scores of experimental sites around the world. It offers direct evidence that N-induced changes in microbial community and physiology play fundamental roles in controlling the soil C cycle. Built upon those three lines of empirical evidence, the DENZY model includes two enzyme pools and explicitly

  6. Development of a new logistic model for microbial growth in foods.

    Science.gov (United States)

    Fujikawa, Hiroshi

    2010-09-01

    Mathematical models are essentially needed to quantitatively predict microbial growth in food products during their production and distribution. Recently we developed a new logistic model for microbial growth. The model is an extended logistic model, which shows a sigmoid curve on a semi-log plot. The model could precisely describe and predict bacterial growth at constant and dynamic temperatures in broth, on nutrient agar plates, and in pouched food. Prediction results with our model were very similar to those with the Baranyi model, which is well known worldwide. The model also predicted the amount of metabolites (toxins) that would be produced by a microorganism. Namely, with the growth model and the kinetics of staphylococcal enterotoxin A production, the amount of the toxins produced by Staphylococcus aureus in milk was successfully predicted. Our model could be a tool in the alert system and the quantitative risk assessment of harmful microbes in food.

  7. Representing life in the Earth system with soil microbial functional traits in the MIMICS model

    Directory of Open Access Journals (Sweden)

    W. R. Wieder

    2015-02-01

    Full Text Available Projecting biogeochemical responses to global environmental change requires multi-scaled perspectives that consider organismal diversity, ecosystem processes and global fluxes. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon cycle–climate feedbacks. We used a microbial trait-based soil carbon (C model, with two physiologically distinct microbial communities to improve current estimates of soil C storage and their likely response to perturbations. Drawing from the application of functional traits used to model other ecosystems, we incorporate copiotrophic and oligotrophic microbial functional groups in the MIcrobial-MIneral Carbon Stabilization (MIMICS model, which incorporates oligotrophic and copiotrophic functional groups, akin to "gleaner" vs. "opportunist" plankton in the ocean, or r vs. K strategists in plant and animals communities. Here we compare MIMICS to a conventional soil C model, DAYCENT, in cross-site comparisons of nitrogen (N enrichment effects on soil C dynamics. MIMICS more accurately simulates C responses to N enrichment; moreover, it raises important hypotheses involving the roles of substrate availability, community-level enzyme induction, and microbial physiological responses in explaining various soil biogeochemical responses to N enrichment. In global-scale analyses, we show that current projections from Earth system models likely overestimate the strength of the land C sink in response to increasing C inputs with elevated carbon dioxide (CO2. Our findings illustrate that tradeoffs between theory and utility can be overcome to develop soil biogeochemistry models that evaluate and advance our theoretical understanding of microbial dynamics and soil biogeochemical responses to environmental change.

  8. LINKING MICROBES TO CLIMATE: INCORPORATING MICROBIAL ACTIVITY INTO CLIMATE MODELS COLLOQUIUM

    Energy Technology Data Exchange (ETDEWEB)

    DeLong, Edward; Harwood, Caroline; Reid, Ann

    2011-01-01

    This report explains the connection between microbes and climate, discusses in general terms what modeling is and how it applied to climate, and discusses the need for knowledge in microbial physiology, evolution, and ecology to contribute to the determination of fluxes and rates in climate models. It recommends with a multi-pronged approach to address the gaps.

  9. The role of dynamic modelling in understanding the microbial contribution to rumen function

    NARCIS (Netherlands)

    Dijkstra, J.; Mills, J.A.N.; France, J.

    2002-01-01

    Mechanistic models of microbial metabolism in the rumen aim at an improved understanding and integration for research purposes or at an improved prediction for practical purposes. The standard way of representing such models is the rate: state formalism. The system is defined by a number of state va

  10. Modelling microbial fuel cells with suspended cells and added electron transfer mediator

    NARCIS (Netherlands)

    Picoreanu, C.; Katuri, K.P.; Van Loosdrecht, M.C.M.; Head, I.M.; Scott, K.

    2009-01-01

    Derivation of a mathematical model for microbial fuel cells (MFC) with suspended biomass and added electron-transfer mediator is described. The model is based on mass balances for several dissolved chemical species such as substrate, oxidized mediator and reduced mediator. Biological, chemical and e

  11. Applications of artificial neural networks for microbial water quality modeling

    Energy Technology Data Exchange (ETDEWEB)

    Brion, G.M.; Lingireddy, S. [Univ. of Kentucky, Dept. of Civil Engineering, Lexington, Kentucky (United States)]. E-mail: gbrion@engr.uky.edu

    2002-06-15

    There has been a significant shift in the recent past towards protecting chemical and microbial quality of source waters rather than developing advanced methods to treat heavily polluted water. The key to successful best management practices in protecting the source waters is to identify sources of non-point pollution and their collective impact on the quality of water at the intake. This article presents a few successful applications where artificial neural networks (ANN) have proven to be the useful mathematical tools in correlating the nonlinear relationships between routinely measured parameters (such as rainfall, turbidity, fecal coliforms etc.) and quality of source waters and/or nature of fecal sources. These applications include, prediction of peak concentrations of Giardia and Cryptosporidium, sorting of fecal sources (e.g. agricultural animals vs. urban animals), predicting relative ages of the runoff sources, identifying the potential for sewage contamination. The ability of ANNs to work with complex, inter-related multiparameter databases, and provide superior predictive power in non-linear relationships has been the key for their successful application to microbial water quality studies. (author)

  12. Modelling geochemical and microbial consumption of dissolved oxygen after backfilling a high level radiactive waste repository.

    Science.gov (United States)

    Yang, Changbing; Samper, Javier; Molinero, Jorge; Bonilla, Mercedes

    2007-08-15

    Dissolved oxygen (DO) left in the voids of buffer and backfill materials of a deep geological high level radioactive waste (HLW) repository could cause canister corrosion. Available data from laboratory and in situ experiments indicate that microbes play a substantial role in controlling redox conditions near a HLW repository. This paper presents the application of a coupled hydro-bio-geochemical model to evaluate geochemical and microbial consumption of DO in bentonite porewater after backfilling of a HLW repository designed according to the Swedish reference concept. In addition to geochemical reactions, the model accounts for dissolved organic carbon (DOC) respiration and methane oxidation. Parameters for microbial processes were derived from calibration of the REX in situ experiment carried out at the Aspö underground laboratory. The role of geochemical and microbial processes in consuming DO is evaluated for several scenarios. Numerical results show that both geochemical and microbial processes are relevant for DO consumption. However, the time needed to consume the DO trapped in the bentonite buffer decreases dramatically from several hundreds of years when only geochemical processes are considered to a few weeks when both geochemical reactions and microbially-mediated DOC respiration and methane oxidation are taken into account simultaneously.

  13. Quantitative Modeling of Microbial Population Responses to Chronic Irradiation Combined with Other Stressors.

    Science.gov (United States)

    Shuryak, Igor; Dadachova, Ekaterina

    2016-01-01

    Microbial population responses to combined effects of chronic irradiation and other stressors (chemical contaminants, other sub-optimal conditions) are important for ecosystem functioning and bioremediation in radionuclide-contaminated areas. Quantitative mathematical modeling can improve our understanding of these phenomena. To identify general patterns of microbial responses to multiple stressors in radioactive environments, we analyzed three data sets on: (1) bacteria isolated from soil contaminated by nuclear waste at the Hanford site (USA); (2) fungi isolated from the Chernobyl nuclear-power plant (Ukraine) buildings after the accident; (3) yeast subjected to continuous γ-irradiation in the laboratory, where radiation dose rate and cell removal rate were independently varied. We applied generalized linear mixed-effects models to describe the first two data sets, whereas the third data set was amenable to mechanistic modeling using differential equations. Machine learning and information-theoretic approaches were used to select the best-supported formalism(s) among biologically-plausible alternatives. Our analysis suggests the following: (1) Both radionuclides and co-occurring chemical contaminants (e.g. NO2) are important for explaining microbial responses to radioactive contamination. (2) Radionuclides may produce non-monotonic dose responses: stimulation of microbial growth at low concentrations vs. inhibition at higher ones. (3) The extinction-defining critical radiation dose rate is dramatically lowered by additional stressors. (4) Reproduction suppression by radiation can be more important for determining the critical dose rate, than radiation-induced cell mortality. In conclusion, the modeling approaches used here on three diverse data sets provide insight into explaining and predicting multi-stressor effects on microbial communities: (1) the most severe effects (e.g. extinction) on microbial populations may occur when unfavorable environmental

  14. Mineral transformations during the dissolution of uranium ore minerals by dissimilatory metal-reducing bacteria

    Science.gov (United States)

    Glasauer, S.; Weidler, P.; Fakra, S.; Tyliszczak, T.; Shuh, D.

    2011-12-01

    Carnotite minerals [X2(UO2)2(VO4)2]; X = K, Ca, Ba, Mn, Na, Cu or Pb] form the major ore of uranium in the Colorado Plateau. These deposits are highly oxidized and contain U(VI) and V(IV). The biotransformation of U(VI) bound in carnotite by bacteria during dissimilatory metal reduction presents a complex puzzle in mineral chemistry. Both U(VI) and V(V) can be respired by metal reducing bacteria, and the mineral structure can change depending on the associated counterion. We incubated anaerobic cultures of S. putrefaciens CN32 with natural carnotite minerals from southeastern Utah in a nutrient-limited defined medium. Strain CN32 is a gram negative bacterium and a terrestrial isolate from New Mexico. The mineral and metal transformations were compared to a system that contained similar concentrations of soluble U(VI) and V(V). Electron (SEM, TEM) microscopies and x-ray spectromicroscopy (STXM) were used in conjunction with XRD to track mineral changes, and bacterial survival was monitored throughout the incubations. Slow rates of metal reduction over 10 months for the treatment with carnotite minerals revealed distinct biotic and abiotic processes, providing insight on mineral transformation and bacteria-metal interactions. The bacteria existed as small flocs or individual cells attached to the mineral phase, but did not adsorb soluble U or V, and accumulated very little of the biominerals. Reduction of mineral V(V) necessarily led to a dismantling of the carnotite structure. Bioreduction of V(V) by CN32 contributed small but profound changes to the mineral system, resulting in new minerals. Abiotic cation exchange within the carnotite group minerals induced the rearrangement of the mineral structures, leading to further mineral transformation. In contrast, bacteria survival was poor for treatments with soluble U(VI) and V(V), although both metals were reduced completely and formed solid UO2 and VO2; we also detected V(III). For these treatments, the bacteria

  15. Microbial functional diversity enhances predictive models linking environmental parameters to ecosystem properties.

    Science.gov (United States)

    Powell, Jeff R; Welsh, Allana; Hallin, Sara

    2015-07-01

    Microorganisms drive biogeochemical processes, but linking these processes to real changes in microbial communities under field conditions is not trivial. Here, we present a model-based approach to estimate independent contributions of microbial community shifts to ecosystem properties. The approach was tested empirically, using denitrification potential as our model process, in a spatial survey of arable land encompassing a range of edaphic conditions and two agricultural production systems. Soil nitrate was the most important single predictor of denitrification potential (the change in Akaike's information criterion, corrected for sample size, ΔAIC(c) = 20.29); however, the inclusion of biotic variables (particularly the evenness and size of denitrifier communities [ΔAIC(c) = 12.02], and the abundance of one denitrifier genotype [ΔAIC(c) = 18.04]) had a substantial effect on model precision, comparable to the inclusion of abiotic variables (biotic R2 = 0.28, abiotic R2 = 0.50, biotic + abiotic R2 = 0.76). This approach provides a valuable tool for explicitly linking microbial communities to ecosystem functioning. By making this link, we have demonstrated that including aspects of microbial community structure and diversity in biogeochemical models can improve predictions of nutrient cycling in ecosystems and enhance our understanding of ecosystem functionality.

  16. In situ examination of microbial populations in a model drinking water distribution system

    DEFF Research Database (Denmark)

    Martiny, Adam Camillo; Nielsen, Alex Toftgaard; Arvin, Erik

    2002-01-01

    A flow cell set-up was used as a model drinking water distribution system to analyze the in situ microbial population. Biofilm growth was followed by transmission light microscopy for 81 days and showed a biofilm consisting of microcolonies separated by a monolayer of cells. Protozoans (ciliates...

  17. Hydration and diffusion processes shape microbial community organization and function in model soil aggregates

    Science.gov (United States)

    Ebrahimi, Ali; Or, Dani

    2015-12-01

    The constantly changing soil hydration status affects gas and nutrient diffusion through soil pores and thus the functioning of soil microbial communities. The conditions within soil aggregates are of particular interest due to limitations to oxygen diffusion into their core, and the presence of organic carbon often acting as binding agent. We developed a model for microbial life in simulated soil aggregates comprising of 3-D angular pore network model (APNM) that mimics soil hydraulic and transport properties. Within these APNM, we introduced individual motile (flagellated) microbial cells with different physiological traits that grow, disperse, and respond to local nutrients and oxygen concentrations. The model quantifies the dynamics and spatial extent of anoxic regions that vary with hydration conditions, and their role in shaping microbial community size and activity and the spatial (self) segregation of anaerobes and aerobes. Internal carbon source and opposing diffusion directions of oxygen and carbon within an aggregate were essential to emergence of stable coexistence of aerobic and anaerobic communities (anaerobes become extinct when carbon sources are external). The model illustrates a range of hydration conditions that promote or suppress denitrification or decomposition of organic matter and thus affect soil GHG emissions. Model predictions of CO2 and N2O production rates were in good agreement with limited experimental data. These limited tests support the dynamic modeling approach whereby microbial community size, composition, and spatial arrangement emerge from internal interactions within soil aggregates. The upscaling of the results to a population of aggregates of different sizes embedded in a soil profile is underway.

  18. Microbial Degradation of Propylene Glycol - Modelling Approach of a Batch Experiment

    Science.gov (United States)

    Dathe, Annette; Fernandez, Perrine; Bakken, Lars; Bloem, Esther; French, Helen

    2016-04-01

    De-icing chemicals are applied in large amounts at airports during winter conditions to keep the runways and aircrafts ice-free. At Gardermoen airport, Norway, most of the applied chemicals can be captured, but about 10 to 20 % infiltrate into the soil along the runways and during take-off. While the commonly used propylene glycol (PG) is easily degradable by local microbial communities, its biological oxygen demand is high, anoxic zones can develop and soluble Fe+2 and Mn+2 ions eventually can reach the groundwater. The objectives of the presented study are to quantify the mechanisms, which control the order of reduction processes in an unsaturated sandy soil, and to test whether measured redox potentials can help to determine underlying biogeochemical reactions. To investigate the mechanisms of microbial degradation, the water phase of soil samples from Gardermoen Airport was replaced by deionized water with 10 mMol PG or 10 mMol glutamate and the samples were incubated at 10°C for about two weeks. The gas phase was sampled and analyzed automatically every three hours. Microbial degradation of the substrate (PG or glutamate) was modelled following a Monod kinetics using the FME (Flexible Modelling Environment) package of R (Project for Statistical Computing). The model was calibrated against measurements of O2 depletion and CO2 production. The initial concentrations of O2, CO2 and PG or glutamate are known and microbial yields and stoichiometric constants can be calculated from the measurements. Parameter values for the initial microbial population size, maximum microbial growth rate, the half saturation constant, and microbial degradation and respiration rates were fitted using the FME package. The model accounts for carbon from the substrate (PG or glutamate) incorporated into the biomass. Results are promising, but because of the large number of parameters needed to fit a Monod kinetics it is challenging to accurately model a whole redox sequence. The

  19. Systems modeling approaches for microbial community studies: From metagenomics to inference of the community structure

    Directory of Open Access Journals (Sweden)

    Mark eHanemaaijer

    2015-03-01

    Full Text Available Microbial communities play important roles in health, industrial applications and earth's ecosystems. With current molecular techniques we can characterize these systems in unprecedented detail. However, such methods provide little mechanistic insight into how the genetic properties and the dynamic couplings between individual microorganisms give rise to their dynamic activities. Neither do they give insight into what we call `the community state', that is the fluxes and concentrations of nutrients within the community. This knowledge is a prerequisite for rational control and intervention in microbial communities. Therefore, the inference of the community structure from experimental data is a major current challenge. We will argue that this inference problem requires mathematical models that can integrate heterogeneous experimental data with existing knowledge. We propose that two types of models are needed. Firstly, mathematical models that integrate existing genomic, physiological, and physicochemical information with metagenomics data so as to maximize information content and predictive power. This can be achieved with the use of constraint-based genome-scale stoichiometric modeling of community metabolism which is ideally suited for this purpose. Next, we propose a simpler coarse-grained model, which is tailored to solve the inference problem from the experimental data. This model unambiguously relate to the more detailed genome-scale stoichiometric models which act as heterogeneous data integrators. The simpler inference models are, in our opinion, key to understanding microbial ecosystems, yet until now, have received remarkably little attention. This has led to the situation where the modeling of microbial communities, using only genome-scale models is currently more a computational, theoretical exercise than a method useful to the experimentalist.

  20. Comparison of Primary Models to Predict Microbial Growth by the Plate Count and Absorbance Methods.

    Science.gov (United States)

    Pla, María-Leonor; Oltra, Sandra; Esteban, María-Dolores; Andreu, Santiago; Palop, Alfredo

    2015-01-01

    The selection of a primary model to describe microbial growth in predictive food microbiology often appears to be subjective. The objective of this research was to check the performance of different mathematical models in predicting growth parameters, both by absorbance and plate count methods. For this purpose, growth curves of three different microorganisms (Bacillus cereus, Listeria monocytogenes, and Escherichia coli) grown under the same conditions, but with different initial concentrations each, were analysed. When measuring the microbial growth of each microorganism by optical density, almost all models provided quite high goodness of fit (r(2) > 0.93) for all growth curves. The growth rate remained approximately constant for all growth curves of each microorganism, when considering one growth model, but differences were found among models. Three-phase linear model provided the lowest variation for growth rate values for all three microorganisms. Baranyi model gave a variation marginally higher, despite a much better overall fitting. When measuring the microbial growth by plate count, similar results were obtained. These results provide insight into predictive microbiology and will help food microbiologists and researchers to choose the proper primary growth predictive model.

  1. Modeling the Influence of Transport on Chemical Reactivity in Microbial Membranes: Mineral Precipitation/Dissolution Reactions.

    Science.gov (United States)

    Felmy, A. R.; Liu, C.; Clark, S.; Straatsma, T.; Rustad, J.

    2003-12-01

    It has long been known that microorganisms can alter the chemical composition of their immediate surroundings and influence such processes as ion uptake or adsorption and mineral precipitation dissolution. However, only recently have molecular imaging and molecular modeling capabilities been developed that begin to shed light on the nature of these processes at the nm to um scale at the surface of bacterial membranes. In this presentation we will show the results of recent molecular simulations of microbial surface reactions and describe our efforts to develop accurate non-equilibrium thermodynamic models for the microbial surface that can describe ion uptake and surface induced mineral precipitation. The thermodynamic models include the influence of the bacterial electrical double layer on the uptake of ions from solution and the removal, or exclusion, of ions from the surface of the cell, non-equilibrium diffusion and chemical reaction within the membrane, as well as a new thermodynamic approach to representing ion activities within the microbial membrane. In the latter case, the variability in the water content within the microbial membrane has a significant influence on the calculated mineral saturation indices. In such cases, we will propose the use of recently developed mixed solvent-electrolyte formalisms. Recent experimental data for mixed-solvent electrolyte systems will also be presented to demonstrate the potential impact of the variable water content on calculated ion activities within the membrane.

  2. Modeling microbial dynamics in heterogeneous environments: growth on soil carbon sources.

    Science.gov (United States)

    Resat, Haluk; Bailey, Vanessa; McCue, Lee Ann; Konopka, Allan

    2012-05-01

    We have developed a new kinetic model to study how microbial dynamics are affected by the heterogeneity in the physical structure of the environment and by different strategies for hydrolysis of polymeric carbon. The hybrid model represented the dynamics of substrates and enzymes using a continuum representation and the dynamics of the cells were modeled individually. Individual-based biological model allowed us to explicitly simulate microbial diversity, and to model cell physiology as regulated via optimal allocation of cellular resources to enzyme synthesis, control of growth rate by protein synthesis capacity, and shifts to dormancy. This model was developed to study how microbial community functioning is influenced by local environmental conditions in heterogeneous media such as soil and by the functional attributes of individual microbes. Microbial community dynamics were simulated at two spatial scales: micro-pores that resemble 6-20-μm size portions of the soil physical structure and in 111-μm size soil aggregates with a random pore structure. Different strategies for acquisition of carbon from polymeric cellulose were investigated. Bacteria that express membrane-associated hydrolase had different growth and survival dynamics in soil pores than bacteria that release extracellular hydrolases. The kinetic differences suggested different functional niches for these two microbe types in cellulose utilization. Our model predicted an emergent behavior in which co-existence of membrane-associated hydrolase and extracellular hydrolases releasing organisms led to higher cellulose utilization efficiency and reduced stochasticity. Our analysis indicated that their co-existence mutually benefits these organisms, where basal cellulose degradation activity by membrane-associated hydrolase-expressing cells shortened the soluble hydrolase buildup time and, when enzyme buildup allowed for cellulose degradation to be fast enough to sustain exponential growth, all the

  3. Microbial and Organic Fine Particle Transport Dynamics in Streams - a Combined Experimental and Stochastic Modeling Approach

    Science.gov (United States)

    Drummond, Jen; Davies-Colley, Rob; Stott, Rebecca; Sukias, James; Nagels, John; Sharp, Alice; Packman, Aaron

    2014-05-01

    Transport dynamics of microbial cells and organic fine particles are important to stream ecology and biogeochemistry. Cells and particles continuously deposit and resuspend during downstream transport owing to a variety of processes including gravitational settling, interactions with in-stream structures or biofilms at the sediment-water interface, and hyporheic exchange and filtration within underlying sediments. Deposited cells and particles are also resuspended following increases in streamflow. Fine particle retention influences biogeochemical processing of substrates and nutrients (C, N, P), while remobilization of pathogenic microbes during flood events presents a hazard to downstream uses such as water supplies and recreation. We are conducting studies to gain insights into the dynamics of fine particles and microbes in streams, with a campaign of experiments and modeling. The results improve understanding of fine sediment transport, carbon cycling, nutrient spiraling, and microbial hazards in streams. We developed a stochastic model to describe the transport and retention of fine particles and microbes in rivers that accounts for hyporheic exchange and transport through porewaters, reversible filtration within the streambed, and microbial inactivation in the water column and subsurface. This model framework is an advance over previous work in that it incorporates detailed transport and retention processes that are amenable to measurement. Solute, particle, and microbial transport were observed both locally within sediment and at the whole-stream scale. A multi-tracer whole-stream injection experiment compared the transport and retention of a conservative solute, fluorescent fine particles, and the fecal indicator bacterium Escherichia coli. Retention occurred within both the underlying sediment bed and stands of submerged macrophytes. The results demonstrate that the combination of local measurements, whole-stream tracer experiments, and advanced modeling

  4. Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

    Science.gov (United States)

    Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

    2016-02-01

    Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  5. Modeling the microbial growth of two Escherichia coli strains in a multi-substrate environment

    OpenAIRE

    Poccia,M. E.; Beccaria, A. J.; R. G. Dondo

    2014-01-01

    The microbial growth in multi-substrate environments may be viewed as an optimal resources allocation problem. The optimization aims at maximizing some biological objective like the biomass growth. The models developed using this hypothesis are called “cybernetic” and they represent the complex cell structure as an optimizing function that regulates the intracellular enzymatic machinery. In this work, a cybernetic model was developed to represent the growth of two E. coli strains (JM 109 and ...

  6. Satellite remote sensing data can be used to model marine microbial metabolite turnover.

    Science.gov (United States)

    Larsen, Peter E; Scott, Nicole; Post, Anton F; Field, Dawn; Knight, Rob; Hamada, Yuki; Gilbert, Jack A

    2015-01-01

    Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km(2)) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes' predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ∼3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology.

  7. From cultured to uncultured genome sequences: metagenomics and modeling microbial ecosystems.

    Science.gov (United States)

    Garza, Daniel R; Dutilh, Bas E

    2015-11-01

    Microorganisms and the viruses that infect them are the most numerous biological entities on Earth and enclose its greatest biodiversity and genetic reservoir. With strength in their numbers, these microscopic organisms are major players in the cycles of energy and matter that sustain all life. Scientists have only scratched the surface of this vast microbial world through culture-dependent methods. Recent developments in generating metagenomes, large random samples of nucleic acid sequences isolated directly from the environment, are providing comprehensive portraits of the composition, structure, and functioning of microbial communities. Moreover, advances in metagenomic analysis have created the possibility of obtaining complete or nearly complete genome sequences from uncultured microorganisms, providing important means to study their biology, ecology, and evolution. Here we review some of the recent developments in the field of metagenomics, focusing on the discovery of genetic novelty and on methods for obtaining uncultured genome sequences, including through the recycling of previously published datasets. Moreover we discuss how metagenomics has become a core scientific tool to characterize eco-evolutionary patterns of microbial ecosystems, thus allowing us to simultaneously discover new microbes and study their natural communities. We conclude by discussing general guidelines and challenges for modeling the interactions between uncultured microorganisms and viruses based on the information contained in their genome sequences. These models will significantly advance our understanding of the functioning of microbial ecosystems and the roles of microbes in the environment.

  8. Fractional differential equations based modeling of microbial survival and growth curves: model development and experimental validation.

    Science.gov (United States)

    Kaur, A; Takhar, P S; Smith, D M; Mann, J E; Brashears, M M

    2008-10-01

    A fractional differential equations (FDEs)-based theory involving 1- and 2-term equations was developed to predict the nonlinear survival and growth curves of foodborne pathogens. It is interesting to note that the solution of 1-term FDE leads to the Weibull model. Nonlinear regression (Gauss-Newton method) was performed to calculate the parameters of the 1-term and 2-term FDEs. The experimental inactivation data of Salmonella cocktail in ground turkey breast, ground turkey thigh, and pork shoulder; and cocktail of Salmonella, E. coli, and Listeria monocytogenes in ground beef exposed at isothermal cooking conditions of 50 to 66 degrees C were used for validation. To evaluate the performance of 2-term FDE in predicting the growth curves-growth of Salmonella typhimurium, Salmonella Enteritidis, and background flora in ground pork and boneless pork chops; and E. coli O157:H7 in ground beef in the temperature range of 22.2 to 4.4 degrees C were chosen. A program was written in Matlab to predict the model parameters and survival and growth curves. Two-term FDE was more successful in describing the complex shapes of microbial survival and growth curves as compared to the linear and Weibull models. Predicted curves of 2-term FDE had higher magnitudes of R(2) (0.89 to 0.99) and lower magnitudes of root mean square error (0.0182 to 0.5461) for all experimental cases in comparison to the linear and Weibull models. This model was capable of predicting the tails in survival curves, which was not possible using Weibull and linear models. The developed model can be used for other foodborne pathogens in a variety of food products to study the destruction and growth behavior.

  9. An electrodynamics-based model for ion diffusion in microbial polysaccharides.

    Science.gov (United States)

    Liu, Chongxuan; Zachara, John M; Felmy, Andrew; Gorby, Yuri

    2004-10-10

    An electrodynamics-based model was formulated for simulation of ion diffusion in microbial polysaccharides. The fixed charges and electrostatic double layers that may associate with microbial polysaccharides and their effects on ion diffusion were explicitly built into the model. The model extends a common multicomponent ion diffusion formulation that is based on irreversible thermodynamics under a zero ionic charge flux condition, which is only applicable to the regions without fixed charges and electrostatic double layers. An efficient numerical procedure was presented to solve the differential equations in the model. The model well described key features of experimental observations of ion diffusion in negatively charged microbial polysaccharides including accelerated diffusive transport of cations, exclusion of anions, and increased rate of cation transport with increasing negative charge density. The simulated diffusive fluxes of cations and anions were consistent with a cation exchange diffusion concept in negatively charged polysaccharides at the interface of plant roots and soils; and the developed model allows to mathematically study such diffusion phenomena. An illustrative example was also provided to simulate dynamic behavior of ionic current during ion diffusion within a charged bacterial cell wall polysaccharide and the effects of the ionic current on the compression or expansion of the bacterial electrostatic double layer at the interface of the cell wall and bulk solution.

  10. FORWARD AND INVERSE BIO-GEOCHEMICAL MODELING OF MICROBIALLY INDUCED PRECIPITATION IN 0.5M COLUMNAR EXPERIMENTS

    Energy Technology Data Exchange (ETDEWEB)

    Tammer Barkouki; Brian Martinez; Brina Mortensen; Tess Weathers; Jason DeJong; Nic Spycher; Tim Ginn; Yoshiko Fujita; Robert Smith

    2009-09-01

    Microbial ureolysis-induced calcite precipitation may offer an in situ remediation for heavy metal and radionuclide contamination, as well as an alternative to traditional soil strengthening techniques. A microbially mediated calcite precipitation model was built in TOUGHREACT v2 and calibrated to batch and columnar experimental data. Kinetic ureolysis and calcite precipitation-rate expressions were parameterized by coupling TOUCHREACT with UCODE.

  11. Putting microbes into microbial-based models of soil organic matter formation

    Science.gov (United States)

    Grandy, S.

    2012-12-01

    Soil organic matter formation (SOM) is a two-step process that begins with litter decomposition and is followed by the incorporation of C into stable SOM pools. It is known that microbes play a critical role in both processes, but their specific contributions remain undefined and even the newest models of SOM formation largely 'black box' the microbial community. For example, the current paradigm predicts that litter chemical changes during decomposition are predictable based on the extent or stage of decomposition, and that chemically distinct litter types will eventually become indistinguishable after decomposition. This convergence in chemical composition is thought to occur regardless of initial differences in litter quality or variation in biological communities. Further, while microbial ecophysiology may have direct influences on the rates of SOM accumulation, chemistry and stability, how the expression of ecophysiological traits vary across environments and between microbial communities is unclear. Here, I examine the role of decomposer communities in regulating the two-step SOM formation process. First, I examine litter chemical changes and convergence during decomposition and the degree to which they are influenced by decomposer community characteristics. In contrast to the current paradigm, I show that decomposer communities strongly mediate changes in litter chemistry during decomposition, and that there is neither chemical convergence nor a consistent, predictable change in litter chemistry during decomposition. Instead, litter chemical changes are a function of the interactions between initial litter quality and the resident decomposer communities, which often vary among soil ecosystems. Second, I identify several knowledge gaps that need to be addressed in order to advance our understanding of litter incorporation into stable SOM pools, focusing on the importance of microbial physiological processes to SOM formation, including: 1) differences in

  12. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

    Science.gov (United States)

    Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

    2011-03-01

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  13. Connection between stochastic and deterministic modelling of microbial growth.

    Science.gov (United States)

    Kutalik, Zoltán; Razaz, Moe; Baranyi, József

    2005-01-21

    We present in this paper various links between individual and population cell growth. Deterministic models of the lag and subsequent growth of a bacterial population and their connection with stochastic models for the lag and subsequent generation times of individual cells are analysed. We derived the individual lag time distribution inherent in population growth models, which shows that the Baranyi model allows a wide range of shapes for individual lag time distribution. We demonstrate that individual cell lag time distributions cannot be retrieved from population growth data. We also present the results of our investigation on the effect of the mean and variance of the individual lag time and the initial cell number on the mean and variance of the population lag time. These relationships are analysed theoretically, and their consequence for predictive microbiology research is discussed.

  14. Modeling the link between soil microbial community structure and function in a bottom-up approach

    Science.gov (United States)

    Kaiser, C.; Richter, A.; Franklin, O.; Evans, S. E.; Dieckmann, U.

    2012-12-01

    Understanding mechanisms of soil carbon (C) turnover requires understanding the link between microbial community dynamics and soil decomposition processes. We present here an individual-based model that aims at elucidating this link by a bottom-up approach. Our approach differs from traditional soil C cycling models in that the overall dynamics of soil organic matter turnover emerges as the result of interactions between individual microbes at the soil microsite level, rather than being described by stock and flow rate equations at the bulk soil level. All soil microbes are modeled individually, each belonging to one of several functional groups defined by functional traits. Specifically, functional traits determine (1) growth and turnover rates, (2) production of extracellular enzymes and (3) microbial cell stoichiometry. Our model incorporates competition for space and nutrients (C and nitrogen, N) as well as synergistic interactions between individual microbes in a spatially structured environment represented by a two-dimensional grid. Due to different C and N limitations of different functional groups, community composition is sensitive to the availability of complex and labile C and N. Thus, altered resource availability changes microbial community composition, which in turn affects CO2 and N release from the soil. In our model, microbes constantly alter their own environment through the decomposition of different substrates, thereby exerting a feedback on community composition, which leads to a succession of microbial groups. We used the model's intrinsic link between resource availability, community dynamics and decomposition function to investigate the mechanism underlying the rhizosphere priming effect (i.e. increased decomposition of older soil C triggered by the input of labile C). In particular, we examined the spatial growth of a root releasing exudates of varying C:N ratios under the presence or absence of different functional groups. We find that a

  15. Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

    Science.gov (United States)

    Momeni, Babak; Xie, Li; Shou, Wenying

    2017-01-01

    Pairwise models are commonly used to describe many-species communities. In these models, an individual receives additive fitness effects from pairwise interactions with each species in the community ('additivity assumption'). All pairwise interactions are typically represented by a single equation where parameters reflect signs and strengths of fitness effects ('universality assumption'). Here, we show that a single equation fails to qualitatively capture diverse pairwise microbial interactions. We build mechanistic reference models for two microbial species engaging in commonly-found chemical-mediated interactions, and attempt to derive pairwise models. Different equations are appropriate depending on whether a mediator is consumable or reusable, whether an interaction is mediated by one or more mediators, and sometimes even on quantitative details of the community (e.g. relative fitness of the two species, initial conditions). Our results, combined with potential violation of the additivity assumption in many-species communities, suggest that pairwise modeling will often fail to predict microbial dynamics. DOI: http://dx.doi.org/10.7554/eLife.25051.001 PMID:28350295

  16. Modeling the effect of substrate stoichiometry on microbial carbon use efficiency and soil C cycling

    Science.gov (United States)

    Abramoff, R. Z.; Tang, J.; Georgiou, K.; Brodie, E.; Torn, M. S.; Riley, W. J.

    2015-12-01

    Microorganisms degrade soil organic matter (SOM) and apportion newly acquired substrates into enzyme production, biomass growth, and respiration. The fraction of acquired substrate that is released into the atmosphere as heterotrophic respiration is determined by the microbial carbon use efficiency (CUE), commonly defined as the fraction of carbon uptake that is allocated to microbial growth and enzyme production. Despite recent demonstrations that changes in CUE can greatly affect predictions of global soil C stocks, most models do not incorporate process-level representation of CUE or how it varies with substrate stoichiometry. Here we introduce coupled C and N cycling into a prognostic CUE model that uses the dynamic energy budget theory to predict CUE at each time step. We solve this model over a range of substrate C:N to simulate the effects of N addition on CUE, and test the model against previously published measurements of CUE after nutrient enrichment with a range of substrates. We find that CUE declines with microbial N limitation due to C overflow and acquisition strategies that favor N immobilization. We also demonstrate that including an intracellular reserve pool in the model alleviates decreases in CUE by allowing excess C to be stored during periods of N limitation. Consistent with previous studies, we find that predictions of soil C stocks are highly sensitive to CUE. Furthermore, we show that interactive effects between substrate inputs and temperature result in a wide range of possible CUE values under global change scenarios.

  17. Source tracking using microbial community fingerprints: Method comparison with hydrodynamic modelling.

    Science.gov (United States)

    McCarthy, D T; Jovanovic, D; Lintern, A; Teakle, I; Barnes, M; Deletic, A; Coleman, R; Rooney, G; Prosser, T; Coutts, S; Hipsey, M R; Bruce, L C; Henry, R

    2017-02-01

    Urban estuaries around the world are experiencing contamination from diffuse and point sources, which increases risks to public health. To mitigate and manage risks posed by elevated levels of contamination in urban waterways, it is critical to identify the primary water sources of contamination within catchments. Source tracking using microbial community fingerprints is one tool that can be used to identify sources. However, results derived from this approach have not yet been evaluated using independent datasets. As such, the key objectives of this investigation were: (1) to identify the major sources of water responsible for bacterial loadings within an urban estuary using microbial source tracking (MST) using microbial communities; and (2) to evaluate this method using a 3-dimensional hydrodynamic model. The Yarra River estuary, which flows through the city of Melbourne in South-East Australia was the focus of this study. We found that the water sources contributing to the bacterial community in the Yarra River estuary varied temporally depending on the estuary's hydrodynamic conditions. The water source apportionment determined using microbial community MST correlated to those determined using a 3-dimensional hydrodynamic model of the transport and mixing of a tracer in the estuary. While there were some discrepancies between the two methods, this investigation demonstrated that MST using bacterial community fingerprints can identify the primary water sources of microorganisms in an estuarine environment. As such, with further optimization and improvements, microbial community MST has the potential to become a powerful tool that could be practically applied in the mitigation of contaminated aquatic systems.

  18. The Earth Microbiome Project and modeling the planets microbial potential (Invited)

    Science.gov (United States)

    Gilbert, J. A.

    2013-12-01

    The understanding of Earth's climate and ecology requires multiscale observations of the biosphere, of which microbial life are a major component. However, to acquire and process physical samples of soil, water and air that comprise the appropriate spatial and temporal resolution to capture the immense variation in microbial dynamics, would require a herculean effort and immense financial resources dwarfing even the most ambitious projects to date. To overcome this hurdle we created the Earth Microbiome Project, a crowd-sourced effort to acquire physical samples from researchers around the world that are, importantly, contextualized with physical, chemical and biological data detailing the environmental properties of that sample in the location and time it was acquired. The EMP leverages these existing efforts to target a systematic analysis of microbial taxonomic and functional dynamics across a vast array of environmental parameter gradients. The EMP captures the environmental gradients, location, time and sampling protocol information about every sample donated by our valued collaborators. Physical samples are then processed using a standardized DNA extraction, PCR, and shotgun sequencing protocol to generate comparable data regarding the microbial community structure and function in each sample. To date we have processed >17,000 samples from 40 different biomes. One of the key goals of the EMP is to map the spatiotemporal variability of microbial communities to capture the changes in important functional processes that need to be appropriately expressed in models to provide reliable forecasts of ecosystem phenotype across our changing planet. This is essential if we are to develop economically sound strategies to be good stewards of our Earth. The EMP recognizes that environments are comprised of complex sets of interdependent parameters and that the development of useful predictive computational models of both terrestrial and atmospheric systems requires

  19. The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism.

    Science.gov (United States)

    Birkel, Garrett W; Ghosh, Amit; Kumar, Vinay S; Weaver, Daniel; Ando, David; Backman, Tyler W H; Arkin, Adam P; Keasling, Jay D; Martín, Héctor García

    2017-04-05

    Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and (13)C Metabolic Flux Analysis. Moreover, it introduces the capability to use (13)C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale (13)C Metabolic Flux Analysis (2S-(13)C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it

  20. Final Report Coupling in silico microbial models with reactive transport models to predict the fate of contaminants in the subsurface.

    Energy Technology Data Exchange (ETDEWEB)

    Lovley, Derek R.

    2012-10-31

    This project successfully accomplished its goal of coupling genome-scale metabolic models with hydrological and geochemical models to predict the activity of subsurface microorganisms during uranium bioremediation. Furthermore, it was demonstrated how this modeling approach can be used to develop new strategies to optimize bioremediation. The approach of coupling genome-scale metabolic models with reactive transport modeling is now well enough established that it has been adopted by other DOE investigators studying uranium bioremediation. Furthermore, the basic principles developed during our studies will be applicable to much broader investigations of microbial activities, not only for other types of bioremediation, but microbial metabolism in diversity of environments. This approach has the potential to make an important contribution to predicting the impact of environmental perturbations on the cycling of carbon and other biogeochemical cycles.

  1. An age-structured population balance model for microbial dynamics

    Directory of Open Access Journals (Sweden)

    Duarte M.V.E.

    2003-01-01

    Full Text Available This work presents an age-structured population balance model (ASPBM for a bioprocess in a continuous stirred-tank fermentor. It relates the macroscopic properties and dynamic behavior of biomass to the operational parameters and microscopic properties of cells. Population dynamics is governed by two time- and age-dependent density functions for living and dead cells, accounting for the influence of substrate and dissolved oxygen concentrations on cell division, aging and death processes. The ASPBM described biomass and substrate oscillations in aerobic continuous cultures as experimentally observed. It is noteworthy that a small data set consisting of nonsegregated measurements was sufficient to adjust a complex segregated mathematical model.

  2. Kinetic model for microbial growth and desulphurisation with Enterobacter sp.

    Science.gov (United States)

    Liu, Long; Guo, Zhiguo; Lu, Jianjiang; Xu, Xiaolin

    2015-02-01

    Biodesulphurisation was investigated by using Enterobacter sp. D4, which can selectively desulphurise and convert dibenzothiophene into 2-hydroxybiphenyl (2-HBP). The experimental values of growth, substrate consumption and product generation were obtained at 95 % confidence level of the fitted values using three models: Hinshelwood equation, Luedeking-Piret and Luedeking-Piret-like equations. The average error values between experimental values and fitted values were less than 10 %. These kinetic models describe all the experimental data with good statistical parameters. The production of 2-HBP in Enterobacter sp. was by "coupled growth".

  3. Use of genome-scale microbial models for metabolic engineering

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

    2004-01-01

    network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction.......Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metabolic...

  4. Microbial growth curves: what the models tell us and what they cannot.

    Science.gov (United States)

    Peleg, Micha; Corradini, Maria G

    2011-12-01

    Most of the models of microbial growth in food are Empirical algebraic, of which the Gompertz model is the most notable, Rate equations, mostly variants of the Verhulst's logistic model, or Population Dynamics models, which can be deterministic and continuous or stochastic and discrete. The models of the first two kinds only address net growth and hence cannot account for cell mortality that can occur at any phase of the growth. Almost invariably, several alternative models of all three types can describe the same set of experimental growth data. This lack of uniqueness is by itself a reason to question any mechanistic interpretation of growth parameters obtained by curve fitting alone. As argued, all the variants of the Verhulst's model, including the Baranyi-Roberts model, are empirical phenomenological models in a rate equation form. None provides any mechanistic insight or has inherent advantage over the others. In principle, models of all three kinds can predict non-isothermal growth patterns from isothermal data. Thus a modeler should choose the simplest and most convenient model for this purpose. There is no reason to assume that the dependence of the "maximum specific growth rate" on temperature, pH, water activity, or other factors follows the original or modified versions of the Arrhenius model, as the success of Ratkowsky's square root model testifies. Most sigmoid isothermal growth curves require three adjustable parameters for their mathematical description and growth curves showing a peak at least four. Although frequently observed, there is no theoretical reason that these growth parameters should always rise and fall in unison in response to changes in external conditions. Thus quantifying the effect of an environmental factor on microbial growth require that all the growth parameters are addressed, not just the "maximum specific growth rate." Different methods to determine the "lag time" often yield different values, demonstrating that it is a

  5. Development of microbial-enzyme-mediated decomposition model parameters through steady-state and dynamic analyses

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Gangsheng [ORNL; Post, Wilfred M [ORNL; Mayes, Melanie [ORNL

    2013-01-01

    We developed a Microbial-ENzyme-mediated Decomposition (MEND) model, based on the Michaelis-Menten kinetics, that describes the dynamics of physically defined pools of soil organic matter (SOC). These include particulate, mineral-associated, dissolved organic matter (POC, MOC, and DOC, respectively), microbial biomass, and associated exoenzymes. The ranges and/or distributions of parameters were determined by both analytical steady-state and dynamic analyses with SOC data from the literature. We used an improved multi-objective parameter sensitivity analysis (MOPSA) to identify the most important parameters for the full model: maintenance of microbial biomass, turnover and synthesis of enzymes, and carbon use efficiency (CUE). The model predicted an increase of 2 C (baseline temperature =12 C) caused the pools of POC-Cellulose, MOC, and total SOC to increase with dynamic CUE and decrease with constant CUE, as indicated by the 50% confidence intervals. Regardless of dynamic or constant CUE, the pool sizes of POC, MOC, and total SOC varied from 8% to 8% under +2 C. The scenario analysis using a single parameter set indicates that higher temperature with dynamic CUE might result in greater net increases in both POC-Cellulose and MOC pools. Different dynamics of various SOC pools reflected the catalytic functions of specific enzymes targeting specific substrates and the interactions between microbes, enzymes, and SOC. With the feasible parameter values estimated in this study, models incorporating fundamental principles of microbial-enzyme dynamics can lead to simulation results qualitatively different from traditional models with fast/slow/passive pools.

  6. Modeling microbial degradation of propylene glycol: electron acceptors and their related redox conditions

    Science.gov (United States)

    Dathe, Annette; Fernandez, Perrine M.; Bloem, Esther; Meeussen, Johannes C. L.; French, Helen K.

    2014-05-01

    De-icing chemicals are applied in large amounts at airports during winter conditions to keep the runways and aircrafts ice-free. The commonly used propylene glycol (PG) is easily degradable by local microbial communities, but anoxic zones develop and soluble Fe+2 and Mn+2 ions can reach the groundwater. To enhance microbial induced remediation and reduce the release of iron and manganese, it was proposed to add NO3- together with PG. However, experiments conducted in the unsaturated zone at Gardermoen airport, Norway, revealed that manganese and iron were preferred over NO3- as electron acceptor [1]. The objectives of this study are to quantify mechanisms which control the order of reduction processes in an unsaturated sandy soil, and to test whether measured redox potentials can help to determine underlying biogeochemical reactions. We are modelling the microbial degradation of PG using Monod kinetics described for the chemical equilibrium tool ORCHESTRA [2], following an approach of [1]. The model is calibrated against gas measurements of CO2, NO2 and N2 released from batch experiments performed under controlled conditions. Fe+2 and Mn+2 were measured for the start and end of the experiment, as well as bulk resistivity, pH and electrical conductivity. With the calibrated model we are working towards a tool to quantify microbial induced redox reactions under different soil water saturations to account for seasonal water fluxes especially during snowmelt. [1] Schotanus, D., Meeussen, J.C.L., Lissner, H., van der Ploeg, M.J., Wehrer, M., Totsche, K.U., van der Zee, S.E.A.T.M., 2013. Transport and degradation of propylene glycol in the vadose zone: model development and sensitivity analysis. Environ Sci Pollut Res Int. [2] Meeussen, J.C.L., 2003. ORCHESTRA: An Object-Oriented Framework for Implementing Chemical Equilibrium Models. Environ. Sci. Technol. 37, 1175-1182.

  7. A model for microbial phosphorus cycling in bioturbated marine sediments

    DEFF Research Database (Denmark)

    Dale, Andrew W.; Boyle, R. A.; Lenton, Timothy M.

    2016-01-01

    A diagenetic model is used to simulate the diagenesis and burial of particulate organic carbon (Corg) and phosphorus (P) in marine sediments underlying anoxic versus oxic bottom waters. The latter are physically mixed by animals moving through the surface sediment (bioturbation) and ventilated by...

  8. Quantitative Modeling of Microbial Population Responses to Chronic Irradiation Combined with Other Stressors.

    Directory of Open Access Journals (Sweden)

    Igor Shuryak

    Full Text Available Microbial population responses to combined effects of chronic irradiation and other stressors (chemical contaminants, other sub-optimal conditions are important for ecosystem functioning and bioremediation in radionuclide-contaminated areas. Quantitative mathematical modeling can improve our understanding of these phenomena. To identify general patterns of microbial responses to multiple stressors in radioactive environments, we analyzed three data sets on: (1 bacteria isolated from soil contaminated by nuclear waste at the Hanford site (USA; (2 fungi isolated from the Chernobyl nuclear-power plant (Ukraine buildings after the accident; (3 yeast subjected to continuous γ-irradiation in the laboratory, where radiation dose rate and cell removal rate were independently varied. We applied generalized linear mixed-effects models to describe the first two data sets, whereas the third data set was amenable to mechanistic modeling using differential equations. Machine learning and information-theoretic approaches were used to select the best-supported formalism(s among biologically-plausible alternatives. Our analysis suggests the following: (1 Both radionuclides and co-occurring chemical contaminants (e.g. NO2 are important for explaining microbial responses to radioactive contamination. (2 Radionuclides may produce non-monotonic dose responses: stimulation of microbial growth at low concentrations vs. inhibition at higher ones. (3 The extinction-defining critical radiation dose rate is dramatically lowered by additional stressors. (4 Reproduction suppression by radiation can be more important for determining the critical dose rate, than radiation-induced cell mortality. In conclusion, the modeling approaches used here on three diverse data sets provide insight into explaining and predicting multi-stressor effects on microbial communities: (1 the most severe effects (e.g. extinction on microbial populations may occur when unfavorable environmental

  9. A microbial model of economic trading and comparative advantage.

    Science.gov (United States)

    Enyeart, Peter J; Simpson, Zachary B; Ellington, Andrew D

    2015-01-07

    The economic theory of comparative advantage postulates that beneficial trading relationships can be arrived at by two self-interested entities producing the same goods as long as they have opposing relative efficiencies in producing those goods. The theory predicts that upon entering trade, in order to maximize consumption both entities will specialize in producing the good they can produce at higher efficiency, that the weaker entity will specialize more completely than the stronger entity, and that both will be able to consume more goods as a result of trade than either would be able to alone. We extend this theory to the realm of unicellular organisms by developing mathematical models of genetic circuits that allow trading of a common good (specifically, signaling molecules) required for growth in bacteria in order to demonstrate comparative advantage interactions. In Conception 1, the experimenter controls production rates via exogenous inducers, allowing exploration of the parameter space of specialization. In Conception 2, the circuits self-regulate via feedback mechanisms. Our models indicate that these genetic circuits can demonstrate comparative advantage, and that cooperation in such a manner is particularly favored under stringent external conditions and when the cost of production is not overly high. Further work could involve implementing the models in living bacteria and searching for naturally occurring cooperative relationships between bacteria that conform to the principles of comparative advantage.

  10. Modeling Microbial Biogeochemistry from Terrestrial to Aquatic Ecosystems Using Trait-Based Approaches

    Science.gov (United States)

    King, E.; Molins, S.; Karaoz, U.; Johnson, J. N.; Bouskill, N.; Hug, L. A.; Thomas, B. C.; Castelle, C. J.; Beller, H. R.; Banfield, J. F.; Steefel, C. I.; Brodie, E.

    2014-12-01

    Currently, there is uncertainty in how climate or land-use-induced changes in hydrology and vegetation will affect subsurface carbon flux, the spatial and temporal distribution of flow and transport, biogeochemical cycling, and microbial metabolic activity. Here we focus on the initial development of a Genome-Enabled Watershed Simulation Capability (GEWaSC), which provides a predictive framework for understanding how genomic information stored in a subsurface microbiome affects biogeochemical watershed functioning, how watershed-scale processes affect microbial function, and how these interactions co-evolve. This multiscale framework builds on a hierarchical approach to multiscale modeling, which considers coupling between defined microscale and macroscale components of a system (e.g., a catchment being defined as macroscale and biogeofacies as microscale). Here, we report our progress in the development of a trait-based modeling approach within a reactive transport framework that simulates coupled guilds of microbes. Guild selection is driven by traits extracted from, and physiological properties inferred from, large-scale assembly of metagenome data. Meta-genomic, -transcriptomic and -proteomic information are also used to complement our existing biogeochemical reaction networks and contributes key reactions where biogeochemical analyses are unequivocal. Our approach models the rate of nutrient uptake and the thermodynamics of coupled electron donors and acceptors for a range of microbial metabolisms including heterotrophs and chemolitho(auto)trophs. Metabolism of exogenous substrates fuels catabolic and anabolic processes, with the proportion of energy used for each based upon dynamic intracellular and environmental conditions. In addition to biomass development, anabolism includes the production of key enzymes, such as nitrogenase for nitrogen fixation or exo-enzymes for the hydrolysis of extracellular polymers. This internal resource partitioning represents a

  11. Characterization and modelling of interspecies electron transfer mechanisms and microbial community dynamics of a syntrophic association

    DEFF Research Database (Denmark)

    Nagarajan, Harish; Embree, Mallory; Rotaru, Amelia-Elena

    2013-01-01

    Syntrophic associations are central to microbial communities and thus have a fundamental role in the global carbon cycle. Despite biochemical approaches describing the physiological activity of these communities, there has been a lack of a mechanistic understanding of the relationship between...... metallireducens and Geobacter sulfurreducens. Genome-scale modelling of direct interspecies electron transfer reveals insights into the energetics of electron transfer mechanisms. While G. sulfurreducens adapts to rapid syntrophic growth by changes at the genomic and transcriptomic level, G. metallireducens...

  12. A mechanistic model of microbial competition in the rhizosphere of wetland plants

    Science.gov (United States)

    Aslkhodapasand, F.; Mayer, K. U.; Neumann, R. B.

    2014-12-01

    Wetlands are the largest natural source of methane to the atmosphere. Although they cover only 4-6% of earth's surface, wetlands contribute 20-39% of global methane emissions. Hollow aerenchyma tissues inside the roots, stems and leaves of plants represent one of the most important methane emission pathways for wetlands. Up to 90% of the emitted methane can diffuse through these hollow tissues that directly connect the atmosphere to the anoxic soils where methane is generated. Thus, concentrations of methane surrounding plant roots directly impact the amount of methane emitted by wetlands. Methane concentrations are controlled by a variety of microbial processes occurring in the soil around the roots of plants (aka the rhizosphere). The rhizosphere is a microbial hotspot sustained by plant inputs of organic carbon and oxygen; plant roots exude excess organic carbon generated in photosynthesis into the rhizosphere and atmospheric oxygen diffuses down to the rhizosphere through the hollow aerenchyma tissues. This environment supports a variety of microbial communities that compete with each other for available carbon and oxygen, including methanogens, methanotrophs, and heterotrophs. Methanogens ferment organic carbon into methane, a reaction that is inhibited by oxygen; methanotrophs use oxygen to oxidize methane into carbon dioxide; and heterotrophs use oxygen to oxidize organic carbon into carbon dioxide. We are interested in understanding how competition between these communities alters methane concentrations and responds to variations in plant inputs. To this end, we have developed a mechanistic root-scale model that describes microbial competition for organic carbon and oxygen in the rhizosphere of wetland plants. Our results focus on variations in rates of methane production, methane oxidation, heterotrophic respiration, and diffusion of methane into plant roots as a result of changes in carbon and oxygen inputs. The study provides insight into how plant

  13. Incorporating Geochemical And Microbial Kinetics In Reactive Transport Models For Generation Of Acid Rock Drainage

    Science.gov (United States)

    Andre, B. J.; Rajaram, H.; Silverstein, J.

    2010-12-01

    Acid mine drainage, AMD, results from the oxidation of metal sulfide minerals (e.g. pyrite), producing ferrous iron and sulfuric acid. Acidophilic autotrophic bacteria such as Acidithiobacillus ferrooxidans and Leptospirillum ferrooxidans obtain energy by oxidizing ferrous iron back to ferric iron, using oxygen as the electron acceptor. Most existing models of AMD do not account for microbial kinetics or iron geochemistry rigorously. Instead they assume that oxygen limitation controls pyrite oxidation and thus focus on oxygen transport. These models have been successfully used for simulating conditions where oxygen availability is a limiting factor (e.g. source prevention by capping), but have not been shown to effectively model acid generation and effluent chemistry under a wider range of conditions. The key reactions, oxidation of pyrite and oxidation of ferrous iron, are both slow kinetic processes. Despite being extensively studied for the last thirty years, there is still not a consensus in the literature about the basic mechanisms, limiting factors or rate expressions for microbially enhanced oxidation of metal sulfides. An indirect leaching mechanism (chemical oxidation of pyrite by ferric iron to produce ferrous iron, with regeneration of ferric iron by microbial oxidation of ferrous iron) is used as the foundation of a conceptual model for microbially enhanced oxidation of pyrite. Using literature data, a rate expression for microbial consumption of ferrous iron is developed that accounts for oxygen, ferrous iron and pH limitation. Reaction rate expressions for oxidation of pyrite and chemical oxidation of ferrous iron are selected from the literature. A completely mixed stirred tank reactor (CSTR) model is implemented coupling the kinetic rate expressions, speciation calculations and flow. The model simulates generation of AMD and effluent chemistry that qualitatively agrees with column reactor and single rock experiments. A one dimensional reaction

  14. Insight into the Functionality of Microbial Exopolysaccharides by NMR Spectroscopy and Molecular Modeling.

    Science.gov (United States)

    Larsen, Flemming H; Engelsen, Søren B

    2015-01-01

    Microbial polysaccharides represent an important class of microbial polymers with diverse functions such as biofilm formation, thickening, and gelling properties as well as health-promoting properties. The broad range of exopolysaccharide (EPS) functionalities has sparked a renewed interest in this class of molecules. Chemical, enzymatic as well as genetic modifications by metabolic engineering can be used to create large numbers of analogous EPS variants with respect to EPS functionality. While this top-down approach is effective in finding new candidates for desired functionality, there seems to be a lack of the corresponding bottom-up approach. The molecular mechanisms of the desired functionalities can be established from Nuclear Magnetic Resonance (NMR) and molecular models and it is proposed that these models can be fed back into the biotechnology by using a quantitative structure-property approach. In this way it will be possible to tailor specific functionality within a given design space. This perspective will include two well-known commercial microbial EPS examples namely gellan and diutan and show how even a limited use of multiphase NMR and molecular modeling can increase the insight into their different properties, which are based on only minor structural differences.

  15. Microbial comparative pan-genomics using binomial mixture models

    Directory of Open Access Journals (Sweden)

    Ussery David W

    2009-08-01

    Full Text Available Abstract Background The size of the core- and pan-genome of bacterial species is a topic of increasing interest due to the growing number of sequenced prokaryote genomes, many from the same species. Attempts to estimate these quantities have been made, using regression methods or mixture models. We extend the latter approach by using statistical ideas developed for capture-recapture problems in ecology and epidemiology. Results We estimate core- and pan-genome sizes for 16 different bacterial species. The results reveal a complex dependency structure for most species, manifested as heterogeneous detection probabilities. Estimated pan-genome sizes range from small (around 2600 gene families in Buchnera aphidicola to large (around 43000 gene families in Escherichia coli. Results for Echerichia coli show that as more data become available, a larger diversity is estimated, indicating an extensive pool of rarely occurring genes in the population. Conclusion Analyzing pan-genomics data with binomial mixture models is a way to handle dependencies between genomes, which we find is always present. A bottleneck in the estimation procedure is the annotation of rarely occurring genes.

  16. Microbial comparative pan-genomics using binomial mixture models

    DEFF Research Database (Denmark)

    Ussery, David; Snipen, L; Almøy, T

    2009-01-01

    The size of the core- and pan-genome of bacterial species is a topic of increasing interest due to the growing number of sequenced prokaryote genomes, many from the same species. Attempts to estimate these quantities have been made, using regression methods or mixture models. We extend the latter...... approach by using statistical ideas developed for capture-recapture problems in ecology and epidemiology. RESULTS: We estimate core- and pan-genome sizes for 16 different bacterial species. The results reveal a complex dependency structure for most species, manifested as heterogeneous detection...... probabilities. Estimated pan-genome sizes range from small (around 2600 gene families) in Buchnera aphidicola to large (around 43000 gene families) in Escherichia coli. Results for Echerichia coli show that as more data become available, a larger diversity is estimated, indicating an extensive pool of rarely...

  17. The Impact of Consumer Phase Models in Microbial Risk Analysis

    DEFF Research Database (Denmark)

    Nauta, Maarten; Christensen, Bjarke Bak

    2011-01-01

    In quantitative microbiological risk assessment (QMRA), the consumer phase model (CPM) describes the part of the food chain between purchase of the food product at retail and exposure. Construction of a CPM is complicated by the large variation in consumer food handling practices and a limited...... availability of data. Therefore, several subjective (simplifying) assumptions have to be made when a CPM is constructed, but with a single CPM their impact on the QMRA results is unclear. We therefore compared the performance of eight published CPMs for Campylobacter in broiler meat in an example of a QMRA......, where all the CPMs were analyzed using one single input distribution of concentrations at retail, and the same dose-response relationship. It was found that, between CPMs, there may be a considerable difference in the estimated probability of illness per serving. However, the estimated relative risk...

  18. Dynamic relationships between microbial biomass, respiration, inorganic nutrients and enzyme activities: informing enzyme based decomposition models

    Directory of Open Access Journals (Sweden)

    Daryl L Moorhead

    2013-08-01

    Full Text Available We re-examined data from a recent litter decay study to determine if additional insights could be gained to inform decomposition modeling. Rinkes et al. (2013 conducted 14-day laboratory incubations of sugar maple (Acer saccharum or white oak (Quercus alba leaves, mixed with sand (0.4% organic C content or loam (4.1% organic C. They measured microbial biomass C, carbon dioxide efflux, soil ammonium, nitrate, and phosphate concentrations, and β-glucosidase (BG, β-N-acetyl-glucosaminidase (NAG, and acid phosphatase (AP activities on days 1, 3, and 14. Analyses of relationships among variables yielded different insights than original analyses of individual variables. For example, although respiration rates per g soil were higher for loam than sand, rates per g soil C were actually higher for sand than loam, and rates per g microbial C showed little difference between treatments. Microbial biomass C peaked on day 3 when biomass-specific activities of enzymes were lowest, suggesting uptake of litter C without extracellular hydrolysis. This result refuted a common model assumption that all enzyme production is constitutive and thus proportional to biomass, and/or indicated that part of litter decay is independent of enzyme activity. The length and angle of vectors defined by ratios of enzyme activities (BG/NAG versus BG/AP represent relative microbial investments in C (length, and N and P (angle acquiring enzymes. Shorter lengths on day 3 suggested low C limitation, whereas greater lengths on day 14 suggested an increase in C limitation with decay. The soils and litter in this study generally had stronger P limitation (angles > 45˚. Reductions in vector angles to < 45˚ for sand by day 14 suggested a shift to N limitation. These relational variables inform enzyme-based models, and are usually much less ambiguous when obtained from a single study in which measurements were made on the same samples than when extrapolated from separate studies.

  19. Heterogeneity Confounds Establishment of "a" Model Microbial Strain.

    Science.gov (United States)

    Keller, Nancy P

    2017-02-21

    Aspergillus fumigatus is a ubiquitous environmental mold and the leading cause of diverse human diseases ranging from allergenic bronchopulmonary aspergillosis (ABPA) to invasive pulmonary aspergillosis (IPA). Experimental investigations of the biology and virulence of this opportunistic pathogen have historically used a few type strains; however, it is increasingly observed with this fungus that heterogeneity among isolates potentially confounds the use of these reference isolates. Illustrating this point, Kowalski et al. (mBio 7:e01515-16, 2016, https://doi.org/10.1128/mBio.01515-16) demonstrated that variation in 16 environmental and clinical isolates of A. fumigatus correlated virulence with fitness in low oxygen, whereas Fuller et al. (mBio 7:e01517-16, 2016, https://doi.org/10.1128/mBio.01517-16) showed wide variation in light responses at a physiological and protein functionality level in 15 A. fumigatus isolates. In both studies, two commonly used type strains, Af293 and CEA10, displayed significant differences in physiological responses to abiotic stimuli and virulence in a murine model of IPA.

  20. Extrapolation of Urn Models via Poissonization: Accurate Measurements of the Microbial Unknown

    CERN Document Server

    Lladser, Manuel; Reeder, Jens; 10.1371/journal.pone.0021105

    2011-01-01

    The availability of high-throughput parallel methods for sequencing microbial communities is increasing our knowledge of the microbial world at an unprecedented rate. Though most attention has focused on determining lower-bounds on the alpha-diversity i.e. the total number of different species present in the environment, tight bounds on this quantity may be highly uncertain because a small fraction of the environment could be composed of a vast number of different species. To better assess what remains unknown, we propose instead to predict the fraction of the environment that belongs to unsampled classes. Modeling samples as draws with replacement of colored balls from an urn with an unknown composition, and under the sole assumption that there are still undiscovered species, we show that conditionally unbiased predictors and exact prediction intervals (of constant length in logarithmic scale) are possible for the fraction of the environment that belongs to unsampled classes. Our predictions are based on a P...

  1. Soil functional operating range linked to microbial biodiversity and community composition using denitrifiers as model guild.

    Directory of Open Access Journals (Sweden)

    Sara Hallin

    Full Text Available Soil microorganisms are key players in biogeochemical cycles. Yet, there is no consistent view on the significance of microbial biodiversity for soil ecosystem functioning. According to the insurance hypothesis, declines in ecosystem functioning due to reduced biodiversity are more likely to occur under fluctuating, extreme or rapidly changing environmental conditions. Here, we compare the functional operating range, a new concept defined as the complete range of environmental conditions under which soil microbial communities are able to maintain their functions, between four naturally assembled soil communities from a long-term fertilization experiment. A functional trait approach was adopted with denitrifiers involved in nitrogen cycling as our model soil community. Using short-term temperature and salt gradients, we show that the functional operating range was broader and process rates were higher when the soil community was phylogenetically more diverse. However, key bacterial genotypes played an important role for maintaining denitrification as an ecosystem functioning under certain conditions.

  2. Modelling highly variable environmental factors to assess potential microbial respiration in complex floodplain landscapes

    Science.gov (United States)

    Tritthart, Michael; Welti, Nina; Bondar-Kunze, Elisabeth; Pinay, Gilles; Hein, Thomas; Habersack, Helmut

    2011-01-01

    The hydrological exchange conditions strongly determine the biogeochemical dynamics in river systems. More specifically, the connectivity of surface waters between main channels and floodplains is directly controlling the delivery of organic matter and nutrients into the floodplains, where biogeochemical processes recycle them with high rates of activity. Hence, an in-depth understanding of the connectivity patterns between main channel and floodplains is important for the modelling of potential gas emissions in floodplain landscapes. A modelling framework that combines steady-state hydrodynamic simulations with long-term discharge hydrographs was developed to calculate water depths as well as statistical probabilities and event durations for every node of a computation mesh being connected to the main river. The modelling framework was applied to two study sites in the floodplains of the Austrian Danube River, East of Vienna. Validation of modelled flood events showed good agreement with gauge readings. Together with measured sediment properties, results of the validated connectivity model were used as basis for a predictive model yielding patterns of potential microbial respiration based on the best fit between characteristics of a number of sampling sites and the corresponding modelled parameters. Hot spots of potential microbial respiration were found in areas of lower connectivity if connected during higher discharges and areas of high water depths. PMID:27667961

  3. Comparing uncertainty resulting from two-step and global regression procedures applied to microbial growth models.

    Science.gov (United States)

    Martino, K G; Marks, B P

    2007-12-01

    Two different microbial modeling procedures were compared and validated against independent data for Listeria monocytogenes growth. The most generally used method is two consecutive regressions: growth parameters are estimated from a primary regression of microbial counts, and a secondary regression relates the growth parameters to experimental conditions. A global regression is an alternative method in which the primary and secondary models are combined, giving a direct relationship between experimental factors and microbial counts. The Gompertz equation was the primary model, and a response surface model was the secondary model. Independent data from meat and poultry products were used to validate the modeling procedures. The global regression yielded the lower standard errors of calibration, 0.95 log CFU/ml for aerobic and 1.21 log CFU/ml for anaerobic conditions. The two-step procedure yielded errors of 1.35 log CFU/ml for aerobic and 1.62 log CFU/ ml for anaerobic conditions. For food products, the global regression was more robust than the two-step procedure for 65% of the cases studied. The robustness index for the global regression ranged from 0.27 (performed better than expected) to 2.60. For the two-step method, the robustness index ranged from 0.42 to 3.88. The predictions were overestimated (fail safe) in more than 50% of the cases using the global regression and in more than 70% of the cases using the two-step regression. Overall, the global regression performed better than the two-step procedure for this specific application.

  4. Mathematical model for microbial fuel cells with anodic biofilms and anaerobic digestion.

    Science.gov (United States)

    Picioreanu, C; van Loosdrecht, M C M; Katuri, K P; Scott, K; Head, I M

    2008-01-01

    This study describes the integration of IWA's anaerobic digestion model (ADM1) within a computational model of microbial fuel cells (MFCs). Several populations of methanogenic and electroactive microorganisms coexist suspended in the anolyte and in the biofilm attached to the anode. A number of biological, chemical and electrochemical reactions occur in the bulk liquid, in the biofilm and at the electrode surface, involving glucose, organic acids, H2 and redox mediators. Model output includes the evolution in time of important measurable MFC parameters (current production, consumption of substrates, suspended and attached biomass growth). Two- and three-dimensional model simulations reveal the importance of current and biomass heterogeneous distribution over the planar anode surface. Voltage- and power-current characteristics can be calculated at different moments in time to evaluate the limiting regime in which the MFC operates. Finally, model simulations are compared with experimental results showing that, in a batch MFC, smaller electrical resistance of the circuit leads to selection of electroactive bacteria. Higher coulombic yields are so obtained because electrons from substrate are transferred to anode rather than following the methanogenesis pathway. In addition to higher currents, faster COD consumption rates are so achieved. The potential of this general modelling framework is in the understanding and design of more complex cases of wastewater-fed microbial fuel cells.

  5. Mechanistic modeling of microbial interactions at pore to profile scale resolve methane emission dynamics from permafrost soil

    Science.gov (United States)

    Ebrahimi, Ali; Or, Dani

    2017-05-01

    The sensitivity of polar regions to raising global temperatures is reflected in rapidly changing hydrological processes associated with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and stimulation of other soil-borne greenhouse gas emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and other environmental factors. Soil structural elements such as aggregates and layering affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hot spots). We developed a mechanistic individual-based model to quantify microbial activity dynamics in soil pore networks considering transport processes and enzymatic activity associated with methane production in soil. The model was upscaled from single aggregates to the soil profile where freezing/thawing provides macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged profile) for resolving methane production and oxidation rates. Methane transport pathways by diffusion and ebullition of bubbles vary with hydration dynamics. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability and enzyme activity) on long-term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

  6. A predictive model for microbial counts on beaches where intertidal sand is the primary source.

    Science.gov (United States)

    Feng, Zhixuan; Reniers, Ad; Haus, Brian K; Solo-Gabriele, Helena M; Wang, John D; Fleming, Lora E

    2015-05-15

    Human health protection at recreational beaches requires accurate and timely information on microbiological conditions to issue advisories. The objective of this study was to develop a new numerical mass balance model for enterococci levels on nonpoint source beaches. The significant advantage of this model is its easy implementation, and it provides a detailed description of the cross-shore distribution of enterococci that is useful for beach management purposes. The performance of the balance model was evaluated by comparing predicted exceedances of a beach advisory threshold value to field data, and to a traditional regression model. Both the balance model and regression equation predicted approximately 70% the advisories correctly at the knee depth and over 90% at the waist depth. The balance model has the advantage over the regression equation in its ability to simulate spatiotemporal variations of microbial levels, and it is recommended for making more informed management decisions.

  7. Stoichiometric modelling of assimilatory and dissimilatory biomass utilisation in a microbial community

    Science.gov (United States)

    Hunt, Kristopher A.; Jennings, Ryan deM.; Inskeep, William P.; Carlson, Ross P.

    2017-01-01

    Summary Assimilatory and dissimilatory utilisation of autotroph biomass by heterotrophs is a fundamental mechanism for the transfer of nutrients and energy across trophic levels. Metagenome data from a tractable, thermoacidophilic microbial community in Yellowstone National Park was used to build an in silico model to study heterotrophic utilisation of autotroph biomass using elementary flux mode analysis and flux balance analysis. Assimilatory and dissimilatory biomass utilisation was investigated using 29 forms of biomass-derived dissolved organic carbon (DOC) including individual monomer pools, individual macromolecular pools and aggregate biomass. The simulations identified ecologically competitive strategies for utilizing DOC under conditions of varying electron donor, electron acceptor or enzyme limitation. The simulated growth environment affected which form of DOC was the most competitive use of nutrients; for instance, oxygen limitation favoured utilisation of less reduced and fermentable DOC while carbon-limited environments favoured more reduced DOC. Additionally, metabolism was studied considering two encompassing metabolic strategies: simultaneous versus sequential use of DOC. Results of this study bound the transfer of nutrients and energy through microbial food webs, providing a quantitative foundation relevant to most microbial ecosystems. PMID:27387069

  8. [Macrokinetic basis for the model of microbial growth in a limited volume under constant conditions with a single leading substrate].

    Science.gov (United States)

    Gendugov, V M; Glazunov, G P

    2013-01-01

    Within the framework of the macrokinetic approach and continuum and chemical/biochemical gross reaction conceptions, an equation describing the complete dynamics of microbial growth and decline as function of a variable concentration of the leading substrate was deduced. This equation allows us to distinguish quantitatively and qualitatively the stages of microbial growth and the intervals of microbial tolerance to the initial concentration of the leading substrate. Adequacy of the model was confirmed by comparison with experimental dynamics of aerobic microorganisms in the samples of groundwater collected from a region polluted with uranium.

  9. Modelling the liquid-water vein system within polar ice sheets as a potential microbial habitat

    Science.gov (United States)

    Dani, K. G. Srikanta; Mader, Heidy M.; Wolff, Eric W.; Wadham, Jemma L.

    2012-06-01

    Based on the fundamental and distinctive physical properties of polycrystalline ice Ih, the chemical and temperature profiles within the polar ice sheets, and the observed selective partitioning of bacteria into liquid water filled veins in the ice, we consider the possibility that microbial life could survive and be sustained within glacial systems. Here, we present a set of modelled vertical profiles of vein diameter, vein chemical concentration, and vein water volume variability across a range of polar ice sheets using their ice core chemical profiles. A sensitivity analysis of VeinsInIce1.0, the numerical model used in this study shows that the ice grain size and the local borehole temperature are the most significant factors that influence the intergranular liquid vein size and the amount of freeze-concentrated impurities partitioned into the veins respectively. Model results estimate the concentration and characteristics of the chemical broth in the veins to be a potential extremophilic microbial medium. The vein sizes are estimated to vary between 0.3 μm to 8 μm across the vertical length of many polar ice sheets and they may contain up to 2 μL of liquid water per litre of solid ice. The results suggest that these veins in polar ice sheets could accommodate populations of psychrophilic and hyperacidophilic ultra-small bacteria and in some regions even support the habitation of unicellular eukaryotes. This highlights the importance of understanding the potential impact of englacial microbial metabolism on polar ice core chemical profiles and provides a model for similar extreme habitats elsewhere in the universe.

  10. Modeling microbial reaction rates in a submarine hydrothermal vent chimney wall

    Science.gov (United States)

    LaRowe, Douglas E.; Dale, Andrew W.; Aguilera, David R.; L'Heureux, Ivan; Amend, Jan P.; Regnier, Pierre

    2014-01-01

    The fluids emanating from active submarine hydrothermal vent chimneys provide a window into subseafloor processes and, through mixing with seawater, are responsible for steep thermal and compositional gradients that provide the energetic basis for diverse biological communities. Although several models have been developed to better understand the dynamic interplay of seawater, hydrothermal fluid, minerals and microorganisms inside chimney walls, none provide a fully integrated approach to quantifying the biogeochemistry of these hydrothermal systems. In an effort to remedy this, a fully coupled biogeochemical reaction-transport model of a hydrothermal vent chimney has been developed that explicitly quantifies the rates of microbial catalysis while taking into account geochemical processes such as fluid flow, solute transport and oxidation-reduction reactions associated with fluid mixing as a function of temperature. The metabolisms included in the reaction network are methanogenesis, aerobic oxidation of hydrogen, sulfide and methane and sulfate reduction by hydrogen and methane. Model results indicate that microbial catalysis is generally fastest in the hottest habitable portion of the vent chimney (77-102 °C), and methane and sulfide oxidation peak near the seawater-side of the chimney. The fastest metabolisms are aerobic oxidation of H2 and sulfide and reduction of sulfate by H2 with maximum rates of 140, 900 and 800 pmol cm-3 d-1, respectively. The maximum rate of hydrogenotrophic methanogenesis is just under 0.03 pmol cm-3 d-1, the slowest of the metabolisms considered. Due to thermodynamic inhibition, there is no anaerobic oxidation of methane by sulfate (AOM). These simulations are consistent with vent chimney metabolic activity inferred from phylogenetic data reported in the literature. The model developed here provides a quantitative approach to describing the rates of biogeochemical transformations in hydrothermal systems and can be used to constrain the

  11. Mathematical modeling as a tool to assess microbial community responses to CO2 injection

    Science.gov (United States)

    Vilcaez, J.

    2014-12-01

    The issue of subsurface microbial community responses to the injection of CO2 has great importance not only from a risk assessment point of view but also from the perspective of CO2 recycling to CH4. In this sense, the objective of this study is to develop mathematical models to make a quantitative description of the responses of subsurface indigenous microbial communities to the injection of CO2. For this end, TOUGHREACTV1.2 reactive transport simulator with its module ECO2N is used as the modeling framework. The targeted microbial community is composed of fermentative bacteria (Organic matter → Acetate & H2), acetotrophic methanogens (Acetate → Methane & CO2), acetotrophic Sulfate Reducing Bacteria (SRB) (Acetate → H2S & CO2), hydrogenotrophic methanogens (H2 & CO2 → CH4), and hydrogenotrophic SRB (H2 → H2S). Due to the multiple hydrogeological, geochemical and microbiological factors intervening in both the response of subsurface microbial communities to the injection of CO2 and the chemical and physical fate of CO2 itself, at this stage simulations have been performed in batch mode. That means numerical simulations aimed to track changes in CO2 saturation levels, pH, and concentrations of mineral and aqueous phase species over time at selected initial conditions. Numerical simulation results indicate that the activity of microbes associated with methanogenic processes in geological storage sites of CO2 is governed by the level of CO2 saturation in the pore space as well as by the presence of pH buffering minerals such as calcite. With calcite in the mineral phase attenuating drops in pH below inhibitory levels, for instance it is shown that acetotrophic and hydrogenotrophic SRB outcompete acetotrophic and hydrogenotrophic methanogens for acetate and H2, respectively. During the initial stages of the reaction when the pH level is lowest, the higher tolerance of hydrogenotrophic methanogens to acidic pH levels is reflected by a preferential formation of

  12. Modeling the formation of soluble microbial products (SMP) in drinking water biofiltration

    Institute of Scientific and Technical Information of China (English)

    Yu Xin; Ye Lin; Wei Gu

    2008-01-01

    Both a theoretical and an empirical model were developed for predicting the formation of soluble microbial products (SMP) during drinking water biofiltration. Four pilot-scale biofilters with ceramsite as the medium were fed with different acetate loadings for the determination of SMP formation. Using numerically simulated and measured parameters, the theoretical model was developed according to the substrate and biomass balance. The results of this model matched the measured data better for higher SMP formation but did not fit well when SMP formation was lower. In order to better simulate the reality and overcome the difficulties of measuring the kinetic parameters, a simpler empirical model was also developed. In this model, SMP formation was expressed as a function of fed organic loadings and the depth of the medium, and a much better fit was obtained.

  13. Modeling the formation of soluble microbial products (SMP in drinking water biofiltration

    Directory of Open Access Journals (Sweden)

    Xin YU

    2008-09-01

    Full Text Available Both a theoretical and an empirical model were developed for predicting the formation of soluble microbial products (SMP during drinking water biofiltration. Four pilot-scale biofilters with ceramsite as the medium were fed with different acetate loadings for the determination of SMP formation. Using numerically simulated and measured parameters, the theoretical model was developed according to the substrate and biomass balance. The results of this model matched the measured data better for higher SMP formation but did not fit well when SMP formation was lower. In order to better simulate the reality and overcome the difficulties of measuring the kinetic parameters, a simpler empirical model was also developed. In this model, SMP formation was expressed as a function of fed organic loadings and the depth of the medium, and a much better fit was obtained.

  14. Modeling the kinetics of microbial degradation of deicing chemicals in porous media under flow conditions.

    Science.gov (United States)

    Wehrer, Markus; Jaesche, Philipp; Totsche, Kai Uwe

    2012-09-01

    A quantitative knowledge of the fate of deicing chemicals in the subsurface can be provided by joint analysis of lab experiments with numerical simulation models. In the present study, published experimental data of microbial degradation of the deicing chemical propylene glycol (PG) under flow conditions in soil columns were simulated inversely to receive the parameters of degradation. We evaluated different scenarios of an advection-dispersion model including different terms for degradation, such as zero order, first order and inclusion of a growing and decaying biomass for their ability to explain the data. The general break-through behavior of propylene glycol in soil columns can be simulated well using a coupled model of solute transport and degradation with growth and decay of biomass. The susceptibility of the model to non-unique solutions was investigated using systematical forward and inverse simulations. We found that the model tends to equifinal solutions under certain conditions.

  15. Microbial production of polyhydroxybutyrate with tailor-made properties: an integrated modelling approach and experimental validation.

    Science.gov (United States)

    Penloglou, Giannis; Chatzidoukas, Christos; Kiparissides, Costas

    2012-01-01

    The microbial production of polyhydroxybutyrate (PHB) is a complex process in which the final quantity and quality of the PHB depend on a large number of process operating variables. Consequently, the design and optimal dynamic operation of a microbial process for the efficient production of PHB with tailor-made molecular properties is an extremely interesting problem. The present study investigates how key process operating variables (i.e., nutritional and aeration conditions) affect the biomass production rate and the PHB accumulation in the cells and its associated molecular weight distribution. A combined metabolic/polymerization/macroscopic modelling approach, relating the process performance and product quality with the process variables, was developed and validated using an extensive series of experiments and measurements. The model predicts the dynamic evolution of the biomass growth, the polymer accumulation, the consumption of carbon and nitrogen sources and the average molecular weights of the PHB in a bioreactor, under batch and fed-batch operating conditions. The proposed integrated model was used for the model-based optimization of the production of PHB with tailor-made molecular properties in Azohydromonas lata bacteria. The process optimization led to a high intracellular PHB accumulation (up to 95% g of PHB per g of DCW) and the production of different grades (i.e., different molecular weight distributions) of PHB.

  16. SHIMMER (1.0: a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems

    Directory of Open Access Journals (Sweden)

    J. A. Bradley

    2015-08-01

    Full Text Available SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response is a new numerical modelling framework which is developed as part of an interdisciplinary, iterative, model-data based approach fully integrating fieldwork and laboratory experiments with model development, testing, and application. SHIMMER is designed to simulate the establishment of microbial biomass and associated biogeochemical cycling during the initial stages of ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers. The model mechanistically describes and predicts transformations in carbon, nitrogen and phosphorus through aggregated components of the microbial community as a set of coupled ordinary differential equations. The rationale for development of the model arises from decades of empirical observation on the initial stages of soil development in glacier forefields. SHIMMER enables a quantitative and process focussed approach to synthesising the existing empirical data and advancing understanding of microbial and biogeochemical dynamics. Here, we provide a detailed description of SHIMMER. The performance of SHIMMER is then tested in two case studies using published data from the Damma Glacier forefield in Switzerland and the Athabasca Glacier in Canada. In addition, a sensitivity analysis helps identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass, and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Simulation results indicate that primary production is responsible for the initial build-up of substrate that

  17. SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems

    Science.gov (United States)

    Bradley, J. A.; Anesio, A. M.; Singarayer, J. S.; Heath, M. R.; Arndt, S.

    2015-08-01

    SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework which is developed as part of an interdisciplinary, iterative, model-data based approach fully integrating fieldwork and laboratory experiments with model development, testing, and application. SHIMMER is designed to simulate the establishment of microbial biomass and associated biogeochemical cycling during the initial stages of ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The model mechanistically describes and predicts transformations in carbon, nitrogen and phosphorus through aggregated components of the microbial community as a set of coupled ordinary differential equations. The rationale for development of the model arises from decades of empirical observation on the initial stages of soil development in glacier forefields. SHIMMER enables a quantitative and process focussed approach to synthesising the existing empirical data and advancing understanding of microbial and biogeochemical dynamics. Here, we provide a detailed description of SHIMMER. The performance of SHIMMER is then tested in two case studies using published data from the Damma Glacier forefield in Switzerland and the Athabasca Glacier in Canada. In addition, a sensitivity analysis helps identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass, and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Simulation results indicate that primary production is responsible for the initial build-up of substrate that subsequently

  18. Modeling of decomposition activity and priming effect in soil using the versatile index of microbial physiological state

    Science.gov (United States)

    Blagodatskiy, Sergey

    2015-04-01

    The implementation of microbial biomass in soil organic matter (SOM) models is still unresolved issue. The approaches using explicit description of microbial biomass (decomposer) interaction with SOM usually cannot be easily verified by means of experimental estimating of total microbial biomass dynamics. Standard experimental methods, such as fumigation extraction or direct microscopic count, does not represent microbial activity (Blagodatskaya and Kuzyakov, 2013), which is essential for the control of decomposition rate. More advanced approaches, explicitly simulating intracellular metabolic activity (Resat et al., 2012) and e.g. production and turnover of extracellular enzymes (Lawrence et al., 2009) are prohibitively complex for the field and larger scales, which are most often under demand for SOM modelling. One possible parsimonious solution is an application of index of microbial physiological state (r), which describes the adaptive variation of the cell composition and metabolic activity by one variable (Panikov, 1995). This variable (r) can reflect the microbial response to the availability of carbon and nitrogen and shift of microbial biomass between active and dormant state (Blagodatsky and Richter, 1998), but also can be used for the description of the effect of external factors, such as temperature and moisture, on microbial activity. This approach is extremely useful for the description of priming effect (Blagodatsky et al., 2010) and the influence of substrate availability and external factors on the size and dynamics of priming. Distinguishing of these two types of driving forces for priming is crucial for modelling of SOM dynamics and steady-state stocks of different SOM pools. I will present the analysis of model response on combination of limiting factors presented as functions controlling the change of microbial physiological state and size of priming effect. Alternatively, the direct effect of the same factors on decomposition rate and priming

  19. Development of a competition model for microbial growth in mixed culture.

    Science.gov (United States)

    Fujikawa, Hiroshi; Munakata, Kanako; Sakha, Mohammad Z

    2014-01-01

    A novel competition model for describing bacterial growth in mixed culture was developed in this study. Several model candidates were made with our logistic growth model that precisely describes the growth of a monoculture of bacteria. These candidates were then evaluated for the usefulness in describing growth of two competing species in mixed culture using Staphylococcus aureus, Escherichia coli, and Salmonella. Bacterial cells of two species grew at initial doses of 10(3), 10(4), and 10(5) CFU/g at 28ºC. Among the candidates, a model where the Lotka-Volterra model, a general competition model in ecology, was incorporated as a new term in our growth model was the best for describing all types of growth of two competitors in mixed culture. Moreover, the values for the competition coefficient in the model were stable at various combinations of the initial populations of the species. The Baranyi model could also successfully describe the above types of growth in mixed culture when it was coupled with the Gimenez and Dalgaard model. However, the values for the competition coefficients in the competition model varied with the conditions. The present study suggested that our model could be a basic model for describing microbial competition.

  20. Kinetics of microbial degradation of deicing chemicals in percolated porous media - the modeling perspective

    Science.gov (United States)

    Wehrer, Markus; Lissner, Heidi; Totsche, Kai

    2013-04-01

    A quantitative knowledge of the fate of deicing chemicals in the subsurface can be provided by analysis of laboratory and field experiments with numerical simulation models. In the present study, experimental data of microbial degradation of the deicing chemical propylene glycol (PG) under flow conditions in soil columns and field lysimeters were simulated to analyze the process conditions of degradation and to obtain the according parameters. Results from the column experiment were evaluated applying different scenarios of an advection-dispersion model using HYDRUS-1D. To reconstruct the data, different competing degradation models were included, i.e., zero order, first order and inclusion of a growing and decaying biomass. The general breakthrough behavior of propylene glycol in soil columns can be simulated well using a coupled model of solute transport and degradation with growth and decay of biomass. The susceptibility of the model to non-unique solutions was investigated using systematical forward and inverse simulations. We found that the model tends to equifinal solutions under certain conditions. Complex experimental boundary conditions can help to avoid this. Under field conditions, the situation is far more complex than in the laboratory. Studying the fate of PG with undisturbed lysimeters we found that aerobic and anaerobic degradation occurs simultaneously. We attribute this to the physical structure and the aggregated nature of the undisturbed soil material . This results in the presence of spatially disjoint oxidative and reductive regions of microbial activity and requires, but is not fully reflected by a dual porosity model. Currently, the numerical simulation of this system is in progress, considering several flow and transport models. A stochastic global search algorithm (DREAM-ZS) is used in conjuction with HYDRUS-1D to avoid local minima in the inverse simulations. The study shows the current limitations and potentials of modeling degradation

  1. Microbial enhanced oil recovery—a modeling study of the potential of spore-forming bacteria

    DEFF Research Database (Denmark)

    Nielsen, Sidsel Marie; Nesterov, Igor; Shapiro, Alexander

    2016-01-01

    Microbial enhanced oil recovery (MEOR) utilizes microbes for enhancing the recovery by several mechanisms, among which the most studied are the following: (1) reduction of oil-water interfacial tension (IFT) by the produced biosurfactant and (2) selective plugging by microbes and metabolic products...... is modification of the relative permeabilities by decreasing the interfacial tension. Attachment of bacteria reduces the pore space available for flow, i.e., the effective porosity and permeability. Clogging of specific areas may occur. An extensive study of the MEOR on the basis of the developed model has...

  2. Characterization of agarose as immobilization matrix model for a microbial biosensor

    Directory of Open Access Journals (Sweden)

    Pernetti Mimma

    2003-01-01

    Full Text Available Microbial biosensors are promising tools for the detection of specific substances in different fields, such as environmental, biomedical, food or agricultural. They allow rapid measurements, no need for complex sample preparation or specialized personnel and easy handling. In order to enhance the managing, miniaturization and stability of the biosensor and to prevent cell leaching, bacteria immobilization is desirable. A systematic characterization procedure to choose a suitable immobilization method and matrix, was proposed in this study. Physical properties, storage stability mass transport phenomena and biocompatibility were evaluated, employing agarose as the model matrix. Preliminary essays with bioluminescent bacteria detecting Tributyltin were also carried out.

  3. Microbial-mediated method for metal oxide nanoparticle formation

    Energy Technology Data Exchange (ETDEWEB)

    Rondinone, Adam J.; Moon, Ji Won; Love, Lonnie J.; Yeary, Lucas W.; Phelps, Tommy J.

    2015-09-08

    The invention is directed to a method for producing metal oxide nanoparticles, the method comprising: (i) subjecting a combination of reaction components to conditions conducive to microbial-mediated formation of metal oxide nanoparticles, wherein said combination of reaction components comprise: metal-reducing microbes, a culture medium suitable for sustaining said metal-reducing microbes, an effective concentration of one or more surfactants, a reducible metal oxide component containing one or more reducible metal species, and one or more electron donors that provide donatable electrons to said metal-reducing microbes during consumption of the electron donor by said metal-reducing microbes; and (ii) isolating said metal oxide nanoparticles, which contain a reduced form of said reducible metal oxide component. The invention is also directed to metal oxide nanoparticle compositions produced by the inventive method.

  4. Development of Linear Irreversible Thermodynamic Model for Oxidation Reduction Potential in Environmental Microbial System

    Science.gov (United States)

    Cheng, Hong-Bang; Kumar, Mathava; Lin, Jih-Gaw

    2007-01-01

    Nernst equation has been directly used to formulate the oxidation reduction potential (ORP) of reversible thermodynamic conditions but applied to irreversible conditions after several assumptions and/or modifications. However, the assumptions are sometimes inappropriate in the quantification of ORP in nonequilibrium system. We propose a linear nonequilibrium thermodynamic model, called microbial related reduction and oxidation reaction (MIRROR Model No. 1) for the interpretation of ORP in biological process. The ORP was related to the affinities of catabolism and anabolism. The energy expenditure of catabolism and anabolism was directly proportional to overpotential (η), straight coefficient of electrode (LEE), and degree of coupling between catabolism and ORP electrode, respectively. Finally, the limitations of MIRROR Model No. 1 were discussed for expanding the applicability of the model. PMID:17496027

  5. Predictive microbiology models vs. modeling microbial growth within Listeria monocytogenes risk assessment: what parameters matter and why.

    Science.gov (United States)

    Pouillot, Régis; Lubran, Meryl B

    2011-06-01

    Predictive microbiology models are essential tools to model bacterial growth in quantitative microbial risk assessments. Various predictive microbiology models and sets of parameters are available: it is of interest to understand the consequences of the choice of the growth model on the risk assessment outputs. Thus, an exercise was conducted to explore the impact of the use of several published models to predict Listeria monocytogenes growth during food storage in a product that permits growth. Results underline a gap between the most studied factors in predictive microbiology modeling (lag, growth rate) and the most influential parameters on the estimated risk of listeriosis in this scenario (maximum population density, bacterial competition). The mathematical properties of an exponential dose-response model for Listeria accounts for the fact that the mean number of bacteria per serving and, as a consequence, the highest achievable concentrations in the product under study, has a strong influence on the estimated expected number of listeriosis cases in this context.

  6. Comparative characterization of the microbial diversities of an artificial microbialite model and a natural stromatolite.

    Science.gov (United States)

    Havemann, Stephanie A; Foster, Jamie S

    2008-12-01

    Microbialites are organosedimentary structures that result from the trapping, binding, and lithification of sediments by microbial mat communities. In this study we developed a model artificial microbialite system derived from natural stromatolites, a type of microbialite, collected from Exuma Sound, Bahamas. We demonstrated that the morphology of the artificial microbialite was consistent with that of the natural system in that there was a multilayer community with a pronounced biofilm on the surface, a concentrated layer of filamentous cyanobacteria in the top 5 mm, and a lithified layer of fused oolitic sand grains in the subsurface. The fused grain layer was comprised predominantly of the calcium carbonate polymorph aragonite, which corresponded to the composition of the Bahamian stromatolites. The microbial diversity of the artificial microbialites and that of natural stromatolites were also compared using automated ribosomal intergenic spacer analysis (ARISA) and 16S rRNA gene sequencing. The ARISA profiling indicated that the Shannon indices of the two communities were comparable and that the overall diversity was not significantly lower in the artificial microbialite model. Bacterial clone libraries generated from each of the three artificial microbialite layers and natural stromatolites indicated that the cyanobacterial and crust layers most closely resembled the ecotypes detected in the natural stromatolites and were dominated by Proteobacteria and Cyanobacteria. We propose that such model artificial microbialites can serve as experimental analogues for natural stromatolites.

  7. Framework for microbial food-safety risk assessments amenable to Bayesian modeling.

    Science.gov (United States)

    Williams, Michael S; Ebel, Eric D; Vose, David

    2011-04-01

    Regulatory agencies often perform microbial risk assessments to evaluate the change in the number of human illnesses as the result of a new policy that reduces the level of contamination in the food supply. These agencies generally have regulatory authority over the production and retail sectors of the farm-to-table continuum. Any predicted change in contamination that results from new policy that regulates production practices occurs many steps prior to consumption of the product. This study proposes a framework for conducting microbial food-safety risk assessments; this framework can be used to quantitatively assess the annual effects of national regulatory policies. Advantages of the framework are that estimates of human illnesses are consistent with national disease surveillance data (which are usually summarized on an annual basis) and some of the modeling steps that occur between production and consumption can be collapsed or eliminated. The framework leads to probabilistic models that include uncertainty and variability in critical input parameters; these models can be solved using a number of different Bayesian methods. The Bayesian synthesis method performs well for this application and generates posterior distributions of parameters that are relevant to assessing the effect of implementing a new policy. An example, based on Campylobacter and chicken, estimates the annual number of illnesses avoided by a hypothetical policy; this output could be used to assess the economic benefits of a new policy. Empirical validation of the policy effect is also examined by estimating the annual change in the numbers of illnesses observed via disease surveillance systems.

  8. A thermodynamically-based model for predicting microbial growth and community composition coupled to system geochemistry: Application to uranium bioreduction.

    Science.gov (United States)

    Istok, J D; Park, M; Michalsen, M; Spain, A M; Krumholz, L R; Liu, C; McKinley, J; Long, P; Roden, E; Peacock, A D; Baldwin, B

    2010-03-01

    'Bioimmobilization' of redox-sensitive heavy metals and radionuclides is being investigated as a way to remediate contaminated groundwater and sediments. In one approach, growth-limiting substrates are added to the subsurface to stimulate the activity of targeted groups of indigenous microorganisms and create conditions favorable for the microbially-mediated reductive precipitation ('bioreduction') of targeted contaminants. We present a theoretical framework for modeling this process that modifies conventional geochemical reaction path modeling to include thermodynamic descriptions for microbial growth and may be called biogeochemical reaction path modeling. In this approach, the actual microbial community is represented by a synthetic microbial community consisting of a collection of microbial groups; each with a unique growth equation that couples a specific pair of energy yielding redox reactions. The growth equations and their computed standard-state free energy yields are appended to the thermodynamic database used in conventional geochemical reaction path modeling, providing a direct coupling between chemical species participating in both microbial growth and geochemical reactions. To compute the biogeochemical reaction paths, growth substrates are reacted incrementally with the defined geochemical environment and the coupled equations are solved simultaneously to predict reaction paths that display changing microbial biomass, community composition (i.e. the fraction of total biomass in each microbial group), and the aqueous and mineral composition of the system, including aqueous speciation and oxidation state of the targeted contaminants. The approach, with growth equations derived from the literature using well-known bioenergetics principles, was used to predict the results of a laboratory microcosm experiment and an in situ field experiment that investigated the bioreduction of uranium. Predicted effects of ethanol or acetate addition on uranium

  9. A thermodynamically-based model for predicting microbial growth and community composition coupled to system geochemistry: Application to uranium bioreduction

    Energy Technology Data Exchange (ETDEWEB)

    Istok, Jonathan D.; Park, Melora M.; Michalsen, Mandy M.; Spain, A. M.; Krumholz, Lee R.; Liu, Chongxuan; McKinley, James P.; Long, Philip E.; Roden, Eric E.; Peacock, Aaron D.; Baldwin, Brett R.

    2010-04-01

    ‘Bioimmobilization’ of redox-sensitive heavy metals and radionuclides is being investigated as a way to remediate contaminated groundwater and sediments. In one approach, growth-limiting substrates are added to the subsurface to stimulate the activity of targeted groups of indigenous microorganisms and create conditions favorable for the microbially-mediated reductive precipitation (‘bioreduction’) of targeted contaminants. We present a theoretical framework for modeling this process that modifies conventional geochemical reaction path modeling to include thermodynamic descriptions for microbial growth and may be called biogeochemical reaction path modeling. In this approach, the actual microbial community is represented by a synthetic microbial community consisting of a collection of microbial groups; each with a unique growth equation that couples a specific pair of energy yielding redox reactions. The growth equations and their computed standard-state free energy yields are appended to the thermodynamic databasse used in conventional geochemical reaction path modeling, providing a direct coupling between chemical species participating in both microbial growth and geochemical reactions. To compute the biogeochemical reaction paths, growth substrates are added incrementally to a defined geochemical environment and the coupled equations are solved simultaneously to predict microbial biomass, community composition (i.e. the fraction of total biomass in each microbial group), and the aqueous and mineral composition of the system, including aqueous speciation and oxidation state of the targeted contaminants. The approach, with growth equations derived from the literature using well known bioenergetics principles, was used to predict the results of a laboratory microcosm experiment and an in situ field experiment that investigated the bioreduction of uranium. Predicted effects of ethanol or acetate addition on uranium concentration and speciation, major ion

  10. A thermodynamically-based model for predicting microbial growth and community composition coupled to system geochemistry: Application to uranium bioreduction

    Science.gov (United States)

    Istok, J. D.; Park, M.; Michalsen, M.; Spain, A. M.; Krumholz, L. R.; Liu, C.; McKinley, J.; Long, P.; Roden, E.; Peacock, A. D.; Baldwin, B.

    2010-03-01

    'Bioimmobilization' of redox-sensitive heavy metals and radionuclides is being investigated as a way to remediate contaminated groundwater and sediments. In one approach, growth-limiting substrates are added to the subsurface to stimulate the activity of targeted groups of indigenous microorganisms and create conditions favorable for the microbially-mediated reductive precipitation ('bioreduction') of targeted contaminants. We present a theoretical framework for modeling this process that modifies conventional geochemical reaction path modeling to include thermodynamic descriptions for microbial growth and may be called biogeochemical reaction path modeling. In this approach, the actual microbial community is represented by a synthetic microbial community consisting of a collection of microbial groups; each with a unique growth equation that couples a specific pair of energy yielding redox reactions. The growth equations and their computed standard-state free energy yields are appended to the thermodynamic database used in conventional geochemical reaction path modeling, providing a direct coupling between chemical species participating in both microbial growth and geochemical reactions. To compute the biogeochemical reaction paths, growth substrates are reacted incrementally with the defined geochemical environment and the coupled equations are solved simultaneously to predict reaction paths that display changing microbial biomass, community composition (i.e. the fraction of total biomass in each microbial group), and the aqueous and mineral composition of the system, including aqueous speciation and oxidation state of the targeted contaminants. The approach, with growth equations derived from the literature using well-known bioenergetics principles, was used to predict the results of a laboratory microcosm experiment and an in situ field experiment that investigated the bioreduction of uranium. Predicted effects of ethanol or acetate addition on uranium

  11. A Molecular Survey of the Diversity of Microbial Communities in Different Amazonian Agricultural Model Systems

    Directory of Open Access Journals (Sweden)

    Acácio A. Navarrete

    2010-05-01

    Full Text Available The processes of land conversion and agricultural intensification are a significant cause of biodiversity loss, with consequent negative effects both on the environment and the sustainability of food production.The anthrosols associated with pre-Colombian settlements in the Amazonian region are examples of how anthropogenic activities may sustain the native populations against harsh tropical environments for human establishment, even without a previous intentionality of anthropic soil formation. In a case study (Model I—“Slash-and-Burn” the community structures detected by automated ribosomal intergenic spacer analysis (ARISA revealed that soil archaeal, bacterial and fungal communities are heterogeneous and each capable of responding differently to environmental characteristics. ARISA data evidenced considerable difference in structure existing between microbial communities in forest and agricultural soils. In a second study (Model II—“Anthropogenic Soil”, the bacterial community structures revealed by terminal restriction fragment length polymorphism (T-RFLP differed among an Amazonian Dark Earth (ADE, black carbon (BC and its adjacent non-anthropogenic oxisoil. The bacterial 16S rRNA gene (OTU richness estimated by pyrosequencing was higher in ADE than BC. The most abundant bacterial phyla in ADE soils and BC were Proteobacteria—24% ADE, 15% BC; Acidobacteria—10% ADE, 21% BC; Actinobacteria—7% ADE, 12% BC; Verrucomicrobia, 8% ADE; 9% BC; Firmicutes—3% ADE, 8% BC. Overall, unclassified bacteria corresponded to 36% ADE, and 26% BC. Regardless of current land uses, our data suggest that soil microbial community structures may be strongly influenced by the historical soil management and that anthrosols in Amazonia, of anthropogenic origins, in addition to their capacity of enhancing crop yields, may also improve microbial diversity, with the support of the black carbon, which may sustain a particular and unique habitat for the

  12. A mechanistic soil biogeochemistry model with explicit representation of microbial and macrofaunal activities and nutrient cycles

    Science.gov (United States)

    Fatichi, Simone; Manzoni, Stefano; Or, Dani; Paschalis, Athanasios

    2016-04-01

    The potential of a given ecosystem to store and release carbon is inherently linked to soil biogeochemical processes. These processes are deeply connected to the water, energy, and vegetation dynamics above and belowground. Recently, it has been advocated that a mechanistic representation of soil biogeochemistry require: (i) partitioning of soil organic carbon (SOC) pools according to their functional role; (ii) an explicit representation of microbial dynamics; (iii) coupling of carbon and nutrient cycles. While some of these components have been introduced in specialized models, they have been rarely implemented in terrestrial biosphere models and tested in real cases. In this study, we combine a new soil biogeochemistry model with an existing model of land-surface hydrology and vegetation dynamics (T&C). Specifically the soil biogeochemistry component explicitly separates different litter pools and distinguishes SOC in particulate, dissolved and mineral associated fractions. Extracellular enzymes and microbial pools are explicitly represented differentiating the functional roles of bacteria, saprotrophic and mycorrhizal fungi. Microbial activity depends on temperature, soil moisture and litter or SOC stoichiometry. The activity of macrofauna is also modeled. Nutrient dynamics include the cycles of nitrogen, phosphorous and potassium. The model accounts for feedbacks between nutrient limitations and plant growth as well as for plant stoichiometric flexibility. In turn, litter input is a function of the simulated vegetation dynamics. Root exudation and export to mycorrhiza are computed based on a nutrient uptake cost function. The combined model is tested to reproduce respiration dynamics and nitrogen cycle in few sites where data were available to test plausibility of results across a range of different metrics. For instance in a Swiss grassland ecosystem, fine root, bacteria, fungal and macrofaunal respiration account for 40%, 23%, 33% and 4% of total belowground

  13. Integrated network modelling for identifying microbial mechanisms of particulate organic carbon accumulation in coastal marine systems

    Science.gov (United States)

    McDonald, Karlie; Turk, Valentina; Mozetič, Patricija; Tinta, Tinkara; Malfatti, Francesca; Hannah, David; Krause, Stefan

    2016-04-01

    Accumulation of particulate organic carbon (POC) has the potential to change the structure and function of marine ecosystems. High abidance of POC can develop into aggregates, known as marine snow or mucus aggregates that can impair essential marine ecosystem functioning and services. Currently marine POC formation, accumulation and sedimentation processes are being explored as potential pathways to remove CO2 from the atmosphere by CO2 sequestration via fixation into biomass by phytoplankton. However, the current ability of scientists, environmental managers and regulators to analyse and predict high POC concentrations is restricted by the limited understanding of the dynamic nature of the microbial mechanisms regulating POC accumulation events in marine environments. We present a proof of concept study that applies a novel Bayesian Networks (BN) approach to integrate relevant biological and physical-chemical variables across spatial and temporal scales in order to identify the interactions of the main contributing microbial mechanisms regulating POC accumulation in the northern Adriatic Sea. Where previous models have characterised only the POC formed, the BN approach provides a probabilistic framework for predicting the occurrence of POC accumulation by linking biotic factors with prevailing environmental conditions. In this paper the BN was used to test three scenarios (diatom, nanoflagellate, and dinoflagellate blooms). The scenarios predicted diatom blooms to produce high chlorophyll a at the water surface while nanoflagellate blooms were predicted to occur at lower depths (> 6m) in the water column and produce lower chlorophyll a concentrations. A sensitivity analysis identified the variables with the greatest influence on POC accumulation being the enzymes protease and alkaline phosphatase, which highlights the importance of microbial community interactions. The developed proof of concept BN model allows for the first time to quantify the impacts of

  14. Improving Control of Microbially-Induced Mineral Precipitation in Flow Systems - Experiments and Modelling

    Science.gov (United States)

    Gerlach, R.; Phillips, A. J.; Lauchnor, E.; Ebigbo, A.; Connolly, J.; Mitchell, A. C.; Helmig, R.; Cunningham, A. B.; Spangler, L.

    2012-12-01

    Batch and flow experiments at atmospheric and geologic CO2 storage-relevant pressures in our laboratories have demonstrated the ability of microbial biofilms and biofilm produced calcium carbonate precipitates to decrease the permeability of natural and artificial porous media as well as improve the stability of unconsolidated porous media. Two overarching challenges in effectively implementing microbially induced calcium carbonate precipitation (MICP) are controlling (1) the spatial and temporal distribution of the formed precipitates and (2) the inactivation of microbes during the calcium carbonate precipitation process. Failure to control either one of those could result in injection well plugging or the necessity to implement costly cell-reinjection or -resuscitation strategies. Our recent work has focused on optimizing strategies for MICP in small (capillaries and micromodels), small columns (1 to 2.5 cm diameter, up to 5 cm in length), meso- (2 ft columns and 4 cm x 8 cm 2-d reactors) and large-scale (75 cm diameter, 38 cm high sandstone radial flow) systems. Results of these experiments have been modelled using two different approaches. (1) a microscale phase-field approach and (2) a large scale volume averaging approach. Close interaction between experimenters and modellers have resulted in improved injection strategies and the models are currently being used as experimental design tools. This presentation will focus on our recent efforts that combined 2 ft column experimentation with Darcy-scale modelling to calibrate and validate a model before utilizing the model for the optimization of biomineralization strategies in radial flow demonstrations in meso-scale sand stone cores at ambient and high pressures. Schematic pore-scale representation of MICP model

  15. SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems

    Science.gov (United States)

    Bradley, J. A.; Anesio, A. M.; Singarayer, J. S.; Heath, M. R.; Arndt, S.

    2015-10-01

    SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework designed to simulate microbial dynamics and biogeochemical cycling during initial ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The rationale for model development arises from decades of empirical observations in glacier forefields, and enables a quantitative and process focussed approach. Here, we provide a detailed description of SHIMMER, test its performance in two case study forefields: the Damma Glacier (Switzerland) and the Athabasca Glacier (Canada) and analyse sensitivity to identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Primary production is responsible for the initial build-up of labile substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter, and nitrogen fixation, are important in sustaining this productivity. The development and application of SHIMMER also highlights aspects of these systems that require further empirical research: quantifying nutrient budgets and biogeochemical rates, exploring seasonality and microbial growth and cell death. This will lead to increased understanding of how glacier forefields contribute to global biogeochemical cycling and climate under future ice retreat.

  16. Numerical Modeling of Microbial Fuel Cell Based on Redox Electron Mediator

    Institute of Scientific and Technical Information of China (English)

    Nanqi Ren

    2015-01-01

    To investigate the behavior of redox electron mediator and its impact to power generation of microbial fuel cell ( MFC ) , this study carries out the numerical modeling of a typical two⁃chamber MFC based on assumption of interfacial electron transfer via redox electron mediator and acetate as sole electron donor. The model simulates the development of cell voltage, current, substrate concentration, redox electron mediator concentration, polarization and power density output under defined conditions. The results demonstrate that the developed models can fit the experimental results well on a qualitative basis, and concentration of electron reduced mediator plays a dominant role in electron transfer process, and the mass transfer may constitute the limiting step when its concentration is at a relatively low level. This study not only provides a better understanding of electron redox mediator behavior during power generation, but also suggests a strategy to improve electron transfer in the anode of MFC.

  17. Ensemble engineering and statistical modeling for parameter calibration towards optimal design of microbial fuel cells

    Science.gov (United States)

    Sun, Hongyue; Luo, Shuai; Jin, Ran; He, Zhen

    2017-07-01

    Mathematical modeling is an important tool to investigate the performance of microbial fuel cell (MFC) towards its optimized design. To overcome the shortcoming of traditional MFC models, an ensemble model is developed through integrating both engineering model and statistical analytics for the extrapolation scenarios in this study. Such an ensemble model can reduce laboring effort in parameter calibration and require fewer measurement data to achieve comparable accuracy to traditional statistical model under both the normal and extreme operation regions. Based on different weight between current generation and organic removal efficiency, the ensemble model can give recommended input factor settings to achieve the best current generation and organic removal efficiency. The model predicts a set of optimal design factors for the present tubular MFCs including the anode flow rate of 3.47 mL min-1, organic concentration of 0.71 g L-1, and catholyte pumping flow rate of 14.74 mL min-1 to achieve the peak current at 39.2 mA. To maintain 100% organic removal efficiency, the anode flow rate and organic concentration should be controlled lower than 1.04 mL min-1 and 0.22 g L-1, respectively. The developed ensemble model can be potentially modified to model other types of MFCs or bioelectrochemical systems.

  18. Porphyromonas gingivalis and Treponema denticola Mixed Microbial Infection in a Rat Model of Periodontal Disease

    Directory of Open Access Journals (Sweden)

    Raj K. Verma

    2010-01-01

    Full Text Available Porphyromonas gingivalis and Treponema denticola are periodontal pathogens that express virulence factors associated with the pathogenesis of periodontitis. In this paper we tested the hypothesis that P. gingivalis and T. denticola are synergistic in terms of virulence; using a model of mixed microbial infection in rats. Groups of rats were orally infected with either P. gingivalis or T. denticola or mixed microbial infections for 7 and 12 weeks. P. gingivalis genomic DNA was detected more frequently by PCR than T. denticola. Both bacteria induced significantly high IgG, IgG2b, IgG1, IgG2a antibody levels indicating a stimulation of Th1 and Th2 immune response. Radiographic and morphometric measurements demonstrated that rats infected with the mixed infection exhibited significantly more alveolar bone loss than shaminfected control rats. Histology revealed apical migration of junctional epithelium, rete ridge elongation, and crestal alveolar bone resorption; resembling periodontal disease lesion. These results showed that P. gingivalis and T. denticola exhibit no synergistic virulence in a rat model of periodontal disease.

  19. Population cycles and species diversity in dynamic Kill-the-Winner model of microbial ecosystems

    Science.gov (United States)

    Maslov, Sergei; Sneppen, Kim

    2017-01-01

    Determinants of species diversity in microbial ecosystems remain poorly understood. Bacteriophages are believed to increase the diversity by the virtue of Kill-the-Winner infection bias preventing the fastest growing organism from taking over the community. Phage-bacterial ecosystems are traditionally described in terms of the static equilibrium state of Lotka-Volterra equations in which bacterial growth is exactly balanced by losses due to phage predation. Here we consider a more dynamic scenario in which phage infections give rise to abrupt and severe collapses of bacterial populations whenever they become sufficiently large. As a consequence, each bacterial population in our model follows cyclic dynamics of exponential growth interrupted by sudden declines. The total population of all species fluctuates around the carrying capacity of the environment, making these cycles cryptic. While a subset of the slowest growing species in our model is always driven towards extinction, in general the overall ecosystem diversity remains high. The number of surviving species is inversely proportional to the variation in their growth rates but increases with the frequency and severity of phage-induced collapses. Thus counter-intuitively we predict that microbial communities exposed to more violent perturbations should have higher diversity.

  20. Anaerobic microbial transformation of halogenated aromatics and fate prediction using electron density modeling.

    Science.gov (United States)

    Cooper, Myriel; Wagner, Anke; Wondrousch, Dominik; Sonntag, Frank; Sonnabend, Andrei; Brehm, Martin; Schüürmann, Gerrit; Adrian, Lorenz

    2015-05-19

    Halogenated homo- and heterocyclic aromatics including disinfectants, pesticides and pharmaceuticals raise concern as persistent and toxic contaminants with often unknown fate. Remediation strategies and natural attenuation in anaerobic environments often build on microbial reductive dehalogenation. Here we describe the transformation of halogenated anilines, benzonitriles, phenols, methoxylated, or hydroxylated benzoic acids, pyridines, thiophenes, furoic acids, and benzenes by Dehalococcoides mccartyi strain CBDB1 and environmental fate modeling of the dehalogenation pathways. The compounds were chosen based on structural considerations to investigate the influence of functional groups present in a multitude of commercially used halogenated aromatics. Experimentally obtained growth yields were 0.1 to 5 × 10(14) cells mol(-1) of halogen released (corresponding to 0.3-15.3 g protein mol(-1) halogen), and specific enzyme activities ranged from 4.5 to 87.4 nkat mg(-1) protein. Chlorinated electron-poor pyridines were not dechlorinated in contrast to electron-rich thiophenes. Three different partial charge models demonstrated that the regioselective removal of halogens is governed by the least negative partial charge of the halogen. Microbial reaction pathways combined with computational chemistry and pertinent literature findings on Co(I) chemistry suggest that halide expulsion during reductive dehalogenation is initiated through single electron transfer from B12Co(I) to the apical halogen site.

  1. Microbial Impacts to the Near-Field Environment Geochemistry: a model for estimating microbial communities in repository drifts at Yucca Mountain

    Science.gov (United States)

    Jolley, Darren M.; Ehrhorn, Thomas F.; Horn, Joanne

    2003-05-01

    Geochemical and microbiological modeling was performed to evaluate the potential quantities and impact of microorganisms on the geochemistry of the area adjacent to and within nuclear waste packages in the proposed repository drifts at Yucca Mountain, Nevada. The microbial growth results from the introduction of water, ground support, and waste package materials into the deep unsaturated rock. The simulations, which spanned 1 million years, were accomplished using a newly developed computer code, Microbial Impacts to the Near-Field Environment Geochemistry (MING). MING uses environmental thresholds for limiting microbial growth to temperatures below 120 °C and above relative humidities of 90% in repository drifts. Once these thresholds are met, MING expands upon a mass balance and thermodynamic approach proposed by McKinley et al. [FEMS Microbiol. Rev. 20 (1997) 545] by using kinetic rates to supply constituents from design materials and constituent fluxes including solubilized rock components into the drift to perform two separate mass balance calculations as a function of time. The first (nutrient limit) assesses the available nutrients (C, N, P and S) and calculates how many microorganisms can be produced based on a microorganism stoichiometry of C 160(H 280O 80)N 30P 2S. The second (energy limit) calculates the energy available from optimally combined redox couples for the temperature and pH at that time. This optimization maximizes those reactions that produce >15 kJ/mol (limit on useable energy) using an iterative linear optimization technique. The final available energy value is converted to microbial mass at a rate of 1 kg of biomass (dry weight) for every 64 MJ of energy. These two values (nutrient limit and energy limit) are then compared and the smaller value represents the number of microorganisms that can be produced over a specified time. MING can also be adapted to investigate other problems of interest as the model can be used in saturated and

  2. Microbial Impacts to the Near-Field Environment Geochemistry (MING): A Model for Estimating Microbial Communities in Repository Drifts at Yucca Mountain

    Energy Technology Data Exchange (ETDEWEB)

    D.M. Jolley; T.F. Ehrhorn; J. Horn

    2002-03-19

    Geochemical and microbiological modeling was performed to evaluate the potential quantities and impact of microorganisms on the geochemistry of the area adjacent to and within nuclear waste packages in the proposed repository drifts at Yucca Mountain, Nevada. The microbial growth results from the introduction of water, ground support, and waste package materials into the deep unsaturated rock. The simulations, which spanned one million years, were accomplished using a newly developed computer code, Microbial Impacts to the Near-Field Environment Geochemistry (MING). MING uses environmental thresholds for limiting microbial growth to temperatures below 120 C and above relative humidities of 90 percent in repository drifts. Once these thresholds are met, MING expands upon a mass balance and thermodynamic approach proposed by McKinley and others (1997), by using kinetic rates to supply constituents from design materials and constituent fluxes including solubilized rock components into the drift, to perform two separate mass-balance calculations as a function of time. The first (nutrient limit) assesses the available nutrients (C, N, P and S) and calculates how many microorganisms can be produced based on a microorganism stoichiometry of C{sub 160}(H{sub 280}O{sub 80})N{sub 30}P{sub 2}S. The second (energy limit) calculates the energy available from optimally combined redox couples for the temperature, and pH at that time. This optimization maximizes those reactions that produce > 15kJ/mol (limit on useable energy) using an iterative linear optimization technique. The final available energy value is converted to microbial mass at a rate of 1 kg of biomass (dry weight) for every 64 MJ of energy. These two values (nutrient limit and energy limit) are then compared and the smaller value represents the number of microorganisms that can be produced over a specified time. MING can also be adapted to investigate other problems of interest as the model can be used in saturated

  3. BiomeNet: a Bayesian model for inference of metabolic divergence among microbial communities.

    Directory of Open Access Journals (Sweden)

    Mahdi Shafiei

    2014-11-01

    Full Text Available Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks, for inferring differential prevalence of metabolic subnetworks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks are shared across all groups (microbiome samples, but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems. The metabosystems are composed of mixtures of tightly connected metabolic subnetworks. BiomeNet differs from other unsupervised methods by allowing researchers to discriminate groups of samples through the metabolic patterns it discovers in the data, and by providing a framework for interpreting them. We describe a collapsed Gibbs sampler for inference of the mixture weights under BiomeNet, and we use simulation to validate the inference algorithm. Application of BiomeNet to human gut metagenomes revealed a metabosystem with greater prevalence among inflammatory bowel disease (IBD patients. Based on the discriminatory subnetworks for this metabosystem, we inferred that the community is likely to be closely associated with the human gut epithelium, resistant to dietary interventions, and interfere with human uptake of an antioxidant connected to IBD. Because this metabosystem has a greater capacity to exploit host-associated glycans, we speculate that IBD

  4. Photocatalytic properties of zinc sulfide nanocrystals biofabricated by metal-reducing bacterium Shewanella oneidensis MR-1

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Xiang [School of The Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013 (China); State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090 (China); Ma, Xiao-Bo [School of The Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013 (China); Yuan, Hang [Key Laboratory of Ion Beam Bioengineering, Institute of Technical Biology & Agriculture Engineering, Chinese Academy of Sciences, Hefei 230031 (China); Liu, Peng-Cheng; Lei, Yu-Bin; Xu, Hui [School of The Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013 (China); Du, Dao-Lin, E-mail: ddl@ujs.edu.cn [School of The Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013 (China); State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090 (China); Sun, Jian-Fan [School of The Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013 (China); Feng, Yu-Jie, E-mail: yujief@hit.edu.cn [State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090 (China)

    2015-05-15

    Highlights: • S. oneidensis MR-1 biofabricated ZnS nanocrystals using artificial wastewater. • ZnS nanocrystals were 5 nm in diameter and aggregated extracellularly. • ZnS had good catalytic activity in the degradation of RHB under UV irradiation. • Photogenerated holes mainly contributed to the degradation of RhB. - Abstract: Accumulation and utilization of heavy metals from wastewater by biological treatment system has aroused great interest. In the present study, a metal-reducing bacterium Shewanella oneidensis MR-1 was used to explore the biofabrication of ZnS nanocrystals from the artificial wastewater. The biogenic H{sub 2}S produced via the reduction of thiosulfate precipitated the Zn(II) as sulfide extracellularly. Characterization by X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), and field emission scanning electron microscope (FESEM) confirmed the precipitates as ZnS nanocrystals. The biogenic ZnS nanocrystals appeared spherical in shape with an average diameter of 5 nm and mainly aggregated in the medium and cell surface of S. oneidensis MR-1. UV–vis DRS spectra showed ZnS nanoparticles appeared a strong absorption below 360 nm. Thus, the photocatalytic activity of ZnS was evaluated by the photodegradation of rhodamine B (RhB) under UV irradiation. The biogenic ZnS nanocrystals showed a high level of photodegradation efficiency to RhB coupled with a significant blue-shift of maximum adsorption peak. A detailed analysis indicated the photogenerated holes, rather than hydroxyl radicals, contributed to the photocatalytic decolorization of RhB. This approach of coupling biosynthesis of nanoparticles with heavy metal removal may offer a potential avenue for efficient bioremediation of heavy metal wastewater.

  5. N-gram analysis of 970 microbial organisms reveals presence of biological language models

    Directory of Open Access Journals (Sweden)

    Ganapathiraju Madhavi K

    2011-01-01

    Full Text Available Abstract Background It has been suggested previously that genome and proteome sequences show characteristics typical of natural-language texts such as "signature-style" word usage indicative of authors or topics, and that the algorithms originally developed for natural language processing may therefore be applied to genome sequences to draw biologically relevant conclusions. Following this approach of 'biological language modeling', statistical n-gram analysis has been applied for comparative analysis of whole proteome sequences of 44 organisms. It has been shown that a few particular amino acid n-grams are found in abundance in one organism but occurring very rarely in other organisms, thereby serving as genome signatures. At that time proteomes of only 44 organisms were available, thereby limiting the generalization of this hypothesis. Today nearly 1,000 genome sequences and corresponding translated sequences are available, making it feasible to test the existence of biological language models over the evolutionary tree. Results We studied whole proteome sequences of 970 microbial organisms using n-gram frequencies and cross-perplexity employing the Biological Language Modeling Toolkit and Patternix Revelio toolkit. Genus-specific signatures were observed even in a simple unigram distribution. By taking statistical n-gram model of one organism as reference and computing cross-perplexity of all other microbial proteomes with it, cross-perplexity was found to be predictive of branch distance of the phylogenetic tree. For example, a 4-gram model from proteome of Shigellae flexneri 2a, which belongs to the Gammaproteobacteria class showed a self-perplexity of 15.34 while the cross-perplexity of other organisms was in the range of 15.59 to 29.5 and was proportional to their branching distance in the evolutionary tree from S. flexneri. The organisms of this genus, which happen to be pathotypes of E.coli, also have the closest perplexity values with

  6. Modeling the impact of the indigenous microbial population on the maximum population density of Salmonella on alfalfa

    NARCIS (Netherlands)

    Rijgersberg, H.; Nierop Groot, M.N.; Tromp, S.O.; Franz, E.

    2013-01-01

    Within a microbial risk assessment framework, modeling the maximum population density (MPD) of a pathogenic microorganism is important but often not considered. This paper describes a model predicting the MPD of Salmonella on alfalfa as a function of the initial contamination level, the total count

  7. A Comparison of Modeling Approaches in Simulating Chlorinated Ethene Removal in a Constructed Wetland by a Microbial Consortia

    Science.gov (United States)

    2007-11-02

    results. Concepts like microbial growth in the form of a biofilm and spatially varying contaminant concentrations bring the validity of the CSTR ...assumption into question. These concepts are incorporated into the different modeling approaches to evaluate the CSTR assumption. Model simulations show that

  8. Disentangling residence time and temperature sensitivity of microbial decomposition in a global soil carbon model

    Science.gov (United States)

    Exbrayat, J.-F.; Pitman, A. J.; Abramowitz, G.

    2014-12-01

    Recent studies have identified the first-order representation of microbial decomposition as a major source of uncertainty in simulations and projections of the terrestrial carbon balance. Here, we use a reduced complexity model representative of current state-of-the-art models of soil organic carbon decomposition. We undertake a systematic sensitivity analysis to disentangle the effect of the time-invariant baseline residence time (k) and the sensitivity of microbial decomposition to temperature (Q10) on soil carbon dynamics at regional and global scales. Our simulations produce a range in total soil carbon at equilibrium of ~ 592 to 2745 Pg C, which is similar to the ~ 561 to 2938 Pg C range in pre-industrial soil carbon in models used in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). This range depends primarily on the value of k, although the impact of Q10 is not trivial at regional scales. As climate changes through the historical period, and into the future, k is primarily responsible for the magnitude of the response in soil carbon, whereas Q10 determines whether the soil remains a sink, or becomes a source in the future mostly by its effect on mid-latitude carbon balance. If we restrict our simulations to those simulating total soil carbon stocks consistent with observations of current stocks, the projected range in total soil carbon change is reduced by 42% for the historical simulations and 45% for the future projections. However, while this observation-based selection dismisses outliers, it does not increase confidence in the future sign of the soil carbon feedback. We conclude that despite this result, future estimates of soil carbon and how soil carbon responds to climate change should be more constrained by available data sets of carbon stocks.

  9. A metastable equilibrium model for the relative abundances of microbial phyla in a hot spring.

    Directory of Open Access Journals (Sweden)

    Jeffrey M Dick

    Full Text Available Many studies link the compositions of microbial communities to their environments, but the energetics of organism-specific biomass synthesis as a function of geochemical variables have rarely been assessed. We describe a thermodynamic model that integrates geochemical and metagenomic data for biofilms sampled at five sites along a thermal and chemical gradient in the outflow channel of the hot spring known as "Bison Pool" in Yellowstone National Park. The relative abundances of major phyla in individual communities sampled along the outflow channel are modeled by computing metastable equilibrium among model proteins with amino acid compositions derived from metagenomic sequences. Geochemical conditions are represented by temperature and activities of basis species, including pH and oxidation-reduction potential quantified as the activity of dissolved hydrogen. By adjusting the activity of hydrogen, the model can be tuned to closely approximate the relative abundances of the phyla observed in the community profiles generated from BLAST assignments. The findings reveal an inverse relationship between the energy demand to form the proteins at equal thermodynamic activities and the abundance of phyla in the community. The distance from metastable equilibrium of the communities, assessed using an equation derived from energetic considerations that is also consistent with the information-theoretic entropy change, decreases along the outflow channel. Specific divergences from metastable equilibrium, such as an underprediction of the relative abundances of phototrophic organisms at lower temperatures, can be explained by considering additional sources of energy and/or differences in growth efficiency. Although the metabolisms used by many members of these communities are driven by chemical disequilibria, the results support the possibility that higher-level patterns of chemotrophic microbial ecosystems are shaped by metastable equilibrium states that

  10. Coupled Transport/Reaction Modelling of Copper Canister Corrosion Aided by Microbial Processes

    Energy Technology Data Exchange (ETDEWEB)

    Jinsong Liu [Royal Institute of Technology, Stockholm (Sweden). Dept. of Chemical Engineering and Technology

    2006-04-15

    Copper canister corrosion is an important issue in the concept of a nuclear fuel repository. Previous studies indicate that the oxygen-free copper canister could hold its integrity for more than 100,000 years in the repository environment. Microbial processes may reduce sulphate to sulphide and considerably increase the amount of sulphides available for corrosion. In this paper, a coupled transport/reaction model is developed to account for the transport of chemical species produced by microbial processes. The corroding agents like sulphide would come not only from the groundwater flowing in a fracture that intersects the canister, but also from the reduction of sulphate near the canister. The reaction of sulphate-reducing bacteria and the transport of sulphide in the bentonite buffer are included in the model. The depth of copper canister corrosion is calculated by the model. With representative 'central values' of the concentrations of sulphate and methane at repository depth at different sites in Fennoscandian Shield the corrosion depth predicted by the model is a few millimetres during 10{sup 5} years. As the concentrations of sulphate and methane are extremely site-specific and future climate changes may significantly influence the groundwater compositions at potential repository sites, sensitivity analyses have been conducted. With a broad perspective of the measured concentrations at different sites in Sweden and in Finland, and some possible mechanisms (like the glacial meltwater intrusion and interglacial seawater intrusion) that may introduce more sulphate into the groundwater at intermediate depths during future climate changes, higher concentrations of either/both sulphate and methane than what is used as the representative 'central' values would be possible. In worst cases. locally, half of the canister thickness could possibly be corroded within 10{sup 5} years.

  11. Microbial Toluene Removal in Hypoxic Model Constructed Wetlands Occurs Predominantly via the Ring Monooxygenation Pathway.

    Science.gov (United States)

    Martínez-Lavanchy, P M; Chen, Z; Lünsmann, V; Marin-Cevada, V; Vilchez-Vargas, R; Pieper, D H; Reiche, N; Kappelmeyer, U; Imparato, V; Junca, H; Nijenhuis, I; Müller, J A; Kuschk, P; Heipieper, H J

    2015-09-01

    In the present study, microbial toluene degradation in controlled constructed wetland model systems, planted fixed-bed reactors (PFRs), was queried with DNA-based methods in combination with stable isotope fractionation analysis and characterization of toluene-degrading microbial isolates. Two PFR replicates were operated with toluene as the sole external carbon and electron source for 2 years. The bulk redox conditions in these systems were hypoxic to anoxic. The autochthonous bacterial communities, as analyzed by Illumina sequencing of 16S rRNA gene amplicons, were mainly comprised of the families Xanthomonadaceae, Comamonadaceae, and Burkholderiaceae, plus Rhodospirillaceae in one of the PFR replicates. DNA microarray analyses of the catabolic potentials for aromatic compound degradation suggested the presence of the ring monooxygenation pathway in both systems, as well as the anaerobic toluene pathway in the PFR replicate with a high abundance of Rhodospirillaceae. The presence of catabolic genes encoding the ring monooxygenation pathway was verified by quantitative PCR analysis, utilizing the obtained toluene-degrading isolates as references. Stable isotope fractionation analysis showed low-level of carbon fractionation and only minimal hydrogen fractionation in both PFRs, which matches the fractionation signatures of monooxygenation and dioxygenation. In combination with the results of the DNA-based analyses, this suggests that toluene degradation occurs predominantly via ring monooxygenation in the PFRs. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  12. Incorporating H2 Dynamics and Inhibition into a Microbially Based Methanogenesis Model for Restored Wetland Sediments

    Science.gov (United States)

    Pal, David; Jaffe, Peter

    2015-04-01

    Estimates of global CH4 emissions from wetlands indicate that wetlands are the largest natural source of CH4 to the atmosphere. In this paper, we propose that there is a missing component to these models that should be addressed. CH4 is produced in wetland sediments from the microbial degradation of organic carbon through multiple fermentation steps and methanogenesis pathways. There are multiple sources of carbon for methananogenesis; in vegetated wetland sediments, microbial communities consume root exudates as a major source of organic carbon. In many methane models propionate is used as a model carbon molecule. This simple sugar is fermented into acetate and H2, acetate is transformed to methane and CO2, while the H2 and CO2 are used to form an additional CH4 molecule. The hydrogenotrophic pathway involves the equilibrium of two dissolved gases, CH4 and H2. In an effort to limit CH4 emissions from wetlands, there has been growing interest in finding ways to limit plant transport of soil gases through root systems. Changing planted species, or genetically modifying new species of plants may control this transport of soil gases. While this may decrease the direct emissions of methane, there is little understanding about how H2 dynamics may feedback into overall methane production. The results of an incubation study were combined with a new model of propionate degradation for methanogenesis that also examines other natural parameters (i.e. gas transport through plants). This presentation examines how we would expect this model to behave in a natural field setting with changing sulfate and carbon loading schemes. These changes can be controlled through new plant species and other management practices. Next, we compare the behavior of two variations of this model, with or without the incorporation of H2 interactions, with changing sulfate, carbon loading and root volatilization. Results show that while the models behave similarly there may be a discrepancy of nearly

  13. Disentangling residence time and temperature sensitivity of microbial decomposition in a global soil carbon model

    Directory of Open Access Journals (Sweden)

    J.-F. Exbrayat

    2014-03-01

    Full Text Available Recent studies have identified the first-order parameterization of microbial decomposition as a major source of uncertainty in simulations and projections of the terrestrial carbon balance. Here, we use a reduced complexity model representative of the current state-of-the-art parameterization of soil organic carbon decomposition. We undertake a systematic sensitivity analysis to disentangle the effect of the time-invariant baseline residence time (k and the sensitvity of microbial decomposition to temperature (Q10 on soil carbon dynamics at regional and global scales. Our simulations produce a range in total soil carbon at equilibrium of ~ 592 to 2745 Pg C which is similar to the ~ 561 to 2938 Pg C range in pre-industrial soil carbon in models used in the fifth phase of the Coupled Model Intercomparison Project. This range depends primarily on the value of k, although the impact of Q10 is not trivial at regional scales. As climate changes through the historical period, and into the future, k is primarily responsible for the magnitude of the response in soil carbon, whereas Q10 determines whether the soil remains a sink, or becomes a source in the future mostly by its effect on mid-latitudes carbon balance. If we restrict our simulations to those simulating total soil carbon stocks consistent with observations of current stocks, the projected range in total soil carbon change is reduced by 42% for the historical simulations and 45% for the future projections. However, while this observation-based selection dismisses outliers it does not increase confidence in the future sign of the soil carbon feedback. We conclude that despite this result, future estimates of soil carbon, and how soil carbon responds to climate change should be constrained by available observational data sets.

  14. Coupled modeling of groundwater flow solute transport, chemical reactions and microbial processes in the 'SP' island

    Energy Technology Data Exchange (ETDEWEB)

    Samper, Javier; Molinero, Jorg; Changbing, Yang; Zhang, Guoxiang

    2003-12-01

    The Redox Zone Experiment was carried out at the Aespoe HRL in order to study the redox behavior and the hydrochemistry of an isolated vertical fracture zone disturbed by the excavation of an access tunnel. Overall results and interpretation of the Redox Zone Project were reported by /Banwart et al, 1995/. Later, /Banwart et al, 1999/ presented a summary of the hydrochemistry of the Redox Zone Experiment. Coupled groundwater flow and reactive transport models of this experiment were carried out by /Molinero, 2000/ who proposed a revised conceptual model for the hydrogeology of the Redox Zone Experiment which could explain simultaneously measured drawdown and salinity data. The numerical model was found useful to understand the natural system. Several conclusions were drawn about the redox conditions of recharge waters, cation exchange capacity of the fracture zone and the role of mineral phases such as pyrite, calcite, hematite and goethite. This model could reproduce the measured trends of dissolved species, except for bicarbonate and sulfate which are affected by microbially-mediated processes. In order to explore the role of microbial processes, a coupled numerical model has been constructed which accounts for water flow, reactive transport and microbial processes. The results of this model is presented in this report. This model accounts for groundwater flow and reactive transport in a manner similar to that of /Molinero, 2000/ and extends the preliminary microbial model of /Zhang, 2001/ by accounting for microbially-driven organic matter fermentation and organic matter oxidation. This updated microbial model considers simultaneously the fermentation of particulate organic matter by yeast and the oxidation of dissolved organic matter, a product of fermentation. Dissolved organic matter is produced by yeast and serves also as a substrate for iron-reducing bacteria. Model results reproduce the observed increase in bicarbonate and sulfate concentration, thus

  15. Redox zone II. Coupled modeling of groundwater flow, solute transport, chemical reactions and microbial processes in the Aespoe island

    Energy Technology Data Exchange (ETDEWEB)

    Samper, Javier; Molinero, Jorge; Changbing Yang; Guoxiang Zhang [Univ. Da Coruna (Spain)

    2003-12-01

    The Redox Zone Experiment was carried out at the Aespoe HRL in order to study the redox behaviour and the hydrochemistry of an isolated vertical fracture zone disturbed by the excavation of an access tunnel. Overall results and interpretation of the Redox Zone Project were reported by Banwart et al. Later, Banwart presented a summary of the hydrochemistry of the Redox Zone Experiment. Coupled groundwater flow and reactive transport models of this experiment were carried out by Molinero who proposed a revised conceptual model for the hydrogeology of the Redox Zone Experiment which could explain simultaneously measured drawdown and salinity data. The numerical model was found useful to understand the natural system. Several conclusions were drawn about the redox conditions of recharge waters, cation exchange capacity of the fracture zone and the role of mineral phases such as pyrite, calcite, hematite and goethite. This model could reproduce the measured trends of dissolved species, except for bicarbonate and sulphate which are affected by microbially-mediated processes. In order to explore the role of microbial processes, a coupled numerical model has been constructed which accounts for water flow, reactive transport and microbial processes. The results of this model is presented in this report. This model accounts for groundwater flow and reactive transport in a manner similar to that of Molinero and extends the preliminary microbial model of Zhang by accounting for microbially-driven organic matter fermentation and organic matter oxidation. This updated microbial model considers simultaneously the fermentation of particulate organic matter by yeast and the oxidation of dissolved organic matter, a product of fermentation. Dissolved organic matter is produced by yeast and serves also as a substrate for iron-reducing bacteria. Model results reproduce the observed increase in bicarbonate and sulfaphe concentration, thus adding additional evidence for the possibility

  16. Impacts of radiation exposure on the experimental microbial ecosystem: a particle-based model simulation approach

    Energy Technology Data Exchange (ETDEWEB)

    Doi, M.; Tanaka, N.; Fuma, S.; Kawabata, Z.

    2004-07-01

    Well-designed experimental model ecosystem could be a simple reference of the actual environment and complex ecological systems. For ecological toxicity test of radiation and other environmental toxicants, we investigated and aquatic microbial ecosystem (closed microcosm) in the test tube with initial substrates,autotroph flagellate algae (Euglena, G.), heterotroph ciliate protozoa (Tetrahymena T.) and saprotroph bacteria (E, coli). These species organizes by itself to construct the ecological system, that keeps the sustainable population dynamics for more than 2 years after inoculation only by adding light diurnally and controlling temperature at 25 degree Celsius. Objective of the study is to develop the particle-based computer simulation by reviewing interactions among microbes and environment, and analyze the ecological toxicities of radiation on the microcosm by replicating experimental results in the computer simulation. (Author) 14 refs.

  17. Application of nonlinear analysis methods for identifying relationships between microbial community structure and groundwater geochemistry.

    Science.gov (United States)

    Schryver, Jack C; Brandt, Craig C; Pfiffner, Susan M; Palumbo, Anthony V; Peacock, Aaron D; White, David C; McKinley, James P; Long, Philip E

    2006-02-01

    The relationship between groundwater geochemistry and microbial community structure can be complex and difficult to assess. We applied nonlinear and generalized linear data analysis methods to relate microbial biomarkers (phospholipids fatty acids, PLFA) to groundwater geochemical characteristics at the Shiprock uranium mill tailings disposal site that is primarily contaminated by uranium, sulfate, and nitrate. First, predictive models were constructed using feedforward artificial neural networks (NN) to predict PLFA classes from geochemistry. To reduce the danger of overfitting, parsimonious NN architectures were selected based on pruning of hidden nodes and elimination of redundant predictor (geochemical) variables. The resulting NN models greatly outperformed the generalized linear models. Sensitivity analysis indicated that tritium, which was indicative of riverine influences, and uranium were important in predicting the distributions of the PLFA classes. In contrast, nitrate concentration and inorganic carbon were least important, and total ionic strength was of intermediate importance. Second, nonlinear principal components (NPC) were extracted from the PLFA data using a variant of the feedforward NN. The NPC grouped the samples according to similar geochemistry. PLFA indicators of Gram-negative bacteria and eukaryotes were associated with the groups of wells with lower levels of contamination. The more contaminated samples contained microbial communities that were predominated by terminally branched saturates and branched monounsaturates that are indicative of metal reducers, actinomycetes, and Gram-positive bacteria. These results indicate that the microbial community at the site is coupled to the geochemistry and knowledge of the geochemistry allows prediction of the community composition.

  18. Application of Nonlinear Analysis Methods for Identifying Relationships Between Microbial Community Structure and Groundwater Geochemistry

    Energy Technology Data Exchange (ETDEWEB)

    Schryver, Jack C.; Brandt, Craig C.; Pfiffner, Susan M.; Palumbo, A V.; Peacock, Aaron D.; White, David C.; McKinley, James P.; Long, Philip E.

    2006-02-01

    The relationship between groundwater geochemistry and microbial community structure can be complex and difficult to assess. We applied nonlinear and generalized linear data analysis methods to relate microbial biomarkers (phospholipids fatty acids, PLFA) to groundwater geochemical characteristics at the Shiprock uranium mill tailings disposal site that is primarily contaminated by uranium, sulfate, and nitrate. First, predictive models were constructed using feedforward artificial neural networks (NN) to predict PLFA classes from geochemistry. To reduce the danger of overfitting, parsimonious NN architectures were selected based on pruning of hidden nodes and elimination of redundant predictor (geochemical) variables. The resulting NN models greatly outperformed the generalized linear models. Sensitivity analysis indicated that tritium, which was indicative of riverine influences, and uranium were important in predicting the distributions of the PLFA classes. In contrast, nitrate concentration and inorganic carbon were least important, and total ionic strength was of intermediate importance. Second, nonlinear principal components (NPC) were extracted from the PLFA data using a variant of the feedforward NN. The NPC grouped the samples according to similar geochemistry. PLFA indicators of Gram-negative bacteria and eukaryotes were associated with the groups of wells with lower levels of contamination. The more contaminated samples contained microbial communities that were predominated by terminally branched saturates and branched monounsaturates that are indicative of metal reducers, actinomycetes, and Gram-positive bacteria. These results indicate that the microbial community at the site is coupled to the geochemistry and knowledge of the geochemistry allows prediction of the community composition.

  19. Modeling of microbial gas generation: application to the eastern Mediterranean “Biogenic Play”

    Energy Technology Data Exchange (ETDEWEB)

    Schneider, M.; Dubille, M.; Montadert, L.

    2016-07-01

    Biogenic gas is becoming increasingly important as an exploration target in the petroleum industry because it occurs in geologically predictable circumstances and in large quantities at shallow depths as free gas or gas hydrates. As accumulations of biogenic gas result in a subtle synchronization between early generation and early trapping, we integrated a macroscopic model of microbial gas generation within a 3D basin and petroleum system forward simulator. The macroscopic model is based on a microscopic model, which consists in a 1D sedimentary column that accounts for sedimentation, compaction, Darcy flow and Diffusion flow. The organic carbon is the only non-soluble element considered in this version of the model. The dissolved elements are O2, SO4 2-, H2, CH3COOH, and CH4. Methane is dissolved in water or present as a free phase if its concentration exceeds its solubility at given pressure and temperature. In this microscopic model, the transformation of substrate into biomass is described through a set of logistic equations coupled with the transport equations (advection and diffusion). Based on the microscopic considerations we developed the macroscopic model of low maturity/biogenic gas generation in which hydrocarbons are generated through first order kinetic reactions at low maturity. This macroscopic model is adapted to petroleum system modeling at basin scale with TemisFlow®, which aims to understand and predict hydrocarbon generation, migration, and accumulation. It is composed of: i) A source rock criteria which allow defining the biogenic gas source rocks potential and ii) A kinetic model of methane generation. The previous model has been successfully applied on different basins such as the Carupano Basin from the offshore Venezuela, the Magdalena Delta (offshore Colombia) and the offshore Vietnam where direct observations of low-maturity gas were available. Furthermore, it has been applied in the offshore Lebanon in order to check the viability of

  20. A mesoscopic stochastic model for the specific consumption rate in substrate-limited microbial growth

    Science.gov (United States)

    2017-01-01

    The specific consumption rate of substrate, as well as the associated specific growth rate, is an essential parameter in the mathematical description of substrate-limited microbial growth. In this paper we develop a completely new kinetic model of substrate transport, based on recent knowledge on the structural biology of transport proteins, which correctly describes very accurate experimental results at near-zero substrate concentration values found in the literature, where the widespread Michaelis-Menten model fails. Additionally, our model converges asymptotically to Michaelis-Menten predictions as substrate concentration increases. Instead of the single active site enzymatic reaction of Michaelis-Menten type, the proposed model assumes a multi-site kinetics, simplified as an apparent all-or-none mechanism for the transport, which is controlled by means of the local substrate concentration in the close vicinity of the transport protein. Besides, the model also assumes that this local concentration is not equal to the mean substrate concentration experimentally determined in the culture medium. Instead, we propose that it fluctuates with a mostly exponential distribution of Weibull type. PMID:28187189

  1. Multi-variable mathematical models for the air-cathode microbial fuel cell system

    Science.gov (United States)

    Ou, Shiqi; Kashima, Hiroyuki; Aaron, Douglas S.; Regan, John M.; Mench, Matthew M.

    2016-05-01

    This research adopted the version control system into the model construction for the single chamber air-cathode microbial fuel cell (MFC) system, to understand the interrelation of biological, chemical, and electrochemical reactions. The anodic steady state model was used to consider the chemical species diffusion and electric migration influence to the MFC performance. In the cathodic steady state model, the mass transport and reactions in a multi-layer, abiotic cathode and multi-bacteria cathode biofilm were simulated. Transport of hydroxide was assumed for cathodic pH change. This assumption is an alternative to the typical notion of proton consumption during oxygen reduction to explain elevated cathode pH. The cathodic steady state model provided the power density and polarization curve performance results that can be compared to an experimental MFC system. Another aspect considered was the relative contributions of platinum catalyst and microbes on the cathode to the oxygen reduction reaction (ORR). Simulation results showed that the biocatalyst in a cathode that includes a Pt/C catalyst likely plays a minor role in ORR, contributing up to 8% of the total power calculated by the models.

  2. The effect of corrosion inhibitors on microbial communities associated with corrosion in a model flow cell system.

    Science.gov (United States)

    Duncan, Kathleen E; Perez-Ibarra, Beatriz Monica; Jenneman, Gary; Harris, Jennifer Busch; Webb, Robert; Sublette, Kerry

    2014-01-01

    A model flow cell system was designed to investigate pitting corrosion in pipelines associated with microbial communities. A microbial inoculum producing copious amounts of H₂S was enriched from an oil pipeline biofilm sample. Reservoirs containing a nutrient solution and the microbial inoculum were pumped continuously through six flow cells containing mild steel corrosion coupons. Two cells received corrosion inhibitor "A", two received corrosion inhibitor "B", and two ("untreated") received no additional chemicals. Coupons were removed after 1 month and analyzed for corrosion profiles and biofilm microbial communities. Coupons from replicate cells showed a high degree of similarity in pitting parameters and in microbial community profiles, as determined by 16S rRNA gene sequence libraries but differed with treatment regimen, suggesting that the corrosion inhibitors differentially affected microbial species. Viable microbial biomass values were more than 10-fold higher for coupons from flow cells treated with corrosion inhibitors than for coupons from untreated flow cells. The total number of pits >10 mils diameter and maximum pitting rate were significantly correlated with each other and the total number of pits with the estimated abundance of sequences classified as Desulfomicrobium. The maximum pitting rate was significantly correlated with the sum of the estimated abundance of Desulfomicrobium plus Clostridiales, and with the sum of the estimated abundance of Desulfomicrobium plus Betaproteobacteria. The lack of significant correlation with the estimated abundance of Deltaproteobacteria suggests not all Deltaproteobacteria species contribute equally to microbiologically influenced corrosion (MIC) and that it is not sufficient to target one bacterial group when monitoring for MIC.

  3. Models of the behaviour of (thermally stressed) microbial spores in foods: Tools to study mechanisms of damage and repair

    NARCIS (Netherlands)

    ter Beek, A.; Hornstra, L.M.; Pandey, R.; Kallemeijn, W.W.; Smelt, J.P.P.M.; Manders, E.M.M.; Brul, S.

    2011-01-01

    The ‘Omics’ revolution has brought a wealth of new mechanistic insights in many fields of biology. It offers options to base predictions of microbial behaviour on mechanistic insight. As the cellular mechanisms involved often turn out to be highly intertwined it is crucial that model development aim

  4. Mathematical model of dynamic behavior of microbial desalination cells for simultaneous wastewater treatment and water desalination.

    Science.gov (United States)

    Ping, Qingyun; Zhang, Chenyao; Chen, Xueer; Zhang, Bo; Huang, Zuyi; He, Zhen

    2014-11-04

    Microbial desalination cells (MDCs) are an emerging concept for simultaneous wastewater treatment and water desalination. This work presents a mathematical model to simulate dynamic behavior of MDCs for the first time through evaluating multiple factors such as organic supply, salt loading, and current generation. Ordinary differential equations were applied to describe the substrate as well as bacterial concentrations in the anode compartment. Local sensitivity analysis was employed to select model parameters that needed to be re-estimated from the previous studies. This model was validated by experimental data from both a bench- and a large-scale MDC system. It could fit current generation fairly well and simulate the change of salt concentration. It was able to predict the response of the MDC with time under various conditions, and also provide information for analyzing the effects of different operating conditions. Furthermore, optimal operating conditions for the MDC used in this study were estimated to have an acetate flow rate of 0.8 mL·min(-1), influent salt concentration of 15 g·L(-1) and salt solution flow rate of 0.04 mL·min(-1), and to be operated with an external resistor less than 30 Ω. The MDC model will be helpful with determining operational parameters to achieve optimal desalination in MDCs.

  5. IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.

    Science.gov (United States)

    Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming

    2017-04-07

    Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

  6. Microbial adhesion and biofilm formation on microfiltration membranes: a detailed characterization using model organisms with increasing complexity.

    Science.gov (United States)

    Vanysacker, L; Denis, C; Declerck, P; Piasecka, A; Vankelecom, I F J

    2013-01-01

    Since many years, membrane biofouling has been described as the Achilles heel of membrane fouling. In the present study, an ecological assay was performed using model systems with increasing complexity: a monospecies assay using Pseudomonas aeruginosa or Escherichia coli separately, a duospecies assay using both microorganisms, and a multispecies assay using activated sludge with or without spiked P. aeruginosa. The microbial adhesion and biofilm formation were evaluated in terms of bacterial cell densities, species richness, and bacterial community composition on polyvinyldifluoride, polyethylene, and polysulfone membranes. The data show that biofouling formation was strongly influenced by the kind of microorganism, the interactions between the organisms, and the changes in environmental conditions whereas the membrane effect was less important. The findings obtained in this study suggest that more knowledge in species composition and microbial interactions is needed in order to understand the complex biofouling process. This is the first report describing the microbial interactions with a membrane during the biofouling development.

  7. Explorative analysis of microbes, colloids and gases together with microbial modelling. Site description model SDM-Site Laxemar

    Energy Technology Data Exchange (ETDEWEB)

    Hallbeck, Lotta; Pedersen, Karsten (Microbial Analytics Sweden AB, Goeteborg (Sweden))

    2008-08-15

    The work has involved the development of descriptive and mathematical models for groundwaters in relation to rock domains, fracture domains and deformation zones. Past climate changes are the major driving force for hydrogeochemical changes and therefore of fundamental importance for understanding the palaeohydrogeological, palaeohydrogeochemical and present evolution of groundwater in the crystalline bedrock of the Fennoscandian Shield. Understanding current undisturbed hydrochemical conditions at the proposed repository site is important when predicting future changes in groundwater chemistry. The causes of copper corrosion and/or bentonite degradation are of particular interest as they may jeopardise the long-term integrity of the planned SKB repository system. Thus, the following variables are considered for the hydrogeochemical site descriptive modelling: pH, Eh, sulphur species, iron, manganese, carbonate, phosphate, nitrogen species, total dissolved solids (TDS), isotopes, colloids, fulvic and humic acids and microorganisms. In addition, dissolved gases (e.g. carbon dioxide, methane and hydrogen) are of interest because of their likely participation in microbial reactions. In this series of reports, the final hydrogeochemical evaluation work of the site investigation at the Laxemar site, is presented. The work was conducted by SKB's hydrogeochemical project group, ChemNet, which consists of independent consultants and Univ. researchers with expertise in geochemistry, hydrochemistry, hydrogeochemistry, microbiology, geomicrobiology, analytical chemistry etc. The resulting site descriptive model version, mainly based on available primary data from the extended data freeze L2.3 (Nov 2007). This report focuses on microbiology, colloids and gases. Several methods must be used to characterise active microbial communities in groundwater. Microbial parameters of interest are the total number of cells (TNC) and the presence of various metabolic groups of

  8. Genome-enabled Modeling of Microbial Biogeochemistry using a Trait-based Approach. Does Increasing Metabolic Complexity Increase Predictive Capabilities?

    Science.gov (United States)

    King, E.; Karaoz, U.; Molins, S.; Bouskill, N.; Anantharaman, K.; Beller, H. R.; Banfield, J. F.; Steefel, C. I.; Brodie, E.

    2015-12-01

    The biogeochemical functioning of ecosystems is shaped in part by genomic information stored in the subsurface microbiome. Cultivation-independent approaches allow us to extract this information through reconstruction of thousands of genomes from a microbial community. Analysis of these genomes, in turn, gives an indication of the organisms present and their functional roles. However, metagenomic analyses can currently deliver thousands of different genomes that range in abundance/importance, requiring the identification and assimilation of key physiologies and metabolisms to be represented as traits for successful simulation of subsurface processes. Here we focus on incorporating -omics information into BioCrunch, a genome-informed trait-based model that represents the diversity of microbial functional processes within a reactive transport framework. This approach models the rate of nutrient uptake and the thermodynamics of coupled electron donors and acceptors for a range of microbial metabolisms including heterotrophs and chemolithotrophs. Metabolism of exogenous substrates fuels catabolic and anabolic processes, with the proportion of energy used for cellular maintenance, respiration, biomass development, and enzyme production based upon dynamic intracellular and environmental conditions. This internal resource partitioning represents a trade-off against biomass formation and results in microbial community emergence across a fitness landscape. Biocrunch was used here in simulations that included organisms and metabolic pathways derived from a dataset of ~1200 non-redundant genomes reflecting a microbial community in a floodplain aquifer. Metagenomic data was directly used to parameterize trait values related to growth and to identify trait linkages associated with respiration, fermentation, and key enzymatic functions such as plant polymer degradation. Simulations spanned a range of metabolic complexities and highlight benefits originating from simulations

  9. Microbial communities involved in enhanced biological phosphorus removal from wastewater--a model system in environmental biotechnology.

    Science.gov (United States)

    Nielsen, Per Halkjær; Saunders, Aaron Marc; Hansen, Aviaja Anna; Larsen, Poul; Nielsen, Jeppe Lund

    2012-06-01

    Enhanced biological phosphorus removal (EBPR) is one of the most advanced and complicated wastewater treatment processes applied today, and it is becoming increasingly popular worldwide as a sustainable way to remove and potentially reuse P. It is carried out by complex microbial communities consisting primarily of uncultured microorganisms. The EBPR process is a well-studied system with clearly defined boundaries which makes it very suitable as a model ecosystem in microbial ecology. Of particular importance are the transformations of C, N, and P, the solid-liquid separation properties and the functional and structural stability. A range of modern molecular methods has been used to study these communities in great detail including single cell microbiology, various -omics methods, flux analyses, and modeling making this one of the best studied microbial ecosystems so far. Recently, an EBPR core microbiome has been described and we present in this article some highlights and show how this complex microbial community can be used as model ecosystem in environmental biotechnology.

  10. Incorporating microbial ecology into the metabolic modelling of polyphosphate accumulating organisms and glycogen accumulating organisms.

    Science.gov (United States)

    Oehmen, A; Carvalho, G; Lopez-Vazquez, C M; van Loosdrecht, M C M; Reis, M A M

    2010-09-01

    In the enhanced biological phosphorus removal (EBPR) process, the competition between polyphosphate accumulating organisms (PAO) and glycogen accumulating organisms (GAO) has been studied intensively in recent years by both microbiologists and engineers, due to its important effects on phosphorus removal performance and efficiency. This study addresses the impact of microbial ecology on assessing the PAO-GAO competition through metabolic modelling, focussing on reviewing recent developments, discussion of how the results from molecular studies can impact the way we model the process, and offering perspectives for future research opportunities based on unanswered questions concerning PAO and GAO metabolism. Indeed, numerous findings that are seemingly contradictory could in fact be explained by the metabolic behaviour of different sub-groups of PAOs and/or GAOs exposed to different environmental and operational conditions. Some examples include the glycolysis pathway (i.e. Embden-Meyerhof-Parnas (EMP) vs. Entner-Doudoroff (ED)), denitrification capacity, anaerobic tricarboxylic acid (TCA) cycle activity and PAOs' ability to adjust their metabolism to e.g. a GAO-like metabolism. Metabolic modelling may further yield far-reaching influences on practical applications as well, and serves as a bridge between molecular/biochemical research studies and the optimisation of wastewater treatment plant operation. Copyright © 2010 Elsevier Ltd. All rights reserved.

  11. Synthetic feedback loop model for increasing microbial biofuel production using a biosensor

    Directory of Open Access Journals (Sweden)

    Mary eHarrison

    2012-10-01

    Full Text Available Current biofuel production methods use engineered bacteria to break down cellulose and convert it to biofuel. A major challenge in microbial fuel production is that increasing biofuel yields can be limited by the toxicity of the biofuel to the organism that is producing it. Previous research has demonstrated that efflux pumps are effective at increasing tolerance to various biofuels. However, when overexpressed, efflux pumps burden cells, which hinders growth and slows biofuel production. Therefore, the toxicity of the biofuel must be balanced with the toxicity of pump overexpression. We have developed a mathematical model for cell growth and biofuel production that implements a synthetic feedback loop using a biosensor to control efflux pump expression. In this way, the production rate will be maximal when the concentration of biofuel is low because the cell does not expend energy expressing efflux pumps when they are not needed. Additionally, the microbe is able to adapt to toxic conditions by triggering the expression of efflux pumps, which allow it to continue biofuel production. Sensitivity analysis indicates that the feedback sensor model is insensitive to most system parameters, but a few key parameters can influence growth and production. In comparison to systems that express efflux pumps at a constant level, the feedback sensor increases overall biofuel production by delaying pump expression until it is needed. This result is more pronounced when model parameters are variable because the system can use feedback to adjust to the actual rate of biofuel production.

  12. Evaluation of factors influencing soluble microbial product in submerged MBR through hybrid ASM model

    Institute of Scientific and Technical Information of China (English)

    Fangyue LI; Joachim BEHRENDT; Knut WICHMANN; Ralf OTTERPOHL

    2009-01-01

    In this study, a mathematical model was established to predict the formation of the soluble microbial product (SMP) in a submerged membrane bioreaetor. The developed model was calibrated under the reference condition. Simulation results were in good agreement with the measured results under the reference condition. The calibrated model was then used in the scenario studies to evaluate the effect of three chosen operating parameters: hydraulic retention time (HRT),dissolved oxygen concentration, and sludge retention time (SRT). Simulation results revealed that the SMP dominated the soluble organic substances in the supernatant. The scenario studies also revealed that the HRT can be decreased to 1 h without deteriorating the effluent quality; dissolved oxygen concentration in the reactor can be kept at 2-3 mg/L to maintain the effluent quality, reduce the content of SMP, and minimize operating costs; the optimal SRT can be controlled to 10-15 d to achieve complete nitrification process, less membrane fouling potential, and acceptable organic removal efficiency.

  13. MbT-Tool: An open-access tool based on Thermodynamic Electron Equivalents Model to obtain microbial-metabolic reactions to be used in biotechnological process.

    Science.gov (United States)

    Araujo, Pablo Granda; Gras, Anna; Ginovart, Marta

    2016-01-01

    Modelling cellular metabolism is a strategic factor in investigating microbial behaviour and interactions, especially for bio-technological processes. A key factor for modelling microbial activity is the calculation of nutrient amounts and products generated as a result of the microbial metabolism. Representing metabolic pathways through balanced reactions is a complex and time-consuming task for biologists, ecologists, modellers and engineers. A new computational tool to represent microbial pathways through microbial metabolic reactions (MMRs) using the approach of the Thermodynamic Electron Equivalents Model has been designed and implemented in the open-access framework NetLogo. This computational tool, called MbT-Tool (Metabolism based on Thermodynamics) can write MMRs for different microbial functional groups, such as aerobic heterotrophs, nitrifiers, denitrifiers, methanogens, sulphate reducers, sulphide oxidizers and fermenters. The MbT-Tool's code contains eighteen organic and twenty inorganic reduction-half-reactions, four N-sources (NH4 (+), NO3 (-), NO2 (-), N2) to biomass synthesis and twenty-four microbial empirical formulas, one of which can be determined by the user (CnHaObNc). MbT-Tool is an open-source program capable of writing MMRs based on thermodynamic concepts, which are applicable in a wide range of academic research interested in designing, optimizing and modelling microbial activity without any extensive chemical, microbiological and programing experience.

  14. MbT-Tool: An open-access tool based on Thermodynamic Electron Equivalents Model to obtain microbial-metabolic reactions to be used in biotechnological process

    Directory of Open Access Journals (Sweden)

    Pablo Araujo Granda

    2016-01-01

    Full Text Available Modelling cellular metabolism is a strategic factor in investigating microbial behaviour and interactions, especially for bio-technological processes. A key factor for modelling microbial activity is the calculation of nutrient amounts and products generated as a result of the microbial metabolism. Representing metabolic pathways through balanced reactions is a complex and time-consuming task for biologists, ecologists, modellers and engineers. A new computational tool to represent microbial pathways through microbial metabolic reactions (MMRs using the approach of the Thermodynamic Electron Equivalents Model has been designed and implemented in the open-access framework NetLogo. This computational tool, called MbT-Tool (Metabolism based on Thermodynamics can write MMRs for different microbial functional groups, such as aerobic heterotrophs, nitrifiers, denitrifiers, methanogens, sulphate reducers, sulphide oxidizers and fermenters. The MbT-Tool's code contains eighteen organic and twenty inorganic reduction-half-reactions, four N-sources (NH4+, NO3−, NO2−, N2 to biomass synthesis and twenty-four microbial empirical formulas, one of which can be determined by the user (CnHaObNc. MbT-Tool is an open-source program capable of writing MMRs based on thermodynamic concepts, which are applicable in a wide range of academic research interested in designing, optimizing and modelling microbial activity without any extensive chemical, microbiological and programing experience.

  15. Integrating plant-microbe interactions to understand soil C stabilization with the MIcrobial-MIneral Carbon Stabilization model (MIMICS)

    Science.gov (United States)

    Grandy, Stuart; Wieder, Will; Kallenbach, Cynthia; Tiemann, Lisa

    2014-05-01

    If soil organic matter is predominantly microbial biomass, plant inputs that build biomass should also increase SOM. This seems obvious, but the implications fundamentally change how we think about the relationships between plants, microbes and SOM. Plant residues that build microbial biomass are typically characterized by low C/N ratios and high lignin contents. However, plants with high lignin contents and high C/N ratios are believed to increase SOM, an entrenched idea that still strongly motivates agricultural soil management practices. Here we use a combination of meta-analysis with a new microbial-explicit soil biogeochemistry model to explore the relationships between plant litter chemistry, microbial communities, and SOM stabilization in different soil types. We use the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, newly built upon the Community Land Model (CLM) platform, to enhance our understanding of biology in earth system processes. The turnover of litter and SOM in MIMICS are governed by the activity of r- and k-selected microbial groups and temperature sensitive Michaelis-Menten kinetics. Plant and microbial residues are stabilized short-term by chemical recalcitrance or long-term by physical protection. Fast-turnover litter inputs increase SOM by >10% depending on temperature in clay soils, and it's only in sandy soils devoid of physical protection mechanisms that recalcitrant inputs build SOM. These results challenge centuries of lay knowledge as well as conventional ideas of SOM formation, but are they realistic? To test this, we conducted a meta-analysis of the relationships between the chemistry of plant liter inputs and SOM concentrations. We find globally that the highest SOM concentrations are associated with plant inputs containing low C/N ratios. These results are confirmed by individual tracer studies pointing to greater stabilization of low C/N ratio inputs, particularly in clay soils. Our model and meta-analysis results suggest

  16. Reduced growth of Listeria monocytogenes in two model cheese microcosms is not associated with individual microbial strains.

    Science.gov (United States)

    Imran, Muhammad; Bré, Jean-Michel; Guéguen, Marielle; Vernoux, Jean-Paul; Desmasures, Nathalie

    2013-02-01

    Two model antilisterial microbial communities consisting of two yeasts, two Gram positive and two Gram negative bacteria, and originating from Livarot cheese smear were previously designed. They were used in the present study to analyse the impact of microbial population dynamics on growth of Listeria monocytogenes in cheese microcosm. Specific culture media and PCR primers were developed for simultaneous culture-dependent and real-time PCR quantification of strains belonging to Marinomonas sp., Paenibacillus sp., Staphylococcus equorum, Arthrobacter arilaitensis, Pseudomonas putida, Serratia liquefaciens, Candida natalensis, and Geotrichum candidum, in cheese microcosms. All strains were enumerated after 3, 5, 8 and 14 days at 15 °C. They established well at high counts in all cheese microcosms. Growth dynamics for all strains in presence of L. monocytogenes WSLC 1685 were compared to those of microbial communities obtained by omitting in turn one of the six members of the initial community. The growth of the microbial strains was neither markedly disturbed by Listeria presence nor by the removal of each strain in turn. Furthermore, these communities had a significant reducing effect on growth of L. monocytogenes independently of pH, as confirmed by mathematical modelling. A barrier effect was observed, that could be explained by specific competition for nutrients.

  17. Towards Predictive Modeling of Information Processing in Microbial Ecosystems With Quorum-Sensing Interactions

    Science.gov (United States)

    Yusufaly, Tahir; Boedicker, James

    Bacteria communicate using external chemical signals in a process known as quorum sensing. However, the efficiency of this communication is reduced by both limitations on the rate of diffusion over long distances and potential interference from neighboring strains. Therefore, having a framework to quantitatively predict how spatial structure and biodiversity shape information processing in bacterial colonies is important, both for understanding the evolutionary dynamics of natural microbial ecosystems, and for the rational design of synthetic ecosystems with desired computational properties. As a first step towards these goals, we implement a reaction-diffusion model to study the dynamics of a LuxI/LuxR quorum sensing circuit in a growing bacterial population. The spatiotemporal concentration profile of acyl-homoserine lactone (AHL) signaling molecules is analyzed, and used to define a measure of physical and functional signaling network connectivity. From this, we systematically investigate how different initial distributions of bacterial populations influence the subsequent efficiency of collective long-range signal propagation in the population. We compare our results with known experimental data, and discuss limitations and extensions to our modeling framework.-/abstract-

  18. A model for improving microbial biofuel production using a synthetic feedback loop

    Energy Technology Data Exchange (ETDEWEB)

    Dunlop, Mary; Keasling, Jay; Mukhopadhyay, Aindrila

    2011-07-14

    Cells use feedback to implement a diverse range of regulatory functions. Building synthetic feedback control systems may yield insight into the roles that feedback can play in regulation since it can be introduced independently of native regulation, and alternative control architectures can be compared. We propose a model for microbial biofuel production where a synthetic control system is used to increase cell viability and biofuel yields. Although microbes can be engineered to produce biofuels, the fuels are often toxic to cell growth, creating a negative feedback loop that limits biofuel production. These toxic effects may be mitigated by expressing efflux pumps that export biofuel from the cell. We developed a model for cell growth and biofuel production and used it to compare several genetic control strategies for their ability to improve biofuel yields. We show that controlling efflux pump expression directly with a biofuel-responsive promoter is a straight forward way of improving biofuel production. In addition, a feed forward loop controller is shown to be versatile at dealing with uncertainty in biofuel production rates.

  19. A mucosal model to study microbial biofilm development and anti-biofilm therapeutics

    Science.gov (United States)

    Anderson, Michele J.; Parks, Patrick J.; Peterson, Marnie L.

    2013-01-01

    Biofilms are a sessile colony of bacteria which adhere to and persist on surfaces. The ability of bacteria to form biofilms is considered a virulence factor, and in fact is central to the pathogenesis of some organisms. Biofilms are inherently resistant to chemotherapy and host immune responses. Clinically, biofilms are considered a primary cause of a majority of infections, such as otitis media, pneumonia in cystic fibrosis patients and endocarditis. However, the vast majority of the data on biofilm formation comes from traditional microtiter-based or flow displacement assays with no consideration given to host factors. These assays, which have been a valuable tool in high-throughput screening for biofilm-related factors, do not mimic a host-pathogen interaction and may contribute to an inappropriate estimation of the role of some factors in clinical biofilm formation. We describe the development of a novel ex vivo model of biofilm formation on a mucosal surface by an important mucosal pathogen, methicillin resistant S. aureus (MRSA). This model is being used for the identification of microbial virulence factors important in mucosal biofilm formation and novel anti-biofilm therapies. PMID:23246911

  20. Metabolic model reconstruction and analysis of an artificial microbial ecosystem for vitamin C production.

    Science.gov (United States)

    Ye, Chao; Zou, Wei; Xu, Nan; Liu, Liming

    2014-07-20

    An artificial microbial ecosystem (AME) consisting of Ketogulonicigenium vulgare and Bacillus megaterium is currently used in a two-step fermentation process for vitamin C production. In order to obtain a comprehensive understanding of the metabolic interactions between the two bacteria, a two-species stoichiometric metabolic model (iWZ-KV-663-BM-1055) consisting of 1718 genes, 1573 metabolites, and 1891 reactions (excluding exchange reactions) was constructed based on separate genome-scale metabolic models (GSMMs) of K. vulgare and B. megaterium. These two compartments (k and b) of iWZ-KV-663-BM-1055 shared 453 reactions and 548 metabolites. Compartment b was richer in subsystems than compartment k. In minimal media with glucose (MG), metabolite exchange between compartments was assessed by constraint-based analysis. Compartment b secreted essential amino acids, nucleic acids, vitamins and cofactors important for K. vulgare growth and biosynthesis of 2-keto-l-gulonic acid (2-KLG). Further research showed that when co-cultured with B. megaterium in l-sorbose-CSLP medium, the growth rate of K. vulgare and 2-KLG production were increased by 111.9% and 29.42%, respectively, under the constraints employed. Our study demonstrated that GSMMs and constraint-based methods can be used to decode the physiological features and inter-species interactions of AMEs used in industrial biotechnology, which will be of benefit for improving regulation and refinement in future industrial processes.

  1. Microbial ecology-based methods to characterize the bacterial communities of non-model insects.

    Science.gov (United States)

    Prosdocimi, Erica M; Mapelli, Francesca; Gonella, Elena; Borin, Sara; Crotti, Elena

    2015-12-01

    Among the animals of the Kingdom Animalia, insects are unparalleled for their widespread diffusion, diversity and number of occupied ecological niches. In recent years they have raised researcher interest not only because of their importance as human and agricultural pests, disease vectors and as useful breeding species (e.g. honeybee and silkworm), but also because of their suitability as animal models. It is now fully recognized that microorganisms form symbiotic relationships with insects, influencing their survival, fitness, development, mating habits and the immune system and other aspects of the biology and ecology of the insect host. Thus, any research aimed at deepening the knowledge of any given insect species (perhaps species of applied interest or species emerging as novel pests or vectors) must consider the characterization of the associated microbiome. The present review critically examines the microbiology and molecular ecology techniques that can be applied to the taxonomical and functional analysis of the microbiome of non-model insects. Our goal is to provide an overview of current approaches and methods addressing the ecology and functions of microorganisms and microbiomes associated with insects. Our focus is on operational details, aiming to provide a concise guide to currently available advanced techniques, in an effort to extend insect microbiome research beyond simple descriptions of microbial communities.

  2. Prebiotic effect of fructooligosaccharide in the simulator of the human intestinal microbial ecosystem (SHIME® model).

    Science.gov (United States)

    Sivieri, Katia; Morales, Martha L Villarreal; Saad, Susana M I; Adorno, Maria A Tallarico; Sakamoto, Isabel Kimiko; Rossi, Elizeu A

    2014-08-01

    Maintaining "gut health" is a goal for scientists throughout the world. Therefore, microbiota management models for testing probiotics, prebiotics, and synbiotics have been developed. The SHIME(®) model was used to study the effect of fructooligosaccharide (FOS) on the fermentation pattern of the colon microbiota. Initially, an inoculum prepared from human feces was introduced into the reactor vessels and stabilized over 2 weeks using a culture medium. This stabilization period was followed by a 2-week control period during which the microbiota was monitored. The microbiota was then subjected to a 4-week treatment period by adding 5 g/day-1 FOS to vessel one (the "stomach" compartment). Plate counts, Denaturing Gradient Gel Electrophoresis (DGGE), short-chain fatty acid (SCFA), and ammonium analyses were used to observe the influence of FOS treatment in simulated colon compartments. A significant increase (P<.01) in the Lactobacillus spp. and Bifidobacterium spp. populations was observed during the treatment period. The DGGE obtained showed the overall microbial community was changed in the ascending colon compartment of the SHIME reactor. FOS induced increase of the SCFA concentration (P<.05) during the treatment period, mainly due to significant increased levels of acetic and butyric acids. However, ammonium concentrations increased during the same period (P<.01). This study indicates the usefulness of in vitro methods that simulate the colon region as part of research towards the improvement of human health.

  3. Microbial Priming and Protected Carbon Responses to Elevated CO2 at Local to Global Scales: a New Modeling Approach

    Science.gov (United States)

    Sulman, B. N.; Oishi, C.; Shevliakova, E.; Pacala, S. W.

    2013-12-01

    The soil carbon formulations commonly used in global carbon cycle models and Earth System models (ESMs) are based on first-order decomposition equations, where turnover of carbon is determined only by the size of the carbon pool and empirical functions of responses to temperature and moisture. These models do not include microbial dynamics or protection of carbon in microaggregates and mineral complexes, making them incapable of simulating important soil processes like priming and the influence of soil physical structure on carbon turnover. We present a new soil carbon dynamics model - Carbon, Organisms, Respiration, and Protection in the Soil Environment (CORPSE) - that explicitly represents microbial biomass and protected carbon pools. The model includes multiple types of carbon with different chemically determined turnover rates that interact with a single dynamic microbial biomass pool, allowing the model to simulate priming effects. The model also includes the formation and turnover of protected carbon that is inaccessible to microbial decomposers. The rate of protected carbon formation increases with microbial biomass. CORPSE has been implemented both as a stand-alone model and as a component of the NOAA Geophysical Fluid Dynamics Laboratory (GFDL) ESM. We calibrated the model against measured soil carbon stocks from the Duke FACE experiment. The model successfully simulated the seasonal pattern of heterotrophic CO2 production. We investigated the roles of priming and protection in soil carbon accumulation by running the model using measured inputs of leaf litter, fine roots, and root exudates from the ambient and elevated CO2 plots at the Duke FACE experiment. Measurements from the experiment showed that elevated CO2 caused enhanced root exudation, increasing soil carbon turnover in the rhizosphere due to priming effects. We tested the impact of increased root exudation on soil carbon accumulation by comparing model simulations of carbon accumulation under

  4. Genome-Enabled Modeling of Biogeochemical Processes Predicts Metabolic Dependencies that Connect the Relative Fitness of Microbial Functional Guilds

    Science.gov (United States)

    Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Steefel, C. I.; Banfield, J. F.; Beller, H. R.; Anantharaman, K.; Ligocki, T. J.; Trebotich, D.

    2015-12-01

    Pore-scale processes mediated by microorganisms underlie a range of critical ecosystem services, regulating carbon stability, nutrient flux, and the purification of water. Advances in cultivation-independent approaches now provide us with the ability to reconstruct thousands of genomes from microbial populations from which functional roles may be assigned. With this capability to reveal microbial metabolic potential, the next step is to put these microbes back where they belong to interact with their natural environment, i.e. the pore scale. At this scale, microorganisms communicate, cooperate and compete across their fitness landscapes with communities emerging that feedback on the physical and chemical properties of their environment, ultimately altering the fitness landscape and selecting for new microbial communities with new properties and so on. We have developed a trait-based model of microbial activity that simulates coupled functional guilds that are parameterized with unique combinations of traits that govern fitness under dynamic conditions. Using a reactive transport framework, we simulate the thermodynamics of coupled electron donor-acceptor reactions to predict energy available for cellular maintenance, respiration, biomass development, and enzyme production. From metagenomics, we directly estimate some trait values related to growth and identify the linkage of key traits associated with respiration and fermentation, macromolecule depolymerizing enzymes, and other key functions such as nitrogen fixation. Our simulations were carried out to explore abiotic controls on community emergence such as seasonally fluctuating water table regimes across floodplain organic matter hotspots. Simulations and metagenomic/metatranscriptomic observations highlighted the many dependencies connecting the relative fitness of functional guilds and the importance of chemolithoautotrophic lifestyles. Using an X-Ray microCT-derived soil microaggregate physical model combined

  5. Comparative analysis and culturing of the microbial community of Aiptasia pallida, A Sea Anemone Model for Coral Biology

    KAUST Repository

    Binsarhan, Mohammad

    2016-01-01

    Recent works has highlighted the contribution of microbes to animal function. In this regard, the microbial community associated with corals has become a growing field of research in order to understand how microbes contribute to the host organisms’ response to environmental changes. It has been shown that microbes associated with corals have important functions in the coral holobiont such as immunity and nutrient assimilation. However, corals are notoriously difficult to work with. To this end, the sea anemone Aiptasia is becoming a model organism for coral symbiosis. Given the importance of host-­microbiome interactions, the topic of this thesis is to assess microbial structure of Aiptasia, culture prominent bacterial members, and compare bacterial community structure to corals. Different molecular methods have been applied using 16S rRNA bacterial gene fragments to characterize the microbial composition of Aiptasia. 16S rRNA gene sequence derived from cultured bacteria was compared to 16S rRNA gene sequences retrieved from native Red Sea Aiptasia. Inter-­individual as well as methodological differences were found to account for variance in microbiome composition. However, all approaches showed a highly abundant microbial taxon belonging to the genus Alteromonas in all samples. The Alteromonas species was successfully isolated for further research targeting microbiome selection mechanisms in Aiptasia. Future investigations by using different molecular tools will help to define the functions and relationship between the Aiptasia and its complex microbiome.

  6. Phototrophic Biofilm Assembly in Microbial-Mat-Derived Unicyanobacterial Consortia: Model Systems for the Study of Autotroph-Heterotroph Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Cole, Jessica K.; Hutchison, Janine R.; Renslow, Ryan S.; Kim, Young-Mo; Chrisler, William B.; Engelmann, Heather E.; Dohnalkova, Alice; Hu, Dehong; Metz, Thomas O.; Fredrickson, Jim K.; Lindemann, Stephen R.

    2014-04-07

    Though microbial autotroph-heterotroph interactions influence biogeochemical cycles on a global scale, the diversity and complexity of natural systems and their intractability to in situ environmental manipulation makes elucidation of the principles governing these interactions challenging. Examination of primary succession during phototrophic biofilm assembly provides a robust means by which to elucidate the dynamics of such interactions and determine their influence upon recruitment and maintenance of phylogenetic and functional diversity in microbial communities. We isolated and characterized two unicyanobacterial consortia from the Hot Lake phototrophic mat, quantifying the structural and community composition of their assembling biofilms. The same heterotrophs were retained in both consortia and included members of Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes, taxa frequently reported as consorts of microbial photoautotrophs. Cyanobacteria led biofilm assembly, eventually giving way to a late heterotrophic bloom. The consortial biofilms exhibited similar patterns of assembly, with the relative abundances of members of Bacteroidetes and Alphaproteobacteria increasing and members of Gammaproteobacteria decreasing as colonization progressed. Despite similar trends in assembly at higher taxa, the consortia exhibited substantial differences in community structure at the species level. These similar patterns of assembly with divergent community structures suggest that, while similar niches are created by the metabolism of the cyanobacteria, the resultant webs of autotroph-heterotroph and heterotroph-heterotroph interactions driving metabolic exchange are specific to each primary producer. Altogether, our data support these Hot Lake unicyanobacterial consortia as generalizable model systems whose simplicity and tractability permit the deciphering of community assembly principles relevant to natural microbial communities.

  7. Unravelling the metabolic impact of SBS-associated microbial dysbiosis: Insights from the piglet short bowel syndrome model

    Science.gov (United States)

    Pereira-Fantini, Prue M.; Byars, Sean G.; Pitt, James; Lapthorne, Susan; Fouhy, Fiona; Cotter, Paul D.; Bines, Julie E.

    2017-01-01

    Liver disease is a major source of morbidity and mortality in children with short bowel syndrome (SBS). SBS-associated microbial dysbiosis has recently been implicated in the development of SBS-associated liver disease (SBS-ALD), however the pathological implications of this association have not been explored. In this study high-throughput sequencing of colonic content from the well-validated piglet SBS-ALD model was examined to determine alterations in microbial communities, and concurrent metabolic alterations identified in urine samples via targeted mass spectrometry approaches (GC-MS, LC-MS, FIA-MS) further uncovered impacts of microbial disturbance on metabolic outcomes in SBS-ALD. Multi-variate analyses were performed to elucidate contributing SBS-ALD microbe and metabolite panels and to identify microbe-metabolite interactions. A unique SBS-ALD microbe panel was clearest at the genus level, with discriminating bacteria predominantly from the Firmicutes and Bacteroidetes phyla. The SBS-ALD metabolome included important alterations in the microbial metabolism of amino acids and the mitochondrial metabolism of branched chain amino acids. Correlation analysis defined microbe-metabolite clustering patterns unique to SBS-ALD and identified a metabolite panel that correlates with dysbiosis of the gut microbiome in SBS. PMID:28230078

  8. Microgradients of microbial oxygen consumption in a barley rhizosphere model system

    DEFF Research Database (Denmark)

    Højberg, Ole; Sorensen, J.

    1993-01-01

    was in turn 10 to 30 times higher than that in the rhizoplane. Both microbial respiration and oxygen uptake by the root varied between different roots. This was probably due to a between-root variation of the exudation rate for easily degradable carbon compounds supporting the microbial oxygen consumption.......A microelectrode technique was used to map the radial distribution of oxygen concentrations and oxygen consumption rates around single roots of 7- day-old barley seedlings. The seedlings were grown in gel-stabilized medium containing a nutrient solution, a soil extract, and an inert polymer. Oxygen...... consumption by microbial respiration in the rhizosphere (30 mm from the root) was determined by using Fick's laws of diffusion and an analytical approach with curve fitting to measured microprofiles of oxygen concentration. A marked increase of microbial respiration...

  9. Development of surrogate correlation models to predict trace organic contaminant oxidation and microbial inactivation during ozonation.

    Science.gov (United States)

    Gerrity, Daniel; Gamage, Sujanie; Jones, Darryl; Korshin, Gregory V; Lee, Yunho; Pisarenko, Aleksey; Trenholm, Rebecca A; von Gunten, Urs; Wert, Eric C; Snyder, Shane A

    2012-12-01

    The performance of ozonation in wastewater depends on water quality and the ability to form hydroxyl radicals (·OH) to meet disinfection or contaminant transformation objectives. Since there are no on-line methods to assess ozone and ·OH exposure in wastewater, many agencies are now embracing indicator frameworks and surrogate monitoring for regulatory compliance. Two of the most promising surrogate parameters for ozone-based treatment of secondary and tertiary wastewater effluents are differential UV(254) absorbance (ΔUV(254)) and total fluorescence (ΔTF). In the current study, empirical correlations for ΔUV(254) and ΔTF were developed for the oxidation of 18 trace organic contaminants (TOrCs), including 1,4-dioxane, atenolol, atrazine, bisphenol A, carbamazepine, diclofenac, gemfibrozil, ibuprofen, meprobamate, naproxen, N,N-diethyl-meta-toluamide (DEET), para-chlorobenzoic acid (pCBA), phenytoin, primidone, sulfamethoxazole, triclosan, trimethoprim, and tris-(2-chloroethyl)-phosphate (TCEP) (R(2) = 0.50-0.83) and the inactivation of three microbial surrogates, including Escherichia coli, MS2, and Bacillus subtilis spores (R(2) = 0.46-0.78). Nine wastewaters were tested in laboratory systems, and eight wastewaters were evaluated at pilot- and full-scale. A predictive model for OH exposure based on ΔUV(254) or ΔTF was also proposed.

  10. The antimicrobial potential of stevia in an in vitro microbial caries model.

    Science.gov (United States)

    Kishta-; Derani, Maryam; Neiva, Gisele F; Boynton, James R; Kim, Youngjoo E; Fontana, Margherita

    2016-04-01

    To determine the effect of stevia on caries development when incorporated into a cariogenic diet in a controlled microbial caries model. 56 bovine tooth specimens (4 x 4 mm) were divided into four groups, each secured in a caries-forming vessel. All vessels were placed on an electric stirrer inside a 37°C incubator. The specimens were inoculated with Streptococcus mutans, and exposed for 4 days to circulating cycles of tryptic soy broth supplemented with 5% sucrose-TSBS (three x/day), and a mineral wash solution. Between TSBS cycles (three x/day), each group received one of four experimental solutions: phosphate buffer (PBS-negative control), 0.5% stevia solution, 5% stevia solution, or 5% xylitol solution. Development of caries lesions was analyzed using enamel surface hardness. Difference in Vickers Hardness between pre and post-treatment was calculated to determine caries development. Plaque was dislodged from six specimens per group, and the CFU/ml calculated. Data were analyzed using ANOVA at 95% confidence level, and individual group differences calculated using Tukey's test. 5% xylitol resulted in significantly less plaque at the end of the study compared to PBS and 5% stevia, but not significantly different than 0.5% stevia. 5% stevia had significantly softer lesions than the other groups, while there was no significant difference in hardness scores between 5% xylitol, 0.5% stevia and PBS.

  11. Remarkable preservation of microbial mats in Neoproterozoic siliciclastic settings: Implications for Ediacaran taphonomic models

    Science.gov (United States)

    Callow, Richard H. T.; Brasier, Martin D.

    2009-10-01

    It is beyond doubt that the appearance of infaunal bioturbation and metazoan biomineralization across the Ediacaran-Cambrian transition irreversibly affected the nature of marine sediment architecture and biogeochemistry. Here we review those changes in relation to their likely effect upon the processes of fossil preservation, especially within siliciclastic sediments. Processes of soft-tissue preservation in siliciclastic settings from the Ediacaran Period, including microbes and microbial mats as well as Ediacaran macrofossils, are here reviewed within this context. Highlighted examples include the exceptional preservation of microbes found in association with wrinkle structures and Ediacaran macrofossils in England and Newfoundland (replicated by silicate minerals) and in the White Sea region of Russia (replicated by iron sulphide). These occurrences show that soft-tissue preservation in siliciclastic settings went well beyond that typical for Ediacaran macrofossils alone and also extended to similar modes of preservation in associated microbes. Using these new observations it can be argued that several existing explanations for Ediacaran fossil preservation can be united within a biogeochemical model that involves evolution of the sediment mixed layer across this transition.

  12. Kinetic modelling and microbial community assessment of anaerobic biphasic fixed film bioreactor treating distillery spent wash.

    Science.gov (United States)

    Acharya, Bhavik K; Pathak, Hilor; Mohana, Sarayu; Shouche, Yogesh; Singh, Vasdev; Madamwar, Datta

    2011-08-01

    Anaerobic digestion, microbial community structure and kinetics were studied in a biphasic continuously fed, upflow anaerobic fixed film reactor treating high strength distillery wastewater. Treatment efficiency of the bioreactor was investigated at different hydraulic retention times (HRT) and organic loading rates (OLR 5-20 kg COD m⁻³ d⁻¹). Applying the modified Stover-Kincannon model to the reactor, the maximum removal rate constant (U(max)) and saturation value constant (K(B)) were found to be 2 kg m⁻³ d⁻¹ and 1.69 kg m⁻³ d⁻¹ respectively. Bacterial community structures of acidogenic and methanogenic reactors were assessed using culture-independent analyses. Sequencing of 16S rRNA genes exhibited a total of 123 distinct operational taxonomic units (OTUs) comprising 49 from acidogenic reactor and 74 (28 of eubacteria and 46 of archaea) from methanogenic reactor. The findings reveal the role of Lactobacillus sp. (Firmicutes) as dominant acid producing organisms in acidogenic reactor and Methanoculleus sp. (Euryarchaeotes) as foremost methanogens in methanogenic reactor.

  13. Growth of Microbial Populations. Mathematical Modeling, Laboratory Exercises, and Model-Based Data Analysis

    Science.gov (United States)

    Juska, Alfonsas; Gedminiene, Genovaite; Ivanec, Ruta

    2006-01-01

    This paper has arisen as a result of teaching Models in Biology to undergraduates of Bioengineering at the Gediminas Technical University of Vilnius. The aim is to teach the students to use a fresh approach to the problems they are familiar with, to come up with an articulate verbal model after a mental effort, to express it in rigorous…

  14. Effects of marine microbial biofilms on the biocide release rate from antifouling paints – A model-based analysis

    DEFF Research Database (Denmark)

    Yebra, Diego Meseguer; Kiil, Søren; Weinell, Claus E.;

    2006-01-01

    The antifouling (AF) paint model of Kiil et al. [S. Kiil, C.E. Weinell, M.S. Pedersen, K. Dam-Johansen, Analysis of self-polishing antifouling paints using rotary experiments and mathematical modelling, Ind. Eng. Chem. Res. 40 (2001) 3906-3920] and the simplified biofilm. growth model of Gujer...... and Warmer [W. Gujer, O. Warmer, Modeling mixed population biofilms, in: W.G. Characklis, K.C. Marshall (Eds.), Biofilms, Wiley-Interscience, New York, 1990] are used to provide a reaction engineering-based insight to the effects of marine microbial slimes on biocide leaching and, to a minor extent...

  15. Microbial Performance of Food Safety Control and Assurance Activities in a Fresh Produce Processing Sector Measured Using a Microbial Assessment Scheme and Statistical Modeling

    DEFF Research Database (Denmark)

    Njage, Patrick Murigu Kamau; Sawe, Chemutai Tonui; Onyango, Cecilia Moraa

    2017-01-01

    Current approaches such as inspections, audits, and end product testing cannot detect the distribution and dynamics of microbial contamination. Despite the implementation of current food safety management systems, foodborne outbreaks linked to fresh produce continue to be reported. A microbial as...

  16. Evaluation of nitrogenous substrates such as peptones from fish:a new method based on Gompertz modeling of microbial growth.

    Science.gov (United States)

    Dufossé, L; De La Broise, D; Guerard, F

    2001-01-01

    Fish peptones from tuna, cod, salmon, and unspecified fish were compared with a casein one by using a new method based on Gompertz modeling of microbial growth. Cumulative results obtained from six species of bacteria, yeasts, and fungi showed that, in most cases, these fish peptones are very effective. Nevertheless, this study raised some questions about the standardization of fish raw material, the enzymatic hydrolysis of fish proteins, and the composition of the culture medium used for testing the peptones.

  17. Dynamics of development and dispersal in sessile microbial communities: examples from Pseudomonas aeruginosa and Pseudomonas putida model biofilms

    DEFF Research Database (Denmark)

    Klausen, M.; Gjermansen, Morten; Kreft, J.-U.;

    2006-01-01

    Surface-associated microbial communities in many cases display dynamic developmental patterns. Model biofilms formed by Pseudomonas aeruginosa and Pseudomonas putida in laboratory flow-chamber setups represent examples of such behaviour. Dependent on the experimental conditions the bacteria...... organisms do not possess comprehensive genetic programs for biofilm development. Instead the bacteria appear to have evolved a number of different mechanisms to optimize surface colonization, of which they express a subset in response to the prevailing environmental conditions. These mechanisms include...

  18. DEB modeling for nanotoxicology, microbial ecology, and environmental engineering. Comment on: ;Physics of metabolic organization; by Marko Jusup et al.

    Science.gov (United States)

    Holden, Patricia A.

    2017-03-01

    Jusup et al. [1] appeal to mathematical physicists, and to biologists, by providing the theoretical basis for dynamic energy budget (DEB) modeling of individual organisms and populations, while emphasizing model simplicity, universality, and applicability to real world problems. Comments herein regard the disciplinary tensions proposed by the authors and suggest that-in addition to important applications in eco- and specifically nano-toxicology-there are opportunities for DEB frameworks to inform relative complexity in microbial ecological process modeling. This commentary also suggests another audience for bridging DEB theory and application-engineers solving environmental problems.

  19. The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

    DEFF Research Database (Denmark)

    Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.

    2017-01-01

    analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed.Results: The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes...

  20. Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction: COMMUNITY DATA-DRIVEN METABOLIC NETWORK MODELING

    Energy Technology Data Exchange (ETDEWEB)

    Henry, Christopher S. [Division of Mathematics and Computer Science, Argonne National Laboratory, Argonne Illinois; Computation Institute, University of Chicago, Chicago Illinois; Bernstein, Hans C. [Biodetection Sciences, National Security Directorate, Pacific Northwest National Laboratory Richland Washington; Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland Washington; The Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, Pullman Washington; Weisenhorn, Pamela [Division of Mathematics and Computer Science, Argonne National Laboratory, Argonne Illinois; Division of Biosciences, Argonne National Laboratory, Argonne Illinois; Taylor, Ronald C. [Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland Washington; Lee, Joon-Yong [Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland Washington; Zucker, Jeremy [Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland Washington; Song, Hyun-Seob [Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland Washington

    2016-06-02

    Metabolic network modeling of microbial communities provides an in-depth understanding of community-wide metabolic and regulatory processes. Compared to single organism analyses, community metabolic network modeling is more complex because it needs to account for interspecies interactions. To date, most approaches focus on reconstruction of high-quality individual networks so that, when combined, they can predict community behaviors as a result of interspecies interactions. However, this conventional method becomes ineffective for communities whose members are not well characterized and cannot be experimentally interrogated in isolation. Here, we tested a new approach that uses community-level data as a critical input for the network reconstruction process. This method focuses on directly predicting interspecies metabolic interactions in a community, when axenic information is insufficient. We validated our method through the case study of a bacterial photoautotroph-heterotroph consortium that was used to provide data needed for a community-level metabolic network reconstruction. Resulting simulations provided experimentally validated predictions of how a photoautotrophic cyanobacterium supports the growth of an obligate heterotrophic species by providing organic carbon and nitrogen sources.

  1. Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil

    National Research Council Canada - National Science Library

    Arbel, Julyan; King, Catherine K; Raymond, Ben; Winsley, Tristrom; Mengersen, Kerrie L

    2015-01-01

    ...‐species toxicity tests. In this study, we apply a Bayesian nonparametric model to a soil microbial data set acquired across a hydrocarbon contamination gradient at the site of a fuel spill in Antarctica...

  2. A network model shows the importance of coupled processes in the microbial N cycle in the Cape Fear River Estuary

    Science.gov (United States)

    Hines, David E.; Lisa, Jessica A.; Song, Bongkeun; Tobias, Craig R.; Borrett, Stuart R.

    2012-06-01

    Estuaries serve important ecological and economic functions including habitat provision and the removal of nutrients. Eutrophication can overwhelm the nutrient removal capacity of estuaries and poses a widely recognized threat to the health and function of these ecosystems. Denitrification and anaerobic ammonium oxidation (anammox) are microbial processes responsible for the removal of fixed nitrogen and diminish the effects of eutrophication. Both of these microbial removal processes can be influenced by direct inputs of dissolved inorganic nitrogen substrates or supported by microbial interactions with other nitrogen transforming pathways such as nitrification and dissimilatory nitrate reduction to ammonium (DNRA). The coupling of nitrogen removal pathways to other transformation pathways facilitates the removal of some forms of inorganic nitrogen; however, differentiating between direct and coupled nitrogen removal is difficult. Network modeling provides a tool to examine interactions among microbial nitrogen cycling processes and to determine the within-system history of nitrogen involved in denitrification and anammox. To examine the coupling of nitrogen cycling processes, we built a nitrogen budget mass balance network model in two adjacent 1 cm3 sections of bottom water and sediment in the oligohaline portion of the Cape Fear River Estuary, NC, USA. Pathway, flow, and environ ecological network analyses were conducted to characterize the organization of nitrogen flow in the estuary and to estimate the coupling of nitrification to denitrification and of nitrification and DNRA to anammox. Centrality analysis indicated NH4+ is the most important form of nitrogen involved in removal processes. The model analysis further suggested that direct denitrification and coupled nitrification-denitrification had similar contributions to nitrogen removal while direct anammox was dominant to coupled forms of anammox. Finally, results also indicated that partial

  3. A New Approach to Predict Microbial Community Assembly and Function Using a Stochastic, Genome-Enabled Modeling Framework

    Science.gov (United States)

    King, E.; Brodie, E.; Anantharaman, K.; Karaoz, U.; Bouskill, N.; Banfield, J. F.; Steefel, C. I.; Molins, S.

    2016-12-01

    Characterizing and predicting the microbial and chemical compositions of subsurface aquatic systems necessitates an understanding of the metabolism and physiology of organisms that are often uncultured or studied under conditions not relevant for one's environment of interest. Cultivation-independent approaches are therefore important and have greatly enhanced our ability to characterize functional microbial diversity. The capability to reconstruct genomes representing thousands of populations from microbial communities using metagenomic techniques provides a foundation for development of predictive models for community structure and function. Here, we discuss a genome-informed stochastic trait-based model incorporated into a reactive transport framework to represent the activities of coupled guilds of hypothetical microorganisms. Metabolic pathways for each microbe within a functional guild are parameterized from metagenomic data with a unique combination of traits governing organism fitness under dynamic environmental conditions. We simulate the thermodynamics of coupled electron donor and acceptor reactions to predict the energy available for cellular maintenance, respiration, biomass development, and enzyme production. While `omics analyses can now characterize the metabolic potential of microbial communities, it is functionally redundant as well as computationally prohibitive to explicitly include the thousands of recovered organisms into biogeochemical models. However, one can derive potential metabolic pathways from genomes along with trait-linkages to build probability distributions of traits. These distributions are used to assemble groups of microbes that couple one or more of these pathways. From the initial ensemble of microbes, only a subset will persist based on the interaction of their physiological and metabolic traits with environmental conditions, competing organisms, etc. Here, we analyze the predicted niches of these hypothetical microbes and

  4. Riverine Dissolved Organic Matter Degradation Modeled Through Microbial Incubations of Vascular Plant Leachates

    Science.gov (United States)

    Harfmann, J.; Hernes, P.; Chuang, C. Y.

    2015-12-01

    Dissolved organic matter (DOM) contains as much carbon as is in the atmosphere, provides the main link between terrestrial and marine carbon reservoirs, and fuels the microbial food web. The fate and removal of DOM is a result of several complex conditions and processes, including photodegradation, sorption/desorption, dominant vascular plant sources, and microbial abundance. In order to better constrain factors affecting microbial degradation, laboratory incubations were performed using Sacramento River water for microbial inoculums and vascular plant leachates. Four vascular plant sources were chosen based on their dominance in the Sacramento River Valley: gymnosperm needles from Pinus sabiniana (foothill pine), angiosperm dicot leaves from Quercus douglassi (blue oak), angiosperm monocot mixed annual grasses, and angiosperm monocot mixed Schoenoplectus acutus (tule) and Typha spp. (cattails). Three concentrations of microbial inoculum were used for each plant material, ranging from 0.2% to 10%. Degradation was monitored as a function of time using dissolved organic carbon (DOC), UV-Vis absorbance, and fluorescent dissolved organic matter (fDOM), and was compared across vascular plant type and inoculum concentration.

  5. Temperature Modeling of an Oil-Contaminated Aquifer with Heat from microbial degradation

    Science.gov (United States)

    Warren, E.; Bekins, B. A.

    2016-12-01

    unsaturated zone. The model results further show that this microbial activity accounts for up to 1.6 °C of the increase in temperature observed while a smaller amount of heat comes from iron reduction in the groundwater at the site.

  6. Approach for estimating microbial growth and the biodegradation of hydrocarbon contaminants in subsoil based on field measurements: 1. Model development and verification.

    Science.gov (United States)

    Song, Dejun; Katayama, Arata

    2010-01-15

    An approach was developed to represent the microbial growth and corresponding biodegradation of hydrocarbons (HCs) during the natural attenuation process based on field measurements of in situ microbial biomass and residual HC concentrations in unsaturated subsurface soil. A kinetic model combining Monod and logistic kinetics represents microbial growth under the limitation of HCs as substrates and environmental factors at actual contaminated sites by the introduction of two new kinetic parameters, the effective rate and the self-limiting coefficient of microbial growth. The correspondence between microbial growth and the biodegradation of HCs in the soil is obtained by dividing the amount of HC and the corresponding degrading microbial groups into two classes: saturated HCs as inert components and aromatic HCs that form a contamination plume as dissolved components. The respiratory quinones were used as indicators of microbial biomass. The biodegradation capacity of contaminated sites was evaluated by the maximum microbial biomass obtained by field measurements, which is considered as the integrated results from measurements of HCs, degrading kinetics, and environmental factors at the site. The feasibility of the proposed approach was verified at two hypothetical contaminated sites. The results suggested that the proposed approach is feasible for application at actual HC-contaminated sites.

  7. PhyloChip microarray analysis reveals altered gastrointestinal microbial communities in a rat model of colonic hypersensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Nelson, T.A.; Holmes, S.; Alekseyenko, A.V.; Shenoy, M.; DeSantis, T.; Wu, C.H.; Andersen, G.L.; Winston, J.; Sonnenburg, J.; Pasricha, P.J.; Spormann, A.

    2010-12-01

    Irritable bowel syndrome (IBS) is a chronic, episodic gastrointestinal disorder that is prevalent in a significant fraction of western human populations; and changes in the microbiota of the large bowel have been implicated in the pathology of the disease. Using a novel comprehensive, high-density DNA microarray (PhyloChip) we performed a phylogenetic analysis of the microbial community of the large bowel in a rat model in which intracolonic acetic acid in neonates was used to induce long lasting colonic hypersensitivity and decreased stool water content and frequency, representing the equivalent of human constipation-predominant IBS. Our results revealed a significantly increased compositional difference in the microbial communities in rats with neonatal irritation as compared with controls. Even more striking was the dramatic change in the ratio of Firmicutes relative to Bacteroidetes, where neonatally irritated rats were enriched more with Bacteroidetes and also contained a different composition of species within this phylum. Our study also revealed differences at the level of bacterial families and species. The PhyloChip is a useful and convenient method to study enteric microflora. Further, this rat model system may be a useful experimental platform to study the causes and consequences of changes in microbial community composition associated with IBS.

  8. Transitioning from microbiome composition to microbial community interactions: the potential of the metaorganism Hydra as an experimental model

    Directory of Open Access Journals (Sweden)

    Peter Deines

    2016-10-01

    Full Text Available Animals are home to complex microbial communities, which are shaped through interactions within the community, interactions with the host, and through environmental factors. The advent of high-throughput sequencing methods has led to novel insights in changing patterns of community composition and structure. However, deciphering the different types of interactions among community members, with their hosts and their interplay with their environment is still a challenge of major proportion. The emerging fields of synthetic microbial ecology and community systems biology have the potential to decrypt these complex relationships. Studying host-associated microbiota across multiple spatial and temporal scales will bridge the gap between individual microorganism studies and large-scale whole community surveys. Here, we discuss the unique potential of Hydra as an emerging experimental model in microbiome research. Through in vivo, in vitro, and in silico approaches the interaction structure of host-associated microbial communities and the effects of the host on the microbiota and its interactions can be disentangled. Research in the model system Hydra can unify disciplines from molecular genetics to ecology, opening up the opportunity to discover fundamental rules that govern microbiome community stability.

  9. 微生物生长模型的极限环%Limit Cycles in a Microbial Growth Model

    Institute of Scientific and Technical Information of China (English)

    Minaya Villasana; 黄迅成

    2008-01-01

    A general microbial growth model is discussed in this paper. The conditions for the existence of periodical solutions, and the estimation of the perimeter and relative position of the limit cycles are obtained. These results are useful in the further study of the oscillation of the microbial growth systems.%讨论了一个一般的微生物生长模型的极限环问题.证明了周期解的存在条件,并估计了有关极限环的周长和相对位置.本文的结果对深入研究微生物生长系统的震荡现象是非常有用的.

  10. Raw-appearing Restructured fish models made with Sodium alginate or Microbial transglutaminase and effect of chilled storage

    Directory of Open Access Journals (Sweden)

    Helena Moreno

    2013-03-01

    Full Text Available Restructuring by adding Sodium Alginate or Microbial Transglutaminase (MTGase using cold gelation technology make it possible to obtain many different raw products from minced and/or chopped fish muscle that are suitable for being used as the basis of new restructured products with different physicochemical properties and even different compositions. Special consideration must be given to their shelf-life and the changes that may take place during chilling, both in visual appearance and physicochemical properties. After chilled storage, the restructured models made with different muscular particle size and composition at low temperature (5 °C, it was observed that microbial growth limited the shelf-life to 7-14 days. Mechanical properties increased (p 0.05 was detected during storage.

  11. The porous surface model, a novel experimental system for online quantitative observation of microbial processes under unsaturated conditions

    DEFF Research Database (Denmark)

    Dechesne, Arnaud; Or, D.; Gulez, Gamze

    2008-01-01

    Water is arguably the most important constituent of microbial microhabitats due to its control of physical and physiological processes critical to microbial activity. In natural environments, bacteria often live on unsaturated surfaces, in thin (micrometric) liquid films. Nevertheless...... of bacterial growth and activity under controlled unsaturated conditions. Bacteria are inoculated on a porous ceramic plate, wetted by a liquid medium. The thickness of the liquid film at the surface of the plate is set by imposing suction, corresponding to soil matric potential, to the liquid medium....... The utility of the PSM was demonstrated using Pseudomonas putida KT2440 tagged with gfp as a model bacterium. Single cells were inoculated at the surface of the PSM, and the rate at which colonies expanded laterally was measured for three matric potentials (–0.5, –1.2, and –3.6 kPa). The matric potential...

  12. Development of a log-quadratic model to describe microbial inactivation, illustrated by thermal inactivation of Clostridium botulinum.

    Science.gov (United States)

    Stone, G; Chapman, B; Lovell, D

    2009-11-01

    In the commercial food industry, demonstration of microbiological safety and thermal process equivalence often involves a mathematical framework that assumes log-linear inactivation kinetics and invokes concepts of decimal reduction time (D(T)), z values, and accumulated lethality. However, many microbes, particularly spores, exhibit inactivation kinetics that are not log linear. This has led to alternative modeling approaches, such as the biphasic and Weibull models, that relax strong log-linear assumptions. Using a statistical framework, we developed a novel log-quadratic model, which approximates the biphasic and Weibull models and provides additional physiological interpretability. As a statistical linear model, the log-quadratic model is relatively simple to fit and straightforwardly provides confidence intervals for its fitted values. It allows a D(T)-like value to be derived, even from data that exhibit obvious "tailing." We also showed how existing models of non-log-linear microbial inactivation, such as the Weibull model, can fit into a statistical linear model framework that dramatically simplifies their solution. We applied the log-quadratic model to thermal inactivation data for the spore-forming bacterium Clostridium botulinum and evaluated its merits compared with those of popular previously described approaches. The log-quadratic model was used as the basis of a secondary model that can capture the dependence of microbial inactivation kinetics on temperature. This model, in turn, was linked to models of spore inactivation of Sapru et al. and Rodriguez et al. that posit different physiological states for spores within a population. We believe that the log-quadratic model provides a useful framework in which to test vitalistic and mechanistic hypotheses of inactivation by thermal and other processes.

  13. Molecular ecology of microbial mats

    NARCIS (Netherlands)

    H. Bolhuis; M.S. Cretoiu; L.J. Stal

    2014-01-01

    Phototrophic microbial mats are ideal model systems for ecological and evolutionary analysis of highly diverse microbial communities. Microbial mats are small-scale, nearly closed, and self-sustaining benthic ecosystems that comprise the major element cycles, trophic levels, and food webs. The steep

  14. Early-life gut microbial colonization shapes Th1/Th2 balance in asthma model in BALB/c mice.

    Science.gov (United States)

    Qian, Li-Juan; Kang, Shu-Min; Xie, Jia-Li; Huang, Li; Wen, Quan; Fan, Yuan-Yuan; Lu, Li-Jun; Jiang, Li

    2017-06-17

    We aimed to investigate the effect of early-life diverse microbial exposures on gut microbial colonization in an OVA-induced asthma model in BALB/c mice. BALB/c mice were divided into 4 groups: A, offsprings were kept in a SPF environment during fetal, lactation, and childhood periods; B, offsprings were kept in the SPF environment during fetal and lactation periods, and kept in the general environment during childhood; C, offsprings were kept in the SPF environment only during fetal period, and then kept in the general environment; and D, offsprings were kept in the general environment during whole periods. The diversity of intestinal flora was analyzed using denaturing gradient gel electrophoresis. Mice were sensitized with OVA to establish an animal model of asthma. Then asthma-related inflammatory cytokines and histological analysis were performed. The diversity of intestinal microflora in group D was significantly higher than groups A, B and C at three days and three weeks after birth, and the diversity of intestinal microflora in groups C and D were significantly higher than groups A and B at five weeks after birth. The pathologic scores of OVA-induced asthmatic mice in group D were significantly lower than group A, and serum IFN-γ levels and the IFN-γ/IL-4 ratio in group D were significantly higher than group A. Exposure to diverse microbial environments in early life affects gut microbial colonization in BALB/c mice. The diversity of the intestinal flora in early life may prevent airway inflammation in asthma via regulating the Th1/Th2 balance.

  15. Statistical analysis and modeling of pelletized cultivation of Mucor circinelloides for microbial lipid accumulation.

    Science.gov (United States)

    Xia, Chunjie; Wei, Wei; Hu, Bo

    2014-04-01

    Microbial oil accumulation via oleaginous fungi has some potential benefits because filamentous fungi can form pellets during cell growth and these pellets are easier to harvest from the culture broth than individual cells. This research studied the effect of various culture conditions on the pelletized cell growth of Mucor circinelloides and its lipid accumulation. The results showed that cell pelletization was positively correlated to biomass accumulation; however, pellet size was negatively correlated to the oil content of the fungal biomass, possibly due to the mass transfer barriers generated by the pellet structure. How to control the size of the pellet is the key to the success of the pelletized microbial oil accumulation process.

  16. A model for microbial phosphorus cycling in bioturbated marine sediments: Significance for phosphorus burial in the early Paleozoic

    Science.gov (United States)

    Dale, Andrew W.; Boyle, Richard A.; Lenton, Timothy M.; Ingall, Ellery D.; Wallmann, Klaus

    2016-09-01

    A diagenetic model is used to simulate the diagenesis and burial of particulate organic carbon (Corg) and phosphorus (P) in marine sediments underlying anoxic versus oxic bottom waters. The latter are physically mixed by animals moving through the surface sediment (bioturbation) and ventilated by burrowing, tube-dwelling organisms (bioirrigation). The model is constrained using an empirical database including burial ratios of Corg with respect to organic P (Corg:Porg) and total reactive P (Corg:Preac), burial efficiencies of Corg and Porg, and inorganic carbon-to-phosphorus regeneration ratios. If Porg is preferentially mineralized relative to Corg during aerobic respiration, as many previous studies suggest, then the simulated Porg pool is found to be completely depleted. A modified model that incorporates the redox-dependent microbial synthesis of polyphosphates and Porg (termed the microbial P pump) allows preferential mineralization of the bulk Porg pool relative to Corg during both aerobic and anaerobic respiration and is consistent with the database. Results with this model show that P burial is strongly enhanced in sediments hosting fauna. Animals mix highly labile Porg away from the aerobic sediment layers where mineralization rates are highest, thereby mitigating diffusive PO43- fluxes to the bottom water. They also expand the redox niche where microbial P uptake occurs. The model was applied to a hypothetical shelf setting in the early Paleozoic; a time of the first radiation of benthic fauna. Results show that even shallow bioturbation at that time may have had a significant impact on P burial. Our model provides support for a recent study that proposed that faunal radiation in ocean sediments led to enhanced P burial and, possibly, a stabilization of atmospheric O2 levels. The results also help to explain Corg:Porg ratios in the geological record and the persistence of Porg in ancient marine sediments.

  17. Proteomics of Streptococcus gordonii within a model developing oral microbial community

    Directory of Open Access Journals (Sweden)

    Hendrickson Erik L

    2012-09-01

    Full Text Available Abstract Background Streptococcus gordonii is one of several species that can initiate the formation of oral biofilms that develop into the complex multispecies microbial communities referred to as dental plaque. It is in the context of dental plaque that periodontal pathogens such as Porphyromonas gingivalis cause disease. We have previously reported a whole cell quantitative proteomics investigation of P. gingivalis in a model dental plaque community of S. gordonii, P. gingivalis, and Fusobacterium nucleatum. Here we report the adaptation of S. gordonii to the same model. Results 1122 S. gordonii proteins were detected in S. gordonii control samples, 915 in communities with F. nucleatum, 849 with P. gingivalis, and 649 with all three organisms. Quantitative comparisons showed extensive proteome changes in association with F. nucleatum or P. gingivalis individually or both P. gingivalis and F. nucleatum together. The changes were species specific, though the P. gingivalis interaction may be dominant, indicated by large differences between the proteomes with F. nucleatum or P. gingivalis but limited changes between communities with P. gingivalis or both P. gingivalis and F. nucleatum. The results were inspected manually and an ontology analysis conducted using DAVID. Extensive changes were seen in nutrition pathways with increases in energy metabolism and changes in the resulting byproducts, while the acid and sugar repressed PTS (phosphoenolpyruvate dependent phosphotransferase system sugar transport systems showed decreases. These results were seen across all the multispecies samples, though with different profiles according to the partner species. F. nucleatum association decreased proteins for the metabolic end products acetate and ethanol but increased lactate, the primary source of acidity from streptococcal cultures. P. gingivalis containing samples had a reduction in levels of proteins for ethanol and formate but increased proteins for

  18. An integrated environmental modeling framework for performing quantitative microbial risk assessments

    Science.gov (United States)

    Standardized methods are often used to assess the likelihood of a human-health effect from exposure to a specified hazard, and inform opinions and decisions about risk management and communication. A Quantitative Microbial Risk Assessment (QMRA) is specifically adapted to detail potential human-heal...

  19. Teaching the Methodology of Science: The Utilization of Microbial Model Systems for Biometric Analysis.

    Science.gov (United States)

    Adamo, Joseph A.

    Students set in their ways are usually reluctant, as a general rule, to deal with open-ended investigative scenarios. In order to acquaint the student with the physical method and philosophical thought process of the discipline, the tone of the course must be set early on. The present study was conducted to develop scenarios and microbial model…

  20. A generic transport-reactive model for simulating microbially influenced mineral precipitation in porous medium

    NARCIS (Netherlands)

    Zhou, J.; Van Turnhout, A.G.; Heimovaara, T.J.; Afanasyev, M.

    2015-01-01

    The spatial and temporal distribution of precipitated minerals is one of the key factors governing various processes in the sub-surface environment, including microbially influenced corrosion (MIC) (Huang, 2002), bio-cementation (van Paassen et al., 2010) and sediment diagenesis (Paraska et al., 201

  1. Trend of Mathematical Models in Microbial Fuel Cell for Environmental Energy Refinery from Waste/Water

    Science.gov (United States)

    Oh, Sung Taek

    A microbial fuel cell (MFC) is a device to use for bio electrochemical energy production. Electrophilic bacteria produce electrons in their metabolic pathway and the electrons can be extracted and concentrated on electrode by the electric potential difference (i.e. Galvanic cell). The bio-electrode may provide new opportunities for the renewable energy in waste water/swage treatment plants.

  2. A generic transport-reactive model for simulating microbially influenced mineral precipitation in porous medium

    NARCIS (Netherlands)

    Zhou, J.; Van Turnhout, A.G.; Heimovaara, T.J.; Afanasyev, M.

    2015-01-01

    The spatial and temporal distribution of precipitated minerals is one of the key factors governing various processes in the sub-surface environment, including microbially influenced corrosion (MIC) (Huang, 2002), bio-cementation (van Paassen et al., 2010) and sediment diagenesis (Paraska et al.,

  3. Simulating microbial degradation of organic matter in a simple porous system using the 3-D diffusion based model MOSAIC

    Science.gov (United States)

    Monga, O.; Garnier, P.; Pot, V.; Coucheney, E.; Nunan, N.; Otten, W.; Chenu, C.

    2013-10-01

    This paper deals with the simulation of microbial degradation in soil within pore space at microscopic scale. Pore space was described using sphere network coming from a geometrical modeling algorithm. The biological model was improved regarding previous work in order to include transformation of dissolved organic compounds and diffusion processes. Our model was tested using experimental results of a simple substrate decomposition (Fructose) within a simple media (the sand). Diverse microbial communities were inoculated. Separated incubations in microcosms were carried out using 5 different bacterial communities at 2 different water potentials of -10 cm and -100 cm of water. We calibrated the biological parameters by means of experimental data obtained at high water content and we tested the model without any parameters change at low water content. Same as for experimental data, our simulation results showed the decrease in water content involved the decrease of mineralisation. The model was able to simulate the decrease of connectivity between substrate and microorganism due the decrease of water content.

  4. Simulating microbial degradation of organic matter in a simple porous system using the 3-D diffusion based model MOSAIC

    Directory of Open Access Journals (Sweden)

    O. Monga

    2013-10-01

    Full Text Available This paper deals with the simulation of microbial degradation in soil within pore space at microscopic scale. Pore space was described using sphere network coming from a geometrical modeling algorithm. The biological model was improved regarding previous work in order to include transformation of dissolved organic compounds and diffusion processes. Our model was tested using experimental results of a simple substrate decomposition (Fructose within a simple media (the sand. Diverse microbial communities were inoculated. Separated incubations in microcosms were carried out using 5 different bacterial communities at 2 different water potentials of −10 cm and −100 cm of water. We calibrated the biological parameters by means of experimental data obtained at high water content and we tested the model without any parameters change at low water content. Same as for experimental data, our simulation results showed the decrease in water content involved the decrease of mineralisation. The model was able to simulate the decrease of connectivity between substrate and microorganism due the decrease of water content.

  5. The Proteome of Dissimilatory Metal-reducing Microorganism Geobacter Sulfurreducens under Various Growth Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Ding, Y-H R.; Hixson, Kim K.; Giometti, Carol S.; Stanley, A; Esteve-Nunez, A; Khare, Tripti; Tollaksen, Sandra L.; Zhu, Wenhong; Adkins, Joshua N.; Lipton, Mary S.; Smith, Richard D.; Mester, Tunde; Lovley, Derek R.

    2006-05-16

    The global protein analysis of Geobacter sulfurreducens, a model for the Geobacter species that predominate in many Fe(III)-reducing subsurface environments, was characterized with ultra high pressure liquid chromatography and mass spectrometry using accurate mass and time (AMT) tags as well as with more traditional two-dimensional polyacrylamide gel electrophoresis (2-D PAGE). Cells were grown under eight different growth conditions in order to enhance the potential that genes would be expressed. Over 3,187 gene products, representing about 92% of the total predicted gene products in the genome, were detected. The AMT approach was able to identify a much higher number of proteins than could be detected with the 2-D PAGE approach. A high proportion of predicted proteins in most protein role categories were detected with the highest number of proteins identified in the hypothetical protein role category. Furthermore, 91 c-type cytochromes of 111 predicted genes in the G. sulfurreducens genome were identified. Localization studies indicated that computational predictions of cytochrome location were limited. Differences in the abundance of cytochromes and other proteins under different growth conditions provided information for future functional analysis of these proteins. These results demonstrate that a high percentage of the predicted proteins in the G. sulfurreducens genome are produced and that the AMT approach provides a rapid method for comparing differential expression of proteins under different growth conditions in this organism.

  6. The proteome of dissimilatory metal-reducing microorganism Geobacter sulfurreducens under various growth conditions.

    Science.gov (United States)

    Ding, Yan-Huai R; Hixson, Kim K; Giometti, Carol S; Stanley, Ann; Esteve-Núñez, Abraham; Khare, Tripti; Tollaksen, Sandra L; Zhu, Wenhong; Adkins, Joshua N; Lipton, Mary S; Smith, Richard D; Mester, Tünde; Lovley, Derek R

    2006-07-01

    The proteome of Geobacter sulfurreducens, a model for the Geobacter species that predominate in many Fe(III)-reducing subsurface environments, was characterized with ultra high-pressure liquid chromatography and mass spectrometry using accurate mass and time (AMT) tags as well as with more traditional two-dimensional polyacrylamide gel electrophoresis (2-D PAGE). Cells were grown under six different growth conditions in order to enhance the potential that a wide range of genes would be expressed. The AMT tag approach was able to identify a much greater number of proteins than could be detected with the 2-D PAGE approach. With the AMT approach over 3,000 gene products were identified, representing about 90% of the total predicted gene products in the genome. A high proportion of predicted proteins in most protein role categories were detected; the highest number of proteins was identified in the hypothetical protein role category. Furthermore, 91 c-type cytochromes of 111 predicted genes in the G. sulfurreducens genome were identified. Differences in the abundance of cytochromes and other proteins under different growth conditions provided information for future functional analysis of these proteins. These results demonstrate that a high percentage of the predicted proteins in the G. sulfurreducens genome are produced and that the AMT tag approach provides a rapid method for comparing differential expression of proteins under different growth conditions in this organism.

  7. Development and evaluation of the microbial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

    Science.gov (United States)

    Hong, Eun-Mi; Park, Yongeun; Muirhead, Richard; Pachepsky, Yakov

    2017-04-01

    Pathogenic microorganisms in recreational and irrigation waters remain the subject of concern. Water quality models are used to estimate microbial quality of water sources, to evaluate microbial contamination-related risks, to guide the microbial water quality monitoring, and to evaluate the effect of agricultural management on the microbial water quality. The Agricultural Policy/Environmental eXtender (APEX) is the watershed-scale water quality model that includes highly detailed representation of agricultural management. The APEX currently does not have microbial fate and transport simulation capabilities. The objective of this work was to develop the first APEX microbial fate and transport module that could use the APEX conceptual model of manure removal together with recently introduced conceptualizations of the in-stream microbial fate and transport. The module utilizes manure erosion rates found in the APEX. The total number of removed bacteria was set to the concentrations of bacteria in soil-manure mixing layer and eroded manure amount. Bacteria survival in soil-manure mixing layer was simulated with the two-stage survival model. Individual survival patterns were simulated for each manure application date. Simulated in-stream microbial fate and transport processes included the reach-scale passive release of bacteria with resuspended bottom sediment during high flow events, the transport of bacteria from bottom sediment due to the hyporheic exchange during low flow periods, the deposition with settling sediment, and the two-stage survival. Default parameter values were available from recently published databases. The APEX model with the newly developed microbial fate and transport module was applied to simulate seven years of monitoring data for the Toenepi watershed in New Zealand. The stream network of the watershed ran through grazing lands with the daily bovine waste deposition. Based on calibration and testing results, the APEX with the microbe module

  8. The Antarctic cryptoendolithic microbial ecosystem as a model for studying microbes in shale and coal

    Energy Technology Data Exchange (ETDEWEB)

    Vestal, J.R. (University of Cincinnati, Cincinnati, OH (USA). Dept. of Biological Sciences)

    1991-04-01

    In Antarctica, there exists a complete microbial ecosystem that lives hidden within the pore spaces of sandstone (cryptoendolithic). Studying microbes within this solid matrix has presented certain technical problems which have been overcome. This has allowed studies to be conducted that have shown the effects of the physical and chemical environment on growth and metabolism of the microbes in these rocks. Similar microbial communities have recently been discovered that can exist within the solid matrix of shale and coal. Even though the community and environment are different from the Antarctic microbes, many of the methods and hypotheses regarding their existence are the same. Answers to questions relating how and why these microbes exist in shale and coal may have important implications for coal desulfurization, or degradation of the shale matrix to release hydrocarbons. 40 refs., 1 fig., 1 tab.

  9. Modelling and simulation of double chamber microbial fuel cell. Cell voltage, power density and temperature variation with process parameters

    Energy Technology Data Exchange (ETDEWEB)

    Shankar, Ravi; Mondal, Prasenjit; Chand, Shri [Indian Institute of Technology Roorkee, Uttaranchal (India). Dept. of Chemical Engineering

    2013-11-01

    In the present paper steady state models of a double chamber glucose glutamic acid microbial fuel cell (GGA-MFC) under continuous operation have been developed and solved using Matlab 2007 software. The experimental data reported in a recent literature has been used for the validation of the models. The present models give prediction on the cell voltage and cell power density with 19-44% errors, which is less (up to 20%) than the errors on the prediction of cell voltage made in some recent literature for the same MFC where the effects of the difference in pH and ionic conductivity between anodic and cathodic solutions on cell voltage were not incorporated in model equations. It also describes the changes in anodic and cathodic chamber temperature due to the increase in substrate concentration and cell current density. Temperature profile across the membrane thickness has also been studied. (orig.)

  10. Establishment and metabolic analysis of a model microbial community for understanding trophic and electron accepting interactions of subsurface anaerobic environments

    Directory of Open Access Journals (Sweden)

    Yang Zamin K

    2010-05-01

    Full Text Available Abstract Background Communities of microorganisms control the rates of key biogeochemical cycles, and are important for biotechnology, bioremediation, and industrial microbiological processes. For this reason, we constructed a model microbial community comprised of three species dependent on trophic interactions. The three species microbial community was comprised of Clostridium cellulolyticum, Desulfovibrio vulgaris Hildenborough, and Geobacter sulfurreducens and was grown under continuous culture conditions. Cellobiose served as the carbon and energy source for C. cellulolyticum, whereas D. vulgaris and G. sulfurreducens derived carbon and energy from the metabolic products of cellobiose fermentation and were provided with sulfate and fumarate respectively as electron acceptors. Results qPCR monitoring of the culture revealed C. cellulolyticum to be dominant as expected and confirmed the presence of D. vulgaris and G. sulfurreducens. Proposed metabolic modeling of carbon and electron flow of the three-species community indicated that the growth of C. cellulolyticum and D. vulgaris were electron donor limited whereas G. sulfurreducens was electron acceptor limited. Conclusions The results demonstrate that C. cellulolyticum, D. vulgaris, and G. sulfurreducens can be grown in coculture in a continuous culture system in which D. vulgaris and G. sulfurreducens are dependent upon the metabolic byproducts of C. cellulolyticum for nutrients. This represents a step towards developing a tractable model ecosystem comprised of members representing the functional groups of a trophic network.

  11. Comparative Characterization of the Microbial Diversities of an Artificial Microbialite Model and a Natural Stromatolite ▿ †

    Science.gov (United States)

    Havemann, Stephanie A.; Foster, Jamie S.

    2008-01-01

    Microbialites are organosedimentary structures that result from the trapping, binding, and lithification of sediments by microbial mat communities. In this study we developed a model artificial microbialite system derived from natural stromatolites, a type of microbialite, collected from Exuma Sound, Bahamas. We demonstrated that the morphology of the artificial microbialite was consistent with that of the natural system in that there was a multilayer community with a pronounced biofilm on the surface, a concentrated layer of filamentous cyanobacteria in the top 5 mm, and a lithified layer of fused oolitic sand grains in the subsurface. The fused grain layer was comprised predominantly of the calcium carbonate polymorph aragonite, which corresponded to the composition of the Bahamian stromatolites. The microbial diversity of the artificial microbialites and that of natural stromatolites were also compared using automated ribosomal intergenic spacer analysis (ARISA) and 16S rRNA gene sequencing. The ARISA profiling indicated that the Shannon indices of the two communities were comparable and that the overall diversity was not significantly lower in the artificial microbialite model. Bacterial clone libraries generated from each of the three artificial microbialite layers and natural stromatolites indicated that the cyanobacterial and crust layers most closely resembled the ecotypes detected in the natural stromatolites and were dominated by Proteobacteria and Cyanobacteria. We propose that such model artificial microbialites can serve as experimental analogues for natural stromatolites. PMID:18836014

  12. Hydrodynamics of microbial filter feeding

    DEFF Research Database (Denmark)

    Nielsen, Lasse Tor; Asadzadeh, Seyed Saeed; Dölger, Julia

    2017-01-01

    Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequat...... predict how optimum filter mesh size increases with cell size in microbial filter feeders, a prediction that accords very well with observations. We expect our results to be of significance for small-scale biophysics and trait-based ecological modeling....

  13. Flow-through Column Experiments and Modeling of Microbially Mediated Cr(VI) Reduction at Hanford 100H

    Science.gov (United States)

    Yang, L.; Molins, S.; Beller, H. R.; Brodie, E. L.; Steefel, C.; Nico, P. S.; Han, R.

    2010-12-01

    Microbially mediated Cr(VI) reduction at the Hanford 100H area was investigated by flow-through column experiments. Three separate experiments were conducted to promote microbial activities associated with denitrification, iron and sulfate reduction, respectively. Replicate columns packed with natural sediments from the site under anaerobic environment were injected with 5mM Lactate as the electron donor and 5 μM Cr(VI) in all experiments. Sulfate and nitrate solutions were added to act as the main electron acceptors in the respective experiments, while iron columns relied on the indigenous sediment iron (and manganese) oxides as electron acceptors. Column effluent solutions were analyzed by IC and ICP-MS to monitor the microbial consumption/conversion of lactate and the associated Cr(VI) reduction. Biogeochemical reactive transport modeling was performed to gain further insights into the reaction mechanisms and Cr(VI) bioreduction rates. All experimental columns showed a reduction of the injected Cr(VI). Columns under denitrifying conditions showed the least Cr(VI) reduction at early stages (cell growth, and the smallest change in Cr(VI) concentrations during the course of the experiment. In contrast, columns under sulfate-reducing/fermentative conditions exhibited the greatest Cr(VI) reduction capacity. Two sulfate columns evolved to complete lactate fermentation with acetate and propionate produced in the column effluent after 40 days of experiments. These fermenting columns showed a complete removal of injected Cr(VI), visible precipitation of sulfide minerals, and a significant increase in effluent Fe and Mn concentrations. Reactive transport simulations suggested that direct reduction of Cr(VI) by Fe(II) and Mn(II) released from the sediment could account for the observed Cr(VI) removal. The biogeochemical modeling was employed to test two hypotheses that could explain the release of Fe(II) and Mn(II) from the column sediments: 1) acetate produced by lactate

  14. Modulation of the reactivity of multiheme cytochromes by site-directed mutagenesis: moving towards the optimization of microbial electrochemical technologies.

    Science.gov (United States)

    Alves, Alexandra S; Costa, Nazua L; Tien, Ming; Louro, Ricardo O; Paquete, Catarina M

    2017-01-01

    Dissimilatory metal-reducing bacteria perform extracellular electron transfer, a metabolic trait that is at the core of a wide range of biotechnological applications. To better understand how these microorganisms transfer electrons from their metabolism to an extracellular electron acceptor, it is necessary to characterize in detail the key players in this process, the multiheme c-type cytochromes. Shewanella oneidensis MR-1 is a model organism for studying extracellular electron transfer, where the heme protein referred to as small tetraheme cytochrome is one of the most abundant multiheme cytochromes found in the periplasmic space of this bacterium. The small tetraheme cytochrome is responsible for the delivery of electrons to the porin-cytochrome supercomplexes that permeate the outer-membrane and reduce metallic minerals or electrodes. In this work, well-established thermodynamic and kinetic models that discriminate the electron transfer activity of the four individual hemes were employed to characterize a set of single amino-acid mutants of the small tetraheme cytochrome and their interaction with small inorganic electron donors and acceptors. The results show that electrostatics play an important role in the reactivity of the small tetraheme cytochrome with small inorganic electron partners, in particularly in the kinetics of the electron transfer processes. This thorough exploration using site-directed mutants provides key mechanistic insights to guide the rational manipulation of the proteins that are key players in extracellular electron transfer processes, towards the improvement of microbial electrochemical applications using dissimilatory metal-reducing bacteria.

  15. Microbially enhanced dissolution and reductive dechlorination of PCE by a mixed culture: Model validation and sensitivity analysis

    Science.gov (United States)

    Chen, Mingjie; Abriola, Linda M.; Amos, Benjamin K.; Suchomel, Eric J.; Pennell, Kurt D.; Löffler, Frank E.; Christ, John A.

    2013-08-01

    Reductive dechlorination catalyzed by organohalide-respiring bacteria is often considered for remediation of non-aqueous phase liquid (NAPL) source zones due to cost savings, ease of implementation, regulatory acceptance, and sustainability. Despite knowledge of the key dechlorinators, an understanding of the processes and factors that control NAPL dissolution rates and detoxification (i.e., ethene formation) is lacking. A recent column study demonstrated a 5-fold cumulative enhancement in tetrachloroethene (PCE) dissolution and ethene formation (Amos et al., 2009). Spatial and temporal monitoring of key geochemical and microbial (i.e., Geobacter lovleyi and Dehalococcoides mccartyi strains) parameters in the column generated a data set used herein as the basis for refinement and testing of a multiphase, compositional transport model. The refined model is capable of simulating the reactive transport of multiple chemical constituents produced and consumed by organohalide-respiring bacteria and accounts for substrate limitations and competitive inhibition. Parameter estimation techniques were used to optimize the values of sensitive microbial kinetic parameters, including maximum utilization rates, biomass yield coefficients, and endogenous decay rates. Comparison and calibration of model simulations with the experimental data demonstrate that the model is able to accurately reproduce measured effluent concentrations, while delineating trends in dechlorinator growth and reductive dechlorination kinetics along the column. Sensitivity analyses performed on the optimized model parameters indicate that the rates of PCE and cis-1,2-dichloroethene (cis-DCE) transformation and Dehalococcoides growth govern bioenhanced dissolution, as long as electron donor (i.e., hydrogen flux) is not limiting. Dissolution enhancements were shown to be independent of cis-DCE accumulation; however, accumulation of cis-DCE, as well as column length and flow rate (i.e., column residence time

  16. Orenia metallireducens sp. nov. strain Z6, a Novel Metal-reducing Firmicute from the Deep Subsurface

    Energy Technology Data Exchange (ETDEWEB)

    Dong, Yiran; Sanford, Robert A.; Boyanov, Maxim I.; Kemner, Kenneth M.; Flynn, Theodore M.; O' Loughlin, Edward J.; Chang, Yun-juan; Locke, Randall A.; Weber, Joseph R.; Egan, Sheila M.; Mackie, Roderick I.; Cann, Isaac; Fouke, Bruce W.

    2016-08-26

    A novel halophilic and metal-reducing bacterium,Orenia metallireducensstrain Z6, was isolated from briny groundwater extracted from a 2.02 km-deep borehole in the Illinois Basin, IL. This organism shared 96% 16S rRNA gene similarity withOrenia marismortui, but demonstrated physiological properties previously unknown for this genus. In addition to exhibiting a fermentative metabolism typical of genusOrenia, strain Z6 reduces various metal oxides [Fe(III), Mn(IV), Co(III), and Cr(VI)] using H2as the electron donor. Strain Z6 actively reduced ferrihydrite over broad ranges of pH (6-9.6), salinity (0.4-3.5 M NaCl) and temperature (20-60 °C). At pH 6.5, strain Z6 also reduced more crystalline iron oxides such as lepidocrocite (γ-FeOOH), goethite (α-FeOOH) and hematite (α-Fe2O3). Analysis of X-ray absorption fine structure (XAFS) following Fe(III) reduction by strain Z6 revealed spectra from ferrous secondary mineral phases consistent with the precipitation of vivianite [Fe3(PO4)2] and siderite (FeCO3). The draft genome assembled for strain Z6 is 3.47 Mb in size and contains 3,269 protein-coding genes. Unlike the well understood iron-reducingShewanellaandGeobacterspecies, this organism lacks thec-type cytochromes for typical Fe(III) reduction. Strain Z6 represents the first bacterial species in the genusOrenia(orderHalanaerobiales) reported to reduce ferric iron minerals and other metal oxides. This microbe expands both the phylogenetic and physiological scope of iron-reducing microorganisms known to inhabit the deep subsurface and suggests new mechanisms for microbial iron reduction. These distinctions from otherOreniaspp. support the designation of strain Z6 as a new species,Orenia metallireducenssp. nov.

  17. Parseq: reconstruction of microbial transcription landscape from RNA-Seq read counts using state-space models.

    Science.gov (United States)

    Mirauta, Bogdan; Nicolas, Pierre; Richard, Hugues

    2014-05-15

    The most common RNA-Seq strategy consists of random shearing, amplification and high-throughput sequencing of the RNA fraction. Methods to analyze transcription level variations along the genome from the read count profiles generated by the RNA-Seq protocol are needed. We developed a statistical approach to estimate the local transcription levels and to identify transcript borders. This transcriptional landscape reconstruction relies on a state-space model to describe transcription level variations in terms of abrupt shifts and more progressive drifts. A new emission model is introduced to capture not only the read count variance inside a transcript but also its short-range autocorrelation and the fraction of positions with zero counts. The estimation relies on a particle Gibbs algorithm whose running time makes it more suited to microbial genomes. The approach outperformed read-overlapping strategies on synthetic and real microbial datasets. A program named Parseq is available at: http://www.lgm.upmc.fr/parseq/. bodgan.mirauta@upmc.fr Supplementary data are available at Bioinformatics online.

  18. Biphasic toxicodynamic features of some antimicrobial agents on microbial growth: a dynamic mathematical model and its implications on hormesis

    Directory of Open Access Journals (Sweden)

    Murado Miguel A

    2010-08-01

    Full Text Available Abstract Background In the present work, we describe a group of anomalous dose-response (DR profiles and develop a dynamic model that is able to explain them. Responses were obtained from conventional assays of three antimicrobial agents (nisin, pediocin and phenol against two microorganisms (Carnobacterium piscicola and Leuconostoc mesenteroides. Results Some of these anomalous profiles show biphasic trends which are usually attributed to hormetic responses. But they can also be explained as the result of the time-course of the response from a microbial population with a bimodal distribution of sensitivity to an effector, and there is evidence suggesting this last origin. In light of interest in the hormetic phenomenology and the possibility of confusing it with other phenomena, especially in the bioassay of complex materials we try to define some criteria which allow us to distinguish between sensu stricto hormesis and biphasic responses due to other causes. Finally, we discuss some problems concerning the metric of the dose in connection with the exposure time, and we make a cautionary suggestion about the use of bacteriocins as antimicrobial agents. Conclusions The mathematical model proposed, which combines the basis of DR theory with microbial growth kinetics, can generate and explain all types of anomalous experimental profiles. These profiles could also be described in a simpler way by means of bisigmoidal equations. Such equations could be successfully used in a microbiology and toxicology context to discriminate between hormesis and other biphasic phenomena.

  19. A new strategy of glucose supply in a microbial fermentation model

    Science.gov (United States)

    Kasbawati, Gunawan, A. Y.; Sidarto, K. A.; Hertadi, R.

    2015-09-01

    Strategy of glucose supply to achieve an optimal productivity of ethanol production of a yeast cell is one of the main features in a microbial fermentation process. Beside a known continuous glucose supply, in this study we consider a new supply strategy so called the on-off supply. An optimal control theory is applied to the fermentation system to find the optimal rate of glucose supply and time of supply. The optimization problem is solved numerically using Differential Evolutionary algorithm. We find two alternative solutions that we can choose to get the similar result: either long period process with low supply or short period process with high glucose supply.

  20. Phototrophic biofilm assembly in microbial-mat-derived unicyanobacterial consortia: model systems for the study of autotroph-heterotroph interactions

    Directory of Open Access Journals (Sweden)

    Jessica K Cole

    2014-04-01

    Full Text Available Microbial autotroph-heterotroph interactions influence biogeochemical cycles on a global scale, but the diversity and complexity of natural systems and their intractability to in situ manipulation make it challenging to elucidate the principles governing these interactions. The study of assembling phototrophic biofilm communities provides a robust means to identify such interactions and evaluate their contributions to the recruitment and maintenance of phylogenetic and functional diversity over time. To examine primary succession in phototrophic communities, we isolated two unicyanobacterial consortia from the microbial mat in Hot Lake, Washington, characterizing the membership and metabolic function of each consortium. We then analyzed the spatial structures and quantified the community compositions of their assembling biofilms. The consortia retained the same suite of heterotrophic species, identified as abundant members of the mat and assigned to Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes. Autotroph growth rates dominated early in assembly, yielding to increasing heterotroph growth rates late in succession. The two consortia exhibited similar assembly patterns, with increasing relative abundances of members from Bacteroidetes and Alphaproteobacteria concurrent with decreasing relative abundances of those from Gammaproteobacteria. Despite these similarities at higher taxonomic levels, the relative abundances of individual heterotrophic species were substantially different in the developing consortial biofilms. This suggests that, although similar niches are created by the cyanobacterial metabolisms, the resulting webs of autotroph-heterotroph and heterotroph-heterotroph interactions are specific to each primary producer. The relative simplicity and tractability of the Hot Lake unicyanobacterial consortia make them useful model systems for deciphering interspecies interactions and assembly principles relevant to natural

  1. Electronic properties of conductive pili of the metal-reducing bacterium Geobacter sulfurreducens probed by scanning tunneling microscopy

    Science.gov (United States)

    Veazey, Joshua P.; Reguera, Gemma; Tessmer, Stuart H.

    2011-12-01

    The metal-reducing bacterium Geobacter sulfurreducens produces conductive protein appendages known as “pilus nanowires” to transfer electrons to metal oxides and to other cells. These processes can be harnessed for the bioremediation of toxic metals and the generation of electricity in bioelectrochemical cells. Key to these applications is a detailed understanding of how these nanostructures conduct electrons. However, to the best of our knowledge, their mechanism of electron transport is not known. We used the capability of scanning tunneling microscopy (STM) to probe conductive materials with higher spatial resolution than other scanning probe methods to gain insights into the transversal electronic behavior of native, cell-anchored pili. Despite the presence of insulating cellular components, the STM topography resolved electronic molecular substructures with periodicities similar to those reported for the pilus shaft. STM spectroscopy revealed electronic states near the Fermi level, consistent with a conducting material, but did not reveal electronic states expected for cytochromes. Furthermore, the transversal conductance was asymmetric, as previously reported for assemblies of helical peptides. Our results thus indicate that the Geobacter pilus shaft has an intrinsic electronic structure that could play a role in charge transport.

  2. Influence of dormancy on microbial competition under intermittent substrate supply: insights from model simulations.

    Science.gov (United States)

    Stolpovsky, Konstantin; Fetzer, Ingo; Van Cappellen, Philippe; Thullner, Martin

    2016-06-01

    Most natural environments are characterized by frequent changes of their abiotic conditions. Microorganisms can respond to such changes by switching their physiological state between activity and dormancy allowing them to endure periods of unfavorable abiotic conditions. As a consequence, the competitiveness of microbial species is not simply determined by their growth performance under favorable conditions but also by their ability and readiness to respond to periods of unfavorable environmental conditions. The present study investigates the relevance of factors controlling the abundance and activity of individual bacterial species competing for an intermittently supplied substrate. For this purpose, numerical experiments were performed addressing the response of microbial systems to regularly applied feeding pulses. Simulation results show that community dynamics may exhibit a non-trivial link to the frequency of the external constraints and that for a certain combination of these environmental conditions coexistence of species is possible. The ecological implication of our results is that even non-dominant, neglected species can have a strong influence on realized species composition of dominant key species, due to their invisible presence enable the coexistence between important key species and by this affecting provided function of the system.

  3. Analysis and modelling of predation on biofilm activated sludge process: Influence on microbial distribution, sludge production and nutrient dosage.

    Science.gov (United States)

    Revilla, Marta; Galán, Berta; Viguri, Javier R

    2016-11-01

    The influence of predation on the biofilm activated sludge (BAS) process is studied using a unified model that incorporates hydrolysis and predation phenomena into the two stages of the BAS system: moving bed biofilm reactor pre-treatment (bacterial-predator stage) and activated sludge (predator stage). The unified model adequately describes the experimental results obtained in a cellulose and viscose full-scale wastewater plant and has been used to evaluate the role and contribution of predator microorganisms towards removal of COD, nutrient requirements, sludge production and microbial distribution. The results indicate that predation is the main factor responsible for the reduction of both nutrient requirements and sludge production. Furthermore, increasing the sludge retention time (SRT) does not influence the total biomass content in the AS reactor of a BAS process in two different industrial wastewater treatments.

  4. Integration of soil microbial processes in a reactive transport model for simulating effects of root-controlled water flow on carbon and nutrient cycling

    Science.gov (United States)

    Espeleta, J. F.; Cardon, Z. G.; Mayer, K. U.; Rastetter, E. B.; Neumann, R. B.

    2013-12-01

    The rhizosphere is a hotbed of microbial activity in terrestrial ecosystems, and numerous models of rhizosphere dynamics have been focused in two main arenas: (1) water flow and nutrient transport around roots, and (2) carbon and nutrient exchanges between roots and microbes. However, coupling of microbial processes with physical flow (water and nutrients) in soils around plant roots is key to understanding how water, carbon and nutrient cycles interact at different scales. In order to explore how spatial distribution and timing of water flow directed by plant roots shapes rhizosphere biogeochemical function, we have developed a mechanistic model that combines a microbial food web with dynamic water flow and associated solute transport (advection, diffusion and cation exchange). We used the flexibility of a previously developed code, MIN3P (a multicomponent reactive transport model developed for variably saturated porous media) and incorporated microbial processes of carbon and nitrogen uptake, assimilation and secretion; microbial growth and death; exo-enzyme production; protozoal grazing, and soil organic matter decomposition within a soil matrix. We focused our attention at the mm-spatial scale, exploring the interaction of temporal oscillations in the magnitude and direction of water flow with soil C and N gradients. In this first modeling step, we prescribed dynamic soil water content representative of the transpiration stream (soil water loss) and hydraulic redistribution (soil water gain), as well as the flux of carbon into the soil. Although we are still in the process of building explicit root and plant behavior into the model, our preliminary results suggest that the diel pulsing of water out/into the soil can potentially change patterns of microbial C/N limitation and soil N availability. We are currently expanding our model to include the effect of plant root processes (uptake and exudation) and investigating the mechanisms explaining the interplay

  5. Measuring and modeling C flux rates through the central metabolic pathways in microbial communities using position-specific 13C-labeled tracers

    Science.gov (United States)

    Dijkstra, P.; van Groenigen, K.; Hagerty, S.; Salpas, E.; Fairbanks, D. E.; Hungate, B. A.; KOCH, G. W.; Schwartz, E.

    2012-12-01

    The production of energy and metabolic precursors occurs in well-known processes such as glycolysis and Krebs cycle. We use position-specific 13C-labeled metabolic tracers, combined with models of microbial metabolic organization, to analyze the response of microbial community energy production, biosynthesis, and C use efficiency (CUE) in soils, decomposing litter, and aquatic communities. The method consists of adding position-specific 13C -labeled metabolic tracers to parallel soil incubations, in this case 1-13C and 2,3-13C pyruvate and 1-13C and U-13C glucose. The measurement of CO2 released from the labeled tracers is used to calculate the C flux rates through the various metabolic pathways. A simplified metabolic model consisting of 23 reactions is solved using results of the metabolic tracer experiments and assumptions of microbial precursor demand. This new method enables direct estimation of fundamental aspects of microbial energy production, CUE, and soil organic matter formation in relatively undisturbed microbial communities. We will present results showing the range of metabolic patterns observed in these communities and discuss results from testing metabolic models.

  6. The role of microbial diversity in the dynamics and stability of global methane consumption: microbial methane oxidation as a model-system for microbial ecology (ESF EuroDiversity METHECO)

    Science.gov (United States)

    Frenzel, P.; Metheco-Team

    2009-04-01

    Ecosystems collectively determine biogeochemical processes that regulate the Earth System. Loss of biodiversity is detrimental to ecosystems and therefore has been a central issue for environmental scientists. Although microorganisms form a major part of the Earth's biomass and biodiversity, and have a critical role in biogeochemistry and ecosystem functioning, they do not feature highly in ongoing debates about global biodiversity loss, global change and conservations issues. The neglect of microbial diversity in conservation issues is because microbial communities are regarded as being highly redundant, omnipresent, and therefore inextinguishable. This, however, is a misconception. Recently, the application of advanced molecular techniques has indicated that microbial communities display habitat preferences and are not universally distributed. Even the highly diverse microbial communities in soils can be affected by agricultural use, indicating that genetic erosion may potentially affect these communities as well. Moreover, many important environmental functions are catalyzed by specific groups of microbes with a very narrow ecological range. Recovery of these functional microbial communities after disturbance may take decades. Even if the species making up the community do not become extinct and eventually re-colonize an environment, the function and service to the biosphere is lost long enough to exert permanent, irreversible damage to the environment. Considering the global importance of microbes, combined with our ignorance of how the composition and functioning of these communities is affected, necessitates the assessment of the vulnerability and the resilience of microbial diversity. The latter is a pressing concern in biodiversity research and conservation policy, urgently needing attention in order to be able to anticipate environmental challenges we are facing. Our general hypothesis is: microbial diversity is linked to important ecosystem services and

  7. Development of a multi-classification neural network model to determine the microbial growth/no growth interface.

    Science.gov (United States)

    Fernández-Navarro, Francisco; Valero, Antonio; Hervás-Martínez, César; Gutiérrez, Pedro A; García-Gimeno, Rosa M; Zurera-Cosano, Gonzalo

    2010-07-15

    Boundary models have been recognized as useful tools to predict the ability of microorganisms to grow at limiting conditions. However, at these conditions, microbial behaviour can vary, being difficult to distinguish between growth or no growth. In this paper, the data from the study of Valero et al. [Valero, A., Pérez-Rodríguez, F., Carrasco, E., Fuentes-Alventosa, J.M., García-Gimeno, R.M., Zurera, G., 2009. Modelling the growth boundaries of Staphylococcus aureus: Effect of temperature, pH and water activity. International Journal of Food Microbiology 133 (1-2), 186-194] belonging to growth/no growth conditions of Staphylococcus aureus against temperature, pH and a(w) were divided into three categorical classes: growth (G), growth transition (GT) and no growth (NG). Subsequently, they were modelled by using a Radial Basis Function Neural Network (RBFNN) in order to create a multi-classification model that was able to predict the probability of belonging at one of the three mentioned classes. The model was developed through an over sampling procedure using a memetic algorithm (MA) in order to balance in part the size of the classes and to improve the accuracy of the classifier. The multi-classification model, named Smote Memetic Radial Basis Function (SMRBF) provided a quite good adjustment to data observed, being able to correctly classify the 86.30% of training data and the 82.26% of generalization data for the three observed classes in the best model. Besides, the high number of replicates per condition tested (n=30) produced a smooth transition between growth and no growth. At the most stringent conditions, the probability of belonging to class GT was higher, thus justifying the inclusion of the class in the new model. The SMRBF model presented in this study can be used to better define microbial growth/no growth interface and the variability associated to these conditions so as to apply this knowledge to a food safety in a decision-making process.

  8. Characterization of wastewater treatment plant microbial communities and the effects of carbon sources on diversity in laboratory models.

    Directory of Open Access Journals (Sweden)

    Sangwon Lee

    Full Text Available We are developing a laboratory-scale model to improve our understanding and capacity to assess the biological risks of genetically engineered bacteria and their genetic elements in the natural environment. Our hypothetical scenario concerns an industrial bioreactor failure resulting in the introduction of genetically engineered bacteria to a downstream municipal wastewater treatment plant (MWWTP. As the first step towards developing a model for this scenario, we sampled microbial communities from the aeration basin of a MWWTP at three seasonal time points. Having established a baseline for community composition, we investigated how the community changed when propagated in the laboratory, including cell culture media conditions that could provide selective pressure in future studies. Specifically, using PhyloChip 16S-rRNA-gene targeting microarrays, we compared the compositions of sampled communities to those of inocula propagated in the laboratory in simulated wastewater conditionally amended with various carbon sources (glucose, chloroacetate, D-threonine or the ionic liquid 1-ethyl-3-methylimidazolium chloride ([C2mim]Cl. Proteobacteria, Bacteroidetes, and Actinobacteria were predominant in both aeration basin and laboratory-cultured communities. Laboratory-cultured communities were enriched in γ-Proteobacteria. Enterobacteriaceae, and Aeromonadaceae were enriched by glucose, Pseudomonadaceae by chloroacetate and D-threonine, and Burkholderiacea by high (50 mM concentrations of chloroacetate. Microbial communities cultured with chloroacetate and D-threonine were more similar to sampled field communities than those cultured with glucose or [C2mim]Cl. Although observed relative richness in operational taxonomic units (OTUs was lower for laboratory cultures than for field communities, both flask and reactor systems supported phylogenetically diverse communities. These results importantly provide a foundation for laboratory models of industrial

  9. Impact of plant species evenness, dominant species identity and spatial arrangement on the structure and functioning of soil microbial communities in a model grassland.

    Science.gov (United States)

    Massaccesi, L; Bardgett, R D; Agnelli, A; Ostle, N; Wilby, A; Orwin, K H

    2015-03-01

    Plant communities, through species richness and composition, strongly influence soil microorganisms and the ecosystem processes they drive. To test the effects of other plant community attributes, such as the identity of dominant plant species, evenness, and spatial arrangement, we set up a model mesocosm experiment that manipulated these three attributes in a full factorial design, using three grassland plant species (Anthoxanthum odoratum, Plantago lanceolata, and Lotus corniculatus). The impact of the three community attributes on the soil microbial community structure and functioning was evaluated after two growing seasons by ester-linked phospholipid fatty-acids analysis, substrate-induced respiration, basal respiration, and nitrogen mineralization and nitrification rates. Our results suggested that the dominant species identity had the most prevalent influence of the three community attributes, with significant effects on most of the measured aspects of microbial biomass, composition and functioning. Evenness had no effects on microbial community structure, but independently influenced basal respiration. Its effects on nitrogen cycling depended on the identity of the dominant plant species, indicating that interactions among species and their effects on functioning can vary with their relative abundance. Systems with an aggregated spatial arrangement had a different microbial community composition and a higher microbial biomass compared to those with a random spatial arrangement, but rarely differed in their functioning. Overall, it appears that dominant species identity was the main driver of soil microorganisms and functioning in these model grassland communities, but that other plant community attributes such as evenness and spatial arrangement can also be important.

  10. Comparison of microbial adherence to antiseptic and antibiotic central venous catheters using a novel agar subcutaneous infection model.

    Science.gov (United States)

    Gaonkar, Trupti A; Modak, Shanta M

    2003-09-01

    An agar subcutaneous infection model (agar model), which simulates the rat subcutaneous infection model (rat model), was developed to assess the ability of antimicrobial catheters to resist microbial colonization. The catheters were implanted in the agar and rat models and the insertion sites were infected immediately or on day 7, 14 or 21 post-implantation. The catheters implanted in the agar model were transferred to fresh media one day before infection on day 7, 14 or 21. The efficacy of chlorhexidine and silver sulfadiazine impregnated (CS) catheters, CS catheters with higher levels of chlorhexidine (CS+ catheters), minocycline-rifampicin (MR) catheters and silver catheters against Staphylococcus aureus and rifampicin-resistant Staphylococcus epidermidis RIF-r2 was compared in the agar and rat models. No significant difference in the adherence or the drug release was found between the in vitro and in vivo models. In both models, CS+ and MR catheters were effective against S. aureus even when infected on day 14, whereas CS catheters were colonized when challenged on day 7. CS+ catheters were effective against S. epidermidis RIF-r2, whereas MR catheters showed adherence when infected on day 7. CS+ catheters prevented colonization of all the organisms including, Enterobacter aerogenes, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Candida albicans in the agar model, whereas MR catheters were effective only against S. aureus and S. epidermidis strains. Silver catheters were ineffective against all the organisms. The agar model may be used to predict the in vivo efficacy of antimicrobial catheters against various pathogens.

  11. Models of the behaviour of (thermally stressed) microbial spores in foods: tools to study mechanisms of damage and repair.

    Science.gov (United States)

    Ter Beek, Alex; Hornstra, Luc M; Pandey, Rachna; Kallemeijn, Wouter W; Smelt, Jan P P M; Manders, Erik M M; Brul, Stanley

    2011-06-01

    The 'Omics' revolution has brought a wealth of new mechanistic insights in many fields of biology. It offers options to base predictions of microbial behaviour on mechanistic insight. As the cellular mechanisms involved often turn out to be highly intertwined it is crucial that model development aims at identifying the level of complexity that is relevant to work at. For the prediction of microbiologically stable foods insight in the behaviour of bacterial spore formers is crucial. Their chances of germination and likelihood of outgrowth are major food stability indicators, as well as the transition from outgrowth to first cell division and vegetative growth. Current available technology to assess these parameters in a time-resolved manner at the single spore level will be discussed. Tools to study molecular processes operative in heat induced damage will be highlighted.

  12. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    Science.gov (United States)

    Tartakovsky, G. D.; Tartakovsky, A. M.; Scheibe, T. D.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

    2013-09-01

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model

  13. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    Energy Technology Data Exchange (ETDEWEB)

    Tartakovsky, Guzel D.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.; Fang, Yilin; Mahadevan, Radhakrishnan; Lovley, Derek R.

    2013-09-07

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparisonto prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under

  14. Simulating microbial degradation of organic matter in a simple porous system using the 3-D diffusion-based model MOSAIC

    Science.gov (United States)

    Monga, O.; Garnier, P.; Pot, V.; Coucheney, E.; Nunan, N.; Otten, W.; Chenu, C.

    2014-04-01

    This paper deals with the simulation of microbial degradation of organic matter in soil within the pore space at a microscopic scale. Pore space was analysed with micro-computed tomography and described using a sphere network coming from a geometrical modelling algorithm. The biological model was improved regarding previous work in order to include the transformation of dissolved organic compounds and diffusion processes. We tested our model using experimental results of a simple substrate decomposition experiment (fructose) within a simple medium (sand) in the presence of different bacterial strains. Separate incubations were carried out in microcosms using five different bacterial communities at two different water potentials of -10 and -100 cm of water. We calibrated the biological parameters by means of experimental data obtained at high water content, and we tested the model without changing any parameters at low water content. Same as for the experimental data, our simulation results showed that the decrease in water content caused a decrease of mineralization rate. The model was able to simulate the decrease of connectivity between substrate and microorganism due the decrease of water content.

  15. Model for the study of the impact of atmospheric heavy metals on soil microbial biomass

    Energy Technology Data Exchange (ETDEWEB)

    Marchionni, M.; Benedetti, A. [Istituto Sperimentale per la Nutrizione delle Piante, Rome (Italy); Riccardi, C.; Villarini, M. [Istituto Superiore per la Sicurezza e la Prevenzione del Lavoro, Rome (Italy)

    2000-12-01

    In the Castelporziano (Rome) protected area the inputs of atmospheric heavy metals on the soil-plant system were evaluated by the analysis of stem-flowing water from Quercus ilex L. The heavy metals detected in the soil under the canopies exhibited higher concentrations near to the tree trunks, highlighting the tree's capacity to concentrate such polluting substances. Microbial biomass, its specific respiration and the biomass calculated as a percentage of total soil organic matter, were utilised as indicators of the state of the soil and consequently also its quality with respect to heavy metal contamination. [Italian] Nell'area protetta di Castelporziano (Roma) e' stato valutato l'apporto dei metalli pesanti di origine atmosferica al sistema suolo-pianta analizzando le acque dilavanti di alberi d'alto fusto (Quercus ilex L.). I metalli pesanti rilevati nel suolo sottochioma presentano una piu' alta concentrazione in prossimita' del fusto, evidenziando la capacita' dell'albero di concentrare tali inquinanti. La biomassa microbica, la sua respirazione specifica e la biomassa espressa come percentuale della sostanza organica totale del suolo, sono state utilizzate quali indicatori dello stato del suolo, quindi della sua qualita', rispetto alla contaminazione da metalli pesanti.

  16. Quantitative microbial risk assessment combined with hydrodynamic modelling to estimate the public health risk associated with bathing after rainfall events.

    Science.gov (United States)

    Eregno, Fasil Ejigu; Tryland, Ingun; Tjomsland, Torulv; Myrmel, Mette; Robertson, Lucy; Heistad, Arve

    2016-04-01

    This study investigated the public health risk from exposure to infectious microorganisms at Sandvika recreational beaches, Norway and dose-response relationships by combining hydrodynamic modelling with Quantitative Microbial Risk Assessment (QMRA). Meteorological and hydrological data were collected to produce a calibrated hydrodynamic model using Escherichia coli as an indicator of faecal contamination. Based on average concentrations of reference pathogens (norovirus, Campylobacter, Salmonella, Giardia and Cryptosporidium) relative to E. coli in Norwegian sewage from previous studies, the hydrodynamic model was used for simulating the concentrations of pathogens at the local beaches during and after a heavy rainfall event, using three different decay rates. The simulated concentrations were used as input for QMRA and the public health risk was estimated as probability of infection from a single exposure of bathers during the three consecutive days after the rainfall event. The level of risk on the first day after the rainfall event was acceptable for the bacterial and parasitic reference pathogens, but high for the viral reference pathogen at all beaches, and severe at Kalvøya-small and Kalvøya-big beaches, supporting the advice of avoiding swimming in the day(s) after heavy rainfall. The study demonstrates the potential of combining discharge-based hydrodynamic modelling with QMRA in the context of bathing water as a tool to evaluate public health risk and support beach management decisions. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. A Pilot Study on Integrating Videography and Environmental Microbial Sampling to Model Fecal Bacterial Exposures in Peri-Urban Tanzania.

    Directory of Open Access Journals (Sweden)

    Timothy R Julian

    Full Text Available Diarrheal diseases are a leading cause of under-five mortality and morbidity in sub-Saharan Africa. Quantitative exposure modeling provides opportunities to investigate the relative importance of fecal-oral transmission routes (e.g. hands, water, food responsible for diarrheal disease. Modeling, however, requires accurate descriptions of individuals' interactions with the environment (i.e., activity data. Such activity data are largely lacking for people in low-income settings. In the present study, we collected activity data and microbiological sampling data to develop a quantitative microbial exposure model for two female caretakers in peri-urban Tanzania. Activity data were combined with microbiological data of contacted surfaces and fomites (e.g. broom handle, soil, clothing to develop example exposure profiles describing second-by-second estimates of fecal indicator bacteria (E. coli and enterococci concentrations on the caretaker's hands. The study demonstrates the application and utility of video activity data to quantify exposure factors for people in low-income countries and apply these factors to understand fecal contamination exposure pathways. This study provides both a methodological approach for the design and implementation of larger studies, and preliminary data suggesting contacts with dirt and sand may be important mechanisms of hand contamination. Increasing the scale of activity data collection and modeling to investigate individual-level exposure profiles within target populations for specific exposure scenarios would provide opportunities to identify the relative importance of fecal-oral disease transmission routes.

  18. Single-walled carbon nanotube release affects the microbial enzyme-catalyzed oxidation processes of organic pollutants and lignin model compounds in nature.

    Science.gov (United States)

    Chen, Ming; Qin, Xiaosheng; Zeng, Guangming

    2016-11-01

    The question how microbial enzyme-catalyzed oxidation processes of organic pollutants and lignin model compounds (LMCs) are affected by the release of single-walled carbon nanotube (SWCNT) into the environment remains to be addressed at the molecular level. We have, therefore concentrated the effects of SWCNT on some important properties associated with enzyme activity and function during microbial oxidation of polycyclic aromatic hydrocarbons (benzo(a)pyrene, acenaphthene and anthracene), LMCs (2,6-dimethoxyphenol, guaiacol and veratryl alcohol) and β-hexachlorocyclohexane, including the behaviour of water molecules, hydrogen bonds (HBs) and hydrophobic interactions (HYs) between ligand and the enzyme, and conformational dynamics in N- and C-terminus. Our study revealed that SWCNT significantly affected the behaviour of water molecules within 5 Å of both these substrates and their respective enzymes during oxidation (p microbial enzyme-catalyzed processes of organic pollutants and LMCs in nature.

  19. Modeling how soluble microbial products (SMP) support heterotrophic bacteria in autotroph-based biofilms

    DEFF Research Database (Denmark)

    Merkey, Brian; Rittmann, Bruce E.; Chopp, David L.

    2009-01-01

    Multi-species biofilm modeling has been used for many years to understand the interactions between species in different biofilm systems, but the complex symbiotic relationship between species is sometimes overlooked, because models do not always include all relevant species and components....... In this paper, we develop and use a mathematical model to describe a model biofilm system that includes autotrophic and heterotrophic bacteria and the key products produced by the bacteria. The model combines the methods of earlier multi-species models with a multi-component biofilm model in order to explore...

  20. Evaluation in a Dog Model of Three Antimicrobial Glassy Coatings: Prevention of Bone Loss around Implants and Microbial Assessments.

    Directory of Open Access Journals (Sweden)

    Roberto López-Píriz

    Full Text Available The aim of the present study is to evaluate, in a ligature-induced peri-implantitis model, the efficacy of three antimicrobial glassy coatings in the prevention of biofilm formation, intrasulcular bacterial growth and the resulting peri-implant bone loss.Mandibular premolars were bilaterally extracted from five beagle dogs. Four dental implants were inserted on each hemiarch. Eight weeks after, one control zirconia abutment and three with different bactericidal coatings (G1n-Ag, ZnO35, G3 were connected. After a plaque control period, bacterial accumulation was allowed and biofilm formation on abutments was observed by Scanning Electron Microscopy (SEM. Peri-implantitis was induced by cotton ligatures. Microbial samples and peri-implant crestal bone levels of all implant sites were obtained before, during and after the breakdown period.During experimental induce peri-implantitis: colony forming units counts from intrasulcular microbial samples at implants with G1n-Ag coated abutment remained close to the basal inoculum; G3 and ZnO35 coatings showed similar low counts; and anaerobic bacterias counts at control abutments exhibited a logarithmic increase by more than 2. Bone loss during passive breakdown period was no statistically significant. Additional bone loss occurred during ligature-induce breakdown: 0.71 (SD 0.48 at G3 coating, 0.57 (SD 0.36 at ZnO35 coating, 0.74 (SD 0.47 at G1n-Ag coating, and 1.29 (SD 0.45 at control abutments; and statistically significant differences (p<0.001 were found. The lowest bone loss at the end of the experiment was exhibited by implants dressing G3 coated abutments (mean 2.1; SD 0.42.Antimicrobial glassy coatings could be a useful tool to ward off, diminish or delay peri-implantitis progression.

  1. Structural model requirements to describe microbial inactivation during a mild heat treatment.

    Science.gov (United States)

    Geeraerd, A H; Herremans, C H; Van Impe, J F

    2000-09-10

    The classical concept of D and z values, established for sterilisation processes, is unable to deal with the typical non-loglinear behaviour of survivor curves occurring during the mild heat treatment of sous vide or cook-chill food products. Structural model requirements are formulated, eliminating immediately some candidate model types. Promising modelling approaches are thoroughly analysed and, if applicable, adapted to the specific needs: two models developed by Casolari (1988), the inactivation model of Sapru et al. (1992), the model of Whiting (1993), the Baranyi and Roberts growth model (1994), the model of Chiruta et al. (1997), the model of Daughtry et al. (1997) and the model of Xiong et al. (1999). A range of experimental data of Bacillus cereus, Yersinia enterocolitica, Escherichia coli O157:H7, Listeria monocytogenes and Lactobacillus sake are used to illustrate the different models' performances. Moreover, a novel modelling approach is developed, fulfilling all formulated structural model requirements, and based on a careful analysis of literature knowledge of the shoulder and tailing phenomenon. Although a thorough insight in the occurrence of shoulders and tails is still lacking from a biochemical point of view, this newly developed model incorporates the possibility of a straightforward interpretation within this framework.

  2. Functional Resilience and Response to a Dietary Additive (Kefir in Models of Foregut and Hindgut Microbial Fermentation In Vitro

    Directory of Open Access Journals (Sweden)

    Gabriel de la Fuente

    2017-06-01

    Full Text Available Stability in gut ecosystems is an important area of study that impacts on the use of additives and is related with several pathologies. Kefir is a fermented milk drink made with a consortium of yeast and bacteria as a fermentation starter, of which the use as additive in companion and livestock animals has increased in the last few years. To investigate the effect of kefir milk on foregut and hindgut digestive systems, an in vitro approach was followed. Either rumen fluid or horse fecal contents were used as a microbial inoculate and the inclusion of kefir (fresh, autoclaved, or pasteurized was tested. Gas production over 72 h of incubation was recorded and pH, volatile fatty acids (VFAs, lactate and ammonia concentration as well as lactic acid (LAB and acetic acid bacteria, and yeast total numbers were also measured. Both direct and indirect (by subtracting their respective blanks effects were analyzed and a multivariate analysis was performed to compare foregut and hindgut fermentation models. Addition of kefir boosted the fermentation by increasing molar concentration of VFAs and ammonia and shifting the Acetate to Propionate ratio in both models but heat processing techniques like pasteurization or autoclaving influenced the way the kefir is fermented and reacts with the present microbiota. In terms of comparison between both models, the foregut model seems to be less affected by the inclusion of Kefir than the hindgut model. In terms of variability in the response, the hindgut model appeared to be more variable than the foregut model in the way that it reacted indirectly to the addition of different types of kefir.

  3. Functional Resilience and Response to a Dietary Additive (Kefir) in Models of Foregut and Hindgut Microbial Fermentation In Vitro.

    Science.gov (United States)

    de la Fuente, Gabriel; Jones, Eleanor; Jones, Shann; Newbold, Charles J

    2017-01-01

    Stability in gut ecosystems is an important area of study that impacts on the use of additives and is related with several pathologies. Kefir is a fermented milk drink made with a consortium of yeast and bacteria as a fermentation starter, of which the use as additive in companion and livestock animals has increased in the last few years. To investigate the effect of kefir milk on foregut and hindgut digestive systems, an in vitro approach was followed. Either rumen fluid or horse fecal contents were used as a microbial inoculate and the inclusion of kefir (fresh, autoclaved, or pasteurized) was tested. Gas production over 72 h of incubation was recorded and pH, volatile fatty acids (VFAs), lactate and ammonia concentration as well as lactic acid (LAB) and acetic acid bacteria, and yeast total numbers were also measured. Both direct and indirect (by subtracting their respective blanks) effects were analyzed and a multivariate analysis was performed to compare foregut and hindgut fermentation models. Addition of kefir boosted the fermentation by increasing molar concentration of VFAs and ammonia and shifting the Acetate to Propionate ratio in both models but heat processing techniques like pasteurization or autoclaving influenced the way the kefir is fermented and reacts with the present microbiota. In terms of comparison between both models, the foregut model seems to be less affected by the inclusion of Kefir than the hindgut model. In terms of variability in the response, the hindgut model appeared to be more variable than the foregut model in the way that it reacted indirectly to the addition of different types of kefir.

  4. Final Report Construction of Whole Genome Microarrays, and Expression Analysis of Desulfovibrio vulgaris cells in Metal-Reducing Conditions

    Energy Technology Data Exchange (ETDEWEB)

    M.W. Fields; J.D. Wall; J. Keasling; J. Zhou

    2008-05-15

    We continue to utilize the oligonucleotide microarrays that were constructed through funding with this project to characterize growth responses of Desulfovibrio vulgaris relevant to metal-reducing conditions. To effectively immobilize heavy metals and radionuclides via sulfate-reduction, it is important to understand the cellular responses to adverse factors observed at contaminated subsurface environments (e.g., nutrients, pH, contaminants, growth requirements and products). One of the major goals of the project is to construct whole-genome microarrays for Desulfovibrio vulgaris. First, in order to experimentally establish the criteria for designing gene-specific oligonucleotide probes, an oligonucleotide array was constructed that contained perfect match (PM) and mismatch (MM) probes (50mers and 70mers) based upon 4 genes. The effects of probe-target identity, continuous stretch, mismatch position, and hybridization free energy on specificity were examined. Little hybridization was observed at a probe-target identity of <85% for both 50mer and 70mer probes. 33 to 48% of the PM signal intensities were detected at a probe-target identity of 94% for 50mer oligonucleotides, and 43 to 55% for 70mer probes at a probe-target identity of 96%. When the effects of sequence identity and continuous stretch were considered independently, a stretch probe (>15 bases) contributed an additional 9% of the PM signal intensity compared to a non-stretch probe (< 15 bases) at the same identity level. Cross-hybridization increased as the length of continuous stretch increased. A 35-base stretch for 50mer probes or a 50-base stretch for 70mer probes had approximately 55% of the PM signal. Mismatches should be as close to the middle position of an oligonucleotide probe as possible to minimize cross-hybridization. Little cross-hybridization was observed for probes with a minimal binding free energy greater than -30 kcal/mol for 50mer probes or -40 kcal/mol for 70mer probes. Based on the

  5. Nitrate-Mediated Microbially Enhanced Oil Recovery (N-MEOR) from model upflow bioreactors.

    Science.gov (United States)

    Gassara, Fatma; Suri, Navreet; Voordouw, Gerrit

    2017-02-15

    Microbially Enhanced Oil Recovery (MEOR) can enhance oil production with less energy input and less costs than other technologies. The present study used different aqueous electron donors (acetate, glucose, molasses) and an aqueous electron acceptor (nitrate) to stimulate growth of heterotrophic nitrate reducing bacteria (hNRB) to improve production of oil. Initial flooding of columns containing heavy oil (viscosity of 3400cP at 20°C) with CSBK (Coleville synthetic brine medium) produced 0.5 pore volume (PV) of oil. Bioreactors were then inoculated with hNRB with 5.8g/L of molasses and 0, 10, 20, 40, 60 or 80mM nitrate, as well as with 17mM glucose or 57mM acetate and 80mM nitrate. During incubations no oil was produced in the bioreactors that received 5.8g/L of molasses and 0, 10, 20, 40 or 60mM nitrate. However, the bioreactors injected with 5.8g/L of molasses, 17mM glucose or 57mM acetate and 80mM nitrate produced 13.9, 11.3±3.1 and 17.8±6.6% of residual oil, respectively. The significant production of oil from these bioreactors may be caused by N2-CO2 gas production. Following continued injection with CSBK without nitrate, subsequent elution of significant residual oil (5-30%) was observed. These results also indicate possible involvement of fermentation products (organic acids, alcohols) to enhance heavy oil recovery. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Modeling and validation of single-chamber microbial fuel cell cathode biofilm growth and response to oxidant gas composition

    Science.gov (United States)

    Ou, Shiqi; Zhao, Yi; Aaron, Douglas S.; Regan, John M.; Mench, Matthew M.

    2016-10-01

    This work describes experiments and computational simulations to analyze single-chamber, air-cathode microbial fuel cell (MFC) performance and cathodic limitations in terms of current generation, power output, mass transport, biomass competition, and biofilm growth. Steady-state and transient cathode models were developed and experimentally validated. Two cathode gas mixtures were used to explore oxygen transport in the cathode: the MFCs exposed to a helium-oxygen mixture (heliox) produced higher current and power output than the group of MFCs exposed to air or a nitrogen-oxygen mixture (nitrox), indicating a dependence on gas-phase transport in the cathode. Multi-substance transport, biological reactions, and electrochemical reactions in a multi-layer and multi-biomass cathode biofilm were also simulated in a transient model. The transient model described biofilm growth over 15 days while providing insight into mass transport and cathodic dissolved species concentration profiles during biofilm growth. Simulation results predict that the dissolved oxygen content and diffusion in the cathode are key parameters affecting the power output of the air-cathode MFC system, with greater oxygen content in the cathode resulting in increased power output and fully-matured biomass.

  7. Integrated experimental investigation and mathematical modeling of brackish water desalination and wastewater treatment in microbial desalination cells.

    Science.gov (United States)

    Ping, Qingyun; Huang, Zuyi; Dosoretz, Carlos; He, Zhen

    2015-06-15

    Desalination of brackish water can provide freshwater for potable use or non potable applications such as agricultural irrigation. Brackish water desalination is especially attractive to microbial desalination cells (MDCs) because of its low salinity, but this has not been well studied before. Herein, three brackish waters prepared according to the compositions of actual brackish water in three locations in Israel were examined with domestic wastewater as an electron source in a bench-scale MDC. All three brackish waters could be effectively desalinated with simultaneous wastewater treatment. The MDC achieved the highest salt removal rate of 1.2 g L(-1) d(-1) with an initial salinity of 5.9 g L(-1) and a hydraulic retention time (HRT) of 0.8 d. The desalinated brackish water could meet the irrigation standard of both salinity (450 mg L(-1) TDS) and the concentrations of major ionic species, given a sufficient HRT. The MDC also accomplished nearly 70% removal of organic compounds in wastewater with Coulombic efficiency varied between 5 and 10%. A previously developed MDC model was improved for brackish water desalination, and could well predict salinity variation and the concentrations of individual ions. The model also simulated a staged operation mode with improved desalination performance. This integrated experiment and mathematical modeling approach provides an effective method to understand the key factors in brackish water desalination by MDCs towards further system development.

  8. Pore-scale network modeling of microbially induced calcium carbonate precipitation: Insight into scale dependence of biogeochemical reaction rates

    Science.gov (United States)

    Qin, Chao-Zhong; Hassanizadeh, S. Majid; Ebigbo, Anozie

    2016-11-01

    The engineering of microbially induced calcium carbonate precipitation (MICP) has attracted much attention in a number of applications, such as sealing of CO2 leakage pathways, soil stabilization, and subsurface remediation of radionuclides and toxic metals. The goal of this work is to gain insight into pore-scale processes of MICP and scale dependence of biogeochemical reaction rates. This will help us develop efficient field-scale MICP models. In this work, we have developed a comprehensive pore-network model for MICP, with geochemical speciation calculated by the open-source PHREEQC module. A numerical pseudo-3-D micromodel as the computational domain was generated by a novel pore-network generation method. We modeled a three-stage process in the engineering of MICP including the growth of biofilm, the injection of calcium-rich medium, and the precipitation of calcium carbonate. A number of test cases were conducted to illustrate how calcite precipitation was influenced by different operating conditions. In addition, we studied the possibility of reducing the computational effort by simplifying geochemical calculations. Finally, the effect of mass transfer limitation of possible carbonate ions in a pore element on calcite precipitation was explored.

  9. Possible Causes of Ileal Injury in Two Models of Microbial Sepsis and Protective Effect of Phytic Acid

    Directory of Open Access Journals (Sweden)

    Rasha Rashad Ahmed

    2010-03-01

    Full Text Available Background: Sepsis related-multiple organ dysfunction is associatedwith ileum injury. We aimed to determine the causes ofileal injury in two models of microbial sepsis resulted from infectionwith Aeromonas hydrophila or its endotoxin. We alsoevaluated the protective effect of phytic acid.Methods: Thin sections of ileum from 60 Swiss male mice incontrol, bacteria-infected or lipopolysaccharides (LPS andbacteria-infected or LPS-infected co-administered with phyticacid were subjected to histopathological and TdT-mediateddUTP nick-end labeling (TUNEL assay for apoptotic cellsdetection while ultra thin sections were stained with uranylacetate and lead citrate for cytological changes examination.Also, ileum images were exposed to the image analysis softwareto determine some related morphometric measures.Results: Necrosis and apoptosis were observed in ileum injuryin both examined sepsis models. The ileum injury was moresevere in LPS model. Phytic acid showed the ability to attenuateileum injury in Aeromonas hydrophila and its endotoxinmodels of sepsis after four weeks administration where itssupplementation significantly minimized the histopathologicaland cytological complications and morphometric alterationsresulted from the injury.Conclusion: The protective effects of phytic acid may becaused by increased mucous secretion, decreased apoptoticindex, attenuating the inflammatory and lymphocytic cellscount or increasing the renewal of the crypt cells and villousepithelial cells proliferation.

  10. Modeling the microbial growth and temperature profile in a fixed-bed bioreactor.

    Science.gov (United States)

    da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

    2014-10-01

    Aiming to scale up and apply control and optimization strategies, currently is required the development of accurate plant models to forecast the process nonlinear dynamics. In this work, a mathematical model to predict the growth of the Kluyveromyces marxianus and temperature profile in a fixed-bed bioreactor for solid-state fermentation using sugarcane bagasse as substrate was built up. A parameter estimation technique was performed to fit the mathematical model to the experimental data. The estimated parameters and the model fitness were evaluated with statistical analyses. The results have shown the estimated parameters significance, with 95 % confidence intervals, and the good quality of process model to reproduce the experimental data.

  11. Introducing a novel interaction model structure for the combined effect of temperature and pH on the microbial growth rate.

    Science.gov (United States)

    Akkermans, Simen; Noriega Fernandez, Estefanía; Logist, Filip; Van Impe, Jan F

    2017-01-02

    Efficient modelling of the microbial growth rate can be performed by combining the effects of individual conditions in a multiplicative way, known as the gamma concept. However, several studies have illustrated that interactions between different effects should be taken into account at stressing environmental conditions to achieve a more accurate description of the growth rate. In this research, a novel approach for modeling the interactions between the effects of environmental conditions on the microbial growth rate is introduced. As a case study, the effect of temperature and pH on the growth rate of Escherichia coli K12 is modeled, based on a set of computer controlled bioreactor experiments performed under static environmental conditions. The models compared in this case study are the gamma model, the model of Augustin and Carlier (2000), the model of Le Marc et al. (2002) and the novel multiplicative interaction model, developed in this paper. This novel model enables the separate identification of interactions between the effects of two (or more) environmental conditions. The comparison of these models focuses on the accuracy, interpretability and compatibility with efficient modeling approaches. Moreover, for the separate effects of temperature and pH, new cardinal parameter model structures are proposed. The novel interaction model contributes to a generic modeling approach, resulting in predictive models that are (i) accurate, (ii) easily identifiable with a limited work load, (iii) modular, and (iv) biologically interpretable.

  12. Multi-Analytical Approach Reveals Potential Microbial Indicators in Soil for Sugarcane Model Systems.

    Directory of Open Access Journals (Sweden)

    Acacio Aparecido Navarrete

    Full Text Available This study focused on the effects of organic and inorganic amendments and straw retention on the microbial biomass (MB and taxonomic groups of bacteria in sugarcane-cultivated soils in a greenhouse mesocosm experiment monitored for gas emissions and chemical factors. The experiment consisted of combinations of synthetic nitrogen (N, vinasse (V; a liquid waste from ethanol production, and sugarcane-straw blankets. Increases in CO2-C and N2O-N emissions were identified shortly after the addition of both N and V to the soils, thus increasing MB nitrogen (MB-N and decreasing MB carbon (MB-C in the N+V-amended soils and altering soil chemical factors that were correlated with the MB. Across 57 soil metagenomic datasets, Actinobacteria (31.5%, Planctomycetes (12.3%, Deltaproteobacteria (12.3%, Alphaproteobacteria (12.0% and Betaproteobacteria (11.1% were the most dominant bacterial groups during the experiment. Differences in relative abundance of metagenomic sequences were mainly revealed for Acidobacteria, Actinobacteria, Gammaproteobacteria and Verrucomicrobia with regard to N+V fertilization and straw retention. Differential abundances in bacterial groups were confirmed using 16S rRNA gene-targeted phylum-specific primers for real-time PCR analysis in all soil samples, whose results were in accordance with sequence data, except for Gammaproteobacteria. Actinobacteria were more responsive to straw retention with Rubrobacterales, Bifidobacteriales and Actinomycetales related to the chemical factors of N+V-amended soils. Acidobacteria subgroup 7 and Opitutae, a verrucomicrobial class, were related to the chemical factors of soils without straw retention as a surface blanket. Taken together, the results showed that MB-C and MB-N responded to changes in soil chemical factors and CO2-C and N2O-N emissions, especially for N+V-amended soils. The results also indicated that several taxonomic groups of bacteria, such as Acidobacteria, Actinobacteria and

  13. Exploration of freely available web-interfaces for comparative homology modelling of microbial proteins.

    Science.gov (United States)

    Nema, Vijay; Pal, Sudhir Kumar

    2013-01-01

    This study was conducted to find the best suited freely available software for modelling of proteins by taking a few sample proteins. The proteins used were small to big in size with available crystal structures for the purpose of benchmarking. Key players like Phyre2, Swiss-Model, CPHmodels-3.0, Homer, (PS)2, (PS)(2)-V(2), Modweb were used for the comparison and model generation. Benchmarking process was done for four proteins, Icl, InhA, and KatG of Mycobacterium tuberculosis and RpoB of Thermus Thermophilus to get the most suited software. Parameters compared during analysis gave relatively better values for Phyre2 and Swiss-Model. This comparative study gave the information that Phyre2 and Swiss-Model make good models of small and large proteins as compared to other screened software. Other software was also good but is often not very efficient in providing full-length and properly folded structure.

  14. Prediction of Competitive Microbial Growth.

    Science.gov (United States)

    Fujikawa, Hiroshi

    2016-01-01

     Prediction of competitive microbial growth is becoming important for microbial food safety. There would be two approaches to predict competitive microbial growth with mathematical models. The first approach is the development of a growth model for competitive microbes. Among several candidates for the competition model considered, the combination of the primary growth model of the new logistic (NL) model and the competition model of the Lotka-Vorttera (LV) model showed the best performance in predicting microbial competitive growth in the mixed culture of two species. This system further successfully predicted the growth of three competitive species in mixed culture. The second approach is the application of the secondary model especially for the parameter of the maximum cell population in the primary growth model. The combination of the NL model and a polynomial model for the maximum population successfully predicted Salmonella growth in raw ground beef. This system further successfully predicted Salmonella growth in beef at various initial concentrations and temperatures. The first approach requires microbial growth data in monoculture for analysis. The second approach to the prediction of competitive growth from the viewpoint of microbial food safety would be more suitable for practical application.

  15. A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes.

    Science.gov (United States)

    Weitz, Joshua S; Stock, Charles A; Wilhelm, Steven W; Bourouiba, Lydia; Coleman, Maureen L; Buchan, Alison; Follows, Michael J; Fuhrman, Jed A; Jover, Luis F; Lennon, Jay T; Middelboe, Mathias; Sonderegger, Derek L; Suttle, Curtis A; Taylor, Bradford P; Frede Thingstad, T; Wilson, William H; Eric Wommack, K

    2015-06-01

    Viral lysis of microbial hosts releases organic matter that can then be assimilated by nontargeted microorganisms. Quantitative estimates of virus-mediated recycling of carbon in marine waters, first established in the late 1990s, were originally extrapolated from marine host and virus densities, host carbon content and inferred viral lysis rates. Yet, these estimates did not explicitly incorporate the cascade of complex feedbacks associated with virus-mediated lysis. To evaluate the role of viruses in shaping community structure and ecosystem functioning, we extend dynamic multitrophic ecosystem models to include a virus component, specifically parameterized for processes taking place in the ocean euphotic zone. Crucially, we are able to solve this model analytically, facilitating evaluation of model behavior under many alternative parameterizations. Analyses reveal that the addition of a virus component promotes the emergence of complex communities. In addition, biomass partitioning of the emergent multitrophic community is consistent with well-established empirical norms in the surface oceans. At steady state, ecosystem fluxes can be probed to characterize the effects that viruses have when compared with putative marine surface ecosystems without viruses. The model suggests that ecosystems with viruses will have (1) increased organic matter recycling, (2) reduced transfer to higher trophic levels and (3) increased net primary productivity. These model findings support hypotheses that viruses can have significant stimulatory effects across whole-ecosystem scales. We suggest that existing efforts to predict carbon and nutrient cycling without considering virus effects are likely to miss essential features of marine food webs that regulate global biogeochemical cycles.

  16. Numerical Modeling Analysis of Hydrodynamic and Microbial Controls on DNAPL Pool Dissolution and Detoxification: Dehalorespirers in Co-culture

    Energy Technology Data Exchange (ETDEWEB)

    Wesseldyke, Eric S.; Becker, Jennifer G.; Seagren, Eric A.; Mayer, Alex S.; Zhang, Changyong

    2015-04-01

    Dissolution of dense non-aqueous phase liquid (DNAPL) contaminants like tetrachloroethene (PCE) can be “bioenhanced” via biodegradation, which increases the concentration gradient at the DNAPL–water interface. Model simulations were used to evaluate the impact of ecological interactions between different dehalorespiring strains and hydrodynamics on the bioenhancement effect and the extent of PCE dechlorination. Simulations were performed using a two-dimensional coupled flow-transport model, with a DNAPL pool source and two microbial species, Dehalococcoides mccartyi 195 and Desulfuromonas michiganensis, which compete for electron acceptors (e.g., PCE), but not for their electron donors. Under biostimulation, low vx conditions, D. michiganensis alone significantly enhanced dissolution by rapidly utilizing aqueous-phase PCE. In co-culture under these conditions, D. mccartyi 195 increased this bioenhancement modestly and greatly increased the extent of PCE transformation. Although D. michiganensis was the dominant population under low velocity conditions, D. mccartyi 195 dominated under high velocity conditions due to bioclogging effects.

  17. Multiphoton microscopy for imaging infectious keratitis: demonstration of the pattern of microbial spread in an experimental model

    Science.gov (United States)

    Sun, Yen; Lo, Wen; Wu, Ruei-Jhih; Lin, Sung-Jan; Lin, Wei-Chou; Jee, Shiou-Hwa; Tan, Hsin-Yuan; Dong, Chen-Yuan

    2006-02-01

    The purpose of this study is to assess the application of multiphoton fluorescence and second harmonic generation (SHG) microscopy for imaging and monitoring the disease progress of infectious keratitis in an experimental model, and to investigate the possible correlation of tissue architecture with spreading patterns of pathogens in an experimental model. Porcine eyes are to be obtained from slaughter house and processed and placed in organ culture system. Fungal infections by common pathogens of infectious keratitis are to be induced in porcine cornea buttons. Multiphoton fluorescence and SHG microscopy will be used for imaging and for monitoring the progression and extension of tissue destruction and possibly the pattern of pathogen spreading. We found that SHG imaging is useful in identifying alterations to collagen architecture while autofluorescence microscopy can be used to visualize the fungi and cells within the stroma. In summary, multiphoton fluorescence and second harmonic generation microscopy can non-invasively demonstrate and monitor tissue destruction associated with infectious keratitis. The pattern of pathogen spreading and its correlation with the tissue architecture can also be shown, which can be useful for future studies of the tissue-microbial interactions for infectious keratitis.

  18. Microbiële kwaliteit voorspellen

    NARCIS (Netherlands)

    Vissers, M.; Straver, J.M.; Giffel, te M.C.; Jong, de P.; Zwietering, M.H.; Boekel, van M.A.J.S.; Lankveld, J.M.G.

    2004-01-01

    Microbial quality and safety of foodstuffs can be improved by reducing the microbial load of the raw materials. Especially in products in which microbial spoilage is caused by sporeforming bacteria this can be the only solution. Combining existing datasets, expert knowledge and quantitative modeling

  19. Disease induction by human microbial pathogens in plant-model systems: potential, problems and prospects

    NARCIS (Netherlands)

    Baarlen, van P.; Belkum, van A.; Thomma, B.P.H.J.

    2007-01-01

    Relatively simple eukaryotic model organisms such as the genetic model weed plant Arabidopsis thaliana possess an innate immune system that shares important similarities with its mammalian counterpart. In fact, some human pathogens infect Arabidopsis and cause overt disease with human symptomology.

  20. Combining Microbial Enzyme Kinetics Models with Light Use Efficiency Models to Predict CO2 and CH4 Ecosystem Exchange from Flooded and Drained Peatland Systems

    Science.gov (United States)

    Oikawa, P. Y.; Jenerette, D.; Knox, S. H.; Sturtevant, C. S.; Verfaillie, J. G.; Baldocchi, D. D.

    2014-12-01

    Under California's Cap-and-Trade program, companies are looking to invest in land-use practices that will reduce greenhouse gas (GHG) emissions. The Sacramento-San Joaquin River Delta is a drained cultivated peatland system and a large source of CO2. To slow soil subsidence and reduce CO2 emissions, there is growing interest in converting drained peatlands to wetlands. However, wetlands are large sources of CH4 that could offset CO2-based GHG reductions. The goal of our research is to provide accurate measurements and model predictions of the changes in GHG budgets that occur when drained peatlands are restored to wetland conditions. We have installed a network of eddy covariance towers across multiple land use types in the Delta and have been measuring CO2 and CH4 ecosystem exchange for multiple years. In order to upscale these measurements through space and time we are using these data to parameterize and validate a process-based biogeochemical model. To predict gross primary productivity (GPP), we are using a simple light use efficiency (LUE) model which requires estimates of light, leaf area index and air temperature and can explain 90% of the observed variation in GPP in a mature wetland. To predict ecosystem respiration we have adapted the Dual Arrhenius Michaelis-Menten (DAMM) model. The LUE-DAMM model allows accurate simulation of half-hourly net ecosystem exchange (NEE) in a mature wetland (r2=0.85). We are working to expand the model to pasture, rice and alfalfa systems in the Delta. To predict methanogenesis, we again apply a modified DAMM model, using simple enzyme kinetics. However CH4 exchange is complex and we have thus expanded the model to predict not only microbial CH4 production, but also CH4 oxidation, CH4 storage and the physical processes regulating the release of CH4 to the atmosphere. The CH4-DAMM model allows accurate simulation of daily CH4 ecosystem exchange in a mature wetland (r2=0.55) and robust estimates of annual CH4 budgets. The LUE

  1. Mathematical Modeling of the Process for Microbial Production of Branched Chained Amino Acids

    Directory of Open Access Journals (Sweden)

    Todorov K.

    2009-12-01

    Full Text Available This article deals with modelling of branched chained amino acids production. One of important branched chained amino acid is L-valine. The aim of the article is synthesis of dynamic unstructured model of fed-batch fermentation process with intensive droppings for L-valine production. The presented approach of the investigation includes the following main procedures: description of the process by generalized stoichiometric equations; preliminary data processing and calculation of specific rates for main kinetic variables; identification of the specific rates takes into account the dissolved oxygen tension; establishment and optimisation of dynamic model of the process; simulation researches. MATLAB is used as a research environment.

  2. Quantitative microbial risk assessment for spray irrigation of dairy manure based on an empirical fate and transport model

    Science.gov (United States)

    Burch, Tucker R; Spencer, Susan K.; Stokdyk, Joel; Kieke, Burney A; Larson, Rebecca A; Firnstahl, Aaron; Rule, Ana M; Borchardt, Mark A.

    2017-01-01

    BACKGROUND: Spray irrigation for land-applying livestock manure is increasing in the United States as farms become larger and economies of scale make manure irrigation affordable. Human health risks from exposure to zoonotic pathogens aerosolized during manure irrigation are not well understood. OBJECTIVES: We aimed to a) estimate human health risks due to aerosolized zoonotic pathogens downwind of spray-irrigated dairy manure; and b) determine which factors (e.g., distance, weather conditions) have the greatest influence on risk estimates. METHODS: We sampled downwind air concentrations of manure-borne fecal indicators and zoonotic pathogens during 21 full-scale dairy manure irri- gation events at three farms. We fit these data to hierarchical empirical models and used model outputs in a quantitative microbial risk assessment (QMRA) to estimate risk [probability of acute gastrointestinal illness (AGI)] for individuals exposed to spray-irrigated dairy manure containing Campylobacter jejuni, enterohemorrhagic Escherichia coli (EHEC), or Salmonella spp. RESULTS: Median risk estimates from Monte Carlo simulations ranged from 10−5 to 10−2 and decreased with distance from the source. Risk estimates for Salmonella or EHEC-related AGI were most sensitive to the assumed level of pathogen prevalence in dairy manure, while risk estimates for C. jejuni were not sensitive to any single variable. Airborne microbe concentrations were negatively associated with distance and positively associated with wind speed, both of which were retained in models as a significant predictor more often than relative humidity, solar irradiation, or temperature. CONCLUSIONS: Our model-based estimates suggest that reducing pathogen prevalence and concentration in source manure would reduce the risk of AGI from exposure to manure irrigation, and that increasing the distance from irrigated manure (i.e., setbacks) and limiting irrigation to times of low wind speed may also reduce risk.

  3. Duckweed (Lemna minor as a model plant system for the study of human microbial pathogenesis.

    Directory of Open Access Journals (Sweden)

    Yong Zhang

    Full Text Available BACKGROUND: Plant infection models provide certain advantages over animal models in the study of pathogenesis. However, current plant models face some limitations, e.g., plant and pathogen cannot co-culture in a contained environment. Development of such a plant model is needed to better illustrate host-pathogen interactions. METHODOLOGY/PRINCIPAL FINDINGS: We describe a novel model plant system for the study of human pathogenic bacterial infection on a large scale. This system was initiated by co-cultivation of axenic duckweed (Lemna minor plants with pathogenic bacteria in 24-well polystyrene cell culture plate. Pathogenesis of bacteria to duckweed was demonstrated with Pseudomonas aeruginosa and Staphylococcus aureus as two model pathogens. P. aeruginosa PAO1 caused severe detriment to duckweed as judged from inhibition to frond multiplication and chlorophyll formation. Using a GFP-marked PAO1 strain, we demonstrated that bacteria colonized on both fronds and roots and formed biofilms. Virulence of PAO1 to duckweed was attenuated in its quorum sensing (QS mutants and in recombinant strains overexpressing the QS quenching enzymes. RN4220, a virulent strain of S. aureus, caused severe toxicity to duckweed while an avirulent strain showed little effect. Using this system for antimicrobial chemical selection, green tea polyphenols exhibited inhibitory activity against S. aureus virulence. This system was further confirmed to be effective as a pathogenesis model using a number of pathogenic bacterial species. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that duckweed can be used as a fast, inexpensive and reproducible model plant system for the study of host-pathogen interactions, could serve as an alternative choice for the study of some virulence factors, and could also potentially be used in large-scale screening for the discovery of antimicrobial chemicals.

  4. Mathematical Modeling of the Process for Microbial Production of Branched Chained Amino Acids

    OpenAIRE

    Todorov K.; Georgiev T.; Ratkov A.

    2009-01-01

    This article deals with modelling of branched chained amino acids production. One of important branched chained amino acid is L-valine. The aim of the article is synthesis of dynamic unstructured model of fed-batch fermentation process with intensive droppings for L-valine production. The presented approach of the investigation includes the following main procedures: description of the process by generalized stoichiometric equations; preliminary data processing and calculation of specific rat...

  5. In-Drift Microbial Communities

    Energy Technology Data Exchange (ETDEWEB)

    D. Jolley

    2000-11-09

    As directed by written work direction (CRWMS M and O 1999f), Performance Assessment (PA) developed a model for microbial communities in the engineered barrier system (EBS) as documented here. The purpose of this model is to assist Performance Assessment and its Engineered Barrier Performance Section in modeling the geochemical environment within a potential repository drift for TSPA-SR/LA, thus allowing PA to provide a more detailed and complete near-field geochemical model and to answer the key technical issues (KTI) raised in the NRC Issue Resolution Status Report (IRSR) for the Evolution of the Near Field Environment (NFE) Revision 2 (NRC 1999). This model and its predecessor (the in-drift microbial communities model as documented in Chapter 4 of the TSPA-VA Technical Basis Document, CRWMS M and O 1998a) was developed to respond to the applicable KTIs. Additionally, because of the previous development of the in-drift microbial communities model as documented in Chapter 4 of the TSPA-VA Technical Basis Document (CRWMS M and O 1998a), the M and O was effectively able to resolve a previous KTI concern regarding the effects of microbial processes on seepage and flow (NRC 1998). This document supercedes the in-drift microbial communities model as documented in Chapter 4 of the TSPA-VA Technical Basis Document (CRWMS M and O 1998a). This document provides the conceptual framework of the revised in-drift microbial communities model to be used in subsequent performance assessment (PA) analyses.

  6. Modeling of microfluidic microbial fuel cells using quantitative bacterial transport parameters

    Science.gov (United States)

    Mardanpour, Mohammad Mahdi; Yaghmaei, Soheila; Kalantar, Mohammad

    2017-02-01

    The objective of present study is to analyze the dynamic modeling of bioelectrochemical processes and improvement of the performance of previous models using quantitative data of bacterial transport parameters. The main deficiency of previous MFC models concerning spatial distribution of biocatalysts is an assumption of initial distribution of attached/suspended bacteria on electrode or in anolyte bulk which is the foundation for biofilm formation. In order to modify this imperfection, the quantification of chemotactic motility to understand the mechanisms of the suspended microorganisms' distribution in anolyte and/or their attachment to anode surface to extend the biofilm is implemented numerically. The spatial and temporal distributions of the bacteria, as well as the dynamic behavior of the anolyte and biofilm are simulated. The performance of the microfluidic MFC as a chemotaxis assay is assessed by analyzing the bacteria activity, substrate variation, bioelectricity production rate and the influences of external resistance on the biofilm and anolyte's features.

  7. Structure and microbial diversity of biofilms on different pipe materials of a model drinking water distribution systems.

    Science.gov (United States)

    Rożej, Agnieszka; Cydzik-Kwiatkowska, Agnieszka; Kowalska, Beata; Kowalski, Dariusz

    2015-01-01

    The experiment was conducted in three model drinking water distribution systems (DWDSs) made of unplasticized polyvinyl chloride (PVC), silane cross-linked polyethylene (PEX) and high density polyethylene (HDPE) pipes to which tap water was introduced. After 2 years of system operation, microbial communities in the DWDSs were characterized with scanning electron microscopy, heterotrophic plate count, and denaturing gradient gel electrophoresis. The most extensive biofilms were found in HDPE pipes where bacteria were either attached to mineral deposits or immersed in exopolymers. On PEX surfaces, bacteria did not form large aggregates; however, they were present in the highest number (1.24 × 10(7) cells cm(-2)). PVC biofilm did not contain mineral deposits but was made of single cells with a high abundance of Pseudomonas aeruginosa, which can be harmful to human health. The members of Proteobacteria and Bacteroidetes were found in all biofilms and the water phase. Sphingomonadales and Methylophilaceae bacteria were found only in PEX samples, whereas Geothrix fermentans, which can reduce Fe(III), were identified only in PEX biofilm. The DNA sequences closely related to the members of Alphaproteobacteria were the most characteristic and intense amplicons detected in the HDPE biofilm.

  8. Effect of gum arabic on glucose levels and microbial short-chain fatty acid production in white rice porridge model and mixed grain porridge model.

    Science.gov (United States)

    Hu, Jie-Lun; Nie, Shao-Ping; Li, Na; Min, Fang-Fang; Li, Chang; Gong, Deming; Xie, Ming-Yong

    2014-07-01

    White rice porridge and mixed grain porridge, which are often consumed in many countries, were used as two models to evaluate the effects of gum arabic on glucose levels and microbial short-chain fatty acids (SCFA). Gum arabic was incorporated into the two porridges individually. Apparent viscosity of the two porridges was significantly increased, and their glucose productions during gastrointestinal digestion were notably lowered (p porridges in mice was considerably lowered after fortified with gum arabic (p porridges was significantly increased after gum arabic addition, which may also have beneficial effects on reducing postprandial glycemic response. Therefore, gum arabic may be a helpful ingredient, which could be added in porridges to have benefits for the reduction of postprandial glycemic response.

  9. A Practical Modeling Approach for NAPL Dissolution Kinetics, Microbially-Mediated Redox Reactions and Aquifer-Aquitard Diffusion to Assess Remedial Options

    Science.gov (United States)

    Parker, J.; Kim, U.; Widdowson, M.; Chappel, F.

    2008-12-01

    Explicit modeling of contaminant dissolution from heterogeneously distributed NAPL sources, microbial growth and reaction kinetics, and diffusion into or out of low permeability layers pose significant difficulties. These include the need to estimate a large number of parameters, which may subject to great uncertainty due to inverse problem ill-posedness given limited data, and to a lesser extent, the large computational effort that may be required to solve a rigorously formulated problem. An upscaled model for NAPL dissolution kinetics is utilized in the present study based on previous work, with extentions to consider concurrent effects of residual DNAPL and pools or lenses and to consider multi-component NAPL mixtures. An approach is presented to model microbially-mediated redox reactions subject to the assumption that microbial growth and reaction rates are primarily limited by transport processes rather than by microbial kinetics at time and space scales relevant for many remediation problems. The simplified model requires only stoichiometric coefficients for electron donor and electron acceptor half-reactions and the fraction of electron donor needed for cell synthesis. Contaminant diffusion into low permeability layers and subsequent back-diffusion is approximated as a first-order mass transfer problem with an effective mass transfer coefficient computed from aquifer-aquitard properties by equating second moments of diffusion and mass transfer solutions. Accuracy of the simplified model formulation is evaluated for a hypothetical problem involving a DNAPL source consisting of a mixture of TCE and Stoddard solvent with background dissolved organic carbon, oxygen and sulfate in groundwater for 40 years followed by injection of vegetable oil as a supplemental electron donor to enhance reductive dechlorination. The simplified solution is compared to numerical results that consider multi-species Monod kinetics with explicit treatment of back-diffusion.

  10. Interpreting microarray data to build models of microbial genetic regulation networks

    Science.gov (United States)

    Sokhansanj, Bahrad A.; Garnham, Janine B.; Fitch, J. Patrick

    2002-06-01

    Microarrays and DNA chips are an efficient, high-throughput technology for measuring temporal changes in the expression of message RNA (mRNA) from thousands of genes (often the entire genome of an organism) in a single experiment. A crucial drawback of microarray experiments is that results are inherently qualitative: data are generally neither quantitatively repeatable, nor may microarray spot intensities be calibrated to in vivo mRNA concentrations. Nevertheless, microarrays represent by the far the cheapest and fastest way to obtain information about a cell's global genetic regulatory networks. Besides poor signal characteristics, the massive number of data produced by microarray experiments pose challenges for visualization, interpretation and model building. Towards initial model development, we have developed a Java tool for visualizing the spatial organization of gene expression in bacteria. We are also developing an approach to inferring and testing qualitative fuzzy logic models of gene regulation using microarray data. Because we are developing and testing qualitative hypotheses that do not require quantitative precision, our statistical evaluation of experimental data is limited to checking for validity and consistency. Our goals are to maximize the impact of inexpensive microarray technology, bearing in mind that biological models and hypotheses are typically qualitative.

  11. Interpreting Microarray Data to Build Models of Microbial Genetic Regulation Networks

    Energy Technology Data Exchange (ETDEWEB)

    Sokhansanj, B; Garnham, J B; Fitch, J P

    2002-01-23

    Microarrays and DNA chips are an efficient, high-throughput technology for measuring temporal changes in the expression of message RNA (mRNA) from thousands of genes (often the entire genome of an organism) in a single experiment. A crucial drawback of microarray experiments is that results are inherently qualitative: data are generally neither quantitatively repeatable, nor may microarray spot intensities be calibrated to in vivo mRNA concentrations. Nevertheless, microarrays represent by the far the cheapest and fastest way to obtain information about a cells global genetic regulatory networks. Besides poor signal characteristics, the massive number of data produced by microarray experiments poses challenges for visualization, interpretation and model building. Towards initial model development, we have developed a Java tool for visualizing the spatial organization of gene expression in bacteria. We are also developing an approach to inferring and testing qualitative fuzzy logic models of gene regulation using microarray data. Because we are developing and testing qualitative hypotheses that do not require quantitative precision, our statistical evaluation of experimental data is limited to checking for validity and consistency. Our goals are to maximize the impact of inexpensive microarray technology, bearing in mind that biological models and hypotheses are typically qualitative.

  12. Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose

    DEFF Research Database (Denmark)

    Owusu-Ansah, Emmanuel de-Graft Johnson; Sampson, Angelina; Amponsah, Samuel K.

    2017-01-01

    The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10− 5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different...... physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study...... to estimate the norovirus count. In all scenarios of using different water sources, the application of the fecal indicator conversion ratio underestimated the norovirus disease burden, measured by the Disability Adjusted Life Years (DALYs), when compared to results using the genome copies norovirus data...

  13. Diet and specific microbial exposure trigger features of environmental enteropathy in a novel murine model.

    Science.gov (United States)

    Brown, Eric M; Wlodarska, Marta; Willing, Benjamin P; Vonaesch, Pascale; Han, Jun; Reynolds, Lisa A; Arrieta, Marie-Claire; Uhrig, Marco; Scholz, Roland; Partida, Oswaldo; Borchers, Christoph H; Sansonetti, Philippe J; Finlay, B Brett

    2015-08-04

    Environmental enteropathy (EE) is a subclinical chronic inflammatory disease of the small intestine and has a profound impact on the persistence of childhood malnutrition worldwide. However, the aetiology of the disease remains unknown and no animal model exists to date, the creation of which would aid in understanding this complex disease. Here we demonstrate that early-life consumption of a moderately malnourished diet, in combination with iterative oral exposure to commensal Bacteroidales species and Escherichia coli, remodels the murine small intestine to resemble features of EE observed in humans. We further report the profound changes that malnutrition imparts on the small intestinal microbiota, metabolite and intraepithelial lymphocyte composition, along with the susceptibility to enteric infection. Our findings provide evidence indicating that both diet and microbes combine to contribute to the aetiology of EE, and describe a novel murine model that can be used to elucidate the mechanisms behind this understudied disease.

  14. In vivo model for microbial invasion of tooth root dentinal tubules.

    Science.gov (United States)

    Brittan, Jane L; Sprague, Susan V; Macdonald, Emma L; Love, Robert M; Jenkinson, Howard F; West, Nicola X

    2016-04-01

    Objective Bacterial penetration of dentinal tubules via exposed dentine can lead to root caries and promote infections of the pulp and root canal system. The aim of this work was to develop a new experimental model for studying bacterial invasion of dentinal tubules within the human oral cavity. Material and Methods Sections of human root dentine were mounted into lower oral appliances that were worn by four human subjects for 15 d. Roots were then fixed, sectioned, stained and examined microscopically for evidence of bacterial invasion. Levels of invasion were expressed as Tubule Invasion Factor (TIF). DNA was extracted from root samples, subjected to polymerase chain reaction amplification of 16S rRNA genes, and invading bacteria were identified by comparison of sequences with GenBank database. Results All root dentine samples with patent tubules showed evidence of bacterial cell invasion (TIF value range from 5.7 to 9.0) to depths of 200 mm or more. A spectrum of Gram-positive and Gram-negative cell morphotypes were visualized, and molecular typing identified species of Granulicatella, Streptococcus, Klebsiella, Enterobacter, Acinetobacter, and Pseudomonas as dentinal tubule residents. Conclusion A novel in vivo model is described, which provides for human root dentine to be efficiently infected by oral microorganisms. A range of bacteria were able to initially invade dentinal tubules within exposed dentine. The model will be useful for testing the effectiveness of antiseptics, irrigants, and potential tubule occluding agents in preventing bacterial invasion of dentine.

  15. Microbial dynamics during conversion from supragingival to subgingival biofilms in an in vitro model.

    Science.gov (United States)

    Thurnheer, T; Bostanci, N; Belibasakis, G N

    2016-04-01

    The development of dental caries and periodontal diseases result from distinct shifts in the microbiota of the tooth-associated biofilm. This in vitro study aimed to investigate changes in biofilm composition and structure, during the shift from a 'supragingival' aerobic profile to a 'subgingival' anaerobic profile. Biofilms consisting of Actinomyces oris, Candida albicans, Fusobacterium nucleatum, Streptococcus oralis, Streptococcus mutans and Veillonella dispar were aerobically grown in saliva-containing medium on hydroxyapatite disks. After 64 h, Campylobacter rectus, Prevotella intermedia and Streptococcus anginosus were further added along with human serum, while culture conditions were shifted to microaerophilic. After 96 h, Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola were finally added and the biofilm was grown anaerobically for another 64 h. At the end of each phase, biofilms were harvested for species-specific quantification and localization. Apart from C. albicans, all other species gradually increased during aerobic and microaerophilic conditions, but remained steady during anaerobic conditions. Biofilm thickness was doubled during the microaerophilic phase, but remained steady throughout the anaerobic phase. Extracellular polysaccharide presence was gradually reduced throughout the growth period. Biofilm viability was reduced during the microaerophilic conversion, but was recovered during the anaerobic phase. This in vitro study has characterized the dynamic structural shifts occurring in an oral biofilm model during the switch from aerobic to anaerobic conditions, potentially modeling the conversion of supragingival to subgingival biofilms. Within the limitations of this experimental model, the findings may provide novel insights into the ecology of oral biofilms.

  16. In vivo model for microbial invasion of tooth root dentinal tubules

    Directory of Open Access Journals (Sweden)

    Jane L. BRITTAN

    2016-04-01

    Full Text Available ABSTRACT Objective Bacterial penetration of dentinal tubules via exposed dentine can lead to root caries and promote infections of the pulp and root canal system. The aim of this work was to develop a new experimental model for studying bacterial invasion of dentinal tubules within the human oral cavity. Material and Methods Sections of human root dentine were mounted into lower oral appliances that were worn by four human subjects for 15 d. Roots were then fixed, sectioned, stained and examined microscopically for evidence of bacterial invasion. Levels of invasion were expressed as Tubule Invasion Factor (TIF. DNA was extracted from root samples, subjected to polymerase chain reaction amplification of 16S rRNA genes, and invading bacteria were identified by comparison of sequences with GenBank database. Results All root dentine samples with patent tubules showed evidence of bacterial cell invasion (TIF value range from 5.7 to 9.0 to depths of 200 mm or more. A spectrum of Gram-positive and Gram-negative cell morphotypes were visualized, and molecular typing identified species of Granulicatella, Streptococcus, Klebsiella, Enterobacter, Acinetobacter, and Pseudomonas as dentinal tubule residents. Conclusion A novel in vivo model is described, which provides for human root dentine to be efficiently infected by oral microorganisms. A range of bacteria were able to initially invade dentinal tubules within exposed dentine. The model will be useful for testing the effectiveness of antiseptics, irrigants, and potential tubule occluding agents in preventing bacterial invasion of dentine.

  17. Simulation modeling for nitrogen removal and experimental estimation of mass fractions of microbial groups in single-sludge system.

    Science.gov (United States)

    Huang, J S; Tsai, C C; Chou, H H; Ting, W H

    2006-01-01

    Nitrification-denitrification in a single-sludge nitrogen removal system (SSNRS; with a sufficient carbon source for denitrification) was performed. With an increase in the mixed liquor recycle ratio (R(m)) from 1 to 2, the total nitrogen (TN) removal efficiency at a lower volumetric loading rate (VLR=0.21 NH(4)(+)-N m(-3) d(-1)) increased, but the TN removal efficiency at a higher VLR (0.35 kg NH(4)(+)-N m(-3) d(-1)) decreased. A kinetic model that accounts for the mass fractions of Nitrosomonas, Nitrobacter, nitrate reducer and nitrite reducer (f(n1), f(n2), f(dn1), and f(dn2)) in the SSNRS and an experimental approach for the estimation of the mass fractions of nitrogen-related microbial groups are also proposed. The estimated f(dn1) plus f(dn2) (0.65-0.83) was significantly larger than the f(n1) plus f(n2) (0.28-0.32); the f(n1) (0.21-0.26) was larger than the f(n2) (0.05-0.07); and the f(dn1) (0.32-0.45) varied slightly with the f(dn2) (0.33-0.38). At the lower VLR, the f(dn1) plus f(dn2) increased with increasing R(m); however at the higher VLR, the f(dn1) plus f(dn2) did not increase with increasing R(m). By using the kinetic model, the calculated residual NH(4)(+)-N and NO(2)(-)-N in the anoxic reactor and NO(2)(-)-N and NO(3)(-)-N in the aerobic reactor were in fairly good agreement with the experimental data; the calculated NO(3)(-)-N in the anoxic reactor was over-estimated and the calculated NH(4)(+)-N in the aerobic reactor was under-estimated.

  18. Model experiments on the microbial removal of chromium from contaminated groundwater.

    Science.gov (United States)

    Vainshtein, M; Kuschk, P; Mattusch, J; Vatsourina, A; Wiessner, A

    2003-03-01

    A bacterial consortium with representatives of sulfate-reducing and denitrifying bacteria was selectively enriched. Model experiments under microaerobic conditions showed that it precipitated chromium from Cr (VI)-containing waters (area of a former electroplating factory, Leipzig, Germany) by two different mechanisms: by sulfate reduction and precipitation as sulfide, and by some direct reduction. Sulfate reduction needed fatty acids as organic substrates and resulted at the first stage in no sulfide accumulation. In the absence of the fatty acids but with straw as organic substrate, the direct reduction of chromium was observed without sulfate reduction. In this case Cr (VI)-reduction rate correlated with that of the denitrification.

  19. Numerical modelling of biophysicochemical effects on multispecies reactive transport in porous media involving Pseudomonas putida for potential microbial enhanced oil recovery application.

    Science.gov (United States)

    Sivasankar, P; Rajesh Kanna, A; Suresh Kumar, G; Gummadi, Sathyanarayana N

    2016-07-01

    pH and resident time of injected slug plays a critical role in characterizing the reservoir for potential microbial enhanced oil recovery (MEOR) application. To investigate MEOR processes, a multispecies (microbes-nutrients) reactive transport model in porous media was developed by coupling kinetic and transport model. The present work differs from earlier works by explicitly determining parametric values required for kinetic model by experimental investigations using Pseudomonas putida at different pH conditions and subsequently performing sensitivity analysis of pH, resident time and water saturation on concentrations of microbes, nutrients and biosurfactant within reservoir. The results suggest that nutrient utilization and biosurfactant production are found to be maximum at pH 8 and 7.5 respectively. It is also found that the sucrose and biosurfactant concentrations are highly sensitive to pH rather than reservoir microbial concentration, while at larger resident time and water saturation, the microbial and nutrient concentrations were lesser due to enhanced dispersion. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Mathematical modeling of microbially induced crown corrosion in wastewater collection systems and laboratory investigation and modeling of sulfuric acid corrosion of concrete

    Science.gov (United States)

    Jahani, Fereidoun

    In the model for microbially induced crown corrosion, the diffusion of sulfide inside the concrete pores, its biological conversion to sulfuric acid, and the corrosion of calcium carbonate aggregates are represented. The corrosion front is modeled as a moving boundary. The location of the interface between the corrosion layer and the concrete is determined as part of the solution to the model equations. This model consisted of a system of one dimensional reaction-diffusion equations coupled to an equation describing the movement of the corrosion front. The equations were solved numerically using finite element Galerkin approximation. The concentration profiles of sulfide in the air and the liquid phases, the pH as a function of concrete depth, and the position of the corrosion front. A new equation for the corrosion rate was also derived. A more specific model for the degradation of a concrete specimen exposed to a sulfuric acid solution was also studied. In this model, diffusion of hydrogen ions and their reaction with alkaline components of concrete were expressed using Fick's Law of diffusion. The model equations described the moving boundary, the dissolution rate of alkaline components in the concrete, volume increase of sulfuric acid solution over the concrete specimen, and the boundary conditions on the surface of the concrete. An apparatus was designed and experiments were performed to measure pH changes on the surface of concrete. The data were used to calculate the dissolution rate of the concrete and, with the model, to determine the diffusion rate of sulfuric acid in the corrosion layer and corrosion layer thickness. Electrochemical Impedance Spectroscopy (EIS) was used to study the corrosion rate of iron pins embedded in the concrete sample. The open circuit potential (OCP) determined the onset of corrosion on the surface of the pins. Visual observation of the corrosion layer thickness was in good agreement with the simulation results.

  1. Microbial xanthophylls.

    Science.gov (United States)

    Bhosale, Prakash; Bernstein, Paul S

    2005-09-01

    Xanthophylls are oxygenated carotenoids abundant in the human food supply. Lutein, zeaxanthin, and cryptoxanthin are major xanthophyll carotenoids in human plasma. The consumption of these xanthophylls is directly associated with reduction in the risk of cancers, cardiovascular disease, age-related macular degeneration, and cataract formation. Canthaxanthin and astaxanthin also have considerable importance in aquaculture for salmonid and crustacean pigmentation, and are of commercial interest for the pharmaceutical and food industries. Chemical synthesis is a major source for the heavy demand of xanthophylls in the consumer market; however, microbial producers also have potential as commercial sources. In this review, we discuss the biosynthesis, commercial utility, and major microbial sources of xanthophylls. We also present a critical review of current research and technologies involved in promoting microbes as potential commercial sources for mass production.

  2. Of Mice, Men, and Microbial Opsins: How Optogenetics Can Help Hone Mouse Models of Mental Illness.

    Science.gov (United States)

    Marton, Tobias F; Sohal, Vikaas S

    2016-01-01

    Genetic, pharmacologic, and behavioral manipulations have long been powerful tools for generating rodent models to study the neural substrates underlying psychiatric disease. Recent advances in the use of optogenetics in awake behaving rodents has added an additional valuable methodology to this experimental toolkit. Here, we review several recent studies that leverage optogenetic technologies to elucidate neural mechanisms possibly related to depression, anxiety, and obsessive-compulsive disorder. We use a few illustrative examples to highlight key emergent principles about how optogenetics, in conjunction with more established modalities, can help to organize our understanding of how disease-related states, specific neuronal circuits, and various behavioral assays fit into hierarchical frameworks such as the National Institute of Mental Health Research Domain Criteria matrix.

  3. The effect of rosemary preparations on the microbial quality and TBARS value of model pork batters

    Directory of Open Access Journals (Sweden)

    Elżbieta Hać-Szymańczuk

    2011-06-01

    Full Text Available Background. Rosemary (Rosmarinus officinalis L. extracts have a potent antioxidant and antibacterial activity and are widely used in the food industry. The effect of added rosemary preparations on the microbiological quality and process of lipid oxidation of model pork batters, immediately after preparation (“0” and 1, 3 and 7 days of chill-storage (4-6°C was analysed in the study. Material and methods. Experiments were conducted with three types of rosemary preparations, i.e.: dried spice, essential oil and a commercial preparation (TasteGuard P. The experimental material consisted of meat batter produced from porcine musculus longissimus dorsi and water. Microbiological examinations covered determinations of the total count of mesophilic aerobic microorganisms, psychrophilic bacteria, coliforms and enterococci. In turn, chemical analyses involved determination of the TBARS value. Results. The rosemary preparations did not exhibit either antibacterial properties against aerobic mesophilic or psychrophilic bacteria. The essential rosemary oil was observed to inhibit the growth of coliform bacteria and enterococci, whereas the dried spice examined was found to increase the counts of aerobic mesophilic bacteria, coliforms and enterococci. None of the rosemary preparations terminated the lipid oxidation process. Conclusions. The results obtained in this study point to the necessity of continuing investigations to determine the dose of rosemary preparations that would inhibit the growth of microflora being the most frequent cause of raw materials and products spoilage and, simultaneously, restrict oxidation of their lipids.

  4. Impact of food model (micro)structure on the microbial inactivation efficacy of cold atmospheric plasma.

    Science.gov (United States)

    Smet, C; Noriega, E; Rosier, F; Walsh, J L; Valdramidis, V P; Van Impe, J F

    2017-01-02

    The large potential of cold atmospheric plasma (CAP) for food decontamination has recently been recognized. Room-temperature gas plasmas can decontaminate foods without causing undesired changes. This innovative technology is a promising alternative for treating fresh produce. However, more fundamental studies are needed before its application in the food industry. The impact of the food structure on CAP decontamination efficacy of Salmonella Typhimurium and Listeria monocytogenes was studied. Cells were grown planktonically or as surface colonies in/on model systems. Both microorganisms were grown in lab culture media in petri dishes at 20°C until cells reached the stationary phase. Before CAP treatment, cells were deposited in a liquid carrier, on a solid(like) surface or on a filter. A dielectric barrier discharge reactor generated helium-oxygen plasma, which was used to treat samples up to 10min. Although L. monocytogenes is more resistant to CAP treatment, similar trends in inactivation behavior as for S. Typhimurium are observed, with log reductions in the range [1.0-2.9] for S. Typhimurium and [0.2-2.2] for L. monocytogenes. For both microorganisms, cells grown planktonically are easily inactivated, as compared to surface colonies. More stressing growth conditions, due to cell immobilization, result in more resistant cells during CAP treatment. The main difference between the inactivation support systems is the absence or presence of a shoulder phase. For experiments in the liquid carrier, which exhibit a long shoulder, the plasma components need to diffuse and penetrate through the medium. This explains the higher efficacies of CAP treatment on cells deposited on a solid(like) surface or on a filter. This research demonstrates that the food structure influences the cell inactivation behavior and efficacy of CAP, and indicates that food intrinsic factors need to be accounted when designing plasma treatment.

  5. Development of a model for evaluation of microbial cross-contamination in the kitchen.

    Science.gov (United States)

    Zhao, P; Zhao, T; Doyle, M P; Rubino, J R; Meng, J

    1998-08-01

    Foods can become contaminated with pathogenic microorganisms from hands, the cutting board, and knives during preparation in the kitchen. A laboratory model was developed to determine occurrence of cross-contamination and efficacy of decontamination procedures in kitchen food-handling practices. Enterobacter aerogenes B199A, an indicator bacterium with attachment characteristics similar to that of Salmonella spp., was used. Chicken meat with skin inoculated with 10(6) CFU of E. aerogenes B199A/g was cut into small pieces on a sterile cutting board. The extent of cross-contamination occurring from meat to the cutting board and from the cutting board to vegetables (lettuce and cucumbers) subsequently cut on the board was determined. Swab samples from the cutting board, hand washings, and lettuce and cucumber samples revealed that approximately 10(5) CFU of E. aerogenes/cm2 were transferred to the board and hands and approximately 10(3) to 10(4) CFU of E. aerogenes/g to the lettuce and cucumbers. The surfaces of the cutting board and hands were treated with antibacterial agents after cutting the meat, and counts of E. aerogenes on the cutting board and vegetables (lettuce and cucumbers) were determined. Results revealed that use of the disinfectant reduced the population of E. aerogenes to almost nondetectable levels on the cutting boards. The average counts after treatment were Salmonella spp. can be readily transferred to cutting boards during food preparation and then cross-contaminate fresh vegetables if the boards are not cleaned. Application of a kitchen disinfectant can greatly reduce bacterial contamination on cutting boards.

  6. Carbohydrate-free peach (Prunus persica and plum (Prunus domestica juice affects fecal microbial ecology in an obese animal model.

    Directory of Open Access Journals (Sweden)

    Giuliana D Noratto

    Full Text Available BACKGROUND: Growing evidence shows the potential of nutritional interventions to treat obesity but most investigations have utilized non-digestible carbohydrates only. Peach and plum contain high amounts of polyphenols, compounds with demonstrated anti-obesity effects. The underlying process of successfully treating obesity using polyphenols may involve an alteration of the intestinal microbiota. However, this phenomenon is not well understood. METHODOLOGY/PRINCIPAL FINDINGS: Obese Zucker rats were assigned to three groups (peach, plum, and control, n = 10 each, wild-type group was named lean (n = 10. Carbohydrates in the fruit juices were eliminated using enzymatic hydrolysis. Fecal samples were obtained after 11 weeks of fruit or control juice administration. Real-time PCR and 454-pyrosequencing were used to evaluate changes in fecal microbiota. Over 1,500 different Operational Taxonomic Units at 97% similarity were detected in all rats. Several bacterial groups (e.g. Lactobacillus and members of Ruminococcacea were found to be more abundant in the peach but especially in the plum group (plum juice contained 3 times more total polyphenolics compared to peach juice. Principal coordinate analysis based on Unifrac-based unweighted distance matrices revealed a distinct separation between the microbiota of control and treatment groups. These changes in fecal microbiota occurred simultaneously with differences in fecal short-chain acids concentrations between the control and treatment groups as well as a significant decrease in body weight in the plum group. CONCLUSIONS: This study suggests that consumption of carbohydrate-free peach and plum juice has the potential to modify fecal microbial ecology in an obese animal model. The separate contribution of polyphenols and non-polyphenols compounds (vitamins and minerals to the observed changes is unknown.

  7. Evaluating a microbial water quality prediction model for beach management under the revised EU Bathing Water Directive.

    Science.gov (United States)

    Bedri, Zeinab; Corkery, Aisling; O'Sullivan, John J; Deering, Louise A; Demeter, Katalin; Meijer, Wim G; O'Hare, Gregory; Masterson, Bartholomew

    2016-02-01

    The revised Bathing Water Directive (2006/7/EC) requires EU member states to minimise the risk to public health from faecal pollution at bathing waters through improved monitoring and management approaches. While increasingly sophisticated measurement methods (such as microbial source tracking) assist in the management of bathing water resources, the use of deterministic predictive models for this purpose, while having the potential to provide decision making support, remains less common. This study explores an integrated, deterministic catchment-coastal hydro-environmental model as a decision-making tool for beach management which, based on advance predictions of bathing water quality, can inform beach managers on appropriate management actions (to prohibit bathing or advise the public not to bathe) in the event of a poor water quality forecast. The model provides a 'moving window' five-day forecast of Escherichia coli levels at a bathing water compliance point off the Irish coast and the accuracy of bathing water management decisions were investigated for model predictions under two scenarios over the period from the 11th August to the 5th September, 2012. Decisions for Scenario 1 were based on model predictions where rainfall forecasts from a meteorological source (www.yr.no) were used to drive the rainfall-runoff processes in the catchment component of the model, and for Scenario 2, were based on predictions that were improved by incorporating real-time rainfall data from a sensor network within the catchment into the forecasted meteorological input data. The accuracy of the model in the decision-making process was assessed using the contingency table and its metrics. The predictive model gave reasonable outputs to support appropriate decision making for public health protection. Scenario 1 provided real-time predictions that, on 77% of instances during the study period where both predicted and E. coli concentrations were available, would correctly inform a

  8. A multi-perspective review of microbial fuel-cells for wastewater treatment: Bio-electro-chemical, microbiologic and modeling aspects

    Science.gov (United States)

    Capodaglio, Andrea G.; Molognoni, Daniele; Pons, Anna Vilajeliu

    2016-07-01

    Microbial Fuel Cells (MFCs) represent a still novel technology for the recovery of energy and resources through wastewater treatment. Although the technology is quite appealing, due its potential benefits, its practical application is still hampered by several drawbacks, such as systems instability (especially when attempting to scale-up reactors from laboratory prototype), internally competing microbial reactions, and limited power generation. This paper is an attempt to address several of the operational issues related to MFCs application to wastewater treatment, in particular when dealing with simultaneous organic matter and nitrogen pollution control. Reactor configuration, operational schemes, electrochemical and microbiological characterization, optimization methods and modelling strategies are reviewed and discussed with a multidisciplinary, multi-perspective approach. The conclusions drawn herein can be of practical interest for all MFC researchers dealing with domestic or industrial wastewater treatment..

  9. Extracting data from the muck: deriving biological insight from complex microbial communities and non-model organisms with next generation sequencing.

    Science.gov (United States)

    Solomon, Kevin V; Haitjema, Charles H; Thompson, Dawn A; O'Malley, Michelle A

    2014-08-01

    It is becoming increasingly clear that microbes within microbial communities, for which cultured isolates have not yet been obtained, have an immense, untapped reservoir of enzymes that could help address grand challenges in human health, energy, and sustainability. Despite the obstacles associated with culturing these microbes, recent advances in next-generation sequencing (NGS) have made it possible to explore complex microbial communities in their native context for the first time. Key to extracting meaning from rapidly growing NGS datasets are bioinformatics tools that assemble the sequence data, annotate homologous sequences and interrogate it to reveal regulatory patterns. Complementing this are advances in proteomics that can link NGS data to biological function. This combination of next generation sequencing, proteomics and bioinformatic analysis forms a powerful tool to study non-model microbes, which will transform what we know about these dynamic systems.

  10. A multi-perspective review of microbial fuel-cells for wastewater treatment: Bio-electro-chemical, microbiologic and modeling aspects

    Energy Technology Data Exchange (ETDEWEB)

    Capodaglio, Andrea G., E-mail: capo@unipv.it; Molognoni, Daniele [DICAr, University of Pavia (Italy); Pons, Anna Vilajeliu [LEQUIA, University of Girona (Spain)

    2016-07-25

    Microbial Fuel Cells (MFCs) represent a still novel technology for the recovery of energy and resources through wastewater treatment. Although the technology is quite appealing, due its potential benefits, its practical application is still hampered by several drawbacks, such as systems instability (especially when attempting to scale-up reactors from laboratory prototype), internally competing microbial reactions, and limited power generation. This paper is an attempt to address several of the operational issues related to MFCs application to wastewater treatment, in particular when dealing with simultaneous organic matter and nitrogen pollution control. Reactor configuration, operational schemes, electrochemical and microbiological characterization, optimization methods and modelling strategies are reviewed and discussed with a multidisciplinary, multi-perspective approach. The conclusions drawn herein can be of practical interest for all MFC researchers dealing with domestic or industrial wastewater treatment..

  11. Spatial pattern formation of microbes at the soil microscale affect soil C and N turnover in an individual-based microbial community model

    Science.gov (United States)

    Kaiser, Christina; Evans, Sarah; Dieckmann, Ulf; Widder, Stefanie

    2016-04-01

    At the μm-scale, soil is a highly structured and complex environment, both in physical as well as in biological terms, characterized by non-linear interactions between microbes, substrates and minerals. As known from mathematics and theoretical ecology, spatial structure significantly affects the system's behaviour by enabling synergistic dynamics, facilitating diversity, and leading to emergent phenomena such as self-organisation and self-regulation. Such phenomena, however, are rarely considered when investigating mechanisms of microbial soil organic matter turnover. Soil organic matter is the largest terrestrial reservoir for organic carbon (C) and nitrogen (N) and plays a pivotal role in global biogeochemical cycles. Still, the underlying mechanisms of microbial soil organic matter buildup and turnover remain elusive. We explored mechanisms of microbial soil organic matter turnover using an individual-based, stoichiometrically and spatially explicit computer model, which simulates the microbial de-composer system at the soil microscale (i.e. on a grid of 100 x 100 soil microsites). Soil organic matter dynamics in our model emerge as the result of interactions among individual microbes with certain functional traits (f.e. enzyme production rates, growth rates, cell stoichiometry) at the microscale. By degrading complex substrates, and releasing labile substances microbes in our model continusly shape their environment, which in turn feeds back to spatiotemporal dynamics of the microbial community. In order to test the effect of microbial functional traits and organic matter input rate on soil organic matter turnover and C and N storage, we ran the model into steady state using continuous inputs of fresh organic material. Surprisingly, certain parameter settings that induce resource limitation of microbes lead to regular spatial pattern formation (f.e. moving spiral waves) of microbes and substrate at the μm-scale at steady-state. The occurrence of these

  12. Microbial Risk Assessment

    Science.gov (United States)

    Ott, C. M.; Mena, K. D.; Nickerson, C.A.; Pierson, D. L.

    2009-01-01

    Historically, microbiological spaceflight requirements have been established in a subjective manner based upon expert opinion of both environmental and clinical monitoring results and the incidence of disease. The limited amount of data, especially from long-duration missions, has created very conservative requirements based primarily on the concentration of microorganisms. Periodic reevaluations of new data from later missions have allowed some relaxation of these stringent requirements. However, the requirements remain very conservative and subjective in nature, and the risk of crew illness due to infectious microorganisms is not well defined. The use of modeling techniques for microbial risk has been applied in the food and potable water industries and has exceptional potential for spaceflight applications. From a productivity standpoint, this type of modeling can (1) decrease unnecessary costs and resource usage and (2) prevent inadequate or inappropriate data for health assessment. In addition, a quantitative model has several advantages for risk management and communication. By identifying the variable components of the model and the knowledge associated with each component, this type of modeling can: (1) Systematically identify and close knowledge gaps, (2) Systematically identify acceptable and unacceptable risks, (3) Improve communication with stakeholders as to the reasons for resource use, and (4) Facilitate external scientific approval of the NASA requirements. The modeling of microbial risk involves the evaluation of several key factors including hazard identification, crew exposure assessment, dose-response assessment, and risk characterization. Many of these factors are similar to conditions found on Earth; however, the spaceflight environment is very specialized as the inhabitants live in a small, semi-closed environment that is often dependent on regenerative life support systems. To further complicate modeling efforts, microbial dose

  13. Microbial Energy Conversion

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, Merry [American Society for Microbiology (ASM), Washington, DC (United States); Wall, Judy D. [Univ. of Missouri, Columbia, MO (United States)

    2006-10-01

    natural gas from the subsurface. The participants discussed--key microbial conversion paths; overarching research issues; current funding models and microbial energy research; education, training, interdisciplinary cooperation and communication. Their recommendations are--Cellulose and lignocellulose are the preferred substrates for producing liquid transportation fuels, of which ethanol is the most commonly considered example. Generating fuels from these materials is still difficult and costly. A number of challenges need to be met in order to make the conversion of cellulose and lignocellulose to transportation fuels more cost-competitive. The design of hydrogen-producing bioreactors must be improved in order to more effectively manage hydrogen removal, oxygen exclusion, and, in the case of photobioreactors, to capture light energy more efficiently. Methane production may be optimized by fine-tuning methanogenic microbial communities. The ability to transfer electrons to an anode in a microbial fuel cell is probably very broadly distributed in the bacterial world. The scientific community needs a larger inventory of cultivated microorganisms from which to draw for energy conversion development. New and unusual organisms for manufacturing fuels and for use in fuel cells can be discovered using bioprospecting techniques. Particular emphasis should be placed on finding microbes, microbial communities, and enzymes that can enhance the conversion of lignocellulosic biomass to usable sugars. Many of the microbial processes critical to energy conversion are carried out by complex communities of organisms, and there is a need to better understand the community interactions that make these transformations possible. Better understanding of microbial community structure, robustness, networks, homeostasis, and cell-to-cell signaling is also needed. A better understanding of the basic enzymology of microorganisms is needed in order to move forward more quickly with microbial energy

  14. An investigation of the sensitivity of low-field nuclear magnetic resonance to microbial growth and activity

    Science.gov (United States)

    Zhang, C.; Keating, K.

    2014-12-01

    Microbes and microbial processes play a significant role in shaping subsurface environments and are involved in applications ranging from microbially enhanced oil recovery to soil and groundwater contaminant remediation. Stimulated microbial growth in such applications could cause wide variety of changes of physical/chemical properties in the subsurface; however, due to the complexity of subsurface systems,it is difficult to monitor the growth of microbes and microbial activity in porous media. The focus of this research is to determine if low-field nuclear magnetic resonance (NMR), a method used in well logging to characterize fluids in hydrocarbon reservoirs or water in aquifers, can be used to directly detect the presence and the growth of microbes in geologic media. In this laboratory study, low-field NMR (2 MHz) relaxation measurements were collected on microbial suspensions with measured densities (i.e. biomasses), microbial pellets (live and dead), and inoculated silica. We focus on the direct contribution of microbes to the NMR signals in the absence of biomineralization. Shewanella oneidensis (MR-1), a facultative metal reducer known to play an important role in subsurface environments, were used as a model organism and were inoculated under aerobic condition. Data were collected using a CPMG pulse sequence, which was to determine the T2-distribution, and using a gradient spin-echo (PGSE) plus CPMG pulse sequence, which was used to encode diffusion properties and determine the effective diffusion-spin-spin relaxation correlation (D-T2) plot. Our data show no obvious change in the T2-distribution as S. oneidensis density varied in suspension, but show a clear distinction in the T2-distribution and D-T2 plots between live and dead cell pellets. A decrease in the T2-distribution is observed in the inoculated sand column. These results will provide a basis for understanding the effect of microbes within geologic media on low-field NMR measurements. This

  15. Microbial Metalloproteomics

    Directory of Open Access Journals (Sweden)

    Peter-Leon Hagedoorn

    2015-12-01

    Full Text Available Metalloproteomics is a rapidly developing field of science that involves the comprehensive analysis of all metal-containing or metal-binding proteins in a biological sample. The purpose of this review is to offer a comprehensive overview of the research involving approaches that can be categorized as inductively coupled plasma (ICP-MS based methods, X-ray absorption/fluorescence, radionuclide based methods and bioinformatics. Important discoveries in microbial proteomics will be reviewed, as well as the outlook to new emerging approaches and research areas.

  16. Microbial Ecosystems, Protection of

    NARCIS (Netherlands)

    Bodelier, P.L.E.; Nelson, K.E.

    2014-01-01

    Synonyms Conservation of microbial diversity and ecosystem functions provided by microbes; Preservation of microbial diversity and ecosystem functions provided by microbes Definition The use, management, and conservation of ecosystems in order to preserve microbial diversity and functioning.

  17. Microbial Ecosystems, Protection of

    NARCIS (Netherlands)

    Bodelier, P.L.E.; Nelson, K.E.

    2014-01-01

    Synonyms Conservation of microbial diversity and ecosystem functions provided by microbes; Preservation of microbial diversity and ecosystem functions provided by microbes Definition The use, management, and conservation of ecosystems in order to preserve microbial diversity and functioning. Introdu

  18. Shifts in Microbial Community Structure with Changes in Cathodic Potential in Marine Sediment Microcosms

    Science.gov (United States)

    Lam, B. R.; Rowe, A. R.; Nealson, K. H.

    2014-12-01

    Microorganisms comprise more than 90% of the biomass of the ocean. Their ability to thrive and survive in a wide range of environments from oligotrophic waters to the deep subsurface stems from the great metabolic versatility that exists among them. This metabolic versatility has further expanded with the discovery of extracellular electron transport (EET). EET is the capability of microorganisms to transfer electrons to and from insoluble substrates outside of the cell. Much of what is known about EET comes from studies of model metal reducing microorganisms in the groups Shewanellaceae and Geobacteraceae. However, EET is not limited to these metal reducing microorganisms, and may play a large role in the biogeochemical cycling of several elements. We have developed an electrochemical culturing technique designed to target microorganisms with EET ability and tested these methods in marine sediments. The use of electrodes allows for greater control and quantification of electrons flowing to insoluble substrates as opposed to insoluble substrates such as minerals that are often difficult to measure. We have recently shown that poising electrodes at different redox potentials will enrich for different microbial groups and thus possible metabolisms. In marine sediment microcosms, triplicate electrodes were poised at different cathodic (electron donating) potentials (-300, -400, -500 and -600 mV) and incubated for eight weeks. Community analysis of the 16S rRNA revealed that at lower negative potentials (-500 and -600 mV), more sulfate reducing bacteria in the class Deltaproteobacteria were enriched in comparison to the communities at -300 and -400 mV being dominated by microorganisms within Alphaproteobacteria, Gammaproteobacteria, and Clostridia. This can be explained by sulfate (abundant in seawater) becoming a more energetically favorable electron acceptor with lower applied potentials. In addition, communities at higher potentials showed greater enrichment of the

  19. Towards Biogeochemical Modeling of Anaerobic Oxidation of Methane: Characterization of Microbial Communities in Methane-bearing North American Continental Margin Sediments

    Science.gov (United States)

    Graw, M. F.; Solomon, E. A.; Chrisler, W.; Krause, S.; Treude, T.; Ruppel, C. D.; Pohlman, J.; Colwell, F. S.

    2015-12-01

    Methane advecting through continental margin sediments may enter the water column and potentially contribute to ocean acidification and increase atmospheric methane concentrations. Anaerobic oxidation of methane (AOM), mediated by syntrophic consortia of anaerobic methanotrophic archaea and sulfate-reducing bacteria (ANME-SRB), consumes nearly all dissolved methane in methane-bearing sediments before it reaches the sediment-water interface. Despite the significant role ANME-SRB play in carbon cycling, our knowledge of these organisms and their surrounding microbial communities is limited. Our objective is to develop a metabolic model of ANME-SRB within methane-bearing sediments and to couple this to a geochemical reaction-transport model for these margins. As a first step towards this goal, we undertook fluorescent microscopic imaging, 16S rRNA gene deep-sequencing, and shotgun metagenomic sequencing of sediments from the US Pacific (Washington) and northern Atlantic margins where ANME-SRB are present. A successful Illumina MiSeq sequencing run yielded 106,257 bacterial and 857,834 archaeal 16S rRNA gene sequences from 12 communities from the Washington Margin using both universal prokaryotic and archaeal-specific primer sets. Fluorescent microscopy confirmed the presence of cells of the ANME-2c lineage in the sequenced communities. Microbial community characterization was coupled with measurements of sediment physical and geochemical properties and, for samples from the US Atlantic margin, 14C-based measurements of AOM rates and 35S-based measurements of sulfate reduction rates. These findings have the potential to increase understanding of ANME-SRB, their surrounding microbial communities, and their role in carbon cycling within continental margins. In addition, they pave the way for future efforts at developing a metabolic model of ANME-SRB and coupling it to geochemical models of the US Washington and Atlantic margins.

  20. Microbial field pilot study

    Energy Technology Data Exchange (ETDEWEB)

    Knapp, R.M.; McInerney, M.J.; Menzie, D.E.; Chisholm, J.L.

    1992-03-01

    The objective of this project is to perform a microbial enhanced oil recovery field pilot in the Southeast Vassar Vertz Sand Unit (SEVVSU) in Payne County, Oklahoma. Indigenous, anaerobic, nitrate reducing bacteria will be stimulated to selectively plug flow paths which have been referentially swept by a prior waterflood. This will force future flood water to invade bypassed regions of the reservoir and increase sweep efficiency. This report covers progress made during the second year, January 1, 1990 to December 31, 1990, of the Microbial Field Pilot Study project. Information on reservoir ecology, surface facilities design, operation of the unit, core experiments, modeling of microbial processes, and reservoir characterization and simulation are presented in the report. To better understand the ecology of the target reservoir, additional analyses of the fluids which support bacteriological growth and the microbiology of the reservoir were performed. The results of the produced and injected water analysis show increasing sulfide concentrations with respect to time. In March of 1990 Mesa Limited Partnership sold their interest in the SEVVSU to Sullivan and Company. In April, Sullivan and Company assumed operation of the field. The facilities for the field operation of the pilot were refined and implementation was begun. Core flood experiments conducted during the last year were used to help define possible mechanisms involved in microbial enhanced oil recovery. The experiments were performed at SEVVSU temperature using fluids and inoculum from the unit. The model described in last year's report was further validated using results from a core flood experiment. The model was able to simulate the results of one of the core flood experiments with good quality.

  1. Microbial field pilot study

    Energy Technology Data Exchange (ETDEWEB)

    Knapp, R.M.; McInerney, M.J.; Menzie, D.E.; Chisholm, J.L.

    1992-03-01

    The objective of this project is to perform a microbial enhanced oil recovery field pilot in the Southeast Vassar Vertz Sand Unit (SEVVSU) in Payne County, Oklahoma. Indigenous, anaerobic, nitrate reducing bacteria will be stimulated to selectively plug flow paths which have been referentially swept by a prior waterflood. This will force future flood water to invade bypassed regions of the reservoir and increase sweep efficiency. This report covers progress made during the second year, January 1, 1990 to December 31, 1990, of the Microbial Field Pilot Study project. Information on reservoir ecology, surface facilities design, operation of the unit, core experiments, modeling of microbial processes, and reservoir characterization and simulation are presented in the report. To better understand the ecology of the target reservoir, additional analyses of the fluids which support bacteriological growth and the microbiology of the reservoir were performed. The results of the produced and injected water analysis show increasing sulfide concentrations with respect to time. In March of 1990 Mesa Limited Partnership sold their interest in the SEVVSU to Sullivan and Company. In April, Sullivan and Company assumed operation of the field. The facilities for the field operation of the pilot were refined and implementation was begun. Core flood experiments conducted during the last year were used to help define possible mechanisms involved in microbial enhanced oil recovery. The experiments were performed at SEVVSU temperature using fluids and inoculum from the unit. The model described in last year`s report was further validated using results from a core flood experiment. The model was able to simulate the results of one of the core flood experiments with good quality.

  2. Hydrothermal Habitats: Measurements of Bulk Microbial Elemental Composition, and Models of Hydrothermal Influences on the Evolution of Dwarf Planets

    Science.gov (United States)

    Neveu, Marc Francois Laurent

    Finding habitable worlds is a key driver of solar system exploration. Many solar system missions seek environments providing liquid water, energy, and nutrients, the three ingredients necessary to sustain life. Such environments include hydrothermal systems, spatially-confined systems where hot aqueous fluid circulates through rock by convection. I sought to characterize hydrothermal microbial communities, collected in hot spring sediments and mats at Yellowstone National Park, USA, by measuring their bulk elemental composition. To do so, one must minimize the contribution of non-biological material to the samples analyzed. I demonstrate that this can be achieved using a separation method that takes advantage of the density contrast between cells and sediment and preserves cellular elemental contents. Using this method, I show that in spite of the tremendous physical, chemical, and taxonomic diversity of Yellowstone hot springs, the composition of microorganisms there is surprisingly ordinary. This suggests the existence of a stoichiometric envelope common to all life as we know it. Thus, future planetary investigations could use elemental fingerprints to assess the astrobiological potential of hydrothermal settings beyond Earth. Indeed, hydrothermal activity may be widespread in the solar system. Most solar system worlds larger than 200 km in radius are dwarf planets, likely composed of an icy, cometary mantle surrounding a rocky, chondritic core. I enhance a dwarf planet evolution code, including the effects of core fracturing and hydrothermal circulation, to demonstrate that dwarf planets likely have undergone extensive water-rock interaction. This supports observations of aqueous products on their surfaces. I simulate the alteration of chondritic rock by pure water or cometary fluid to show that aqueous alteration feeds back on geophysical evolution: it modifies the fluid antifreeze content, affecting its persistence over geological timescales; and the

  3. Accumulation and transport of microbial-size particles in a pressure protected model burn unit: CFD simulations and experimental evidence

    Directory of Open Access Journals (Sweden)

    Mimoun Maurice

    2011-03-01

    Full Text Available Abstract Background Controlling airborne contamination is of major importance in burn units because of the high susceptibility of burned patients to infections and the unique environmental conditions that can accentuate the infection risk. In particular the required elevated temperatures in the patient room can create thermal convection flows which can transport airborne contaminates throughout the unit. In order to estimate this risk and optimize the design of an intensive care room intended to host severely burned patients, we have relied on a computational fluid dynamic methodology (CFD. Methods The study was carried out in 4 steps: i patient room design, ii CFD simulations of patient room design to model air flows throughout the patient room, adjacent anterooms and the corridor, iii construction of a prototype room and subsequent experimental studies to characterize its performance iv qualitative comparison of the tendencies between CFD prediction and experimental results. The Electricité De France (EDF open-source software Code_Saturne® (http://www.code-saturne.org was used and CFD simulations were conducted with an hexahedral mesh containing about 300 000 computational cells. The computational domain included the treatment room and two anterooms including equipment, staff and patient. Experiments with inert aerosol particles followed by time-resolved particle counting were conducted in the prototype room for comparison with the CFD observations. Results We found that thermal convection can create contaminated zones near the ceiling of the room, which can subsequently lead to contaminate transfer in adjacent rooms. Experimental confirmation of these phenomena agreed well with CFD predictions and showed that particles greater than one micron (i.e. bacterial or fungal spore sizes can be influenced by these thermally induced flows. When the temperature difference between rooms was 7°C, a significant contamination transfer was observed to

  4. Coupling a continuous watershed-scale microbial fate and transport model with a stochastic dose-response model to estimate risk of illness in an urban watershed.

    Science.gov (United States)

    Liao, Hehuan; Krometis, Leigh-Anne H; Kline, Karen

    2016-05-01

    Within the United States, elevated levels of fecal indicator bacteria (FIB) remain the leading cause of surface water-quality impairments requiring formal remediation plans under the federal Clean Water Act's Total Maximum Daily Load (TMDL) program. The sufficiency of compliance with numerical FIB criteria as the targeted endpoint of TMDL remediation plans may be questionable given poor correlations between FIB and pathogenic microorganisms and varying degrees of risk associated with exposure to different fecal pollution sources (e.g. human vs animal). The present study linked a watershed-scale FIB fate and transport model with a dose-response model to continuously predict human health risks via quantitative microbial risk assessment (QMRA), for comparison to regulatory benchmarks. This process permitted comparison of risks associated with different fecal pollution sources in an impaired urban watershed in order to identify remediation priorities. Results indicate that total human illness risks were consistently higher than the regulatory benchmark of 36 illnesses/1000 people for the study watershed, even when the predicted FIB levels were in compliance with the Escherichia coli geometric mean standard of 126CFU/100mL. Sanitary sewer overflows were associated with the greatest risk of illness. This is of particular concern, given increasing indications that sewer leakage is ubiquitous in urban areas, yet not typically fully accounted for during TMDL development. Uncertainty analysis suggested the accuracy of risk estimates would be improved by more detailed knowledge of site-specific pathogen presence and densities. While previous applications of the QMRA process to impaired waterways have mostly focused on single storm events or hypothetical situations, the continuous modeling framework presented in this study could be integrated into long-term water quality management planning, especially the United States' TMDL program, providing greater clarity to watershed

  5. Establishing equivalence for microbial-growth-inhibitory effects ("iso-hurdle rules") by analyzing disparate listeria monocytogenes data with a gamma-type predictive model.

    Science.gov (United States)

    Pujol, Laure; Kan-King-Yu, Denis; Le Marc, Yvan; Johnston, Moira D; Rama-Heuzard, Florence; Guillou, Sandrine; McClure, Peter; Membré, Jeanne-Marie

    2012-02-01

    Preservative factors act as hurdles against microorganisms by inhibiting their growth; these are essential control measures for particular food-borne pathogens. Different combinations of hurdles can be quantified and compared to each other in terms of their inhibitory effect ("iso-hurdle"). We present here a methodology for establishing microbial iso-hurdle rules in three steps: (i) developing a predictive model based on existing but disparate data sets, (ii) building an experimental design focused on the iso-hurdles using the model output, and (iii) validating the model and the iso-hurdle rules with new data. The methodology is illustrated with Listeria monocytogenes. Existing data from industry, a public database, and the literature were collected and analyzed, after which a total of 650 growth rates were retained. A gamma-type model was developed for the factors temperature, pH, a(w), and acetic, lactic, and sorbic acids. Three iso-hurdle rules were assessed (40 logcount curves generated): salt replacement by addition of organic acids, sorbic acid replacement by addition of acetic and lactic acid, and sorbic acid replacement by addition of lactic/acetic acid and salt. For the three rules, the growth rates were equivalent in the whole experimental domain (γ from 0.1 to 0.5). The lag times were also equivalent in the case of mild inhibitory conditions (γ ≥ 0.2), while they were longer in the presence of salt than acids under stress conditions (γ microbial safety and stability.

  6. Modeling microbial spoilage and quality of gilthead seabream fillets: combined effect of osmotic pretreatment, modified atmosphere packaging, and nisin on shelf life.

    Science.gov (United States)

    Tsironi, Theofania N; Taoukis, Petros S

    2010-05-01

    The objective of the study was the kinetic modeling of the effect of storage temperature on the quality and shelf life of chilled fish, modified atmosphere-packed (MAP), and osmotically pretreated with the addition of nisin as antimicrobial agent. Fresh gilthead seabream (Sparus aurata) fillets were osmotically treated with 50% high dextrose equivalent maltodextrin (DE 47) plus 5% NaCl. Water loss, solid gain, salt content, and water activity were monitored throughout treatment and treatment conditions were selected for the shelf life study. Untreated and osmotically pretreated slices with and without nisin (2 x 10(4) IU/100 g osmotic solution), packed in air or modified atmosphere (50% CO(2)-50% air), and stored at controlled isothermal conditions (0, 5, 10, and 15 degrees C) were studied. Quality assessment and modeling were based on growth of several microbial indices, total volatile nitrogen, trimethylamine nitrogen, lipid oxidation (TBARS), and sensory scoring. Temperature dependence of quality loss rates was modeled by the Arrhenius equation, validated under dynamic conditions. Pretreated samples showed improved quality stability during subsequent refrigerated storage, in terms of microbial growth, chemical changes, and organoleptic degradation. Osmotic pretreatment with the addition of nisin in combination with MAP was the most effective treatment resulting in significant shelf life extension of gilthead seabream fillets (48 days compared to 10 days for the control at 0 degrees C).

  7. The microbial ocean from genomes to biomes.

    Science.gov (United States)

    DeLong, Edward F

    2009-05-14

    Numerically, microbial species dominate the oceans, yet their population dynamics, metabolic complexity and synergistic interactions remain largely uncharted. A full understanding of life in the ocean requires more than knowledge of marine microbial taxa and their genome sequences. The latest experimental techniques and analytical approaches can provide a fresh perspective on the biological interactions within marine ecosystems, aiding in the construction of predictive models that can interrelate microbial dynamics with the biogeochemical matter and energy fluxes that make up the ocean ecosystem.

  8. MICROBIAL DEGRADATION OF SEVEN AMIDES BY SUSPENDED BACTERIAL POPULATIONS

    Science.gov (United States)

    Microbial transformation rate constants were determined for seven amides in natural pond water. A second-order mathematical rate expression served as the model for describing the microbial transformation. Also investigated was the relationship between the infrared spectra and the...

  9. Molecular ecology of microbial mats.

    Science.gov (United States)

    Bolhuis, Henk; Cretoiu, Mariana Silvia; Stal, Lucas J

    2014-11-01

    Phototrophic microbial mats are ideal model systems for ecological and evolutionary analysis of highly diverse microbial communities. Microbial mats are small-scale, nearly closed, and self-sustaining benthic ecosystems that comprise the major element cycles, trophic levels, and food webs. The steep and fluctuating physicochemical microgradients, that are the result of the ever changing environmental conditions and of the microorganisms' own activities, give rise to a plethora of potential niches resulting in the formation of one of the most diverse microbial ecosystems known to date. For several decades, microbial mats have been studied extensively and more recently molecular biological techniques have been introduced that allowed assessing and investigating the diversity and functioning of these systems. These investigations also involved metagenomics analyses using high-throughput DNA and RNA sequencing. Here, we summarize some of the latest developments in metagenomic analysis of three representative phototrophic microbial mat types (coastal, hot spring, and hypersaline). We also present a comparison of the available metagenomic data sets from mats emphasizing the major differences between them as well as elucidating the overlap in overall community composition.

  10. Constraints on mechanisms and rates of anaerobic oxidation of methane by microbial consortia: process-based modeling of ANME-2 archaea and sulfate reducing bacteria interactions

    Directory of Open Access Journals (Sweden)

    B. Orcutt

    2008-11-01

    Full Text Available Anaerobic oxidation of methane (AOM is the main process responsible for the removal of methane generated in Earth's marine subsurface environments. However, the biochemical mechanism of AOM remains elusive. By explicitly resolving the observed spatial arrangement of methanotrophic archaea and sulfate reducing bacteria found in consortia mediating AOM, potential intermediates involved in the electron transfer between the methane oxidizing and sulfate reducing partners were investigated via a consortium-scale reaction transport model that integrates the effect of diffusional transport with thermodynamic and kinetic controls on microbial activity. Model simulations were used to assess the impact of poorly constrained microbial characteristics such as minimum energy requirements to sustain metabolism and cell specific rates. The role of environmental conditions such as the influence of methane levels on the feasibility of H2, formate and acetate as intermediate species, and the impact of the abundance of intermediate species on pathway reversal were examined. The results show that higher production rates of intermediates via AOM lead to increased diffusive fluxes from the methane oxidizing archaea to sulfate reducing bacteria, but the build-up of the exchangeable species can cause the energy yield of AOM to drop below that required for ATP production. Comparison to data from laboratory experiments shows that under the experimental conditions of Nauhaus et al. (2007, none of the potential intermediates considered here is able to support metabolic activity matching the measured rates.

  11. Coupling a continuous watershed-scale microbial fate and transport model with a stochastic dose-response model to estimate risk of illness in an urban watershed

    Energy Technology Data Exchange (ETDEWEB)

    Liao, Hehuan, E-mail: hehuan86@vt.edu [Department of Biological Systems Engineering, Virginia Tech, 155 Ag Quad Lane, Blacksburg, VA 24061 (United States); Krometis, Leigh-Anne H. [Department of Biological Systems Engineering, Virginia Tech, 155 Ag Quad Lane, Blacksburg, VA 24061 (United States); Kline, Karen [Department of Biological Systems Engineering, Virginia Tech, 155 Ag Quad Lane, Blacksburg, VA 24061 (United States); Center for Watershed Studies, Virginia Tech, 155 Ag Quad Lane, Blacksburg, VA 24061 (United States)

    2016-05-01

    Within the United States, elevated levels of fecal indicator bacteria (FIB) remain the leading cause of surface water-quality impairments requiring formal remediation plans under the federal Clean Water Act's Total Maximum Daily Load (TMDL) program. The sufficiency of compliance with numerical FIB criteria as the targeted endpoint of TMDL remediation plans may be questionable given poor correlations between FIB and pathogenic microorganisms and varying degrees of risk associated with exposure to different fecal pollution sources (e.g. human vs animal). The present study linked a watershed-scale FIB fate and transport model with a dose-response model to continuously predict human health risks via quantitative microbial risk assessment (QMRA), for comparison to regulatory benchmarks. This process permitted comparison of risks associated with different fecal pollution sources in an impaired urban watershed in order to identify remediation priorities. Results indicate that total human illness risks were consistently higher than the regulatory benchmark of 36 illnesses/1000 people for the study watershed, even when the predicted FIB levels were in compliance with the Escherichia coli geometric mean standard of 126 CFU/100 mL. Sanitary sewer overflows were associated with the greatest risk of illness. This is of particular concern, given increasing indications that sewer leakage is ubiquitous in urban areas, yet not typically fully accounted for during TMDL development. Uncertainty analysis suggested the accuracy of risk estimates would be improved by more detailed knowledge of site-specific pathogen presence and densities. While previous applications of the QMRA process to impaired waterways have mostly focused on single storm events or hypothetical situations, the continuous modeling framework presented in this study could be integrated into long-term water quality management planning, especially the United States' TMDL program, providing greater clarity to

  12. Systems biology of Microbial Communities

    Energy Technology Data Exchange (ETDEWEB)

    Navid, A; Ghim, C; Fenley, A; Yoon, S; Lee, S; Almaas, E

    2008-04-11

    Microbes exist naturally in a wide range of environments, spanning the extremes of high acidity and high temperature to soil and the ocean, in communities where their interactions are significant. We present a practical discussion of three different approaches for modeling microbial communities: rate equations, individual-based modeling, and population dynamics. We illustrate the approaches with detailed examples. Each approach is best fit to different levels of system representation, and they have different needs for detailed biological input. Thus, this set of approaches is able to address the operation and function of microbial communities on a wide range of organizational levels.

  13. Microbial successions are associated with changes in chemical profiles of a model refrigerated fresh pork sausage during an 80-day shelf life study.

    Science.gov (United States)

    Benson, Andrew K; David, Jairus R D; Gilbreth, Stefanie Evans; Smith, Gordon; Nietfeldt, Joseph; Legge, Ryan; Kim, Jaehyoung; Sinha, Rohita; Duncan, Christopher E; Ma, Junjie; Singh, Indarpal

    2014-09-01

    Fresh pork sausage is produced without a microbial kill step and therefore chilled or frozen to control microbial growth. In this report, the microbiota in a chilled fresh pork sausage model produced with or without an antimicrobial combination of sodium lactate and sodium diacetate was studied using a combination of traditional microbiological methods and deep pyrosequencing of 16S rRNA gene amplicons. In the untreated system, microbial populations rose from 10(2) to 10(6) CFU/g within 15 days of storage at 4°C, peaking at nearly 10(8) CFU/g by day 30. Pyrosequencing revealed a complex community at day 0, with taxa belonging to the Bacilli, Gammaproteobacteria, Betaproteobacteria, Actinobacteria, Bacteroidetes, and Clostridia. During storage at 4°C, the untreated system displayed a complex succession, with species of Weissella and Leuconostoc that dominate the product at day 0 being displaced by species of Pseudomonas (P. lini and P. psychrophila) within 15 days. By day 30, a second wave of taxa (Lactobacillus graminis, Carnobacterium divergens, Buttiauxella brennerae, Yersinia mollaretti, and a taxon of Serratia) dominated the population, and this succession coincided with significant chemical changes in the matrix. Treatment with lactate-diacetate altered the dynamics dramatically, yielding a monophasic growth curve of a single species of Lactobacillus (L. graminis), followed by a uniform selective die-off of the majority of species in the population. Of the six species of Lactobacillus that were routinely detected, L. graminis became the dominant member in all samples, and its origins were traced to the spice blend used in the formulation.

  14. Modelling sediment-microbial dynamics in the South Nation River, Ontario, Canada: Towards the prediction of aquatic and human health risk.

    Science.gov (United States)

    Droppo, I G; Krishnappan, B G; Liss, S N; Marvin, C; Biberhofer, J

    2011-06-01

    Runoff from agricultural watersheds can carry a number of agricultural pollutants and pathogens; often associated with the sediment fraction. Deposition of this sediment can impact water quality and the ecology of the river, and the re-suspension of such sediment can become sources of contamination for reaches downstream. In this paper a modelling framework to predict sediment and associated microbial erosion, transport and deposition is proposed for the South Nation River, Ontario, Canada. The modelling framework is based on empirical relationships (deposition and re-suspension fluxes), derived from laboratory experiments in a rotating circular flume using sediment collected from the river bed. The bed shear stress governing the deposition and re-suspension processes in the stream was predicted using a one dimensional mobile boundary flow model called MOBED. Counts of live bacteria associated with the suspended and bed sediments were used in conjunction with measured suspended sediment concentration at an upstream section to allow for the estimation of sediment associated microbial erosion, transport and deposition within the modelled river reach. Results suggest that the South Nation River is dominated by deposition periods with erosion only occurring at flows above approximately 250 m(3) s(-1) (above this threshold, all sediment (suspended and eroded) with associated bacteria are transported through the modelled reach). As microbes are often associated with sediments, and can survive for extended periods of time, the river bed is shown to be a possible source of pathogenic organisms for erosion and transport downstream during large storm events. It is clear that, shear levels, bacteria concentrations and suspended sediment are interrelated requiring that these parameters be studied together in order to understand aquatic microbial dynamics. It is important that any management strategies and operational assessments for the protection of human and aquatic health

  15. Modeling and process optimization for microbial desulfurization of coal by using a two-level full factorial design

    Institute of Scientific and Technical Information of China (English)

    Golshani T.; Jorjani E.; Chelgani S.Chehreh; Shafaei S.Z.; Nafechi Y.Heidari

    2013-01-01

    The microbial sulfur removal was investigated on high sulfur content (1.9%) coal concentrate from Tabas coal preparation plant.A mixed culture of ferrooxidans microorganisms was isolated from the tailing dam of the plant.Full factorial method was used to design laboratory test and to evaluate the effects of pH,particle size,iron sulfate concentration,pulp density,and bioleaching time on sulfur reduction.Statistical analyses of experimental data were considered and showed increases of pH and particle size had negative effects on sulfur reduction,whereas increases of pulp density and bioleaching time raised microbial desulfurization rate.According to results of designing,and regarding statistical factors,the optimum values for maximum sulfur reduction were obtained; pH (1.5),particle size (-180μm),iron sulfate concentration (2.7 mmol/L),pulp density (10%) and bioleaching time (14d),which leaded to 51.5% reduction from the total sulfur of sample.

  16. Scaling soil organic matter formation with microbial physiology

    Science.gov (United States)

    Grandy, S.

    2015-12-01

    Soil organic matter (SOM) regulates multiple ecosystem processes, including the exchange of trace gases and primary productivity. Recently, there has been vigorous debate over the role that microbial products play in forming stable soil organic matter, with increasing analytical evidence using isotopes, molecular chemistry, and microcopy all showing that SOM possesses a strong microbial signature. However, scaling these observations - typically made at the molecular to nano or micron scales - to ecosystems or larger scales remains challenging. Here we show that microbial physiological processes such as growth efficiency and growth rate regulate the accumulation of microbial products. These processes are also strongly regulated by ecosystem disturbance and can be readily incorporated into microbial-explicit global C cycling models. In our experiments with model artificial soils accruing SOM and field soils with varying soil C concentrations, the accumulation of SOM is closely related to microbial physiology. Further, the rate and efficiency that isotopically labelled C is converted to soil C depends strongly on microbial physiological characteristics. Given the sensitivity of microbial physiological characteristics to disturbance, these physiological traits can help explain ecosystem-scale SOM responses to environmental changes. Variation in microbial physiology can also be directly incorporated into models, allowing us to scale microbial processes that regulate SOM formation to regional and global scales. Here we demonstrate the incorporation of microbial processes into MIMICS, the MIcrobial MIneral Carbon Stabilization model. Moving from ecosystem to larger scales, we demonstrate that MIMICS, a microbial-explicit model with output strongly dependent on microbial physiology is able to predict large-scale soil C dynamics as well as or better than conventional models. Microbial physiology, which varies among microbial groups and is highly sensitive disturbance, can

  17. Dissolved carbon dioxide and oxygen concentrations in purge of vacuum-packaged pork chops and the relationship to shelf life and models for estimating microbial populations.

    Science.gov (United States)

    Adams, K R; Niebuhr, S E; Dickson, J S

    2015-12-01

    The objectives of this study were to determine the dissolved CO2 and O2 concentrations in the purge of vacuum-packaged pork chops over a 60 day storage period, and to elucidate the relationship of dissolved CO2 and O2 to the microbial populations and shelf life. As the populations of spoilage bacteria increased, the dissolved CO2 increased and the dissolved O2 decreased in the purge. Lactic acid bacteria dominated the spoilage microflora, followed by Enterobacteriaceae and Brochothrix thermosphacta. The surface pH decreased to 5.4 due to carbonic acid and lactic acid production before rising to 5.7 due to ammonia production. A mathematical model was developed which estimated microbial populations based on dissolved CO2 concentrations. Scanning electron microscope images were also taken of the packaging film to observe the biofilm development. The SEM images revealed a two-layer biofilm on the packaging film that was the result of the tri-phase growth environment. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Divergence in plant and microbial allocation strategies explains continental patterns in microbial allocation and biogeochemical fluxes.

    Science.gov (United States)

    Averill, Colin

    2014-10-01

    Allocation trade-offs shape ecological and biogeochemical phenomena at local to global scale. Plant allocation strategies drive major changes in ecosystem carbon cycling. Microbial allocation to enzymes that decompose carbon vs. organic nutrients may similarly affect ecosystem carbon cycling. Current solutions to this allocation problem prioritise stoichiometric tradeoffs implemented in plant ecology. These solutions may not maximise microbial growth and fitness under all conditions, because organic nutrients are also a significant carbon resource for microbes. I created multiple allocation frameworks and simulated microbial growth using a microbial explicit biogeochemical model. I demonstrate that prioritising stoichiometric trade-offs does not optimise microbial allocation, while exploiting organic nutrients as carbon resources does. Analysis of continental-scale enzyme data supports the allocation patterns predicted by this framework, and modelling suggests large deviations in soil C loss based on which strategy is implemented. Therefore, understanding microbial allocation strategies will likely improve our understanding of carbon cycling and climate.

  19. Investment into the future of microbial resources: culture collection funding models and BRC business plans for biological resource centres.

    Science.gov (United States)

    Smith, David; McCluskey, Kevin; Stackebrandt, Erko

    2014-01-01

    Through their long history of public service, diverse microbial Biological Resource Centres (mBRCs) have made myriad contributions to society and science. They have enabled the maintenance of specimens isolated before antibiotics, made available strains showing the development and change of pathogenicity toward animals, humans and plants, and have maintained and provided reference strains to ensure quality and reproducibility of science. However, this has not been achieved without considerable financial commitment. Different collections have unique histories and their support is often tied to their origins. However many collections have grown to serve large constituencies and need to develop novel funding mechanisms. Moreover, several international initiatives have described mBRCs as a factor in economic development and have led to the increased professionalism among mBRCs.

  20. Microbial Genomics Research in China

    Institute of Scientific and Technical Information of China (English)

    ZHAO Guo-ping

    2004-01-01

    @@ Microorganisms, including phage/virus, were initial targets and tools for developing DNA sequencing technology. Microbial genomic study was started as a model system for the Human Genome Project (HGP) and it did successfully supported the HGP, particularly with respect to BAC contig construction and large-scale shotgun sequencing and assembly. Microbial genomics study has become the fastest developed genomics discipline along with HGP, taking the advantage of the organisms' highly diversified physiology, extremely long history of evolution, close relationship with human/environment,as well as relatively small genome sizes and simple systems for functional analysis.

  1. Microbial Genomics Research in China

    Institute of Scientific and Technical Information of China (English)

    ZHAOGuo-ping

    2004-01-01

    Microorganisms, including phage/virus, were initial targets and tools for developing DNA sequencing technology. Microbial genomic study was started as a model system for the Human Genome Project (HGP) and it did successfully supported the HGP, particularly with respect to BAC contig construction and large-scale shotgun sequencing and assembly. Microbial genomics study has become the fastest developed genomics discipline along with HGP, taking the advantage of the organisms' highly diversified physiology, extremely long history of evolution, close relationship with human/environment,as well as relatively small genome sizes and simple systems for functional analysis.

  2. Microbial conversions of terpenoids

    OpenAIRE

    Parshikov, Igor A

    2015-01-01

    The monograph describes examples of the application of microbial technology for obtaining of derivatives of terpenoids. Obtaining new derivatives of terpenoids, including artemisinin derivatives with increased antimalarial activity, is an important goal of research in microbial biotechnology and medicinal chemistry.

  3. Microfluidics and microbial engineering.

    Science.gov (United States)

    Kou, Songzi; Cheng, Danhui; Sun, Fei; Hsing, I-Ming

    2016-02-01

    The combination of microbial engineering and microfluidics is synergistic in nature. For example, microfluidics is benefiting from the outcome of microbial engineering and many reported point-of-care microfluidic devices employ engineered microbes as functional parts for the microsystems. In addition, microbial engineering is facilitated by various microfluidic techniques, due to their inherent strength in high-throughput screening and miniaturization. In this review article, we firstly examine the applications of engineered microbes for toxicity detection, biosensing, and motion generation in microfluidic platforms. Secondly, we look into how microfluidic technologies facilitate the upstream and downstream processes of microbial engineering, including DNA recombination, transformation, target microbe selection, mutant characterization, and microbial function analysis. Thirdly, we highlight an emerging concept in microbial engineering, namely, microbial consortium engineering, where the behavior of a multicultural microbial community rather than that of a single cell/species is delineated. Integrating the disciplines of microfluidics and microbial engineering opens up many new opportunities, for example in diagnostics, engineering of microbial motors, development of portable devices for genetics, high throughput characterization of genetic mutants, isolation and identification of rare/unculturable microbial species, single-cell analysis with high spatio-temporal resolution, and exploration of natural microbial communities.

  4. Childhood microbial keratitis

    Directory of Open Access Journals (Sweden)

    Abdullah G Al Otaibi

    2012-01-01

    Conclusion: Children with suspected microbial keratitis require comprehensive evaluation and management. Early recognition, identifying the predisposing factors and etiological microbial organisms, and instituting appropriate treatment measures have a crucial role in outcome. Ocular trauma was the leading cause of childhood microbial keratitis in our study.

  5. Constraints on mechanisms and rates of anaerobic oxidation of methane by microbial consortia: process-based modeling of ANME-2 archaea and sulfate reducing bacteria interactions

    Directory of Open Access Journals (Sweden)

    B. Orcutt

    2008-05-01

    Full Text Available Anaerobic oxidation of methane (AOM is the main process responsible for the removal of methane generated in Earth's marine subsurface environments. However, the biochemical mechanism of AOM remains elusive. By explicitly resolving the observed spatial arrangement of methanotrophic archaea and sulfate reducing bacteria found in consortia mediating AOM, potential intermediates involved in the electron transfer between the methane oxidizing and sulfate reducing partners were investigated via a consortium-scale reaction transport model that integrates the effect of diffusional transport with thermodynamic and kinetic controls on microbial activity. Model simulations were used to assess the impact of poorly constrained microbial characteristics such as minimum energy requirements to sustain metabolism, substrate affinity and cell specific rates. The role of environmental conditions such as the influence of methane levels on the feasibility of H2, formate and acetate as intermediate species, and the impact of the abundance of intermediate species on pathway reversal was examined. The results show that higher production rates of intermediates via AOM lead to increased diffusive fluxes from the methane oxidizing archaea to sulfate reducing bacteria, but the build-up of the exchangeable species causes the energy yield of AOM to drop below that required for ATP production. Comparison to data from laboratory experiments shows that under the experimental conditions of Nauhaus et al. (2007, neither hydrogen nor formate is exchanged fast enough between the consortia partners to achieve measured rates of metabolic activity, but that acetate exchange might support rates that approach those observed.

  6. Microbial metabolism shifts towards an adverse profile with supplementary iron in the TIM-2 in vitro model of the human colon

    Directory of Open Access Journals (Sweden)

    Guus A.M. Kortman

    2016-01-01

    Full Text Available Oral iron administration in African children can increase the risk for infections. However, it remains unclear to what extent supplementary iron affects the intestinal microbiome. We here explored the impact of iron preparations on microbial growth and metabolism in the well-controlled TNO’s in vitro model of the large intestine (TIM-2. The model was inoculated with a human microbiota, without supplementary iron, or with 50 or 250 µmol/L ferrous sulfate, 50 or 250 µmol/L ferric citrate, or 50 µmol/L hemin. High resolution responses of the microbiota were examined by 16S rDNA pyrosequencing, microarray analysis, and metagenomic sequencing. The metabolome was assessed by fatty acid quantification, gas chromatography-mass spectrometry (GC-MS and 1H-NMR spectroscopy. Cultured intestinal epithelial Caco-2 cells were used to assess fecal water toxicity. Microbiome analysis showed, among others, that supplementary iron induced decreased levels of Bifidobacteriaceae and Lactobacillaceae, while it caused higher levels of Roseburia and Prevotella. Metagenomic analyses showed an enrichment of microbial motility-chemotaxis systems, while the metabolome markedly changed from a saccharolytic to a proteolytic profile in response to iron. Branched chain fatty acids and ammonia levels increased significantly, in particular with ferrous sulfate. Importantly, the metabolite-containing effluent from iron-rich conditions showed increased cytotoxicity to Caco-2 cells. Our explorations indicate that in the absence of host influences, iron induces a more hostile environment characterized by a reduction of microbes that are generally beneficial, and increased levels of bacterial metabolites that can impair the barrier function of a cultured intestinal epithelial monolayer.

  7. Microbial Field Pilot Study

    Energy Technology Data Exchange (ETDEWEB)

    Knapp, R.M.; McInerney, M.J.; Menzie, D.E.; Chisholm, J.L.

    1990-11-01

    This report covers progress made during the first year of the Microbial Field Pilot Study project. Information on reservoir ecology and characterization, facility and treatment design, core experiments, bacterial mobility, and mathematical modeling are addressed. To facilitate an understanding of the ecology of the target reservoir analyses of the fluids which support bacteriological growth and the microbiology of the reservoir were performed. A preliminary design of facilities for the operation of the field pilot test was prepared. In addition, procedures for facilities installation and for injection treatments are described. The Southeast Vassar Vertz Sand Unit (SEVVSU), the site of the proposed field pilot study, is described physically, historically, and geologically. The fields current status is presented and the ongoing reservoir simulation is discussed. Core flood experiments conducted during the last year were used to help define possible mechanisms involved in microbial enhanced oil recovery. Two possible mechanisms, relative permeability effects and changes in the capillary number, are discussed and related to four Berea core experiments' results. The experiments were conducted at reservoir temperature using SEVVSU oil, brine, and bacteria. The movement and activity of bacteria in porous media were investigated by monitoring the growth of bacteria in sandpack cores under no flow conditions. The rate of bacteria advancement through the cores was determined. A mathematical model of the MEOR process has been developed. The model is a three phase, seven species, one dimensional model. Finite difference methods are used for solution. Advection terms in balance equations are represented with a third- order upwind differencing scheme to reduce numerical dispersion and oscillations. The model is applied to a batch fermentation example. 52 refs., 26 figs., 21 tabs.

  8. Comparative Proteomic Analysis of Desulfotomaculum reducens MI-1: Insights into the Metabolic Versatility of a Gram-Positive Sulfate- and Metal-Reducing Bacterium.

    Science.gov (United States)

    Otwell, Anne E; Callister, Stephen J; Zink, Erika M; Smith, Richard D; Richardson, Ruth E

    2016-01-01

    The proteomes of the metabolically versatile and poorly characterized Gram-positive bacterium Desulfotomaculum reducens MI-1 were compared across four cultivation conditions including sulfate reduction, soluble Fe(III) reduction, insoluble Fe(III) reduction, and pyruvate fermentation. Collectively across conditions, we observed at high confidence ~38% of genome-encoded proteins. Here, we focus on proteins that display significant differential abundance on conditions tested. To the best of our knowledge, this is the first full-proteome study focused on a Gram-positive organism cultivated either on sulfate or metal-reducing conditions. Several proteins with uncharacterized function encoded within heterodisulfide reductase (hdr)-containing loci were upregulated on either sulfate (Dred_0633-4, Dred_0689-90, and Dred_1325-30) or Fe(III)-citrate-reducing conditions (Dred_0432-3 and Dred_1778-84). Two of these hdr-containing loci display homology to recently described flavin-based electron bifurcation (FBEB) pathways (Dred_1325-30 and Dred_1778-84). Additionally, we propose that a cluster of proteins, which is homologous to a described FBEB lactate dehydrogenase (LDH) complex, is performing lactate oxidation in D. reducens (Dred_0367-9). Analysis of the putative sulfate reduction machinery in D. reducens revealed that most of these proteins are constitutively expressed across cultivation conditions tested. In addition, peptides from the single multiheme c-type cytochrome (MHC) in the genome were exclusively observed on the insoluble Fe(III) condition, suggesting that this MHC may play a role in reduction of insoluble metals.

  9. Comparative Proteomic Analysis of Desulfotomaculum reducens MI-1: Insights into the Metabolic Versatility of a Gram-positive Sulfate and Metal-reducing Bacterium

    Directory of Open Access Journals (Sweden)

    Anne Elyse Otwell

    2016-02-01

    Full Text Available The proteomes of the metabolically versatile and poorly characterized Gram-positive bacterium Desulfotomaculum reducens MI-1 were compared across four cultivation conditions including sulfate reduction, soluble Fe(III reduction, insoluble Fe(III reduction, and pyruvate fermentation. Collectively across conditions, we observed at high confidence ~38% of genome-encoded proteins. Here, we focus on proteins that display significant differential abundance on conditions tested. To the best of our knowledge, this is the first full-proteome study focused on a Gram-positive organism grown either on sulfate or metal-reducing conditions. Several proteins with uncharacterized function encoded within heterodisulfide reductase (hdr-containing loci were upregulated on either sulfate (Dred_0633-4, Dred_0689-90, and Dred_1325-30 or Fe(III-citrate-reducing conditions (Dred_0432-3 and Dred_1778-84. Two of these hdr-containing loci display homology to recently described flavin-based electron bifurcation (FBEB pathways (Dred_1325-30 and Dred_1778-84. Additionally, we propose that a cluster of proteins, which is homologous to a described FBEB lactate dehydrogenase (LDH complex, is performing lactate oxidation in D. reducens (Dred_0367-9. Analysis of the putative sulfate reduction machinery in D. reducens revealed that most of these proteins are constitutively expressed across cultivation conditions tested. In addition, peptides from the single multiheme c-type cytochrome (MHC in the genome were exclusively observed on the insoluble Fe(III condition, suggesting that this MHC may play a role in reduction of insoluble metals.

  10. A novel derivation of a within-batch sampling plan based on a Poisson-gamma model characterising low microbial counts in foods.

    Science.gov (United States)

    Gonzales-Barron, Ursula; Zwietering, Marcel H; Butler, Francis

    2013-02-01

    This study proposes a novel step-wise methodology for the derivation of a sampling plan by variables for food production systems characterised by relatively low concentrations of the inspected microorganism. After representing the universe of contaminated batches by modelling the between-batch and within-batch variability in microbial counts, a tolerance criterion defining batch acceptability (i.e., up to a tolerance percentage of the food units having microbial concentrations lower or equal to a critical concentration) is established to delineate a limiting quality contour that separates satisfactory from unsatisfactory batches. The problem consists then of finding the optimum decision criterion - arithmetic mean of the analytical results (microbiological limit, m(L)) and the sample size (n) - that satisfies a pre-defined level of confidence measured on the samples' mean distributions from all possible true within-batch distributions. This is approached by obtaining decision landscape curves representing collectively the conditional and joint producer's and consumer's risks at different microbiological limits along with confidence intervals representing uncertainty due to the propagated between-batch variability. Whilst the method requires a number of risk management decisions to be made such as the objective of the sampling plan (GMP-based or risk-based), the modality of derivation, the tolerance criterion or level of safety, and the statistical level of confidence, the proposed method can be used when past monitoring data are available so as to produce statistically-sound dynamic sampling plans with optimised efficiency and discriminatory power. For the illustration of Enterobacteriaceae concentrations on Irish sheep carcasses, a sampling regime of n=10 and m(L)=17.5CFU/cm(2) is recommended to ensure that the producer has at least a 90% confidence of accepting a satisfactory batch whilst the consumer at least a 97.5% confidence that a batch will not be

  11. An integrative computational model for large-scale identification of metalloproteins in microbial genomes: a focus on iron-sulfur cluster proteins.

    Science.gov (United States)

    Estellon, Johan; Ollagnier de Choudens, Sandrine; Smadja, Myriam; Fontecave, Marc; Vandenbrouck, Yves

    2014-10-01

    Metalloproteins represent a ubiquitous group of molecules which are crucial to the survival of all living organisms. While several metal-binding motifs have been defined, it remains challenging to confidently identify metalloproteins from primary protein sequences using computational approaches alone. Here, we describe a comprehensive strategy based on a machine learning approach to design and assess a penalized generalized linear model. We used this strategy to detect members of the iron-sulfur cluster protein family. A new category of descriptors, whose profile is based on profile hidden Markov models, encoding structural information was combined with public descriptors into a linear model. The model was trained and tested on distinct datasets composed of well-characterized iron-sulfur protein sequences, and the resulting model provided higher sensitivity compared to a motif-based approach, while maintaining a good level of specificity. Analysis of this linear model allows us to detect and quantify the contribution of each descriptor, providing us with a better understanding of this complex protein family along with valuable indications for further experimental characterization. Two newly-identified proteins, YhcC and YdiJ, were functionally validated as genuine iron-sulfur proteins, confirming the prediction. The computational model was then applied to over 550 prokaryotic genomes to screen for iron-sulfur proteomes; the results are publicly available at: . This study represents a proof-of-concept for the application of a penalized linear model to identify metalloprotein superfamilies on a large-scale. The application employed here, screening for iron-sulfur proteomes, provides new candidates for further biochemical and structural analysis as well as new resources for an extensive exploration of iron-sulfuromes in the microbial world.

  12. Planetary resources and astroecology. Planetary microcosm models of asteroid and meteorite interiors: electrolyte solutions and microbial growth--implications for space populations and panspermia.

    Science.gov (United States)

    Mautner, Michael N

    2002-01-01

    Planetary microcosms were constructed using extracts from meteorites that simulate solutions in the pores of carbonaceous chondrites. The microcosms were found to support the growth of complex algal and microbial populations. Such astroecology experiments demonstrate how a diverse ecosystem could exist in fluids within asteroids, and in meteorites that land on aqueous planets. The microcosm solutions were obtained by extracting nutrient electrolytes under natural conditions from powders of the Allende (CV3) and Murchison (CM2) meteorites at low (0.02 g/ml) and high (10.0 g/ml) solid/solution ratios. The latter solutions contain > 3 mol/L electrolytes and about 10 g/L organics, that simulate natural fluids in asteroids during aqueous alteration and in the pores of meteorites, which can help prebiotic synthesis and the survival of early microorganisms. These solutions and wet solids were in fact found to support complex self-sustaining microbial communities with populations of 4 x 10(5) algae and 6 x 10(6) bacteria and fungi for long periods (> 8 months). The results show that planetary microcosms based on meteorites can: assay the fertilities of planetary materials; identify space bioresources; target astrobiology exploration; and model past and future space-based ecosystems. The results show that bioresources in the carbonaceous asteroids can sustain a biomass of 10(18) kg, comprising 10(32) microorganisms and a human population of 10(14). The results also suggest that protoplanetary nebulae can support and disperse microorganisms and can be therefore effective environments for natural and directed panspermia.

  13. Universality of human microbial dynamics

    Science.gov (United States)

    Bashan, Amir; Gibson, Travis E.; Friedman, Jonathan; Carey, Vincent J.; Weiss, Scott T.; Hohmann, Elizabeth L.; Liu, Yang-Yu

    2016-06-01

    Human-associated microbial communities have a crucial role in determining our health and well-being, and this has led to the continuing development of microbiome-based therapies such as faecal microbiota transplantation. These microbial communities are very complex, dynamic and highly personalized ecosystems, exhibiting a high degree of inter-individual variability in both species assemblages and abundance profiles. It is not known whether the underlying ecological dynamics of these communities, which can be parameterized by growth rates, and intra- and inter-species interactions in population dynamics models, are largely host-independent (that is, universal) or host-specific. If the inter-individual variability reflects host-specific dynamics due to differences in host lifestyle, physiology or genetics, then generic microbiome manipulations may have unintended consequences, rendering them ineffective or even detrimental. Alternatively, microbial ecosystems of different subjects may exhibit universal dynamics, with the inter-individual variability mainly originating from differences in the sets of colonizing species. Here we develop a new computational method to characterize human microbial dynamics. By applying this method to cross-sectional data from two large-scale metagenomic studies—the Human Microbiome Project and the Student Microbiome Project—we show that gut and mouth microbiomes display pronounced universal dynamics, whereas communities associated with certain skin sites are probably shaped by differences in the host environment. Notably, the universality of gut microbial dynamics is not observed in subjects with recurrent Clostridium difficile infection but is observed in the same set of subjects after faecal microbiota transplantation. These results fundamentally improve our understanding of the processes that shape human microbial ecosystems, and pave the way to designing general microbiome-based therapies.

  14. Multiple-Strain Approach and Probabilistic Modeling of Consumer Habits in Quantitative Microbial Risk Assessment: A Quantitative Assessment of Exposure to Staphylococcal Enterotoxin A in Raw Milk.

    Science.gov (United States)

    Crotta, Matteo; Rizzi, Rita; Varisco, Giorgio; Daminelli, Paolo; Cunico, Elena Cosciani; Luini, Mario; Graber, Hans Ulrich; Paterlini, Franco; Guitian, Javier

    2016-03-01

    Quantitative microbial risk assessment (QMRA) models are extensively applied to inform management of a broad range of food safety risks. Inevitably, QMRA modeling involves an element of simplification of the biological process of interest. Two features that are frequently simplified or disregarded are the pathogenicity of multiple strains of a single pathogen and consumer behavior at the household level. In this study, we developed a QMRA model with a multiple-strain approach and a consumer phase module (CPM) based on uncertainty distributions fitted from field data. We modeled exposure to staphylococcal enterotoxin A in raw milk in Lombardy; a specific enterotoxin production module was thus included. The model is adaptable and could be used to assess the risk related to other pathogens in raw milk as well as other staphylococcal enterotoxins. The multiplestrain approach, implemented as a multinomial process, allowed the inclusion of variability and uncertainty with regard to pathogenicity at the bacterial level. Data from 301 questionnaires submitted to raw milk consumers were used to obtain uncertainty distributions for the CPM. The distributions were modeled to be easily updatable with further data or evidence. The sources of uncertainty due to the multiple-strain approach and the CPM were identified, and their impact on the output was assessed by comparing specific scenarios to the baseline. When the distributions reflecting the uncertainty in consumer behavior were fixed to the 95th percentile, the risk of exposure increased up to 160 times. This reflects the importance of taking into consideration the diversity of consumers' habits at the household level and the impact that the lack of knowledge about variables in the CPM can have on the final QMRA estimates. The multiple-strain approach lends itself to use in other food matrices besides raw milk and allows the model to better capture the complexity of the real world and to be capable of geographical

  15. Development of a predictive model for the growth kinetics of aerobic microbial population on pomegranate marinated chicken breast fillets under isothermal and dynamic temperature conditions.

    Science.gov (United States)

    Lytou, Anastasia; Panagou, Efstathios Z; Nychas, George-John E

    2016-05-01

    The aim of this study was the development of a model to describe the growth kinetics of aerobic microbial population of chicken breast fillets marinated in pomegranate juice under isothermal and dynamic temperature conditions. Moreover, the effect of pomegranate juice on the extension of the shelf life of the product was investigated. Samples (10 g) of chicken breast fillets were immersed in marinades containing pomegranate juice for 3 h at 4 °C following storage under aerobic conditions at 4, 10, and 15 °C for 10 days. Total Viable Counts (TVC), Pseudomonas spp and lactic acid bacteria (LAB) were enumerated, in parallel with sensory assessment (odor and overall appearance) of marinated and non-marinated samples. The Baranyi model was fitted to the growth data of TVC to calculate the maximum specific growth rate (μmax) that was further modeled as a function of temperature using a square root-type model. The validation of the model was conducted under dynamic temperature conditions based on two fluctuating temperature scenarios with periodic changes from 6 to 13 °C. The shelf life was determined both mathematically and with sensory assessment and its temperature dependence was modeled by an Arrhenius type equation. Results showed that the μmax of TVC of marinated samples was significantly lower compared to control samples regardless temperature, while under dynamic temperature conditions the model satisfactorily predicted the growth of TVC in both control and marinated samples. The shelf-life of marinated samples was significantly extended compared to the control (5 days extension at 4 °C). The calculated activation energies (Ea), 82 and 52 kJ/mol for control and marinated samples, respectively, indicated higher temperature dependence of the shelf life of control samples compared to marinated ones. The present results indicated that pomegranate juice could be used as an alternative ingredient in marinades to prolong the shelf life of chicken.

  16. Application of the finite difference method to model pH and substrate concentration in a double-chamber microbial fuel cell.

    Science.gov (United States)

    Zhang, Liwei; Deshusses, Marc

    2014-01-01

    The purpose of this study was to develop a mathematical model that can describe glucose degradation in a microbial fuel cell (MFC) with the use of finite difference approach. The dynamic model can describe both substrate and pH changes in the anode chamber of a double-chamber MFC. It was developed using finite differences and incorporates basic mass transfer concepts. Model simulation results could fit the experimental data for substrate consumption well, while there was a moderate discrepancy (maximum 0.11 pH unit) between the simulated pH and the experimental data. A parametric sensitivity analysis showed that increases in acetate and propionate consumption rates can cause great decrease in chemical oxygen demand (COD) in the anode chamber, while an increase in glucose consumption rate does not result in significant changes of COD reduction. Therefore, the rate limitation steps of glucose degradation are the oxidations of secondary degradation products of glucose (acetate and propionate). Due to the buffering effect of the nutrient solution, the increases in glucose, acetate and propionate consumption rates did not result in much change on pH of the anode chamber.

  17. Gut microbial diversity analysis using Illumina sequencing for functional dyspepsia with liver depression-spleen deficiency syndrome and the interventional Xiaoyaosan in a rat model

    Science.gov (United States)

    Qiu, Juan-Juan; Liu, Zhe; Zhao, Peng; Wang, Xue-Jun; Li, Yu-Chun; Sui, Hua; Owusu, Lawrence; Guo, Hui-Shu; Cai, Zheng-Xu

    2017-01-01

    AIM To investigate gut microbial diversity and the interventional effect of Xiaoyaosan (XYS) in a rat model of functional dyspepsia (FD) with liver depression-spleen deficiency syndrome. METHODS The FD with liver depression-spleen deficiency syndrome rat model was established through classic chronic mild unpredictable stimulation every day. XYS group rats received XYS 1 h before the stimulation. The models were assessed by parameters including state of the rat, weight, sucrose test result and open-field test result. After 3 wk, the stools of rats were collected and genomic DNA was extracted. PCR products of the V4 region of 16S rDNA were sequenced using a barcoded Illumina paired-end sequencing technique. The primary composition of the microbiome in the stool samples was determined and analyzed by cluster analysis. RESULTS Rat models were successfully established, per data from rat state, weight and open-field test. The microbiomes contained 20 phyla from all samples. Firmicutes, Bacteroidetes, Proteobacteria, Cyanobacteria and Tenericutes were the most abundant taxonomic groups. The relative abundance of Firmicutes, Proteobacteria and Cyanobacteria in the model group was higher than that in the normal group. On the contrary, the relative abundance of Bacteroidetes in the model group was lower than that in the normal group. Upon XYS treatment, the relative abundance of all dysregulated phyla was restored to levels similar to those observed in the normal group. Abundance clustering heat map of phyla corroborated the taxonomic distribution. CONCLUSION The microbiome relative abundance of FD rats with liver depression-spleen deficiency syndrome was significantly different from the normal cohort. XYS intervention may effectively adjust the gut dysbacteriosis in FD. PMID:28223725

  18. Effects of aqueous uranyl speciation on the kinetics of microbial uranium reduction

    Science.gov (United States)

    Belli, Keaton M.; DiChristina, Thomas J.; Van Cappellen, Philippe; Taillefert, Martial

    2015-05-01

    The ability to predict the success of the microbial reduction of soluble U(VI) to highly insoluble U(IV) as an in situ bioremediation strategy is complicated by the wide range of geochemical conditions at contaminated sites and the strong influence of aqueous uranyl speciation on the bioavailability and toxicity of U(VI) to metal-reducing bacteria. To determine the effects of aqueous uranyl speciation on uranium bioreduction kinetics, incubations and viability assays with Shewanella putrefaciens strain 200 were conducted over a range of pH and dissolved inorganic carbon (DIC), Ca2+, and Mg2+ concentrations. A speciation-dependent kinetic model was developed to reproduce the observed time series of total dissolved uranium concentration over the range of geochemical conditions tested. The kinetic model yielded the highest rate constant for the reduction of uranyl non-carbonate species (i.e., the 'free' hydrated uranyl ion, uranyl hydroxides, and other minor uranyl complexes), indicating that they represent the most readily reducible fraction of U(VI) despite being the least abundant uranyl species in solution. The presence of DIC, Ca2+, and Mg2+ suppressed the formation of more bioavailable uranyl non-carbonate species and resulted in slower bioreduction rates. At high concentrations of bioavailable U(VI), however, uranium toxicity to S. putrefaciens inhibited bioreduction, and viability assays confirmed that the concentration of non-carbonate uranyl species best predicts the degree of toxicity. The effect of uranium toxicity was accounted for by incorporating the free ion activity model of metal toxicity into the bioreduction rate law. Overall, these results demonstrate that, in the absence of competing terminal electron acceptors, uranium bioreduction kinetics can be predicted over a wide range of geochemical conditions based on the bioavailability and toxicity imparted on U(VI) by solution composition. These findings also imply that the concentration of uranyl non

  19. Integrated Field, Laboratory, and Modeling Studies to Determine the Effects of Linked Microbial and Physical Spatial Heterogeneity on Engineered Vadose Zone Bioremediation

    Energy Technology Data Exchange (ETDEWEB)

    Fred Brokman; John Selker; Mark Rockhold

    2004-01-26

    While numerous techniques exist for remediation of contaminant plumes in groundwater or near the soil surface, remediation methods in the deep vadose zone are less established due to complex transport dynamics and sparse microbial populations. There is a lack of knowledge on how physical and hydrologic features of the vadose zone control microbial growth and colonization in response to nutrient delivery during bioremediation. Yet pollution in the vadose zone poses a serious threat to the groundwater resources lying deeper in the sediment. While the contaminants may be slowly degraded by native microbial communities, microbial degradation rates rarely keep pace with the spread of the pollutant. It is crucial to increase indigenous microbial degradation in the vadose zone to combat groundwater contamination.

  20. Integrated Field, Laboratory, and Modeling Studies to Determine the Effects of Linked Microbial and Physical Spatial Heterogeneity on Engineered Vadose Zone Bioremediation

    Energy Technology Data Exchange (ETDEWEB)

    Brockman, Fred J.; Selker, John S.; Rockhold, Mark L.

    2004-10-31

    Executive Summary - While numerous techniques exist for remediation of contaminant plumes in groundwater or near the soil surface, remediation methods in the deep vadose zone are less established due to complex transport dynamics and sparse microbial populations. There is a lack of knowledge on how physical and hydrologic features of the vadose zone control microbial growth and colonization in response to nutrient delivery during bioremediation. Yet pollution in the vadose zone poses a serious threat to the groundwater resources lying deeper in the sediment. While the contaminants may be slowly degraded by native microbial communities, microbial degradation rates rarely keep pace with the spread of the pollutant. It is crucial to increase indigenous microbial degradation in the vadose zone to combat groundwater contamination...

  1. Evaluating the urate-lowering effects of different microbial fermented extracts in hyperuricemic models accompanied with a safety study

    Directory of Open Access Journals (Sweden)

    Rong-Jane Chen

    2017-07-01

    Full Text Available Uric acid (UA is an end product of purine metabolism by the enzyme xanthine oxidase (XOD. Hyperuricemia is characterized by the accumulation of serum UA and is an important risk factor for gout and many chronic disorders. XOD inhibitors or uricase (catalyzes UA to the more soluble end product can prevent these chronic diseases. However, currently available hypouricemic agents induce severe side effects. Therefore, we developed new microbial fermented extracts (MFEs with substantial XOD inhibition activity from Lactobacillus (MFE-21 and Acetobacter (MFE-25, and MFE-120 with high uricase activity from Aspergillus. The urate-lowering effects and safety of these MFEs were evaluated. Our results showed that MFE-25 exerts superior urate-lowering effects in the therapeutic model. In the preventive model, both MFE-120 and MFE-25 significantly reduced UA. The results of the safety study showed that no organ toxicity and no treatment-related adverse effects were observed in mice treated with high doses of MFEs. Taken together, the results showed the effectiveness of MFEs in reducing hyperuricemia without systemic toxicity in mice at high doses, suggesting that they are safe for use in the treatment and prevention of hyperuricemia.

  2. The microbial contribution to macroecology

    Directory of Open Access Journals (Sweden)

    Albert eBarberan

    2014-05-01

    Full Text Available There has been a recent explosion of research within the field of microbial ecology that has been fueled, in part, by methodological improvements that make it feasible to characterize microbial communities to an extent that was inconceivable only a few years ago. Furthermore, there is increasing recognition within the field of ecology that microorganisms play a critical role in the health of organisms and ecosystems. Despite these developments, an important gap still persists between the theoretical framework of macroecology and microbial ecology. We highlight two idiosyncrasies of microorganisms that are fundamental to understanding macroecological patterns and their mechanistic drivers. First, high dispersal rates provide novel opportunities to test the relative importance of niche, stochastic, and historical processes in structuring biological communities. Second, high speciation rates potentially lead to the convergence of ecological and evolutionary time scales. After reviewing these unique aspects, we discuss strategies for improving the conceptual integration of microbes into macroecology. As examples, we discuss the use of phylogenetic ecology as an integrative approach to explore patterns across the tree of life. Then we demonstrate how two general theories of biodiversity (i.e., the recently developed theory of stochastic geometry and the neutral theory can be adapted to microorganisms. We demonstrate how conceptual models that integrate evolutionary and ecological mechanisms can contribute to the unification of microbial ecology and macroecology.

  3. Dynamics of development and dispersal in sessile microbial communities: examples from Pseudomonas aeruginosa and Pseudomonas putida model biofilms

    DEFF Research Database (Denmark)

    Klausen, M.; Gjermansen, Morten; Kreft, J.-U.

    2006-01-01

    in these model biofilms develop characteristic multicellular structures through a series of distinct steps where cellular migration plays an important role. Despite the appearance of these characteristic developmental patterns in the model biofilms the available evidence suggest that the biofilm forming...

  4. Long-Term Impacts of Bacteria-Sediment Interactions in Watershed-Scale Microbial Fate and Transport Modeling.

    Science.gov (United States)

    Liao, Hehuan; Krometis, Leigh-Anne H; Kline, Karen; Hession, W C

    2015-09-01

    Elevated levels of fecal indicator bacteria (FIB) remain the leading cause of surface water-quality impairments in the United States. Under the Clean Water Act, basin-specific total maximum daily load (TMDL) restoration plans are responsible for bringing identified water impairments in compliance with applicable standards. Watershed-scale model predictions of FIB concentrations that facilitate the development of TMDLs are associated with considerable uncertainty. An increasingly cited criticism of existing modeling practice is the common strategy that assumes bacteria behave similarly to "free-phase" contaminants, although many field evidence indicates a nontrivial number of cells preferentially associate with particulates. Few attempts have been made to evaluate the impacts of sediment on the predictions of in-stream FIB concentrations at the watershed scale, with limited observational data available for model development, calibration, and validation. This study evaluates the impacts of bacteria-sediment interactions in a continuous, watershed-scale model widely used in TMDL development. In addition to observed FIB concentrations in the water column, streambed sediment-associated FIB concentrations were available for model calibration. While improved model performance was achieved compared with previous studies, model performance under a "sediment-attached" scenario was essentially equivalent to the simpler "free-phase" scenario. Watershed-specific characteristics (e.g., steep slope, high imperviousness) likely contributed to the dominance of wet-weather pollutant loading in the water column, which may have obscured sediment impacts. As adding a module accounting for bacteria-sediment interactions would increase the model complexity considerably, site evaluation preceding modeling efforts is needed to determine whether the additional model complexity and effort associated with partitioning phases of FIB is sufficiently offset by gains in predictive capacity.

  5. Human Liver Infection in a Dish: Easy-To-Build 3D Liver Models for Studying Microbial Infection.

    Directory of Open Access Journals (Sweden)

    Debora B Petropolis

    Full Text Available Human liver infection is a major cause of death worldwide, but fundamental studies on infectious diseases affecting humans have been hampered by the lack of robust experimental models that accurately reproduce pathogen-host interactions in an environment relevant for the human disease. In the case of liver infection, one consequence of this absence of relevant models is a lack of understanding of how pathogens cross the sinusoidal endothelial barrier and parenchyma. To fill that gap we elaborated human 3D liver in vitro models, composed of human liver sinusoidal endothelial cells (LSEC and Huh-7 hepatoma cells as hepatocyte model, layered in a structure mimicking the hepatic sinusoid, which enable studies of key features of early steps of hepatic infection. Built with established cell lines and scaffold, these models provide a reproducible and easy-to-build cell culture approach of reduced complexity compared to animal models, while preserving higher physiological relevance compared to standard 2D systems. For proof-of-principle we challenged the models with two hepatotropic pathogens: the parasitic amoeba Entamoeba histolytica and hepatitis B virus (HBV. We constructed four distinct setups dedicated to investigating specific aspects of hepatic invasion: 1 pathogen 3D migration towards hepatocytes, 2 hepatocyte barrier crossing, 3 LSEC and subsequent hepatocyte crossing, and 4 quantification of human hepatic virus replication (HBV. Our methods comprise automated quantification of E. histolytica migration and hepatic cells layer crossing in the 3D liver models. Moreover, replication of HBV virus occurs in our virus infection 3D liver model, indicating that routine in vitro assays using HBV or others viruses can be performed in this easy-to-build but more physiological hepatic environment. These results illustrate that our new 3D liver infection models are simple but effective, enabling new investigations on infectious disease mechanisms. The

  6. Reconstruction and Use of Microbial Metabolic Networks: the Core Escherichia coli Metabolic Model as an Educational Guide.

    Science.gov (United States)

    Orth, Jeffrey D; Fleming, R M T; Palsson, Bernhard Ø

    2010-09-01

    Biochemical network reconstructions have become popular tools in systems biology. Metabolicnetwork reconstructions are biochemically, genetically, and genomically (BiGG) structured databases of biochemical reactions and metabolites. They contain information such as exact reaction stoichiometry, reaction reversibility, and the relationships between genes, proteins, and reactions. Network reconstructions have been used extensively to study the phenotypic behavior of wild-type and mutant stains under a variety of conditions, linking genotypes with phenotypes. Such phenotypic simulations have allowed for the prediction of growth after genetic manipulations, prediction of growth phenotypes after adaptive evolution, and prediction of essential genes. Additionally, because network reconstructions are organism specific, they can be used to understand differences between organisms of species in a functional context.There are different types of reconstructions representing various types of biological networks (metabolic, regulatory, transcription/translation). This chapter serves as an introduction to metabolic and regulatory network reconstructions and models and gives a complete description of the core Escherichia coli metabolic model. This model can be analyzed in any computational format (such as MATLAB or Mathematica) based on the information given in this chapter. The core E. coli model is a small-scale model that can be used for educational purposes. It is meant to be used by senior undergraduate and first-year graduate students learning about constraint-based modeling and systems biology. This model has enough reactions and pathways to enable interesting and insightful calculations, but it is also simple enough that the results of such calculations can be understoodeasily.

  7. A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes

    DEFF Research Database (Denmark)

    Weitz, Joshua S.; Stock, Charles A.; Wilhelm, Steven W.

    2015-01-01

    ecosystem models to include a virus component, specifically parameterized for processes taking place in the ocean euphotic zone. Crucially, we are able to solve this model analytically, facilitating evaluation of model behavior under many alternative parameterizations. Analyses reveal that the addition...... that viruses can have significant stimulatory effects across whole-ecosystem scales. We suggest that existing efforts to predict carbon and nutrient cycling without considering virus effects are likely to miss essential features of marine food webs that regulate global biogeochemical cycles.The ISME Journal...

  8. Sonoassisted microbial reduction of chromium.

    Science.gov (United States)

    Kathiravan, Mathur Nadarajan; Karthick, Ramalingam; Muthu, Naggapan; Muthukumar, Karuppan; Velan, Manickam

    2010-04-01

    This study presents sonoassisted microbial reduction of hexavalent chromium (Cr(VI)) using Bacillus sp. isolated from tannery effluent contaminated site. The experiments were carried out with free cells in the presence and absence of ultrasound. The optimum pH and temperature for the reduction of Cr(VI) by Bacillus sp. were found to be 7.0 and 37 degrees C, respectively. The Cr(VI) reduction was significantly influenced by the electron donors and among the various electron donors studied, glucose offered maximum reduction. The ultrasound-irradiated reduction of Cr(VI) with Bacillus sp. showed efficient Cr(VI) reduction. The percent reduction was found to increase with an increase in biomass concentration and decrease with an increase in initial concentration. The changes in the functional groups of Bacillus sp., before and after chromium reduction were observed with FTIR spectra. Microbial growth was described with Monod and Andrews model and best fit was observed with Andrews model.

  9. Antioxidant amplifies antibiotic protection in the cecal ligation and puncture model of microbial sepsis through interleukin-10 production.

    Science.gov (United States)

    Kotake, Yashige; Moore, Danny R; Vasquez-Walden, Angelica; Tabatabaie, Tahereh; Sang, Hong

    2003-03-01

    Preadministration of antioxidants such as pyrrolidine dithiocarbamate (PDTC) and phenyl N-tert-butyl nitrone (PBN) protects animals from lethality in sepsis models. However, the requirement of preadministration greatly diminishes the clinical significance of these studies. Although the synthetic antioxidant PBN has been shown to effectively protect rodents from lethality in endotoxemia (lipopolysaccharide [LPS] model), preliminary screening indicates that pre- or postadministration of PBN does not protect in the rat cecal ligation and puncture (CLP) model. We show in this report that in a rat CLP model, the administration of PBN (150 mg/kg, 30 min after CLP) followed by the antibiotic imipenem (IMP; 10 mg/kg, 1 h after CLP) significantly increased survival compared with other single treatment groups. Previously, we have shown that PBN's protection in a rat LPS model is mediated by the overproduction of the anti-inflammatory cytokine interleukin (IL)-10. We show in this study that the increase in survival found in the PBN + IMP-treated group was abrogated by immunoneutralization with anti-IL-10 antibody, indicating that endogenous IL-10 is an effective protective factor. Plasma LPS levels were shown to be elevated after imipenem treatment, and the increased LPS level could have assisted to overproduce endogenous IL-10, as in the case of the PBN-treated LPS model. Statistical analysis indicated that the increase of IL-10 in PBN + IMP-treated group at early time period has significant association to the improvement of survival.

  10. Assessing microbial competition in a hydrogen-based membrane biofilm reactor (MBfR) using multidimensional modeling.

    Science.gov (United States)

    Martin, Kelly J; Picioreanu, Cristian; Nerenberg, Robert

    2015-09-01

    The membrane biofilm reactor (MBfR) is a novel technology that safely delivers hydrogen to the base of a denitrifying biofilm via gas-supplying membranes. While hydrogen is an effective electron donor for denitrifying bacteria (DNB), it also supports sulfate-reducing bacteria (SRB) and methanogens (MET), which consume hydrogen and create undesirable by-products. SRB and MET are only competitive for hydrogen when local nitrate concentrations are low, therefore SRB and MET primarily grow near the base of the biofilm. In an MBfR, hydrogen concentrations are greatest at the base of the biofilm, making SRB and MET more likely to proliferate in an MBfR system than a conventional biofilm reactor. Modeling results showed that because of this, control of the hydrogen concentration via the intramembrane pressure was a key tool for limiting SRB and MET development. Another means is biofilm management, which supported both sloughing and erosive detachment. For the conditions simulated, maintaining thinner biofilms promoted higher denitrification fluxes and limited the presence of SRB and MET. The 2-d modeling showed that periodic biofilm sloughing helped control slow-growing SRB and MET. Moreover, the rough (non-flat) membrane assembly in the 2-d model provided a special niche for SRB and MET that was not represented in the 1-d model. This study compared 1-d and 2-d biofilm model applicability for simulating competition in counter-diffusional biofilms. Although more computationally expensive, the 2-d model captured important mechanisms unseen in the 1-d model. © 2015 Wiley Periodicals, Inc.

  11. Cheese Microbial Risk Assessments — A Review

    Directory of Open Access Journals (Sweden)

    Kyoung-Hee Choi

    2016-03-01

    Full Text Available Cheese is generally considered a safe and nutritious food, but foodborne illnesses linked to cheese consumption have occurred in many countries. Several microbial risk assessments related to Listeria monocytogenes, Staphylococcus aureus, and Escherichia coli infections, causing cheese-related foodborne illnesses, have been conducted. Although the assessments of microbial risk in soft and low moisture cheeses such as semi-hard and hard cheeses have been accomplished, it has been more focused on the correlations between pathogenic bacteria and soft cheese, because cheese-associated foodborne illnesses have been attributed to the consumption of soft cheeses. As a part of this microbial risk assessment, predictive models have been developed to describe the relationship between several factors (pH, Aw, starter culture, and time and the fates of foodborne pathogens in cheese. Predictions from these studies have been used for microbial risk assessment as a part of exposure assessment. These microbial risk assessments have identified that risk increased in cheese with high moisture content, especially for raw milk cheese, but the risk can be reduced by preharvest and postharvest preventions. For accurate quantitative microbial risk assessment, more data including interventions such as curd cooking conditions (temperature and time and ripening period should be available for predictive models developed with cheese, cheese consumption amounts and cheese intake frequency data as well as more dose-response models.

  12. An Economic Framework of Microbial Trade.

    Science.gov (United States)

    Tasoff, Joshua; Mee, Michael T; Wang, Harris H

    2015-01-01

    A large fraction of microbial life on earth exists in complex communities where metabolic exchange is vital. Microbes trade essential resources to promote their own growth in an analogous way to countries that exchange goods in modern economic markets. Inspired by these similarities, we developed a framework based on general equilibrium theory (GET) from economics to predict the population dynamics of trading microbial communities. Our biotic GET (BGET) model provides an a priori theory of the growth benefits of microbial trade, yielding several novel insights relevant to understanding microbial ecology and engineering synthetic communities. We find that the economic concept of comparative advantage is a necessary condition for mutualistic trade. Our model suggests that microbial communities can grow faster when species are unable to produce essential resources that are obtained through trade, thereby promoting metabolic specialization and increased intercellular exchange. Furthermore, we find that species engaged in trade exhibit a fundamental tradeoff between growth rate and relative population abundance, and that different environments that put greater pressure on group selection versus individual selection will promote varying strategies along this growth-abundance spectrum. We experimentally tested this tradeoff using a synthetic consortium of Escherichia coli cells and found the results match the predictions of the model. This framework provides a foundation to study natural and engineered microbial communities through a new lens based on economic theories developed over the past century.

  13. An Economic Framework of Microbial Trade.

    Directory of Open Access Journals (Sweden)

    Joshua Tasoff

    Full Text Available A large fraction of microbial life on earth exists in complex communities where metabolic exchange is vital. Microbes trade essential resources to promote their own growth in an analogous way to countries that exchange goods in modern economic markets. Inspired by these similarities, we developed a framework based on general equilibrium theory (GET from economics to predict the population dynamics of trading microbial communities. Our biotic GET (BGET model provides an a priori theory of the growth benefits of microbial trade, yielding several novel insights relevant to understanding microbial ecology and engineering synthetic communities. We find that the economic concept of comparative advantage is a necessary condition for mutualistic trade. Our model suggests that microbial communities can grow faster when species are unable to produce essential resources that are obtained through trade, thereby promoting metabolic specialization and increased intercellular exchange. Furthermore, we find that species engaged in trade exhibit a fundamental tradeoff between growth rate and relative population abundance, and that different environments that put greater pressure on group selection versus individual selection will promote varying strategies along this growth-abundance spectrum. We experimentally tested this tradeoff using a synthetic consortium of Escherichia coli cells and found the results match the predictions of the model. This framework provides a foundation to study natural and engineered microbial communities through a new lens based on economic theories developed over the past century.

  14. Adding mucins to an in vitro batch fermentation model of the large intestine induces changes in microbial population isolated from porcine feces depending on the substrate.

    Science.gov (United States)

    Tran, T H T; Boudry, C; Everaert, N; Théwis, A; Portetelle, D; Daube, G; Nezer, C; Taminiau, B; Bindelle, J

    2016-02-01

    Adding mucus to in vitro fermentation models of the large intestine shows that some genera, namely lactobacilli, are dependent on host-microbiota interactions and that they rely on mucosal layers to increase their activity. This study investigated whether this dependence on mucus is substrate dependent and to what extent other genera are impacted by the presence of mucus. Inulin and cellulose were fermented in vitro by a fecal inoculum from pig in the presence or not of mucin beads in order to compare fermentation patterns and bacterial communities. Mucins increased final gas production with inulin and shifted short-chain fatty acid molar ratios (P inulin was fermented. A more in-depth community analysis indicated that the mucins increased Proteobacteria (0.55 vs 0.25%, P = 0.013), Verrucomicrobia (5.25 vs 0.03%, P = 0.032), Ruminococcaceae, Bacteroidaceae and Akkermansia spp. Proteobacteria (5.67 vs 0.55%, P < 0.001) and Lachnospiraceae (33 vs 10.4%) were promoted in the mucus compared with the broth, while Ruminococcaceae decreased. The introduction of mucins affected many microbial genera and fermentation patterns, but from PCA results, the impact of mucus was independent of the fermentation substrate.

  15. Influence of pH on dynamics of microbial enhanced oil recovery processes using biosurfactant producing Pseudomonas putida: Mathematical modelling and numerical simulation.

    Science.gov (United States)

    Sivasankar, P; Suresh Kumar, G

    2017-01-01

    In present work, the influence of reservoir pH conditions on dynamics of microbial enhanced oil recovery (MEOR) processes using Pseudomonas putida was analysed numerically from the developed mathematical model for MEOR processes. Further, a new strategy to improve the MEOR performance has also been proposed. It is concluded from present study that by reversing the reservoir pH from highly acidic to low alkaline condition (pH 5-8), flow and mobility of displaced oil, displacement efficiency, and original oil in place (OOIP) recovered gets significantly enhanced, resulting from improved interfacial tension (IFT) reduction by biosurfactants. At pH 8, maximum of 26.1% of OOIP was recovered with higher displacement efficiency. The present study introduces a new strategy to increase the recovery efficiency of MEOR technique by characterizing the biosurfactants for IFTmin/IFTmax values for different pH conditions and subsequently, reversing the reservoir pH conditions at which the IFTmin/IFTmax value is minimum. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Chaos and microbial systems

    Energy Technology Data Exchange (ETDEWEB)

    Kot, M.

    1990-07-01

    A recurrent theme of much recent research is that seemingly random fluctuations often occur as the result of simple deterministic mechanisms. Hence, much of the recent work in nonlinear dynamics has centered on new techniques for identifying order in seemingly chaotic systems. To determine the robustness of these techniques, chaos must, to some extent, be brought into the laboratory. Preliminary investigations of the forced double-Monod equations, a model for a predator and a prey in a chemostat with periodic variation in inflowing substrate concentration, suggest that simple microbial systems may provide the perfect framework for determining the efficacy and relevance of the new nonlinear dynamics in dealing with complex population dynamics. This research has two main goals, that is the mathematical analysis and computer simulation of the periodically forced double-Monod equations and of related models; and experimental (chemostat) population studies that evaluate the accuracy and generality of the models, and that judge the usefulness of various new techniques of nonlinear dynamics to the study of populations.

  17. An organotypic slice model for ex vivo study of neural, immune, and microbial interactions of mouse intestine.

    Science.gov (United States)

    Schwerdtfeger, Luke A; Ryan, Elizabeth P; Tobet, Stuart A

    2016-02-15

    Organotypic tissue slices provide seminatural, three-dimensional microenvironments for use in ex vivo study of specific organs and have advanced investigative capabilities compared with isolated cell cultures. Several characteristics of the gastrointestinal tract have made in vitro models for studying the intestine challenging, such as maintaining the intricate structure of microvilli, the intrinsic enteric nervous system, Peyer's patches, the microbiome, and the active contraction of gut muscles. In the present study, an organotypic intestinal slice model was developed that allows for functional investigation across regions of the intestine. Intestinal tissue slices were maintained ex vivo for several days in a physiologically relevant environment that preserved normal enterocyte structure, intact and proliferating crypt cells, submucosal organization, and muscle wall composure. Cell death was measured by a membrane-impermeable DNA binding indicator, ethidium homodimer, and less than 5% of cells were labeled in all regions of the villi and crypt epithelia at 24 h ex vivo. This tissue slice model demonstrated intact myenteric and submucosal neuronal plexuses and functional interstitial cells of Cajal to the extent that nonstimulated, segmental contractions occurred for up to 48 h ex vivo. To detect changes in physiological responses, slices were also assessed for segmental contractions in the presence and absence of antibiotic treatment, which resulted in slices with lesser or greater amounts of commensal bacteria, respectively. Segmental contractions were significantly greater in slices without antibiotics and increased native microbiota. This model renders mechanisms of neuroimmune-microbiome interactions in a complex gut environment available to direct observation and controlled perturbation.

  18. Sorption kinetics and microbial biodegradation activity of hydrophobic chemicals in sewage sludge: Model and measurements based on free concentrations

    NARCIS (Netherlands)

    Artola-Garicano, E.; Borkent, I.; Damen, K.; Jager, T.; Vaes, W.H.J.

    2003-01-01

    In the current study, a new method is introduced with which the rate-limiting factor of biodegradation processes of hydrophobic chemicals in organic and aqueous systems can be determined. The novelty of this approach lies in the combination of a free concentration-based kinetic model with measuremen

  19. Systematic Study of Separators in Air-Breathing Flat-Plate Microbial Fuel Cells—Part 2: Numerical Modeling

    Directory of Open Access Journals (Sweden)

    Sona Kazemi

    2016-01-01

    Full Text Available The separator plays a key role on the performance of passive air-breathing flat-plate MFCs (FPMFC as it isolates the anaerobic anode from the air-breathing cathode. The goal of the present work was to study the separator characteristics and its effect on the performance of passive air-breathing FPMFCs. This was performed partially through characterization of structure, properties, and performance correlations of eight separators presented in Part 1. Current work (Part 2 presents a numerical model developed based on the mixed potential theory to investigate the sensitivity of the electrode potentials and the power output to the separator characteristics. According to this numerical model, the decreased peak power results from an increase in the mass transfer coefficients of oxygen and ethanol, but mainly increasing mixed potentials at the anode by oxygen crossover. The model also indicates that the peak power is affected by the proton transport number of the separator, which affects the cathode pH. Anode pH, on the other hand, remains constant due to application of phosphate buffer solution as the electrolyte. Also according to this model, the peak power is not sensitive to the resistivity of the separator because of the overshadowing effect of the oxygen crossover.

  20. MICROBIAL FUEL CELL

    DEFF Research Database (Denmark)

    2008-01-01

    A novel microbial fuel cell construction for the generation of electrical energy. The microbial fuel cell comprises: (i) an anode electrode, (ii) a cathode chamber, said cathode chamber comprising an in let through which an influent enters the cathode chamber, an outlet through which an effluent...

  1. Biofilms: A microbial home

    Science.gov (United States)

    Chandki, Rita; Banthia, Priyank; Banthia, Ruchi

    2011-01-01

    Microbial biofilms are mainly implicated in etiopathogenesis of caries and periodontal disease. Owing to its properties, these pose great challenges. Continuous and regular disruption of these biofilms is imperative for prevention and management of oral diseases. This essay provides a detailed insight into properties, mechanisms of etiopathogenesis, detection and removal of these microbial biofilms. PMID:21976832

  2. Biofilms: A microbial home

    OpenAIRE

    Chandki, Rita; Banthia, Priyank; Banthia, Ruchi

    2011-01-01

    Microbial biofilms are mainly implicated in etiopathogenesis of caries and periodontal disease. Owing to its properties, these pose great challenges. Continuous and regular disruption of these biofilms is imperative for prevention and management of oral diseases. This essay provides a detailed insight into properties, mechanisms of etiopathogenesis, detection and removal of these microbial biofilms.

  3. Kinetic model of microbial oils produced by fermenting corn stover hydrolysate%玉米秸秆水解液发酵产微生物油脂的动力学模型研究

    Institute of Scientific and Technical Information of China (English)

    徐洪章; 叶小金; 薛冬桦

    2014-01-01

    The dynamics of microbial oils fermented from corn stover hydrolysate was studied.The math-ematic model of thalli growth and microbial oils synthesis during the fermentation of microbial oils changed along with the time was built based on Logistic equation and Luedeking -Piret equation.The test value was validated with the model.The compositions of unsaturated fatty acid in microbial oils were analyzed by the gas chromatography.The results indicated that the corn stover was used as a raw materi-al,mortierella isabellina as a strain,after aerobic intermittent fermentation,the biomass and content of microbial oils reached 10.63 g/L and 49.53% respectively.A good coincidence between models calcula-tion values and experimental data was observed,therefore,the model equations can really reflect the process of the microbial oils fermentation.%对玉米秸秆水解液发酵产微生物油脂动力学进行研究,基于 Logistic 方程和 Luedeking -Piret 方程分别建立了微生物油脂发酵过程菌体生长和油脂合成随时间变化的数学模型,同时对试验值与模型进行了验证比较,应用气相色谱技术对微生物油脂中的不饱和脂肪酸成分进行分析。结果表明,以玉米秸秆为原料、深黄被孢霉为菌株,好氧间歇发酵,得到生物量为10.63 g/L,油脂含量为49.53%。模型模拟计算结果与试验值能较好地吻合,该模型能较好地反映玉米秸秆水解液发酵产微生物油脂发酵的过程。

  4. Bioremediation model for atrazine contaminated agricultural soils using phytoremediation (using Phaseolus vulgaris L.) and a locally adapted microbial consortium.

    Science.gov (United States)

    Madariaga-Navarrete, Alfredo; Rodríguez-Pastrana, Blanca Rosa; Villagómez-Ibarra, José Roberto; Acevedo-Sandoval, Otilio Arturo; Perry, Gregory; Islas-Pelcastre, Margarita

    2017-06-03

    The objective of the present study was to examine a biological model under greenhouse conditions for the bioremediation of atrazine contaminated soils. The model consisted in a combination of phytoremediation (using Phaseolus vulgaris L.) and rhizopheric bio-augmentation using native Trichoderma sp., and Rhizobium sp. microorganisms that showed no inhibitory growth at 10,000 mg L(-1) of herbicide concentration. 33.3 mg of atrazine 50 g(-1) of soil of initial concentration was used and an initial inoculation of 1 × 10(9) UFC mL(-1) of Rhizobium sp. and 1 × 10(5) conidia mL(-1) of Trichoderma sp. were set. Four treatments were arranged: Bean + Trichoderma sp. (B+T); Bean + Rhizobium sp. (BR); Bean + Rhizobium sp. + Trichoderma sp. (B+R+T) and Bean (B). 25.51 mg of atrazine 50 g(-1) of soil (76.63%) was removed by the B+T treatment in 40 days (a = 0.050, Tukey). This last indicate that the proposed biological model and methodology developed is useful for atrazine contaminated bioremediation agricultural soils, which can contribute to reduce the effects of agrochemical abuse.

  5. Added value of experts' knowledge to improve a quantitative microbial exposure assessment model--Application to aseptic-UHT food products.

    Science.gov (United States)

    Pujol, Laure; Johnson, Nicholas Brian; Magras, Catherine; Albert, Isabelle; Membré, Jeanne-Marie

    2015-10-15

    In a previous study, a quantitative microbial exposure assessment (QMEA) model applied to an aseptic-UHT food process was developed [Pujol, L., Albert, I., Magras, C., Johnson, N. B., Membré, J. M. Probabilistic exposure assessment model to estimate aseptic UHT product failure rate. 2015 International Journal of Food Microbiology. 192, 124-141]. It quantified Sterility Failure Rate (SFR) associated with Bacillus cereus and Geobacillus stearothermophilus per process module (nine modules in total from raw material reception to end-product storage). Previously, the probabilistic model inputs were set by experts (using knowledge and in-house data). However, only the variability dimension was taken into account. The model was then improved using expert elicitation knowledge in two ways. First, the model was refined by adding the uncertainty dimension to the probabilistic inputs, enabling to set a second order Monte Carlo analysis. The eight following inputs, and their impact on SFR, are presented in detail in this present study: D-value for each bacteria of interest (B. cereus and G. stearothermophilus) associated with the inactivation model for the UHT treatment step, i.e., two inputs; log reduction (decimal reduction) number associated with the inactivation model for the packaging sterilization step for each bacterium and each part of the packaging (product container and sealing component), i.e., four inputs; and bacterial spore air load of the aseptic tank and the filler cabinet rooms, i.e., two inputs. Second, the model was improved by leveraging expert knowledge to develop further the existing model. The proportion of bacteria in the product which settled on surface of pipes (between the UHT treatment and the aseptic tank on one hand, and between the aseptic tank and the filler cabinet on the other hand) leading to a possible biofilm formation for each bacterium, was better characterized. It was modeled as a function of the hygienic design level of the aseptic

  6. A thermodynamic theory of microbial growth.

    Science.gov (United States)

    Desmond-Le Quéméner, Elie; Bouchez, Théodore

    2014-08-01

    Our ability to model the growth of microbes only relies on empirical laws, fundamentally restricting our understanding and predictive capacity in many environmental systems. In particular, the link between energy balances and growth dynamics is still not understood. Here we demonstrate a microbial growth equation relying on an explicit theoretical ground sustained by Boltzmann statistics, thus establishing a relationship between microbial growth rate and available energy. The validity of our equation was then questioned by analyzing the microbial isotopic fractionation phenomenon, which can be viewed as a kinetic consequence of the differences in energy contents of isotopic isomers used for growth. We illustrate how the associated theoretical predictions are actually consistent with recent experimental evidences. Our work links microbial population dynamics to the thermodynamic driving forces of the ecosystem, which opens the door to many biotechnological and ecological developments.

  7. The microbial fermentation characteristics depend on both carbohydrate source and heat processing: a model experiment with ileo-cannulated pigs

    DEFF Research Database (Denmark)

    Nielsen, Tina Skau; Jørgensen, Henry Johs. Høgh; Knudsen, Knud Erik Bach

    2017-01-01

    The effects of carbohydrate (CHO) source and processing (extrusion cooking) on large intestinal fermentation products were studied in ileo-cannulated pigs as a model for humans. Pigs were fed diets containing barley, pea or a mixture of potato starch:wheat bran (PSWB) either raw or extrusion cooked....... Extrusion cooking reduced the amount of starch fermented in the large intestine by 52–96% depending on the CHO source and the total pool of butyrate in the distal small intestine + large intestine by on average 60% across diets. Overall, extrusion cooking caused a shift in the composition of short...

  8. Synthetic microbial ecosystems for biotechnology.

    Science.gov (United States)

    Pandhal, Jagroop; Noirel, Josselin

    2014-06-01

    Most highly controlled and specific applications of microorganisms in biotechnology involve pure cultures. Maintaining single strain cultures is important for industry as contaminants can reduce productivity and lead to longer "down-times" during sterilisation. However, microbes working together provide distinct advantages over pure cultures. They can undertake more metabolically complex tasks, improve efficiency and even expand applications to open systems. By combining rapidly advancing technologies with ecological theory, the use of microbial ecosystems in biotechnology will inevitably increase. This review provides insight into the use of synthetic microbial communities in biotechnology by applying the engineering paradigm of measure, model, manipulate and manufacture, and illustrate the emerging wider potential of the synthetic ecology field. Systems to improve biofuel production using microalgae are also discussed.

  9. Simulation of Zinc Release Affected by Microbial Inoculation and Salinity Levels in a non-sterile Calcareous Soil Using kinetic Models

    Directory of Open Access Journals (Sweden)

    hamidreza boostani

    2017-02-01

    physical and chemical properties. The experiment was conducted in the greenhouse of agriculture college of Shahid Chamran University, Ahvaz, Iran. A factorial experiment as a completely randomized design with three replications was conducted in greenhouse conditions. The first factor consisted of salinity levels (0, 15 and 30 cmol(c kg-1 salt supplied as a 3:2:1 Na:Ca:Mg chloride salts and the second factor was microbial inoculation (without inoculation, fungi, bacteria, bacteria + fungi.Soil samples were extracted using DTPA extractant for periods of 0.5, 1, 2, 6, 12 and 24 hours. Cumulative Zn released (q as a function of time (T was evaluated using seven different kinetic models. A relatively high values of coefficient of determination (r2 and low values of standard error of estimate (SEE were used as criteria for the selection of the best fitted models. Statistical analysis of data was done using MSTATC package (Mstatc, 1991. Comparison between means was performed using Duncan's multiple range test (DMRT at the significant level of P < 0.05. Also, charts were drawn by excel computer package. Results and Discussion: Investigation of Zn release patterns showed that the control and all treated soils had a uniform pattern of Zn release. Overall, Zn release patterns were generally characterized by an initial fast reaction at first two hours, followed by slower continuing reaction. It seems likely that the release of zinc is controlled by two different mechanisms. Two-step process of releases (rapid and subsequent slow is attributed to the existence of places with different energy. The use of all microbial treatments increased the initial release of Zn compared to control. The most and the least Zn initial release observed in fungi-bacterial and bacterial treatment respectively. By application of all microbial treatments, Zn release rate declined compared to control and the lowest decrease observed in fungal treatment. In general, Zn initial release was increased and Zn

  10. Modeling low-temperature serpentinization reactions to estimate molecular hydrogen production with implications for potential microbial life on Saturn's moon Enceladus.

    Science.gov (United States)

    Zwicker, Jennifer; Smrzka, Daniel; Taubner, Ruth-Sophie; Bach, Wolfgang; Rittmann, Simon; Schleper, Christa; Peckmann, Jörn

    2017-04-01

    Serpentinization of ultramafic rocks attracts much interest in research on the origin of life on Earth and the search for life on extraterrestrial bodies including icy moons like Enceladus. Serpentinization on Earth occurs in peridotite-hosted systems at slow-spreading mid-ocean ridges, and produces large amounts of molecular hydrogen and methane. These reduced compounds can be utilized by diverse chemosynthetic microbial consortia as a metabolic energy source. Although many hydrothermal vents emit hot and acidic fluids today, it is more likely that life originated in the Archean at sites producing much cooler and more alkaline fluids that allowed for the synthesis and stability of essential organic molecules necessary for life. Therefore, a detailed understanding of water-rock interaction processes during low-temperature serpentinization is of crucial importance in assessing the life-sustaining potential of these environments. In the course of serpentinization, the metasomatic hydration of olivine and pyroxene produces various minerals including serpentine minerals, magnetite, brucite, and carbonates. Hydrogen production only occurs if ferrous iron within iron-bearing minerals is oxidized and incorporated as ferric iron into magnetite. The PHREEQC code was used to model the pH- and temperature-dependent dissolution of olivine and pyroxene to form serpentine, magnetite and hydrogen under pressure and temperature conditions that may exist on Saturn's icy moon Enceladus. Various model setups at 25 and 50°C were run to assess the influence of environmental parameters on hydrogen production. The results reveal that hydrogen production rates depend on the composition of the initial mineral assemblage and temperature. The current assumption is that there is a gaseous phase between Enceladus' ice sheet and subsurface ocean. To test various scenarios, model runs were conducted with and without the presence of a gas phase. The model results show that hydrogen production is

  11. Ecological impacts of environmental toxicants and radiation on the microbial ecosystem: a model simulation of computational microbiology

    Energy Technology Data Exchange (ETDEWEB)

    Doi, Masahiro; Sakashita, Tetsuya; Ishii, Nobuyoshi; Fuma, Shoichi; Takeda, Hiroshi; Miyamoto, Kiriko; Yanagisawa, K.; Nakamura, Yuji [National Institute of Radiological Sciences, Inage, Chiba (Japan); Kawabata, Zenichiro [Center for Ecological Research, Kyoto Univ., Otsu, Shiga (Japan)

    2000-05-01

    This study explores a microorganic closed-ecosystem by computer simulation to illustrate symbiosis among populations in the microcosm that consists of heterotroph protozoa, Tetrahymena thermophila B as a consumer, autotroph algae, Euglena gracilis Z as a primary producer and saprotroph Bacteria, Escherichia coli DH5 as decomposer. The simulation program is written as a procedure of StarLogoT1.5.1, which is developed by Center for Connected Learning and Computer-Based Modeling, Tufts University. The virtual microcosm is structured and operated by the following rules; (1) Environment is defined as a lattice model, which consists of 10,201 square patches, 300 micron Wide, 300 micron Length and 100 micron Hight. (2) Each patch has its own attributes, Nutrient, Detritus and absolute coordinates, (3) Components of the species, Tetrahymena, Euglena and E-coli are defined as sub-system, and each sub-system has its own attributes as location, heading direction, cell-age, structured biomass, reserves energy and demographic parameters (assimilation rate, breeding threshold, growth rate, etc.). (4) Each component of the species, Tetrahymena, Euglena and E-coli, lives by foraging (Tetrahymena eats E-coli), excreting its metabolic products to the environment (as a substrate of E-coli), breeding and dying according vital condition. (5) Euglena utilizes sunlight energy by photosynthesis process and produces organic compounds. E-coli breaks down the organic compounds of dead protoplasm or metabolic wastes (Detritus) and releases inorganic substances to construct down stream of food cycle. Virtual ecosystem in this study is named SIM-COSM, a parallel computing model for self-sustaining system of complexity. It found that SIM-COSM is a valuable to illustrate symbiosis among populations in the microcosm, where a feedback mechanism acts in response to disturbances and interactions among species and environment. In the simulation, microbes increased demographic and environmental

  12. High microbial production and characterization of strictly periodic polymers modelled on the repetitive domain of wheat gliadins.

    Science.gov (United States)

    Sourice, Sophie; Nisole, Audrey; Guéguen, Jacques; Popineau, Yves; Elmorjani, Khalil

    2003-12-26

    Primary structures of wheat prolamins contain repetitive domains involved in the mechanical properties of gluten. In order to experience the ability of recombinant strictly periodic polypeptides, modelled on a consensus sequence of wheat gliadins (PQQPY)(8) and (PQQPY)(17) (SPR8 and SPR17 polypeptides, respectively), to be formulated in film solutions, their heterologous expression conditions, in batch culture and low cell densities, were optimized to match the high requirements of this process. A convenient and general purification procedure was also devised. Moreover, FTIR-ATR characterizations indicated that these periodic polypeptides prepared as hydrated doughy state and dried have the tendency to form a protein network through intermolecular beta-sheets, strongly maintained by hydrogen bonds. Accordingly, these recombinant polypeptides are assumed to be a suitable candidate for potential application.

  13. Molecular and cultivation-dependent analysis of metal-reducing bacteria implicated in arsenic mobilisation in south-east asian aquifers

    Energy Technology Data Exchange (ETDEWEB)

    Hery, Marina; Gault, Andrew G.; Rowland, Helen A.L.; Lear, Gavin; Polya, David A. [School of Earth, Atmospheric and Environmental Sciences and Williamson Research Centre for Molecular Environmental Science, University of Manchester, Manchester M13 9PL (United Kingdom); Lloyd, Jonathan R. [School of Earth, Atmospheric and Environmental Sciences and Williamson Research Centre for Molecular Environmental Science, University of Manchester, Manchester M13 9PL (United Kingdom)], E-mail: jon.lloyd@manchester.ac.uk

    2008-11-15

    The reduction of sorbed As(V) to the potentially more mobile As(III) by As-respiring anaerobic bacteria has been implicated in the mobilisation of the toxic metalloid in aquifer sediments in SE Asia. However, there is currently only a limited amount of information on the identity of the organisms that can respire As(V) in these sediment systems. Here experiments are described that have targeted As(V)-respiring bacteria using cultivation-independent molecular techniques, and also more traditional microbiological approaches that have used growth media highly selective for organisms that can grow using arsenate as the sole electron acceptor supplied for anaerobic growth. The molecular techniques used have initially targeted DNA from microcosms displaying maximal rates of arsenate reduction, both with and without added electron donor. More recent studies from the authors' laboratory have used stable isotope probing techniques, targeting DNA from the active microbial fraction in microcosms labelled with [{sup 13}C]acetate supplied as an electron donor for arsenate reduction. Phylogenetic analyses using a highly conserved genetic marker (the 16S rRNA gene) have suggested the involvement of Sulfurospirillum and Geobacter species in arsenate-respiration, and this has been supported further by complimentary experiments using more traditional microbiological techniques. Additional research required to clarify the role of these organisms in the mobilisation of As in situ are discussed.

  14. Microbially mediated mineral carbonation

    Science.gov (United States)

    Power, I. M.; Wilson, S. A.; Dipple, G. M.; Southam, G.

    2010-12-01

    Mineral carbonation involves silicate dissolution and carbonate precipitation, which are both natural processes that microorganisms are able to mediate in near surface environments (Ferris et al., 1994; Eq. 1). (Ca,Mg)SiO3 + 2H2CO3 + H2O → (Ca,Mg)CO3 + H2O + H4SiO4 + O2 (1) Cyanobacteria are photoautotrophs with cell surface characteristics and metabolic processes involving inorganic carbon that can induce carbonate precipitation. This occurs partly by concentrating cations within their net-negative cell envelope and through the alkalinization of their microenvironment (Thompson & Ferris, 1990). Regions with mafic and ultramafic bedrock, such as near Atlin, British Columbia, Canada, represent the best potential sources of feedstocks for mineral carbonation. The hydromagnesite playas near Atlin are a natural biogeochemical model for the carbonation of magnesium silicate minerals (Power et al., 2009). Field-based studies at Atlin and corroborating laboratory experiments demonstrate the ability of a microbial consortium dominated by filamentous cyanobacteria to induce the precipitation of carbonate minerals. Phototrophic microbes, such as cyanobacteria, have been proposed as a means for producing biodiesel and other value added products because of their efficiency as solar collectors and low requirement for valuable, cultivable land in comparison to crops (Dismukes et al., 2008). Carbonate precipitation and biomass production could be facilitated using specifically designed ponds to collect waters rich in dissolved cations (e.g., Mg2+ and Ca2+), which would allow for evapoconcentration and provide an appropriate environment for growth of cyanobacteria. Microbially mediated carbonate precipitation does not require large quantities of energy or chemicals needed for industrial systems that have been proposed for rapid carbon capture and storage via mineral carbonation (e.g., Lackner et al., 1995). Therefore, this biogeochemical approach may represent a readily

  15. Quantitative microbial risk assessment for Escherichia coli O157:H7, Salmonella enterica, and Listeria monocytogenes in leafy green vegetables consumed at salad bars, based on modeling supply chain logistics.

    Science.gov (United States)

    Tromp, S O; Rijgersberg, H; Franz, E

    2010-10-01

    Quantitative microbial risk assessments do not usually account for the planning and ordering mechanisms (logistics) of a food supply chain. These mechanisms and consumer demand determine the storage and delay times of products. The aim of this study was to quantitatively assess the difference between simulating supply chain logistics (MOD) and assuming fixed storage times (FIX) in microbial risk estimation for the supply chain of fresh-cut leafy green vegetables destined for working-canteen salad bars. The results of the FIX model were previously published (E. Franz, S. O. Tromp, H. Rijgersberg, and H. J. van der Fels-Klerx, J. Food Prot. 73:274-285, 2010). Pathogen growth was modeled using stochastic discrete-event simulation of the applied logistics concept. The public health effects were assessed by conducting an exposure assessment and risk characterization. The relative growths of Escherichia coli O157 (17%) and Salmonella enterica (15%) were identical in the MOD and FIX models. In contrast, the relative growth of Listeria monocytogenes was considerably higher in the MOD model (1,156%) than in the FIX model (194%). The probability of L. monocytogenes infection in The Netherlands was higher in the MOD model (5.18×10(-8)) than in the FIX model (1.23×10(-8)). The risk of listeriosis-induced fetal mortality in the perinatal population increased from 1.24×10(-4) (FIX) to 1.66×10(-4) (MOD). Modeling the probabilistic nature of supply chain logistics is of additional value for microbial risk assessments regarding psychrotrophic pathogens in food products for which time and temperature are the postharvest preventive measures in guaranteeing food safety.

  16. New Markov Model Approaches to Deciphering Microbial Genome Function and Evolution: Comparative Genomics of Laterally Transferred Genes

    Energy Technology Data Exchange (ETDEWEB)

    Borodovsky, M.

    2013-04-11

    Algorithmic methods for gene prediction have been developed and successfully applied to many different prokaryotic genome sequences. As the set of genes in a particular genome is not homogeneous with respect to DNA sequence composition features, the GeneMark.hmm program utilizes two Markov models representing distinct classes of protein coding genes denoted "typical" and "atypical". Atypical genes are those whose DNA features deviate significantly from those classified as typical and they represent approximately 10% of any given genome. In addition to the inherent interest of more accurately predicting genes, the atypical status of these genes may also reflect their separate evolutionary ancestry from other genes in that genome. We hypothesize that atypical genes are largely comprised of those genes that have been relatively recently acquired through lateral gene transfer (LGT). If so, what fraction of atypical genes are such bona fide LGTs? We have made atypical gene predictions for all fully completed prokaryotic genomes; we have been able to compare these results to other "surrogate" methods of LGT prediction.

  17. Microbial, metabolomic, and immunologic dynamics in a relapsing genetic mouse model of colitis induced by T-synthase deficiency.

    Science.gov (United States)

    Jacobs, Jonathan P; Lin, Lin; Goudarzi, Maryam; Ruegger, Paul; McGovern, Dermot P B; Fornace, Albert J; Borneman, James; Xia, Lijun; Braun, Jonathan

    2017-01-02

    Intestinal dysbiosis is thought to confer susceptibility to inflammatory bowel disease (IBD), but it is unknown whether dynamic changes in the microbiome contribute to fluctuations in disease activity. We explored this question using mice with intestine-specific deletion of C1galt1 (also known as T-synthase) (Tsyn mice). These mice develop spontaneous microbiota-dependent colitis with a remitting/relapsing course due to loss of mucin core-1 derived O-glycans. 16S rRNA sequencing and untargeted metabolomics demonstrated age-specific perturbations in the intestinal microbiome and metabolome of Tsyn mice compare with littermate controls at weeks 3 (disease onset), 5 (during remission), and 9 (after relapse). Colitis remission corresponded to increased levels of FoxP3+RORγt+CD4+ T cells in the colonic lamina propria that were positively correlated with operational taxonomic units (OTUs) in the S24-7 family and negatively correlated with OTUs in the Clostridiales order. Relapse was characterized by marked expansion of FoxP3-RORγt+CD4+ T cells expressing IFNγ and IL17A, which were associated with Clostridiales OTUs distinct from those negatively correlated with FoxP3+RORγt+CD4+ T cells. Our findings suggest that colitis remission and relapse in the Tsyn model may reflect alterations in the microbiome due to reduced core-1 O-glycosylation that shift the balance of regulatory and pro-inflammatory T cell subsets. We investigated whether genetic variation in C1galt1 correlated with the microbiome in a cohort of 78 Crohn's disease patients and 101 healthy controls. Polymorphisms near C1galt1 (rs10486157) and its molecular chaperone, Cosmc (rs4825729), were associated with altered composition of the colonic mucosal microbiota, supporting the relevance of core-1 O-glycosylation to host regulation of the microbiome.

  18. Potentiostatically Poised Electrodes Mimic Iron Oxide and Interact with Soil Microbial Communities to Alter the Biogeochemistry of Arctic Peat Soils

    Directory of Open Access Journals (Sweden)

    Largus T. Angenent

    2013-09-01

    Full Text Available Dissimilatory metal-reducing bacteria are ubiquitous in soils worldwide, possess the ability to transfer electrons outside of their cell membranes, and are capable of respiring with various metal oxides. Reduction of iron oxides is one of the more energetically favorable forms of anaerobic respiration, with a higher energy yield than both sulfate reduction and methanogenesis. As such, this process has significant implications for soil carbon balances, especially in the saturated, carbon-rich soils of the northern latitudes. However, the dynamics of these microbial processes within the context of the greater soil microbiome remain largely unstudied. Previously, we have demonstrated the capability of potentiostatically poised electrodes to mimic the redox potential of iron(III- and humic acid-compounds and obtain a measure of metal-reducing respiration. Here, we extend this work by utilizing poised electrodes to provide an inexaustable electron acceptor for iron- and humic acid-reducing microbes, and by measuring the effects on both microbial community structure and greenhouse gas emissions. The application of both nonpoised and poised graphite electrodes in peat soils stimulated methane emissions by 15%–43% compared to soils without electrodes. Poised electrodes resulted in higher (13%–24% methane emissions than the nonpoised electrodes. The stimulation of methane emissions for both nonpoised and poised electrodes correlated with the enrichment of proteobacteria, verrucomicrobia, and bacteroidetes. Here, we demonstrate a tool for precisely manipulating localized redox conditions in situ (via poised electrodes and for connecting microbial community dynamics with larger ecosystem processes. This work provides a foundation for further studies examining the role of dissimilatory metal-reducing bacteria in global biogeochemical cycles.

  19. Modeling the effectiveness of U(VI) biomineralization in dual-porosity porous media

    Science.gov (United States)

    Rotter, B. E.; Barry, D. A.; Gerhard, J. I.; Small, J. S.

    2011-05-01

    SummaryUranium contamination is a serious environmental concern worldwide. Recent attention has focused on the in situ immobilization of uranium by stimulation of dissimilatory metal-reducing bacteria (DMRB). The objective of this work was to investigate the effectiveness of this approach in heterogeneous and structured porous media, since such media may significantly affect the geochemical and microbial processes taking place in contaminated sites, impacting remediation efficiency during biostimulation. A biogeochemical reactive transport model was developed for uranium remediation by immobile-region-resident DMRB in two-region porous media. Simulations were used to investigate the parameter sensitivities of the system over wide-ranging geochemical, microbial and groundwater transport conditions. The results suggest that optimal biomineralization is generally likely to occur when the regional mass transfer timescale is less than one-thirtieth the value of the volumetric flux timescale, and/or the organic carbon fermentation timescale is less than one-thirtieth the value of the advective timescale, and/or the mobile region porosity ranges between equal to and four times the immobile region porosity. Simulations including U(VI) surface complexation to Fe oxides additionally suggest that, while systems exhibiting U(VI) surface complexation may be successfully remediated, they are likely to display different degrees of remediation efficiency over varying microbial efficiency, mobile-immobile mass transfer, and porosity ratios. Such information may aid experimental and field designs, allowing for optimized remediation in dual-porosity (two-regi