Uncovering co-expression gene network modules regulating fruit acidity in diverse apples.

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Bai, Yang; Dougherty, Laura; Cheng, Lailiang; Zhong, Gan-Yuan; Xu, Kenong

2015-08-16

Acidity is a major contributor to fruit quality. Several organic acids are present in apple fruit, but malic acid is predominant and determines fruit acidity. The trait is largely controlled by the Malic acid (Ma) locus, underpinning which Ma1 that putatively encodes a vacuolar aluminum-activated malate transporter1 (ALMT1)-like protein is a strong candidate gene. We hypothesize that fruit acidity is governed by a gene network in which Ma1 is key member. The goal of this study is to identify the gene network and the potential mechanisms through which the network operates. Guided by Ma1, we analyzed the transcriptomes of mature fruit of contrasting acidity from six apple accessions of genotype Ma_ (MaMa or Mama) and four of mama using RNA-seq and identified 1301 fruit acidity associated genes, among which 18 were most significant acidity genes (MSAGs). Network inferring using weighted gene co-expression network analysis (WGCNA) revealed five co-expression gene network modules of significant (P acidity. Overall, this study provides important insight into the Ma1-mediated gene network controlling acidity in mature apple fruit of diverse genetic background.

Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases.

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Kai Wang

2009-12-01

Full Text Available Co-expression networks are routinely used to study human diseases like obesity and diabetes. Systematic comparison of these networks between species has the potential to elucidate common mechanisms that are conserved between human and rodent species, as well as those that are species-specific characterizing evolutionary plasticity. We developed a semi-parametric meta-analysis approach for combining gene-gene co-expression relationships across expression profile datasets from multiple species. The simulation results showed that the semi-parametric method is robust against noise. When applied to human, mouse, and rat liver co-expression networks, our method out-performed existing methods in identifying gene pairs with coherent biological functions. We identified a network conserved across species that highlighted cell-cell signaling, cell-adhesion and sterol biosynthesis as main biological processes represented in genome-wide association study candidate gene sets for blood lipid levels. We further developed a heterogeneity statistic to test for network differences among multiple datasets, and demonstrated that genes with species-specific interactions tend to be under positive selection throughout evolution. Finally, we identified a human-specific sub-network regulated by RXRG, which has been validated to play a different role in hyperlipidemia and Type 2 diabetes between human and mouse. Taken together, our approach represents a novel step forward in integrating gene co-expression networks from multiple large scale datasets to leverage not only common information but also differences that are dataset-specific.

Identification of PEG-induced water stress responsive transcripts using co-expression network in Eucalyptus grandis.

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Ghosh Dasgupta, Modhumita; Dharanishanthi, Veeramuthu

2017-09-05

Ecophysiological studies in Eucalyptus have shown that water is the principal factor limiting stem growth. Effect of water deficit conditions on physiological and biochemical parameters has been extensively reported in Eucalyptus. The present study was conducted to identify major polyethylene glycol induced water stress responsive transcripts in Eucalyptus grandis using gene co-expression network. A customized array representing 3359 water stress responsive genes was designed to document their expression in leaves of E. grandis cuttings subjected to -0.225MPa of PEG treatment. The differentially expressed transcripts were documented and significantly co-expressed transcripts were used for construction of network. The co-expression network was constructed with 915 nodes and 3454 edges with degree ranging from 2 to 45. Ninety four GO categories and 117 functional pathways were identified in the network. MCODE analysis generated 27 modules and module 6 with 479 nodes and 1005 edges was identified as the biologically relevant network. The major water responsive transcripts represented in the module included dehydrin, osmotin, LEA protein, expansin, arabinogalactans, heat shock proteins, major facilitator proteins, ARM repeat proteins, raffinose synthase, tonoplast intrinsic protein and transcription factors like DREB2A, ARF9, AGL24, UNE12, WLIM1 and MYB66, MYB70, MYB 55, MYB 16 and MYB 103. The coordinated analysis of gene expression patterns and coexpression networks developed in this study identified an array of transcripts that may regulate PEG induced water stress responses in E. grandis. Copyright © 2017 Elsevier B.V. All rights reserved.

Long-term oil contamination alters the molecular ecological networks of soil microbial functional genes

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Yuting eLiang

2016-02-01

Full Text Available With knowledge on microbial composition and diversity, investigation of within-community interactions is a further step to elucidate microbial ecological functions, such as the biodegradation of hazardous contaminants. In this work, microbial functional molecular ecological networks were studied in both contaminated and uncontaminated soils to determine the possible influences of oil contamination on microbial interactions and potential functions. Soil samples were obtained from an oil-exploring site located in South China, and the microbial functional genes were analyzed with GeoChip, a high-throughput functional microarray. By building random networks based on null model, we demonstrated that overall network structures and properties were significantly different between contaminated and uncontaminated soils (P < 0.001. Network connectivity, module numbers, and modularity were all reduced with contamination. Moreover, the topological roles of the genes (module hub and connectors were altered with oil contamination. Subnetworks of genes involved in alkane and polycyclic aromatic hydrocarbon degradation were also constructed. Negative co-occurrence patterns prevailed among functional genes, thereby indicating probable competition relationships. The potential keystone genes, defined as either hubs or genes with highest connectivities in the network, were further identified. The network constructed in this study predicted the potential effects of anthropogenic contamination on microbial community co-occurrence interactions.

MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

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Gonzalez-Dominguez, Jorge; Martin, Maria J

2017-10-10

In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

Co-expression networks reveal the tissue-specific regulation of transcription and splicing.

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Saha, Ashis; Kim, Yungil; Gewirtz, Ariel D H; Jo, Brian; Gao, Chuan; McDowell, Ian C; Engelhardt, Barbara E; Battle, Alexis

2017-11-01

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues. © 2017 Saha et al.; Published by Cold Spring Harbor Laboratory Press.

Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

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Dhaeseleer, Patrik; Liang, Shoudan; Somogyi, Roland

2000-01-01

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

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Recep Colak

2010-10-01

Full Text Available Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented.We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples.We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

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Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

2010-10-25

Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large

[Weighted gene co-expression network analysis in biomedicine research].

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Liu, Wei; Li, Li; Ye, Hua; Tu, Wei

2017-11-25

High-throughput biological technologies are now widely applied in biology and medicine, allowing scientists to monitor thousands of parameters simultaneously in a specific sample. However, it is still an enormous challenge to mine useful information from high-throughput data. The emergence of network biology provides deeper insights into complex bio-system and reveals the modularity in tissue/cellular networks. Correlation networks are increasingly used in bioinformatics applications. Weighted gene co-expression network analysis (WGCNA) tool can detect clusters of highly correlated genes. Therefore, we systematically reviewed the application of WGCNA in the study of disease diagnosis, pathogenesis and other related fields. First, we introduced principle, workflow, advantages and disadvantages of WGCNA. Second, we presented the application of WGCNA in disease, physiology, drug, evolution and genome annotation. Then, we indicated the application of WGCNA in newly developed high-throughput methods. We hope this review will help to promote the application of WGCNA in biomedicine research.

An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

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Botía, Juan A; Vandrovcova, Jana; Forabosco, Paola; Guelfi, Sebastian; D'Sa, Karishma; Hardy, John; Lewis, Cathryn M; Ryten, Mina; Weale, Michael E

2017-04-12

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn ). We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.

Gene co-expression networks shed light into diseases of brain iron accumulation.

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Bettencourt, Conceição; Forabosco, Paola; Wiethoff, Sarah; Heidari, Moones; Johnstone, Daniel M; Botía, Juan A; Collingwood, Joanna F; Hardy, John; Milward, Elizabeth A; Ryten, Mina; Houlden, Henry

2016-03-01

Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce.

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Lamara, Mebarek; Raherison, Elie; Lenz, Patrick; Beaulieu, Jean; Bousquet, Jean; MacKay, John

2016-04-01

Association studies are widely utilized to analyze complex traits but their ability to disclose genetic architectures is often limited by statistical constraints, and functional insights are usually minimal in nonmodel organisms like forest trees. We developed an approach to integrate association mapping results with co-expression networks. We tested single nucleotide polymorphisms (SNPs) in 2652 candidate genes for statistical associations with wood density, stiffness, microfibril angle and ring width in a population of 1694 white spruce trees (Picea glauca). Associations mapping identified 229-292 genes per wood trait using a statistical significance level of P wood associated genes and several known MYB and NAC regulators were identified as network hubs. The network revealed a link between the gene PgNAC8, wood stiffness and microfibril angle, as well as considerable within-season variation for both genetic control of wood traits and gene expression. Trait associations were distributed throughout the network suggesting complex interactions and pleiotropic effects. Our findings indicate that integration of association mapping and co-expression networks enhances our understanding of complex wood traits. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Estimation of the proteomic cancer co-expression sub networks by using association estimators.

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Cihat Erdoğan

Full Text Available In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA. Correlation and mutual information (MI based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators' performance, a multi-layer data integration platform on gene-disease associations (DisGeNET and the Molecular Signatures Database (MSigDB was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink and 64% for Schurmann-Grassberger (SG association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists.

Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

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Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

2017-08-01

This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients

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DeYoung Joseph

2009-08-01

Full Text Available Abstract Background Amyotrophic Lateral Sclerosis (ALS is a lethal disorder characterized by progressive degeneration of motor neurons in the brain and spinal cord. Diagnosis is mainly based on clinical symptoms, and there is currently no therapy to stop the disease or slow its progression. Since access to spinal cord tissue is not possible at disease onset, we investigated changes in gene expression profiles in whole blood of ALS patients. Results Our transcriptional study showed dramatic changes in blood of ALS patients; 2,300 probes (9.4% showed significant differential expression in a discovery dataset consisting of 30 ALS patients and 30 healthy controls. Weighted gene co-expression network analysis (WGCNA was used to find disease-related networks (modules and disease related hub genes. Two large co-expression modules were found to be associated with ALS. Our findings were replicated in a second (30 patients and 30 controls and third dataset (63 patients and 63 controls, thereby demonstrating a highly significant and consistent association of two large co-expression modules with ALS disease status. Ingenuity Pathway Analysis of the ALS related module genes implicates enrichment of functional categories related to genetic disorders, neurodegeneration of the nervous system and inflammatory disease. The ALS related modules contain a number of candidate genes possibly involved in pathogenesis of ALS. Conclusion This first large-scale blood gene expression study in ALS observed distinct patterns between cases and controls which may provide opportunities for biomarker development as well as new insights into the molecular mechanisms of the disease.

A contribution to the study of plant development evolution based on gene co-expression networks

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Francisco J. Romero-Campero

2013-08-01

Full Text Available Phototrophic eukaryotes are among the most successful organisms on Earth due to their unparalleled efficiency at capturing light energy and fixing carbon dioxide to produce organic molecules. A conserved and efficient network of light-dependent regulatory modules could be at the bases of this success. This regulatory system conferred early advantages to phototrophic eukaryotes that allowed for specialization, complex developmental processes and modern plant characteristics. We have studied light-dependent gene regulatory modules from algae to plants employing integrative-omics approaches based on gene co-expression networks. Our study reveals some remarkably conserved ways in which eukaryotic phototrophs deal with day length and light signaling. Here we describe how a family of Arabidopsis transcription factors involved in photoperiod response has evolved from a single algal gene according to the innovation, amplification and divergence theory of gene evolution by duplication. These modifications of the gene co-expression networks from the ancient unicellular green algae Chlamydomonas reinhardtii to the modern brassica Arabidopsis thaliana may hint on the evolution and specialization of plants and other organisms.

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses.

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Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N; Jones, Byron C; Lu, Lu; Wang, Xusheng

2018-01-01

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

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Jie Luo

2018-04-01

Full Text Available Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1, down-regulation in NOE but rescue in RSE (pattern 2, up-regulation in both restraint stress followed by a saline injection (RSS and NOE, and further amplification in RSE (pattern 3, and up-regulation in RSS but reduction in both NOE and RSE (pattern 4. We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

A co-expression gene network associated with developmental regulation of apple fruit acidity.

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Bai, Yang; Dougherty, Laura; Cheng, Lailiang; Xu, Kenong

2015-08-01

Apple fruit acidity, which affects the fruit's overall taste and flavor to a large extent, is primarily determined by the concentration of malic acid. Previous studies demonstrated that the major QTL malic acid (Ma) on chromosome 16 is largely responsible for fruit acidity variations in apple. Recent advances suggested that a natural mutation that gives rise to a premature stop codon in one of the two aluminum-activated malate transporter (ALMT)-like genes (called Ma1) is the genetic causal element underlying Ma. However, the natural mutation does not explain the developmental changes of fruit malate levels in a given genotype. Using RNA-seq data from the fruit of 'Golden Delicious' taken at 14 developmental stages from 1 week after full-bloom (WAF01) to harvest (WAF20), we characterized their transcriptomes in groups of high (12.2 ± 1.6 mg/g fw, WAF03-WAF08), mid (7.4 ± 0.5 mg/g fw, WAF01-WAF02 and WAF10-WAF14) and low (5.4 ± 0.4 mg/g fw, WAF16-WAF20) malate concentrations. Detailed analyses showed that a set of 3,066 genes (including Ma1) were expressed not only differentially (P FDR < 0.05) between the high and low malate groups (or between the early and late developmental stages) but also in significant (P < 0.05) correlation with malate concentrations. The 3,066 genes fell in 648 MapMan (sub-) bins or functional classes, and 19 of them were significantly (P FDR < 0.05) co-enriched or co-suppressed in a malate dependent manner. Network inferring using the 363 genes encompassed in the 19 (sub-) bins, identified a major co-expression network of 239 genes. Since the 239 genes were also differentially expressed between the early (WAF03-WAF08) and late (WAF16-WAF20) developmental stages, the major network was considered to be associated with developmental regulation of apple fruit acidity in 'Golden Delicious'.

In vitro co-cultures of human gut bacterial species as predicted from co-occurrence network analysis

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Das, Promi; Ji, Boyang; Kovatcheva-Datchary, Petia

2018-01-01

Network analysis of large metagenomic datasets generated by current sequencing technologies can reveal significant co-occurrence patterns between microbial species of a biological community. These patterns can be analyzed in terms of pairwise combinations between all species comprising a community...... thetaiotaomicron, as well as Faecalibacterium prausnitzii and Roseburia inulinivorans as model organisms for our study. We then delineate the outcome of the co-cultures when equal distributions of resources were provided. The growth behavior of the co-culture was found to be dependent on the types of microbial...... species present, their specific metabolic activities, and resulting changes in the culture environment. Through this reductionist approach and using novel in vitro combinations of microbial species under anaerobic conditions, the results of this work will aid in the understanding and design of synthetic...

Step-by-Step Construction of Gene Co-expression Networks from High-Throughput Arabidopsis RNA Sequencing Data.

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Contreras-López, Orlando; Moyano, Tomás C; Soto, Daniela C; Gutiérrez, Rodrigo A

2018-01-01

The rapid increase in the availability of transcriptomics data generated by RNA sequencing represents both a challenge and an opportunity for biologists without bioinformatics training. The challenge is handling, integrating, and interpreting these data sets. The opportunity is to use this information to generate testable hypothesis to understand molecular mechanisms controlling gene expression and biological processes (Fig. 1). A successful strategy to generate tractable hypotheses from transcriptomics data has been to build undirected network graphs based on patterns of gene co-expression. Many examples of new hypothesis derived from network analyses can be found in the literature, spanning different organisms including plants and specific fields such as root developmental biology.In order to make the process of constructing a gene co-expression network more accessible to biologists, here we provide step-by-step instructions using published RNA-seq experimental data obtained from a public database. Similar strategies have been used in previous studies to advance root developmental biology. This guide includes basic instructions for the operation of widely used open source platforms such as Bio-Linux, R, and Cytoscape. Even though the data we used in this example was obtained from Arabidopsis thaliana, the workflow developed in this guide can be easily adapted to work with RNA-seq data from any organism.

In-silico gene co-expression network analysis in Paracoccidioides brasiliensis with reference to haloacid dehalogenase superfamily hydrolase gene

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Raghunath Satpathy

2015-01-01

Full Text Available Context: Paracoccidioides brasiliensis, a dimorphic fungus is the causative agent of paracoccidioidomycosis, a disease globally affecting millions of people. The haloacid dehalogenase (HAD superfamily hydrolases enzyme in the fungi, in particular, is known to be responsible in the pathogenesis by adhering to the tissue. Hence, identification of novel drug targets is essential. Aims: In-silico based identification of co-expressed genes along with HAD superfamily hydrolase in P. brasiliensis during the morphogenesis from mycelium to yeast to identify possible genes as drug targets. Materials and Methods: In total, four datasets were retrieved from the NCBI-gene expression omnibus (GEO database, each containing 4340 genes, followed by gene filtration expression of the data set. Further co-expression (CE study was performed individually and then a combination these genes were visualized in the Cytoscape 2. 8.3. Statistical Analysis Used: Mean and standard deviation value of the HAD superfamily hydrolase gene was obtained from the expression data and this value was subsequently used for the CE calculation purpose by selecting specific correlation power and filtering threshold. Results: The 23 genes that were thus obtained are common with respect to the HAD superfamily hydrolase gene. A significant network was selected from the Cytoscape network visualization that contains total 7 genes out of which 5 genes, which do not have significant protein hits, obtained from gene annotation of the expressed sequence tags by BLAST X. For all the protein PSI-BLAST was performed against human genome to find the homology. Conclusions: The gene co-expression network was obtained with respect to HAD superfamily dehalogenase gene in P. Brasiliensis.

Integrative analysis of many weighted co-expression networks using tensor computation.

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Wenyuan Li

2011-06-01

Full Text Available The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks.

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

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Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Functional characterization of a Penicillium chrysogenum mutanase gene induced upon co-cultivation with Bacillus subtilis

NARCIS (Netherlands)

Bajaj, I.; Veiga, T.; Van Dissel, D.; Pronk, J.T.; Daran, J.M.

2014-01-01

Background Microbial gene expression is strongly influenced by environmental growth conditions. Comparison of gene expression under different conditions is frequently used for functional analysis and to unravel regulatory networks, however, gene expression responses to co-cultivation with other

Bacterial networks and co-occurrence relationships in the lettuce root microbiota.

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Cardinale, Massimiliano; Grube, Martin; Erlacher, Armin; Quehenberger, Julian; Berg, Gabriele

2015-01-01

Lettuce is one of the most common raw foods worldwide, but occasionally also involved in pathogen outbreaks. To understand the correlative structure of the bacterial community as a network, we studied root microbiota of eight ancient and modern Lactuca sativa cultivars and the wild ancestor Lactuca serriola by pyrosequencing of 16S rRNA gene amplicon libraries. The lettuce microbiota was dominated by Proteobacteria and Bacteriodetes, as well as abundant Chloroflexi and Actinobacteria. Cultivar specificity comprised 12.5% of the species. Diversity indices were not different between lettuce cultivar groups but higher than in L. serriola, suggesting that domestication lead to bacterial diversification in lettuce root system. Spearman correlations between operational taxonomic units (OTUs) showed that co-occurrence prevailed over co-exclusion, and complementary fluorescence in situ hybridization-confocal laser scanning microscopy (FISH-CLSM) analyses revealed that this pattern results from both potential interactions and habitat sharing. Predominant taxa, such as Pseudomonas, Flavobacterium and Sphingomonadaceae rather suggested interactions, even though these are not necessarily part of significant modules in the co-occurrence networks. Without any need for complex interactions, single organisms are able to invade into this microbial network and to colonize lettuce plants, a fact that can influence the susceptibility to pathogens. The approach to combine co-occurrence analysis and FISH-CLSM allows reliably reconstructing and interpreting microbial interaction networks. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Integrated Approach to Reconstruction of Microbial Regulatory Networks

Energy Technology Data Exchange (ETDEWEB)

Rodionov, Dmitry A [Sanford-Burnham Medical Research Institute; Novichkov, Pavel S [Lawrence Berkeley National Laboratory

2013-11-04

This project had the goal(s) of development of integrated bioinformatics platform for genome-scale inference and visualization of transcriptional regulatory networks (TRNs) in bacterial genomes. The work was done in Sanford-Burnham Medical Research Institute (SBMRI, P.I. D.A. Rodionov) and Lawrence Berkeley National Laboratory (LBNL, co-P.I. P.S. Novichkov). The developed computational resources include: (1) RegPredict web-platform for TRN inference and regulon reconstruction in microbial genomes, and (2) RegPrecise database for collection, visualization and comparative analysis of transcriptional regulons reconstructed by comparative genomics. These analytical resources were selected as key components in the DOE Systems Biology KnowledgeBase (SBKB). The high-quality data accumulated in RegPrecise will provide essential datasets of reference regulons in diverse microbes to enable automatic reconstruction of draft TRNs in newly sequenced genomes. We outline our progress toward the three aims of this grant proposal, which were: Develop integrated platform for genome-scale regulon reconstruction; Infer regulatory annotations in several groups of bacteria and building of reference collections of microbial regulons; and Develop KnowledgeBase on microbial transcriptional regulation.

Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

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Xiaolin Xiao

2014-01-01

Full Text Available Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states. Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based and humans (mRNA-sequencing-based and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi

Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

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Xiao, Xiaolin; Moreno-Moral, Aida; Rotival, Maxime; Bottolo, Leonardo; Petretto, Enrico

2014-01-01

Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states). Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks) that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted) networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based) and humans (mRNA-sequencing-based) and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi-tissue subnetwork of co-expressed

Microarray profiling and co-expression network analysis of circulating lncRNAs and mRNAs associated with major depressive disorder.

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Zhifen Liu

Full Text Available LncRNAs, which represent one of the most highly expressed classes of ncRNAs in the brain, are becoming increasingly interesting with regard to brain functions and disorders. However, changes in the expression of regulatory lncRNAs in Major Depressive Disorder (MDD have not yet been reported. Using microarrays, we profiled the expression of 34834 lncRNAs and 39224 mRNAs in peripheral blood sampled from MDD patients as well as demographically-matched controls. Among these, we found that 2007 lncRNAs and 1667 mRNAs were differentially expressed, 17 of which were documented as depression-related gene in previous studies. Gene Ontology (GO and pathway analyses indicated that the biological functions of differentially expressed mRNAs were related to fundamental metabolic processes and neurodevelopment diseases. To investigate the potential regulatory roles of the differentially expressed lncRNAs on the mRNAs, we also constructed co-expression networks composed of the lncRNAs and mRNAs, which shows significant correlated patterns of expression. In the MDD-derived network, there were a greater number of nodes and connections than that in the control-derived network. The lncRNAs located at chr10:874695-874794, chr10:75873456-75873642, and chr3:47048304-47048512 may be important factors regulating the expression of mRNAs as they have previously been reported associations with MDD. This study is the first to explore genome-wide lncRNA expression and co-expression with mRNA patterns in MDD using microarray technology. We identified circulating lncRNAs that are aberrantly expressed in MDD and the results suggest that lncRNAs may contribute to the molecular pathogenesis of MDD.

GeneCAT--novel webtools that combine BLAST and co-expression analyses

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Mutwil, Marek; Obro, Jens; Willats, William G T

2008-01-01

The gene co-expression analysis toolbox (GeneCAT) introduces several novel microarray data analyzing tools. First, the multigene co-expression analysis, combined with co-expressed gene networks, provides a more powerful data mining technique than standard, single-gene co-expression analysis. Second...... orthologs in the plant model organisms Arabidopsis thaliana and Hordeum vulgare (Barley). GeneCAT is equipped with expression data for the model plant A. thaliana, and first to introduce co-expression mining tools for the monocot Barley. GeneCAT is available at http://genecat.mpg.de....

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

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Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

2016-05-01

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration.

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

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Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis

Characterization of WRKY co-regulatory networks in rice and Arabidopsis

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Kikuchi Shoshi

2009-09-01

Full Text Available Abstract Background The WRKY transcription factor gene family has a very ancient origin and has undergone extensive duplications in the plant kingdom. Several studies have pointed out their involvement in a range of biological processes, revealing that a large number of WRKY genes are transcriptionally regulated under conditions of biotic and/or abiotic stress. To investigate the existence of WRKY co-regulatory networks in plants, a whole gene family WRKYs expression study was carried out in rice (Oryza sativa. This analysis was extended to Arabidopsis thaliana taking advantage of an extensive repository of gene expression data. Results The presented results suggested that 24 members of the rice WRKY gene family (22% of the total were differentially-regulated in response to at least one of the stress conditions tested. We defined the existence of nine OsWRKY gene clusters comprising both phylogenetically related and unrelated genes that were significantly co-expressed, suggesting that specific sets of WRKY genes might act in co-regulatory networks. This hypothesis was tested by Pearson Correlation Coefficient analysis of the Arabidopsis WRKY gene family in a large set of Affymetrix microarray experiments. AtWRKYs were found to belong to two main co-regulatory networks (COR-A, COR-B and two smaller ones (COR-C and COR-D, all including genes belonging to distinct phylogenetic groups. The COR-A network contained several AtWRKY genes known to be involved mostly in response to pathogens, whose physical and/or genetic interaction was experimentally proven. We also showed that specific co-regulatory networks were conserved between the two model species by identifying Arabidopsis orthologs of the co-expressed OsWRKY genes. Conclusion In this work we identified sets of co-expressed WRKY genes in both rice and Arabidopsis that are functionally likely to cooperate in the same signal transduction pathways. We propose that, making use of data from co

CoNekT: an open-source framework for comparative genomic and transcriptomic network analyses.

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Proost, Sebastian; Mutwil, Marek

2018-05-01

The recent accumulation of gene expression data in the form of RNA sequencing creates unprecedented opportunities to study gene regulation and function. Furthermore, comparative analysis of the expression data from multiple species can elucidate which functional gene modules are conserved across species, allowing the study of the evolution of these modules. However, performing such comparative analyses on raw data is not feasible for many biologists. Here, we present CoNekT (Co-expression Network Toolkit), an open source web server, that contains user-friendly tools and interactive visualizations for comparative analyses of gene expression data and co-expression networks. These tools allow analysis and cross-species comparison of (i) gene expression profiles; (ii) co-expression networks; (iii) co-expressed clusters involved in specific biological processes; (iv) tissue-specific gene expression; and (v) expression profiles of gene families. To demonstrate these features, we constructed CoNekT-Plants for green alga, seed plants and flowering plants (Picea abies, Chlamydomonas reinhardtii, Vitis vinifera, Arabidopsis thaliana, Oryza sativa, Zea mays and Solanum lycopersicum) and thus provide a web-tool with the broadest available collection of plant phyla. CoNekT-Plants is freely available from http://conekt.plant.tools, while the CoNekT source code and documentation can be found at https://github.molgen.mpg.de/proost/CoNekT/.

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model.

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Omony, Jimmy; de Jong, Anne; Krawczyk, Antonina O; Eijlander, Robyn T; Kuipers, Oscar P

2018-02-09

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes.

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus

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Chaoqun Li

2018-01-01

Full Text Available Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice. Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus.

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Li, Chaoqun; Cao, Feifei; Li, Shengli; Huang, Shenglin; Li, Wei; Abumaria, Nashat

2017-01-01

Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA) has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice). Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to stress

Extreme CO2 disturbance and the resilience of soil microbial communities

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McFarland, Jack W.; Waldrop, Mark P.; Haw, Monica

2013-01-01

Carbon capture and storage (CSS) technology has the potential to inadvertently release large quantities of CO2 through geologic substrates and into surrounding soils and ecosystems. Such a disturbance has the potential to not only alter the structure and function of plant and animal communities, but also soils, soil microbial communities, and the biogeochemical processes they mediate. At Mammoth Mountain, we assessed the soil microbial community response to CO2 disturbance (derived from volcanic ‘cold’ CO2) that resulted in localized tree kill; soil CO2 concentrations in our study area ranged from 0.6% to 60%. Our objectives were to examine how microbial communities and their activities are restructured by extreme CO2 disturbance, and assess the response of major microbial taxa to the reintroduction of limited plant communities following an extensive period (15–20 years) with no plants. We found that CO2-induced tree kill reduced soil carbon (C) availability along our sampling transect. In response, soil microbial biomass decreased by an order of magnitude from healthy forest to impacted areas. Soil microorganisms were most sensitive to changes in soil organic C, which explained almost 60% of the variation for microbial biomass C (MBC) along the CO2gradient. We employed phospholipid fatty acid analysis and quantitative PCR (qPCR) to determine compositional changes among microbial communities in affected areas and found substantial reductions in microbial biomass linked to the loss of soil fungi. In contrast, archaeal populations responded positively to the CO2 disturbance, presumably due to reduced competition of bacteria and fungi, and perhaps unique adaptations to energy stress. Enzyme activities important in the cycling of soil C, nitrogen (N), and phosphorus (P) declined with increasing CO2, though specific activities (per unit MBC) remained stable or increased suggesting functional redundancy among restructured communities. We conclude that both the

Thermodynamic and Kinetic Response of Microbial Reactions to High CO2.

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Jin, Qusheng; Kirk, Matthew F

2016-01-01

Geological carbon sequestration captures CO 2 from industrial sources and stores the CO 2 in subsurface reservoirs, a viable strategy for mitigating global climate change. In assessing the environmental impact of the strategy, a key question is how microbial reactions respond to the elevated CO 2 concentration. This study uses biogeochemical modeling to explore the influence of CO 2 on the thermodynamics and kinetics of common microbial reactions in subsurface environments, including syntrophic oxidation, iron reduction, sulfate reduction, and methanogenesis. The results show that increasing CO 2 levels decreases groundwater pH and modulates chemical speciation of weak acids in groundwater, which in turn affect microbial reactions in different ways and to different extents. Specifically, a thermodynamic analysis shows that increasing CO 2 partial pressure lowers the energy available from syntrophic oxidation and acetoclastic methanogenesis, but raises the available energy of microbial iron reduction, hydrogenotrophic sulfate reduction and methanogenesis. Kinetic modeling suggests that high CO 2 has the potential of inhibiting microbial sulfate reduction while promoting iron reduction. These results are consistent with the observations of previous laboratory and field studies, and highlight the complexity in microbiological responses to elevated CO 2 abundance, and the potential power of biogeochemical modeling in evaluating and quantifying these responses.

Thermodynamic and kinetic response of microbial reactions to high CO2

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Qusheng Jin

2016-11-01

Full Text Available Geological carbon sequestration captures CO2 from industrial sources and stores the CO2 in subsurface reservoirs, a viable strategy for mitigating global climate change. In assessing the environmental impact of the strategy, a key question is how microbial reactions respond to the elevated CO2 concentration. This study uses biogeochemical modeling to explore the influence of CO2 on the thermodynamics and kinetics of common microbial reactions in subsurface environments, including syntrophic oxidation, iron reduction, sulfate reduction, and methanogenesis. The results show that increasing CO2 levels decreases groundwater pH and modulates chemical speciation of weak acids in groundwater, which in turn affect microbial reactions in different ways and to different extents. Specifically, a thermodynamic analysis shows that increasing CO2 partial pressure lowers the energy available from syntrophic oxidation and acetoclastic methanogenesis, but raises the available energy of microbial iron reduction, hydrogenotrophic sulfate reduction and methanogenesis. Kinetic modeling suggests that high CO2 has the potential of inhibiting microbial sulfate reduction while promoting iron reduction. These results are consistent with the observations of previous laboratory and field studies, and highlight the complexity in microbiological responses to elevated CO2 abundance, and the potential power of biogeochemical modeling in evaluating and quantifying these responses.

Global similarity and local divergence in human and mouse gene co-expression networks

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Koonin Eugene V

2006-09-01

Full Text Available Abstract Background A genome-wide comparative analysis of human and mouse gene expression patterns was performed in order to evaluate the evolutionary divergence of mammalian gene expression. Tissue-specific expression profiles were analyzed for 9,105 human-mouse orthologous gene pairs across 28 tissues. Expression profiles were resolved into species-specific coexpression networks, and the topological properties of the networks were compared between species. Results At the global level, the topological properties of the human and mouse gene coexpression networks are, essentially, identical. For instance, both networks have topologies with small-world and scale-free properties as well as closely similar average node degrees, clustering coefficients, and path lengths. However, the human and mouse coexpression networks are highly divergent at the local level: only a small fraction ( Conclusion The dissonance between global versus local network divergence suggests that the interspecies similarity of the global network properties is of limited biological significance, at best, and that the biologically relevant aspects of the architectures of gene coexpression are specific and particular, rather than universal. Nevertheless, there is substantial evolutionary conservation of the local network structure which is compatible with the notion that gene coexpression networks are subject to purifying selection.

Analysis of Microbial Communities in the Oil Reservoir Subjected to CO2-Flooding by Using Functional Genes as Molecular Biomarkers for Microbial CO2 Sequestration

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Jin-Feng eLiu

2015-03-01

Full Text Available Sequestration of CO2 in oil reservoirs is considered to be one of the feasible options for mitigating atmospheric CO2 building up and also for the in situ potential bioconversion of stored CO2 to methane. However, the information on these functional microbial communities and the impact of CO2 storage on them is hardly available. In this paper a comprehensive molecular survey was performed on microbial communities in production water samples from oil reservoirs experienced CO2-flooding by analysis of functional genes involved in the process, including cbbM, cbbL, fthfs, [FeFe]-hydrogenase and mcrA. As a comparison, these functional genes in the production water samples from oil reservoir only experienced water-flooding in areas of the same oil bearing bed were also analyzed. It showed that these functional genes were all of rich diversity in these samples, and the functional microbial communities and their diversity were strongly affected by a long-term exposure to injected CO2. More interestingly, microorganisms affiliated with members of the genera Methanothemobacter, Acetobacterium and Halothiobacillus as well as hydrogen producers in CO2 injected area either increased or remained unchanged in relative abundance compared to that in water-flooded area, which implied that these microorganisms could adapt to CO2 injection and, if so, demonstrated the potential for microbial fixation and conversion of CO2 into methane in subsurface oil reservoirs.

Comparison of co-expression measures: mutual information, correlation, and model based indices.

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Song, Lin; Langfelder, Peter; Horvath, Steve

2012-12-09

Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures. Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes). We provide a comprehensive comparison between mutual information and several correlation measures in 8 empirical data sets and in simulations. We also study different approaches for transforming an adjacency matrix, e.g. using the topological overlap measure. Overall, we confirm close relationships between MI and correlation in all data sets which reflects the fact that most gene pairs satisfy linear or monotonic relationships. We discuss rare situations when the two measures disagree. We also compare correlation and MI based approaches when it comes to defining co-expression network modules. We show that a robust measure of correlation (the biweight midcorrelation transformed via the topological overlap transformation) leads to modules that are superior to MI based modules and maximal information coefficient (MIC) based modules in terms of gene ontology enrichment. We present a function that relates correlation to mutual information which can be used to approximate the mutual information from the corresponding correlation coefficient. We propose the use of polynomial or spline regression models as an alternative to MI for capturing non-linear relationships between quantitative variables. The biweight midcorrelation outperforms MI in terms of elucidating gene pairwise relationships. Coupled with the topological overlap matrix transformation, it often leads to more significantly enriched co-expression modules. Spline and polynomial networks form attractive alternatives to MI in case of non-linear relationships. Our results indicate that MI

Depth-resolved microbial community analyses in the anaerobic co-digester of dewatered sewage sludge with food waste.

Science.gov (United States)

Xu, Rui; Yang, Zhao-Hui; Zheng, Yue; Zhang, Hai-Bo; Liu, Jian-Bo; Xiong, Wei-Ping; Zhang, Yan-Ru; Ahmad, Kito

2017-11-01

This study evaluated the impacts of FW addition on co-digestion in terms of microbial community. Anaerobic co-digestion (AcoD) reactors were conducted at gradually increased addition of food waste (FW) from 0 to 4kg-VSm -3 d -1 for 220days. Although no markable acidification was found at an OLR of 4kg-VSm -3 d -1 , the unhealthy operation was observed in aspect of an inhibited methane yield (185mLg -1 VS added ), which was restricted by 40% when compared with its peak value. Deterioration of digestion process was timely indicated by the dramatic decrease of archaeal population and microbial biodiversity. Furthermore, the cooperation network showed a considerable number of rare species (<1%) were strongly correlated with methane production, which were frequently overlooked due to the limits of detecting resolution or analysis methods before. Advances in the analysis of sensitive microbial community enable us to detect the early disturbances in AcoD reactors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Construction and comparison of gene co-expression networks shows complex plant immune responses

Directory of Open Access Journals (Sweden)

Luis Guillermo Leal

2014-10-01

Full Text Available Gene co-expression networks (GCNs are graphic representations that depict the coordinated transcription of genes in response to certain stimuli. GCNs provide functional annotations of genes whose function is unknown and are further used in studies of translational functional genomics among species. In this work, a methodology for the reconstruction and comparison of GCNs is presented. This approach was applied using gene expression data that were obtained from immunity experiments in Arabidopsis thaliana, rice, soybean, tomato and cassava. After the evaluation of diverse similarity metrics for the GCN reconstruction, we recommended the mutual information coefficient measurement and a clustering coefficient-based method for similarity threshold selection. To compare GCNs, we proposed a multivariate approach based on the Principal Component Analysis (PCA. Branches of plant immunity that were exemplified by each experiment were analyzed in conjunction with the PCA results, suggesting both the robustness and the dynamic nature of the cellular responses. The dynamic of molecular plant responses produced networks with different characteristics that are differentiable using our methodology. The comparison of GCNs from plant pathosystems, showed that in response to similar pathogens plants could activate conserved signaling pathways. The results confirmed that the closeness of GCNs projected on the principal component space is an indicative of similarity among GCNs. This also can be used to understand global patterns of events triggered during plant immune responses.

The influence of e-waste recycling on the molecular ecological network of soil microbial communities in Pakistan and China.

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Jiang, Longfei; Cheng, Zhineng; Zhang, Dayi; Song, Mengke; Wang, Yujie; Luo, Chunling; Yin, Hua; Li, Jun; Zhang, Gan

2017-12-01

Primitive electronic waste (e-waste) recycling releases large amounts of organic pollutants and heavy metals into the environment. As crucial moderators of geochemical cycling processes and pollutant remediation, soil microbes may be affected by these contaminants. We collected soil samples heavily contaminated by e-waste recycling in China and Pakistan, and analyzed the indigenous microbial communities. The results of this work revealed that the microbial community composition and diversity, at both whole and core community levels, were affected significantly by polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs) and heavy metals (e.g., Cu, Zn, and Pb). The geographical distance showed limited impacts on microbial communities compared with geochemical factors. The constructed ecological network of soil microbial communities illustrated microbial co-occurrence, competition and antagonism across soils, revealing the response of microbes to soil properties and pollutants. Two of the three main modules constructed with core operational taxonomic units (OTUs) were sensitive to nutrition (total organic carbon and total nitrogen) and pollutants. Five key OTUs assigned to Acidobacteria, Proteobacteria, and Nitrospirae in ecological network were identified. This is the first study to report the effects of e-waste pollutants on soil microbial network, providing a deeper understanding of the ecological influence of crude e-waste recycling activities on soil ecological functions. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

OpenAIRE

Musungu, Bryan M.; Bhatnagar, Deepak; Brown, Robert L.; Payne, Gary A.; OBrian, Greg; Fakhoury, Ahmad M.; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flav...

Impact of CO_2 on the Evolution of Microbial Communities Exposed to Carbon Storage Conditions, Enhanced Oil Recovery, and CO_2 Leakage

International Nuclear Information System (INIS)

Gulliver, Djuna M.; Gregory, Kelvin B.; Lowry, Gregory V.

2016-01-01

Geologic carbon storage (GCS) is a crucial part of a proposed mitigation strategy to reduce the anthropogenic carbon dioxide (CO_2) emissions to the atmosphere. During this process, CO_2 is injected as super critical carbon dioxide (SC-CO_2) in confined deep subsurface storage units, such as saline aquifers and depleted oil reservoirs. The deposition of vast amounts of CO_2 in subsurface geologic formations could unintentionally lead to CO_2 leakage into overlying freshwater aquifers. Introduction of CO_2 into these subsurface environments will greatly increase the CO_2 concentration and will create CO_2 concentration gradients that drive changes in the microbial communities present. While it is expected that altered microbial communities will impact the biogeochemistry of the subsurface, there is no information available on how CO_2 gradients will impact these communities. The overarching goal of this project is to understand how CO_2 exposure will impact subsurface microbial communities at temperatures and pressures that are relevant to GCS and CO_2 leakage scenarios. To meet this goal, unfiltered, aqueous samples from a deep saline aquifer, a depleted oil reservoir, and a fresh water aquifer were exposed to varied concentrations of CO_2 at reservoir pressure and temperature. The microbial ecology of the samples was examined using molecular, DNA-based techniques. The results from these studies were also compared across the sites to determine any existing trends. Results reveal that increasing CO_2 leads to decreased DNA concentrations regardless of the site, suggesting that microbial processes will be significantly hindered or absent nearest the CO_2 injection/leakage plume where CO_2 concentrations are highest. At CO_2 exposures expected downgradient from the CO_2 plume, selected microorganisms emerged as dominant in the CO_2 exposed conditions. Results suggest that the altered microbial community was site specific and highly dependent on pH. The site

Functional modules by relating protein interaction networks and gene expression.

Science.gov (United States)

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Responses of soil microbial activity to cadmium pollution and elevated CO2.

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Chen, Yi Ping; Liu, Qiang; Liu, Yong Jun; Jia, Feng An; He, Xin Hua

2014-03-06

To address the combined effects of cadmium (Cd) and elevated CO2 on soil microbial communities, DGGE (denaturing gradient gel electrophoresis) profiles, respiration, carbon (C) and nitrogen (N) concentrations, loessial soils were exposed to four levels of Cd, i.e., 0 (Cd0), 1.5 (Cd1.5), 3.0 (Cd3.0) and 6.0 (Cd6.0) mg Cd kg(-1) soil, and two levels of CO2, i.e., 360 (aCO2) and 480 (eCO2) ppm. Compared to Cd0, Cd1.5 increased fungal abundance but decreased bacterial abundance under both CO2 levels, whilst Cd3.0 and Cd6.0 decreased both fungal and bacterial abundance. Profiles of DGGE revealed alteration of soil microbial communities under eCO2. Soil respiration decreased with Cd concentrations and was greater under eCO2 than under aCO2. Soil total C and N were greater under higher Cd. These results suggest eCO2 could stimulate, while Cd pollution could restrain microbial reproduction and C decomposition with the restraint effect alleviated by eCO2.

Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network

Science.gov (United States)

Li, Huajiao; An, Haizhong; Wang, Yue; Huang, Jiachen; Gao, Xiangyun

2016-05-01

Keeping abreast of trends in the articles and rapidly grasping a body of article's key points and relationship from a holistic perspective is a new challenge in both literature research and text mining. As the important component, keywords can present the core idea of the academic article. Usually, articles on a single theme or area could share one or some same keywords, and we can analyze topological features and evolution of the articles co-keyword networks and keywords co-occurrence networks to realize the in-depth analysis of the articles. This paper seeks to integrate statistics, text mining, complex networks and visualization to analyze all of the academic articles on one given theme, complex network(s). All 5944 ;complex networks; articles that were published between 1990 and 2013 and are available on the Web of Science are extracted. Based on the two-mode affiliation network theory, a new frontier of complex networks, we constructed two different networks, one taking the articles as nodes, the co-keyword relationships as edges and the quantity of co-keywords as the weight to construct articles co-keyword network, and another taking the articles' keywords as nodes, the co-occurrence relationships as edges and the quantity of simultaneous co-occurrences as the weight to construct keyword co-occurrence network. An integrated method for analyzing the topological features and evolution of the articles co-keyword network and keywords co-occurrence networks is proposed, and we also defined a new function to measure the innovation coefficient of the articles in annual level. This paper provides a useful tool and process for successfully achieving in-depth analysis and rapid understanding of the trends and relationships of articles in a holistic perspective.

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

Science.gov (United States)

Musungu, Bryan M.; Bhatnagar, Deepak; Brown, Robert L.; Payne, Gary A.; OBrian, Greg; Fakhoury, Ahmad M.; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus, a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays, and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays, there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus. Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus. PMID:27917194

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways.

Science.gov (United States)

Musungu, Bryan M; Bhatnagar, Deepak; Brown, Robert L; Payne, Gary A; OBrian, Greg; Fakhoury, Ahmad M; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus , a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays , and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays , there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus . Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus .

Network Analysis of Earth's Co-Evolving Geosphere and Biosphere

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Hazen, R. M.; Eleish, A.; Liu, C.; Morrison, S. M.; Meyer, M.; Consortium, K. D.

2017-12-01

A fundamental goal of Earth science is the deep understanding of Earth's dynamic, co-evolving geosphere and biosphere through deep time. Network analysis of geo- and bio- `big data' provides an interactive, quantitative, and predictive visualization framework to explore complex and otherwise hidden high-dimension features of diversity, distribution, and change in the evolution of Earth's geochemistry, mineralogy, paleobiology, and biochemistry [1]. Networks also facilitate quantitative comparison of different geological time periods, tectonic settings, and geographical regions, as well as different planets and moons, through network metrics, including density, centralization, diameter, and transitivity.We render networks by employing data related to geographical, paragenetic, environmental, or structural relationships among minerals, fossils, proteins, and microbial taxa. An important recent finding is that the topography of many networks reflects parameters not explicitly incorporated in constructing the network. For example, networks for minerals, fossils, and protein structures reveal embedded qualitative time axes, with additional network geometries possibly related to extinction and/or other punctuation events (see Figure). Other axes related to chemical activities and volatile fugacities, as well as pressure and/or depth of formation, may also emerge from network analysis. These patterns provide new insights into the way planets evolve, especially Earth's co-evolving geosphere and biosphere. 1. Morrison, S.M. et al. (2017) Network analysis of mineralogical systems. American Mineralogist 102, in press. Figure Caption: A network of Phanerozoic Era fossil animals from the past 540 million years includes blue, red, and black circles (nodes) representing family-level taxa and grey lines (links) between coexisting families. Age information was not used in the construction of this network; nevertheless an intrinsic timeline is embedded in the network topology. In

Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design.

Science.gov (United States)

Li, Jianqiang; Zhou, Doudou; Qiu, Weiliang; Shi, Yuliang; Yang, Ji-Jiang; Chen, Shi; Wang, Qing; Pan, Hui

2018-01-12

Investigating how genes jointly affect complex human diseases is important, yet challenging. The network approach (e.g., weighted gene co-expression network analysis (WGCNA)) is a powerful tool. However, genomic data usually contain substantial batch effects, which could mask true genomic signals. Paired design is a powerful tool that can reduce batch effects. However, it is currently unclear how to appropriately apply WGCNA to genomic data from paired design. In this paper, we modified the current WGCNA pipeline to analyse high-throughput genomic data from paired design. We illustrated the modified WGCNA pipeline by analysing the miRNA dataset provided by Shiah et al. (2014), which contains forty oral squamous cell carcinoma (OSCC) specimens and their matched non-tumourous epithelial counterparts. OSCC is the sixth most common cancer worldwide. The modified WGCNA pipeline identified two sets of novel miRNAs associated with OSCC, in addition to the existing miRNAs reported by Shiah et al. (2014). Thus, this work will be of great interest to readers of various scientific disciplines, in particular, genetic and genomic scientists as well as medical scientists working on cancer.

In situ acetate separation in microbial electrosynthesis from CO

NARCIS (Netherlands)

Bajracharya, Suman; Burg, van den Bart; Vanbroekhoven, Karolien; Wever, De Heleen; Buisman, Cees J.N.; Pant, Deepak; Strik, David P.B.T.B.

2017-01-01

Bioelectrochemical reduction of carbon dioxide (CO₂) to multi-carbon organic compounds particularly acetate has been achieved in microbial electrosynthesis (MES) using the reducing equivalents produced at the electrically polarized cathode. MES based on CO₂ reduction

Ethylene-Related Gene Expression Networks in Wood Formation

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Carolin Seyfferth

2018-03-01

Full Text Available Thickening of tree stems is the result of secondary growth, accomplished by the meristematic activity of the vascular cambium. Secondary growth of the stem entails developmental cascades resulting in the formation of secondary phloem outwards and secondary xylem (i.e., wood inwards of the stem. Signaling and transcriptional reprogramming by the phytohormone ethylene modifies cambial growth and cell differentiation, but the molecular link between ethylene and secondary growth remains unknown. We addressed this shortcoming by analyzing expression profiles and co-expression networks of ethylene pathway genes using the AspWood transcriptome database which covers all stages of secondary growth in aspen (Populus tremula stems. ACC synthase expression suggests that the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC is synthesized during xylem expansion and xylem cell maturation. Ethylene-mediated transcriptional reprogramming occurs during all stages of secondary growth, as deduced from AspWood expression profiles of ethylene-responsive genes. A network centrality analysis of the AspWood dataset identified EIN3D and 11 ERFs as hubs. No overlap was found between the co-expressed genes of the EIN3 and ERF hubs, suggesting target diversification and hence independent roles for these transcription factor families during normal wood formation. The EIN3D hub was part of a large co-expression gene module, which contained 16 transcription factors, among them several new candidates that have not been earlier connected to wood formation and a VND-INTERACTING 2 (VNI2 homolog. We experimentally demonstrated Populus EIN3D function in ethylene signaling in Arabidopsis thaliana. The ERF hubs ERF118 and ERF119 were connected on the basis of their expression pattern and gene co-expression module composition to xylem cell expansion and secondary cell wall formation, respectively. We hereby establish data resources for ethylene-responsive genes and

Elevated atmospheric CO2 increases microbial growth rates and enzymes activity in soil

Science.gov (United States)

Blagodatskaya, Evgenia; Blagodatsky, Sergey; Dorodnikov, Maxim; Kuzyakov, Yakov

2010-05-01

Increasing the belowground translocation of assimilated carbon by plants grown under elevated CO2 can cause a shift in the structure and activity of the microbial community responsible for the turnover of organic matter in soil. We investigated the long-term effect of elevated CO2 in the atmosphere on microbial biomass and specific growth rates in root-free and rhizosphere soil. The experiments were conducted under two free air carbon dioxide enrichment (FACE) systems: in Hohenheim and Braunschweig, as well as in the intensively managed forest mesocosm of the Biosphere 2 Laboratory (B2L) in Oracle, AZ. Specific microbial growth rates (μ) were determined using the substrate-induced respiration response after glucose and/or yeast extract addition to the soil. We evaluated the effect of elevated CO2 on b-glucosidase, chitinase, phosphatase, and sulfatase to estimate the potential enzyme activity after soil amendment with glucose and nutrients. For B2L and both FACE systems, up to 58% higher μ were observed under elevated vs. ambient CO2, depending on site, plant species and N fertilization. The μ-values increased linearly with atmospheric CO2 concentration at all three sites. The effect of elevated CO2 on rhizosphere microorganisms was plant dependent and increased for: Brassica napus=Triticum aestivumyeast extract then for those growing on glucose, i.e. the effect of elevated CO2 was smoothed on rich vs. simple substrate. So, the r/K strategies ratio can be better revealed by studying growth on simple (glucose) than on rich substrate mixtures (yeast extract). After adding glucose, enzyme activities under elevated CO2 were 1.2-1.9-fold higher than under ambient CO2. This indicates the increased activity of microorganisms, which leads to accelerated C turnover in soil under elevated CO2. Our results clearly showed that the functional characteristics of the soil microbial community (i.e. specific growth rates and enzymes activity) rather than total microbial biomass

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

Species co-occurrence networks: Can they reveal trophic and non-trophic interactions in ecological communities?

Science.gov (United States)

Freilich, Mara A; Wieters, Evie; Broitman, Bernardo R; Marquet, Pablo A; Navarrete, Sergio A

2018-03-01

Co-occurrence methods are increasingly utilized in ecology to infer networks of species interactions where detailed knowledge based on empirical studies is difficult to obtain. Their use is particularly common, but not restricted to, microbial networks constructed from metagenomic analyses. In this study, we test the efficacy of this procedure by comparing an inferred network constructed using spatially intensive co-occurrence data from the rocky intertidal zone in central Chile to a well-resolved, empirically based, species interaction network from the same region. We evaluated the overlap in the information provided by each network and the extent to which there is a bias for co-occurrence data to better detect known trophic or non-trophic, positive or negative interactions. We found a poor correspondence between the co-occurrence network and the known species interactions with overall sensitivity (probability of true link detection) equal to 0.469, and specificity (true non-interaction) equal to 0.527. The ability to detect interactions varied with interaction type. Positive non-trophic interactions such as commensalism and facilitation were detected at the highest rates. These results demonstrate that co-occurrence networks do not represent classical ecological networks in which interactions are defined by direct observations or experimental manipulations. Co-occurrence networks provide information about the joint spatial effects of environmental conditions, recruitment, and, to some extent, biotic interactions, and among the latter, they tend to better detect niche-expanding positive non-trophic interactions. Detection of links (sensitivity or specificity) was not higher for well-known intertidal keystone species than for the rest of consumers in the community. Thus, as observed in previous empirical and theoretical studies, patterns of interactions in co-occurrence networks must be interpreted with caution, especially when extending interaction

VSNL1 Co-expression networks in aging include calcium signaling, synaptic plasticity, and Alzheimer’s disease pathways

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C W Lin

2015-03-01

Full Text Available The Visinin-like 1 (VSNL1 gene encodes Visinin-like protein 1, a peripheral biomarker for Alzheimer disease (AD. Little is known, however, about normal VSNL1 expression in brain and the biologic networks in which it participates. Frontal cortex gray matter from 209 subjects without neurodegenerative or psychiatric illness, ranging in age from 16–91, were processed on Affymetrix GeneChip 1.1 ST and Human SNP Array 6.0. VSNL1 expression was unaffected by age and sex, and not significantly associated with SNPs in cis or trans. VSNL1 was significantly co-expressed with genes in pathways for Calcium Signaling, AD, Long Term Potentiation, Long Term Depression, and Trafficking of AMPA Receptors. The association with AD was driven, in part, by correlation with amyloid precursor protein (APP expression. These findings provide an unbiased link between VSNL1 and molecular mechanisms of AD, including pathways implicated in synaptic pathology in AD. Whether APP may drive increased VSNL1 expression, VSNL1 drives increased APP expression, or both are downstream of common pathogenic regulators will need to be evaluated in model systems.

Construction and evaluation of yeast expression networks by database-guided predictions

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Katharina Papsdorf

2016-05-01

Full Text Available DNA-Microarrays are powerful tools to obtain expression data on the genome-wide scale. We performed microarray experiments to elucidate the transcriptional networks, which are up- or down-regulated in response to the expression of toxic polyglutamine proteins in yeast. Such experiments initially generate hit lists containing differentially expressed genes. To look into transcriptional responses, we constructed networks from these genes. We therefore developed an algorithm, which is capable of dealing with very small numbers of microarrays by clustering the hits based on co-regulatory relationships obtained from the SPELL database. Here, we evaluate this algorithm according to several criteria and further develop its statistical capabilities. Initially, we define how the number of SPELL-derived co-regulated genes and the number of input hits influences the quality of the networks. We then show the ability of our networks to accurately predict further differentially expressed genes. Including these predicted genes into the networks improves the network quality and allows quantifying the predictive strength of the networks based on a newly implemented scoring method. We find that this approach is useful for our own experimental data sets and also for many other data sets which we tested from the SPELL microarray database. Furthermore, the clusters obtained by the described algorithm greatly improve the assignment to biological processes and transcription factors for the individual clusters. Thus, the described clustering approach, which will be available through the ClusterEx web interface, and the evaluation parameters derived from it represent valuable tools for the fast and informative analysis of yeast microarray data.

Statistics of the uplink co-tier interference in closed access heterogeneous networks

KAUST Repository

Tabassum, Hina

2013-09-01

In this paper, we derive a statistical model of the co-tier interference in closed access two tier heterogeneous wireless cellular networks with femtocell deployments. The derived model captures the impact of bounded path loss model, wall penetration loss, user distributions, random locations, and density of the femtocells. Firstly, we derive the analytical expressions for the probability density function (PDF) and moment generating function (MGF) of the co-tier interference considering a single femtocell interferer by exploiting the random disc line picking theory from geometric probability. We then derive the MGF of the cumulative interference from all femtocell interferers considering full spectral reuse in each femtocell. Orthogonal spectrum partitioning is assumed between the macrocell and femtocell networks to avoid any cross-tier interference. Finally, the accuracy of the derived expressions is validated through Monte-Carlo simulations and the expressions are shown to be useful in quantifying important network performance metrics such as ergodic capacity. © 2013 IEEE.

ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

Science.gov (United States)

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

Analysis of co-occurrence toponyms in web pages based on complex networks

Science.gov (United States)

Zhong, Xiang; Liu, Jiajun; Gao, Yong; Wu, Lun

2017-01-01

A large number of geographical toponyms exist in web pages and other documents, providing abundant geographical resources for GIS. It is very common for toponyms to co-occur in the same documents. To investigate these relations associated with geographic entities, a novel complex network model for co-occurrence toponyms is proposed. Then, 12 toponym co-occurrence networks are constructed from the toponym sets extracted from the People's Daily Paper documents of 2010. It is found that two toponyms have a high co-occurrence probability if they are at the same administrative level or if they possess a part-whole relationship. By applying complex network analysis methods to toponym co-occurrence networks, we find the following characteristics. (1) The navigation vertices of the co-occurrence networks can be found by degree centrality analysis. (2) The networks express strong cluster characteristics, and it takes only several steps to reach one vertex from another one, implying that the networks are small-world graphs. (3) The degree distribution satisfies the power law with an exponent of 1.7, so the networks are free-scale. (4) The networks are disassortative and have similar assortative modes, with assortative exponents of approximately 0.18 and assortative indexes less than 0. (5) The frequency of toponym co-occurrence is weakly negatively correlated with geographic distance, but more strongly negatively correlated with administrative hierarchical distance. Considering the toponym frequencies and co-occurrence relationships, a novel method based on link analysis is presented to extract the core toponyms from web pages. This method is suitable and effective for geographical information retrieval.

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

Science.gov (United States)

Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structure, Variation, and Co-occurrence of Soil Microbial Communities in Abandoned Sites of a Rare Earth Elements Mine.

Science.gov (United States)

Chao, Yuanqing; Liu, Wenshen; Chen, Yanmei; Chen, Wenhui; Zhao, Lihua; Ding, Qiaobei; Wang, Shizhong; Tang, Ye-Tao; Zhang, Tong; Qiu, Rong-Liang

2016-11-01

Mining activity for rare earth elements (REEs) has caused serious environmental pollution, particularly for soil ecosystems. However, the effects of REEs on soil microbiota are still poorly understood. In this study, soils were collected from abandoned sites of a REEs mine, and the structure, diversity, and co-occurrence patterns of soil microbiota were evaluated by Illumina high-throughput sequencing targeting 16S rRNA genes. Although microbiota developed significantly along with the natural restoration, the microbial structure on the site abandoned for 10 years still significantly differed from that on the unmined site. Potential plant growth promoting bacteria (PGPB) were identified by comparing 16S sequences against a self-constructed PGPB database via BLAST, and it was found that siderophore-producing and phosphorus-solubilizing bacteria were more abundant in the studied soils than in reference soils. Canonical correspondence analysis indicated that species richness of plant community was the prime factor affecting microbial structure, followed by limiting nutrients (total carbon and total nitrogen) and REEs content. Further co-occurring network analysis revealed nonrandom assembly patterns of microbiota in the studied soils. These results increase our understanding of microbial variation and assembly pattern during natural restoration in REE contaminated soils.

Inferring the transcriptional landscape of bovine skeletal muscle by integrating co-expression networks.

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Nicholas J Hudson

Full Text Available BACKGROUND: Despite modern technologies and novel computational approaches, decoding causal transcriptional regulation remains challenging. This is particularly true for less well studied organisms and when only gene expression data is available. In muscle a small number of well characterised transcription factors are proposed to regulate development. Therefore, muscle appears to be a tractable system for proposing new computational approaches. METHODOLOGY/PRINCIPAL FINDINGS: Here we report a simple algorithm that asks "which transcriptional regulator has the highest average absolute co-expression correlation to the genes in a co-expression module?" It correctly infers a number of known causal regulators of fundamental biological processes, including cell cycle activity (E2F1, glycolysis (HLF, mitochondrial transcription (TFB2M, adipogenesis (PIAS1, neuronal development (TLX3, immune function (IRF1 and vasculogenesis (SOX17, within a skeletal muscle context. However, none of the canonical pro-myogenic transcription factors (MYOD1, MYOG, MYF5, MYF6 and MEF2C were linked to muscle structural gene expression modules. Co-expression values were computed using developing bovine muscle from 60 days post conception (early foetal to 30 months post natal (adulthood for two breeds of cattle, in addition to a nutritional comparison with a third breed. A number of transcriptional landscapes were constructed and integrated into an always correlated landscape. One notable feature was a 'metabolic axis' formed from glycolysis genes at one end, nuclear-encoded mitochondrial protein genes at the other, and centrally tethered by mitochondrially-encoded mitochondrial protein genes. CONCLUSIONS/SIGNIFICANCE: The new module-to-regulator algorithm complements our recently described Regulatory Impact Factor analysis. Together with a simple examination of a co-expression module's contents, these three gene expression approaches are starting to illuminate the in vivo

A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes.

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Simone de Jong

Full Text Available Despite large-scale genome-wide association studies (GWAS, the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1, is located in, and regulated by the major histocompatibility (MHC complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network.

Mapping the ecological networks of microbial communities.

Science.gov (United States)

Xiao, Yandong; Angulo, Marco Tulio; Friedman, Jonathan; Waldor, Matthew K; Weiss, Scott T; Liu, Yang-Yu

2017-12-11

Mapping the ecological networks of microbial communities is a necessary step toward understanding their assembly rules and predicting their temporal behavior. However, existing methods require assuming a particular population dynamics model, which is not known a priori. Moreover, those methods require fitting longitudinal abundance data, which are often not informative enough for reliable inference. To overcome these limitations, here we develop a new method based on steady-state abundance data. Our method can infer the network topology and inter-taxa interaction types without assuming any particular population dynamics model. Additionally, when the population dynamics is assumed to follow the classic Generalized Lotka-Volterra model, our method can infer the inter-taxa interaction strengths and intrinsic growth rates. We systematically validate our method using simulated data, and then apply it to four experimental data sets. Our method represents a key step towards reliable modeling of complex, real-world microbial communities, such as the human gut microbiota.

Microbial network for waste activated sludge cascade utilization in an integrated system of microbial electrolysis and anaerobic fermentation

DEFF Research Database (Denmark)

Liu, Wenzong; He, Zhangwei; Yang, Chunxue

2016-01-01

in an integrated system of microbial electrolysis cell (MEC) and anaerobic digestion (AD) for waste activated sludge (WAS). Microbial communities in integrated system would build a thorough energetic and metabolic interaction network regarding fermentation communities and electrode respiring communities...... to Firmicutes (Acetoanaerobium, Acetobacterium, and Fusibacter) showed synergistic relationship with exoelectrogensin the degradation of complex organic matter or recycling of MEC products (H2). High protein and polysaccharide but low fatty acid content led to the dominance of Proteiniclasticum...... biofilm. The overall performance of WAS cascade utilization was substantially related to the microbial community structures, which in turn depended on the initial pretreatment to enhance WAS fermentation. It is worth noting that species in AD and MEC communities are able to build complex networks...

Improving Griffith's protocol for co-extraction of microbial DNA and RNA in adsorptive soils

DEFF Research Database (Denmark)

Paulin, Mélanie Marie; Nicolaisen, Mette Haubjerg; Jacobsen, Carsten Suhr

2013-01-01

Quantification of microbial gene expression is increasingly being used to study key functions in soil microbial communities, yet major limitations still exist for efficient extraction of nucleic acids, especially RNA for transcript analysis, from this complex matrix. We present an improved......-time PCR on both the RNA (after conversion to cDNA) and the DNA fraction of the extracts. Non-adsorptive soils were characterized by low clay content and/or high phosphate content, whereas adsorptive soils had clay contents above 20% and/or a strong presence of divalent Ca in combination with high p......H. Modifications to the co-extraction protocol improved nucleic acid extraction efficiency from all adsorptive soils and were successfully validated by DGGE analysis of the indigenous community based on 16S rRNA gene and transcripts in soils representing low biomass and/or high clay content. This new approach...

In silico identification of miRNAs and their target genes and analysis of gene co-expression network in saffron (Crocus sativus L.) stigma

Science.gov (United States)

Zinati, Zahra; Shamloo-Dashtpagerdi, Roohollah; Behpouri, Ali

2016-01-01

As an aromatic and colorful plant of substantive taste, saffron (Crocus sativus L.) owes such properties of matter to growing class of the secondary metabolites derived from the carotenoids, apocarotenoids. Regarding the critical role of microRNAs in secondary metabolic synthesis and the limited number of identified miRNAs in C. sativus, on the other hand, one may see the point how the characterization of miRNAs along with the corresponding target genes in C. sativus might expand our perspectives on the roles of miRNAs in carotenoid/apocarotenoid biosynthetic pathway. A computational analysis was used to identify miRNAs and their targets using EST (Expressed Sequence Tag) library from mature saffron stigmas. Then, a gene co- expression network was constructed to identify genes which are potentially involved in carotenoid/apocarotenoid biosynthetic pathways. EST analysis led to the identification of two putative miRNAs (miR414 and miR837-5p) along with the corresponding stem- looped precursors. To our knowledge, this is the first report on miR414 and miR837-5p in C. sativus. Co-expression network analysis indicated that miR414 and miR837-5p may play roles in C. sativus metabolic pathways and led to identification of candidate genes including six transcription factors and one protein kinase probably involved in carotenoid/apocarotenoid biosynthetic pathway. Presence of transcription factors, miRNAs and protein kinase in the network indicated multiple layers of regulation in saffron stigma. The candidate genes from this study may help unraveling regulatory networks underlying the carotenoid/apocarotenoid biosynthesis in saffron and designing metabolic engineering for enhanced secondary metabolites. PMID:28261627

Comprehensive analysis of coding-lncRNA gene co-expression network uncovers conserved functional lncRNAs in zebrafish.

Science.gov (United States)

Chen, Wen; Zhang, Xuan; Li, Jing; Huang, Shulan; Xiang, Shuanglin; Hu, Xiang; Liu, Changning

2018-05-09

Zebrafish is a full-developed model system for studying development processes and human disease. Recent studies of deep sequencing had discovered a large number of long non-coding RNAs (lncRNAs) in zebrafish. However, only few of them had been functionally characterized. Therefore, how to take advantage of the mature zebrafish system to deeply investigate the lncRNAs' function and conservation is really intriguing. We systematically collected and analyzed a series of zebrafish RNA-seq data, then combined them with resources from known database and literatures. As a result, we obtained by far the most complete dataset of zebrafish lncRNAs, containing 13,604 lncRNA genes (21,128 transcripts) in total. Based on that, a co-expression network upon zebrafish coding and lncRNA genes was constructed and analyzed, and used to predict the Gene Ontology (GO) and the KEGG annotation of lncRNA. Meanwhile, we made a conservation analysis on zebrafish lncRNA, identifying 1828 conserved zebrafish lncRNA genes (1890 transcripts) that have their putative mammalian orthologs. We also found that zebrafish lncRNAs play important roles in regulation of the development and function of nervous system; these conserved lncRNAs present a significant sequential and functional conservation, with their mammalian counterparts. By integrative data analysis and construction of coding-lncRNA gene co-expression network, we gained the most comprehensive dataset of zebrafish lncRNAs up to present, as well as their systematic annotations and comprehensive analyses on function and conservation. Our study provides a reliable zebrafish-based platform to deeply explore lncRNA function and mechanism, as well as the lncRNA commonality between zebrafish and human.

Co-regulation of metabolic genes is better explained by flux coupling than by network distance.

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Richard A Notebaart

2008-01-01

Full Text Available To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools.

Microbial network of the carbonate precipitation process induced by microbial consortia and the potential application to crack healing in concrete.

Science.gov (United States)

Zhang, Jiaguang; Zhou, Aijuan; Liu, Yuanzhen; Zhao, Bowei; Luan, Yunbo; Wang, Sufang; Yue, Xiuping; Li, Zhu

2017-11-06

Current studies have employed various pure-cultures for improving concrete durability based on microbially induced carbonate precipitation (MICP). However, there have been very few reports concerned with microbial consortia, which could perform more complex tasks and be more robust in their resistance to environmental fluctuations. In this study, we constructed three microbial consortia that are capable of MICP under aerobic (AE), anaerobic (AN) and facultative anaerobic (FA) conditions. The results showed that AE consortia showed more positive effects on inorganic carbon conversion than AN and FA consortia. Pyrosequencing analysis showed that clear distinctions appeared in the community structure between different microbial consortia systems. Further investigation on microbial community networks revealed that the species in the three microbial consortia built thorough energetic and metabolic interaction networks regarding MICP, nitrate-reduction, bacterial endospores and fermentation communities. Crack-healing experiments showed that the selected cracks of the three consortia-based concrete specimens were almost completely healed in 28 days, which was consistent with the studies using pure cultures. Although the economic advantage might not be clear yet, this study highlights the potential implementation of microbial consortia on crack healing in concrete.

Functional response of a near-surface soil microbial community to a simulated underground CO2 storage leak.

Science.gov (United States)

Morales, Sergio E; Holben, William E

2013-01-01

Understanding the impacts of leaks from geologic carbon sequestration, also known as carbon capture and storage, is key to developing effective strategies for carbon dioxide (CO2) emissions management and mitigation of potential negative effects. Here, we provide the first report on the potential effects of leaks from carbon capture and storage sites on microbial functional groups in surface and near-surface soils. Using a simulated subsurface CO2 storage leak scenario, we demonstrate how CO2 flow upward through the soil column altered both the abundance (DNA) and activity (mRNA) of microbial functional groups mediating carbon and nitrogen transformations. These microbial responses were found to be seasonally dependent and correlated to shifts in atmospheric conditions. While both DNA and mRNA levels were affected by elevated CO2, they did not react equally, suggesting two separate mechanisms for soil microbial community response to high CO2 levels. The results did not always agree with previous studies on elevated atmospheric (rather than subsurface) CO2 using FACE (Free-Air CO2 Enrichment) systems, suggesting that microbial community response to CO2 seepage from the subsurface might differ from its response to atmospheric CO2 increases.

Impact of CO₂ on the Evolution of Microbial Communities Exposed to Carbon Storage Conditions, Enhanced Oil Recovery, and CO₂ Leakage

Energy Technology Data Exchange (ETDEWEB)

Gulliver, Djuna M. [National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States); Gregory, Kelvin B. [Carnegie Mellon Univ., Pittsburgh, PA (United States). Dept. of Civil and Environmental Engineering; Lowry, Gregory V. [Carnegie Mellon Univ., Pittsburgh, PA (United States). Dept. of Civil and Environmental Engineering

2016-06-20

Geologic carbon storage (GCS) is a crucial part of a proposed mitigation strategy to reduce the anthropogenic carbon dioxide (CO₂) emissions to the atmosphere. During this process, CO₂ is injected as super critical carbon dioxide (SC-CO₂) in confined deep subsurface storage units, such as saline aquifers and depleted oil reservoirs. The deposition of vast amounts of CO₂ in subsurface geologic formations could unintentionally lead to CO₂ leakage into overlying freshwater aquifers. Introduction of CO₂ into these subsurface environments will greatly increase the CO₂ concentration and will create CO₂ concentration gradients that drive changes in the microbial communities present. While it is expected that altered microbial communities will impact the biogeochemistry of the subsurface, there is no information available on how CO₂ gradients will impact these communities. The overarching goal of this project is to understand how CO₂ exposure will impact subsurface microbial communities at temperatures and pressures that are relevant to GCS and CO₂ leakage scenarios. To meet this goal, unfiltered, aqueous samples from a deep saline aquifer, a depleted oil reservoir, and a fresh water aquifer were exposed to varied concentrations of CO₂ at reservoir pressure and temperature. The microbial ecology of the samples was examined using molecular, DNA-based techniques. The results from these studies were also compared across the sites to determine any existing trends. Results reveal that increasing CO₂ leads to decreased DNA concentrations regardless of the site, suggesting that microbial processes will be significantly hindered or absent nearest the CO₂ injection/leakage plume where CO₂ concentrations are highest. At CO₂ exposures expected downgradient from the CO₂ plume, selected microorganisms

Impact of CO₂ on the Evolution of Microbial Communities Exposed to Carbon Storage Conditions, Enhanced Oil Recovery, and CO₂ Leakage

Energy Technology Data Exchange (ETDEWEB)

Gulliver, Djuna [National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States); Gregory, Kelvin B. [Carnegie Mellon Univ., Pittsburgh, PA (United States); Lowry, Gregorgy V. [Carnegie Mellon Univ., Pittsburgh, PA (United States)

2016-06-20

Geologic carbon storage (GCS) is a crucial part of a proposed mitigation strategy to reduce the anthropogenic carbon dioxide (CO₂) emissions to the atmosphere. During this process, CO₂ is injected as super critical carbon dioxide (SC-CO₂) in confined deep subsurface storage units, such as saline aquifers and depleted oil reservoirs. The deposition of vast amounts of CO₂ in subsurface geologic formations could unintentionally lead to CO₂ leakage into overlying freshwater aquifers. Introduction of CO₂ into these subsurface environments will greatly increase the CO₂2 concentration and will create CO₂ concentration gradients that drive changes in the microbial communities present. While it is expected that altered microbial communities will impact the biogeochemistry of the subsurface, there is no information available on how CO₂ gradients will impact these communities. The overarching goal of this project is to understand how CO₂ exposure will impact subsurface microbial communities at temperatures and pressures that are relevant to GCS and CO₂ leakage scenarios. To meet this goal, unfiltered, aqueous samples from a deep saline aquifer, a depleted oil reservoir, and a fresh water aquifer were exposed to varied concentrations of CO₂ at reservoir pressure and temperature. The microbial ecology of the samples was examined using molecular, DNA-based techniques. The results from these studies were also compared across the sites to determine any existing trends. Results reveal that increasing CO₂ leads to decreased DNA concentrations regardless of the site, suggesting that microbial processes will be significantly hindered or absent nearest the CO₂ injection/leakage plume where CO₂ concentrations are highest. At CO₂ exposures expected downgradient from the CO₂ plume, selected microorganisms

Weighted Gene Co-expression Network Analysis of the Dioscin Rich Medicinal Plant Dioscorea nipponica

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Wei Sun

2017-06-01

Full Text Available Dioscorea contains critically important species which can be used as staple foods or sources of bioactive substances, including Dioscorea nipponica, which has been used to develop highly successful drugs to treat cardiovascular disease. Its major active ingredients are thought to be sterol compounds such as diosgenin, which has been called “medicinal gold” because of its valuable properties. However, reliance on naturally growing plants as a production system limits the potential use of D. nipponica, raising interest in engineering metabolic pathways to enhance the production of secondary metabolites. However, the biosynthetic pathway of diosgenin is still poorly understood, and D. nipponica is poorly characterized at a molecular level, hindering in-depth investigation. In the present work, the RNAs from five organs and seven methyl jasmonate treated D. nipponica rhizomes were sequenced using the Illumina high-throughput sequencing platform, yielding 52 gigabases of data, which were pooled and assembled into a reference transcriptome. Four hundred and eighty two genes were found to be highly expressed in the rhizomes, and these genes are mainly involved in stress response and transcriptional regulation. Based on their expression patterns, 36 genes were selected for further investigation as candidate genes involved in dioscin biosynthesis. Constructing co-expression networks based on significant changes in gene expression revealed 15 gene modules. Of these, four modules with properties correlating to dioscin regulation and biosynthesis, consisting of 4,665 genes in total, were selected for further functional investigation. These results improve our understanding of dioscin biosynthesis in this important medicinal plant and will help guide more intensive investigations.

Weighted gene co-expression network analysis reveals potential genes involved in early metamorphosis process in sea cucumber Apostichopus japonicus.

Science.gov (United States)

Li, Yongxin; Kikuchi, Mani; Li, Xueyan; Gao, Qionghua; Xiong, Zijun; Ren, Yandong; Zhao, Ruoping; Mao, Bingyu; Kondo, Mariko; Irie, Naoki; Wang, Wen

2018-01-01

Sea cucumbers, one main class of Echinoderms, have a very fast and drastic metamorphosis process during their development. However, the molecular basis under this process remains largely unknown. Here we systematically examined the gene expression profiles of Japanese common sea cucumber (Apostichopus japonicus) for the first time by RNA sequencing across 16 developmental time points from fertilized egg to juvenile stage. Based on the weighted gene co-expression network analysis (WGCNA), we identified 21 modules. Among them, MEdarkmagenta was highly expressed and correlated with the early metamorphosis process from late auricularia to doliolaria larva. Furthermore, gene enrichment and differentially expressed gene analysis identified several genes in the module that may play key roles in the metamorphosis process. Our results not only provide a molecular basis for experimentally studying the development and morphological complexity of sea cucumber, but also lay a foundation for improving its emergence rate. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of gene co-networks reveals the molecular mechanisms of the rice (Oryza sativa L.) response to Rhizoctonia solani AG1 IA infection.

Science.gov (United States)

Zhang, Jinfeng; Zhao, Wenjuan; Fu, Rong; Fu, Chenglin; Wang, Lingxia; Liu, Huainian; Li, Shuangcheng; Deng, Qiming; Wang, Shiquan; Zhu, Jun; Liang, Yueyang; Li, Ping; Zheng, Aiping

2018-05-05

Rhizoctonia solani causes rice sheath blight, an important disease affecting the growth of rice (Oryza sativa L.). Attempts to control the disease have met with little success. Based on transcriptional profiling, we previously identified more than 11,947 common differentially expressed genes (TPM > 10) between the rice genotypes TeQing and Lemont. In the current study, we extended these findings by focusing on an analysis of gene co-expression in response to R. solani AG1 IA and identified gene modules within the networks through weighted gene co-expression network analysis (WGCNA). We compared the different genes assigned to each module and the biological interpretations of gene co-expression networks at early and later modules in the two rice genotypes to reveal differential responses to AG1 IA. Our results show that different changes occurred in the two rice genotypes and that the modules in the two groups contain a number of candidate genes possibly involved in pathogenesis, such as the VQ protein. Furthermore, these gene co-expression networks provide comprehensive transcriptional information regarding gene expression in rice in response to AG1 IA. The co-expression networks derived from our data offer ideas for follow-up experimentation that will help advance our understanding of the translational regulation of rice gene expression changes in response to AG1 IA.

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

Science.gov (United States)

Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

2017-11-13

The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly

Interactive network configuration maintains bacterioplankton community structure under elevated CO2 in a eutrophic coastal mesocosm experiment

Science.gov (United States)

Lin, Xin; Huang, Ruiping; Li, Yan; Li, Futian; Wu, Yaping; Hutchins, David A.; Dai, Minhan; Gao, Kunshan

2018-01-01

There is increasing concern about the effects of ocean acidification on marine biogeochemical and ecological processes and the organisms that drive them, including marine bacteria. Here, we examine the effects of elevated CO2 on the bacterioplankton community during a mesocosm experiment using an artificial phytoplankton community in subtropical, eutrophic coastal waters of Xiamen, southern China. Through sequencing the bacterial 16S rRNA gene V3-V4 region, we found that the bacterioplankton community in this high-nutrient coastal environment was relatively resilient to changes in seawater carbonate chemistry. Based on comparative ecological network analysis, we found that elevated CO2 hardly altered the network structure of high-abundance bacterioplankton taxa but appeared to reassemble the community network of low abundance taxa. This led to relatively high resilience of the whole bacterioplankton community to the elevated CO2 level and associated chemical changes. We also observed that the Flavobacteria group, which plays an important role in the microbial carbon pump, showed higher relative abundance under the elevated CO2 condition during the early stage of the phytoplankton bloom in the mesocosms. Our results provide new insights into how elevated CO2 may influence bacterioplankton community structure.

Facilitating value co-creation in networks

DEFF Research Database (Denmark)

Rasmussen, Mette Apollo

participants in varied ways come to grasp the meaning of networking. The dissertation draws on insights from the Service-Dominant (S-D) Logic to explain how networks can be seen as spheres for value co-creation. Co-creation as a theoretical construct has evolved from varied streams of service marketing...... of networking. The concept of “imaginative value” (Beckert, 2011) is used to explain the oscillating behaviors observed in the two networks. Imaginative value can be defined as symbolic value that actors ascribe to an object, in this case the network. I argue that the group practices in the networks led......The dissertation investigates through two ethnographic case studies how value co-creation takes place in inter-organizational networks that have been facilitated by a municipality. The contribution of the study to business network research is the emphasis on development phases of networks...

Monitoring of the microbial community composition of the saline aquifers during CO2 storage by fluorescence in situ hybridisation

OpenAIRE

Daria Morozova; M. Wandrey; Mashal Alawi; Martin Zimmer; Andrea Vieth-Hillebrand [Vieth; M. Zettlitzer; Hilke Würdemann

2010-01-01

This study reveals the first analyses of the composition and activity of the microbial community of a saline CO2 storage aquifer. Microbial monitoring during CO2 injection has been reported. By using fluorescence in situ hybridisation (FISH), we have shown that the microbial community was strongly influenced by the CO2 injection. Before CO2 arrival, up to 6 × 106 cells ml−1 were detected by DAPI staining at a depth of 647 m below the surface. The microbial community was dominated by the dom...

Detection of stable community structures within gut microbiota co-occurrence networks from different human populations.

Science.gov (United States)

Jackson, Matthew A; Bonder, Marc Jan; Kuncheva, Zhana; Zierer, Jonas; Fu, Jingyuan; Kurilshikov, Alexander; Wijmenga, Cisca; Zhernakova, Alexandra; Bell, Jordana T; Spector, Tim D; Steves, Claire J

2018-01-01

Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses.

[Progress in expression and molecular modification of microbial transglutaminase].

Science.gov (United States)

Liu, Song; Zhang, Dongxu; Du, Guocheng; Chen, Jian

2011-12-01

Microbial transglutaminase, which could catalyze the cross-linking of many proteins or non-protein materials, has been widely used in food, pharmaceutical and textile industry. To enhance the yield of the enzyme and establish corresponding platform for molecular modification, the researchers of Japanese Ajinomoto began to construct the recombinant strain producing transglutaminase in the 1990s. So far, the enzyme has been successfully expressed in different expression systems. Some of the recombinant strains are more productive than wild strains. Recently, progress has been made in the molecular modification of microbial transglutaminase, and the activity, thermo-stability and specificity of the enzyme are improved. This review briefly summarized and analyzed the strategies involved in these studies, and noted its trends.

Divergent Responses of Forest Soil Microbial Communities under Elevated CO2 in Different Depths of Upper Soil Layers.

Science.gov (United States)

Yu, Hao; He, Zhili; Wang, Aijie; Xie, Jianping; Wu, Liyou; Van Nostrand, Joy D; Jin, Decai; Shao, Zhimin; Schadt, Christopher W; Zhou, Jizhong; Deng, Ye

2018-01-01

Numerous studies have shown that the continuous increase of atmosphere CO 2 concentrations may have profound effects on the forest ecosystem and its functions. However, little is known about the response of belowground soil microbial communities under elevated atmospheric CO 2 (eCO 2 ) at different soil depth profiles in forest ecosystems. Here, we examined soil microbial communities at two soil depths (0 to 5 cm and 5 to 15 cm) after a 10-year eCO 2 exposure using a high-throughput functional gene microarray (GeoChip). The results showed that eCO 2 significantly shifted the compositions, including phylogenetic and functional gene structures, of soil microbial communities at both soil depths. Key functional genes, including those involved in carbon degradation and fixation, methane metabolism, denitrification, ammonification, and nitrogen fixation, were stimulated under eCO 2 at both soil depths, although the stimulation effect of eCO 2 on these functional markers was greater at the soil depth of 0 to 5 cm than of 5 to 15 cm. Moreover, a canonical correspondence analysis suggested that NO 3 -N, total nitrogen (TN), total carbon (TC), and leaf litter were significantly correlated with the composition of the whole microbial community. This study revealed a positive feedback of eCO 2 in forest soil microbial communities, which may provide new insight for a further understanding of forest ecosystem responses to global CO 2 increases. IMPORTANCE The concentration of atmospheric carbon dioxide (CO 2 ) has continuously been increasing since the industrial revolution. Understanding the response of soil microbial communities to elevated atmospheric CO 2 (eCO 2 ) is important for predicting the contribution of the forest ecosystem to global atmospheric change. This study analyzed the effect of eCO 2 on microbial communities at two soil depths (0 to 5 cm and 5 to 15 cm) in a forest ecosystem. Our findings suggest that the compositional and functional structures of microbial

Electricity generation from synthesis gas by microbial processes: CO fermentation and microbial fuel cell technology.

Science.gov (United States)

Kim, Daehee; Chang, In Seop

2009-10-01

A microbiological process was established to harvest electricity from the carbon monoxide (CO). A CO fermenter was enriched with CO as the sole carbon source. The DGGE/DNA sequencing results showed that Acetobacterium spp. were enriched from the anaerobic digester fluid. After the fermenter was operated under continuous mode, the products were then continuously fed to the microbial fuel cell (MFC) to generate electricity. Even though the conversion yield was quite low, this study proved that synthesis gas (syn-gas) can be converted to electricity with the aid of microbes that do not possess the drawbacks of metal catalysts of conventional methods.

Geochemical Influence on Microbial Communities at CO2-Leakage Analog Sites.

Science.gov (United States)

Ham, Baknoon; Choi, Byoung-Young; Chae, Gi-Tak; Kirk, Matthew F; Kwon, Man Jae

2017-01-01

Microorganisms influence the chemical and physical properties of subsurface environments and thus represent an important control on the fate and environmental impact of CO 2 that leaks into aquifers from deep storage reservoirs. How leakage will influence microbial populations over long time scales is largely unknown. This study uses natural analog sites to investigate the long-term impact of CO 2 leakage from underground storage sites on subsurface biogeochemistry. We considered two sites with elevated CO 2 levels (sample groups I and II) and one control site with low CO 2 content (group III). Samples from sites with elevated CO 2 had pH ranging from 6.2 to 4.5 and samples from the low-CO 2 control group had pH ranging from 7.3 to 6.2. Solute concentrations were relatively low for samples from the control group and group I but high for samples from group II, reflecting varying degrees of water-rock interaction. Microbial communities were analyzed through clone library and MiSeq sequencing. Each 16S rRNA analysis identified various bacteria, methane-producing archaea, and ammonia-oxidizing archaea. Both bacterial and archaeal diversities were low in groundwater with high CO 2 content and community compositions between the groups were also clearly different. In group II samples, sequences classified in groups capable of methanogenesis, metal reduction, and nitrate reduction had higher relative abundance in samples with relative high methane, iron, and manganese concentrations and low nitrate levels. Sequences close to Comamonadaceae were abundant in group I, while the taxa related to methanogens, Nitrospirae , and Anaerolineaceae were predominant in group II. Our findings provide insight into subsurface biogeochemical reactions that influence the carbon budget of the system including carbon fixation, carbon trapping, and CO 2 conversion to methane. The results also suggest that monitoring groundwater microbial community can be a potential tool for tracking CO 2

Geochemical Influence on Microbial Communities at CO2-Leakage Analog Sites

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Baknoon Ham

2017-11-01

Full Text Available Microorganisms influence the chemical and physical properties of subsurface environments and thus represent an important control on the fate and environmental impact of CO2 that leaks into aquifers from deep storage reservoirs. How leakage will influence microbial populations over long time scales is largely unknown. This study uses natural analog sites to investigate the long-term impact of CO2 leakage from underground storage sites on subsurface biogeochemistry. We considered two sites with elevated CO2 levels (sample groups I and II and one control site with low CO2 content (group III. Samples from sites with elevated CO2 had pH ranging from 6.2 to 4.5 and samples from the low-CO2 control group had pH ranging from 7.3 to 6.2. Solute concentrations were relatively low for samples from the control group and group I but high for samples from group II, reflecting varying degrees of water-rock interaction. Microbial communities were analyzed through clone library and MiSeq sequencing. Each 16S rRNA analysis identified various bacteria, methane-producing archaea, and ammonia-oxidizing archaea. Both bacterial and archaeal diversities were low in groundwater with high CO2 content and community compositions between the groups were also clearly different. In group II samples, sequences classified in groups capable of methanogenesis, metal reduction, and nitrate reduction had higher relative abundance in samples with relative high methane, iron, and manganese concentrations and low nitrate levels. Sequences close to Comamonadaceae were abundant in group I, while the taxa related to methanogens, Nitrospirae, and Anaerolineaceae were predominant in group II. Our findings provide insight into subsurface biogeochemical reactions that influence the carbon budget of the system including carbon fixation, carbon trapping, and CO2 conversion to methane. The results also suggest that monitoring groundwater microbial community can be a potential tool for tracking

Microbial electrolytic capture, separation and regeneration of CO2 for biogas upgrading

DEFF Research Database (Denmark)

Jin, Xiangdan; Zhang, Yifeng; Li, Xiaohu

2017-01-01

challenges. In this study, an innovative microbial electrolytic system was developed to capture, separate and regenerate CO2 for biogas upgrading without external supply of chemicals, and potentially to treat wastewater. The new system was operated at varied biogas flow rates and external applied voltages....... CO2 was effectively separated from the raw biogas and the CH4 content in the outlet reached as high as 97.0±0.2% at the external voltage of 1.2 V and gas flow rate of 19.6 mL/h. Regeneration of CO2 was also achieved in the regeneration chamber with low pH (1.34±0.04). The relatively low electric...... and potentially expands the application of microbial electrochemical technologies....

Novel co-culture plate enables growth dynamic-based assessment of contact-independent microbial interactions.

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Thomas J Moutinho

Full Text Available Interactions between microbes are central to the dynamics of microbial communities. Understanding these interactions is essential for the characterization of communities, yet challenging to accomplish in practice. There are limited available tools for characterizing diffusion-mediated, contact-independent microbial interactions. A practical and widely implemented technique in such characterization involves the simultaneous co-culture of distinct bacterial species and subsequent analysis of relative abundance in the total population. However, distinguishing between species can be logistically challenging. In this paper, we present a low-cost, vertical membrane, co-culture plate to quantify contact-independent interactions between distinct bacterial populations in co-culture via real-time optical density measurements. These measurements can be used to facilitate the analysis of the interaction between microbes that are physically separated by a semipermeable membrane yet able to exchange diffusible molecules. We show that diffusion across the membrane occurs at a sufficient rate to enable effective interaction between physically separate cultures. Two bacterial species commonly found in the cystic fibrotic lung, Pseudomonas aeruginosa and Burkholderia cenocepacia, were co-cultured to demonstrate how this plate may be implemented to study microbial interactions. We have demonstrated that this novel co-culture device is able to reliably generate real-time measurements of optical density data that can be used to characterize interactions between microbial species.

Large-scale analysis of Arabidopsis transcription reveals a basal co-regulation network

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Chamovitz Daniel A

2009-09-01

Full Text Available Abstract Background Analyses of gene expression data from microarray experiments has become a central tool for identifying co-regulated, functional gene modules. A crucial aspect of such analysis is the integration of data from different experiments and different laboratories. How to weigh the contribution of different experiments is an important point influencing the final outcomes. We have developed a novel method for this integration, and applied it to genome-wide data from multiple Arabidopsis microarray experiments performed under a variety of experimental conditions. The goal of this study is to identify functional globally co-regulated gene modules in the Arabidopsis genome. Results Following the analysis of 21,000 Arabidopsis genes in 43 datasets and about 2 × 108 gene pairs, we identified a globally co-expressed gene network. We found clusters of globally co-expressed Arabidopsis genes that are enriched for known Gene Ontology annotations. Two types of modules were identified in the regulatory network that differed in their sensitivity to the node-scoring parameter; we further showed these two pertain to general and specialized modules. Some of these modules were further investigated using the Genevestigator compendium of microarray experiments. Analyses of smaller subsets of data lead to the identification of condition-specific modules. Conclusion Our method for identification of gene clusters allows the integration of diverse microarray experiments from many sources. The analysis reveals that part of the Arabidopsis transcriptome is globally co-expressed, and can be further divided into known as well as novel functional gene modules. Our methodology is general enough to apply to any set of microarray experiments, using any scoring function.

Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis

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Zhou X

2018-05-01

Full Text Available Xian-guo Zhou,1,2,* Xiao-liang Huang,1,2,* Si-yuan Liang,1–3 Shao-mei Tang,1,2 Si-kao Wu,1,2 Tong-tong Huang,1,2 Zeng-nan Mo,1,2,4 Qiu-yan Wang1,2,5 1Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 2Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 3Department of Colorectal Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 4Department of Urology and Nephrology, The First Affiliated Hospital of Guangxi, Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 5Guangxi Colleges and Universities Key Laboratory of Biological Molecular Medicine Research, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China *These authors contributed equally to this work Introduction: Colorectal cancer (CRC is the fourth most common cause of cancer-related mortality worldwide. The tumor, node, metastasis (TNM stage remains the standard for CRC prognostication. Identification of meaningful microRNA (miRNA and gene modules or representative biomarkers related to the pathological stage of colon cancer helps to predict prognosis and reveal the mechanisms behind cancer progression.Materials and methods: We applied a systems biology approach by combining differential expression analysis and weighted gene co-expression network analysis (WGCNA to detect the pathological stage-related miRNA and gene modules and construct a miRNA–gene network. The Cancer Genome Atlas (TCGA colon adenocarcinoma (CAC RNA-sequencing data and miRNA-sequencing data were subjected to WGCNA analysis, and the GSE29623, GSE35602 and GSE39396 were utilized to validate and

Taxon abundance, diversity, co-occurrence and network analysis of the ruminal microbiota in response to dietary changes in dairy cows.

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Ilma Tapio

Full Text Available The ruminal microbiome, comprising large numbers of bacteria, ciliate protozoa, archaea and fungi, responds to diet and dietary additives in a complex way. The aim of this study was to investigate the benefits of increasing the depth of the community analysis in describing and explaining responses to dietary changes. Quantitative PCR, ssu rRNA amplicon based taxa composition, diversity and co-occurrence network analyses were applied to ruminal digesta samples obtained from four multiparous Nordic Red dairy cows fitted with rumen cannulae. The cows received diets with forage:concentrate ratio either 35:65 (diet H or 65:35 (L, supplemented or not with sunflower oil (SO (0 or 50 g/kg diet dry matter, supplied in a 4 × 4 Latin square design with a 2 × 2 factorial arrangement of treatments and four 35-day periods. Digesta samples were collected on days 22 and 24 and combined. QPCR provided a broad picture in which a large fall in the abundance of fungi was seen with SO in the H but not the L diet. Amplicon sequencing showed higher community diversity indices in L as compared to H diets and revealed diet specific taxa abundance changes, highlighting large differences in protozoal and fungal composition. Methanobrevibacter ruminantium and Mbb. gottschalkii dominated archaeal communities, and their abundance correlated negatively with each other. Co-occurrence network analysis provided evidence that no microbial domain played a more central role in network formation, that some minor-abundance taxa were at nodes of highest centrality, and that microbial interactions were diet specific. Networks added new dimensions to our understanding of the diet effect on rumen microbial community interactions.

Soil Conditions Rather Than Long-Term Exposure to Elevated CO2 Affect Soil Microbial Communities Associated with N-Cycling

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Kristof Brenzinger

2017-10-01

Full Text Available Continuously rising atmospheric CO2 concentrations may lead to an increased transfer of organic C from plants to the soil through rhizodeposition and may affect the interaction between the C- and N-cycle. For instance, fumigation of soils with elevated CO2 (eCO2 concentrations (20% higher compared to current atmospheric concentrations at the Giessen Free-Air Carbon Dioxide Enrichment (GiFACE sites resulted in a more than 2-fold increase of long-term N2O emissions and an increase in dissimilatory reduction of nitrate compared to ambient CO2 (aCO2. We hypothesized that the observed differences in soil functioning were based on differences in the abundance and composition of microbial communities in general and especially of those which are responsible for N-transformations in soil. We also expected eCO2 effects on soil parameters, such as on nitrate as previously reported. To explore the impact of long-term eCO2 on soil microbial communities, we applied a molecular approach (qPCR, T-RFLP, and 454 pyrosequencing. Microbial groups were analyzed in soil of three sets of two FACE plots (three replicate samples from each plot, which were fumigated with eCO2 and aCO2, respectively. N-fixers, denitrifiers, archaeal and bacterial ammonia oxidizers, and dissimilatory nitrate reducers producing ammonia were targeted by analysis of functional marker genes, and the overall archaeal community by 16S rRNA genes. Remarkably, soil parameters as well as the abundance and composition of microbial communities in the top soil under eCO2 differed only slightly from soil under aCO2. Wherever differences in microbial community abundance and composition were detected, they were not linked to CO2 level but rather determined by differences in soil parameters (e.g., soil moisture content due to the localization of the GiFACE sets in the experimental field. We concluded that +20% eCO2 had little to no effect on the overall microbial community involved in N-cycling in the

Soil Conditions Rather Than Long-Term Exposure to Elevated CO2 Affect Soil Microbial Communities Associated with N-Cycling.

Science.gov (United States)

Brenzinger, Kristof; Kujala, Katharina; Horn, Marcus A; Moser, Gerald; Guillet, Cécile; Kammann, Claudia; Müller, Christoph; Braker, Gesche

2017-01-01

Continuously rising atmospheric CO 2 concentrations may lead to an increased transfer of organic C from plants to the soil through rhizodeposition and may affect the interaction between the C- and N-cycle. For instance, fumigation of soils with elevated CO 2 ( e CO 2 ) concentrations (20% higher compared to current atmospheric concentrations) at the Giessen Free-Air Carbon Dioxide Enrichment (GiFACE) sites resulted in a more than 2-fold increase of long-term N 2 O emissions and an increase in dissimilatory reduction of nitrate compared to ambient CO 2 ( a CO 2 ). We hypothesized that the observed differences in soil functioning were based on differences in the abundance and composition of microbial communities in general and especially of those which are responsible for N-transformations in soil. We also expected e CO 2 effects on soil parameters, such as on nitrate as previously reported. To explore the impact of long-term e CO 2 on soil microbial communities, we applied a molecular approach (qPCR, T-RFLP, and 454 pyrosequencing). Microbial groups were analyzed in soil of three sets of two FACE plots (three replicate samples from each plot), which were fumigated with e CO 2 and a CO 2 , respectively. N-fixers, denitrifiers, archaeal and bacterial ammonia oxidizers, and dissimilatory nitrate reducers producing ammonia were targeted by analysis of functional marker genes, and the overall archaeal community by 16S rRNA genes. Remarkably, soil parameters as well as the abundance and composition of microbial communities in the top soil under e CO 2 differed only slightly from soil under a CO 2 . Wherever differences in microbial community abundance and composition were detected, they were not linked to CO 2 level but rather determined by differences in soil parameters (e.g., soil moisture content) due to the localization of the GiFACE sets in the experimental field. We concluded that +20% e CO 2 had little to no effect on the overall microbial community involved in N

Relationships Among Tweets Related to Radiation: Visualization Using Co-Occurring Networks.

Science.gov (United States)

Yagahara, Ayako; Hanai, Keiri; Hasegawa, Shin; Ogasawara, Katsuhiko

2018-03-15

After the Fukushima Daiichi nuclear accident on March 11, 2011, interest in, and fear of, radiation increased among citizens. When such accidents occur, appropriate risk communication must provided by the government. It is therefore necessary to understand the fears of citizens in the days after such accidents. This study aimed to identify the progression of people's concerns, specifically fear, from a study of radiation-related tweets in the days after the Fukushima Daiichi nuclear accident. From approximately 1.5 million tweets in Japanese including any of the phrases "radiation" (), "radioactivity" (), and "radioactive substance" () sent March 11-17, 2011, we extracted tweets that expressed fear. We then performed a morphological analysis on the extracted tweets. Citizens' fears were visualized by creating co-occurrence networks using co-occurrence degrees showing relationship strength. Moreover, we calculated the Jaccard coefficient, which is one of the co-occurrence indices for expressing the strength of the relationship between morphemes when creating networks. From the visualization of the co-occurrence networks, we found high citizen interest in "nuclear power plant" on March 11 and 12, "health" on March 12 and 13, "medium" on March 13 and 14, and "economy" on March 15. On March 16 and 17, citizens' interest changed to "lack of goods in the afflicted area." In each co-occurrence network, trending topics, citizens' fears, and opinions to the government were extracted. This study used Twitter to understand changes in the concerns of Japanese citizens during the week after the Fukushima Daiichi nuclear accident, with a focus specifically on citizens' fears. We found that immediately after the accident, the interest in the accident itself was high, and then interest shifted to concerns affecting life, such as health and economy, as the week progressed. Clarifying citizens' fears and the dissemination of information through mass media and social media can add to

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

Directory of Open Access Journals (Sweden)

Brian R Granger

2016-04-01

Full Text Available The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space, a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

Science.gov (United States)

Granger, Brian R; Chang, Yi-Chien; Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

2016-04-01

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

Using isotopic tracers to assess the impact of tillage and straw management on the microbial metabolic network in soil

Science.gov (United States)

Van Groenigen, K.; Forristal, D.; Jones, M. B.; Schwartz, E.; Hungate, B. A.; Dijkstra, P.

2013-12-01

By decomposing soil organic matter, microbes gain energy and building blocks for biosynthesis and release CO2 to the atmosphere. Therefore, insight into the effect of management practices on microbial metabolic pathways and C use efficiency (CUE; microbial C produced per substrate C utilized) may help to predict long term changes in soil C stocks. We studied the effects of reduced (RT) and conventional tillage (CT) on the microbial central C metabolic network, using soil samples from a 12-year-old field experiment in an Irish winter wheat cropping system. Each year after harvest, straw was removed from half of the RT and CT plots or incorporated into the soil in the other half, resulting in four treatment combinations. We added 1-13C and 2,3-13C pyruvate and 1-13C and U-13C glucose as metabolic tracer isotopomers to composite soil samples taken at two depths (0-15 cm and 15-30 cm) from each treatment and used the rate of position-specific respired 13CO2 to parameterize a metabolic model. Model outcomes were then used to calculate CUE of the microbial community. We found that the composite samples differed in CUE, but the changes were small, with values ranging between 0.757-0.783 across treatments and soil depth. Increases in CUE were associated with a decrease in tricarboxylic acid cycle and reductive pentose phosphate pathway activity and increased consumption of metabolic intermediates for biosynthesis. Our results indicate that RT and straw incorporation promote soil C storage without substantially changing CUE or any of the microbial metabolic pathways. This suggests that at our site, RT and straw incorporation promote soil C storage mostly through direct effects such as increased soil C input and physical protection from decomposition, rather than by feedback responses of the microbial community.

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.

Design, Modeling, and Development of Microbial Cell Factories

KAUST Repository

Kodzius, Rimantas; Behzad, H.; Archer, John A.C.; Bajic, Vladimir B.; Gojobori, Takashi

2014-01-01

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.

Rain-induced changes in soil CO2 flux and microbial community composition in a tropical forest of China.

Science.gov (United States)

Deng, Qi; Hui, Dafeng; Chu, Guowei; Han, Xi; Zhang, Quanfa

2017-07-17

Rain-induced soil CO 2 pulse, a rapid excitation in soil CO 2 flux after rain, is ubiquitously observed in terrestrial ecosystems, yet the underlying mechanisms in tropical forests are still not clear. We conducted a rain simulation experiment to quantify rain-induced changes in soil CO 2 flux and microbial community composition in a tropical forest. Soil CO 2 flux rapidly increased by ~83% after rains, accompanied by increases in both bacterial (~51%) and fungal (~58%) Phospholipid Fatty Acids (PLFA) biomass. However, soil CO 2 flux and microbial community in the plots without litters showed limited response to rains. Direct releases of CO 2 from litter layer only accounted for ~19% increases in soil CO 2 flux, suggesting that the leaching of dissolved organic carbon (DOC) from litter layer to the topsoil is the major cause of rain-induced soil CO 2 pulse. In addition, rain-induced changes in soil CO 2 flux and microbial PLFA biomass decreased with increasing rain sizes, but they were positively correlated with litter-leached DOC concentration rather than total DOC flux. Our findings reveal an important role of litter-leached DOC input in regulating rain-induced soil CO 2 pulses and microbial community composition, and may have significant implications for CO 2 losses from tropical forest soils under future rainfall changes.

Gene Co-expression Analysis to Characterize Genes Related to Marbling Trait in Hanwoo (Korean) Cattle.

Science.gov (United States)

Lim, Dajeong; Lee, Seung-Hwan; Kim, Nam-Kuk; Cho, Yong-Min; Chai, Han-Ha; Seong, Hwan-Hoo; Kim, Heebal

2013-01-01

Marbling (intramuscular fat) is an important trait that affects meat quality and is a casual factor determining the price of beef in the Korean beef market. It is a complex trait and has many biological pathways related to muscle and fat. There is a need to identify functional modules or genes related to marbling traits and investigate their relationships through a weighted gene co-expression network analysis based on the system level. Therefore, we investigated the co-expression relationships of genes related to the 'marbling score' trait and systemically analyzed the network topology in Hanwoo (Korean cattle). As a result, we determined 3 modules (gene groups) that showed statistically significant results for marbling score. In particular, one module (denoted as red) has a statistically significant result for marbling score (p = 0.008) and intramuscular fat (p = 0.02) and water capacity (p = 0.006). From functional enrichment and relationship analysis of the red module, the pathway hub genes (IL6, CHRNE, RB1, INHBA and NPPA) have a direct interaction relationship and share the biological functions related to fat or muscle, such as adipogenesis or muscle growth. This is the first gene network study with m.logissimus in Hanwoo to observe co-expression patterns in divergent marbling phenotypes. It may provide insights into the functional mechanisms of the marbling trait.

Gene Co-expression Analysis to Characterize Genes Related to Marbling Trait in Hanwoo (Korean Cattle

Directory of Open Access Journals (Sweden)

Dajeong Lim

2013-01-01

Full Text Available Marbling (intramuscular fat is an important trait that affects meat quality and is a casual factor determining the price of beef in the Korean beef market. It is a complex trait and has many biological pathways related to muscle and fat. There is a need to identify functional modules or genes related to marbling traits and investigate their relationships through a weighted gene co-expression network analysis based on the system level. Therefore, we investigated the co-expression relationships of genes related to the ‘marbling score’ trait and systemically analyzed the network topology in Hanwoo (Korean cattle. As a result, we determined 3 modules (gene groups that showed statistically significant results for marbling score. In particular, one module (denoted as red has a statistically significant result for marbling score (p = 0.008 and intramuscular fat (p = 0.02 and water capacity (p = 0.006. From functional enrichment and relationship analysis of the red module, the pathway hub genes (IL6, CHRNE, RB1, INHBA and NPPA have a direct interaction relationship and share the biological functions related to fat or muscle, such as adipogenesis or muscle growth. This is the first gene network study with m.logissimus in Hanwoo to observe co-expression patterns in divergent marbling phenotypes. It may provide insights into the functional mechanisms of the marbling trait.

Elevated Atmospheric CO2 and Drought Affect Soil Microbial Community and Functional Diversity Associated with Glycine max

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Junfeng Wang

2017-12-01

Full Text Available Abstract Under the background of climate change, the increase of atmospheric CO2 and drought frequency have been considered as significant influencers on the soil microbial communities and the yield and quality of crop. In this study, impacts of increased ambient CO2 and drought on soil microbial structure and functional diversity of a Stagnic Anthrosol were investigated in phytotron growth chambers, by testing two representative CO2 levels, three soil moisture levels, and two soil cover types (with or without Glycine max. The 16S rDNA and 18S rDNA fragments were amplified to analyze the functional diversity of fungi and bacteria. Results showed that rhizosphere microbial biomass and community structure were significantly affected by drought, but effects differed between fungi and bacteria. Drought adaptation of fungi was found to be easier than that of bacteria. The diversity of fungi was less affected by drought than that of bacteria, evidenced by their higher diversity. Severe drought reduced soil microbial functional diversity and restrained the metabolic activity. Elevated CO2 alone, in the absence of crops (bare soil, did not enhance the metabolic activity of soil microorganisms. Generally, due to the co-functioning of plant and soil microorganisms in water and nutrient use, plants have major impacts on the soil microbial community, leading to atmospheric CO2 enrichment, but cannot significantly reduce the impacts of drought on soil microorganisms.

Evaluation of physical, chemical and microbial quality of distribution network drinkingwater in Bushehr, Iran

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Elham Shabankareh fard

2015-01-01

Full Text Available Background: The physical, chemical and microbial properties of water are the criteria to consider it as drinking water quality. Unfavorable changes in such parameters may threat consumers' health. The aim of this study is to give a clear view of physical, chemical and microbial quality of distribution network drinking water in Bushehr and compare with national and EPA standards. Materials and Methods: This descriptive sectional study was done during Sep 2012 to Feb 2013 (6 months. 50 Samples were collected directly from distribution network drinking water in Bushehr. Physical and chemical analyses were done according to standard methods. Multiple tube fermentation method was used to determine fecal and total coliform bacteria and spread plate method was used to measure heterotrophic bacteria. Results: The mean values of measured parameters were as follow: electrical conductivity 1155.5 µs/cm, turbidity 0.27 NTU, pH 7.12, alkalinity 171.5, total hardness 458.96, calcium hardness 390.96, magnesium hardness 68 mg/L as CaCO3, calcium 156.38, magnesium 16.95, residual chlorine 0.61, chloride 83.26, TDS 577.7, iron 0.115, fluoride 0.48, phosphate 0.059, nitrate 3.08, nitrite 0.003 and sulphate 728.38 mg/L. Total coliform (0, fecal coliform (0 MPN/100 ml and HPC 309.8 CFU/mL. Except TDS and sulphate, all cited results met the national and EPA standards. Conclusion: Quality of water from distribution network in Bushehr was not problematical from health point of view. However, high TDS and sulphate content may increase diarrhea risk in consumer as well as corrosive effect of water.

CoBOP: Microbial Biofilms: A Parameter Altering the Apparent Optical Properties of Sediments, Seagrasses and Surfaces

Science.gov (United States)

2002-09-30

CoBOP: Microbial Biofilms: A Parameter Altering the Apparent Optical Properties of Sediments, Seagrasses and Surfaces Alan W. Decho Department...TITLE AND SUBTITLE CoBOP: Microbial Biofilms: A Parameter Altering the Apparent Optical Properties of Sediments, Seagrasses and Surfaces 5a. CONTRACT...structures produced by bacteria. Their growth appears to depend on biofilm processes and light distributions ( photosynthesis ). Therefore, the data acquired

Soil Microbial Responses to Elevated CO2 and O3 in a Nitrogen-Aggrading Agroecosystem

Science.gov (United States)

Cheng, Lei; Booker, Fitzgerald L.; Burkey, Kent O.; Tu, Cong; Shew, H. David; Rufty, Thomas W.; Fiscus, Edwin L.; Deforest, Jared L.; Hu, Shuijin

2011-01-01

Climate change factors such as elevated atmospheric carbon dioxide (CO2) and ozone (O3) can exert significant impacts on soil microbes and the ecosystem level processes they mediate. However, the underlying mechanisms by which soil microbes respond to these environmental changes remain poorly understood. The prevailing hypothesis, which states that CO2- or O3-induced changes in carbon (C) availability dominate microbial responses, is primarily based on results from nitrogen (N)-limiting forests and grasslands. It remains largely unexplored how soil microbes respond to elevated CO2 and O3 in N-rich or N-aggrading systems, which severely hinders our ability to predict the long-term soil C dynamics in agroecosystems. Using a long-term field study conducted in a no-till wheat-soybean rotation system with open-top chambers, we showed that elevated CO2 but not O3 had a potent influence on soil microbes. Elevated CO2 (1.5×ambient) significantly increased, while O3 (1.4×ambient) reduced, aboveground (and presumably belowground) plant residue C and N inputs to soil. However, only elevated CO2 significantly affected soil microbial biomass, activities (namely heterotrophic respiration) and community composition. The enhancement of microbial biomass and activities by elevated CO2 largely occurred in the third and fourth years of the experiment and coincided with increased soil N availability, likely due to CO2-stimulation of symbiotic N2 fixation in soybean. Fungal biomass and the fungi∶bacteria ratio decreased under both ambient and elevated CO2 by the third year and also coincided with increased soil N availability; but they were significantly higher under elevated than ambient CO2. These results suggest that more attention should be directed towards assessing the impact of N availability on microbial activities and decomposition in projections of soil organic C balance in N-rich systems under future CO2 scenarios. PMID:21731722

Linking social and pathogen transmission networks using microbial genetics in giraffe (Giraffa camelopardalis).

Science.gov (United States)

VanderWaal, Kimberly L; Atwill, Edward R; Isbell, Lynne A; McCowan, Brenda

2014-03-01

Although network analysis has drawn considerable attention as a promising tool for disease ecology, empirical research has been hindered by limitations in detecting the occurrence of pathogen transmission (who transmitted to whom) within social networks. Using a novel approach, we utilize the genetics of a diverse microbe, Escherichia coli, to infer where direct or indirect transmission has occurred and use these data to construct transmission networks for a wild giraffe population (Giraffe camelopardalis). Individuals were considered to be a part of the same transmission chain and were interlinked in the transmission network if they shared genetic subtypes of E. coli. By using microbial genetics to quantify who transmits to whom independently from the behavioural data on who is in contact with whom, we were able to directly investigate how the structure of contact networks influences the structure of the transmission network. To distinguish between the effects of social and environmental contact on transmission dynamics, the transmission network was compared with two separate contact networks defined from the behavioural data: a social network based on association patterns, and a spatial network based on patterns of home-range overlap among individuals. We found that links in the transmission network were more likely to occur between individuals that were strongly linked in the social network. Furthermore, individuals that had more numerous connections or that occupied 'bottleneck' positions in the social network tended to occupy similar positions in the transmission network. No similar correlations were observed between the spatial and transmission networks. This indicates that an individual's social network position is predictive of transmission network position, which has implications for identifying individuals that function as super-spreaders or transmission bottlenecks in the population. These results emphasize the importance of association patterns in

General expressions for downlink signal to interference and noise ratio in homogeneous and heterogeneous LTE-Advanced networks.

Science.gov (United States)

Ali, Nora A; Mourad, Hebat-Allah M; ElSayed, Hany M; El-Soudani, Magdy; Amer, Hassanein H; Daoud, Ramez M

2016-11-01

The interference is the most important problem in LTE or LTE-Advanced networks. In this paper, the interference was investigated in terms of the downlink signal to interference and noise ratio (SINR). In order to compare the different frequency reuse methods that were developed to enhance the SINR, it would be helpful to have a generalized expression to study the performance of the different methods. Therefore, this paper introduces general expressions for the SINR in homogeneous and in heterogeneous networks. In homogeneous networks, the expression was applied for the most common types of frequency reuse techniques: soft frequency reuse (SFR) and fractional frequency reuse (FFR). The expression was examined by comparing it with previously developed ones in the literature and the comparison showed that the expression is valid for any type of frequency reuse scheme and any network topology. Furthermore, the expression was extended to include the heterogeneous network; the expression includes the problem of co-tier and cross-tier interference in heterogeneous networks (HetNet) and it was examined by the same method of the homogeneous one.

General expressions for downlink signal to interference and noise ratio in homogeneous and heterogeneous LTE-Advanced networks

Directory of Open Access Journals (Sweden)

Nora A. Ali

2016-11-01

Full Text Available The interference is the most important problem in LTE or LTE-Advanced networks. In this paper, the interference was investigated in terms of the downlink signal to interference and noise ratio (SINR. In order to compare the different frequency reuse methods that were developed to enhance the SINR, it would be helpful to have a generalized expression to study the performance of the different methods. Therefore, this paper introduces general expressions for the SINR in homogeneous and in heterogeneous networks. In homogeneous networks, the expression was applied for the most common types of frequency reuse techniques: soft frequency reuse (SFR and fractional frequency reuse (FFR. The expression was examined by comparing it with previously developed ones in the literature and the comparison showed that the expression is valid for any type of frequency reuse scheme and any network topology. Furthermore, the expression was extended to include the heterogeneous network; the expression includes the problem of co-tier and cross-tier interference in heterogeneous networks (HetNet and it was examined by the same method of the homogeneous one.

Microbial electrolysis desalination and chemical-production cell for CO2 sequestration

KAUST Repository

Zhu, Xiuping; Logan, Bruce E.

2014-01-01

Mineral carbonation can be used for CO2 sequestration, but the reaction rate is slow. In order to accelerate mineral carbonation, acid generated in a microbial electrolysis desalination and chemical-production cell (MEDCC) was examined to dissolve

Distinct responses of soil microbial communities to elevated CO2 and O3 in a soybean agro-ecosystem.

Science.gov (United States)

He, Zhili; Xiong, Jinbo; Kent, Angela D; Deng, Ye; Xue, Kai; Wang, Gejiao; Wu, Liyou; Van Nostrand, Joy D; Zhou, Jizhong

2014-03-01

The concentrations of atmospheric carbon dioxide (CO2) and tropospheric ozone (O3) have been rising due to human activities. However, little is known about how such increases influence soil microbial communities. We hypothesized that elevated CO2 (eCO2) and elevated O3 (eO3) would significantly affect the functional composition, structure and metabolic potential of soil microbial communities, and that various functional groups would respond to such atmospheric changes differentially. To test these hypotheses, we analyzed 96 soil samples from a soybean free-air CO2 enrichment (SoyFACE) experimental site using a comprehensive functional gene microarray (GeoChip 3.0). The results showed the overall functional composition and structure of soil microbial communities shifted under eCO2, eO3 or eCO2+eO3. Key functional genes involved in carbon fixation and degradation, nitrogen fixation, denitrification and methane metabolism were stimulated under eCO2, whereas those involved in N fixation, denitrification and N mineralization were suppressed under eO3, resulting in the fact that the abundance of some eO3-supressed genes was promoted to ambient, or eCO2-induced levels by the interaction of eCO2+eO3. Such effects appeared distinct for each treatment and significantly correlated with soil properties and soybean yield. Overall, our analysis suggests possible mechanisms of microbial responses to global atmospheric change factors through the stimulation of C and N cycling by eCO2, the inhibition of N functional processes by eO3 and the interaction by eCO2 and eO3. This study provides new insights into our understanding of microbial functional processes in response to global atmospheric change in soybean agro-ecosystems.

Microbial diversity and metabolic networks in acid mine drainage habitats

Directory of Open Access Journals (Sweden)

Celia eMendez-Garcia

2015-05-01

Full Text Available Acid mine drainage (AMD emplacements are low-complexity natural systems. Low-pH conditions appear to be the main factor underlying the limited diversity of the microbial populations thriving in these environments, although temperature, ionic composition, total organic carbon and dissolved oxygen are also considered to significantly influence their microbial life. This natural reduction in diversity driven by extreme conditions was reflected in several studies on the microbial populations inhabiting the various micro-environments present in such ecosystems. Early studies based on the physiology of the autochthonous microbiota and the growing success of omics technologies have enabled a better understanding of microbial ecology and function in low-pH mine outflows; however, complementary omics-derived data should be included to completely describe their microbial ecology. Furthermore, recent updates on the distribution of eukaryotes and ultra-micro-archaea demand their inclusion in the microbial characterisation of AMD systems. In this review, we present a complete overview of the bacterial, archaeal (including ultra-micro-archaeal and eukaryotic diversity in these ecosystems and include a thorough depiction of the metabolism and element cycling in AMD habitats. We also review different metabolic network structures at the organismal level, which is necessary to disentangle the role of each member of the AMD communities described thus far.

Co-occurrence analysis of microbial taxa in the Atlantic Ocean reveals high connectivity in the free-living bacterioplankton

Directory of Open Access Journals (Sweden)

Mathias eMilici

2016-05-01

Full Text Available We determined the taxonomic composition of the bacterioplankton of the epipelagic zone of the Atlantic Ocean along a latitudinal transect (51°S – 47°N using Illumina sequencing of the V5-V6 region of the 16S rRNA gene and inferred co-occurrence networks. Bacterioplankon community composition was distinct for Longhurstian provinces and water depth. Free-living microbial communities (between 0.22-3 µm were dominated by highly abundant and ubiquitous taxa with streamlined genomes (e.g. SAR11, SAR86, OM1, Prochlorococcus and could clearly be separated from particle-associated communities which were dominated by Bacteroidetes, Planktomycetes, Verrucomicrobia and Roseobacters. From a total of 369 different communities we then inferred co-occurrence networks for each size fraction and depth layer of the plankton between bacteria and between bacteria and phototrophic micro-eukaryotes. The inferred networks showed a reduction of edges in the deepest layer of the photic zone. Networks comprised of free-living bacteria had a larger amount of connections per OTU when compared to the particle associated communities throughout the water column. Negative correlations accounted for roughly one third of the total edges in the free-living communities at all depths, while they decreased with depth in the particle associated communities where they amounted for roughly 10% of the total in the last part of the epipelagic zone. Co-occurrence networks of bacteria with phototrophic micro-eukaryotes were not taxon-specific, and dominated by mutual exclusion (~60%. The data show a high degree of specialization to micro-environments in the water column and highlight the importance of interdependencies particularly between free-living bacteria in the upper layers of the epipelagic zone.

A CoAP-Based Network Access Authentication Service for Low-Power Wide Area Networks: LO-CoAP-EAP

Directory of Open Access Journals (Sweden)

Dan Garcia-Carrillo

2017-11-01

Full Text Available The Internet-of-Things (IoT landscape is expanding with new radio technologies. In addition to the Low-Rate Wireless Personal Area Network (LR-WPAN, the recent set of technologies conforming the so-called Low-Power Wide Area Networks (LP-WAN offers long-range communications, allowing one to send small pieces of information at a reduced energy cost, which promotes the creation of new IoT applications and services. However, LP-WAN technologies pose new challenges since they have strong limitations in the available bandwidth. In general, a first step prior to a smart object being able to gain access to the network is the process of network access authentication. It involves authentication, authorization and key management operations. This process is of vital importance for operators to control network resources. However, proposals for managing network access authentication in LP-WAN are tailored to the specifics of each technology, which could introduce interoperability problems in the future. In this sense, little effort has been put so far into providing a wireless-independent solution for network access authentication in the area of LP-WAN. To fill this gap, we propose a service named Low-Overhead CoAP-EAP (LO-CoAP-EAP, which is based on previous work designed for LR-WPAN. LO-CoAP-EAP integrates the use of Authentication, Authorization and Accounting (AAA infrastructures and the Extensible Authentication Protocol (EAP protocol. For this integration, we use the Constrained Application Protocol (CoAP to design a network authentication service independent of the type of LP-WAN technology. LO-CoAP-EAP represents a trade-off between flexibility, wireless technology independence, scalability and performance in LP-WAN.

A CoAP-Based Network Access Authentication Service for Low-Power Wide Area Networks: LO-CoAP-EAP.

Science.gov (United States)

Garcia-Carrillo, Dan; Marin-Lopez, Rafael; Kandasamy, Arunprabhu; Pelov, Alexander

2017-11-17

The Internet-of-Things (IoT) landscape is expanding with new radio technologies. In addition to the Low-Rate Wireless Personal Area Network (LR-WPAN), the recent set of technologies conforming the so-called Low-Power Wide Area Networks (LP-WAN) offers long-range communications, allowing one to send small pieces of information at a reduced energy cost, which promotes the creation of new IoT applications and services. However, LP-WAN technologies pose new challenges since they have strong limitations in the available bandwidth. In general, a first step prior to a smart object being able to gain access to the network is the process of network access authentication. It involves authentication, authorization and key management operations. This process is of vital importance for operators to control network resources. However, proposals for managing network access authentication in LP-WAN are tailored to the specifics of each technology, which could introduce interoperability problems in the future. In this sense, little effort has been put so far into providing a wireless-independent solution for network access authentication in the area of LP-WAN. To fill this gap, we propose a service named Low-Overhead CoAP-EAP (LO-CoAP-EAP), which is based on previous work designed for LR-WPAN. LO-CoAP-EAP integrates the use of Authentication, Authorization and Accounting (AAA) infrastructures and the Extensible Authentication Protocol (EAP) protocol. For this integration, we use the Constrained Application Protocol (CoAP) to design a network authentication service independent of the type of LP-WAN technology. LO-CoAP-EAP represents a trade-off between flexibility, wireless technology independence, scalability and performance in LP-WAN.

Cell cycle gene expression networks discovered using systems biology: Significance in carcinogenesis

Science.gov (United States)

Scott, RE; Ghule, PN; Stein, JL; Stein, GS

2015-01-01

The early stages of carcinogenesis are linked to defects in the cell cycle. A series of cell cycle checkpoints are involved in this process. The G1/S checkpoint that serves to integrate the control of cell proliferation and differentiation is linked to carcinogenesis and the mitotic spindle checkpoint with the development of chromosomal instability. This paper presents the outcome of systems biology studies designed to evaluate if networks of covariate cell cycle gene transcripts exist in proliferative mammalian tissues including mice, rats and humans. The GeneNetwork website that contains numerous gene expression datasets from different species, sexes and tissues represents the foundational resource for these studies (www.genenetwork.org). In addition, WebGestalt, a gene ontology tool, facilitated the identification of expression networks of genes that co-vary with key cell cycle targets, especially Cdc20 and Plk1 (www.bioinfo.vanderbilt.edu/webgestalt). Cell cycle expression networks of such covariate mRNAs exist in multiple proliferative tissues including liver, lung, pituitary, adipose and lymphoid tissues among others but not in brain or retina that have low proliferative potential. Sixty-three covariate cell cycle gene transcripts (mRNAs) compose the average cell cycle network with p = e−13 to e−36. Cell cycle expression networks show species, sex and tissue variability and they are enriched in mRNA transcripts associated with mitosis many of which are associated with chromosomal instability. PMID:25808367

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular networks

NARCIS (Netherlands)

R. Colak; F. Moser; J. Shu; A. Schönhuth (Alexander); N. Chen; M. Ester

2010-01-01

htmlabstractBackground Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not

Genome-Scale Co-Expression Network Comparison across Escherichia coli and Salmonella enterica Serovar Typhimurium Reveals Significant Conservation at the Regulon Level of Local Regulators Despite Their Dissimilar Lifestyles

Science.gov (United States)

Zarrineh, Peyman; Sánchez-Rodríguez, Aminael; Hosseinkhan, Nazanin; Narimani, Zahra; Marchal, Kathleen; Masoudi-Nejad, Ali

2014-01-01

Availability of genome-wide gene expression datasets provides the opportunity to study gene expression across different organisms under a plethora of experimental conditions. In our previous work, we developed an algorithm called COMODO (COnserved MODules across Organisms) that identifies conserved expression modules between two species. In the present study, we expanded COMODO to detect the co-expression conservation across three organisms by adapting the statistics behind it. We applied COMODO to study expression conservation/divergence between Escherichia coli, Salmonella enterica, and Bacillus subtilis. We observed that some parts of the regulatory interaction networks were conserved between E. coli and S. enterica especially in the regulon of local regulators. However, such conservation was not observed between the regulatory interaction networks of B. subtilis and the two other species. We found co-expression conservation on a number of genes involved in quorum sensing, but almost no conservation for genes involved in pathogenicity across E. coli and S. enterica which could partially explain their different lifestyles. We concluded that despite their different lifestyles, no significant rewiring have occurred at the level of local regulons involved for instance, and notable conservation can be detected in signaling pathways and stress sensing in the phylogenetically close species S. enterica and E. coli. Moreover, conservation of local regulons seems to depend on the evolutionary time of divergence across species disappearing at larger distances as shown by the comparison with B. subtilis. Global regulons follow a different trend and show major rewiring even at the limited evolutionary distance that separates E. coli and S. enterica. PMID:25101984

Phenotypic responses to interspecies competition and commensalism in a naturally-derived microbial co-culture

Energy Technology Data Exchange (ETDEWEB)

Khan, Nymul; Maezato, Yukari; McClure, Ryan S.; Brislawn, Colin J.; Mobberley, Jennifer M.; Isern, Nancy; Chrisler, William B.; Markillie, Lye Meng; Barney, Brett M.; Song, Hyun-Seob; Nelson, William C.; Bernstein, Hans C.

2018-01-10

The fundamental question of whether different microbial species will co-exist or compete in a given environment depends on context, composition and environmental constraints. Model microbial systems can yield some general principles related to this question. In this study we employed a naturally occurring co-culture composed of heterotrophic bacteria, Halomonas sp. HL-48 and Marinobacter sp. HL-58, to ask two fundamental scientific questions: 1) how do the phenotypes of two naturally co-existing species respond to partnership as compared to axenic growth? and 2) how do growth and molecular phenotypes of these species change with respect to competitive and commensal interactions? We hypothesized – and confirmed – that co-cultivation under glucose as the sole carbon source would result in a competitive interactions. Similarly, when glucose was swapped with xylose, the interactions became commensal because Marinobacter HL-58 was supported by metabolites derived from Halomonas HL-48. Each species responded to partnership by changing both its growth and molecular phenotype as assayed via batch growth kinetics and global transcriptomics. These phenotypic responses depended nutrient availability and so the environment ultimately controlled how they responded to each other. This simplified model community revealed that microbial interactions are context-specific and different environmental conditions dictate how interspecies partnerships will unfold.

Directed evolution to re-adapt a co-evolved network within an enzyme.

Science.gov (United States)

Strafford, John; Payongsri, Panwajee; Hibbert, Edward G; Morris, Phattaraporn; Batth, Sukhjeet S; Steadman, David; Smith, Mark E B; Ward, John M; Hailes, Helen C; Dalby, Paul A

2012-01-01

We have previously used targeted active-site saturation mutagenesis to identify a number of transketolase single mutants that improved activity towards either glycolaldehyde (GA), or the non-natural substrate propionaldehyde (PA). Here, all attempts to recombine the singles into double mutants led to unexpected losses of specific activity towards both substrates. A typical trade-off occurred between soluble expression levels and specific activity for all single mutants, but many double mutants decreased both properties more severely suggesting a critical loss of protein stability or native folding. Statistical coupling analysis (SCA) of a large multiple sequence alignment revealed a network of nine co-evolved residues that affected all but one double mutant. Such networks maintain important functional properties such as activity, specificity, folding, stability, and solubility and may be rapidly disrupted by introducing one or more non-naturally occurring mutations. To identify variants of this network that would accept and improve upon our best D469 mutants for activity towards PA, we created a library of random single, double and triple mutants across seven of the co-evolved residues, combining our D469 variants with only naturally occurring mutations at the remaining sites. A triple mutant cluster at D469, E498 and R520 was found to behave synergistically for the specific activity towards PA. Protein expression was severely reduced by E498D and improved by R520Q, yet variants containing both mutations led to improved specific activity and enzyme expression, but with loss of solubility and the formation of inclusion bodies. D469S and R520Q combined synergistically to improve k(cat) 20-fold for PA, more than for any previous transketolase mutant. R520Q also doubled the specific activity of the previously identified D469T to create our most active transketolase mutant to date. Our results show that recombining active-site mutants obtained by saturation mutagenesis

Carbon flow from volcanic CO2 into soil microbial communities of a wetland mofette

DEFF Research Database (Denmark)

Beulig, Felix

2015-01-01

Effects of extremely high carbon dioxide (CO2) concentrations on soil microbial communities and associated processes are largely unknown. We studied a wetland area affected by spots of subcrustal CO2 degassing (mofettes) with focus on anaerobic autotrophic methanogenesis and acetogenesis because ...

Carbon flow from volcanic CO2 into soil microbial communities of a wetland mofette

DEFF Research Database (Denmark)

Beulig, Felix

2015-01-01

Effects of extremely high carbon dioxide (CO2) concentrations on soil microbial communities and associated processes are largely unknown. We studied a wetland area affected by spots of subcrustal CO2 degassing (mofettes) with focus on anaerobic autotrophic methanogenesis and acetogenesis because ......2-induced geochemical changes promoted anaerobic and acidophilic organisms and altered carbon turnover in affected soils.......Effects of extremely high carbon dioxide (CO2) concentrations on soil microbial communities and associated processes are largely unknown. We studied a wetland area affected by spots of subcrustal CO2 degassing (mofettes) with focus on anaerobic autotrophic methanogenesis and acetogenesis because...... the pore gas phase was largely hypoxic. Compared with a reference soil, the mofette was more acidic (ΔpH ~0.8), strongly enriched in organic carbon (up to 10 times), and exhibited lower prokaryotic diversity. It was dominated by methanogens and subdivision 1 Acidobacteria, which likely thrived under stable...

Elevated CO2 shifts the functional structure and metabolic potentials of soil microbial communities in a C4 agroecosystem.

Science.gov (United States)

Xiong, Jinbo; He, Zhili; Shi, Shengjing; Kent, Angela; Deng, Ye; Wu, Liyou; Van Nostrand, Joy D; Zhou, Jizhong

2015-03-20

Atmospheric CO2 concentration is continuously increasing, and previous studies have shown that elevated CO2 (eCO2) significantly impacts C3 plants and their soil microbial communities. However, little is known about effects of eCO2 on the compositional and functional structure, and metabolic potential of soil microbial communities under C4 plants. Here we showed that a C4 maize agroecosystem exposed to eCO2 for eight years shifted the functional and phylogenetic structure of soil microbial communities at both soil depths (0-5 cm and 5-15 cm) using EcoPlate and functional gene array (GeoChip 3.0) analyses. The abundances of key genes involved in carbon (C), nitrogen (N) and phosphorus (P) cycling were significantly stimulated under eCO2 at both soil depths, although some differences in carbon utilization patterns were observed between the two soil depths. Consistently, CO2 was found to be the dominant factor explaining 11.9% of the structural variation of functional genes, while depth and the interaction of depth and CO2 explained 5.2% and 3.8%, respectively. This study implies that eCO2 has profound effects on the functional structure and metabolic potential/activity of soil microbial communities associated with C4 plants, possibly leading to changes in ecosystem functioning and feedbacks to global change in C4 agroecosystems.

Social Network: a Cytoscape app for visualizing co-authorship networks.

Science.gov (United States)

Kofia, Victor; Isserlin, Ruth; Buchan, Alison M J; Bader, Gary D

2015-01-01

Networks that represent connections between individuals can be valuable analytic tools. The Social Network Cytoscape app is capable of creating a visual summary of connected individuals automatically. It does this by representing relationships as networks where each node denotes an individual and an edge linking two individuals represents a connection. The app focuses on creating visual summaries of individuals connected by co-authorship links in academia, created from bibliographic databases like PubMed, Scopus and InCites. The resulting co-authorship networks can be visualized and analyzed to better understand collaborative research networks or to communicate the extent of collaboration and publication productivity among a group of researchers, like in a grant application or departmental review report. It can also be useful as a research tool to identify important research topics, researchers and papers in a subject area.

Co-Cultures of Pseudomonas aeruginosa and Roseobacter denitrificans Reveal Shifts in Gene Expression Levels Compared to Solo Cultures

Directory of Open Access Journals (Sweden)

Crystal A. Conway

2012-01-01

Full Text Available Consistent biosynthesis of desired secondary metabolites (SMs from pure microbial cultures is often unreliable. In a proof-of-principle study to induce SM gene expression and production, we describe mixed “co-culturing” conditions and monitoring of messages via quantitative real-time PCR (qPCR. Gene expression of model bacterial strains (Pseudomonas aeruginosa PAO1 and Roseobacter denitrificans Och114 was analyzed in pure solo and mixed cocultures to infer the effects of interspecies interactions on gene expression in vitro, Two P. aeruginosa genes (PhzH coding for portions of the phenazine antibiotic pathway leading to pyocyanin (PCN and the RhdA gene for thiosulfate: cyanide sulfurtransferase (Rhodanese and two R. denitrificans genes (BetaLact for metallo-beta-lactamase and the DMSP gene for dimethylpropiothetin dethiomethylase were assessed for differential expression. Results showed that R. denitrificans DMSP and BetaLact gene expression became elevated in a mixed culture. In contrast, P. aeruginosa co-cultures with R. denitrificans or a third species did not increase target gene expression above control levels. This paper provides insight for better control of target SM gene expression in vitro and bypass complex genetic engineering manipulations.

Integration of liver gene co-expression networks and eGWAs analyses highlighted candidate regulators implicated in lipid metabolism in pigs.

Science.gov (United States)

Ballester, Maria; Ramayo-Caldas, Yuliaxis; Revilla, Manuel; Corominas, Jordi; Castelló, Anna; Estellé, Jordi; Fernández, Ana I; Folch, Josep M

2017-04-19

In the present study, liver co-expression networks and expression Genome Wide Association Study (eGWAS) were performed to identify DNA variants and molecular pathways implicated in the functional regulatory mechanisms of meat quality traits in pigs. With this purpose, the liver mRNA expression of 44 candidates genes related with lipid metabolism was analysed in 111 Iberian x Landrace backcross animals. The eGWAS identified 92 eSNPs located in seven chromosomal regions and associated with eight genes: CROT, CYP2U1, DGAT1, EGF, FABP1, FABP5, PLA2G12A, and PPARA. Remarkably, cis-eSNPs associated with FABP1 gene expression which may be determining the C18:2(n-6)/C18:3(n-3) ratio in backfat through the multiple interaction of DNA variants and genes were identified. Furthermore, a hotspot on SSC8 associated with the gene expression of eight genes was identified and the TBCK gene was pointed out as candidate gene regulating it. Our results also suggested that the PI3K-Akt-mTOR pathway plays an important role in the control of the analysed genes highlighting nuclear receptors as the NR3C1 or PPARA. Finally, sex-dimorphism associated with hepatic lipid metabolism was identified with over-representation of female-biased genes. These results increase our knowledge of the genetic architecture underlying fat composition traits.

Microbial co-habitation and lateral gene transfer: what transposases can tell us

Energy Technology Data Exchange (ETDEWEB)

Hooper, Sean D.; Mavromatis, Konstantinos; Kyrpides, Nikos C.

2009-03-01

Determining the habitat range for various microbes is not a simple, straightforward matter, as habitats interlace, microbes move between habitats, and microbial communities change over time. In this study, we explore an approach using the history of lateral gene transfer recorded in microbial genomes to begin to answer two key questions: where have you been and who have you been with? All currently sequenced microbial genomes were surveyed to identify pairs of taxa that share a transposase that is likely to have been acquired through lateral gene transfer. A microbial interaction network including almost 800 organisms was then derived from these connections. Although the majority of the connections are between closely related organisms with the same or overlapping habitat assignments, numerous examples were found of cross-habitat and cross-phylum connections. We present a large-scale study of the distributions of transposases across phylogeny and habitat, and find a significant correlation between habitat and transposase connections. We observed cases where phylogenetic boundaries are traversed, especially when organisms share habitats; this suggests that the potential exists for genetic material to move laterally between diverse groups via bridging connections. The results presented here also suggest that the complex dynamics of microbial ecology may be traceable in the microbial genomes.

Short-term responses and resistance of soil microbial community structure to elevated CO2 and N addition in grassland mesocosms.

Science.gov (United States)

Simonin, Marie; Nunan, Naoise; Bloor, Juliette M G; Pouteau, Valérie; Niboyet, Audrey

2017-05-01

Nitrogen (N) addition is known to affect soil microbial communities, but the interactive effects of N addition with other drivers of global change remain unclear. The impacts of multiple global changes on the structure of microbial communities may be mediated by specific microbial groups with different life-history strategies. Here, we investigated the combined effects of elevated CO2 and N addition on soil microbial communities using PLFA profiling in a short-term grassland mesocosm experiment. We also examined the linkages between the relative abundance of r- and K-strategist microorganisms and resistance of the microbial community structure to experimental treatments. N addition had a significant effect on microbial community structure, likely driven by concurrent increases in plant biomass and in soil labile C and N. In contrast, microbial community structure did not change under elevated CO2 or show significant CO2 × N interactions. Resistance of soil microbial community structure decreased with increasing fungal/bacterial ratio, but showed a positive relationship with the Gram-positive/Gram-negative bacterial ratio. Our findings suggest that the Gram-positive/Gram-negative bacteria ratio may be a useful indicator of microbial community resistance and that K-strategist abundance may play a role in the short-term stability of microbial communities under global change. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Analysis of Microbial Activity Under a Supercritical CO{sub 2} Atmosphere

Energy Technology Data Exchange (ETDEWEB)

Thompson, Janelle

2012-11-30

Because the extent and impact of microbial activity in deep saline aquifers during geologic sequestration is unknown, the objectives of this proposal were to: (1) characterize the growth requirements and optima of a biofilm-producing supercritical CO{sub 2}-tolerant microbial consortium (labeled MIT0212) isolated from hydrocarbons recovered from the Frio Ridge, TX carbon sequestration site; (2) evaluate the ability of this consortium to grow under simulated reservoir conditions associated with supercritical CO{sub 2} injection; (3) isolate and characterize individual microbial strains from this consortium; and (4) investigate the mechanisms of supercritical CO{sub 2} tolerance in isolated strains and the consortium through genome-enabled studies. Molecular analysis of genetic diversity in the consortium MIT0212 revealed a predominance of sequences closely related to species of the spore-forming genus Bacillus. Strain MIT0214 was isolated from this consortium and characterized by physiological profiling and genomic analysis. We have shown that the strain MIT0214 is an aerobic spore-former and capable of facultative anaerobic growth under both reducing N{sub 2} and CO{sub 2} atmospheres by fermentation and possibly anaerobic respiration. Strain MIT0214 is best adapted to anaerobic growth at pressures of 1 atm but is able to growth at elevated pressures After 1 week growth was observed at pressures as high as 27 atm (N{sub 2}) or 9 atm (CO{sub 2}) and after 26-30 days growth can be observed under supercritical CO{sub 2}. In addition, we have determined that spores of strain B. cereus MIT0214 are tolerant of both direct and indirect exposure to supercritical CO{sub 2}. Additional physiological characterization under aerobic conditions have revealed MIT0214 is able to grow from temperature of 21 to 45 °C and salinities 0.01 to 40 g/L NaCl with optimal growth occurring at 30°C and from 1 - 5 g NaCl/L. The genome sequence of B. cereus MIT0214 shared 89 to 91% of genes

Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803

International Nuclear Information System (INIS)

Pei, Guangsheng; Chen, Lei; Wang, Jiangxin; Qiao, Jianjun; Zhang, Weiwen

2014-01-01

Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein–protein interaction network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.

Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803

Energy Technology Data Exchange (ETDEWEB)

Pei, Guangsheng; Chen, Lei; Wang, Jiangxin; Qiao, Jianjun, E-mail: jianjunq@tju.edu.cn; Zhang, Weiwen, E-mail: jianjunq@tju.edu.cn [Laboratory of Synthetic Microbiology, School of Chemical Engineering and Technology, Tianjin University, Tianjin (China); Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin (China); SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering, Tianjin (China)

2014-11-03

Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein–protein interaction network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.

A powerful nonparametric method for detecting differentially co-expressed genes: distance correlation screening and edge-count test.

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Zhang, Qingyang

2018-05-16

Differential co-expression analysis, as a complement of differential expression analysis, offers significant insights into the changes in molecular mechanism of different phenotypes. A prevailing approach to detecting differentially co-expressed genes is to compare Pearson's correlation coefficients in two phenotypes. However, due to the limitations of Pearson's correlation measure, this approach lacks the power to detect nonlinear changes in gene co-expression which is common in gene regulatory networks. In this work, a new nonparametric procedure is proposed to search differentially co-expressed gene pairs in different phenotypes from large-scale data. Our computational pipeline consisted of two main steps, a screening step and a testing step. The screening step is to reduce the search space by filtering out all the independent gene pairs using distance correlation measure. In the testing step, we compare the gene co-expression patterns in different phenotypes by a recently developed edge-count test. Both steps are distribution-free and targeting nonlinear relations. We illustrate the promise of the new approach by analyzing the Cancer Genome Atlas data and the METABRIC data for breast cancer subtypes. Compared with some existing methods, the new method is more powerful in detecting nonlinear type of differential co-expressions. The distance correlation screening can greatly improve computational efficiency, facilitating its application to large data sets.

Co-expression analysis identifies CRC and AP1 the regulator of Arabidopsis fatty acid biosynthesis.

Science.gov (United States)

Han, Xinxin; Yin, Linlin; Xue, Hongwei

2012-07-01

Fatty acids (FAs) play crucial rules in signal transduction and plant development, however, the regulation of FA metabolism is still poorly understood. To study the relevant regulatory network, fifty-eight FA biosynthesis genes including de novo synthases, desaturases and elongases were selected as "guide genes" to construct the co-expression network. Calculation of the correlation between all Arabidopsis thaliana (L.) genes with each guide gene by Arabidopsis co-expression dating mining tools (ACT) identifies 797 candidate FA-correlated genes. Gene ontology (GO) analysis of these co-expressed genes showed they are tightly correlated to photosynthesis and carbohydrate metabolism, and function in many processes. Interestingly, 63 transcription factors (TFs) were identified as candidate FA biosynthesis regulators and 8 TF families are enriched. Two TF genes, CRC and AP1, both correlating with 8 FA guide genes, were further characterized. Analyses of the ap1 and crc mutant showed the altered total FA composition of mature seeds. The contents of palmitoleic acid, stearic acid, arachidic acid and eicosadienoic acid are decreased, whereas that of oleic acid is increased in ap1 and crc seeds, which is consistent with the qRT-PCR analysis revealing the suppressed expression of the corresponding guide genes. In addition, yeast one-hybrid analysis and electrophoretic mobility shift assay (EMSA) revealed that CRC can bind to the promoter regions of KCS7 and KCS15, indicating that CRC may directly regulate FA biosynthesis. © 2012 Institute of Botany, Chinese Academy of Sciences.

Deep microbial life in the Altmark natural gas reservoir: baseline characterization prior CO2 injection

Science.gov (United States)

Morozova, Daria; Shaheed, Mina; Vieth, Andrea; Krüger, Martin; Kock, Dagmar; Würdemann, Hilke

2010-05-01

Within the framework of the CLEAN project (CO2 Largescale Enhanced gas recovery in the Altmark Natural gas field) technical basics with special emphasis on process monitoring are explored by injecting CO2 into a gas reservoir. Our study focuses on the investigation of the in-situ microbial community of the Rotliegend natural gas reservoir in the Altmark, located south of the city Salzwedel, Germany. In order to characterize the microbial life in the extreme habitat we aim to localize and identify microbes including their metabolism influencing the creation and dissolution of minerals. The ability of microorganisms to speed up dissolution and formation of minerals might result in changes of the local permeability and the long-term safety of CO2 storage. However, geology, structure and chemistry of the reservoir rock and the cap rock as well as interaction with saline formation water and natural gases and the injected CO2 affect the microbial community composition and activity. The reservoir located at the depth of about 3500m, is characterised by high salinity fluid and temperatures up to 127° C. It represents an extreme environment for microbial life and therefore the main focus is on hyperthermophilic, halophilic anaerobic microorganisms. In consequence of the injection of large amounts of CO2 in the course of a commercial EGR (Enhanced Gas Recovery) the environmental conditions (e.g. pH, temperature, pressure and solubility of minerals) for the autochthonous microorganisms will change. Genetic profiling of amplified 16S rRNA genes are applied for detecting structural changes in the community by using PCR- SSCP (PCR-Single-Strand-Conformation Polymorphism) and DGGE (Denaturing Gradient Gel Electrophoresis). First results of the baseline survey indicate the presence of microorganisms similar to representatives from other saline, hot, anoxic, deep environments. However, due to the hypersaline and hyperthermophilic reservoir conditions, cell numbers are low, so that

Gene co-expression networks and profiles reveal potential biomarkers of boar taint in pigs

DEFF Research Database (Denmark)

Drag, Markus; Skinkyté-Juskiené, R.; Do, Duy Ngoc

synthesis. In testis, >80 DE genes were functionally classified by the PANTHER tool to “Gonadotropin releasing hormone receptor” and “Wnt signaling” pathways which play a role in reproductive maturation and proliferation of spermatogonia, respectively. WGCNA was used to build co-expression modules...

Microbial expression profiles in the rhizosphere of willows depend on soil contamination

Science.gov (United States)

Yergeau, Etienne; Sanschagrin, Sylvie; Maynard, Christine; St-Arnaud, Marc; Greer, Charles W

2014-01-01

The goal of phytoremediation is to use plants to immobilize, extract or degrade organic and inorganic pollutants. In the case of organic contaminants, plants essentially act indirectly through the stimulation of rhizosphere microorganisms. A detailed understanding of the effect plants have on the activities of rhizosphere microorganisms could help optimize phytoremediation systems and enhance their use. In this study, willows were planted in contaminated and non-contaminated soils in a greenhouse, and the active microbial communities and the expression of functional genes in the rhizosphere and bulk soil were compared. Ion Torrent sequencing of 16S rRNA and Illumina sequencing of mRNA were performed. Genes related to carbon and amino-acid uptake and utilization were upregulated in the willow rhizosphere, providing indirect evidence of the compositional content of the root exudates. Related to this increased nutrient input, several microbial taxa showed a significant increase in activity in the rhizosphere. The extent of the rhizosphere stimulation varied markedly with soil contamination levels. The combined selective pressure of contaminants and rhizosphere resulted in higher expression of genes related to competition (antibiotic resistance and biofilm formation) in the contaminated rhizosphere. Genes related to hydrocarbon degradation were generally more expressed in contaminated soils, but the exact complement of genes induced was different for bulk and rhizosphere soils. Together, these results provide an unprecedented view of microbial gene expression in the plant rhizosphere during phytoremediation. PMID:24067257

Co-expression modules construction by WGCNA and identify potential prognostic markers of uveal melanoma.

Science.gov (United States)

Wan, Qi; Tang, Jing; Han, Yu; Wang, Dan

2018-01-01

Uveal melanoma is an aggressive cancer which has a high percentage recurrence and with a worse prognosis. Identify the potential prognostic markers of uveal melanoma may provide information for early detection of recurrence and treatment. RNA sequence data of uveal melanoma and patient clinic traits were obtained from The Cancer Genome Atlas (TCGA) database. Co-expression modules were built by weighted gene co -expression network analysis (WGCNA) and applied to investigate the relationship underlying modules and clinic traits. Besides, functional enrichment analysis was performed on these co-expression genes from interested modules. First, using WGCNA, identified 21 co-expression modules were constructed by the 10975 genes from the 80 human uveal melanoma samples. The number of genes in these modules ranged from 42 to 5091. Found four co -expression modules significantly correlated with three clinic traits (status, recurrence and recurrence Time). Module red, and purple positively correlated with patient's life status and recurrence Time. Module green positively correlates with recurrence. The result of functional enrichment analysis showed that the module magenta was mainly enriched genetic material assemble processes, the purple module was mainly enriched in tissue homeostasis and melanosome membrane and the module red was mainly enriched metastasis of cell, suggesting its critical role in the recurrence and development of the disease. Additionally, identified the hug gene (top connectivity with other genes) in each module. The hub gene SLC17A7, NTRK2, ABTB1 and ADPRHL1 might play a vital role in recurrence of uveal melanoma. Our findings provided the framework of co-expression gene modules of uveal melanoma and identified some prognostic markers might be detection of recurrence and treatment for uveal melanoma. Copyright © 2017 Elsevier Ltd. All rights reserved.

Determination of microbial versus root-produced CO2 in an agricultural ecosystem by means of δ13CO2 measurements in soil air

NARCIS (Netherlands)

Schüßler, Wolfram; Neubert, Rolf; Levin, Ingeborg; Fischer, Natalie; Sonntag, Christian

2000-01-01

The amounts of microbial and root-respired CO2 in a maize/winter wheat agricultural system in south western Germany were investigated by measurements of the CO2 mixing ratio and the 13C/12C ratio in soil air. CO2 fluxes at the soil surface for the period of investigation (1993–1995) were also

Network Compression as a Quality Measure for Protein Interaction Networks

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Royer, Loic; Reimann, Matthias; Stewart, A. Francis; Schroeder, Michael

2012-01-01

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients. PMID:22719828

An extensive (co-expression analysis tool for the cytochrome P450 superfamily in Arabidopsis thaliana

Directory of Open Access Journals (Sweden)

Provart Nicholas J

2008-04-01

Full Text Available Abstract Background Sequencing of the first plant genomes has revealed that cytochromes P450 have evolved to become the largest family of enzymes in secondary metabolism. The proportion of P450 enzymes with characterized biochemical function(s is however very small. If P450 diversification mirrors evolution of chemical diversity, this points to an unexpectedly poor understanding of plant metabolism. We assumed that extensive analysis of gene expression might guide towards the function of P450 enzymes, and highlight overlooked aspects of plant metabolism. Results We have created a comprehensive database, 'CYPedia', describing P450 gene expression in four data sets: organs and tissues, stress response, hormone response, and mutants of Arabidopsis thaliana, based on public Affymetrix ATH1 microarray expression data. P450 expression was then combined with the expression of 4,130 re-annotated genes, predicted to act in plant metabolism, for co-expression analyses. Based on the annotation of co-expressed genes from diverse pathway annotation databases, co-expressed pathways were identified. Predictions were validated for most P450s with known functions. As examples, co-expression results for P450s related to plastidial functions/photosynthesis, and to phenylpropanoid, triterpenoid and jasmonate metabolism are highlighted here. Conclusion The large scale hypothesis generation tools presented here provide leads to new pathways, unexpected functions, and regulatory networks for many P450s in plant metabolism. These can now be exploited by the community to validate the proposed functions experimentally using reverse genetics, biochemistry, and metabolic profiling.

Construction and analysis of the transcription factor-microRNA co-regulatory network response to Mycobacterium tuberculosis: a view from the blood.

Science.gov (United States)

Lin, Yan; Duan, Zipeng; Xu, Feng; Zhang, Jiayuan; Shulgina, Marina V; Li, Fan

2017-01-01

Mycobacterium tuberculosis ( Mtb ) infection has been regional outbreak, recently. The traditional focus on the patterns of "reductionism" which was associated with single molecular changes has been unable to meet the demand of early diagnosis and clinical application when current tuberculosis infection happened. In this study, we employed a systems biology approach to collect large microarray data sets including mRNAs and microRNAs (miRNAs) to identify the differentially expressed mRNAs and miRNAs in the whole blood of TB patients. The aim was to identify key genes associated with the immune response in the pathogenic process of tuberculosis by analyzing the co-regulatory network that was consisted of transcription factors and miRNAs as well as their target genes. The network along with their co-regulatory genes was analyzed utilizing Transcriptional Regulatory Element Database (TRED) and Database for Annotation, Visualization and Integrated Discovery (DAVID). We got 21 (19 up-regulated and 2 down-regulated) differentially expressed genes that were co-regulated by transcription factors and miRNAs. KEGG pathway enrichment analysis showed that the 21 differentially expressed genes were predominantly involved in Tuberculosis signaling pathway, which may play a major role in tuberculosis biological process. Quantitative real-time PCR was performed to verify the over expression of co-regulatory genes ( FCGR1A and CEBPB ). The genetic expression was correlated with clinicopathological characteristics in TB patients and inferences drawn. Our results suggest the TF-miRNA gene co-regulatory network may help us further understand the molecular mechanism of immune response to tuberculosis and provide us a new angle of future biomarker and therapeutic targets.

Microbial Electrolytic Capture, Separation and Regeneration of CO2 for Biogas Upgrading.

Science.gov (United States)

Jin, Xiangdan; Zhang, Yifeng; Li, Xiaohu; Zhao, Nannan; Angelidaki, Irini

2017-08-15

Biogas upgrading to natural gas quality is essential for the efficient use of biogas in various applications. Carbon dioxide (CO 2 ) which constitutes a major part of the biogas is generally removed by physicochemical methods. However, most of the methods are expensive and often present environmental challenges. In this study, an innovative microbial electrolytic system was developed to capture, separate and regenerate CO 2 for biogas upgrading without external supply of chemicals, and potentially to treat wastewater. The new system was operated at varied biogas flow rates and external applied voltages. CO 2 was effectively separated from the raw biogas and the CH 4 content in the outlet reached as high as 97.0 ± 0.2% at the external voltage of 1.2 V and gas flow rate of 19.6 mL/h. Regeneration of CO 2 was also achieved in the regeneration chamber with low pH (1.34 ± 0.04). The relatively low electric energy consumption (≤0.15 kWh/m 3 biogas) along with the H 2 production which can contribute to the energy input makes the overall energy need of the system low, and thereby makes the technology promising. This work provides the first attempt for development of a sustainable biogas upgrading technology and potentially expands the application of microbial electrochemical technologies.

The interaction of soil phototrophs and fungi with pH and their impact on soil CO2, CO18O and OCS exchange.

Science.gov (United States)

Sauze, Joana; Ogée, Jérôme; Maron, Pierre-Alain; Crouzet, Olivier; Nowak, Virginie; Wohl, Steven; Kaisermann, Aurore; Jones, Sam P; Wingate, Lisa

2017-12-01

The stable oxygen isotope composition of atmospheric CO 2 and the mixing ratio of carbonyl sulphide (OCS) are potential tracers of biospheric CO 2 fluxes at large scales. However, the use of these tracers hinges on our ability to understand and better predict the activity of the enzyme carbonic anhydrase (CA) in different soil microbial groups, including phototrophs. Because different classes of the CA family (α, β and γ) may have different affinities to CO 2 and OCS and their expression should also vary between different microbial groups, differences in the community structure could impact the 'community-integrated' CA activity differently for CO 2 and OCS. Four soils of different pH were incubated in the dark or with a diurnal cycle for forty days to vary the abundance of native phototrophs. Fluxes of CO 2 , CO 18 O and OCS were measured to estimate CA activity alongside the abundance of bacteria, fungi and phototrophs. The abundance of soil phototrophs increased most at higher soil pH. In the light, the strength of the soil CO 2 sink and the CA-driven CO 2 -H 2 O isotopic exchange rates correlated with phototrophs abundance. OCS uptake rates were attributed to fungi whose abundance was positively enhanced in alkaline soils but only in the presence of increased phototrophs. Our findings demonstrate that soil-atmosphere CO 2 , OCS and CO 18 O fluxes are strongly regulated by the microbial community structure in response to changes in soil pH and light availability and supports the idea that different members of the microbial community express different classes of CA, with different affinities to CO 2 and OCS.

Improvisation and co-expression in explorative digital music systems

DEFF Research Database (Denmark)

Hansen, Anne-Marie Skriver

relationships. The benefit of the digitally networked electronic musical instruments is that particular patterns of co-expression can be found and mediated by the music system (that also contains all individual instruments) in ways that make players aware of their mutual play and perhaps will encourage players...... other when they are given a number of creative restrictions in the sonic/musical material that they interact with. The benefit with digital musical instruments is that non-musicians and novices can get access to limited musical material that they are immediately able to master without any musical...... be developed in future designs. The Wacom® pen tablet, a simple drawing interface, was turned into an array of digital musical instruments in order to investigate the benefit of networked musical instruments in the context of the genre of casual games. Through qualitative and quantitative studies of player...

Effect of elevated CO2 on degradation of azoxystrobin and soil microbial activity in rice soil.

Science.gov (United States)

Manna, Suman; Singh, Neera; Singh, V P

2013-04-01

An experiment was conducted in open-top chambers (OTC) to study the effect of elevated CO2 (580 ± 20 μmol mol(-1)) on azoxystrobin degradation and soil microbial activities. Results indicated that elevated CO2 did not have any significant effect on the persistence of azoxystrobin in rice-planted soil. The half-life values for the azoxystrobin in rice soils were 20.3 days in control (rice grown at ambient CO2 outdoors), 19.3 days in rice grown under ambient CO2 atmosphere in OTC, and 17.5 days in rice grown under elevated CO2 atmosphere in OTC. Azoxystrobin acid was recovered as the only metabolite of azoxystrobin, but it did not accumulate in the soil/water and was further metabolized. Elevated CO2 enhanced soil microbial biomass (MBC) and alkaline phosphatase activity of soil. Compared with rice grown at ambient CO2 (both outdoors and in OTC), the soil MBC at elevated CO2 increased by twofold. Elevated CO2 did not affect dehydrogenase, fluorescein diacetate, and acid phosphatase activity. Azoxystrobin application to soils, both ambient and elevated CO2, inhibited alkaline phosphates activity, while no effect was observed on other enzymes. Slight increase (1.8-2 °C) in temperature inside OTC did not affect microbial parameters, as similar activities were recorded in rice grown outdoors and in OTC at ambient CO2. Higher MBC in soil at elevated CO2 could be attributed to increased carbon availability in the rhizosphere via plant metabolism and root secretion; however, it did not significantly increase azoxystrobin degradation, suggesting that pesticide degradation was not the result of soil MBC alone. Study suggested that increased CO2 levels following global warming might not adversely affect azoxystrobin degradation. However, global warming is a continuous and cumulative process, therefore, long-term studies are necessary to get more realistic assessment of global warming on fate of pesticide.

A comprehensive analysis on preservation patterns of gene co-expression networks during Alzheimer's disease progression.

Science.gov (United States)

Ray, Sumanta; Hossain, Sk Md Mosaddek; Khatun, Lutfunnesa; Mukhopadhyay, Anirban

2017-12-20

Alzheimer's disease (AD) is a chronic neuro-degenerative disruption of the brain which involves in large scale transcriptomic variation. The disease does not impact every regions of the brain at the same time, instead it progresses slowly involving somewhat sequential interaction with different regions. Analysis of the expression patterns of the genes in different regions of the brain influenced in AD surely contribute for a enhanced comprehension of AD pathogenesis and shed light on the early characterization of the disease. Here, we have proposed a framework to identify perturbation and preservation characteristics of gene expression patterns across six distinct regions of the brain ("EC", "HIP", "PC", "MTG", "SFG", and "VCX") affected in AD. Co-expression modules were discovered considering a couple of regions at once. These are then analyzed to know the preservation and perturbation characteristics. Different module preservation statistics and a rank aggregation mechanism have been adopted to detect the changes of expression patterns across brain regions. Gene ontology (GO) and pathway based analysis were also carried out to know the biological meaning of preserved and perturbed modules. In this article, we have extensively studied the preservation patterns of co-expressed modules in six distinct brain regions affected in AD. Some modules are emerged as the most preserved while some others are detected as perturbed between a pair of brain regions. Further investigation on the topological properties of preserved and non-preserved modules reveals a substantial association amongst "betweenness centrality" and "degree" of the involved genes. Our findings may render a deeper realization of the preservation characteristics of gene expression patterns in discrete brain regions affected by AD.

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates.

Science.gov (United States)

Xia, Li C; Steele, Joshua A; Cram, Jacob A; Cardon, Zoe G; Simmons, Sheri L; Vallino, Joseph J; Fuhrman, Jed A; Sun, Fengzhu

2011-01-01

The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa.

Inferring gene networks from discrete expression data

KAUST Repository

Zhang, L.

2013-07-18

The modeling of gene networks from transcriptional expression data is an important tool in biomedical research to reveal signaling pathways and to identify treatment targets. Current gene network modeling is primarily based on the use of Gaussian graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which generate counts of mRNAtranscripts in cell samples.We propose a generalized linear model to fit the discrete gene expression data and assume that the log ratios of the mean expression levels follow a Gaussian distribution.We restrict the gene network structures to decomposable graphs and derive the graphs by selecting the covariance matrix of the Gaussian distribution with the hyper-inverse Wishart priors. Furthermore, we incorporate prior network models based on gene ontology information, which avails existing biological information on the genes of interest. We conduct simulation studies to examine the performance of our discrete graphical model and apply the method to two real datasets for gene network inference. © The Author 2013. Published by Oxford University Press. All rights reserved.

A critical review on the interaction of substrate nutrient balance and microbial community structure and function in anaerobic co-digestion.

Science.gov (United States)

Xu, Rong; Zhang, Kai; Liu, Pu; Khan, Aman; Xiong, Jian; Tian, Fake; Li, Xiangkai

2018-01-01

Anaerobic co-digestion generally results in a higher yield of biogas than mono-digestion, hence co-digestion has become a topic of general interest in recent studies of anaerobic digestion. Compared with mono-digestion, co-digestion utilizes multiple substrates. The balance of substrate nutrient in co-digestion comprises better adjustments of C/N ratio, pH, moisture, trace elements, and dilution of toxic substances. All of these changes could result in positive shifts in microbial community structure and function in the digestion processes and consequent augmentation of biogas production. Nevertheless, there have been few reviews on the interaction of nutrient and microbial community in co-digestions. The objective of this review is to investigate recent achievements and perspectives on the interaction of substrate nutrient balance and microbial community structure and function. This may provide valuable information on the optimization of combinations of substrates and prediction of bioreactor performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Microbial electrolysis desalination and chemical-production cell for CO2 sequestration

KAUST Repository

Zhu, Xiuping

2014-05-01

Mineral carbonation can be used for CO2 sequestration, but the reaction rate is slow. In order to accelerate mineral carbonation, acid generated in a microbial electrolysis desalination and chemical-production cell (MEDCC) was examined to dissolve natural minerals rich in magnesium/calcium silicates (serpentine), and the alkali generated by the same process was used to absorb CO2 and precipitate magnesium/calcium carbonates. The concentrations of Mg2+ and Ca2+ dissolved from serpentine increased 20 and 145 times by using the acid solution. Under optimal conditions, 24mg of CO2 was absorbed into the alkaline solution and 13mg of CO2 was precipitated as magnesium/calcium carbonates over a fed-batch cycle (24h). Additionally, the MEDCC removed 94% of the COD (initially 822mg/L) and achieved 22% desalination (initially 35g/L NaCl). These results demonstrate the viability of this process for effective CO2 sequestration using renewable organic matter and natural minerals. © 2014 Elsevier Ltd.

Effects of co-composting of lincomycin mycelia dregs with furfural slag on lincomycin degradation, maturity and microbial communities.

Science.gov (United States)

Ren, Shengtao; Guo, Xiali; Lu, Aqian; Guo, Xiaoying; Wang, Yan; Sun, Guoping; Guo, Weiwei; Ren, Chaobin; Wang, Lianzhong

2018-05-26

This paper investigated the effect of co-composting of lincomycin mycelia dregs (LMDs) with furfural slag on the degradation of lincomycin, maturity and microbial communities. Results showed that after 66 days composting, the concentration of lincomycin was removed above 99%. The final pH, C/N and germination index (GI) all met the national standards in maturity. Enumeration of total cultivable microbes showed the composting process was not inhibited by the addition of LMDs. Microbial diversity suggested that co-composting was beneficial to increase the abundance and diversity of bacterial communities for LMDs' treatment. Canonical correlation analysis (CCA) indicated the bacteria communities were strongly affected by residual lincomycin, with lincomycin reduced greatly, microbial communities of T and CK became similar at the end of composting. The potential bacteria to degrade lincomycin were Anaerococcus, Peptostreptococcus, and Lactobacillus. Based on these results, this research indicated that the co-composting was a feasible treatment for LMDs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Measuring co-authorship and networking-adjusted scientific impact.

Directory of Open Access Journals (Sweden)

John P A Ioannidis

Full Text Available Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I(1 for a single scientist as the number of authors who appear in at least I(1 papers of the specific scientist. For a group of scientists or institution, I(n is defined as the number of authors who appear in at least I(n papers that bear the affiliation of the group or institution. I(1 depends on the number of papers authored N(p. The power exponent R of the relationship between I(1 and N(p categorizes scientists as solitary (R>2.5, nuclear (R = 2.25-2.5, networked (R = 2-2.25, extensively networked (R = 1.75-2 or collaborators (R<1.75. R may be used to adjust for co-authorship networking the citation impact of a scientist. I(n similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.

Low Microbial Diversity and Abnormal Microbial Succession Is Associated with Necrotizing Enterocolitis in Preterm Infants

Science.gov (United States)

Dobbler, Priscila T.; Procianoy, Renato S.; Mai, Volker; Silveira, Rita C.; Corso, Andréa L.; Rojas, Bruna S.; Roesch, Luiz F. W.

2017-01-01

Despite increased efforts, the diverse etiologies of Necrotizing Enterocolitis (NEC) have remained largely elusive. Clinical predictors of NEC remain ill-defined and currently lack sufficient specificity. The development of a thorough understanding of initial gut microbiota colonization pattern in preterm infants might help to improve early detection or prediction of NEC and its associated morbidities. Here we compared the fecal microbiota successions, microbial diversity, abundance and structure of newborns that developed NEC with preterm controls. A 16S rRNA based microbiota analysis was conducted in a total of 132 fecal samples that included the first stool (meconium) up until the 5th week of life or NEC diagnosis from 40 preterm babies (29 controls and 11 NEC cases). A single phylotype matching closest to the Enterobacteriaceae family correlated strongly with NEC. In DNA from the sample with the greatest abundance of this phylotype additional shotgun metagenomic sequencing revealed Citrobacter koseri and Klebsiella pneumoniae as the dominating taxa. These two taxa might represent suitable microbial biomarker targets for early diagnosis of NEC. In NEC cases, we further detected lower microbial diversity and an abnormal succession of the microbial community before NEC diagnosis. Finally, we also detected a disruption in anaerobic microorganisms in the co-occurrence network of meconium samples from NEC cases. Our data suggest that a strong dominance of Citrobacter koseri and/or Klebsiella pneumoniae, low diversity, low abundance of Lactobacillus, as well as an altered microbial-network structure during the first days of life, correlate with NEC risk in preterm infants. Confirmation of these findings in other hospitals might facilitate the development of a microbiota based screening approach for early detection of NEC. PMID:29187842

Nuclear based technologies for estimating microbial protein supply in ruminant livestock. Proceedings of the second research co-ordination meeting of a co-ordinated research project (phase 1)

International Nuclear Information System (INIS)

1999-06-01

The Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture through its Co-ordinated Research Projects (CRPs), has been assisting national agricultural research systems in Member States to develop and apply nuclear and related techniques for improving livestock productivity. The programmes have focused on animal nutrition, animal reproduction and more recently on animal nutrition/reproduction interactions with emphasis on smallholder farming systems. The measurement of microbial protein supply to ruminant livestock has been an important area of research in ruminant nutrition. An estimate of microbial protein contribution to the intestinal protein flow is important for estimating the protein requirement of ruminant animals. Understanding the process of microbial protein synthesis has been difficult however, and due to the lack of simple and accurate methods for measuring microbial protein production in vivo, the methods used are based on complex microbial markers which require surgically prepared animals. As a result of a consultants meeting held in May 1995 to advise the Joint FAO/IAEA Division on the feasibility of using nuclear and related techniques for the development and validation of techniques for measuring microbial protein supply in ruminant animals, an FAO/IAEA Co-ordinated Research Project on Development, Standardization and Validation of Nuclear Based Technologies for Measuring Microbial Protein Supply in Ruminant Livestock for Improving Productivity was initiated in 1996, with a view to validating and adapting this technology for use in developing countries. To assist scientists participating in the CRP, a laboratory manual containing experimental protocols and methodologies for standardization and validation of the urine purine derivative technique and the development of models to suit local conditions, was published as IAEA-TECDOC-945. The present publication contains the final reports from participants in Phase 1 of the project

Nuclear based technologies for estimating microbial protein supply in ruminant livestock. Proceedings of the second research co-ordination meeting of a co-ordinated research project (phase 1)

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-06-01

The Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture through its Co-ordinated Research Projects (CRPs), has been assisting national agricultural research systems in Member States to develop and apply nuclear and related techniques for improving livestock productivity. The programmes have focused on animal nutrition, animal reproduction and more recently on animal nutrition/reproduction interactions with emphasis on smallholder farming systems. The measurement of microbial protein supply to ruminant livestock has been an important area of research in ruminant nutrition. An estimate of microbial protein contribution to the intestinal protein flow is important for estimating the protein requirement of ruminant animals. Understanding the process of microbial protein synthesis has been difficult however, and due to the lack of simple and accurate methods for measuring microbial protein production in vivo, the methods used are based on complex microbial markers which require surgically prepared animals. As a result of a consultants meeting held in May 1995 to advise the Joint FAO/IAEA Division on the feasibility of using nuclear and related techniques for the development and validation of techniques for measuring microbial protein supply in ruminant animals, an FAO/IAEA Co-ordinated Research Project on Development, Standardization and Validation of Nuclear Based Technologies for Measuring Microbial Protein Supply in Ruminant Livestock for Improving Productivity was initiated in 1996, with a view to validating and adapting this technology for use in developing countries. To assist scientists participating in the CRP, a laboratory manual containing experimental protocols and methodologies for standardization and validation of the urine purine derivative technique and the development of models to suit local conditions, was published as IAEA-TECDOC-945. The present publication contains the final reports from participants in Phase 1 of the project

Relation of Transcriptional Factors to the Expression and Activity of Cytochrome P450 and UDP-Glucuronosyltransferases 1A in Human Liver: Co-Expression Network Analysis.

Science.gov (United States)

Zhong, Shilong; Han, Weichao; Hou, Chuqi; Liu, Junjin; Wu, Lili; Liu, Menghua; Liang, Zhi; Lin, Haoming; Zhou, Lili; Liu, Shuwen; Tang, Lan

2017-01-01

Cytochrome P450 (CYPs) and UDP-glucuronosyltransferases (UGTs) play important roles in the metabolism of exogenous and endogenous compounds. The gene transcription of CYPs and UGTs can be enhanced or reduced by transcription factors (TFs). This study aims to explore novel TFs involved in the regulatory network of human hepatic UGTs/CYPs. Correlations between the transcription levels of 683 key TFs and CYPs/UGTs in three different human liver expression profiles (n = 640) were calculated first. Supervised weighted correlation network analysis (sWGCNA) was employed to define hub genes among the selected TFs. The relationship among 17 defined TFs, CYPs/UGTs expression, and activity were evaluated in 30 liver samples from Chinese patients. The positive controls (e.g., PPARA, NR1I2, NR1I3) and hub TFs (NFIA, NR3C2, and AR) in the Grey sWGCNA Module were significantly and positively associated with CYPs/UGTs expression. And the cancer- or inflammation-related TFs (TEAD4, NFKB2, and NFKB1) were negatively associated with mRNA expression of CYP2C9/CYP2E1/UGT1A9. Furthermore, the effect of NR1I2, NR1I3, AR, TEAD4, and NFKB2 on CYP450/UGT1A gene transcription translated into moderate influences on enzyme activities. To our knowledge, this is the first study to integrate Gene Expression Omnibus (GEO) datasets and supervised weighted correlation network analysis (sWGCNA) for defining TFs potentially related to CYPs/UGTs. We detected several novel TFs involved in the regulatory network of hepatic CYPs and UGTs in humans. Further validation and investigation may reveal their exact mechanism of CYPs/UGTs regulation.

Network Completion for Static Gene Expression Data

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Natsu Nakajima

2014-01-01

Full Text Available We tackle the problem of completing and inferring genetic networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which addition of edges and deletion of edges are basic modification operations. For this problem, we present a new method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data. Furthermore, we demonstrate that our proposed method can distinguish the differences between two types of genetic networks under stationary conditions from lung cancer and normal gene expression data.

Microbial electrochemical separation of CO2 for biogas upgrading

DEFF Research Database (Denmark)

Kokkoli, Argyro; Zhang, Yifeng; Angelidaki, Irini

2018-01-01

was obtained at 1.2 V, inlet biogas rate of 0.088 mL/h/mL reactor and NaCl concentration of 100 mM at a 5-day operation. Meanwhile, the organic matter of the domestic wastewater in the anode was almost completely removed at the end. The study demonstrated a new sustainable way to simultaneously upgrade biogas......Biogas upgrading to natural gas quality has been under focus the recent years for increasing the utilization potential of biogas. Conventional methods for CO2 removal are expensive and have environmental challenges, such as increased emissions of methane in the atmosphere with serious greenhouse...... impact. In this study, an innovative microbial electrochemical separation cell (MESC) was developed to in-situ separate and regenerate CO2 via alkali and acid regeneration. The MESC was tested under different applied voltages, inlet biogas rates and electrolyte concentrations. Pure biomethane...

Wind and sunlight shape microbial diversity in surface waters of the North Pacific Subtropical Gyre.

Science.gov (United States)

Bryant, Jessica A; Aylward, Frank O; Eppley, John M; Karl, David M; Church, Matthew J; DeLong, Edward F

2016-06-01

Few microbial time-series studies have been conducted in open ocean habitats having low seasonal variability such as the North Pacific Subtropical Gyre (NPSG), where surface waters experience comparatively mild seasonal variation. To better describe microbial seasonal variability in this habitat, we analyzed rRNA amplicon and shotgun metagenomic data over two years at the Hawaii Ocean Time-series Station ALOHA. We postulated that this relatively stable habitat might reveal different environmental factors that influence planktonic microbial community diversity than those previously observed in more seasonally dynamic habitats. Unexpectedly, the data showed that microbial diversity at 25 m was positively correlated with average wind speed 3 to 10 days prior to sampling. In addition, microbial community composition at 25 m exhibited significant correlations with solar irradiance. Many bacterial groups whose relative abundances varied with solar radiation corresponded to taxa known to exhibit strong seasonality in other oceanic regions. Network co-correlation analysis of 25 m communities showed seasonal transitions in composition, and distinct successional cohorts of co-occurring phylogenetic groups. Similar network analyses of metagenomic data also indicated distinct seasonality in genes originating from cyanophage, and several bacterial clades including SAR116 and SAR324. At 500 m, microbial community diversity and composition did not vary significantly with any measured environmental parameters. The minimal seasonal variability in the NPSG facilitated detection of more subtle environmental influences, such as episodic wind variation, on surface water microbial diversity. Community composition in NPSG surface waters varied in response to solar irradiance, but less dramatically than reported in other ocean provinces.

A new method to construct co-author networks

Science.gov (United States)

Liu, Jie; Li, Yunpeng; Ruan, Zichan; Fu, Guangyuan; Chen, Xiaowu; Sadiq, Rehan; Deng, Yong

2015-02-01

In this paper, we propose a new method to evaluate the importance of nodes in a given network. The proposed method is based on the PageRank algorithm. However, we have made necessary improvements to combine the importance of the node itself and that of its community status. First, we propose an improved method to better evaluate the real impact of a paper. The proposed method calibrates the real influence of a paper over time. Then we propose a scheme of evaluating the contribution of each author in a paper. We later develop a new method to combine the information of the author itself and the structure of the co-author network. We use the number of co-authorship to calculate the effective distance between two authors, and evaluate the strength of their influence to each other with the law of gravity. The strength of influence is used to build a new network of authors, which is a comprehensive topological representation of both the quality of the node and its role in network. Finally, we apply our method to the Erdos co-author community and AMiner Citation Network to identify the most influential authors.

Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells.

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Hongbo Shi

Full Text Available Myocardial infarction (MI is a serious heart disease and a leading cause of mortality and morbidity worldwide. Although some molecules (genes, miRNAs and transcription factors (TFs associated with MI have been studied in a specific pathological context, their dynamic characteristics in gene expressions, biological functions and regulatory interactions in MI progression have not been fully elucidated to date. In the current study, we analyzed time-series RNA expression data from peripheral blood mononuclear cells. We observed that significantly differentially expressed genes were sharply up- or down-regulated in the acute phase of MI, and then changed slowly until the chronic phase. Biological functions involved at each stage of MI were identified. Additionally, dynamic miRNA-TF co-regulatory networks were constructed based on the significantly differentially expressed genes and miRNA-TF co-regulatory motifs, and the dynamic interplay of miRNAs, TFs and target genes were investigated. Finally, a new panel of candidate diagnostic biomarkers (STAT3 and ICAM1 was identified to have discriminatory capability for patients with or without MI, especially the patients with or without recurrent events. The results of the present study not only shed new light on the understanding underlying regulatory mechanisms involved in MI progression, but also contribute to the discovery of true diagnostic biomarkers for MI.

Network-based group variable selection for detecting expression quantitative trait loci (eQTL

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Zhang Xuegong

2011-06-01

Full Text Available Abstract Background Analysis of expression quantitative trait loci (eQTL aims to identify the genetic loci associated with the expression level of genes. Penalized regression with a proper penalty is suitable for the high-dimensional biological data. Its performance should be enhanced when we incorporate biological knowledge of gene expression network and linkage disequilibrium (LD structure between loci in high-noise background. Results We propose a network-based group variable selection (NGVS method for QTL detection. Our method simultaneously maps highly correlated expression traits sharing the same biological function to marker sets formed by LD. By grouping markers, complex joint activity of multiple SNPs can be considered and the dimensionality of eQTL problem is reduced dramatically. In order to demonstrate the power and flexibility of our method, we used it to analyze two simulations and a mouse obesity and diabetes dataset. We considered the gene co-expression network, grouped markers into marker sets and treated the additive and dominant effect of each locus as a group: as a consequence, we were able to replicate results previously obtained on the mouse linkage dataset. Furthermore, we observed several possible sex-dependent loci and interactions of multiple SNPs. Conclusions The proposed NGVS method is appropriate for problems with high-dimensional data and high-noise background. On eQTL problem it outperforms the classical Lasso method, which does not consider biological knowledge. Introduction of proper gene expression and loci correlation information makes detecting causal markers more accurate. With reasonable model settings, NGVS can lead to novel biological findings.

Study of co-authorship network of papers in the Journal of Research in Medical Sciences using social network analysis

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Firoozeh Zare-Farashbandi

2014-01-01

Full Text Available Background: Co-authorship is one of the most tangible forms of research collaboration. A co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. The present research using the social network analysis studied co-authorship network of 681 articles published in Journal of Research in Medical Sciences (JRMS during 2008-2012. Materials and Methods: The study was carried out with the scientometrics approach and using co-authorship network analysis of authors. The topology of the co-authorship network of 681 published articles in JRMS between 2008 and 2012 was analyzed using macro-level metrics indicators of network analysis such as density, clustering coefficient, components and mean distance. In addition, in order to evaluate the performance of each authors and countries in the network, the micro-level indicators such as degree centrality, closeness centrality and betweenness centrality as well as productivity index were used. The UCINET and NetDraw softwares were used to draw and analyze the co-authorship network of the papers. Results: The assessment of the authors productivity in this journal showed that the first ranks were belonged to only five authors, respectively. Furthermore, analysis of the co-authorship of the authors in the network demonstrated that in the betweenness centrality index, three authors of them had the good position in the network. They can be considered as the network leaders able to control the flow of information in the network compared with the other members based on the shortest paths. On the other hand, the key role of the network according to the productivity and centrality indexes was belonged to Iran, Malaysia and United States of America. Conclusion: Co-authorship network of JRMS has the characteristics of a small world network. In addition, the theory of 6° separation is valid in this network was also true.

The Annotation, Mapping, Expression and Network (AMEN suite of tools for molecular systems biology

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Primig Michael

2008-02-01

Full Text Available Abstract Background High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpretation by life scientists. Many solutions currently exist, but they are often limited to specific steps in the complex process of data management and analysis and some require extensive informatics skills to be installed and run efficiently. Results We developed the Annotation, Mapping, Expression and Network (AMEN software as a stand-alone, unified suite of tools that enables biological and medical researchers with basic bioinformatics training to manage and explore genome annotation, chromosomal mapping, protein-protein interaction, expression profiling and proteomics data. The current version provides modules for (i uploading and pre-processing data from microarray expression profiling experiments, (ii detecting groups of significantly co-expressed genes, and (iii searching for enrichment of functional annotations within those groups. Moreover, the user interface is designed to simultaneously visualize several types of data such as protein-protein interaction networks in conjunction with expression profiles and cellular co-localization patterns. We have successfully applied the program to interpret expression profiling data from budding yeast, rodents and human. Conclusion AMEN is an innovative solution for molecular systems biological data analysis freely available under the GNU license. The program is available via a website at the Sourceforge portal which includes a user guide with concrete examples, links to external databases and helpful comments to implement additional functionalities. We emphasize that AMEN will continue to be developed and maintained by our laboratory because it has proven to be extremely useful for our genome biological research program.

Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

Science.gov (United States)

Astegiano, Julia; Altermatt, Florian; Massol, François

2017-11-13

Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.

Co-Expression of Neighboring Genes in the Zebrafish (Danio rerio Genome

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Daryi Wang

2009-08-01

Full Text Available Neighboring genes in the eukaryotic genome have a tendency to express concurrently, and the proximity of two adjacent genes is often considered a possible explanation for their co-expression behavior. However, the actual contribution of the physical distance between two genes to their co-expression behavior has yet to be defined. To further investigate this issue, we studied the co-expression of neighboring genes in zebrafish, which has a compact genome and has experienced a whole genome duplication event. Our analysis shows that the proportion of highly co-expressed neighboring pairs (Pearson’s correlation coefficient R>0.7 is low (0.24% ~ 0.67%; however, it is still significantly higher than that of random pairs. In particular, the statistical result implies that the co-expression tendency of neighboring pairs is negatively correlated with their physical distance. Our findings therefore suggest that physical distance may play an important role in the co-expression of neighboring genes. Possible mechanisms related to the neighboring genes’ co-expression are also discussed.

Breast cancer publication network: profile of co-authorship and co-organization.

Science.gov (United States)

Biglu, Mohammad-Hossein; Abotalebi, Parvaneh; Ghavami, Mostafa

2016-01-01

Introduction: Breast cancer is one of the highest reasons of deaths for people in the world. The objective of current study is to analyze and visualize the trend of global scientific activities in the field of breast cancer during a period of 10 years through 2006-2015. Methods: The current study was performed by utilizing the scientometrics analysis and mapping the co-authorship and co-organization networks. The Web of Science Core Collection (WoS-CC)database was used to extract all papers indexed as a topic of breast cancer through 2006 to 2015. Research productivity was measured through analysis several parameters, including: the number and time course of publications, the journal and language of publications, the frequency and type of publications, as well as top 20 active sub-categories together with country contribution. The extracted data were transferred into the Excel charts and plotted as diagrams. The Science of Science (Sci2) and CiteSpace softwares were used as tools for mapping the co-authorship and co-organization networks of the published papers. Results: Analysis of data indicated that the number of publications in the field of breast cancer has linearly increased and correlated with the time-course of the study. The number of publication indexed in WoS-CC in 2015 was two times greater than that of 2006, which reached from 15 229 documents in 2006 to 30 667 documents in 2015. English Language accounted for 98% of total publications as the most dominant language. The vast majority of publications' type was in the form of original journal articles (64.7%). Based on Bradford scatterings law, the journal of "Cancer Research" was the most productive journal among the core journals, while the USA, China, and England were the most prolific countries in the field. The co-organization network indicated the dominant role of Harvard University in the field. Conclusion: The integrity of network indicated that scientists in the field of breast cancer

Facial expression recognition based on improved deep belief networks

Science.gov (United States)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to improve the robustness of facial expression recognition, a method of face expression recognition based on Local Binary Pattern (LBP) combined with improved deep belief networks (DBNs) is proposed. This method uses LBP to extract the feature, and then uses the improved deep belief networks as the detector and classifier to extract the LBP feature. The combination of LBP and improved deep belief networks is realized in facial expression recognition. In the JAFFE (Japanese Female Facial Expression) database on the recognition rate has improved significantly.

Effect of elevated CO2 on chlorpyriphos degradation and soil microbial activities in tropical rice soil.

Science.gov (United States)

Adak, Totan; Munda, Sushmita; Kumar, Upendra; Berliner, J; Pokhare, Somnath S; Jambhulkar, N N; Jena, M

2016-02-01

Impact of elevated CO2 on chlorpyriphos degradation, microbial biomass carbon, and enzymatic activities in rice soil was investigated. Rice (variety Naveen, Indica type) was grown under four conditions, namely, chambered control, elevated CO2 (550 ppm), elevated CO2 (700 ppm) in open-top chambers and open field. Chlorpyriphos was sprayed at 500 g a.i. ha(-1) at maximum tillering stage. Chlorpyriphos degraded rapidly from rice soils, and 88.4% of initially applied chlorpyriphos was lost from the rice soil maintained under elevated CO2 (700 ppm) by day 5 of spray, whereas the loss was 80.7% from open field rice soil. Half-life values of chlorpyriphos under different conditions ranged from 2.4 to 1.7 days with minimum half-life recorded with two elevated CO2 treatments. Increased CO2 concentration led to increase in temperature (1.2 to 1.8 °C) that played a critical role in chlorpyriphos persistence. Microbial biomass carbon and soil enzymatic activities specifically, dehydrogenase, fluorescien diacetate hydrolase, urease, acid phosphatase, and alkaline phosphatase responded positively to elevated CO2 concentrations. Generally, the enzyme activities were highly correlated with each other. Irrespective of the level of CO2, short-term negative influence of chlorpyriphos was observed on soil enzymes till day 7 of spray. Knowledge obtained from this study highlights that the elevated CO2 may negatively influence persistence of pesticide but will have positive effects on soil enzyme activities.

The United States Culture Collection Network (USCCN): Enhancing Microbial Genomics Research through Living Microbe Culture Collections

Science.gov (United States)

Boundy-Mills, Kyria; Hess, Matthias; Bennett, A. Rick; Ryan, Matthew; Kang, Seogchan; Nobles, David; Eisen, Jonathan A.; Inderbitzin, Patrik; Sitepu, Irnayuli R.; Torok, Tamas; Brown, Daniel R.; Cho, Juliana; Wertz, John E.; Mukherjee, Supratim; Cady, Sherry L.

2015-01-01

The mission of the United States Culture Collection Network (USCCN; http://usccn.org) is “to facilitate the safe and responsible utilization of microbial resources for research, education, industry, medicine, and agriculture for the betterment of human kind.” Microbial culture collections are a key component of life science research, biotechnology, and emerging global biobased economies. Representatives and users of several microbial culture collections from the United States and Europe gathered at the University of California, Davis, to discuss how collections of microorganisms can better serve users and stakeholders and to showcase existing resources available in public culture collections. PMID:26092453

Co-occurrence patterns in aquatic bacterial communities across changing permafrost landscapes

Science.gov (United States)

Comte, J.; Lovejoy, C.; Crevecoeur, S.; Vincent, W. F.

2016-01-01

Permafrost thaw ponds and lakes are widespread across the northern landscape and may play a central role in global biogeochemical cycles, yet knowledge about their microbial ecology is limited. We sampled a set of thaw ponds and lakes as well as shallow rock-basin lakes that are located in distinct valleys along a north-south permafrost degradation gradient. We applied high-throughput sequencing of the 16S rRNA gene to determine co-occurrence patterns among bacterial taxa (operational taxonomic units, OTUs), and then analyzed these results relative to environmental variables to identify variables controlling bacterial community structure. Network analysis was applied to identify possible ecological linkages among the bacterial taxa and with abiotic and biotic variables. The results showed an overall high level of shared taxa among bacterial communities within each valley; however, the bacterial co-occurrence patterns were non-random, with evidence of habitat preferences. There were taxonomic differences in bacterial assemblages among the different valleys that were statistically related to dissolved organic carbon concentration, conductivity and phytoplankton biomass. Co-occurrence networks revealed complex interdependencies within the bacterioplankton communities and showed contrasting linkages to environmental conditions among the main bacterial phyla. The thaw pond networks were composed of a limited number of highly connected taxa. This "small world network" property would render the communities more robust to environmental change but vulnerable to the loss of microbial "keystone species". These highly connected nodes (OTUs) in the network were not merely the numerically dominant taxa, and their loss would alter the organization of microbial consortia and ultimately the food web structure and functioning of these aquatic ecosystems.

Characterizing Microbial Diversity and Function in Natural Subsurface CO2 Reservoir Systems for Applied Use in Geologic Carbon Sequestration Environments

Science.gov (United States)

Freedman, A.; Thompson, J. R.

2013-12-01

The injection of CO2 into geological formations at quantities necessary to significantly reduce CO2 emissions will represent an environmental perturbation on a continental scale. The extent to which biological processes may play a role in the fate and transport of CO2 injected into geological formations has remained an open question due to the fact that at temperatures and pressures associated with reservoirs targeted for sequestration CO2 exists as a supercritical fluid (scCO2), which has generally been regarded as a sterilizing agent. Natural subsurface accumulations of CO2 serve as an excellent analogue for studying the long-term effects, implications and benefits of CO2 capture and storage (CCS). While several geologic formations bearing significant volumes of nearly pure scCO2 phases have been identified in the western United States, no study has attempted to characterize the microbial community present in these systems. Because the CO2 in the region is thought to have first accumulated millions of years ago, it is reasonable to assume that native microbial populations have undergone extensive and unique physiological and behavioral adaptations to adjust to the exceedingly high scCO2 content. Our study focuses on the microbial communities associated with the dolomite limestone McElmo Dome scCO2 Field in the Colorado Plateau region, approximately 1,000 m below the surface. Fluid samples were collected from 10 wells at an industrial CO2 production facility outside Cortez, CO. Subsamples preserved on site in 3.7% formaldehyde were treated in the lab with Syto 9 green-fluorescent nucleic acid stain, revealing 3.2E6 to 1.4E8 microbial cells per liter of produced fluid and 8.0E9 cells per liter of local pond water used in well drilling fluids. Extracted DNAs from sterivex 0.22 um filters containing 20 L of sample biomass were used as templates for PCR targeting the 16S rRNA gene. 16S rRNA amplicons from these samples were cloned, sequenced and subjected to microbial

Effects of Elevated Carbon Dioxide and Salinity on the Microbial Diversity in Lithifying Microbial Mats

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Steven R. Ahrendt

2014-03-01

Full Text Available Atmospheric levels of carbon dioxide (CO2 are rising at an accelerated rate resulting in changes in the pH and carbonate chemistry of the world’s oceans. However, there is uncertainty regarding the impact these changing environmental conditions have on carbonate-depositing microbial communities. Here, we examine the effects of elevated CO2, three times that of current atmospheric levels, on the microbial diversity associated with lithifying microbial mats. Lithifying microbial mats are complex ecosystems that facilitate the trapping and binding of sediments, and/or the precipitation of calcium carbonate into organosedimentary structures known as microbialites. To examine the impact of rising CO2 and resulting shifts in pH on lithifying microbial mats, we constructed growth chambers that could continually manipulate and monitor the mat environment. The microbial diversity of the various treatments was compared using 16S rRNA gene pyrosequencing. The results indicated that elevated CO2 levels during the six month exposure did not profoundly alter the microbial diversity, community structure, or carbonate precipitation in the microbial mats; however some key taxa, such as the sulfate-reducing bacteria Deltasulfobacterales, were enriched. These results suggest that some carbonate depositing ecosystems, such as the microbialites, may be more resilient to anthropogenic-induced environmental change than previously thought.

A multi-platform flow device for microbial (co- cultivation and microscopic analysis.

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Matthijn C Hesselman

Full Text Available Novel microbial cultivation platforms are of increasing interest to researchers in academia and industry. The development of materials with specialized chemical and geometric properties has opened up new possibilities in the study of previously unculturable microorganisms and has facilitated the design of elegant, high-throughput experimental set-ups. Within the context of the international Genetically Engineered Machine (iGEM competition, we set out to design, manufacture, and implement a flow device that can accommodate multiple growth platforms, that is, a silicon nitride based microsieve and a porous aluminium oxide based microdish. It provides control over (co-culturing conditions similar to a chemostat, while allowing organisms to be observed microscopically. The device was designed to be affordable, reusable, and above all, versatile. To test its functionality and general utility, we performed multiple experiments with Escherichia coli cells harboring synthetic gene circuits and were able to quantitatively study emerging expression dynamics in real-time via fluorescence microscopy. Furthermore, we demonstrated that the device provides a unique environment for the cultivation of nematodes, suggesting that the device could also prove useful in microscopy studies of multicellular microorganisms.

Influence of arsenic co-contamination on DDT breakdown and microbial activity

International Nuclear Information System (INIS)

Zwieten, Lukas van; Ayres, Matthew R.; Morris, Stephen G.

2003-01-01

Co-occurrence of arsenic and DDT in soil may result increased persistence of DDT. - The impacts of arsenic co-contamination on the natural breakdown of 1,1,1-trichloro-2,2-bis(4-chlorophenyl)ethane (DDT) in soil are investigated in a study of 12 former cattle dip sites located in northeastern NSW, Australia. This study examines the relationship between the intrinsic breakdown of DDT to 1,1-dichloro-2,2-bis(4-chlorophenyl)ethane (DDD) and 1,1-dichloro-2,2-bis(4-chlorophenyl)ethylene (DDE), and the impacts of arsenic co-contamination on this breakdown. Between-site analysis demonstrated that arsenic at 2000 mg/kg gave a 50% reduction in the concentration of DDD compared to background arsenic of 5 mg/kg. Within-site analysis also showed the ratio of DDT:DDD increased in soils as arsenic concentrations increased. This within-site trend was also apparent with the DDT:DDE ratio, suggesting inhibition of DDT breakdown by arsenic co-contamination. Microbial activity was inhibited as residues of total DDTs and arsenic increased. Hence arsenic co-contamination and high concentrations of DDT in soil may result in an increased persistence of DDT in the environment studied

Co-opetition and knowledge co-creation in Japanese supplier-networks : The case of Toyota

NARCIS (Netherlands)

Wilhelm, Miriam M.; Kohlbacher, Florian

This article examines how knowledge co-creation takes place within the Toyota network. We extend the work of Dyer and Nobeoka, who contributed to the theory of network-level learning by showing how Toyota succeeded in 'creating and managing a high-performance knowledge-sharing network'. By examining

A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes

DEFF Research Database (Denmark)

de Jong, Simone; Boks, Marco P M; Fuller, Tova F

2012-01-01

Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood...... of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co......, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes...

Effect of simulated tillage on microbial autotrophic CO2 fixation in paddy and upland soils

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Ge, Tida; Wu, Xiaohong; Liu, Qiong; Zhu, Zhenke; Yuan, Hongzhao; Wang, Wei; Whiteley, A. S.; Wu, Jinshui

2016-01-01

Tillage is a common agricultural practice affecting soil structure and biogeochemistry. To evaluate how tillage affects soil microbial CO2 fixation, we incubated and continuously labelled samples from two paddy soils and two upland soils subjected to simulated conventional tillage (CT) and no-tillage (NT) treatments. Results showed that CO2 fixation (14C-SOC) in CT soils was significantly higher than in NT soils. We also observed a significant, soil type- and depth-dependent effect of tillage on the incorporation rates of labelled C to the labile carbon pool. Concentrations of labelled C in the carbon pool significantly decreased with soil depth, irrespective of tillage. Additionally, quantitative PCR assays revealed that for most soils, total bacteria and cbbL-carrying bacteria were less abundant in CT versus NT treatments, and tended to decrease in abundance with increasing depth. However, specific CO2 fixation activity was significantly higher in CT than in NT soils, suggesting that the abundance of cbbL-containing bacteria may not always reflect their functional activity. This study highlights the positive effect of tillage on soil microbial CO2 fixation, and the results can be readily applied to the development of sustainable agricultural management. PMID:26795428

A defined co-culture of Geobacter sulfurreducens and Escherichia coli in a membrane-less microbial fuel cell.

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Bourdakos, Nicholas; Marsili, Enrico; Mahadevan, Radhakrishnan

2014-04-01

Wastewater-fed microbial fuel cells (MFCs) are a promising technology to treat low-organic carbon wastewater and recover part of the chemical energy in wastewater as electrical power. However, the interactions between electrochemically active and fermentative microorganisms cannot be easily studied in wastewater-fed MFCs because of their complex microbial communities. Defined co-culture MFCs provide a detailed understanding of such interactions. In this study, we characterize the extracellular metabolites in laboratory-scale membrane-less MFCs inoculated with Geobacter sulfurreducens and Escherichia coli co-culture and compare them with pure culture MFCs. G. sulfurreducens MFCs are sparged to maintain anaerobic conditions, while co-culture MFCs rely on E. coli for oxygen removal. G. sulfurreducens MFCs have a power output of 128 mW m(-2) , compared to 63 mW m(-2) from the co-culture MFCs. Analysis of metabolites shows that succinate production in co-culture MFCs decreases current production by G. sulfurreducens and that the removal of succinate is responsible for the increased current density in the late co-culture MFCs. Interestingly, pH adjustment is not required for co-culture MFCs but a base addition is necessary for E. coli MFCs and cultures in vials. Our results show that defined co-culture MFCs provide clear insights into metabolic interactions among bacteria while maintaining a low operational complexity. © 2013 Wiley Periodicals, Inc.

Integrative Analysis of Hippocampus Gene Expression Profiles Identifies Network Alterations in Aging and Alzheimer’s Disease

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Vinay Lanke

2018-05-01

Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder contributing to rapid decline in cognitive function and ultimately dementia. Most cases of AD occur in elderly and later years. There is a growing need for understanding the relationship between aging and AD to identify shared and unique hallmarks associated with the disease in a region and cell-type specific manner. Although genomic studies on AD have been performed extensively, the molecular mechanism of disease progression is still not clear. The major objective of our study is to obtain a higher-order network-level understanding of aging and AD, and their relationship using the hippocampal gene expression profiles of young (20–50 years, aging (70–99 years, and AD (70–99 years. The hippocampus is vulnerable to damage at early stages of AD and altered neurogenesis in the hippocampus is linked to the onset of AD. We combined the weighted gene co-expression network and weighted protein–protein interaction network-level approaches to study the transition from young to aging to AD. The network analysis revealed the organization of co-expression network into functional modules that are cell-type specific in aging and AD. We found that modules associated with astrocytes, endothelial cells and microglial cells are upregulated and significantly correlate with both aging and AD. The modules associated with neurons, mitochondria and endoplasmic reticulum are downregulated and significantly correlate with AD than aging. The oligodendrocytes module does not show significant correlation with neither aging nor disease. Further, we identified aging- and AD-specific interactions/subnetworks by integrating the gene expression with a human protein–protein interaction network. We found dysregulation of genes encoding protein kinases (FYN, SYK, SRC, PKC, MAPK1, ephrin receptors and transcription factors (FOS, STAT3, CEBPB, MYC, NFKβ, and EGR1 in AD. Further, we found genes that encode proteins

Differential effects of Pseudomonas mendocina and Glomus intraradices on lettuce plants physiological response and aquaporin PIP2 gene expression under elevated atmospheric CO2 and drought.

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Alguacil, Maria Del Mar; Kohler, Josef; Caravaca, Fuensanta; Roldán, Antonio

2009-11-01

Arbuscular mycorrhizal (AM) symbiosis and plant-growth-promoting rhizobacterium (PGPR) can alleviate the effects of water stress in plants, but it is unknown whether these benefits can be maintained at elevated CO2. Therefore, we carried out a study where seedlings of Lactuca sativa were inoculated with the AM fungus (AMF) Glomus intraradices N.C. Schenk & G.S. Sm. or the PGPR Pseudomonas mendocina Palleroni and subjected to two levels of watering and two levels of atmospheric CO2 to ascertain their effects on plant physiological parameters and gene expression of one PIP aquaporin in roots. The inoculation with PGPR produced the greatest growth in lettuce plants under all assayed treatments as well as the highest foliar potassium concentration and leaf relative water content under elevated [CO2] and drought. However, under such conditions, the PIP2 gene expression remained almost unchanged. G. intraradices increased significantly the AMF colonization, foliar phosphorus concentration and leaf relative water content in plants grown under drought and elevated [CO2]. Under drought and elevated [CO2], the plants inoculated with G. intraradices showed enhanced expression of the PIP2 gene as compared to P. mendocina or control plants. Our results suggest that both microbial inoculation treatments could help to alleviate drought at elevated [CO2]. However, the PIP2 gene expression was increased only by the AMF but not by the PGPR under these conditions.

Genes and co-expression modules common to drought and bacterial stress responses in Arabidopsis and rice.

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Rafi Shaik

Full Text Available Plants are simultaneously exposed to multiple stresses resulting in enormous changes in the molecular landscape within the cell. Identification and characterization of the synergistic and antagonistic components of stress response mechanisms contributing to the cross talk between stresses is of high priority to explore and enhance multiple stress responses. To this end, we performed meta-analysis of drought (abiotic, bacterial (biotic stress response in rice and Arabidopsis by analyzing a total of 386 microarray samples belonging to 20 microarray studies and identified approximately 3100 and 900 DEGs in rice and Arabidopsis, respectively. About 38.5% (1214 and 28.7% (272 DEGs were common to drought and bacterial stresses in rice and Arabidopsis, respectively. A majority of these common DEGs showed conserved expression status in both stresses. Gene ontology enrichment analysis clearly demarcated the response and regulation of various plant hormones and related biological processes. Fatty acid metabolism and biosynthesis of alkaloids were upregulated and, nitrogen metabolism and photosynthesis was downregulated in both stress conditions. WRKY transcription family genes were highly enriched in all upregulated gene sets while 'CO-like' TF family showed inverse relationship of expression between drought and bacterial stresses. Weighted gene co-expression network analysis divided DEG sets into multiple modules that show high co-expression and identified stress specific hub genes with high connectivity. Detection of consensus modules based on DEGs common to drought and bacterial stress revealed 9 and 4 modules in rice and Arabidopsis, respectively, with conserved and reversed co-expression patterns.

Meta genome-wide network from functional linkages of genes in human gut microbial ecosystems.

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Ji, Yan; Shi, Yixiang; Wang, Chuan; Dai, Jianliang; Li, Yixue

2013-03-01

The human gut microbial ecosystem (HGME) exerts an important influence on the human health. In recent researches, meta-genomics provided deep insights into the HGME in terms of gene contents, metabolic processes and genome constitutions of meta-genome. Here we present a novel methodology to investigate the HGME on the basis of a set of functionally coupled genes regardless of their genome origins when considering the co-evolution properties of genes. By analyzing these coupled genes, we showed some basic properties of HGME significantly associated with each other, and further constructed a protein interaction map of human gut meta-genome to discover some functional modules that may relate with essential metabolic processes. Compared with other studies, our method provides a new idea to extract basic function elements from meta-genome systems and investigate complex microbial environment by associating its biological traits with co-evolutionary fingerprints encoded in it.

Discovery of cis-elements between sorghum and rice using co-expression and evolutionary conservation

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Haberer Georg

2009-06-01

Full Text Available Abstract Background The spatiotemporal regulation of gene expression largely depends on the presence and absence of cis-regulatory sites in the promoter. In the economically highly important grass family, our knowledge of transcription factor binding sites and transcriptional networks is still very limited. With the completion of the sorghum genome and the available rice genome sequence, comparative promoter analyses now allow genome-scale detection of conserved cis-elements. Results In this study, we identified thousands of phylogenetic footprints conserved between orthologous rice and sorghum upstream regions that are supported by co-expression information derived from three different rice expression data sets. In a complementary approach, cis-motifs were discovered by their highly conserved co-occurrence in syntenic promoter pairs. Sequence conservation and matches to known plant motifs support our findings. Expression similarities of gene pairs positively correlate with the number of motifs that are shared by gene pairs and corroborate the importance of similar promoter architectures for concerted regulation. This strongly suggests that these motifs function in the regulation of transcript levels in rice and, presumably also in sorghum. Conclusion Our work provides the first large-scale collection of cis-elements for rice and sorghum and can serve as a paradigm for cis-element analysis through comparative genomics in grasses in general.

Analysis of global gene expression in Brachypodium distachyon reveals extensive network plasticity in response to abiotic stress.

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Henry D Priest

Full Text Available Brachypodium distachyon is a close relative of many important cereal crops. Abiotic stress tolerance has a significant impact on productivity of agriculturally important food and feedstock crops. Analysis of the transcriptome of Brachypodium after chilling, high-salinity, drought, and heat stresses revealed diverse differential expression of many transcripts. Weighted Gene Co-Expression Network Analysis revealed 22 distinct gene modules with specific profiles of expression under each stress. Promoter analysis implicated short DNA sequences directly upstream of module members in the regulation of 21 of 22 modules. Functional analysis of module members revealed enrichment in functional terms for 10 of 22 network modules. Analysis of condition-specific correlations between differentially expressed gene pairs revealed extensive plasticity in the expression relationships of gene pairs. Photosynthesis, cell cycle, and cell wall expression modules were down-regulated by all abiotic stresses. Modules which were up-regulated by each abiotic stress fell into diverse and unique gene ontology GO categories. This study provides genomics resources and improves our understanding of abiotic stress responses of Brachypodium.

Presence and Expression of Microbial Genes Regulating Soil Nitrogen Dynamics Along the Tanana River Successional Sequence

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Boone, R. D.; Rogers, S. L.

2004-12-01

We report on work to assess the functional gene sequences for soil microbiota that control nitrogen cycle pathways along the successional sequence (willow, alder, poplar, white spruce, black spruce) on the Tanana River floodplain, Interior Alaska. Microbial DNA and mRNA were extracted from soils (0-10 cm depth) for amoA (ammonium monooxygenase), nifH (nitrogenase reductase), napA (nitrate reductase), and nirS and nirK (nitrite reductase) genes. Gene presence was determined by amplification of a conserved sequence of each gene employing sequence specific oligonucleotide primers and Polymerase Chain Reaction (PCR). Expression of the genes was measured via nested reverse transcriptase PCR amplification of the extracted mRNA. Amplified PCR products were visualized on agarose electrophoresis gels. All five successional stages show evidence for the presence and expression of microbial genes that regulate N fixation (free-living), nitrification, and nitrate reduction. We detected (1) nifH, napA, and nirK presence and amoA expression (mRNA production) for all five successional stages and (2) nirS and amoA presence and nifH, nirK, and napA expression for early successional stages (willow, alder, poplar). The results highlight that the existing body of previous process-level work has not sufficiently considered the microbial potential for a nitrate economy and free-living N fixation along the complete floodplain successional sequence.

Photo-cross-linked poly(thioether-co-carbonate) networks derived from the natural product quinic acid.

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Link, Lauren A; Lonnecker, Alexander T; Hearon, Keith; Maher, Cameron A; Raymond, Jeffery E; Wooley, Karen L

2014-10-22

Polycarbonate networks derived from the natural product quinic acid that can potentially return to their natural building blocks upon hydrolytic degradation are described herein. Solvent-free thiol-ene chemistry was utilized in the copolymerization of tris(alloc)quinic acid and a variety of multifunctional thiol monomers to obtain poly(thioether-co-carbonate) networks with a wide range of achievable thermomechanical properties including glass transition temperatures from -18 to +65 °C and rubbery moduli from 3.8 to 20 MPa. The network containing 1,2-ethanedithiol expressed an average toughness at 25 and 63 °C of 1.08 and 2.35 MJ/m(3), respectively, and an order-of-magnitude increase in the average toughness at 37 °C of 15.56 MJ/m(3).

Microbial-Host Co-metabolites Are Prodromal Markers Predicting Phenotypic Heterogeneity in Behavior, Obesity, and Impaired Glucose Tolerance

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Marc-Emmanuel Dumas

2017-07-01

Full Text Available The influence of the gut microbiome on metabolic and behavioral traits is widely accepted, though the microbiome-derived metabolites involved remain unclear. We carried out untargeted urine 1H-NMR spectroscopy-based metabolic phenotyping in an isogenic C57BL/6J mouse population (n = 50 and show that microbial-host co-metabolites are prodromal (i.e., early markers predicting future divergence in metabolic (obesity and glucose homeostasis and behavioral (anxiety and activity outcomes with 94%–100% accuracy. Some of these metabolites also modulate disease phenotypes, best illustrated by trimethylamine-N-oxide (TMAO, a product of microbial-host co-metabolism predicting future obesity, impaired glucose tolerance (IGT, and behavior while reducing endoplasmic reticulum stress and lipogenesis in 3T3-L1 adipocytes. Chronic in vivo TMAO treatment limits IGT in HFD-fed mice and isolated pancreatic islets by increasing insulin secretion. We highlight the prodromal potential of microbial metabolites to predict disease outcomes and their potential in shaping mammalian phenotypic heterogeneity.

Microbial electrochemical separation of CO2 for biogas upgrading.

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Kokkoli, Argyro; Zhang, Yifeng; Angelidaki, Irini

2018-01-01

Biogas upgrading to natural gas quality has been under focus the recent years for increasing the utilization potential of biogas. Conventional methods for CO 2 removal are expensive and have environmental challenges, such as increased emissions of methane in the atmosphere with serious greenhouse impact. In this study, an innovative microbial electrochemical separation cell (MESC) was developed to in-situ separate and regenerate CO 2 via alkali and acid regeneration. The MESC was tested under different applied voltages, inlet biogas rates and electrolyte concentrations. Pure biomethane was obtained at 1.2V, inlet biogas rate of 0.088mL/h/mL reactor and NaCl concentration of 100mM at a 5-day operation. Meanwhile, the organic matter of the domestic wastewater in the anode was almost completely removed at the end. The study demonstrated a new sustainable way to simultaneously upgrade biogas and treat wastewater which can be used as proof of concept for further investigation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

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Min Peng

2017-10-01

Full Text Available Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition.

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Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

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Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve. PMID:29081753

Microbial respiration per unit microbial biomass increases with carbon-to-nutrient ratios in soils

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Spohn, Marie; Chodak, Marcin

2015-04-01

The ratio of carbon-to-nutrient in forest floors is usually much higher than the ratio of carbon-to-nutrient that soil microorganisms require for their nutrition. In order to understand how this mismatch affects carbon cycling, the respiration rate per unit soil microbial biomass carbon - the metabolic quotient (qCO2) - was studied. This was done in a field study (Spohn and Chodak, 2015) and in a meta-analysis of published data (Spohn, 2014). Cores of beech, spruce, and mixed spruce-beech forest soils were cut into slices of 1 cm from the top of the litter layer down to 5 cm in the mineral soil, and the relationship between the qCO2 and the soil carbon-to-nitrogen (C:N) and the soil carbon-to-phosphorus (C:P) ratio was analyzed. We found that the qCO2 was positively correlated with soil C:N ratio in spruce soils (R = 0.72), and with the soil C:P ratio in beech (R = 0.93), spruce (R = 0.80) and mixed forest soils (R = 0.96). We also observed a close correlation between the qCO2 and the soil C concentration in all three forest types. Yet, the qCO2 decreased less with depth than the C concentration in all three forest types, suggesting that the change in qCO2 is not only controlled by the soil C concentration. We conclude that microorganisms increase their respiration rate per unit biomass with increasing soil C:P ratio and C concentration, which adjusts the substrate to their nutritional demands in terms of stoichiometry. In an analysis of literature data, I tested the effect of the C:N ratio of soil litter layers on microbial respiration in absolute terms and per unit microbial biomass C. For this purpose, a global dataset on the microbial respiration rate per unit microbial biomass C - termed the metabolic quotient (qCO2) - was compiled form literature data. It was found that the qCO2 in the soil litter layers was positively correlated with the litter C:N ratio and negatively related with the litter nitrogen (N) concentration. The positive relation between the qCO2

Volatile Gas Production by Methyl Halide Transferase: An In Situ Reporter Of Microbial Gene Expression In Soil.

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Cheng, Hsiao-Ying; Masiello, Caroline A; Bennett, George N; Silberg, Jonathan J

2016-08-16

Traditional visual reporters of gene expression have only very limited use in soils because their outputs are challenging to detect through the soil matrix. This severely restricts our ability to study time-dependent microbial gene expression in one of the Earth's largest, most complex habitats. Here we describe an approach to report on dynamic gene expression within a microbial population in a soil under natural water levels (at and below water holding capacity) via production of methyl halides using a methyl halide transferase. As a proof-of-concept application, we couple the expression of this gas reporter to the conjugative transfer of a bacterial plasmid in a soil matrix and show that gas released from the matrix displays a strong correlation with the number of transconjugant bacteria that formed. Gas reporting of gene expression will make possible dynamic studies of natural and engineered microbes within many hard-to-image environmental matrices (soils, sediments, sludge, and biomass) at sample scales exceeding those used for traditional visual reporting.

Lattice Boltzmann simulation of CO2 reactive transport in network fractured media

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Tian, Zhiwei; Wang, Junye

2017-08-01

Carbon dioxide (CO2) geological sequestration plays an important role in mitigating CO2 emissions for climate change. Understanding interactions of the injected CO2 with network fractures and hydrocarbons is key for optimizing and controlling CO2 geological sequestration and evaluating its risks to ground water. However, there is a well-known, difficult process in simulating the dynamic interaction of fracture-matrix, such as dynamic change of matrix porosity, unsaturated processes in rock matrix, and effect of rock mineral properties. In this paper, we develop an explicit model of the fracture-matrix interactions using multilayer bounce-back treatment as a first attempt to simulate CO2 reactive transport in network fractured media through coupling the Dardis's LBM porous model for a new interface treatment. Two kinds of typical fracture networks in porous media are simulated: straight cross network fractures and interleaving network fractures. The reaction rate and porosity distribution are illustrated and well-matched patterns are found. The species concentration distribution and evolution with time steps are also analyzed and compared with different transport properties. The results demonstrate the capability of this model to investigate the complex processes of CO2 geological injection and reactive transport in network fractured media, such as dynamic change of matrix porosity.

The Importance of Transition Metals in the Expanding Network of Microbial Metabolism in the Archean Eon

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Moore, E. K.; Jelen, B. I.; Giovannelli, D.; Prabhu, A.; Raanan, H.; Falkowski, P. G.

2017-12-01

Deep time changes in Earth surface redox conditions, particularly due to global oxygenation, has impacted the availability of different metals and substrates that are central in biology. Oxidoreductase proteins are molecular nanomachines responsible for all biological electron transfer processes across the tree of life. These enzymes largely contain transition metals in their active sites. Microbial metabolic pathways form a global network of electron transfer, which expanded throughout the Archean eon. Older metabolisms (sulfur reduction, methanogenesis, anoxygenic photosynthesis) accessed negative redox potentials, while later evolving metabolisms (oxygenic photosynthesis, nitrification/denitrification, aerobic respiration) accessed positive redox potentials. The incorporation of different transition metals facilitated biological innovation and the expansion of the network of microbial metabolism. Network analysis was used to examine the connections between microbial taxa, metabolic pathways, crucial metallocofactors, and substrates in deep time by incorporating biosignatures preserved in the geologic record. Nitrogen fixation and aerobic respiration have the highest level of betweenness among metabolisms in the network, indicating that the oldest metabolisms are not the most central. Fe has by far the highest betweenness among metals. Clustering analysis largely separates High Metal Bacteria (HMB), Low Metal Bacteria (LMB), and Archaea showing that simple un-weighted links between taxa, metabolism, and metals have phylogenetic relevance. On average HMB have the highest betweenness among taxa, followed by Archaea and LMB. There is a correlation between the number of metallocofactors and metabolic pathways in representative bacterial taxa, but Archaea do not follow this trend. In many cases older and more recently evolved metabolisms were clustered together supporting previous findings that proliferation of metabolic pathways is not necessarily chronological.

Value Co-creation and Co-innovation: Linking Networked Organisations and Customer Communities

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Romero, David; Molina, Arturo

Strategic networks such as Collaborative Networked Organisations (CNOs) and Virtual Customer Communities (VCCs) show a high potential as drivers of value co-creation and collaborative innovation in today’s Networking Era. Both look at the network structures as a source of jointly value creation and open innovation through access to new skills, knowledge, markets and technologies by sharing risk and integrating complementary competencies. This collaborative endeavour has proven to be able to enhance the adaptability and flexibility of CNOs and VCCs value creating systems in order to react in response to external drivers such as collaborative (business) opportunities. This paper presents a reference framework for creating interface networks, also known as ‘experience-centric networks’, as enablers for linking networked organisations and customer communities in order to support the establishment of user-driven and collaborative innovation networks.

Large clusters of co-expressed genes in the Drosophila genome.

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Boutanaev, Alexander M; Kalmykova, Alla I; Shevelyov, Yuri Y; Nurminsky, Dmitry I

2002-12-12

Clustering of co-expressed, non-homologous genes on chromosomes implies their co-regulation. In lower eukaryotes, co-expressed genes are often found in pairs. Clustering of genes that share aspects of transcriptional regulation has also been reported in higher eukaryotes. To advance our understanding of the mode of coordinated gene regulation in multicellular organisms, we performed a genome-wide analysis of the chromosomal distribution of co-expressed genes in Drosophila. We identified a total of 1,661 testes-specific genes, one-third of which are clustered on chromosomes. The number of clusters of three or more genes is much higher than expected by chance. We observed a similar trend for genes upregulated in the embryo and in the adult head, although the expression pattern of individual genes cannot be predicted on the basis of chromosomal position alone. Our data suggest that the prevalent mechanism of transcriptional co-regulation in higher eukaryotes operates with extensive chromatin domains that comprise multiple genes.

An approach to mitigating soil CO2 emission by biochemically inhibiting cellulolytic microbial populations through mediation via the medicinal herb Isatis indigotica

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Wu, Hong-Sheng; Chen, Su-Yun; Li, Ji; Liu, Dong-Yang; Zhou, Ji; Xu, Ya; Shang, Xiao-Xia; Wei, Dong-yang; Yu, Lu-ji; Fang, Xiao-hang; Li, Shun-yi; Wang, Ke-ke

2017-06-01

Greenhouse gases (GHGs, particularly carbon dioxide (CO2)) emissions from soil under wheat production are a significant source of agricultural carbon emissions that have not been mitigated effectively. A field experiment and a static incubation study in a lab were conducted to stimulate wheat growth and investigate its potential to reduce CO2 emissions from soil through intercropping with a traditional Chinese medicinal herb called Isatis indigotica. This work was conducted by adding I. indigotica root exudates based on the quantitative real-time PCR (qPCR) analysis of the DNA copy number of the rhizosphere or bulk soil microbial populations. This addition was performed in relation to the CO2 formation by cellulolytic microorganisms (Penicillium oxalicum, fungi and Ruminococcus albus) to elucidate the microbial ecological basis for the molecular mechanism that decreases CO2 emissions from wheat fields using I. indigotica. The results showed that the panicle weight and full grains per panicle measured through intercropping with I. indigotica (NPKWR) increased by 39% and 28.6%, respectively, compared to that of the CK (NPKW). Intercropping with I. indigotica significantly decreased the CO2 emissions from soil under wheat cultivation. Compared with CK, the total CO2 emission flux during the wheat growth period in the I. indigotica (NPKWR) intercropping treatment decreased by 29.26%. The intensity of CO2 emissions per kg of harvested wheat grain declined from 7.53 kg CO2/kg grain in the NPKW (CK) treatment to 5.55 kg CO2/kg grain in the NPKWR treatment. The qPCR analysis showed that the DNA copy number of the microbial populations of cellulolytic microorganisms (P. oxalicum, fungi and R. albus) in the field rhizosphere around I. indigotica or in the bulk soil under laboratory incubation was significantly lower than that of CK. This finding indicated that root exudates from I. indigotica inhibited the activity and number of cellulolytic microbial populations, which led

Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

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Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

Dissection of Microbial Community Functions during a Cyanobacterial Bloom in the Baltic Sea via Metatranscriptomics

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Carlo Berg

2018-02-01

Full Text Available Marine and brackish surface waters are highly dynamic habitats that undergo repeated seasonal variations in microbial community composition and function throughout time. While succession of the various microbial groups has been well investigated, little is known about the underlying gene-expression of the microbial community. We investigated microbial interactions via metatranscriptomics over a spring to fall seasonal cycle in the brackish Baltic Sea surface waters, a temperate brackish water ecosystem periodically promoting massive cyanobacterial blooms, which have implications for primary production, nutrient cycling, and expansion of hypoxic zones. Network analysis of the gene expression of all microbes from 0.22 to 200 μm in size and of the major taxonomic groups dissected the seasonal cycle into four components that comprised genes peaking during different periods of the bloom. Photoautotrophic nitrogen-fixing Cyanobacteria displayed the highest connectivity among the microbes, in contrast to chemoautotrophic ammonia-oxidizing Thaumarchaeota, while heterotrophs dominated connectivity among pre- and post-bloom peaking genes. The network was also composed of distinct functional connectivities, with an early season balance between carbon metabolism and ATP synthesis shifting to a dominance of ATP synthesis during the bloom, while carbon degradation, specifically through the glyoxylate shunt, characterized the post-bloom period, driven by Alphaproteobacteria as well as by Gammaproteobacteria of the SAR86 and SAR92 clusters. Our study stresses the exceptionally strong biotic driving force executed by cyanobacterial blooms on associated microbial communities in the Baltic Sea and highlights the impact cyanobacterial blooms have on functional microbial community composition.

Comparative transcriptome and gene co-expression network analysis reveal genes and signaling pathways adaptively responsive to varied adverse stresses in the insect fungal pathogen, Beauveria bassiana.

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He, Zhangjiang; Zhao, Xin; Lu, Zhuoyue; Wang, Huifang; Liu, Pengfei; Zeng, Fanqin; Zhang, Yongjun

2018-01-01

Sensing, responding, and adapting to the surrounding environment are crucial for all living organisms to survive, proliferate, and differentiate in their biological niches. Beauveria bassiana is an economically important insect-pathogenic fungus which is widely used as a biocontrol agent to control a variety of insect pests. The fungal pathogen unavoidably encounters a variety of adverse environmental stresses and defense response from the host insects during application of the fungal agents. However, few are known about the transcription response of the fungus to respond or adapt varied adverse stresses. Here, we comparatively analyzed the transcriptome of B. bassiana in globe genome under the varied stationary-phase stresses including osmotic agent (0.8 M NaCl), high temperature (32 °C), cell wall-perturbing agent (Congo red), and oxidative agents (H 2 O 2 or menadione). Total of 12,412 reads were obtained, and mapped to the 6767 genes of the B. bassiana. All of these stresses caused transcription responses involved in basal metabolism, cell wall construction, stress response or cell rescue/detoxification, signaling transduction and gene transcription regulation, and likely other cellular processes. An array of genes displayed similar transcription patterns in response to at least two of the five stresses, suggesting a shared transcription response to varied adverse stresses. Gene co-expression network analysis revealed that mTOR signaling pathway, but not HOG1 MAP kinase pathway, played a central role in regulation the varied adverse stress responses, which was verified by RNAi-mediated knockdown of TOR1. Our findings provided an insight of transcription response and gene co-expression network of B. bassiana in adaptation to varied environments. Copyright © 2017 Elsevier Inc. All rights reserved.

Codon based co-occurrence network motifs in human mitochondria

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Pramod Shinde

2017-10-01

Full Text Available The nucleotide polymorphism in human mitochondrial genome (mtDNA tolled by codon position bias plays an indispensable role in human population dispersion and expansion. Herein, we constructed genome-wide nucleotide co-occurrence networks using a massive data consisting of five different geographical regions and around 3000 samples for each region. We developed a powerful network model to describe complex mitochondrial evolutionary patterns between codon and non-codon positions. It was interesting to report a different evolution of Asian genomes than those of the rest which is divulged by network motifs. We found evidence that mtDNA undergoes substantial amounts of adaptive evolution, a finding which was supported by a number of previous studies. The dominance of higher order motifs indicated the importance of long-range nucleotide co-occurrence in genomic diversity. Most notably, codon motifs apparently underpinned the preferences among codon positions for co-evolution which is probably highly biased during the origin of the genetic code. Our analyses manifested that codon position co-evolution is very well conserved across human sub-populations and independently maintained within human sub-populations implying the selective role of evolutionary processes on codon position co-evolution. Ergo, this study provided a framework to investigate cooperative genomic interactions which are critical in underlying complex mitochondrial evolution.

Formate-Dependent Microbial Conversion of CO2 and the Dominant Pathways of methanogenesis in production water of high-temperature oil reservoirs amended with bicarbonate

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Guang-Chao eYang

2016-03-01

Full Text Available CO2 sequestration in deep-subsurface formations including oil reservoirs is a potential measure to reduce the CO2 concentration in the atmosphere. However, the fate of the CO2 and the ecological influences in Carbon Dioxide Capture and Storage (CDCS facilities is not understood clearly. In the current study, the fate of CO2 (in bicarbonate form (0~90 mM with 10 mM of formate as electron donor and carbon source was investigated with high-temperature production water from oilfield in China. The isotope data showed that bicarbonate could be reduced to methane by methanogens and major pathway of methanogenesis could be syntrophic formate oxidation coupled with CO2 reduction and formate methanogenesis under the anaerobic conditions. The bicarbonate addition induced the shift of microbial community. Addition of bicarbonate and formate was associated with a decrease of Methanosarcinales, but promotion of Methanobacteriales in all treatments. Thermodesulfovibrio was the major group in all the samples and Thermacetogenium dominated in the high bicarbonate treatments. The results indicated that CO2 from CDCS could be transformed to methane and the possibility of microbial CO2 conversion for enhanced microbial energy recovery in oil reservoirs.

Response of soil microbial communities and microbial interactions to long-term heavy metal contamination.

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Li, Xiaoqi; Meng, Delong; Li, Juan; Yin, Huaqun; Liu, Hongwei; Liu, Xueduan; Cheng, Cheng; Xiao, Yunhua; Liu, Zhenghua; Yan, Mingli

2017-12-01

Due to the persistence of metals in the ecosystem and their threat to all living organisms, effects of heavy metal on soil microbial communities were widely studied. However, little was known about the interactions among microorganisms in heavy metal-contaminated soils. In the present study, microbial communities in Non (CON), moderately (CL) and severely (CH) contaminated soils were investigated through high-throughput Illumina sequencing of 16s rRNA gene amplicons, and networks were constructed to show the interactions among microbes. Results showed that the microbial community composition was significantly, while the microbial diversity was not significantly affected by heavy metal contamination. Bacteria showed various response to heavy metals. Bacteria that positively correlated with Cd, e.g. Acidobacteria_Gp and Proteobacteria_thiobacillus, had more links between nodes and more positive interactions among microbes in CL- and CH-networks, while bacteria that negatively correlated with Cd, e.g. Longilinea, Gp2 and Gp4 had fewer network links and more negative interactions in CL and CH-networks. Unlike bacteria, members of the archaeal domain, i.e. phyla Crenarchaeota and Euryarchaeota, class Thermoprotei and order Thermoplasmatales showed only positive correlation with Cd and had more network interactions in CH-networks. The present study indicated that (i) the microbial community composition, as well as network interactions was shift to strengthen adaptability of microorganisms to heavy metal contamination, (ii) archaea were resistant to heavy metal contamination and may contribute to the adaption to heavy metals. It was proposed that the contribution might be achieved either by improving environment conditions or by cooperative interactions. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Terrestrial Microbial Fuel Cell for Powering a Single-Hop Wireless Sensor Network.

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Zhang, Daxing; Zhu, Yingmin; Pedrycz, Witold; Guo, Yongxian

2016-05-18

Microbial fuel cells (MFCs) are envisioned as one of the most promising alternative renewable energy sources because they can generate electric current continuously while treating waste. Terrestrial Microbial Fuel Cells (TMFCs) can be inoculated and work on the use of soil, which further extends the application areas of MFCs. Energy supply, as a primary influential factor determining the lifetime of Wireless Sensor Network (WSN) nodes, remains an open challenge in sensor networks. In theory, sensor nodes powered by MFCs have an eternal life. However, low power density and high internal resistance of MFCs are two pronounced problems in their operation. A single-hop WSN powered by a TMFC experimental setup was designed and experimented with. Power generation performance of the proposed TMFC, the relationships between the performance of the power generation and the environment temperature, the water content of the soil by weight were measured by experiments. Results show that the TMFC can achieve good power generation performance under special environmental conditions. Furthermore, the experiments with sensor data acquisition and wireless transmission of the TMFC powering WSN were carried out. We demonstrate that the obtained experimental results validate the feasibility of TMFCs powering WSNs.

A Terrestrial Microbial Fuel Cell for Powering a Single-Hop Wireless Sensor Network

Science.gov (United States)

Zhang, Daxing; Zhu, Yingmin; Pedrycz, Witold; Guo, Yongxian

2016-01-01

Microbial fuel cells (MFCs) are envisioned as one of the most promising alternative renewable energy sources because they can generate electric current continuously while treating waste. Terrestrial Microbial Fuel Cells (TMFCs) can be inoculated and work on the use of soil, which further extends the application areas of MFCs. Energy supply, as a primary influential factor determining the lifetime of Wireless Sensor Network (WSN) nodes, remains an open challenge in sensor networks. In theory, sensor nodes powered by MFCs have an eternal life. However, low power density and high internal resistance of MFCs are two pronounced problems in their operation. A single-hop WSN powered by a TMFC experimental setup was designed and experimented with. Power generation performance of the proposed TMFC, the relationships between the performance of the power generation and the environment temperature, the water content of the soil by weight were measured by experiments. Results show that the TMFC can achieve good power generation performance under special environmental conditions. Furthermore, the experiments with sensor data acquisition and wireless transmission of the TMFC powering WSN were carried out. We demonstrate that the obtained experimental results validate the feasibility of TMFCs powering WSNs. PMID:27213346

Performance study and optimization of cooperative diversity networks with co-channel interference

KAUST Repository

Ikki, Salama Said

2014-01-01

In this paper, we investigate the effect of co-channel interference on the performance of cooperative diversity networks with amplify-and-forward (AF) relaying. We consider both conventional and opportunistic relaying. First, we obtain a tight upper-bound for the equivalent signal-to-interference-plus-noise ratio (SINR) at the destination. Subsequently, the cumulative distribution function (CDF), probability density function (PDF) and moment generating function (MGF) of the effective SINR are determined based on the upper-bound. Expressions for the error probabilities in both conventional and opportunistic relaying are derived utilizing the statistical characterization of the effective SINR. We also derive an approximate PDF of the equivalent instantaneous SINR at the destination. This leads to a simple and general asymptotic error probability expression which facilitates better insight into the effect of different system parameters on the error probability. Furthermore, we investigate the problem of optimum resource allocation in the network aiming at improving performance in the presence of resource constraints. We present numerical results that illustrate the excellent match between the analytical results and the simulation results, and the performance enhancement resulting from the proposed optimal resource allocation. © 2014 IEEE.

Microbial Succession in Co-Composting of Chipped-Ground Oil Palm Frond and Palm Oil Mill Effluent

International Nuclear Information System (INIS)

Mohd Najib Ahmad; Siti Ramlah Ahmad Ali; Mohd Ali Hassan

2016-01-01

Succession and phylogenetic profile of microbial communities during co-composting of chipped-ground oil palm frond (CG-OPF) and palm oil mill effluent (POME) were studied by apply-ing polymerase chain reaction-denaturant gel gradient electrophoresis (PCR-DGGE) analysis. The results indicated that the dominant microbial community detected was γ-Pro bacteria such as Pseudomonas sp. at almost throughout the composting process. Whilst Bacillales such as Bacillus psychrodurans were found toward the end of the composting process. Bacteroidetes such as Pedobacter solani were detected at the final stage of composting. This study contributed to a better understanding of microbial shifting and functioning throughout CG-OPF composting. Therefore, PCR-DGGE is recommended to be used as a tool to identify potential microbes that can contribute to a better performance of composting process. (author)

Effect of methyl-β-cyclodextrin on gene expression in microbial conversion of phytosterol.

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Shtratnikova, Victoria Y; Schelkunov, Mikhail I; Dovbnya, Dmitry V; Bragin, Eugeny Y; Donova, Marina V

2017-06-01

Modified β-cyclodextrins are widely used for the enhancement of microbial conversions of lipophilic compounds such as steroids. Multiple mechanisms of cyclodextrin-mediated enhancement of phytosterol bioconversion by mycobacteria had previously been shown to include steroid solubilization, alterations in the cell wall permeability for both steroids and nutrients, facilitation of protein leaking, and activity suppression of some steroid-transforming enzymes.In this work, we studied whether cyclodextrins might affect expression of the genes involved in the steroid catabolic pathway. Phytosterol bioconversion with 9α-hydroxy-androst-4-ene-3,17-dione accumulation by Mycobacterium sp. VKM Ac-1817D in the presence of methylated β-cyclodextrin (MCD) was investigated. RNA sequencing of the whole transcriptomes in different combinations of phytosterol and MCD showed a similar expression level of the steroid catabolism genes related to the KstR-regulon and was responsible for side chain and initial steps of steroid core oxidation; whereas, induction levels of the genes related to the KstR2-regulon were attenuated in the presence of MCD in this strain. The data were attenuated with quantitative real-time PCR.The results contribute to the understanding of cyclodextrin effects on microbial steroid conversion and provide a basis for the use of cyclodextrins as expression enhancers for studies of sterol catabolism in actinobacteria.

The Strategic Impact of Corporate Responsibility and Criminal Networks on Value Co-Creation

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Peter Zettinig

2011-02-01

Full Text Available This article is motivated by the increasing concern about the ever-declining security of pharmaceutical products due to the abundance of counterfeit network actors. We argue that if networks are effective mechanisms for criminal organizations to infiltrate into any value chain, then networks should also work for responsible businesses in their quests to counter this phenomenon of value destruction, which is ultimately detrimental to the value co-creation process. Thus, this article demonstrates a nuanced understanding of the strategic impact of corporate responsibility of actors in networks on value co-creation. The current discourse on value co-creation in business networks is structured in such a way that it precludes its inherent corporate responsibility component even though they are not mutually exclusive. Moreover, research on value co-creation aimed at the proactive and responsible defence of a network substance via value co-protection has been mostly scant. We propose a model of value-optimization through value co-protection and ethical responsibility. This way of theorizing has several implications for both policy making and managerial decision making in the pharmaceutical industry and beyond.

Differential sharing and distinct co-occurrence networks among spatially close bacterial microbiota of bark, mosses and lichens‬‬.

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Aschenbrenner, Ines Aline; Cernava, Tomislav; Erlacher, Armin; Berg, Gabriele; Grube, Martin

2017-05-01

Knowledge of bacterial community host-specificity has increased greatly in recent years. However, the intermicrobiome relationships of unrelated but spatially close organisms remain little understood. Trunks of trees covered by epiphytes represent complex habitats with a mosaic of ecological niches. In this context, we investigated the structure, diversity and interactions of microbiota associated with lichens, mosses and the bare tree bark. Comparative analysis revealed significant differences in the habitat-associated community structures. Corresponding co-occurrence analysis indicated that the lichen microbial network is less complex and less densely interconnected than the moss- and bark-associated networks. Several potential generalists and specialists were identified for the selected habitats. Generalists belonged mainly to Proteobacteria, with Sphingomonas as the most abundant genus. The generalists comprise microorganisms with generally beneficial features, such as nitrogen fixation or other supporting functions, according to a metagenomic analysis. We argue that beneficial strains shared among hosts contribute to ecological stability of the host biocoenoses. © 2017 John Wiley & Sons Ltd.

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

Science.gov (United States)

Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

2015-06-12

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

Microbial Gene Abundance and Expression Patterns across a River to Ocean Salinity Gradient.

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Caroline S Fortunato

Full Text Available Microbial communities mediate the biogeochemical cycles that drive ecosystems, and it is important to understand how these communities are affected by changing environmental conditions, especially in complex coastal zones. As fresh and marine waters mix in estuaries and river plumes, the salinity, temperature, and nutrient gradients that are generated strongly influence bacterioplankton community structure, yet, a parallel change in functional diversity has not been described. Metagenomic and metatranscriptomic analyses were conducted on five water samples spanning the salinity gradient of the Columbia River coastal margin, including river, estuary, plume, and ocean, in August 2010. Samples were pre-filtered through 3 μm filters and collected on 0.2 μm filters, thus results were focused on changes among free-living microbial communities. Results from metagenomic 16S rRNA sequences showed taxonomically distinct bacterial communities in river, estuary, and coastal ocean. Despite the strong salinity gradient observed over sampling locations (0 to 33, the functional gene profiles in the metagenomes were very similar from river to ocean with an average similarity of 82%. The metatranscriptomes, however, had an average similarity of 31%. Although differences were few among the metagenomes, we observed a change from river to ocean in the abundance of genes encoding for catabolic pathways, osmoregulators, and metal transporters. Additionally, genes specifying both bacterial oxygenic and anoxygenic photosynthesis were abundant and expressed in the estuary and plume. Denitrification genes were found throughout the Columbia River coastal margin, and most highly expressed in the estuary. Across a river to ocean gradient, the free-living microbial community followed three different patterns of diversity: 1 the taxonomy of the community changed strongly with salinity, 2 metabolic potential was highly similar across samples, with few differences in

Microbial Gene Abundance and Expression Patterns across a River to Ocean Salinity Gradient.

Science.gov (United States)

Fortunato, Caroline S; Crump, Byron C

2015-01-01

Microbial communities mediate the biogeochemical cycles that drive ecosystems, and it is important to understand how these communities are affected by changing environmental conditions, especially in complex coastal zones. As fresh and marine waters mix in estuaries and river plumes, the salinity, temperature, and nutrient gradients that are generated strongly influence bacterioplankton community structure, yet, a parallel change in functional diversity has not been described. Metagenomic and metatranscriptomic analyses were conducted on five water samples spanning the salinity gradient of the Columbia River coastal margin, including river, estuary, plume, and ocean, in August 2010. Samples were pre-filtered through 3 μm filters and collected on 0.2 μm filters, thus results were focused on changes among free-living microbial communities. Results from metagenomic 16S rRNA sequences showed taxonomically distinct bacterial communities in river, estuary, and coastal ocean. Despite the strong salinity gradient observed over sampling locations (0 to 33), the functional gene profiles in the metagenomes were very similar from river to ocean with an average similarity of 82%. The metatranscriptomes, however, had an average similarity of 31%. Although differences were few among the metagenomes, we observed a change from river to ocean in the abundance of genes encoding for catabolic pathways, osmoregulators, and metal transporters. Additionally, genes specifying both bacterial oxygenic and anoxygenic photosynthesis were abundant and expressed in the estuary and plume. Denitrification genes were found throughout the Columbia River coastal margin, and most highly expressed in the estuary. Across a river to ocean gradient, the free-living microbial community followed three different patterns of diversity: 1) the taxonomy of the community changed strongly with salinity, 2) metabolic potential was highly similar across samples, with few differences in functional gene abundance

Modular co-evolution of metabolic networks

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Yu Zhong-Hao

2007-08-01

Full Text Available Abstract Background The architecture of biological networks has been reported to exhibit high level of modularity, and to some extent, topological modules of networks overlap with known functional modules. However, how the modular topology of the molecular network affects the evolution of its member proteins remains unclear. Results In this work, the functional and evolutionary modularity of Homo sapiens (H. sapiens metabolic network were investigated from a topological point of view. Network decomposition shows that the metabolic network is organized in a highly modular core-periphery way, in which the core modules are tightly linked together and perform basic metabolism functions, whereas the periphery modules only interact with few modules and accomplish relatively independent and specialized functions. Moreover, over half of the modules exhibit co-evolutionary feature and belong to specific evolutionary ages. Peripheral modules tend to evolve more cohesively and faster than core modules do. Conclusion The correlation between functional, evolutionary and topological modularity suggests that the evolutionary history and functional requirements of metabolic systems have been imprinted in the architecture of metabolic networks. Such systems level analysis could demonstrate how the evolution of genes may be placed in a genome-scale network context, giving a novel perspective on molecular evolution.

Supra-molecular networks for CO2 capture

Science.gov (United States)

Sadowski, Jerzy; Kestell, John

Utilizing capabilities of low-energy electron microscopy (LEEM) for non-destructive interrogation of the real-time molecular self-assembly, we have investigated supramolecular systems based on carboxylic acid-metal complexes, such as trimesic and mellitic acid, doped with transition metals. Such 2D networks can act as host systems for transition-metal phthalocyanines (MPc; M = Fe, Ti, Sc). The electrostatic interactions of CO2 molecules with transition metal ions can be tuned by controlling the type of TM ion and the size of the pore in the host network. We further applied infrared reflection-absorption spectroscopy (IRRAS) to determine of the molecular orientation of the functional groups and the whole molecule in the 2D monolayers of carboxylic acid. The kinetics and mechanism of the CO2 adsorption/desorption on the 2D molecular network, with and without the TM ion doping, have been also investigated. This research used resources of the Center for Functional Nanomaterials, which is the U.S. DOE Office of Science User Facility, at Brookhaven National Laboratory under Contract No. DE-SC0012704.

Soil microbial metabolic quotient (qCO2) of twelve ecosystems of Mt. Kilimanjaro

Science.gov (United States)

Pabst, Holger; Gerschlauer, Friederike; Kiese, Ralf; Kuzyakov, Yakov

2014-05-01

Soil organic carbon, microbial biomass carbon (MBC) and the metabolic quotient qCO2 - as sensitive and important parameters for soil fertility and C turnover - are strongly affected by land-use changes all over the world. These effects are particularly distinct upon conversion of natural to agricultural ecosystems due to very fast carbon (C) and nutrient cycles and high vulnerability, especially in the tropics. In this study, we used an elevational gradient on Mt. Kilimanjaro to investigate the effects of land-use change and elevation on Corg, MBC and qCO2. Down to a soil depth of 18 cm we compared 4 natural (Helichrysum, Erica forest, Podocarpus forest, Ocotea forest), 5 seminatural (disturbed Podocarpus forest, disturbed Ocotea forest, lower montane forest, grassland, savannah), 1 sustainably used (homegarden) and 2 intensively used ecosystems (coffee plantation, maize field) on an elevation gradient from 950 to 3880 m a.s.l.. Using an incubation device, soil CO2-efflux of 18 cm deep soil cores was measured under field moist conditions and mean annual temperature. MBC to Corg ratios varied between 0.7 and 2.3%. qCO2 increased with magnitude of the disturbance, albeit this effect decreased with elevation. Following the annual precipitation of the ecosystems, both, Corg and MBC showed a hum-shaped distribution with elevation, whereas their maxima were between 2500 and 3000 m a.s.l.. Additionaly, Corg and MBC contents were significantly reduced in intensively used agricultural systems. We conclude that the soil microbial biomass and its activity in Mt. Kilimanjaro ecosystems are strongly altered by land-use. This effect is more distinct in lower than in higher elevated ecosystems and strongly dependent on the magnitude of disturbance.

Studying Microbial Mat Functioning Amidst "Unexpected Diversity": Methodological Approaches and Initial Results from Metatranscriptomes of Mats Over Diel cycles, iTags from Long Term Manipulations, and Biogeochemical Cycling in Simplified Microbial Mats Constructed from Cultures

Science.gov (United States)

Bebout, B.; Bebout, L. E.; Detweiler, A. M.; Everroad, R. C.; Lee, J.; Pett-Ridge, J.; Weber, P. K.

2014-12-01

Microbial mats are famously amongst the most diverse microbial ecosystems on Earth, inhabiting some of the most inclement environments known, including hypersaline, dry, hot, cold, nutrient poor, and high UV environments. The high microbial diversity of microbial mats makes studies of microbial ecology notably difficult. To address this challenge, we have been using a combination of metagenomics, metatranscriptomics, iTags and culture-based simplified microbial mats to study biogeochemical cycling (H2 production, N2 fixation, and fermentation) in microbial mats collected from Elkhorn Slough, Monterey Bay, California. Metatranscriptomes of microbial mats incubated over a diel cycle have revealed that a number of gene systems activate only during the day in Cyanobacteria, while the remaining appear to be constitutive. The dominant cyanobacterium in the mat (Microcoleus chthonoplastes) expresses several pathways for nitrogen scavenging undocumented in cultured strains, as well as the expression of two starch storage and utilization cycles. Community composition shifts in response to long term manipulations of mats were assessed using iTags. Changes in community diversity were observed as hydrogen fluxes increased in response to a lowering of sulfate concentrations. To produce simplified microbial mats, we have isolated members of 13 of the 15 top taxa from our iTag libraries into culture. Simplified microbial mats and simple co-cultures and consortia constructed from these isolates reproduce many of the natural patterns of biogeochemical cycling in the parent natural microbial mats, but against a background of far lower overall diversity, simplifying studies of changes in gene expression (over the short term), interactions between community members, and community composition changes (over the longer term), in response to environmental forcing.

Prokaryotes in subsoil – evidence for spatial separation of oligotrophs and copiotrophs by co-occurrence networks

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Michael eSchloter

2015-11-01

Full Text Available Soil microbial communities provide a wide range of soil functions including nutrient cycling, soil formation, and plant growth promotion. On the small scale, nutrient rich soil hotspots developed from soil animal or plant activity are important drivers for microbial communities and their activity pattern. Nevertheless, in subsoil, the spatial heterogeneity of microbes with diverging lifestyles has been barely considered so far. In this study, the phylogenetic composition of the bacterial and archaeal microbiome based on 16S rRNA gene pyrosequencing was investigated in the soil compartments bulk soil, drilosphere, and rhizosphere in topsoil and in the subsoil of an agricultural field. With co-occurrence network analysis, the spatial separation of typically oligotrophs and heterotrophs in subsoil and hotspots was assessed. Four co-occurring bacterial communities were identified and attributed to bulk topsoil, bulk subsoil, drilosphere, and rhizosphere. The bacterial phyla Proteobacteria and Bacteroidetes, which represent many copiotrophic bacteria, are affiliated to the hotspot communities – the rhizosphere and drilosphere – both in topsoil and subsoil. Acidobacteria, Actinobacteria, Gemmatimonadetes, Planctomycetes, and Verrucomicrobia with many oligotrophic bacteria, are the abundant groups of the bulk subsoil community. The bacterial core microbiome in this soil was estimated and only covers 7.6% of the bacterial sequencing reads but includes both oligotrophic and copiotrophic bacteria. Instead, the archaeal core microbiome includes 56% of the overall archaeal diversity and comprises only the ammonium oxidizing Nitrososphaera. Thus, the spatial variability of nutrient quality and quantity strongly shapes the bacterial community composition and their interaction in subsoil, whereas archaea are a stable backbone of the soil prokaryotes.

Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.

Science.gov (United States)

Rubiolo, Mariano; Milone, Diego H; Stegmayer, Georgina

2015-01-01

Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel method based on a pool of neural networks for obtaining a gene regulatory network from a gene expression dataset. They are used for modeling each possible interaction between pairs of genes in the dataset, and a set of mining rules is applied to accurately detect the subjacent relations among genes. The results obtained on artificial and real datasets confirm the method effectiveness for discovering regulatory networks from a proper modeling of the temporal dynamics of gene expression profiles.

The microbial fate of carbon in high-latitude seas: Impact of the microbial loop on oceanic uptake of CO{sub 2}

Energy Technology Data Exchange (ETDEWEB)

Yager, P.L.

1996-12-31

This dissertation examines pelagic microbial processes in high-latitude seas, how they affect regional and global carbon cycling, and how they might respond to hypothesized changes in climate. Critical to these interests is the effect of cold temperature on bacterial activity. Also important is the extent to which marine biological processes in general impact the inorganic carbon cycle. The study area is the Northeast Water (NEW) Polynya, a seasonally-recurrent opening in the permanent ice situated over the northeastern Greenland continental shelf. This work was part of an international, multi-disciplinary research project studying carbon cycling in the coastal Arctic. The first chapter describes a simple model which links a complex marine food web to a simplified ocean and atmosphere. The second chapter investigates the inorganic carbon inventory of the summertime NEW Polynya surface waters to establish the effect of biological processes on the air-sea pCO{sub 2} gradient. The third and fourth chapters use a kinetic approach to examine microbial activities in the NEW Polynya as a function of temperature and dissolved organic substrate concentration, testing the so-called Pomeroy hypothesis that microbial activity is disproportionately reduced at low environmental temperatures owing to increased organic substrate requirements. Together, the suite of data collected on microbial activities, cell size, and grazing pressure suggest how unique survival strategies adopted by an active population of high-latitude bacteria may contribute to, rather than detract from, an efficient biological carbon pump.

Visualization and Analysis of the Co-authorship Network of Articles of National Congress on “Family Pathology” Using Social Network Analysis Indicators

OpenAIRE

امیررضا اصنافی; الهه حسینی; سارا آمایه

2017-01-01

The present paper aims to visualize and analyze the co-authorship network of articles of national congress on family pathology using social network analysis (SNA) indicators. The present paper employed the descriptive research method with scientometrics approach and analyzed social network by micro and macro indicators. UCINET software was used to visualize and analyze the co-authorship network, and VOS viewer software was utilized to visualize a density network of the co-authorship. The 6th ...

Layered signaling regulatory networks analysis of gene expression involved in malignant tumorigenesis of non-resolving ulcerative colitis via integration of cross-study microarray profiles.

Science.gov (United States)

Fan, Shengjun; Pan, Zhenyu; Geng, Qiang; Li, Xin; Wang, Yefan; An, Yu; Xu, Yan; Tie, Lu; Pan, Yan; Li, Xuejun

2013-01-01

Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups. In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks. Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one. The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis sketched a directive insight into colorectal carcinogenesis

Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

Directory of Open Access Journals (Sweden)

Paules Richard S

2007-11-01

Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying

Effects of co-inoculating rice straw with ruminal microbiota and anaerobic sludge: digestion performance and spatial distribution of microbial communities.

Science.gov (United States)

Deng, Yuying; Huang, Zhenxing; Zhao, Mingxing; Ruan, Wenquan; Miao, Hengfeng; Ren, Hongyan

2017-07-01

Ruminal microbiota (RM) were co-inoculated with anaerobic sludge (AS) at different ratios to study the digestion of rice straw in batch experiments. The CH 4 yield reached 273.64 mL/g volatile solid (VS) at a co-inoculum ratio of 1:1. The xylanase and cellulase activities were 198.88-212.88 and 24.51-29.08 U/mL in co-inoculated samples, respectively, and were significantly different compared to the results for single inoculum (p rumen did not settle in the co-inoculated system, whereas Clostridiales members became the main polysaccharide degraders. Microbial interactions involving hydrolytic bacteria and acetoclastic methanogens in the residue were considered to be significant for hydrolysis activities and methane production. Syntrophy involving propionate oxidizers with associated methanogens occurred in the liquid phase. Our findings provide a better understanding of the anaerobic digestion of rice straw that is driven by specific microbial populations.

Biomarkers of inflammation, coagulation and microbial translocation in HIV/HCV co-infected patients in the SMART study

DEFF Research Database (Denmark)

Peters, Lars; Neuhaus, Jacqueline; Duprez, Daniel

2014-01-01

BACKGROUND: Previous results from the SMART study showed that HIV/viral hepatitis co-infected persons with impaired liver function are at increased risk of death following interruption of antiretroviral therapy (ART). OBJECTIVES: To investigate the influence of fibrosis and ART interruption...... on levels of biomarkers of inflammation, coagulation and microbial translocation in HIV/HCV co-infected persons in the SMART study. STUDY DESIGN: All HIV/HCV co-infected persons with stored plasma at study entry and at six months of follow-up were included (N=362). D-dimer, IL-6, sCD14 and hepatic...

Benefits to decomposition rates when using digestate as compost co-feedstock: Part II - Focus on microbial community dynamics.

Science.gov (United States)

Arab, Golnaz; Razaviarani, Vahid; Sheng, Zhiya; Liu, Yang; McCartney, Daryl

2017-10-01

Linkage between composting reactor performance and microbial community dynamics was investigated during co-composting of digestate and fresh feedstock (organic fraction of municipal solid waste) using 25L reactors. Previously, the relationship between composting performance and various physicochemical parameters were reported in Part I of the study (Arab and McCartney, 2017). Three digestate to fresh feedstock ratios (0, 40, and 100%; wet weight basis) were selected for analysis of microbial community dynamics. The 40% ratio was selected because it was found to perform the best (Arab and McCartney, 2017). Illumina sequencing results revealed that the reactor with a greater composting performance (higher organic matter degradation and higher heat generation; 40% ratio) was associated with higher microbial diversity. Two specific bacterial orders that might result in higher performance were Thermoactinomycetaceae and Actinomycetales with a higher sequence abundance during thermophilic composting phase and during the maturing composting phase, respectively. Galactomyces, Pichia, Chaetomium, and Acremonium were the four fungal genera that are probably also involved in higher organic matter degradation in the reactor with better performance. The redundancy analysis (RDA) biplot indicated that among the studied environmental variables, temperature, total ammonia nitrogen and nitrate concentration accounted for much of the major shifts in microbial sequence abundance during the co-composting process. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Genetic architecture of gene expression in the chicken

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Stanley Dragana

2013-01-01

Full Text Available Abstract Background The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse gene expression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome. Results Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted. Conclusions We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

Co-evolution of social networks and continuous actor attributes

NARCIS (Netherlands)

Niezink, Nynke M.D.; Snijders, Tom A.B.

2017-01-01

Social networks and the attributes of the actors in these networks are not static; they may develop interdependently over time. The stochastic actor-oriented model allows for statistical inference on the mechanisms driving this co-evolution process. In earlier versions of this model, dynamic actor

The Arabidopsis co-expression tool (act): a WWW-based tool and database for microarray-based gene expression analysis

DEFF Research Database (Denmark)

Jen, C. H.; Manfield, I. W.; Michalopoulos, D. W.

2006-01-01

be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots......We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (act) , based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression...

Diversity and stability of coral endolithic microbial communities at a naturally high pCO2 reef.

Science.gov (United States)

Marcelino, Vanessa Rossetto; Morrow, Kathleen M; van Oppen, Madeleine J H; Bourne, David G; Verbruggen, Heroen

2017-10-01

The health and functioning of reef-building corals is dependent on a balanced association with prokaryotic and eukaryotic microbes. The coral skeleton harbours numerous endolithic microbes, but their diversity, ecological roles and responses to environmental stress, including ocean acidification (OA), are not well characterized. This study tests whether pH affects the diversity and structure of prokaryotic and eukaryotic algal communities associated with skeletons of Porites spp. using targeted amplicon (16S rRNA gene, UPA and tufA) sequencing. We found that the composition of endolithic communities in the massive coral Porites spp. inhabiting a naturally high pCO 2 reef (avg. pCO 2 811 μatm) is not significantly different from corals inhabiting reference sites (avg. pCO 2 357 μatm), suggesting that these microbiomes are less disturbed by OA than previously thought. Possible explanations may be that the endolithic microhabitat is highly homeostatic or that the endolithic micro-organisms are well adapted to a wide pH range. Some of the microbial taxa identified include nitrogen-fixing bacteria (Rhizobiales and cyanobacteria), algicidal bacteria in the phylum Bacteroidetes, symbiotic bacteria in the family Endozoicomoniaceae, and endolithic green algae, considered the major microbial agent of reef bioerosion. Additionally, we test whether host species has an effect on the endolithic community structure. We show that the endolithic community of massive Porites spp. is substantially different and more diverse than that found in skeletons of the branching species Seriatopora hystrix and Pocillopora damicornis. This study reveals highly diverse and structured microbial communities in Porites spp. skeletons that are possibly resilient to OA. © 2017 John Wiley & Sons Ltd.

Using species co-occurrence networks to assess the impacts of climate change

DEFF Research Database (Denmark)

Bastos Araujo, Miguel; Rozenfeld, Alejandro; Rahbek, Carsten

2011-01-01

Viable populations of species occur in a given place if three conditions are met: the environment at the place is suitable; the species is able to colonize it; co-occurrence is possible despite or because of interactions with other species. Studies investigating the effects of climate change...... on species have mainly focused on measuring changes in climate suitability. Complex interactions among species have rarely been explored in such studies. We extend network theory to the analysis of complex patterns of co-occurrence among species. The framework is used to explore the robustness of networks...... under climate change. With our data, we show that networks describing the geographic pattern of co-occurrence among species display properties shared by other complex networks, namely that most species are poorly connected to other species in the network and only a few are highly connected. In our...

Gene co-expression analysis identifies gene clusters associated with isotropic and polarized growth in Aspergillus fumigatus conidia.

Science.gov (United States)

Baltussen, Tim J H; Coolen, Jordy P M; Zoll, Jan; Verweij, Paul E; Melchers, Willem J G

2018-04-26

Aspergillus fumigatus is a saprophytic fungus that extensively produces conidia. These microscopic asexually reproductive structures are small enough to reach the lungs. Germination of conidia followed by hyphal growth inside human lungs is a key step in the establishment of infection in immunocompromised patients. RNA-Seq was used to analyze the transcriptome of dormant and germinating A. fumigatus conidia. Construction of a gene co-expression network revealed four gene clusters (modules) correlated with a growth phase (dormant, isotropic growth, polarized growth). Transcripts levels of genes encoding for secondary metabolites were high in dormant conidia. During isotropic growth, transcript levels of genes involved in cell wall modifications increased. Two modules encoding for growth and cell cycle/DNA processing were associated with polarized growth. In addition, the co-expression network was used to identify highly connected intermodular hub genes. These genes may have a pivotal role in the respective module and could therefore be compelling therapeutic targets. Generally, cell wall remodeling is an important process during isotropic and polarized growth, characterized by an increase of transcripts coding for hyphal growth and cell cycle/DNA processing when polarized growth is initiated. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Effect of ecosystems substitutions and CO2 increase of the atmosphere on the microbial ecosystems of forests

International Nuclear Information System (INIS)

Martin, F.

2007-01-01

Biological diversity is often exclusively considered at the level of plants and animals, whereas the bulk of global biodiversity is in fact at the microbial level. Although it is clear that the ecology of our planet is driven by microbial ecosystems, we are severely hampered by our limited understanding of the diversity and function of such microbial ecosystems. In the present project, teams in the disciplines of geochemistry, soil microbiology, genomics and ecosystem processes are assembled to study the relationship between environmental change, land use changes, biodiversity, and functioning of forest ecosystems. The network has a strong focus on developing and applying biochemical and genotyping methodologies to address key scientific issues in soil microbial ecology. These include assessing the impact of environmental- and land use changes on microbial diversity and function and exploring the evolutionary and mechanistic links between biological diversity and ecosystem function. In the present study, we have shown that: (1) The native mixed forest showed the highest microbial diversity (2) The mono specific plantations of tree species (e.g., oak, beech, pine, spruce) strikingly alter genetic and functional diversities of soil bacterial and fungal species. (3) Bacterial denitrification rates were dramatically modified by the planted species. Only by taking into account the impact of forest management on below-ground microbial diversity can one hope to get a full ecosystem-based understanding, and this must be addressed via modelling in order to provide relevant and useful information for conservation and policy making. (author)

The pH and pCO2 dependence of sulfate reduction in shallow-sea hydrothermal CO2 - venting sediments (Milos Island, Greece).

Science.gov (United States)

Bayraktarov, Elisa; Price, Roy E; Ferdelman, Timothy G; Finster, Kai

2013-01-01

Microbial sulfate reduction (SR) is a dominant process of organic matter mineralization in sulfate-rich anoxic environments at neutral pH. Recent studies have demonstrated SR in low pH environments, but investigations on the microbial activity at variable pH and CO2 partial pressure are still lacking. In this study, the effect of pH and pCO2 on microbial activity was investigated by incubation experiments with radioactive (35)S targeting SR in sediments from the shallow-sea hydrothermal vent system of Milos, Greece, where pH is naturally decreased by CO2 release. Sediments differed in their physicochemical characteristics with distance from the main site of fluid discharge. Adjacent to the vent site (T ~40-75°C, pH ~5), maximal sulfate reduction rates (SRR) were observed between pH 5 and 6. SR in hydrothermally influenced sediments decreased at neutral pH. Sediments unaffected by hydrothermal venting (T ~26°C, pH ~8) expressed the highest SRR between pH 6 and 7. Further experiments investigating the effect of pCO2 on SR revealed a steep decrease in activity when the partial pressure increased from 2 to 3 bar. Findings suggest that sulfate reducing microbial communities associated with hydrothermal vent system are adapted to low pH and high CO2, while communities at control sites required a higher pH for optimal activity.

Measuring co-authorship and networking-adjusted scientific impact.

Science.gov (United States)

Ioannidis, John P A

2008-07-23

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I(1) for a single scientist as the number of authors who appear in at least I(1) papers of the specific scientist. For a group of scientists or institution, I(n) is defined as the number of authors who appear in at least I(n) papers that bear the affiliation of the group or institution. I(1) depends on the number of papers authored N(p). The power exponent R of the relationship between I(1) and N(p) categorizes scientists as solitary (R>2.5), nuclear (R = 2.25-2.5), networked (R = 2-2.25), extensively networked (R = 1.75-2) or collaborators (Raccountable co-authorship behaviour in published articles.

Co-creation and Co-innovation in a Collaborative Networked Environment

Science.gov (United States)

Klen, Edmilson Rampazzo

Leveraged by the advances in communication and information Technologies, producers and consumers are developing a new behavior. Together with the new emerging collaborative manifestations this behavior may directly impact the way products are developed. This powerful combination indicates that consumers will be involved in a very early stage in product development processes supporting even more the creation and innovation of products. This new way of collaboration gives rise to a new collaborative networked environment based on co-creation and co-innovation. This work will present some evolutionary steps that point to the development of this environment where prosumer communities and virtual organizations interact and collaborate.

A Mobile Sensor Network to Map CO2 in Urban Environments

Science.gov (United States)

Lee, J.; Christen, A.; Nesic, Z.; Ketler, R.

2014-12-01

Globally, an estimated 80% of all fuel-based CO2 emissions into the atmosphere are attributable to cities, but there is still a lack of tools to map, visualize and monitor emissions to the scales at which emissions reduction strategies can be implemented - the local and urban scale. Mobile CO2 sensors, such as those attached to taxis and other existing mobile platforms, may be a promising way to observe and map CO2 mixing ratios across heterogenous urban environments with a limited number of sensors. Emerging modular open source technologies, and inexpensive compact sensor components not only enable rapid prototyping and replication, but also are allowing for the miniaturization and mobilization of traditionally fixed sensor networks. We aim to optimize the methods and technologies for monitoring CO2 in cities using a network of CO2 sensors deployable on vehicles and bikes. Our sensor technology is contained in a compact weather-proof case (35.8cm x 27.8cm x 11.8cm), powered independently by battery or by car, and includes the Li-Cor Li-820 infrared gas analyzer (Licor Inc, lincoln, NB, USA), Arduino Mega microcontroller (Arduino CC, Italy) and Adafruit GPS (Adafruit Technologies, NY, USA), and digital air temperature thermometer which measure CO2 mixing ratios (ppm), geolocation and speed, pressure and temperature, respectively at 1-second intervals. With the deployment of our sensor technology, we will determine if such a semi-autonomous mobile approach to monitoring CO2 in cities can determine excess urban CO2 mixing ratios (i.e. the 'urban CO2 dome') when compared to values measured at a fixed, remote background site. We present results from a pilot study in Vancouver, BC, where the a network of our new sensors was deployed both in fixed network and in a mobile campaign and examine the spatial biases of the two methods.

Expression and function of serotonin 2A and 2B receptors in the mammalian respiratory network.

Directory of Open Access Journals (Sweden)

Marcus Niebert

Full Text Available Neurons of the respiratory network in the lower brainstem express a variety of serotonin receptors (5-HTRs that act primarily through adenylyl cyclase. However, there is one receptor family including 5-HT(2A, 5-HT(2B, and 5-HT(2C receptors that are directed towards protein kinase C (PKC. In contrast to 5-HT(2ARs, expression and function of 5-HT(2BRs within the respiratory network are still unclear. 5-HT(2BR utilizes a Gq-mediated signaling cascade involving calcium and leading to activation of phospholipase C and IP3/DAG pathways. Based on previous studies, this signal pathway appears to mediate excitatory actions on respiration. In the present study, we analyzed receptor expression in pontine and medullary regions of the respiratory network both at the transcriptional and translational level using quantitative RT-PCR and self-made as well as commercially available antibodies, respectively. In addition we measured effects of selective agonists and antagonists for 5-HT(2ARs and 5-HT(2BRs given intra-arterially on phrenic nerve discharges in juvenile rats using the perfused brainstem preparation. The drugs caused significant changes in discharge activity. Co-administration of both agonists revealed a dominance of the 5-HT(2BR. Given the nature of the signaling pathways, we investigated whether intracellular calcium may explain effects observed in the respiratory network. Taken together, the results of this study suggest a significant role of both receptors in respiratory network modulation.

Effects of Calcium Source on Biochemical Properties of Microbial CaCO3 Precipitation.

Science.gov (United States)

Xu, Jing; Du, Yali; Jiang, Zhengwu; She, Anming

2015-01-01

The biochemical properties of CaCO3 precipitation induced by Sporosarcina pasteurii, an ureolytic type microorganism, were investigated. Effects of calcium source on the precipitation process were examined, since calcium source plays a key role in microbiologically induced mineralization. Regardless of the calcium source type, three distinct stages in the precipitation process were identified by Ca(2+), NH4 (+), pH and cell density monitoring. Compared with stage 1 and 3, stage 2 was considered as the most critical part since biotic CaCO3 precipitation occurs during this stage. Kinetics studies showed that the microbial CaCO3 precipitation rate for calcium lactate was over twice of that for calcium nitrate, indicating that calcium lactate is more beneficial for the cell activity, which in turn determines urease production and CaCO3 precipitation. X-ray diffraction analysis confirmed the CaCO3 crystal as calcite, although scanning electron microscopy revealed a difference in crystal size and morphology if calcium source was different. The findings of this paper further suggest a promising application of microbiologically induced CaCO3 precipitation in remediation of surface and cracks of porous media, e.g., cement-based composites, particularly by using organic source of calcium lactate.

Integration of biological networks and gene expression data using Cytoscape

DEFF Research Database (Denmark)

Cline, M.S.; Smoot, M.; Cerami, E.

2007-01-01

of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules......Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context...... and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape....

A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression

Directory of Open Access Journals (Sweden)

Mao Yu

2009-07-01

Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From

Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils

Science.gov (United States)

Álvarez-Yela, Astrid Catalina; Gómez-Cano, Fabio; Zambrano, María Mercedes; Husserl, Johana; Danies, Giovanna; Restrepo, Silvia; González-Barrios, Andrés Fernando

2017-01-01

Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community. PMID:28767679

Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils.

Directory of Open Access Journals (Sweden)

María Camila Alvarez-Silva

Full Text Available Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community.

Response of core microbial consortia to hydrocarbon contaminations in coastal sediment habitats

Directory of Open Access Journals (Sweden)

Mathilde Jeanbille

2016-10-01

Full Text Available Traditionally, microbial surveys investigating the effect of chronic anthropogenic pressure such as polyaromatic hydrocarbons (PAHs contaminations consider just the alpha and beta diversity and ignore the interactions among the different taxa forming the microbial community. Here, we investigated the ecological relationships between the three domains of life (i.e. Bacteria, Archaea and Eukarya using 454 pyrosequencing data of the 16S rRNA and 18S rRNA genes from chronically impacted and pristine sediments, along the coasts of the Mediterranean Sea (Gulf of Lion, Vermillion coast, Corsica, Bizerte lagoon and Lebanon and the French Atlantic Ocean (Bay of Biscay and English Channel. Our approach provided a robust ecological framework for the partition of the taxa abundance distribution into 859 core OTUs and 6629 satellite OTUs. OTUs forming the core microbial community showed the highest sensitivity to changes in environmental and contaminant variations, with salinity, latitude, temperature, particle size distribution, total organic carbon (TOC and PAH concentrations as main drivers of community assembly. The core communities were dominated by Gammaproteobacteria and Deltaproteobacteria for Bacteria, by Thaumarchaeota, Bathyarchaeota and Thermoplasmata for Archaea and Metazoa and Dinoflagellata for Eukarya. In order to find associations among microorganisms, we generated a co-occurrence network in which PAHs were found to impact significantly the potential predator – prey relationship in one microbial consortium composed of ciliates and Actinobacteria. Comparison of network topological properties between contaminated and non-contaminated samples showed substantial differences in the structure of the network and indicated a higher vulnerability to environmental perturbations in the contaminated sediments.

Plant stimulation of soil microbial community succession: how sequential expression mediates soil carbon stabilization and turnover

Energy Technology Data Exchange (ETDEWEB)

Firestone, Mary [Univ. of California, Berkeley, CA (United States)

2015-03-31

It is now understood that most plant C is utilized or transformed by soil microorganisms en route to stabilization. Hence the composition of microbial communities that mediate decomposition and transformation of root C is critical, as are the metabolic capabilities of these communities. The change in composition and function of the C-transforming microbial communities over time in effect defines the biological component of soil C stabilization. Our research was designed to test 2 general hypotheses; the first two hypotheses are discussed first; H1: Root-exudate interactions with soil microbial populations results in the expression of enzymatic capacities for macromolecular, complex carbon decomposition; and H2: Microbial communities surrounding roots undergo taxonomic succession linked to functional gene activities as roots grow, mature, and decompose in soil. Over the term of the project we made significant progress in 1) quantifying the temporal pattern of root interactions with the soil decomposing community and 2) characterizing the role of root exudates in mediating these interactions.

The pH and pCO2 dependence of sulfate reduction in shallow-sea hydrothermal CO2 – venting sediments (Milos Island, Greece)

Science.gov (United States)

Bayraktarov, Elisa; Price, Roy E.; Ferdelman, Timothy G.; Finster, Kai

2013-01-01

Microbial sulfate reduction (SR) is a dominant process of organic matter mineralization in sulfate-rich anoxic environments at neutral pH. Recent studies have demonstrated SR in low pH environments, but investigations on the microbial activity at variable pH and CO2 partial pressure are still lacking. In this study, the effect of pH and pCO2 on microbial activity was investigated by incubation experiments with radioactive 35S targeting SR in sediments from the shallow-sea hydrothermal vent system of Milos, Greece, where pH is naturally decreased by CO2 release. Sediments differed in their physicochemical characteristics with distance from the main site of fluid discharge. Adjacent to the vent site (T ~40–75°C, pH ~5), maximal sulfate reduction rates (SRR) were observed between pH 5 and 6. SR in hydrothermally influenced sediments decreased at neutral pH. Sediments unaffected by hydrothermal venting (T ~26°C, pH ~8) expressed the highest SRR between pH 6 and 7. Further experiments investigating the effect of pCO2 on SR revealed a steep decrease in activity when the partial pressure increased from 2 to 3 bar. Findings suggest that sulfate reducing microbial communities associated with hydrothermal vent system are adapted to low pH and high CO2, while communities at control sites required a higher pH for optimal activity. PMID:23658555

Disease gene characterization through large-scale co-expression analysis.

Directory of Open Access Journals (Sweden)

Allen Day

2009-12-01

Full Text Available In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET.Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2 and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.

Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities

Science.gov (United States)

Yusufaly, Tahir I.; Boedicker, James Q.

2017-08-01

Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating gene expression. However, the biology of QS remains incompletely understood in heterogeneous communities, where variant bacterial strains possess distinct QS systems that produce chemically unique AIs. AI molecules bind to ‘cognate’ receptors, but also to ‘non-cognate’ receptors found in other strains, resulting in inter-strain crosstalk. Understanding these interactions is a prerequisite for deciphering the consequences of crosstalk in real ecosystems, where multiple AIs are regularly present in the same environment. As a step towards this goal, we map crosstalk in a heterogeneous community of variant QS strains onto an artificial neural network model. This formulation allows us to systematically analyze how crosstalk regulates the community’s capacity for flexible decision making, as quantified by the Boltzmann entropy of all QS gene expression states of the system. In a mean-field limit of complete cross-inhibition between variant strains, the model is exactly solvable, allowing for an analytical formula for the number of variants that maximize capacity as a function of signal kinetics and activation parameters. An analysis of previous experimental results on the Staphylococcus aureus two-component Agr system indicates that the observed combination of variant numbers, gene expression rates and threshold concentrations lies near this critical regime of parameter space where capacity peaks. The results are suggestive of a potential evolutionary driving force for diversification in certain QS systems.

Analysis of gut microbial regulation of host gene expression along the length of the gut and regulation of gut microbial ecology through MyD88.

Science.gov (United States)

Larsson, Erik; Tremaroli, Valentina; Lee, Ying Shiuan; Koren, Omry; Nookaew, Intawat; Fricker, Ashwana; Nielsen, Jens; Ley, Ruth E; Bäckhed, Fredrik

2012-08-01

The gut microbiota has profound effects on host physiology but local host-microbial interactions in the gut are only poorly characterised and are likely to vary from the sparsely colonised duodenum to the densely colonised colon. Microorganisms are recognised by pattern recognition receptors such as Toll-like receptors, which signal through the adaptor molecule MyD88. To identify host responses induced by gut microbiota along the length of the gut and whether these required MyD88, transcriptional profiles of duodenum, jejunum, ileum and colon were compared from germ-free and conventionally raised wild-type and Myd88-/- mice. The gut microbial ecology was assessed by 454-based pyrosequencing and viruses were analysed by PCR. The gut microbiota modulated the expression of a large set of genes in the small intestine and fewer genes in the colon but surprisingly few microbiota-regulated genes required MyD88 signalling. However, MyD88 was essential for microbiota-induced colonic expression of the antimicrobial genes Reg3β and Reg3γ in the epithelium, and Myd88 deficiency was associated with both a shift in bacterial diversity and a greater proportion of segmented filamentous bacteria in the small intestine. In addition, conventionally raised Myd88-/- mice had increased expression of antiviral genes in the colon, which correlated with norovirus infection in the colonic epithelium. This study provides a detailed description of tissue-specific host transcriptional responses to the normal gut microbiota along the length of the gut and demonstrates that the absence of MyD88 alters gut microbial ecology.

Microbial electrosynthetic cells

Energy Technology Data Exchange (ETDEWEB)

May, Harold D.; Marshall, Christopher W.; Labelle, Edward V.

2018-01-30

Methods are provided for microbial electrosynthesis of H.sub.2 and organic compounds such as methane and acetate. Method of producing mature electrosynthetic microbial populations by continuous culture is also provided. Microbial populations produced in accordance with the embodiments as shown to efficiently synthesize H.sub.2, methane and acetate in the presence of CO.sub.2 and a voltage potential. The production of biodegradable and renewable plastics from electricity and carbon dioxide is also disclosed.

Research on a practical telecom and CATV co-network transmission system

Science.gov (United States)

Mao, Youju

1998-12-01

A practical co-network transmission system of Telecom and CATV over installed Telecom network is designed. The system, making use of WDM and other technologies, has undergone experiments and performance tests on the Public Switched Telephone Network, which illustrate that optical fiber telecommunication network could be thereby transformed into a unified broadband network integrating VOICE, DATA, and VEDIO expeditiously and conveniently.

Synthesis, Physico-chemical Characterization, Crystal Structure and Influence on Microbial and Tumor Cells of Some Co(II Complexes with 5,7-Dimethyl-1,2,4-triazolo[1,5-a]pyrimidine

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Luminiţa Măruţescu

2017-07-01

Full Text Available Three complexes, namely [Co(dmtp2(OH24][CoCl4] (1, [Co(dmtp2Cl2] (2 and [Co(dmtp2(OH24]Cl2∙2H2O (3 (dmtp: 5,7-dimethyl-1,2,4-triazolo[1,5-a]pyrimidine, were synthesized and characterized by spectral (IR, UV-Vis-NIR, and magnetic measurements at room temperature, as well as single crystal X-ray diffraction. Complex (1 crystallizes in monoclinic system (space group C2/c, complex (2 adopts an orthorhombic system (space group Pbca, and complex (3 crystallizes in triclinic system (space group P1. Various types of extended hydrogen bonds and π–π interactions provide a supramolecular architecture for all complexes. All species were evaluated for antimicrobial activity towards planktonic and biofilm-embedded microbial cells and influence on HEp-2 cell viability, cellular cycle and gene expression.

Organic micropollutants in aerobic and anaerobic membrane bioreactors: Changes in microbial communities and gene expression

KAUST Repository

Harb, Moustapha

2016-07-09

Organic micro-pollutants (OMPs) are contaminants of emerging concern in wastewater treatment due to the risk of their proliferation into the environment, but their impact on the biological treatment process is not well understood. The purpose of this study is to examine the effects of the presence of OMPs on the core microbial populations of wastewater treatment. Two nanofiltration-coupled membrane bioreactors (aerobic and anaerobic) were subjected to the same operating conditions while treating synthetic municipal wastewater spiked with OMPs. Microbial community dynamics, gene expression levels, and antibiotic resistance genes were analyzed using molecular-based approaches. Results showed that presence of OMPs in the wastewater feed had a clear effect on keystone bacterial populations in both the aerobic and anaerobic sludge while also significantly impacting biodegradation-associated gene expression levels. Finally, multiple antibiotic-type OMPs were found to have higher removal rates in the anaerobic MBR, while associated antibiotic resistance genes were lower.

Organic micropollutants in aerobic and anaerobic membrane bioreactors: Changes in microbial communities and gene expression

KAUST Repository

Harb, Moustapha; Wei, Chunhai; Wang, Nan; Amy, Gary L.; Hong, Pei-Ying

2016-01-01

Organic micro-pollutants (OMPs) are contaminants of emerging concern in wastewater treatment due to the risk of their proliferation into the environment, but their impact on the biological treatment process is not well understood. The purpose of this study is to examine the effects of the presence of OMPs on the core microbial populations of wastewater treatment. Two nanofiltration-coupled membrane bioreactors (aerobic and anaerobic) were subjected to the same operating conditions while treating synthetic municipal wastewater spiked with OMPs. Microbial community dynamics, gene expression levels, and antibiotic resistance genes were analyzed using molecular-based approaches. Results showed that presence of OMPs in the wastewater feed had a clear effect on keystone bacterial populations in both the aerobic and anaerobic sludge while also significantly impacting biodegradation-associated gene expression levels. Finally, multiple antibiotic-type OMPs were found to have higher removal rates in the anaerobic MBR, while associated antibiotic resistance genes were lower.

Extraction of temporal networks from term co-occurrences in online textual sources.

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Marko Popović

Full Text Available A stream of unstructured news can be a valuable source of hidden relations between different entities, such as financial institutions, countries, or persons. We present an approach to continuously collect online news, recognize relevant entities in them, and extract time-varying networks. The nodes of the network are the entities, and the links are their co-occurrences. We present a method to estimate the significance of co-occurrences, and a benchmark model against which their robustness is evaluated. The approach is applied to a large set of financial news, collected over a period of two years. The entities we consider are 50 countries which issue sovereign bonds, and which are insured by Credit Default Swaps (CDS in turn. We compare the country co-occurrence networks to the CDS networks constructed from the correlations between the CDS. The results show relatively small, but significant overlap between the networks extracted from the news and those from the CDS correlations.

A Co-Citation Network of Young Children's Learning with Technology

Science.gov (United States)

Tang, Kai-Yu; Li, Ming-Chaun; Hsin, Ching-Ting; Tsai, Chin-Chung

2016-01-01

This paper used a novel literature review approach--co-citation network analysis--to illuminate the latent structure of 87 empirical papers in the field of young children's learning with technology (YCLT). Based on the document co-citation analysis, a total of 206 co-citation relationships among the 87 papers were identified and then graphically…

Long-term sustainability of microbial-induced CaCO3 precipitation in aqueous media.

Science.gov (United States)

Gat, Daniella; Ronen, Zeev; Tsesarsky, Michael

2017-10-01

Microbially induced CaCO 3 precipitation (MICP) via urea hydrolysis is an emerging technique for soil amelioration, building materials rehabilitation and pollutants sequestration amongst other various environmental applications. The successful application of MICP requires the sustainability of the precipitated CaCO 3 ; to which the fate of ammonia, the main by-product of ureolysis, is potentially significante. Ammonia volatilization and biological ammonia oxidation both induce a pH decrease, which, in turn, might cause CaCO 3 dissolution. To examine the potential effect of accumulated ammonia on precipitated CaCO 3 , we conducted a long-term MICP batch experiment, using environmental enrichment cultures of ureolytic bacteria. Here we show that CaCO 3 precipitation was completed within 15-27 days, along with a rise in ammonium concentration. Following completion of ureolysis and precipitation, ammonium concentrations decreased, leading to a pH decrease. About 30 days after precipitation was completed, as much as 30% CaCO 3 dissolution, was observed. A two-step model, describing urea hydrolysis followed by the removal of ammonia from the precipitation solution, predicted CaCO 3 dissolution due to ammonia volatilization. We suggest that ureolytic MICP might result in ammonia volatilization, leading to significant CaCO 3 dissolution. These results provide basic insights into the sustainability of ureolytic MICP and should further encourage removal of the accumulated ammonia from the treated site. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Effect of the Co-Operative Network Model for Students' Quality in Thai Primary Schools

Science.gov (United States)

Khanthaphum, Udomsin; Tesaputa, Kowat; Weangsamoot, Visoot

2016-01-01

This research aimed: 1) to study the current and desirable states of the co-operative network in developing the learners' quality in Thai primary schools, 2) to develop a model of the co-operative network in developing the learners' quality, and 3) to examine the results of implementation of the co-operative network model in the primary school.…

Changes in the microbial communities during co-composting of digestates☆

Science.gov (United States)

Franke-Whittle, Ingrid H.; Confalonieri, Alberto; Insam, Heribert; Schlegelmilch, Mirko; Körner, Ina

2014-01-01

Anaerobic digestion is a waste treatment method which is of increasing interest worldwide. At the end of the process, a digestate remains, which can gain added value by being composted. A study was conducted in order to investigate microbial community dynamics during the composting process of a mixture of anaerobic digestate (derived from the anaerobic digestion of municipal food waste), green wastes and a screened compost (green waste/kitchen waste compost), using the COMPOCHIP microarray. The composting process showed a typical temperature development, and the highest degradation rates occurred during the first 14 days of composting, as seen from the elevated CO2 content in the exhaust air. With an exception of elevated nitrite and nitrate levels in the day 34 samples, physical–chemical parameters for all compost samples collected during the 63 day process indicated typical composting conditions. The microbial communities changed over the 63 days of composting. According to principal component analysis of the COMPOCHIP microarray results, compost samples from the start of the experiment were found to cluster most closely with the digestate and screened compost samples. The green waste samples were found to group separately. All starting materials investigated were found to yield fewer and lower signals when compared to the samples collected during the composting experiment. PMID:24456768

Comparing Existing Pipeline Networks with the Potential Scale of Future U.S. CO2 Pipeline Networks

Energy Technology Data Exchange (ETDEWEB)

Dooley, James J.; Dahowski, Robert T.; Davidson, Casie L.

2008-02-29

There is growing interest regarding the potential size of a future U.S. dedicated CO2 pipeline infrastructure if carbon dioxide capture and storage (CCS) technologies are commercially deployed on a large scale. In trying to understand the potential scale of a future national CO2 pipeline network, comparisons are often made to the existing pipeline networks used to deliver natural gas and liquid hydrocarbons to markets within the U.S. This paper assesses the potential scale of the CO2 pipeline system needed under two hypothetical climate policies and compares this to the extant U.S. pipeline infrastructures used to deliver CO2 for enhanced oil recovery (EOR), and to move natural gas and liquid hydrocarbons from areas of production and importation to markets. The data presented here suggest that the need to increase the size of the existing dedicated CO2 pipeline system should not be seen as a significant obstacle for the commercial deployment of CCS technologies.

TBLR1 regulates the expression of nuclear hormone receptor co-repressors

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Brown Stuart

2006-08-01

Full Text Available Abstract Background Transcription is regulated by a complex interaction of activators and repressors. The effectors of repression are large multimeric complexes which contain both the repressor proteins that bind to transcription factors and a number of co-repressors that actually mediate transcriptional silencing either by inhibiting the basal transcription machinery or by recruiting chromatin-modifying enzymes. Results TBLR1 [GenBank: NM024665] is a co-repressor of nuclear hormone transcription factors. A single highly conserved gene encodes a small family of protein molecules. Different isoforms are produced by differential exon utilization. Although the ORF of the predominant form contains only 1545 bp, the human gene occupies ~200 kb of genomic DNA on chromosome 3q and contains 16 exons. The genomic sequence overlaps with the putative DC42 [GenBank: NM030921] locus. The murine homologue is structurally similar and is also located on Chromosome 3. TBLR1 is closely related (79% homology at the mRNA level to TBL1X and TBL1Y, which are located on Chromosomes X and Y. The expression of TBLR1 overlaps but is distinct from that of TBL1. An alternatively spliced form of TBLR1 has been demonstrated in human material and it too has an unique pattern of expression. TBLR1 and the homologous genes interact with proteins that regulate the nuclear hormone receptor family of transcription factors. In resting cells TBLR1 is primarily cytoplasmic but after perturbation the protein translocates to the nucleus. TBLR1 co-precipitates with SMRT, a co-repressor of nuclear hormone receptors, and co-precipitates in complexes immunoprecipitated by antiserum to HDAC3. Cells engineered to over express either TBLR1 or N- and C-terminal deletion variants, have elevated levels of endogenous N-CoR. Co-transfection of TBLR1 and SMRT results in increased expression of SMRT. This co-repressor undergoes ubiquitin-mediated degradation and we suggest that the stabilization of

Influence of co-substrate on textile wastewater treatment and microbial community changes in the anaerobic biological sulfate reduction process

International Nuclear Information System (INIS)

Rasool, Kashif; Mahmoud, Khaled A.; Lee, Dae Sung

2015-01-01

Highlights: • Textile wastewater treatment performance was investigated with different co-substrates. • Dye biodegradation and biotransformation enhanced with lactate as co-substrate. • Sulfate removal significantly decreased under limited co-substrate concentration. • Changes in microbial community structure were studied using bar-coded pyrosequencing. • Lactate as co-substrate showed the highest relative abundance of sulfate reducing bacteria. - Abstract: This study investigated the anaerobic treatment of sulfate-rich synthetic textile wastewater in three sulfidogenic sequential batch reactors (SBRs). The experimental protocol was designed to examine the effect of three different co-substrates (lactate, glucose, and ethanol) and their concentrations on wastewater treatment performance. Sulfate reduction and dye degradation were improved when lactate and ethanol were used as electron donors, as compared with glucose. Moreover, under co-substrate limited concentrations, color, sulfate, and chemical oxygen demand (COD) removal efficiencies were declined. By reducing co-substrate COD gradually from 3000 to 500 mg/L, color removal efficiencies were decreased from 98.23% to 78.46%, 63.37%, and 69.10%, whereas, sulfate removal efficiencies were decreased from 98.42%, 82.35%, and 87.0%, to 30.27%, 21.50%, and 10.13%, for lactate, glucose, and ethanol fed reactors, respectively. Fourier transform infrared spectroscopy (FTIR) and total aromatic amine analysis revealed lactate to be a potential co-substrate for further biodegradation of intermediate metabolites formed after dye degradation. Pyrosequencing analysis showed that microbial community structure was significantly affected by the co-substrate. The reactor with lactate as co-substrate showed the highest relative abundance of sulfate reducing bacteria (SRBs), followed by ethanol, whereas the glucose-fed reactor showed the lowest relative abundance of SRB.

Influence of co-substrate on textile wastewater treatment and microbial community changes in the anaerobic biological sulfate reduction process

Energy Technology Data Exchange (ETDEWEB)

Rasool, Kashif; Mahmoud, Khaled A. [Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Qatar Foundation, PO BOX 5825, Doha (Qatar); Lee, Dae Sung, E-mail: daesung@knu.ac.kr [Department of Environmental Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 702-701 (Korea, Republic of)

2015-12-15

Highlights: • Textile wastewater treatment performance was investigated with different co-substrates. • Dye biodegradation and biotransformation enhanced with lactate as co-substrate. • Sulfate removal significantly decreased under limited co-substrate concentration. • Changes in microbial community structure were studied using bar-coded pyrosequencing. • Lactate as co-substrate showed the highest relative abundance of sulfate reducing bacteria. - Abstract: This study investigated the anaerobic treatment of sulfate-rich synthetic textile wastewater in three sulfidogenic sequential batch reactors (SBRs). The experimental protocol was designed to examine the effect of three different co-substrates (lactate, glucose, and ethanol) and their concentrations on wastewater treatment performance. Sulfate reduction and dye degradation were improved when lactate and ethanol were used as electron donors, as compared with glucose. Moreover, under co-substrate limited concentrations, color, sulfate, and chemical oxygen demand (COD) removal efficiencies were declined. By reducing co-substrate COD gradually from 3000 to 500 mg/L, color removal efficiencies were decreased from 98.23% to 78.46%, 63.37%, and 69.10%, whereas, sulfate removal efficiencies were decreased from 98.42%, 82.35%, and 87.0%, to 30.27%, 21.50%, and 10.13%, for lactate, glucose, and ethanol fed reactors, respectively. Fourier transform infrared spectroscopy (FTIR) and total aromatic amine analysis revealed lactate to be a potential co-substrate for further biodegradation of intermediate metabolites formed after dye degradation. Pyrosequencing analysis showed that microbial community structure was significantly affected by the co-substrate. The reactor with lactate as co-substrate showed the highest relative abundance of sulfate reducing bacteria (SRBs), followed by ethanol, whereas the glucose-fed reactor showed the lowest relative abundance of SRB.

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

Science.gov (United States)

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite.

Science.gov (United States)

Peng, Hui; Lan, Chaowang; Zheng, Yi; Hutvagner, Gyorgy; Tao, Dacheng; Li, Jinyan

2017-03-24

MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunctional target genes cooperatively in the development of multiple diseases. The research is potentially useful for human disease studies at the transcriptional level and for the study of multi-purpose microRNA therapeutics. We designed a computational method to detect multi-disease associated co-functional microRNA pairs and conducted cross disease analysis on a reconstructed disease-gene-microRNA (DGR) tripartite network. The construction of the DGR tripartite network is by the integration of newly predicted disease-microRNA associations with those relationships of diseases, microRNAs and genes maintained by existing databases. The prediction method uses a set of reliable negative samples of disease-microRNA association and a pre-computed kernel matrix instead of kernel functions. From this reconstructed DGR tripartite network, multi-disease associated co-functional microRNA pairs are detected together with their common dysfunctional target genes and ranked by a novel scoring method. We also conducted proof-of-concept case studies on cancer-related co-functional microRNA pairs as well as on non-cancer disease-related microRNA pairs. With the prioritization of the co-functional microRNAs that relate to a series of diseases, we found that the co-function phenomenon is not unusual. We also confirmed that the regulation of the microRNAs for the development of cancers is more complex and have more unique properties than those of non-cancer diseases.

Network design for quantifying urban CO2 emissions: assessing trade-offs between precision and network density

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A. J. Turner

2016-11-01

Full Text Available The majority of anthropogenic CO2 emissions are attributable to urban areas. While the emissions from urban electricity generation often occur in locations remote from consumption, many of the other emissions occur within the city limits. Evaluating the effectiveness of strategies for controlling these emissions depends on our ability to observe urban CO2 emissions and attribute them to specific activities. Cost-effective strategies for doing so have yet to be described. Here we characterize the ability of a prototype measurement network, modeled after the Berkeley Atmospheric CO2 Observation Network (BEACO2N in California's Bay Area, in combination with an inverse model based on the coupled Weather Research and Forecasting/Stochastic Time-Inverted Lagrangian Transport (WRF-STILT to improve our understanding of urban emissions. The pseudo-measurement network includes 34 sites at roughly 2 km spacing covering an area of roughly 400 km2. The model uses an hourly 1  ×  1 km2 emission inventory and 1  ×  1 km2 meteorological calculations. We perform an ensemble of Bayesian atmospheric inversions to sample the combined effects of uncertainties of the pseudo-measurements and the model. We vary the estimates of the combined uncertainty of the pseudo-observations and model over a range of 20 to 0.005 ppm and vary the number of sites from 1 to 34. We use these inversions to develop statistical models that estimate the efficacy of the combined model–observing system in reducing uncertainty in CO2 emissions. We examine uncertainty in estimated CO2 fluxes on the urban scale, as well as for sources embedded within the city such as a line source (e.g., a highway or a point source (e.g., emissions from the stacks of small industrial facilities. Using our inversion framework, we find that a dense network with moderate precision is the preferred setup for estimating area, line, and point sources from a combined uncertainty and cost

A comparative study on the reliability of co-authorship networks with emphases on edges and nodes

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Sandra Cristina de Oliveira

2016-06-01

Full Text Available A scientific co-authorship network may be modeled by a graph G composed of k nodes and m edges. Researchers that make up this network may be interpreted as its nodes and the link between these agents (co-authored papers as its edges. Current work evaluated and compared the reliability measure of networks with two emphases: 1 On nodes (perfectly reliable edges and 2 On edges (perfectly reliable nodes. Specifically, the reliability of a fictitious co-authorship network at a given time t was analyzed taking into account, first, the reliability of nodes (researchers equal and different, and, second, the reliability of edges (co-authorship relations, equal and different. Additionally, centrality measures of nodes were obtained to identify situations where the insertion of an edge significantly increased the reliability of the network. Results showed that the reliability of the co-authorship network focusing on edges is more sensitive to changes in individual reliabilities than the reliability of the network focusing on nodes. Additionally, the use of centrality measures was viable to identify possible insertions of edges or co-authorship relations to increase the reliability of the network in the two approaches.

Finding gene regulatory network candidates using the gene expression knowledge base.

Science.gov (United States)

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Marine Microbial Systems Ecology: Microbial Networks in the Sea

NARCIS (Netherlands)

Muijzer, G.; Stal, L.J.; Cretoiu, M.S.

2016-01-01

Next-generation sequencing of DNA has revolutionized microbial ecology. Using this technology, it became for the first time possible to analyze hundreds of samples simultaneously and in great detail. 16S rRNA amplicon sequencing, metagenomics and metatranscriptomics became available to determine the

Co-Design Based Lateral Motion Control of All-Wheel-Independent-Drive Electric Vehicles with Network Congestion

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Wanke Cao

2017-10-01

Full Text Available All-wheel-independent-drive electric vehicles (AWID-EVs have considerable advantages in terms of energy optimization, drivability and driving safety due to the remarkable actuation flexibility of electric motors. However, in their current implementations, various real-time data in the vehicle control system are exchanged via a controller area network (CAN, which causes network congestion and network-induced delays. These problems could lead to systemic instability and make the system integration difficult. The goal of this paper is to provide a design methodology that can cope with all these challenges for the lateral motion control of AWID-EVs. Firstly, a continuous-time model of an AWID-EV is derived. Then an expression for determining upper and lower bounds on the delays caused by CAN is presented and with which a discrete-time model of the closed-loop CAN system is derived. An expression on the bandwidth utilization is introduced as well. Thirdly, a co-design based scheme combining a period-dependent linear quadratic regulator (LQR and a dynamic period scheduler is designed for the resulting model and the stability criterion is also derived. The results of simulations and hard-in-loop (HIL experiments show that the proposed methodology can effectively guarantee the stability of the vehicle lateral motion control while obviously declining the network congestion.

A multilayer network analysis of hashtags in twitter via co-occurrence and semantic links

Science.gov (United States)

Türker, Ilker; Sulak, Eyüb Ekmel

2018-02-01

Complex network studies, as an interdisciplinary framework, span a large variety of subjects including social media. In social networks, several mechanisms generate miscellaneous structures like friendship networks, mention networks, tag networks, etc. Focusing on tag networks (namely, hashtags in twitter), we made a two-layer analysis of tag networks from a massive dataset of Twitter entries. The first layer is constructed by converting the co-occurrences of these tags in a single entry (tweet) into links, while the second layer is constructed converting the semantic relations of the tags into links. We observed that the universal properties of the real networks like small-world property, clustering and power-law distributions in various network parameters are also evident in the multilayer network of hashtags. Moreover, we outlined that co-occurrences of hashtags in tweets are mostly coupled with semantic relations, whereas a small number of semantically unrelated, therefore random links reduce node separation and network diameter in the co-occurrence network layer. Together with the degree distributions, the power-law consistencies of degree difference, edge weight and cosine similarity distributions in both layers are also appealing forms of Zipf’s law evident in nature.

Anaerobic microbial dehalogenation of organohalides-state of the art and remediation strategies.

Science.gov (United States)

Nijenhuis, Ivonne; Kuntze, Kevin

2016-04-01

Contamination and remediation of groundwater with halogenated organics and understanding of involved microbial reactions still poses a challenge. Over the last years, research in anaerobic microbial dehalogenation has advanced in many aspects providing information about the reaction, physiology of microorganisms as well as approaches to investigate the activity of microorganisms in situ. Recently published crystal structures of reductive dehalogenases (Rdh), heterologous expression systems and advanced analytical, proteomic and stable isotope approaches allow addressing the overall reaction and specific enzymes as well as co-factors involved during anaerobic microbial dehalogenation. In addition to Dehalococcoides spp., Dehalobacter and Dehalogenimonas strains have been recognized as important and versatile organohalide respirers. Together, these provide perspectives for integrated concepts allowing to improve and monitor in situ biodegradation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Microbial trophic interactions and mcrA gene expression in monitoring of anaerobic digesters

Science.gov (United States)

Alvarado, Alejandra; Montañez-Hernández, Lilia E.; Palacio-Molina, Sandra L.; Oropeza-Navarro, Ricardo; Luévanos-Escareño, Miriam P.; Balagurusamy, Nagamani

2014-01-01

Anaerobic digestion (AD) is a biological process where different trophic groups of microorganisms break down biodegradable organic materials in the absence of oxygen. A wide range of AD technologies is being used to convert livestock manure, municipal and industrial wastewaters, and solid organic wastes into biogas. AD gains importance not only because of its relevance in waste treatment but also because of the recovery of carbon in the form of methane, which is a renewable energy and is used to generate electricity and heat. Despite the advances on the engineering and design of new bioreactors for AD, the microbiology component always poses challenges. Microbiology of AD processes is complicated as the efficiency of the process depends on the interactions of various trophic groups involved. Due to the complex interdependence of microbial activities for the functionality of the anaerobic bioreactors, the genetic expression of mcrA, which encodes a key enzyme in methane formation, is proposed as a parameter to monitor the process performance in real time. This review evaluates the current knowledge on microbial groups, their interactions, and their relationship to the performance of anaerobic biodigesters with a focus on using mcrA gene expression as a tool to monitor the process. PMID:25429286

Microbial trophic interactions and mcrA gene expression in monitoring of anaerobic digesters

Directory of Open Access Journals (Sweden)

Alejandra eAlvarado

2014-11-01

Full Text Available Anaerobic digestion (AD is a biological process where different trophic groups of microorganisms break down biodegradable organic materials in the absence of oxygen. A wide range of anaerobic digestion technologies is being used to convert livestock manure, municipal and industrial wastewaters, and solid organic wastes into biogas. AD gains importance not only because of its relevance in waste treatment but also because of the recovery of carbon in the form of methane, which is a renewable energy and is used to generate electricity and heat. Despite the advances on the engineering and design of new bioreactors for anaerobic digestion, the microbiology component always poses challenges. Microbiology of AD processes is complicated as the efficiency of the process depends on the interactions of various trophic groups involved. Due to the complex interdependence of microbial activities for the functionality of the anaerobic bioreactors, the genetic expression of mcrA, which encodes a key enzyme in methane formation, is proposed as a parameter to monitor the process performance in real time. This review evaluates the current knowledge on microbial groups, their interactions and their relationship to the performance of anaerobic biodigesters with a focus on using mcrA gene expression as a tool to monitor the process.

The Microbial DNA Index System (MiDIS): A tool for microbial pathogen source identification

Energy Technology Data Exchange (ETDEWEB)

Velsko, S. P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2010-08-09

The microbial DNA Index System (MiDIS) is a concept for a microbial forensic database and investigative decision support system that can be used to help investigators identify the sources of microbial agents that have been used in a criminal or terrorist incident. The heart of the proposed system is a rigorous method for calculating source probabilities by using certain fundamental sampling distributions associated with the propagation and mutation of microbes on disease transmission networks. This formalism has a close relationship to mitochondrial and Y-chromosomal human DNA forensics, and the proposed decision support system is somewhat analogous to the CODIS and SWGDAM mtDNA databases. The MiDIS concept does not involve the use of opportunistic collections of microbial isolates and phylogenetic tree building as a basis for inference. A staged approach can be used to build MiDIS as an enduring capability, beginning with a pilot demonstration program that must meet user expectations for performance and validation before evolving into a continuing effort. Because MiDIS requires input from a a broad array of expertise including outbreak surveillance, field microbial isolate collection, microbial genome sequencing, disease transmission networks, and laboratory mutation rate studies, it will be necessary to assemble a national multi-laboratory team to develop such a system. The MiDIS effort would lend direction and focus to the national microbial genetics research program for microbial forensics, and would provide an appropriate forensic framework for interfacing to future national and international disease surveillance efforts.

G-NEST: A gene neighborhood scoring tool to identify co-conserved, co-expressed genes

Science.gov (United States)

In previous studies, gene neighborhoods--spatial clusters of co-expressed genes in the genome--have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Sc...

Cross-border Co-operation and Policy Networks in West Africa

DEFF Research Database (Denmark)

Trémolières, Marie; Walther, Olivier

This publication examines how policy actors involved in cross-border co-operation contribute to the regional integration process in West Africa. It uses a pioneering methodology, known as social network analysis, to visualise the formal and informal relationships between actors involved in cross...... West Africa to develop cross-border initiatives in a number of ways. Combining these two analyses with the perceptions of regional policy makers as to which border areas they consider as priorities for regional integration, the publication concludes with the analytical foundations for more effective......-border policy networks, showing that borders have notable and diverse impacts on exchanges of information and the relative power of networks. The report then analyses a range of regional indicators of co-operation potential, visually demonstrating that borders can also affect the ability of sub-regions within...

Co-extinction in a host-parasite network: identifying key hosts for network stability.

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Dallas, Tad; Cornelius, Emily

2015-08-17

Parasites comprise a substantial portion of total biodiversity. Ultimately, this means that host extinction could result in many secondary extinctions of obligate parasites and potentially alter host-parasite network structure. Here, we examined a highly resolved fish-parasite network to determine key hosts responsible for maintaining parasite diversity and network structure (quantified here as nestedness and modularity). We evaluated four possible host extinction orders and compared the resulting co-extinction dynamics to random extinction simulations; including host removal based on estimated extinction risk, parasite species richness and host level contributions to nestedness and modularity. We found that all extinction orders, except the one based on realistic extinction risk, resulted in faster declines in parasite diversity and network structure relative to random biodiversity loss. Further, we determined species-level contributions to network structure were best predicted by parasite species richness and host family. Taken together, we demonstrate that a small proportion of hosts contribute substantially to network structure and that removal of these hosts results in rapid declines in parasite diversity and network structure. As network stability can potentially be inferred through measures of network structure, our findings may provide insight into species traits that confer stability.

cooccurNet: an R package for co-occurrence network construction and analysis.

Science.gov (United States)

Zou, Yuanqiang; Wu, Zhiqiang; Deng, Lizong; Wu, Aiping; Wu, Fan; Li, Kenli; Jiang, Taijiao; Peng, Yousong

2017-06-15

Previously, we developed a computational model to identify genomic co-occurrence networks that was applied to capture the coevolution patterns within genomes of influenza viruses. To facilitate easy public use of this model, an R package 'cooccurNet' is presented here. 'cooccurNet' includes functionalities of construction and analysis of residues (e.g. nucleotides, amino acids and SNPs) co-occurrence network. In addition, a new method for measuring residues coevolution, defined as residue co-occurrence score (RCOS), is proposed and implemented in 'cooccurNet' based on the co-occurrence network. 'cooccurNet' is publicly available on CRAN repositories under the GPL-3 Open Source License ( http://cran.r-project.org/package=cooccurNet ). taijiao@ibms.pumc.edu.cn or pys2013@hnu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Globally homochiral assembly of two-dimensional molecular networks triggered by co-absorbers.

Science.gov (United States)

Chen, Ting; Yang, Wen-Hong; Wang, Dong; Wan, Li-Jun

2013-01-01

Understanding the chirality induction and amplification processes, and the construction of globally homochiral surfaces, represent essential challenges in surface chirality studies. Here we report the induction of global homochirality in two-dimensional enantiomorphous networks of achiral molecules via co-assembly with chiral co-absorbers. The scanning tunnelling microscopy investigations and molecular mechanics simulations demonstrate that the point chirality of the co-absorbers transfers to organizational chirality of the assembly units via enantioselective supramolecular interactions, and is then hierarchically amplified to the global homochirality of two-dimensional networks. The global homochirality of the network assembly shows nonlinear dependence on the enantiomeric excess of chiral co-absorber in the solution phase, demonstrating, for the first time, the validation of the 'majority rules' for the homochirality control of achiral molecules at the liquid/solid interface. Such an induction and nonlinear chirality amplification effect promises a new approach towards two-dimensional homochirality control and may reveal important insights into asymmetric heterogeneous catalysis, chiral separation and chiral crystallization.

Inferring Microbial Interactions in the Gut of the Hong Kong Whipping Frog (Polypedates megacephalus) and a Validation Using Probiotics

Science.gov (United States)

Weng, Francis Cheng-Hsuan; Shaw, Grace Tzun-Wen; Weng, Chieh-Yin; Yang, Yi-Ju; Wang, Daryi

2017-01-01

concentrations than single strains, and the immune response (interleukin-10 expression) also significantly changed in a manner consistent with improved probiotic effects. By taking advantage of microbial community shift from simple to complex, we thus constructed a reliable microbial interaction network, and validated it using probiotic strains as a test system. PMID:28424669

Microbial community changes at a terrestrial volcanic CO2 vent induced by soil acidification and anaerobic microhabitats within the soil column.

Science.gov (United States)

Frerichs, Janin; Oppermann, Birte I; Gwosdz, Simone; Möller, Ingo; Herrmann, Martina; Krüger, Martin

2013-04-01

CO2 capture and storage (CCS) in deep geological formations is one option currently evaluated to reduce greenhouse gas emissions. Consequently, the impact of a possible CO2 leakage from a storage site into surface environments has to be evaluated. During such a hypothetical leakage event, the CO2 migrates upwards along fractures entering surface soils, a scenario similar to naturally occurring CO2 vents. Therefore, such a natural analogue site at the Laacher See was chosen for an ecosystem study on the effects of high CO2 concentrations on soil chemistry and microbiology. The microbial activities revealed differences in their spatial distribution and temporal variability for CO2 -rich and reference soils. Furthermore, the abundance of several functional and group-specific gene markers revealed further differences, for example, a decrease in Geobacteraceae and an increase in sulphate-reducing prokaryotes in the vent centre. Molecular-biological fingerprinting of the microbial communities with DGGE indicated a shift in the environmental conditions within the Laacher See soil column leading to anaerobic and potentially acidic microenvironments. Furthermore, the distribution and phylogenetic affiliation of the archaeal 16S rRNA genes, the presence of ammonia-oxidizing Archaea and the biomarker analysis revealed a predominance of Thaumarchaeota as possible indicator organisms for elevated CO2 concentrations in soils. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

NATURAL CO2 FLOW FROM THE LOIHI VENT: IMPACT ON MICROBIAL PRODUCTION AND FATE OF THE CO2

Energy Technology Data Exchange (ETDEWEB)

Richard B. Coffin; Thomas J. Boyd; David L. Knies; Kenneth S. Grabowski; John W. Pohlman; Clark S. Mitchell

2004-02-27

The program for International Collaboration on CO{sub 2} Ocean Sequestration was initiated December 1997. Preliminary steps involved surveying a suite of biogeochemical parameters off the coast of Kona on the Big Island of Hawaii. The preliminary survey was conducted twice, in 1999 and 2000, to obtain a thorough data set including measurements of pH, current profiles, CO{sub 2} concentrations, microbial activities, and water and sediment chemistries. These data were collected in order to interpret a planned CO{sub 2} injection experiment. After these preliminary surveys were completed, local environment regulation forced moving the project to the coast north east of Bergen, Norway. The preliminary survey along the Norwegian Coast was conducted during 2002. However, Norwegian government revoked a permit, approved by the Norwegian State Pollution Control Authority, for policy reasons regarding the CO{sub 2} injection experiment. As a result the research team decided to monitor the natural CO{sub 2} flow off the southern coast of the Big Island. From December 3rd-13th 2002 scientists from four countries representing the Technical Committee of the International Carbon Dioxide Sequestration Experiment examined the hydrothermal venting at Loihi Seamount (Hawaiian Islands, USA). Work focused on tracing the venting gases, the impacts of the vent fluids on marine organisms, and CO{sub 2} influence on biogeochemical cycles. The cruise on the R/V Ka'imikai-O-Kanaloa (KOK) included 8 dives by the PISCES V submarine, 6 at Loihi and 2 at a nearby site in the lee of the Big Island. Data for this final report is from the last 2 dives on Loihi.

Molecular ecological network analyses.

Science.gov (United States)

Deng, Ye; Jiang, Yi-Huei; Yang, Yunfeng; He, Zhili; Luo, Feng; Zhou, Jizhong

2012-05-30

Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open

Inferring gene networks from discrete expression data

KAUST Repository

Zhang, L.; Mallick, B. K.

2013-01-01

graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which

Formation of nanoscale networks: selectively swelling amphiphilic block copolymers with CO2-expanded liquids.

Science.gov (United States)

Gong, Jianliang; Zhang, Aijuan; Bai, Hua; Zhang, Qingkun; Du, Can; Li, Lei; Hong, Yanzhen; Li, Jun

2013-02-07

Polymeric films with nanoscale networks were prepared by selectively swelling an amphiphilic diblock copolymer, polystyrene-block-poly(4-vinylpyridine) (PS-b-P4VP), with the CO(2)-expanded liquid (CXL), CO(2)-methanol. The phase behavior of the CO(2)-methanol system was investigated by both theoretical calculation and experiments, revealing that methanol can be expanded by CO(2), forming homogeneous CXL under the experimental conditions. When treated with the CO(2)-methanol system, the spin cast compact PS-b-P4VP film was transformed into a network with interconnected pores, in a pressure range of 12-20 MPa and a temperature range of 45-60 °C. The formation mechanism of the network, involving plasticization of PS and selective swelling of P4VP, was proposed. Because the diblock copolymer diffusion process is controlled by the activated hopping of individual block copolymer chains with the thermodynamic barrier for moving PVP segments from one to another, the formation of the network structures is achieved in a short time scale and shows "thermodynamically restricted" character. Furthermore, the resulting polymer networks were employed as templates, for the preparation of polypyrrole networks, by an electrochemical polymerization process. The prepared porous polypyrrole film was used to fabricate a chemoresistor-type gas sensor which showed high sensitivity towards ammonia.

Gene expression network reconstruction by convex feature selection when incorporating genetic perturbations.

Directory of Open Access Journals (Sweden)

Benjamin A Logsdon

Full Text Available Cellular gene expression measurements contain regulatory information that can be used to discover novel network relationships. Here, we present a new algorithm for network reconstruction powered by the adaptive lasso, a theoretically and empirically well-behaved method for selecting the regulatory features of a network. Any algorithms designed for network discovery that make use of directed probabilistic graphs require perturbations, produced by either experiments or naturally occurring genetic variation, to successfully infer unique regulatory relationships from gene expression data. Our approach makes use of appropriately selected cis-expression Quantitative Trait Loci (cis-eQTL, which provide a sufficient set of independent perturbations for maximum network resolution. We compare the performance of our network reconstruction algorithm to four other approaches: the PC-algorithm, QTLnet, the QDG algorithm, and the NEO algorithm, all of which have been used to reconstruct directed networks among phenotypes leveraging QTL. We show that the adaptive lasso can outperform these algorithms for networks of ten genes and ten cis-eQTL, and is competitive with the QDG algorithm for networks with thirty genes and thirty cis-eQTL, with rich topologies and hundreds of samples. Using this novel approach, we identify unique sets of directed relationships in Saccharomyces cerevisiae when analyzing genome-wide gene expression data for an intercross between a wild strain and a lab strain. We recover novel putative network relationships between a tyrosine biosynthesis gene (TYR1, and genes involved in endocytosis (RCY1, the spindle checkpoint (BUB2, sulfonate catabolism (JLP1, and cell-cell communication (PRM7. Our algorithm provides a synthesis of feature selection methods and graphical model theory that has the potential to reveal new directed regulatory relationships from the analysis of population level genetic and gene expression data.

Recent advances in engineering propionyl-CoA metabolism for microbial production of value-added chemicals and biofuels.

Science.gov (United States)

Srirangan, Kajan; Bruder, Mark; Akawi, Lamees; Miscevic, Dragan; Kilpatrick, Shane; Moo-Young, Murray; Chou, C Perry

2017-09-01

Diminishing fossil fuel reserves and mounting environmental concerns associated with petrochemical manufacturing practices have generated significant interests in developing whole-cell biocatalytic systems for the production of value-added chemicals and biofuels. Although acetyl-CoA is a common natural biogenic precursor for the biosynthesis of numerous metabolites, propionyl-CoA is unpopular and non-native to most organisms. Nevertheless, with its C3-acyl moiety as a discrete building block, propionyl-CoA can serve as another key biogenic precursor to several biological products of industrial importance. As a result, engineering propionyl-CoA metabolism, particularly in genetically tractable hosts with the use of inexpensive feedstocks, has paved an avenue for novel biomanufacturing. Herein, we present a systematic review on manipulation of propionyl-CoA metabolism as well as relevant genetic and metabolic engineering strategies for microbial production of value-added chemicals and biofuels, including odd-chain alcohols and organic acids, bio(co)polymers and polyketides. [Formula: see text].

A social network analysis approach to alcohol use and co-occurring addictive behavior in young adults.

Science.gov (United States)

Meisel, Matthew K; Clifton, Allan D; MacKillop, James; Goodie, Adam S

2015-12-01

The current study applied egocentric social network analysis (SNA) to investigate the prevalence of addictive behavior and co-occurring substance use in college students' networks. Specifically, we examined individuals' perceptions of the frequency of network members' co-occurring addictive behavior and investigated whether co-occurring addictive behavior is spread evenly throughout networks or is more localized in clusters. We also examined differences in network composition between individuals with varying levels of alcohol use. The study utilized an egocentric SNA approach in which respondents ("egos") enumerated 30 of their closest friends, family members, co-workers, and significant others ("alters") and the relations among alters listed. Participants were 281 undergraduates at a large university in the Southeastern United States. Robust associations were observed among the frequencies of gambling, smoking, drinking, and using marijuana by network members. We also found that alters tended to cluster together into two distinct groups: one cluster moderate-to-high on co-occurring addictive behavior and the other low on co-occurring addictive behavior. Lastly, significant differences were present when examining egos' perceptions of alters' substance use between the networks of at-risk, light, and nondrinkers. These findings provide empirical evidence of distinct clustering of addictive behavior among young adults and suggest the promise of social network-based interventions for this cohort. Copyright © 2015. Published by Elsevier Ltd.

Interactive visualization of gene regulatory networks with associated gene expression time series data

NARCIS (Netherlands)

Westenberg, M.A.; Hijum, van S.A.F.T.; Lulko, A.T.; Kuipers, O.P.; Roerdink, J.B.T.M.; Linsen, L.; Hagen, H.; Hamann, B.

2008-01-01

We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes,

Hierarchically porous MgCo2O4 nanochain networks: template-free synthesis and catalytic application

Science.gov (United States)

Guan, Xiangfeng; Yu, Yunlong; Li, Xiaoyan; Chen, Dagui; Luo, Peihui; Zhang, Yu; Guo, Shanxin

2018-01-01

In this work, hierarchically porous MgCo2O4 nanochain networks were successfully synthesized by a novel template-free method realized via a facile solvothermal synthesis followed by a heat treatment. The morphologies of MgCo2O4 precursor could be adjusted from nanosheets to nanobelts and finally to interwoven nanowires, depending on the volume ratio of diethylene glycol to deionized water in the solution. After calcination, the interwoven precursor nanowires were transformed to hierarchical MgCo2O4 nanochain networks with marco-/meso-porosity, which are composed of 10-20 nm nanoparticles connected one by one. Moreover, the relative formation mechanism of the MgCo2O4 nanochain networks was discussed. More importantly, when evaluated as catalytic additive for AP thermal decomposition, the MgCo2O4 nanochain networks show excellent accelerating effect. It is benefited from the unique hierarchically porous network structure and multicomponent effect, which effectively accelerates ammonia oxidation and {{{{ClO}}}4}- species dissociation. This approach opens the way to design other hierarchically porous multicomponent metal oxides.

Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis.

Science.gov (United States)

van Dam, Jesse C J; Schaap, Peter J; Martins dos Santos, Vitor A P; Suárez-Diez, María

2014-09-26

Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each separate set has an intrinsic value that is diluted and partly lost when building a consensus network. Here we present a methodology to generate co-expression networks and, instead of a consensus network, we propose an integration framework where the different networks are kept and analysed with additional tools to efficiently combine the information extracted from each network. We developed a workflow to efficiently analyse information generated by different inference and prediction methods. Our methodology relies on providing the user the means to simultaneously visualise and analyse the coexisting networks generated by different algorithms, heterogeneous datasets, and a suite of analysis tools. As a show case, we have analysed the gene co-expression networks of Mycobacterium tuberculosis generated using over 600 expression experiments. Regarding DNA damage repair, we identified SigC as a key control element, 12 new targets for LexA, an updated LexA binding motif, and a potential mismatch repair system. We expanded the DevR regulon with 27 genes while identifying 9 targets wrongly assigned to this regulon. We discovered 10 new genes linked to zinc uptake and a new regulatory mechanism for ZuR. The use of co-expression networks to perform system level analysis allows the development of custom made methodologies. As show cases we implemented a pipeline to integrate ChIP-seq data and another method to uncover multiple regulatory layers. Our workflow is based on representing the multiple types of information as network representations and presenting these networks in a synchronous framework that allows their simultaneous visualization while keeping specific associations from the different

C60-pentacene network formation by 2-D co-crystallization.

Science.gov (United States)

Jin, Wei; Dougherty, Daniel B; Cullen, William G; Robey, Steven; Reutt-Robey, Janice E

2009-09-01

We report experiments highlighting the mechanistic role of mobile pentacene precursors in the formation of a network C(60)-pentacene co-crystalline structure on Ag(111). This co-crystalline arrangement was first observed by low temperature scanning tunneling microscopy (STM) by Zhang et al. (Zhang, H. L.; Chen, W.; Huang, H.; Chen, L.; Wee, A. T. S. J. Am. Chem. Soc. 2008, 130, 2720-2721). We now show that this structure forms readily at room temperature from a two-dimensional (2-D) mixture. Pentacene, evaporated onto Ag(111) to coverages of 0.4-1.0 ML, produces a two-dimensional (2-D) gas. Subsequently deposited C(60) molecules combine with the pentacene 2-D gas to generate a network structure, consisting of chains of close-packed C(60) molecules, spaced by individual C(60) linkers and 1 nm x 2.5 nm pores containing individual pentacene molecules. Spontaneous formation of this stoichiometric (C(60))(4)-pentacene network from a range of excess pentacene surface coverage (0.4 to 1.0 ML) indicates a self-limiting assembly process. We refine the structure model for this phase and discuss the generality of this co-crystallization mechanism.

Daily dynamics of bacterial numbers, CO2 emissions from soil and relationships between their wavelike fluctuations and succession of the microbial community

Science.gov (United States)

Semenov, A. M.; Bubnov, I. A.; Semenov, V. M.; Semenova, E. V.; Zelenev, V. V.; Semenova, N. A.

2013-08-01

The daily dynamics of the number of copiotrophic and oligotrophic bacteria (in colony-forming units) and CO2 emissions from cultivated soils after short- and long-term disturbances were studied for 25-27 days in a microfield experiment. The relationship of the wavelike fluctuations of the bacterial number and CO2 emission with the succession of the soil microbial community was determined by the polymerase chain reaction method—denaturing gradient gel electrophoresis (PCR-DGGE). Short-term disturbances involved the application of organic or mineral fertilizers, pesticides, and plant residues to the soils of different plots. The long-term effect was a result of using biological and intensive farming systems for three years. The short-term disturbances resulted in increased peaks of the bacterial number, the significance of which was confirmed by harmonics analysis. The daily dynamics of the structure of the soil microbial community, which was studied for 27 days by the DGGE method, also had an oscillatory pattern. Statistical processing of the data (principal components analysis, harmonics and cross-correlation analyses) has revealed significant fluctuations in the structure of microbial communities coinciding with those of the bacterial populations. The structure of the microbial community changed within each peak of the dynamics of the bacterial number (but not from peak to peak), pointing to the cyclical character of the short-term succession. The long-term effects resulted in a less intense response of the microbiota—a lower rate of CO2 emission from the soil cultivated according to the organic farming system.

Microbial Degradation Behavior in Seawater of Polyester Blends Containing Poly(3-hydroxybutyrate-co-3-hydroxyhexanoate (PHBHHx

Directory of Open Access Journals (Sweden)

Hitoshi Sashiwa

2018-01-01

Full Text Available The microbial degradation behavior of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate (PHBHHx and its compound with several polyesters such as poly(butylene adipate-co-telephtharate (PBAT, poly(butylene succinate (PBS, and polylactic acid (PLA in seawater was tested by a biological oxygen demand (BOD method. PHBHHx showed excellent biodegradation in seawater in this study. In addition, the biodegradation rate of several blends was much influenced by the weight ratio of PHBHHx in their blends and decreased in accordance with the decrement of PHBHHX ratio. The surface morphology of the sheet was important factor for controlling the biodegradation rate of PHBHHx-containing blends in seawater.

Microbial network, phylogenetic diversity and community membership in the active layer across a permafrost thaw gradient.

Science.gov (United States)

Mondav, Rhiannon; McCalley, Carmody K; Hodgkins, Suzanne B; Frolking, Steve; Saleska, Scott R; Rich, Virginia I; Chanton, Jeff P; Crill, Patrick M

2017-08-01

Biogenic production and release of methane (CH 4 ) from thawing permafrost has the potential to be a strong source of radiative forcing. We investigated changes in the active layer microbial community of three sites representative of distinct permafrost thaw stages at a palsa mire in northern Sweden. The palsa site (intact permafrost and low radiative forcing signature) had a phylogenetically clustered community dominated by Acidobacteria and Proteobacteria. The bog (thawing permafrost and low radiative forcing signature) had lower alpha diversity and midrange phylogenetic clustering, characteristic of ecosystem disturbance affecting habitat filtering. Hydrogenotrophic methanogens and Acidobacteria dominated the bog shifting from palsa-like to fen-like at the waterline. The fen (no underlying permafrost, high radiative forcing signature) had the highest alpha, beta and phylogenetic diversity, was dominated by Proteobacteria and Euryarchaeota and was significantly enriched in methanogens. The Mire microbial network was modular with module cores consisting of clusters of Acidobacteria, Euryarchaeota or Xanthomonodales. Loss of underlying permafrost with associated hydrological shifts correlated to changes in microbial composition, alpha, beta and phylogenetic diversity associated with a higher radiative forcing signature. These results support the complex role of microbial interactions in mediating carbon budget changes and climate feedback in response to climate forcing. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

EMMPRIN co-expressed with matrix metalloproteinases predicts poor prognosis in patients with osteosarcoma.

Science.gov (United States)

Futamura, Naohisa; Nishida, Yoshihiro; Urakawa, Hiroshi; Kozawa, Eiji; Ikuta, Kunihiro; Hamada, Shunsuke; Ishiguro, Naoki

2014-06-01

Several studies have focused on the relationships between the expression of extracellular matrix metalloproteinase inducer (EMMPRIN) and the prognosis of patients with malignant tumors. However, few of these have investigated the expression of EMMPRIN in osteosarcoma. We examined expression levels of EMMPRIN immunohistochemically in 53 cases of high-grade osteosarcoma of the extremities and analyzed the correlation of its expression with patient prognosis. The correlation between matrix metalloproteinases (MMPs) and EMMPRIN expression and the prognostic value of co-expression were also analyzed. Staining positivity for EMMPRIN was negative in 7 cases, low in 17, moderate in 19, and strong in 10. The overall and disease-free survivals (OS and DFS) in patients with higher EMMPRIN expression (strong-moderate) were significantly lower than those in the lower (weak-negative) group (0.037 and 0.024, respectively). In multivariate analysis, age (P=0.004), location (P=0.046), and EMMPRIN expression (P=0.038) were significant prognostic factors for overall survival. EMMPRIN expression (P=0.024) was also a significant prognostic factor for disease-free survival. Co-expression analyses of EMMPRIN and MMPs revealed that strong co-expression of EMMPRIN and membrane-type 1 (MT1)-MMP had a poor prognostic value (P=0.056 for DFS, P=0.006 for OS). EMMPRIN expression and co-expression with MMPs well predict the prognosis of patients with extremity osteosarcoma, making EMMPRIN a possible therapeutic target in these patients.

Heterologous Expression of the Clostridium carboxidivorans CO Dehydrogenase Alone or Together with the Acetyl Coenzyme A Synthase Enables both Reduction of CO2 and Oxidation of CO by Clostridium acetobutylicum.

Science.gov (United States)

Carlson, Ellinor D; Papoutsakis, Eleftherios T

2017-08-15

With recent advances in synthetic biology, CO 2 could be utilized as a carbon feedstock by native or engineered organisms, assuming the availability of electrons. Two key enzymes used in autotrophic CO 2 fixation are the CO dehydrogenase (CODH) and acetyl coenzyme A (acetyl-CoA) synthase (ACS), which form a bifunctional heterotetrameric complex. The CODH/ACS complex can reversibly catalyze CO 2 to CO, effectively enabling a biological water-gas shift reaction at ambient temperatures and pressures. The CODH/ACS complex is part of the Wood-Ljungdahl pathway (WLP) used by acetogens to fix CO 2 , and it has been well characterized in native hosts. So far, only a few recombinant CODH/ACS complexes have been expressed in heterologous hosts, none of which demonstrated in vivo CO 2 reduction. Here, functional expression of the Clostridium carboxidivorans CODH/ACS complex is demonstrated in the solventogen Clostridium acetobutylicum , which was engineered to express CODH alone or together with the ACS. Both strains exhibited CO 2 reduction and CO oxidation activities. The CODH reactions were interrogated using isotopic labeling, thus verifying that CO was a direct product of CO 2 reduction, and vice versa. CODH apparently uses a native C. acetobutylicum ferredoxin as an electron carrier for CO 2 reduction. Heterologous CODH activity depended on actively growing cells and required the addition of nickel, which is inserted into CODH without the need to express the native Ni insertase protein. Increasing CO concentrations in the gas phase inhibited CODH activity and altered the metabolite profile of the CODH-expressing cells. This work provides the foundation for engineering a complete and functional WLP in nonnative host organisms. IMPORTANCE Functional expression of CO dehydrogenase (CODH) from Clostridium carboxidivorans was demonstrated in C. acetobutylicum , which is natively incapable of CO 2 fixation. The expression of CODH, alone or together with the C. carboxidivorans

A fuzzy network module extraction technique for gene expression data

Indian Academy of Sciences (India)

2014-05-01

expression network from the distance matrix. The distance matrix is .... mental process, cellular component assembly involved in ..... the molecules are present in the network. User can ... hsa05213:Endometrial cancer. 24. 0.07.

Characterization of microbial associations with methanotrophic archaea and sulfate-reducing bacteria through statistical comparison of nested Magneto-FISH enrichments

Directory of Open Access Journals (Sweden)

Elizabeth Trembath-Reichert

2016-04-01

Full Text Available Methane seep systems along continental margins host diverse and dynamic microbial assemblages, sustained in large part through the microbially mediated process of sulfate-coupled Anaerobic Oxidation of Methane (AOM. This methanotrophic metabolism has been linked to consortia of anaerobic methane-oxidizing archaea (ANME and sulfate-reducing bacteria (SRB. These two groups are the focus of numerous studies; however, less is known about the wide diversity of other seep associated microorganisms. We selected a hierarchical set of FISH probes targeting a range of Deltaproteobacteria diversity. Using the Magneto-FISH enrichment technique, we then magnetically captured CARD-FISH hybridized cells and their physically associated microorganisms from a methane seep sediment incubation. DNA from nested Magneto-FISH experiments was analyzed using Illumina tag 16S rRNA gene sequencing (iTag. Enrichment success and potential bias with iTag was evaluated in the context of full-length 16S rRNA gene clone libraries, CARD-FISH, functional gene clone libraries, and iTag mock communities. We determined commonly used Earth Microbiome Project (EMP iTAG primers introduced bias in some common methane seep microbial taxa that reduced the ability to directly compare OTU relative abundances within a sample, but comparison of relative abundances between samples (in nearly all cases and whole community-based analyses were robust. The iTag dataset was subjected to statistical co-occurrence measures of the most abundant OTUs to determine which taxa in this dataset were most correlated across all samples. Many non-canonical microbial partnerships were statistically significant in our co-occurrence network analysis, most of which were not recovered with conventional clone library sequencing, demonstrating the utility of combining Magneto-FISH and iTag sequencing methods for hypothesis generation of associations within complex microbial communities. Network analysis pointed to

Characterization of microbial associations with methanotrophic archaea and sulfate-reducing bacteria through statistical comparison of nested Magneto-FISH enrichments.

Science.gov (United States)

Trembath-Reichert, Elizabeth; Case, David H; Orphan, Victoria J

2016-01-01

Methane seep systems along continental margins host diverse and dynamic microbial assemblages, sustained in large part through the microbially mediated process of sulfate-coupled Anaerobic Oxidation of Methane (AOM). This methanotrophic metabolism has been linked to consortia of anaerobic methane-oxidizing archaea (ANME) and sulfate-reducing bacteria (SRB). These two groups are the focus of numerous studies; however, less is known about the wide diversity of other seep associated microorganisms. We selected a hierarchical set of FISH probes targeting a range of Deltaproteobacteria diversity. Using the Magneto-FISH enrichment technique, we then magnetically captured CARD-FISH hybridized cells and their physically associated microorganisms from a methane seep sediment incubation. DNA from nested Magneto-FISH experiments was analyzed using Illumina tag 16S rRNA gene sequencing (iTag). Enrichment success and potential bias with iTag was evaluated in the context of full-length 16S rRNA gene clone libraries, CARD-FISH, functional gene clone libraries, and iTag mock communities. We determined commonly used Earth Microbiome Project (EMP) iTAG primers introduced bias in some common methane seep microbial taxa that reduced the ability to directly compare OTU relative abundances within a sample, but comparison of relative abundances between samples (in nearly all cases) and whole community-based analyses were robust. The iTag dataset was subjected to statistical co-occurrence measures of the most abundant OTUs to determine which taxa in this dataset were most correlated across all samples. Many non-canonical microbial partnerships were statistically significant in our co-occurrence network analysis, most of which were not recovered with conventional clone library sequencing, demonstrating the utility of combining Magneto-FISH and iTag sequencing methods for hypothesis generation of associations within complex microbial communities. Network analysis pointed to many co

Mass spectral molecular networking of living microbial colonies

NARCIS (Netherlands)

Watrous, J.; Roach, P.; Alexandrov, T.; Heath, B.S.; Yang, J.Y.; Kersten, R.D.; Voort, van der M.; Pogliano, K.; Gross, H.; Raaijmakers, J.; Moore, B.S.; Laskin, J.; Bandeira, N.; Dorrestein, P.C.

2012-01-01

Integrating the governing chemistry with the genomics and phenotypes of microbial colonies has been a “holy grail” in microbiology. This work describes a highly sensitive, broadly applicable, and cost-effective approach that allows metabolic profiling of live microbial colonies directly from a Petri

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

Perceived Conventionality in Co-speech Gestures Involves the Fronto-Temporal Language Network

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Dhana Wolf

2017-11-01

Full Text Available Face-to-face communication is multimodal; it encompasses spoken words, facial expressions, gaze, and co-speech gestures. In contrast to linguistic symbols (e.g., spoken words or signs in sign language relying on mostly explicit conventions, gestures vary in their degree of conventionality. Bodily signs may have a general accepted or conventionalized meaning (e.g., a head shake or less so (e.g., self-grooming. We hypothesized that subjective perception of conventionality in co-speech gestures relies on the classical language network, i.e., the left hemispheric inferior frontal gyrus (IFG, Broca's area and the posterior superior temporal gyrus (pSTG, Wernicke's area and studied 36 subjects watching video-recorded story retellings during a behavioral and an functional magnetic resonance imaging (fMRI experiment. It is well documented that neural correlates of such naturalistic videos emerge as intersubject covariance (ISC in fMRI even without involving a stimulus (model-free analysis. The subjects attended either to perceived conventionality or to a control condition (any hand movements or gesture-speech relations. Such tasks modulate ISC in contributing neural structures and thus we studied ISC changes to task demands in language networks. Indeed, the conventionality task significantly increased covariance of the button press time series and neuronal synchronization in the left IFG over the comparison with other tasks. In the left IFG, synchronous activity was observed during the conventionality task only. In contrast, the left pSTG exhibited correlated activation patterns during all conditions with an increase in the conventionality task at the trend level only. Conceivably, the left IFG can be considered a core region for the processing of perceived conventionality in co-speech gestures similar to spoken language. In general, the interpretation of conventionalized signs may rely on neural mechanisms that engage during language comprehension.

Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling.

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Junha Shin

Full Text Available Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life-Archaea, Bacteria, and Eukaryota-suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co

[Co-authorship and Spanish pediatric scientific collaboration networks (2006-2010)].

Science.gov (United States)

Aleixandre Benavent, R; González de Dios, J; Alonso Arroyo, A; Bolaños Pizarro, M; Castelló Cogollos, L; González Alcaide, G; Vidal Infer, A; Navarro Molina, C; Coronado Ferrer, S; González Muñoz, M; Málaga Guerrero, S

2013-06-01

Scientific collaboration is very important, as it is the basis of the scientific development of every discipline. The aim of this paper is to identify the indicators of scientific collaboration and co-authorship networks of Spanish researchers and institutions publishing in national and international paediatric, multidisciplinary or other knowledge areas journals during the period 2006-2010. The papers studied were obtained from the databases including, Science Citation Index Expanded, Scopus, Índice Médico Español and Índice Bibliográfico Español en Ciencias de la Salud, by means of applying different search profiles. All the papers signed by co-authors were quantified in order to identify the authorship and institutional collaboration networks. Furthermore the degree, betweenness index, and closeness index were obtained as a measurement of the structural analysis. Co-authorships were represented graphically by the network analysis and display software Pajek. A total of 7971 articles were published during the period 2006-2010, with 90.55% completed in collaboration. Using a threshold of 10 or more co-authorships, 77 research groups in Pediatrics were identified. Most papers were published in collaboration between institutions of the same Autonomous Community (42.28%), and 14.84% with international collaboration. The analysis of institutional participation enabled a large nucleus or institutional collaboration network to be identified, with 52 linked institutions. International collaboration was led by the USA and European countries, such as United Kingdom, Germany and Italy. Authors, institutions and the most active working groups in Spanish pediatrics were identified, which is very interesting information to establish contacts to increase the existing networks, to prevent redundancies, and to take advantage of the new emerging groups. It is necessary to promote the collaboration of Spanish researchers, especially with their international colleagues, since a

Organized network for supporting the amateur-scientist co-operation in Finland

Science.gov (United States)

Mäkelä, V.; Haukka, H.; Oksanen, A.; Hentunen, V.-P.

2014-04-01

PROAM network is a working group of Ursa Astronomical Association [1] for supporting Finnish amateur astronomers participating to co-operation projects between professional and amateur astronomers. The network relays the information on projects, maintains professional contacts and arranges training on technical skills for research work.

Preliminary investigation to use Bayesian networks in predicting NOx, CO, CO2 and HC emissions

International Nuclear Information System (INIS)

Karri, V.; Hafez, H.A.; Kristiansen, M.

2005-01-01

A Bayesian network was used to characterize Lister-Petter diesel combustion engine emissions. Three sets of tests were conducted: (1) full open throttle; (2) 68 per cent closed throttle; and (3) 58 per cent closed throttle. The first test simulated normal lean burning conditions, while the last 2 tests simulated a clogged air filter. Experiments were conducted in an engine generator assembly with a fixed speed governor of 1500 rpm. Electrochemical sensors were used to detect nitrogen oxide (NO x ); carbon dioxide (CO 2 ); carbon monoxide (CO); hydrocarbons; and particulate matter. Engine oil, engine outlet, and engine inlet and exhaust temperatures were digitally measured. Data from 20 experimental sets of tests were used to train, test and project accurate emission levels. The Bayesian network model was built using input variables and measured output parameters related to the exhaust components. Human knowledge was used to build relationships between defined nodes and a path condition algorithm. An estimation-maximization algorithm was used. Results of the validation study showed that the Bayesian network accurately predicted emissions levels. It was concluded that it is possible to predict engine emission outputs with probable acceptable levels using Bayesian network modelling techniques and limited experimental data. 33 refs., 3 tabs., 8 figs

Methane production from formate, acetate and H2/CO2; focusing on kinetics and microbial characterization

DEFF Research Database (Denmark)

Pan, Xiaofang; Angelidaki, Irini; Alvarado-Morales, Merlin

2016-01-01

For evaluating the methanogenesis from typical methanogenic precursors (formate, acetate and H-2/CO2), CH4 production kinetics were investigated at 37 +/- 1 degrees C in batch anaerobic digestion tests and stimulated by modified Gompertz model. The results showed that maximum methanation rate from...... formate, acetate and H-2/CO2 were 19.58 +/- 0.49, 42.65 +/- 1.17 and 314.64 +/- 3.58 N mL/gVS/d in digested manure system and 6.53 +/- 0.31, 132.04 +/- 3.96 and 640.16 +/- 19.92 N mL/gVS/d in sewage sludge system during second generation incubation. Meanwhile the model could not fit well in granular...... sludge system, while the rate of formate methanation was faster than from H-2/CO2 and acetate. Considering both the kinetic results and microbial assay we could conclude that H-2/CO2 methanation was the fastest methanogenic step in digested manure and sewage sludge system with Methanomicrobiales...

Novel RuCoSe as non-platinum catalysts for oxygen reduction reaction in microbial fuel cells

Science.gov (United States)

Rozenfeld, Shmuel; Schechter, Michal; Teller, Hanan; Cahan, Rivka; Schechter, Alex

2017-09-01

Microbial electrochemical cells (MECs) are explored for the conversion of acetate directly to electrical energy. This device utilizes a Geobacter sulfurreducens anode and a novel RuCoSe air cathode. RuCoSe synthesized in selected compositions by a borohydride reduction method produces amorphous structures of powdered agglomerates. Oxygen reduction reaction (ORR) was measured in a phosphate buffer solution pH 7 using a rotating disc electrode (RDE), from which the kinetic current (ik) was measured as a function of potential and composition. The results show that ik of RuxCoySe catalysts increases in the range of XRu = 0.25 > x > 0.7 and y < 0.15 for all tested potentials. A poisoning study of RuCoSe and Pt catalysts in a high concentration acetate solution shows improved tolerance of RuCoSe to this fuel at acetate concentration ≥500 mM. MEC discharge plots under physiological conditions show that ∼ RuCo2Se (sample S3) has a peak power density of 750 mW cm-2 which is comparable with Pt 900 mW cm-2.

Antimicrobial activity of apple cider vinegar against Escherichia coli, Staphylococcus aureus and Candida albicans; downregulating cytokine and microbial protein expression.

Science.gov (United States)

Yagnik, Darshna; Serafin, Vlad; J Shah, Ajit

2018-01-29

The global escalation in antibiotic resistance cases means alternative antimicrobials are essential. The aim of this study was to investigate the antimicrobial capacity of apple cider vinegar (ACV) against E. coli, S. aureus and C. albicans. The minimum dilution of ACV required for growth inhibition varied for each microbial species. For C. albicans, a 1/2 ACV had the strongest effect, S. aureus, a 1/25 dilution ACV was required, whereas for E-coli cultures, a 1/50 ACV dilution was required (p < 0.05). Monocyte co-culture with microbes alongside ACV resulted in dose dependent downregulation of inflammatory cytokines (TNFα, IL-6). Results are expressed as percentage decreases in cytokine secretion comparing ACV treated with non-ACV treated monocytes cultured with E-coli (TNFα, 99.2%; IL-6, 98%), S. aureus (TNFα, 90%; IL-6, 83%) and C. albicans (TNFα, 83.3%; IL-6, 90.1%) respectively. Proteomic analyses of microbes demonstrated that ACV impaired cell integrity, organelles and protein expression. ACV treatment resulted in an absence in expression of DNA starvation protein, citrate synthase, isocitrate and malate dehydrogenases in E-coli; chaperone protein DNak and ftsz in S. aureus and pyruvate kinase, 6-phosphogluconate dehydrogenase, fructose bisphosphate were among the enzymes absent in C.albican cultures. The results demonstrate ACV has multiple antimicrobial potential with clinical therapeutic implications.

Corpus Linguistics, Network Analysis and Co-occurrence Matrices Corpus Linguistics, Network Analysis and Co-occurrence Matrices

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Keith Stuart

2009-12-01

Full Text Available This article describes research undertaken in order to design a methodology for the reticular representation of knowledge of a specific discourse community. To achieve this goal, a representative corpus of the scientific production of the members of this discourse community (Universidad Politécnica de Valencia, UPV was created. The article presents the practical analysis (frequency, keyword, collocation and cluster analysis that was carried out in the initial phases of the study aimed at establishing the theoretical and practical background and framework for our matrix and network analysis of the scientific discourse of the UPV. In the methodology section, the processes that have allowed us to extract from the corpus the linguistic elements needed to develop co-occurrence matrices, as well as the computer tools used in the research, are described. From these co-occurrence matrices, semantic networks of subject and discipline knowledge were generated. Finally, based on the results obtained, we suggest that it may be viable to extract and to represent the intellectual capital of an academic institution using corpus linguistics methods in combination with the formulations of network theory.En este artículo describimos la investigación que se ha desarrollado en el diseño de una metodología para la representación reticular del conocimiento que se genera en el seno de una institución a partir de un corpus representativo de la producción científica de los integrantes de dicha comunidad discursiva, la Universidad Politécnica de Valencia.. Para ello, presentamos las acciones que se realizaron en las fases iniciales del estudio encaminadas a establecer el marco teórico y práctico en el que se inscribe nuestro análisis. En la sección de metodología se describen las herramientas informáticas utilizadas, así como los procesos que nos permitieron disponer de aquellos elementos presentes en el corpus, que nos llevarían al desarrollo de

Exogenous Nitrogen Addition Reduced the Temperature Sensitivity of Microbial Respiration without Altering the Microbial Community Composition

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Hui Wei

2017-12-01

Full Text Available Atmospheric nitrogen (N deposition is changing in both load quantity and chemical composition. The load effects have been studied extensively, whereas the composition effects remain poorly understood. We conducted a microcosm experiment to study how N chemistry affected the soil microbial community composition characterized by phospholipid fatty acids (PLFAs and activity indicated by microbial CO2 release. Surface and subsurface soils collected from an old-growth subtropical forest were supplemented with three N-containing materials (ammonium, nitrate, and urea at the current regional deposition load (50 kg ha-1 yr-1 and incubated at three temperatures (10, 20, and 30°C to detect the interactive effects of N deposition and temperature. The results showed that the additions of N, regardless of form, did not alter the microbial PLFAs at any of the three temperatures. However, the addition of urea significantly stimulated soil CO2 release in the early incubation stage. Compared with the control, N addition consistently reduced the temperature dependency of microbial respiration, implying that N deposition could potentially weaken the positive feedback of the warming-stimulated soil CO2 release to the atmosphere. The consistent N effects for the surface and subsurface soils suggest that the effects of N on soil microbial communities may be independent of soil chemical contents and stoichiometry.

Bioinformatic approaches reveal metagenomic characterization of soil microbial community.

Directory of Open Access Journals (Sweden)

Zhuofei Xu

Full Text Available As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.

Microbial reductive dehalogenation of trihalomethanes by a Dehalobacter-containing co-culture.

Science.gov (United States)

Zhao, Siyan; Rogers, Matthew J; He, Jianzhong

2017-07-01

Trihalomethanes such as chloroform and bromoform, although well-known as a prominent class of disinfection by-products, are ubiquitously distributed in the environment due to widespread industrial usage in the past decades. Chloroform and bromoform are particularly concerning, of high concentrations detected and with long half-lives up to several hundred days in soils and groundwater. In this study, we report a Dehalobacter- and Desulfovibrio-containing co-culture that exhibits dehalogenation of chloroform (~0.61 mM) to dichloromethane and bromoform (~0.67 mM) to dibromomethane within 10-15 days. This co-culture was further found to dechlorinate 1,1,1-trichloroethane (1,1,1-TCA) (~0.65 mM) to 1,1-dichloroethane within 12 days. The Dehalobacter species present in this co-culture, designated Dehalobacter sp. THM1, was found to couple growth with dehalogenation of chloroform, bromoform, and 1,1,1-TCA. Strain THM1 harbors a newly identified reductive dehalogenase (RDase), ThmA, which catalyzes chloroform, bromoform, and 1,1,1-TCA dehalogenation. Additionally, based on the sequences of thmA and other identified chloroform RDase genes, ctrA, cfrA, and tmrA, a pair of chloroform RDase gene-specific primers were designed and successfully applied to investigate the chloroform dechlorinating potential of microbial communities. The comparative analysis of chloroform RDases with tetrachloroethene RDases suggests a possible approach in predicting the substrate specificity of uncharacterized RDases in the future.

G-NEST: a gene neighborhood scoring tool to identify co-conserved, co-expressed genes

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Lemay Danielle G

2012-09-01

Full Text Available Abstract Background In previous studies, gene neighborhoods—spatial clusters of co-expressed genes in the genome—have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Scoring Tool (G-NEST which combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all possible window sizes simultaneously. Results Using G-NEST on atlases of mouse and human tissue expression data, we found that large neighborhoods of ten or more genes are extremely rare in mammalian genomes. When they do occur, neighborhoods are typically composed of families of related genes. Both the highest scoring and the largest neighborhoods in mammalian genomes are formed by tandem gene duplication. Mammalian gene neighborhoods contain highly and variably expressed genes. Co-localized noisy gene pairs exhibit lower evolutionary conservation of their adjacent genome locations, suggesting that their shared transcriptional background may be disadvantageous. Genes that are essential to mammalian survival and reproduction are less likely to occur in neighborhoods, although neighborhoods are enriched with genes that function in mitosis. We also found that gene orientation and protein-protein interactions are partially responsible for maintenance of gene neighborhoods. Conclusions Our experiments using G-NEST confirm that tandem gene duplication is the primary driver of non-random gene order in mammalian genomes. Non-essentiality, co-functionality, gene orientation, and protein-protein interactions are additional forces that maintain gene neighborhoods, especially those formed by tandem duplicates. We expect G-NEST to be useful for other applications such as the identification of core regulatory modules, common transcriptional backgrounds, and chromatin domains. The

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

Science.gov (United States)

Uddin, Raihan; Singh, Shiva M

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they

Microbially-reduced graphene scaffolds to facilitate extracellular electron transfer in microbial fuel cells.

Science.gov (United States)

Yuan, Yong; Zhou, Shungui; Zhao, Bo; Zhuang, Li; Wang, Yueqiang

2012-07-01

A one-pot method is exploited by adding graphene oxide (GO) and acetate into an microbial fuel cell (MFC) in which GO is microbially reduced, leading to in situ construction of a bacteria/graphene network in the anode. The obtained microbially reduced graphene (MRG) exhibits comparable conductivity and physical characteristics to the chemically reduced graphene. Electrochemical measurements reveal that the number of exoelectrogens involved in extracellular electron transfer (EET) to the solid electrode, increases due to the presence of graphene scaffolds, and the EET is facilitated in terms of electron transfer kinetics. As a result, the maximum power density of the MFC is enhanced by 32% (from 1440 to 1905 mW m(-2)) and the coulombic efficiency is improved by 80% (from 30 to 54%). The results demonstrate that the construction of the bacteria/graphene network is an effective alternative to improve the MFC performance. Copyright © 2012 Elsevier Ltd. All rights reserved.

Co-occurrence correlations of heavy metals in sediments revealed using network analysis.

Science.gov (United States)

Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong

2015-01-01

In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Carbon flow from volcanic CO2 into soil microbial communities of a wetland mofette.

Science.gov (United States)

Beulig, Felix; Heuer, Verena B; Akob, Denise M; Viehweger, Bernhard; Elvert, Marcus; Herrmann, Martina; Hinrichs, Kai-Uwe; Küsel, Kirsten

2015-03-01

Effects of extremely high carbon dioxide (CO2) concentrations on soil microbial communities and associated processes are largely unknown. We studied a wetland area affected by spots of subcrustal CO2 degassing (mofettes) with focus on anaerobic autotrophic methanogenesis and acetogenesis because the pore gas phase was largely hypoxic. Compared with a reference soil, the mofette was more acidic (ΔpH ∼0.8), strongly enriched in organic carbon (up to 10 times), and exhibited lower prokaryotic diversity. It was dominated by methanogens and subdivision 1 Acidobacteria, which likely thrived under stable hypoxia and acidic pH. Anoxic incubations revealed enhanced formation of acetate and methane (CH4) from hydrogen (H2) and CO2 consistent with elevated CH4 and acetate levels in the mofette soil. (13)CO2 mofette soil incubations showed high label incorporations with ∼512 ng (13)C g (dry weight (dw)) soil(-1) d(-1) into the bulk soil and up to 10.7 ng (13)C g (dw) soil(-1) d(-1) into almost all analyzed bacterial lipids. Incorporation of CO2-derived carbon into archaeal lipids was much lower and restricted to the first 10 cm of the soil. DNA-SIP analysis revealed that acidophilic methanogens affiliated with Methanoregulaceae and hitherto unknown acetogens appeared to be involved in the chemolithoautotrophic utilization of (13)CO2. Subdivision 1 Acidobacteriaceae assimilated (13)CO2 likely via anaplerotic reactions because Acidobacteriaceae are not known to harbor enzymatic pathways for autotrophic CO2 assimilation. We conclude that CO2-induced geochemical changes promoted anaerobic and acidophilic organisms and altered carbon turnover in affected soils.

Social networks and online environments: when science and practice co-evolve

OpenAIRE

Rosen, Devan; Barnett, George A.; Kim, Jang Hyun

2011-01-01

The science of social network analysis has co-evolved with the development of online environments and computer-mediated communication. Unique and precise data available from computer and information systems have allowed network scientists to explore novel social phenomena and develop new methods. Additionally, advances in the structural analysis and visualization of computer-mediated social networks have informed developers and shaped the design of social media tools. This article reviews som...

Heavy metal immobilization via microbially induced carbonate precipitation and co-precipitation

Science.gov (United States)

Lauchnor, E. G.; Stoick, E.

2017-12-01

Microbially induced CaCO3 precipitation (MICP) has been successfully used in applications such as porous media consolidation and sealing of leakage pathways in the subsurface, and it has the potential to be used for remediation of metal and radionuclide contaminants in surface and groundwater. In this work, MICP is investigated for removal of dissolved heavy metals from contaminated mine discharge water via co-precipitation in CaCO3 or formation of other metal carbonates. The bacterially catalyzed hydrolysis of urea produces inorganic carbon and ammonium and increases pH and the saturation index of carbonate minerals to promote precipitation of CaCO3. Other heavy metal cations can be co-precipitated in CaCO3 as impurities or by replacing Ca2+ in the crystal lattice. We performed laboratory batch experiments of MICP in alkaline mine drainage sampled from an abandoned mine site in Montana and containing a mixture of heavy metals at near neutral pH. Both a model bacterium, Sporosarcina pasteurii, and a ureolytic bacterium isolated from sediments on the mine site were used to promote MICP. Removal of dissolved metals from the aqueous phase was determined via inductively coupled plasma mass spectrometry and resulting precipitates were analyzed via electron microscopy and energy dispersive x-ray spectroscopy (EDX). Both S. pasteurii and the native ureolytic isolate demonstrated ureolysis, increased the pH and promoted precipitation of CaCO3 in batch tests. MICP by the native bacterium reduced concentrations of the heavy metals zinc, copper, cadmium, nickel and manganese in the water. S. pasteurii was also able to promote MICP, but with less removal of dissolved metals. Analysis of precipitates revealed calcium carbonate and phosphate minerals were likely present. The native isolate is undergoing identification via 16S DNA sequencing. Ongoing work will evaluate biofilm formation and MICP by the isolate in continuous flow, gravel-filled laboratory columns. This research

Microbial electrosynthesis of biochemicals

NARCIS (Netherlands)

Bajracharya, S.

2016-01-01

Microbial electrosynthesis (MES) is an electricity-driven production of chemicals from low-value waste using microorganisms as biocatalysts. MES from CO2 comprises conversion of CO2 to multi-carbon compounds employing microbes at the cathode which use electricity as an energy source. This thesis

Biogas production from spent rose hips (Rosa canina L.): fraction separation, organic loading and co-digestion with N-rich microbial biomass.

Science.gov (United States)

Osojnik Črnivec, Ilja Gasan; Muri, Petra; Djinović, Petar; Pintar, Albin

2014-11-01

Complex waste streams originating from extraction processes containing residual organic solvents and increased C/N ratios have not yet been considered as feedstock for biogas production to a great extent. In this study, spent rosehip (Rosa canina L.) solid residue (64%VS, 22 MJ/kg HHV, 30C/1N) was obtained from an industrial ethanol aided extraction process, and extensively examined in an automated batch bioreactor system for biogas production. Fraction separation of the compact lignocellulosic seeds increased the available sugar and ethanol content, resulting in high biogas potential of the sieved residue (516 NL/kg VS'). In co-digestion of spent rosehip substrate with non-deactivated nitrogen rich microbial co-substrates, methanogenesis was favored (Y(m) > 68%(CH4)). In individual digestion of microbial co-substrates, this was not the case, as biogas with 28 vol.% N2 was produced from activated sludge supplement. Therefore, effective inhibition of exogenous microbiota was achieved in the presence of carbonaceous spent rose hip. Copyright © 2014 Elsevier Ltd. All rights reserved.

CoMiniGut—a small volume in vitro colon model for the screening of gut microbial fermentation processes

Science.gov (United States)

Khakimov, Bekzod; Nielsen, Sebastian; Sørensen, Helena; van den Berg, Frans; Nielsen, Dennis Sandris

2018-01-01

Driven by the growing recognition of the influence of the gut microbiota (GM) on human health and disease, there is a rapidly increasing interest in understanding how dietary components, pharmaceuticals and pre- and probiotics influence GM. In vitro colon models represent an attractive tool for this purpose. With the dual objective of facilitating the investigation of rare and expensive compounds, as well as an increased throughput, we have developed a prototype in vitro parallel gut microbial fermentation screening tool with a working volume of only 5 ml consisting of five parallel reactor units that can be expanded with multiples of five to increase throughput. This allows e.g., the investigation of interpersonal variations in gut microbial dynamics and the acquisition of larger data sets with enhanced statistical inference. The functionality of the in vitro colon model, Copenhagen MiniGut (CoMiniGut) was first demonstrated in experiments with two common prebiotics using the oligosaccharide inulin and the disaccharide lactulose at 1% (w/v). We then investigated fermentation of the scarce and expensive human milk oligosaccharides (HMOs) 3-Fucosyllactose, 3-Sialyllactose, 6-Sialyllactose and the more common Fructooligosaccharide in fermentations with infant gut microbial communities. Investigations of microbial community composition dynamics in the CoMiniGut reactors by MiSeq-based 16S rRNA gene amplicon high throughput sequencing showed excellent experimental reproducibility and allowed us to extract significant differences in gut microbial composition after 24 h of fermentation for all investigated substrates and fecal donors. Furthermore, short chain fatty acids (SCFAs) were quantified for all treatments and donors. Fermentations with inulin and lactulose showed that inulin leads to a microbiota dominated by obligate anaerobes, with high relative abundance of Bacteroidetes, while the more easily fermented lactulose leads to higher relative abundance of

CoMiniGut-a small volume in vitro colon model for the screening of gut microbial fermentation processes.

Science.gov (United States)

Wiese, Maria; Khakimov, Bekzod; Nielsen, Sebastian; Sørensen, Helena; van den Berg, Frans; Nielsen, Dennis Sandris

2018-01-01

Driven by the growing recognition of the influence of the gut microbiota (GM) on human health and disease, there is a rapidly increasing interest in understanding how dietary components, pharmaceuticals and pre- and probiotics influence GM. In vitro colon models represent an attractive tool for this purpose. With the dual objective of facilitating the investigation of rare and expensive compounds, as well as an increased throughput, we have developed a prototype in vitro parallel gut microbial fermentation screening tool with a working volume of only 5 ml consisting of five parallel reactor units that can be expanded with multiples of five to increase throughput. This allows e.g., the investigation of interpersonal variations in gut microbial dynamics and the acquisition of larger data sets with enhanced statistical inference. The functionality of the in vitro colon model, Copenhagen MiniGut (CoMiniGut) was first demonstrated in experiments with two common prebiotics using the oligosaccharide inulin and the disaccharide lactulose at 1% (w/v). We then investigated fermentation of the scarce and expensive human milk oligosaccharides (HMOs) 3-Fucosyllactose, 3-Sialyllactose, 6-Sialyllactose and the more common Fructooligosaccharide in fermentations with infant gut microbial communities. Investigations of microbial community composition dynamics in the CoMiniGut reactors by MiSeq-based 16S rRNA gene amplicon high throughput sequencing showed excellent experimental reproducibility and allowed us to extract significant differences in gut microbial composition after 24 h of fermentation for all investigated substrates and fecal donors. Furthermore, short chain fatty acids (SCFAs) were quantified for all treatments and donors. Fermentations with inulin and lactulose showed that inulin leads to a microbiota dominated by obligate anaerobes, with high relative abundance of Bacteroidetes, while the more easily fermented lactulose leads to higher relative abundance of

CoMiniGut—a small volume in vitro colon model for the screening of gut microbial fermentation processes

Directory of Open Access Journals (Sweden)

Maria Wiese

2018-01-01

Full Text Available Driven by the growing recognition of the influence of the gut microbiota (GM on human health and disease, there is a rapidly increasing interest in understanding how dietary components, pharmaceuticals and pre- and probiotics influence GM. In vitro colon models represent an attractive tool for this purpose. With the dual objective of facilitating the investigation of rare and expensive compounds, as well as an increased throughput, we have developed a prototype in vitro parallel gut microbial fermentation screening tool with a working volume of only 5 ml consisting of five parallel reactor units that can be expanded with multiples of five to increase throughput. This allows e.g., the investigation of interpersonal variations in gut microbial dynamics and the acquisition of larger data sets with enhanced statistical inference. The functionality of the in vitro colon model, Copenhagen MiniGut (CoMiniGut was first demonstrated in experiments with two common prebiotics using the oligosaccharide inulin and the disaccharide lactulose at 1% (w/v. We then investigated fermentation of the scarce and expensive human milk oligosaccharides (HMOs 3-Fucosyllactose, 3-Sialyllactose, 6-Sialyllactose and the more common Fructooligosaccharide in fermentations with infant gut microbial communities. Investigations of microbial community composition dynamics in the CoMiniGut reactors by MiSeq-based 16S rRNA gene amplicon high throughput sequencing showed excellent experimental reproducibility and allowed us to extract significant differences in gut microbial composition after 24 h of fermentation for all investigated substrates and fecal donors. Furthermore, short chain fatty acids (SCFAs were quantified for all treatments and donors. Fermentations with inulin and lactulose showed that inulin leads to a microbiota dominated by obligate anaerobes, with high relative abundance of Bacteroidetes, while the more easily fermented lactulose leads to higher relative

Neural Networks to model the innovativeness perception of co-creative firms

DEFF Research Database (Denmark)

Tanev, Stoyan

2012-01-01

contribution is to make a quantitative analysis in order to assess the relationship between value co-creation and innovation in technology-driven firms: we are using Artificial Neural Network (ANN) to investigate the relationship between value co-creation and innovativeness, and Self Organising Map (SOM) models...

Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks

Directory of Open Access Journals (Sweden)

He Weiming

2010-07-01

Full Text Available Abstract Background Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions. Results Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways. Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods. Conclusions Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

Microbial Insights into Shifting Methane Production Potential in Thawing Permafrost

Science.gov (United States)

Crossen, K.; Wilson, R.; Raab, N.; Neumann, R.; Chanton, J.; Saleska, S. R.; Rich, V. I.

2017-12-01

Permafrost, which stores 50% of global soil carbon, is thawing rapidly due to climate change, and resident microbes are contributing to changing carbon gas emissions. Predictions of the fate of carbon in these regions is poorly constrained; however, improved, careful mapping of microbial community members influencing CO2 and CH4 emissions will help clarify the system response to continued change. In order to more fully understand connections between the microbial communities, major geochemical transformations, and CO2 and CH4 emissions, peat cores were collected from the active layers of three permafrost habitats spanning a thaw gradient (collapsed palsa, bog, and fen) at Stordalen Mire, Abisko, Sweden. Anaerobic incubations of shallow and deep subsamples from these sites were performed, with time-course characterization of the changes in microbial communities, peat geochemistry, and carbon gas production. The latter were profiled with 16S rRNA amplicon sequencing, and targeted metagenomes. The communities within each habitat and depth were statistically distinct, and changed significantly over the course of the incubations. Acidobacteria was consistently the dominant bacterial phylum in all three habitat types. With increased thaw, the relative abundance of Actinobacteria tended to decrease, while Chloroflexi and Bacteroidetes increased with thaw. The relative abundance of methanogens increased with thaw and with depth within each habitat. Over time in the incubations, the richness of the communities tended to decrease. Homoacetogenesis (CO2 + H2 -> CH3COOH) has been documented in other peatlands, and homoacetogens can influence CH4 production by interacting with methanogens, competing with hydrogenotrophs while providing substrate for acetoclasts. Modelling of microbial reaction networks suggests potential for highest homoacetogenesis rates in the collapsed palsa, which also contains the highest relative abundances of lineages taxonomically affiliated with known

Global investigation of composition and interaction networks in gut microbiomes of individuals belonging to diverse geographies and age-groups.

Science.gov (United States)

Yadav, Deepak; Ghosh, Tarini Shankar; Mande, Sharmila S

2016-01-01

Factors like ethnicity, diet and age of an individual have been hypothesized to play a role in determining the makeup of gut microbiome. In order to investigate the gut microbiome structure as well as the inter-microbial associations present therein, we have performed a comprehensive global comparative profiling of the structure (composition, relative heterogeneity and diversity) and the inter-microbial networks in the gut microbiomes of 399 individuals of eight different nationalities. The study identified certain geography-specific trends with respect to composition, intra-group heterogeneity and diversity of the gut microbiomes. Interestingly, the gut microbial association/mutual-exlusion networks were observed to exhibit several cross-geography trends. It was seen that though the composition of gut microbiomes of the American and European individuals were similar, there were distinct patterns in their microbial interaction networks. Amongst European gut-microbiomes, the co-occurrence network obtained for the Danish population was observed to be most dense. Distinct patterns were also observed within Chinese, Japanese and Indian datasets. While performing an age-wise comparison, it was observed that the microbial interactions increased with the age of individuals. Furthermore, certain bacterial groups were identified to be present only in the older age groups. The trends observed in gut microbial networks could be due to the inherent differences in the diet of individuals belonging to different nationalities. For example, the higher number of microbial associations in the Danish population as compared to the Spanish population, may be attributed to the evenly distributed diet of the later. This is in line with previously reported findings which indicate an increase in functional interdependency of microbes in individuals with higher nutritional status. To summarise, the present study identifies geography and age specific patterns in the composition as well as

The Role of Co-occurring Emotions and Personality Traits in Anger Expression

Science.gov (United States)

Mill, Aire; Kööts-Ausmees, Liisi; Allik, Jüri; Realo, Anu

2018-01-01

The main aim of the current study was to examine the role of co-occurring emotions and their interactive effects with the Big Five personality traits in anger expression. Everyday anger expression (“anger-in” and “anger-out” behavior) was studied with the experience-sampling method in a group of 110 participants for 14 consecutive days on 7 random occasions per day. Our results showed that the simultaneously co-occurring emotions that buffer against anger expression are sadness, surprise, disgust, disappointment, and irritation for anger-in behavior, and fear, sadness and disappointment for anger-out reactions. While previous studies have shown that differentiating one's current affect into discrete emotion categories buffers against anger expression (Pond et al., 2012), our study further demonstrated the existence of specific interactive effects between the experience of momentary emotions and personality traits that lead to higher levels of either suppression or expression of anger behavior (or both). For example, the interaction between the trait Openness and co-occurring surprise, in predicting anger-in behavior, indicates that less open people hold their anger back more, and more open people use less anger-in behavior. Co-occurring disgust increases anger-out reactions in people low in Conscientiousness, but decreases anger-out reactions in people high in Conscientiousness. People high in Neuroticism are less likely to engage in anger-in behavior when experiencing disgust, surprise, or irritation alongside anger, but show more anger out in the case of co-occurring contempt. The results of the current study help to further clarify the interactions between the basic personality traits and the experience of momentary co-occurring emotions in determining anger behavior. PMID:29479333

Characterization of chemically induced liver injuries using gene co-expression modules.

Directory of Open Access Journals (Sweden)

Gregory J Tawa

Full Text Available Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1 known biochemical pathways associated with liver injuries and 2 clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20% genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.

Microbial interactions: ecology in a molecular perspective.

Science.gov (United States)

Braga, Raíssa Mesquita; Dourado, Manuella Nóbrega; Araújo, Welington Luiz

2016-12-01

The microorganism-microorganism or microorganism-host interactions are the key strategy to colonize and establish in a variety of different environments. These interactions involve all ecological aspects, including physiochemical changes, metabolite exchange, metabolite conversion, signaling, chemotaxis and genetic exchange resulting in genotype selection. In addition, the establishment in the environment depends on the species diversity, since high functional redundancy in the microbial community increases the competitive ability of the community, decreasing the possibility of an invader to establish in this environment. Therefore, these associations are the result of a co-evolution process that leads to the adaptation and specialization, allowing the occupation of different niches, by reducing biotic and abiotic stress or exchanging growth factors and signaling. Microbial interactions occur by the transference of molecular and genetic information, and many mechanisms can be involved in this exchange, such as secondary metabolites, siderophores, quorum sensing system, biofilm formation, and cellular transduction signaling, among others. The ultimate unit of interaction is the gene expression of each organism in response to an environmental (biotic or abiotic) stimulus, which is responsible for the production of molecules involved in these interactions. Therefore, in the present review, we focused on some molecular mechanisms involved in the microbial interaction, not only in microbial-host interaction, which has been exploited by other reviews, but also in the molecular strategy used by different microorganisms in the environment that can modulate the establishment and structuration of the microbial community. Copyright © 2016 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Degradation of vinasse in soil under different humidity levels: CO sub 2 liberation, microbial biomass formation and immobilization of added nitrogen. Decomposicao de vinhaca em solo sob diferentes niveis de umidade: liberacao de CO sub 2 , formacao de biomassa microbiana e imobilizacao do nitrogenio adicionado

Energy Technology Data Exchange (ETDEWEB)

Minhoni, M T.A. [UNESP, Botucatu, SP (Brazil). Dept. de Defesa Fitossanitaria; Cerri, C C [Centro de Energia Nuclear na Agricultura (CENA), Piracicaba, SP (Brazil)

1987-01-01

Degradation of vinasse added to a sandy Red-Yellow Latosol at the rate of 200m{sup 3}/ha and kept at 40,60 and 80% of the holding capacity (w.h.c.), was studied and compared for liberation of CO{sub 2}, formation of microbial biomass and immobilization of nitrogen added. The CO{sub 2} liberated was evaluated by NaOH retention followed by titration with HCl. The microbial biomass was determined by using gamma radiation as biocide. Nitrogen immobilization was determined using the Kjeldahl method and {sup 15}N enrichment according to Rittemberg's method. Soil moisture, which affected the oxygen level of the soil, had a significant influence in CO{sub 2} liberation, formation of microbial biomassa and nitrogen immobilization. Samples kept under drier conditions (40% w.h.c.) showed initially greater Co{sub 2} liberation. However, at the end of 3 month incubation period, total carbon evolved was similar at all misture levels used, with an average of 3805{mu}g C/g soil. The microbial biomass showed greater formation for the drier samples (40% w.h.c.), reaching a maximum of 519{mu}g C/g soil. Immobilization of the N added showed an increasing initial rate, which was greater with dryness of the soil, followed by stabilization. Nevertheless, at the end of 3 month incubation period, the percentages of immobilization were similar and about 40% of total {sup 15}N irrespective of the soil moisture content. Therefore, the increasing rate of carbon assimilation was not totally acompanied by an increasing immobilization for the N added. The greatest intensity was reached by CO{sub 2} liberation in residue degradation, 2/3 of the carbon having evolved to CO{sub 2} and than 1/3 having been immobilized by the microbial biomass. (author).

Assembling networks of microbial genomes using linear programming.

Science.gov (United States)

Holloway, Catherine; Beiko, Robert G

2010-11-20

Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.