Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks.

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Vipin Narang

Full Text Available Human gene regulatory networks (GRN can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs. Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data accompanying this manuscript.

Towards a predictive theory for genetic regulatory networks

Science.gov (United States)

Tkacik, Gasper

When cells respond to changes in the environment by regulating the expression levels of their genes, we often draw parallels between these biological processes and engineered information processing systems. One can go beyond this qualitative analogy, however, by analyzing information transmission in biochemical ``hardware'' using Shannon's information theory. Here, gene regulation is viewed as a transmission channel operating under restrictive constraints set by the resource costs and intracellular noise. We present a series of results demonstrating that a theory of information transmission in genetic regulatory circuits feasibly yields non-trivial, testable predictions. These predictions concern strategies by which individual gene regulatory elements, e.g., promoters or enhancers, read out their signals; as well as strategies by which small networks of genes, independently or in spatially coupled settings, respond to their inputs. These predictions can be quantitatively compared to the known regulatory networks and their function, and can elucidate how reproducible biological processes, such as embryonic development, can be orchestrated by networks built out of noisy components. Preliminary successes in the gap gene network of the fruit fly Drosophila indicate that a full ab initio theoretical prediction of a regulatory network is possible, a feat that has not yet been achieved for any real regulatory network. We end by describing open challenges on the path towards such a prediction.

A relay network of extracellular heme-binding proteins drives C. albicans iron acquisition from hemoglobin.

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Kuznets, Galit; Vigonsky, Elena; Weissman, Ziva; Lalli, Daniela; Gildor, Tsvia; Kauffman, Sarah J; Turano, Paola; Becker, Jeffrey; Lewinson, Oded; Kornitzer, Daniel

2014-10-01

Iron scavenging constitutes a crucial challenge for survival of pathogenic microorganisms in the iron-poor host environment. Candida albicans, like many microbial pathogens, is able to utilize iron from hemoglobin, the largest iron pool in the host's body. Rbt5 is an extracellular glycosylphosphatidylinositol (GPI)-anchored heme-binding protein of the CFEM family that facilitates heme-iron uptake by an unknown mechanism. Here, we characterize an additional C. albicans CFEM protein gene, PGA7, deletion of which elicits a more severe heme-iron utilization phenotype than deletion of RBT5. The virulence of the pga7-/- mutant is reduced in a mouse model of systemic infection, consistent with a requirement for heme-iron utilization for C. albicans pathogenicity. The Pga7 and Rbt5 proteins exhibit distinct cell wall attachment, and discrete localization within the cell envelope, with Rbt5 being more exposed than Pga7. Both proteins are shown here to efficiently extract heme from hemoglobin. Surprisingly, while Pga7 has a higher affinity for heme in vitro, we find that heme transfer can occur bi-directionally between Pga7 and Rbt5, supporting a model in which they cooperate in a heme-acquisition relay. Together, our data delineate the roles of Pga7 and Rbt5 in a cell surface protein network that transfers heme from extracellular hemoglobin to the endocytic pathway, and provide a paradigm for how receptors embedded in the cell wall matrix can mediate nutrient uptake across the fungal cell envelope.

Network perturbation by recurrent regulatory variants in cancer.

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Kiwon Jang

2017-03-01

Full Text Available Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes.

Regulatory Office for Network Industries

International Nuclear Information System (INIS)

2005-01-01

The main goal of the economic regulation of network industries is to ensure a balance between the interests of consumers and investors and to encourage providing high-quality goods and services. The task of the regulatory authority is to protect the interests of consumers against monopolistic behaviour of regulated enterprises. At the same time, the regulatory office has to protect the interests of investors by giving them an opportunity to achieve an adequate return on their investments. And last, but not least, the regulatory office has to provide regulated enterprises with appropriate incentives to make them function in an efficient and effective manner and to guarantee the security of delivery of energies and related services. All this creates an efficient regulatory framework that is capable of attracting the required amount and type of investments. This also means providing third party access to the grids, the opening of energy markets, the un-bundling of accounts according to production, distribution, transmission and other activities and the establishment of a transparent and stable legislative environment for regulated companies, investors and consumers. Otherwise, in the long run consumers may suffer from a serious deterioration of service quality, although in the short run they are protected against increased prices. Under the Act No. 276/2001 Coll. on Regulation of Network Industries and on amendment of some acts the Office for Regulation of Network Industries has been commissioned to implement the main objectives of regulation of network industries. By network industries the Act No. 276/2001 Coll. on Regulation means the following areas: (a) Production, purchase, transit and distribution of electricity; (b) Production, purchase, transit and distribution of gas; (c) Production, purchase and distribution of heat; (d) Water management activities relating to the operation of the public water supply system or the public sewerage system; (e) Water management

A High-Level Petri Net Framework for Genetic Regulatory Networks

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Banks Richard

2007-12-01

Full Text Available To understand the function of genetic regulatory networks in the development of cellular systems, we must not only realise the individual network entities, but also the manner by which they interact. Multi-valued networks are a promising qualitative approach for modelling such genetic regulatory networks, however, at present they have limited formal analysis techniques and tools. We present a flexible formal framework for modelling and analysing multi-valued genetic regulatory networks using high-level Petri nets and logic minimization techniques. We demonstrate our approach with a detailed case study in which part of the genetic regulatory network responsible for the carbon starvation stress response in Escherichia coli is modelled and analysed. We then compare and contrast this multivalued model to a corresponding Boolean model and consider their formal relationship.

Harnessing diversity towards the reconstructing of large scale gene regulatory networks.

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Takeshi Hase

Full Text Available Elucidating gene regulatory network (GRN from large scale experimental data remains a central challenge in systems biology. Recently, numerous techniques, particularly consensus driven approaches combining different algorithms, have become a potentially promising strategy to infer accurate GRNs. Here, we develop a novel consensus inference algorithm, TopkNet that can integrate multiple algorithms to infer GRNs. Comprehensive performance benchmarking on a cloud computing framework demonstrated that (i a simple strategy to combine many algorithms does not always lead to performance improvement compared to the cost of consensus and (ii TopkNet integrating only high-performance algorithms provide significant performance improvement compared to the best individual algorithms and community prediction. These results suggest that a priori determination of high-performance algorithms is a key to reconstruct an unknown regulatory network. Similarity among gene-expression datasets can be useful to determine potential optimal algorithms for reconstruction of unknown regulatory networks, i.e., if expression-data associated with known regulatory network is similar to that with unknown regulatory network, optimal algorithms determined for the known regulatory network can be repurposed to infer the unknown regulatory network. Based on this observation, we developed a quantitative measure of similarity among gene-expression datasets and demonstrated that, if similarity between the two expression datasets is high, TopkNet integrating algorithms that are optimal for known dataset perform well on the unknown dataset. The consensus framework, TopkNet, together with the similarity measure proposed in this study provides a powerful strategy towards harnessing the wisdom of the crowds in reconstruction of unknown regulatory networks.

Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network.

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Kordmahalleh, Mina Moradi; Sefidmazgi, Mohammad Gorji; Harrison, Scott H; Homaifar, Abdollah

2017-01-01

The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design. Interactions in gene regulatory networks (GRNs) include effects of transcription factors, repressors, small metabolites, and microRNA species. In addition, the effects of regulatory interactions are not always simultaneous, but can occur after a finite time delay, or as a combined outcome of simultaneous and time delayed interactions. Powerful biotechnologies have been rapidly and successfully measuring levels of genetic expression to illuminate different states of biological systems. This has led to an ensuing challenge to improve the identification of specific regulatory mechanisms through regulatory network reconstructions. Solutions to this challenge will ultimately help to spur forward efforts based on the usage of regulatory network reconstructions in systems biology applications. We have developed a hierarchical recurrent neural network (HRNN) that identifies time-delayed gene interactions using time-course data. A customized genetic algorithm (GA) was used to optimize hierarchical connectivity of regulatory genes and a target gene. The proposed design provides a non-fully connected network with the flexibility of using recurrent connections inside the network. These features and the non-linearity of the HRNN facilitate the process of identifying temporal patterns of a GRN. Our HRNN method was implemented with the Python language. It was first evaluated on simulated data representing linear and nonlinear time-delayed gene-gene interaction models across a range of network sizes and variances of noise. We then further demonstrated the capability of our method in reconstructing GRNs of the Saccharomyces cerevisiae synthetic network for in vivo benchmarking of reverse-engineering and modeling approaches (IRMA). We compared the performance of our method to TD-ARACNE, HCC-CLINDE, TSNI and ebdbNet across different network

Inference of cancer-specific gene regulatory networks using soft computing rules.

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Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

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Cicin-Sain, Damjan; Ashyraliyev, Maksat; Jaeger, Johannes

2012-01-01

Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to

Take it of leave it : Mechanisms underlying bacterial bistable regulatory networks

NARCIS (Netherlands)

Siebring, Jeroen; Sorg, Robin; Herber, Martijn; Kuipers, Oscar; Filloux, Alain A.M.

2012-01-01

Bistable switches occur in regulatory networks that can exist in two distinct stable states. Such networks allow distinct switching of individual cells. In bacteria these switches coexist with regulatory networks that respond gradually to environmental input. Bistable switches play key roles in high

4th IEA International CCS Regulatory Network Meeting

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-07-01

On 9 and 10 May 2012, the IEA International CCS Regulatory Network (Network), launched in Paris in May 2008 to provide a neutral forum for CCS regulators, policy makers and stakeholders to share updates and views on CCS regulatory developments, held its fourth meeting at the International Energy Agency (IEA) offices in Paris, France. The aim of the meeting was to: provide an update on government efforts to develop and implement carbon capture and storage (CCS) legal and regulatory frameworks; and consider ways in which governments are dealing with some of the more difficult or complex aspects of CCS regulation. This report summarises the proceedings of the meeting.

The impact of measurement errors in the identification of regulatory networks

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Sato João R

2009-12-01

Full Text Available Abstract Background There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent and non-time series (independent data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models and dependent (autoregressive models data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error. The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Sequence-based model of gap gene regulatory network.

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Kozlov, Konstantin; Gursky, Vitaly; Kulakovskiy, Ivan; Samsonova, Maria

2014-01-01

The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. We developed a new model that provides a dynamical description of gap gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces gap gene expression patterns in wild type embryos and is able to predict gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the gap gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded. The reconstructed topology of the gap gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3

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

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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.

Robust and global delay-dependent stability for genetic regulatory networks with parameter uncertainties.

Science.gov (United States)

Tian, Li-Ping; Wang, Jianxin; Wu, Fang-Xiang

2012-09-01

The study of stability is essential for designing or controlling genetic regulatory networks, which can be described by nonlinear differential equations with time delays. Much attention has been paid to the study of delay-independent stability of genetic regulatory networks and as a result, many sufficient conditions have been derived for delay-independent stability. Although it might be more interesting in practice, delay-dependent stability of genetic regulatory networks has been studied insufficiently. Based on the linear matrix inequality (LMI) approach, in this study we will present some delay-dependent stability conditions for genetic regulatory networks. Then we extend these results to genetic regulatory networks with parameter uncertainties. To illustrate the effectiveness of our theoretical results, gene repressilatory networks are analyzed .

Integration of Bacterial Small RNAs in Regulatory Networks.

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Nitzan, Mor; Rehani, Rotem; Margalit, Hanah

2017-05-22

Small RNAs (sRNAs) are central regulators of gene expression in bacteria, controlling target genes posttranscriptionally by base pairing with their mRNAs. sRNAs are involved in many cellular processes and have unique regulatory characteristics. In this review, we discuss the properties of regulation by sRNAs and how it differs from and combines with transcriptional regulation. We describe the global characteristics of the sRNA-target networks in bacteria using graph-theoretic approaches and review the local integration of sRNAs in mixed regulatory circuits, including feed-forward loops and their combinations, feedback loops, and circuits made of an sRNA and another regulator, both derived from the same transcript. Finally, we discuss the competition effects in posttranscriptional regulatory networks that may arise over shared targets, shared regulators, and shared resources and how they may lead to signal propagation across the network.

Candida/Candida biofilms. First description of dual-species Candida albicans/C. rugosa biofilm.

Science.gov (United States)

Martins, Carlos Henrique Gomes; Pires, Regina Helena; Cunha, Aline Oliveira; Pereira, Cristiane Aparecida Martins; Singulani, Junya de Lacorte; Abrão, Fariza; Moraes, Thais de; Mendes-Giannini, Maria José Soares

2016-04-01

Denture liners have physical properties that favour plaque accumulation and colonization by Candida species, irritating oral tissues and causing denture stomatitis. To isolate and determine the incidence of oral Candida species in dental prostheses, oral swabs were collected from the dental prostheses of 66 patients. All the strains were screened for their ability to form biofilms; both monospecies and dual-species combinations were tested. Candida albicans (63 %) was the most frequently isolated microorganism; Candida tropicalis (14 %), Candida glabrata (13 %), Candida rugosa (5 %), Candida parapsilosis (3 %), and Candida krusei (2 %) were also detected. The XTT assay showed that C. albicans SC5314 possessed a biofilm-forming ability significantly higher (p biofilm was less than the total CFU of a monospecies C. albicans biofilm. In contrast to the profuse hyphae verified in monospecies C. albicans biofilms, micrographies showed that the C. albicans/non-albicans Candida biofilms consisted of sparse yeast forms and profuse budding yeast cells that generated a network. These results suggested that C. albicans and the tested Candida species could co-exist in biofilms displaying apparent antagonism. The study provide the first description of C. albicans/C. rugosa mixed biofilm. Copyright © 2016 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviours

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Daria eMolodtsova

2014-12-01

Full Text Available It is increasingly apparent that genes and networks that influence complex behaviour are evolutionary conserved, which is paradoxical considering that behaviour is labile over evolutionary timescales. How does adaptive change in behaviour arise if behaviour is controlled by conserved, pleiotropic, and likely evolutionary constrained genes? Pleiotropy and connectedness are known to constrain the general rate of protein evolution, prompting some to suggest that the evolution of complex traits, including behaviour, is fuelled by regulatory sequence evolution. However, we seldom have data on the strength of selection on mutations in coding and regulatory sequences, and this hinders our ability to study how pleiotropy influences coding and regulatory sequence evolution. Here we use population genomics to estimate the strength of selection on coding and regulatory mutations for a transcriptional regulatory network that influences complex behaviour of honey bees. We found that replacement mutations in highly connected transcription factors and target genes experience significantly stronger negative selection relative to weakly connected transcription factors and targets. Adaptively evolving proteins were significantly more likely to reside at the periphery of the regulatory network, while proteins with signs of negative selection were near the core of the network. Interestingly, connectedness and network structure had minimal influence on the strength of selection on putative regulatory sequences for both transcription factors and their targets. Our study indicates that adaptive evolution of complex behaviour can arise because of positive selection on protein-coding mutations in peripheral genes, and on regulatory sequence mutations in both transcription factors and their targets throughout the network.

Inference of Cancer-specific Gene Regulatory Networks Using Soft Computing Rules

Directory of Open Access Journals (Sweden)

Xiaosheng Wang

2010-03-01

Full Text Available Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

The transcriptional regulatory network of Mycobacterium tuberculosis.

Directory of Open Access Journals (Sweden)

Joaquín Sanz

Full Text Available Under the perspectives of network science and systems biology, the characterization of transcriptional regulatory (TR networks beyond the context of model organisms offers a versatile tool whose potential remains yet mainly unexplored. In this work, we present an updated version of the TR network of Mycobacterium tuberculosis (M.tb, which incorporates newly characterized transcriptional regulations coming from 31 recent, different experimental works available in the literature. As a result of the incorporation of these data, the new network doubles the size of previous data collections, incorporating more than a third of the entire genome of the bacterium. We also present an exhaustive topological analysis of the new assembled network, focusing on the statistical characterization of motifs significances and the comparison with other model organisms. The expanded M.tb transcriptional regulatory network, considering its volume and completeness, constitutes an important resource for diverse tasks such as dynamic modeling of gene expression and signaling processes, computational reliability determination or protein function prediction, being the latter of particular relevance, given that the function of only a small percent of the proteins of M.tb is known.

Beyond Candida albicans: Mechanisms of immunity to non-albicans Candida species

Science.gov (United States)

Whibley, Natasha; Gaffen, Sarah L.

2015-01-01

The fungal genus Candida encompasses numerous species that inhabit a variety of hosts, either as commensal microbes and/or pathogens. Candida species are a major cause of fungal infections, yet to date there are no vaccines against Candida or indeed any other fungal pathogen. Our knowledge of immunity to Candida mainly comes from studies on C. albicans, the most frequent species associated with disease. However, non-albicans Candida (NAC) species also cause disease and their prevalence is increasing. Although research into immunity to NAC species is still at an early stage, it is becoming apparent that immunity to C. albicans differs in important ways from non-albicans species, with important implications for treatment, therapy and predicted demographic susceptibility. This review will discuss the current understanding of immunity to NAC species in the context of immunity to C. albicans, and highlight as-yet unanswered questions. PMID:26276374

Genomic analysis of the hierarchical structure of regulatory networks

Science.gov (United States)

Yu, Haiyuan; Gerstein, Mark

2006-01-01

A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

Learning gene regulatory networks from only positive and unlabeled data

Directory of Open Access Journals (Sweden)

Elkan Charles

2010-05-01

Full Text Available Abstract Background Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled as a binary classification problem for each pair of genes. A statistical classifier is trained to recognize the relationships between the activation profiles of gene pairs. This approach has been proven to outperform previous unsupervised methods. However, the supervised approach raises open questions. In particular, although known regulatory connections can safely be assumed to be positive training examples, obtaining negative examples is not straightforward, because definite knowledge is typically not available that a given pair of genes do not interact. Results A recent advance in research on data mining is a method capable of learning a classifier from only positive and unlabeled examples, that does not need labeled negative examples. Applied to the reconstruction of gene regulatory networks, we show that this method significantly outperforms the current state of the art of machine learning methods. We assess the new method using both simulated and experimental data, and obtain major performance improvement. Conclusions Compared to unsupervised methods for gene network inference, supervised methods are potentially more accurate, but for training they need a complete set of known regulatory connections. A supervised method that can be trained using only positive and unlabeled data, as presented in this paper, is especially beneficial for the task of inferring gene regulatory networks, because only an incomplete set of known regulatory connections is available in public databases such as RegulonDB, TRRD, KEGG, Transfac, and IPA.

Synthetic tetracycline-inducible regulatory networks: computer-aided design of dynamic phenotypes

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Kaznessis Yiannis N

2007-01-01

Full Text Available Abstract Background Tightly regulated gene networks, precisely controlling the expression of protein molecules, have received considerable interest by the biomedical community due to their promising applications. Among the most well studied inducible transcription systems are the tetracycline regulatory expression systems based on the tetracycline resistance operon of Escherichia coli, Tet-Off (tTA and Tet-On (rtTA. Despite their initial success and improved designs, limitations still persist, such as low inducer sensitivity. Instead of looking at these networks statically, and simply changing or mutating the promoter and operator regions with trial and error, a systematic investigation of the dynamic behavior of the network can result in rational design of regulatory gene expression systems. Sophisticated algorithms can accurately capture the dynamical behavior of gene networks. With computer aided design, we aim to improve the synthesis of regulatory networks and propose new designs that enable tighter control of expression. Results In this paper we engineer novel networks by recombining existing genes or part of genes. We synthesize four novel regulatory networks based on the Tet-Off and Tet-On systems. We model all the known individual biomolecular interactions involved in transcription, translation, regulation and induction. With multiple time-scale stochastic-discrete and stochastic-continuous models we accurately capture the transient and steady state dynamics of these networks. Important biomolecular interactions are identified and the strength of the interactions engineered to satisfy design criteria. A set of clear design rules is developed and appropriate mutants of regulatory proteins and operator sites are proposed. Conclusion The complexity of biomolecular interactions is accurately captured through computer simulations. Computer simulations allow us to look into the molecular level, portray the dynamic behavior of gene regulatory

The capacity for multistability in small gene regulatory networks

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Grotewold Erich

2009-09-01

Full Text Available Abstract Background Recent years have seen a dramatic increase in the use of mathematical modeling to gain insight into gene regulatory network behavior across many different organisms. In particular, there has been considerable interest in using mathematical tools to understand how multistable regulatory networks may contribute to developmental processes such as cell fate determination. Indeed, such a network may subserve the formation of unicellular leaf hairs (trichomes in the model plant Arabidopsis thaliana. Results In order to investigate the capacity of small gene regulatory networks to generate multiple equilibria, we present a chemical reaction network (CRN-based modeling formalism and describe a number of methods for CRN analysis in a parameter-free context. These methods are compared and applied to a full set of one-component subnetworks, as well as a large random sample from 40,680 similarly constructed two-component subnetworks. We find that positive feedback and cooperativity mediated by transcription factor (TF dimerization is a requirement for one-component subnetwork bistability. For subnetworks with two components, the presence of these processes increases the probability that a randomly sampled subnetwork will exhibit multiple equilibria, although we find several examples of bistable two-component subnetworks that do not involve cooperative TF-promoter binding. In the specific case of epidermal differentiation in Arabidopsis, dimerization of the GL3-GL1 complex and cooperative sequential binding of GL3-GL1 to the CPC promoter are each independently sufficient for bistability. Conclusion Computational methods utilizing CRN-specific theorems to rule out bistability in small gene regulatory networks are far superior to techniques generally applicable to deterministic ODE systems. Using these methods to conduct an unbiased survey of parameter-free deterministic models of small networks, and the Arabidopsis epidermal cell

Empirical Bayes conditional independence graphs for regulatory network recovery

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Mahdi, Rami; Madduri, Abishek S.; Wang, Guoqing; Strulovici-Barel, Yael; Salit, Jacqueline; Hackett, Neil R.; Crystal, Ronald G.; Mezey, Jason G.

2012-01-01

Motivation: Computational inference methods that make use of graphical models to extract regulatory networks from gene expression data can have difficulty reconstructing dense regions of a network, a consequence of both computational complexity and unreliable parameter estimation when sample size is small. As a result, identification of hub genes is of special difficulty for these methods. Methods: We present a new algorithm, Empirical Light Mutual Min (ELMM), for large network reconstruction that has properties well suited for recovery of graphs with high-degree nodes. ELMM reconstructs the undirected graph of a regulatory network using empirical Bayes conditional independence testing with a heuristic relaxation of independence constraints in dense areas of the graph. This relaxation allows only one gene of a pair with a putative relation to be aware of the network connection, an approach that is aimed at easing multiple testing problems associated with recovering densely connected structures. Results: Using in silico data, we show that ELMM has better performance than commonly used network inference algorithms including GeneNet, ARACNE, FOCI, GENIE3 and GLASSO. We also apply ELMM to reconstruct a network among 5492 genes expressed in human lung airway epithelium of healthy non-smokers, healthy smokers and individuals with chronic obstructive pulmonary disease assayed using microarrays. The analysis identifies dense sub-networks that are consistent with known regulatory relationships in the lung airway and also suggests novel hub regulatory relationships among a number of genes that play roles in oxidative stress and secretion. Availability and implementation: Software for running ELMM is made available at http://mezeylab.cb.bscb.cornell.edu/Software.aspx. Contact: ramimahdi@yahoo.com or jgm45@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22685074

Inference of Transcription Regulatory Network in Low Phytic Acid Soybean Seeds

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Neelam Redekar

2017-11-01

Full Text Available A dominant loss of function mutation in myo-inositol phosphate synthase (MIPS gene and recessive loss of function mutations in two multidrug resistant protein type-ABC transporter genes not only reduce the seed phytic acid levels in soybean, but also affect the pathways associated with seed development, ultimately resulting in low emergence. To understand the regulatory mechanisms and identify key genes that intervene in the seed development process in low phytic acid crops, we performed computational inference of gene regulatory networks in low and normal phytic acid soybeans using a time course transcriptomic data and multiple network inference algorithms. We identified a set of putative candidate transcription factors and their regulatory interactions with genes that have functions in myo-inositol biosynthesis, auxin-ABA signaling, and seed dormancy. We evaluated the performance of our unsupervised network inference method by comparing the predicted regulatory network with published regulatory interactions in Arabidopsis. Some contrasting regulatory interactions were observed in low phytic acid mutants compared to non-mutant lines. These findings provide important hypotheses on expression regulation of myo-inositol metabolism and phytohormone signaling in developing low phytic acid soybeans. The computational pipeline used for unsupervised network learning in this study is provided as open source software and is freely available at https://lilabatvt.github.io/LPANetwork/.

A parallel attractor-finding algorithm based on Boolean satisfiability for genetic regulatory networks.

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Wensheng Guo

Full Text Available In biological systems, the dynamic analysis method has gained increasing attention in the past decade. The Boolean network is the most common model of a genetic regulatory network. The interactions of activation and inhibition in the genetic regulatory network are modeled as a set of functions of the Boolean network, while the state transitions in the Boolean network reflect the dynamic property of a genetic regulatory network. A difficult problem for state transition analysis is the finding of attractors. In this paper, we modeled the genetic regulatory network as a Boolean network and proposed a solving algorithm to tackle the attractor finding problem. In the proposed algorithm, we partitioned the Boolean network into several blocks consisting of the strongly connected components according to their gradients, and defined the connection between blocks as decision node. Based on the solutions calculated on the decision nodes and using a satisfiability solving algorithm, we identified the attractors in the state transition graph of each block. The proposed algorithm is benchmarked on a variety of genetic regulatory networks. Compared with existing algorithms, it achieved similar performance on small test cases, and outperformed it on larger and more complex ones, which happens to be the trend of the modern genetic regulatory network. Furthermore, while the existing satisfiability-based algorithms cannot be parallelized due to their inherent algorithm design, the proposed algorithm exhibits a good scalability on parallel computing architectures.

The Reconstruction and Analysis of Gene Regulatory Networks.

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Zheng, Guangyong; Huang, Tao

2018-01-01

In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks.

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Guo, Liyuan; Wang, Jing

2018-01-04

Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element-target gene pairs (E-G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother

OpenAIRE

Khan, Jehandad; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

2014-01-01

It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inf...

Controllability analysis of transcriptional regulatory networks reveals circular control patterns among transcription factors

DEFF Research Database (Denmark)

Österlund, Tobias; Bordel, Sergio; Nielsen, Jens

2015-01-01

% for the human network. The high controllability (low number of drivers needed to control the system) in yeast, mouse and human is due to the presence of internal loops in their regulatory networks where the TFs regulate each other in a circular fashion. We refer to these internal loops as circular control...... motifs (CCM). The E. coli transcriptional regulatory network, which does not have any CCMs, shows a hierarchical structure of the transcriptional regulatory network in contrast to the eukaryal networks. The presence of CCMs also has influence on the stability of these networks, as the presence of cycles...

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

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Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

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Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A; Kellis, Manolis

2012-07-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein-protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level.

Gene regulatory and signaling networks exhibit distinct topological distributions of motifs

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Ferreira, Gustavo Rodrigues; Nakaya, Helder Imoto; Costa, Luciano da Fontoura

2018-04-01

The biological processes of cellular decision making and differentiation involve a plethora of signaling pathways and gene regulatory circuits. These networks in turn exhibit a multitude of motifs playing crucial parts in regulating network activity. Here we compare the topological placement of motifs in gene regulatory and signaling networks and observe that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.

Robustness and accuracy in sea urchin developmental gene regulatory networks

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Smadar eBen-Tabou De-Leon

2016-02-01

Full Text Available Developmental gene regulatory networks robustly control the timely activation of regulatory and differentiation genes. The structure of these networks underlies their capacity to buffer intrinsic and extrinsic noise and maintain embryonic morphology. Here I illustrate how the use of specific architectures by the sea urchin developmental regulatory networks enables the robust control of cell fate decisions. The Wnt-βcatenin signaling pathway patterns the primary embryonic axis while the BMP signaling pathway patterns the secondary embryonic axis in the sea urchin embryo and across bilateria. Interestingly, in the sea urchin in both cases, the signaling pathway that defines the axis controls directly the expression of a set of downstream regulatory genes. I propose that this direct activation of a set of regulatory genes enables a uniform regulatory response and a clear cut cell fate decision in the endoderm and in the dorsal ectoderm. The specification of the mesodermal pigment cell lineage is activated by Delta signaling that initiates a triple positive feedback loop that locks down the pigment specification state. I propose that the use of compound positive feedback circuitry provides the endodermal cells enough time to turn off mesodermal genes and ensures correct mesoderm vs. endoderm fate decision. Thus, I argue that understanding the control properties of repeatedly used regulatory architectures illuminates their role in embryogenesis and provides possible explanations to their resistance to evolutionary change.

Splitting Strategy for Simulating Genetic Regulatory Networks

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Xiong You

2014-01-01

Full Text Available The splitting approach is developed for the numerical simulation of genetic regulatory networks with a stable steady-state structure. The numerical results of the simulation of a one-gene network, a two-gene network, and a p53-mdm2 network show that the new splitting methods constructed in this paper are remarkably more effective and more suitable for long-term computation with large steps than the traditional general-purpose Runge-Kutta methods. The new methods have no restriction on the choice of stepsize due to their infinitely large stability regions.

A Regulatory Network Analysis of Orphan Genes in Arabidopsis Thaliana

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Singh, Pramesh; Chen, Tianlong; Arendsee, Zebulun; Wurtele, Eve S.; Bassler, Kevin E.

Orphan genes, which are genes unique to each particular species, have recently drawn significant attention for their potential usefulness for organismal robustness. Their origin and regulatory interaction patterns remain largely undiscovered. Recently, methods that use the context likelihood of relatedness to infer a network followed by modularity maximizing community detection algorithms on the inferred network to find the functional structure of regulatory networks were shown to be effective. We apply improved versions of these methods to gene expression data from Arabidopsis thaliana, identify groups (clusters) of interacting genes with related patterns of expression and analyze the structure within those groups. Focusing on clusters that contain orphan genes, we compare the identified clusters to gene ontology (GO) terms, regulons, and pathway designations and analyze their hierarchical structure. We predict new regulatory interactions and unravel the structure of the regulatory interaction patterns of orphan genes. Work supported by the NSF through Grants DMR-1507371 and IOS-1546858.

Yeast casein kinase 2 governs morphology, biofilm formation, cell wall integrity, and host cell damage of Candida albicans.

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Jung, Sook-In; Rodriguez, Natalie; Irrizary, Jihyun; Liboro, Karl; Bogarin, Thania; Macias, Marlene; Eivers, Edward; Porter, Edith; Filler, Scott G; Park, Hyunsook

2017-01-01

The regulatory networks governing morphogenesis of a pleomorphic fungus, Candida albicans are extremely complex and remain to be completely elucidated. This study investigated the function of C. albicans yeast casein kinase 2 (CaYck2p). The yck2Δ/yck2Δ strain displayed constitutive pseudohyphae in both yeast and hyphal growth conditions, and formed enhanced biofilm under non-biofilm inducing condition. This finding was further supported by gene expression analysis of the yck2Δ/yck2Δ strain which showed significant upregulation of UME6, a key transcriptional regulator of hyphal transition and biofilm formation, and cell wall protein genes ALS3, HWP1, and SUN41, all of which are associated with morphogenesis and biofilm architecture. The yck2Δ/yck2Δ strain was hypersensitive to cell wall damaging agents and had increased compensatory chitin deposition in the cell wall accompanied by an upregulation of the expression of the chitin synthase genes, CHS2, CHS3, and CHS8. Absence of CaYck2p also affected fungal-host interaction; the yck2Δ/yck2Δ strain had significantly reduced ability to damage host cells. However, the yck2Δ/yck2Δ strain had wild-type susceptibility to cyclosporine and FK506, suggesting that CaYck2p functions independently from the Ca+/calcineurin pathway. Thus, in C. albicans, Yck2p is a multifunctional kinase that governs morphogenesis, biofilm formation, cell wall integrity, and host cell interactions.

Fused Regression for Multi-source Gene Regulatory Network Inference.

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Kari Y Lam

2016-12-01

Full Text Available Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. This approach improves network inference performance even when orthology mapping and conservation are incomplete. We refine this method by presenting an algorithm that extracts the true conserved subnetwork from a larger set of potentially conserved interactions and demonstrate the utility of our method in cross species network inference. Last, we demonstrate our method's utility in learning from data collected on different experimental platforms.

Iterative reconstruction of transcriptional regulatory networks: an algorithmic approach.

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Christian L Barrett

2006-05-01

Full Text Available The number of complete, publicly available genome sequences is now greater than 200, and this number is expected to rapidly grow in the near future as metagenomic and environmental sequencing efforts escalate and the cost of sequencing drops. In order to make use of this data for understanding particular organisms and for discerning general principles about how organisms function, it will be necessary to reconstruct their various biochemical reaction networks. Principal among these will be transcriptional regulatory networks. Given the physical and logical complexity of these networks, the various sources of (often noisy data that can be utilized for their elucidation, the monetary costs involved, and the huge number of potential experiments approximately 10(12 that can be performed, experiment design algorithms will be necessary for synthesizing the various computational and experimental data to maximize the efficiency of regulatory network reconstruction. This paper presents an algorithm for experimental design to systematically and efficiently reconstruct transcriptional regulatory networks. It is meant to be applied iteratively in conjunction with an experimental laboratory component. The algorithm is presented here in the context of reconstructing transcriptional regulation for metabolism in Escherichia coli, and, through a retrospective analysis with previously performed experiments, we show that the produced experiment designs conform to how a human would design experiments. The algorithm is able to utilize probability estimates based on a wide range of computational and experimental sources to suggest experiments with the highest potential of discovering the greatest amount of new regulatory knowledge.

Comparative Evolution of Morphological Regulatory Functions in Candida Species

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Lackey, Erika; Vipulanandan, Geethanjali; Childers, Delma S.

2013-01-01

Morphological transitions play an important role in virulence and virulence-related processes in a wide variety of pathogenic fungi, including the most commonly isolated human fungal pathogen Candida albicans. While environmental signals, transcriptional regulators, and target genes associated with C. albicans morphogenesis are well-characterized, considerably little is known about morphological regulatory mechanisms and the extent to which they are evolutionarily conserved in less pathogenic and less filamentous non-albicans Candida species (NACS). We have identified specific optimal filament-inducing conditions for three NACS (C. tropicalis, C. parapsilosis, and C. guilliermondii), which are very limited, suggesting that these species may be adapted for niche-specific filamentation in the host. Only a subset of evolutionarily conserved C. albicans filament-specific target genes were induced upon filamentation in C. tropicalis, C. parapsilosis, and C. guilliermondii. One of the genes showing conserved expression was UME6, a key filament-specific regulator of C. albicans hyphal development. Constitutive high-level expression of UME6 was sufficient to drive increased filamentation as well as biofilm formation and partly restore conserved filament-specific gene expression in both C. tropicalis and C. parapsilosis, suggesting that evolutionary differences in filamentation ability among pathogenic Candida species may be partially attributed to alterations in the expression level of a conserved filamentous growth machinery. In contrast to UME6, NRG1, an important repressor of C. albicans filamentation, showed only a partly conserved role in controlling NACS filamentation. Overall, our results suggest that C. albicans morphological regulatory functions are partially conserved in NACS and have evolved to respond to more specific sets of host environmental cues. PMID:23913541

Learning a Markov Logic network for supervised gene regulatory network inference.

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Brouard, Céline; Vrain, Christel; Dubois, Julie; Castel, David; Debily, Marie-Anne; d'Alché-Buc, Florence

2013-09-12

Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate "regulates", starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black-box model such as a

A gene regulatory network armature for T-lymphocyte specification

Energy Technology Data Exchange (ETDEWEB)

Fung, Elizabeth-sharon [Los Alamos National Laboratory

2008-01-01

Choice of a T-lymphoid fate by hematopoietic progenitor cells depends on sustained Notch-Delta signaling combined with tightly-regulated activities of multiple transcription factors. To dissect the regulatory network connections that mediate this process, we have used high-resolution analysis of regulatory gene expression trajectories from the beginning to the end of specification; tests of the short-term Notchdependence of these gene expression changes; and perturbation analyses of the effects of overexpression of two essential transcription factors, namely PU.l and GATA-3. Quantitative expression measurements of >50 transcription factor and marker genes have been used to derive the principal components of regulatory change through which T-cell precursors progress from primitive multipotency to T-lineage commitment. Distinct parts of the path reveal separate contributions of Notch signaling, GATA-3 activity, and downregulation of PU.l. Using BioTapestry, the results have been assembled into a draft gene regulatory network for the specification of T-cell precursors and the choice of T as opposed to myeloid dendritic or mast-cell fates. This network also accommodates effects of E proteins and mutual repression circuits of Gfil against Egr-2 and of TCF-l against PU.l as proposed elsewhere, but requires additional functions that remain unidentified. Distinctive features of this network structure include the intense dose-dependence of GATA-3 effects; the gene-specific modulation of PU.l activity based on Notch activity; the lack of direct opposition between PU.l and GATA-3; and the need for a distinct, late-acting repressive function or functions to extinguish stem and progenitor-derived regulatory gene expression.

Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

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Liang Jinghang

2012-08-01

Full Text Available Abstract Background Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs. As a logical model, probabilistic Boolean networks (PBNs consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n or O(nN2n for a sparse matrix. Results This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN. An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n, where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a

Lactobacillus rhamnosus inhibits Candida albicans virulence factors in vitro and modulates immune system in Galleria mellonella.

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Ribeiro, F C; de Barros, P P; Rossoni, R D; Junqueira, J C; Jorge, A O C

2017-01-01

The aim of this study was to evaluate the potential anti-Candida effects of Lactobacillus rhamnosus ATCC 9595 on Candida albicans ATCC 18804 using in vitro and in vivo models. The in vitro analysis evaluated the effects of L. rhamnosus on C. albicans's biofilm formation by CFU count and metabolic activity, filamentation capacity, and adhesion (ALS3 and HWP1) and transcriptional regulatory gene (BCR1 and CPH1) expression. The in vitro results showed that both the L. rhamnosus cells and supernatant reduced C. albicans biofilm formation, filamentation and gene expression. In the in vivo study, the treatment with L. rhamnosus supernatant increased 80% the survival of Galleria mellonella larvae infected with C. albicans. Furthermore, the supernatant of L. rhamnosus recruited haemocytes into the haemolymph (2·1-fold increase). Lactobacillus rhamnosus reduced the biofilm formation and filamentation of C. albicans in vitro by negatively regulating all studied C. albicans genes. Lactobacillus rhamnosus protected G. mellonella against experimental candidiasis in vivo. This study is the first study to report the anti-Candida properties of L. rhamnosus ATCC 9595. The supernatant of this strain has immunomodulatory effects on the G. mellonella model and protects the larvae against pathogens. © 2016 The Society for Applied Microbiology.

Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

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Masanao Sato

Full Text Available Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2. This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i the components of the network are highly interconnected; and (ii negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector

Exploring the miRNA regulatory network using evolutionary correlations.

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Benedikt Obermayer

2014-10-01

Full Text Available Post-transcriptional regulation by miRNAs is a widespread and highly conserved phenomenon in metazoans, with several hundreds to thousands of conserved binding sites for each miRNA, and up to two thirds of all genes under miRNA regulation. At the same time, the effect of miRNA regulation on mRNA and protein levels is usually quite modest and associated phenotypes are often weak or subtle. This has given rise to the notion that the highly interconnected miRNA regulatory network exerts its function less through any individual link and more via collective effects that lead to a functional interdependence of network links. We present a Bayesian framework to quantify conservation of miRNA target sites using vertebrate whole-genome alignments. The increased statistical power of our phylogenetic model allows detection of evolutionary correlation in the conservation patterns of site pairs. Such correlations could result from collective functions in the regulatory network. For instance, co-conservation of target site pairs supports a selective benefit of combinatorial regulation by multiple miRNAs. We find that some miRNA families are under pronounced co-targeting constraints, indicating a high connectivity in the regulatory network, while others appear to function in a more isolated way. By analyzing coordinated targeting of different curated gene sets, we observe distinct evolutionary signatures for protein complexes and signaling pathways that could reflect differences in control strategies. Our method is easily scalable to analyze upcoming larger data sets, and readily adaptable to detect high-level selective constraints between other genomic loci. We thus provide a proof-of-principle method to understand regulatory networks from an evolutionary perspective.

Challenges for modeling global gene regulatory networks during development: insights from Drosophila.

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Wilczynski, Bartek; Furlong, Eileen E M

2010-04-15

Development is regulated by dynamic patterns of gene expression, which are orchestrated through the action of complex gene regulatory networks (GRNs). Substantial progress has been made in modeling transcriptional regulation in recent years, including qualitative "coarse-grain" models operating at the gene level to very "fine-grain" quantitative models operating at the biophysical "transcription factor-DNA level". Recent advances in genome-wide studies have revealed an enormous increase in the size and complexity or GRNs. Even relatively simple developmental processes can involve hundreds of regulatory molecules, with extensive interconnectivity and cooperative regulation. This leads to an explosion in the number of regulatory functions, effectively impeding Boolean-based qualitative modeling approaches. At the same time, the lack of information on the biophysical properties for the majority of transcription factors within a global network restricts quantitative approaches. In this review, we explore the current challenges in moving from modeling medium scale well-characterized networks to more poorly characterized global networks. We suggest to integrate coarse- and find-grain approaches to model gene regulatory networks in cis. We focus on two very well-studied examples from Drosophila, which likely represent typical developmental regulatory modules across metazoans. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Regulatory networks and connected components of the neutral space. A look at functional islands

Science.gov (United States)

Boldhaus, G.; Klemm, K.

2010-09-01

The functioning of a living cell is largely determined by the structure of its regulatory network, comprising non-linear interactions between regulatory genes. An important factor for the stability and evolvability of such regulatory systems is neutrality - typically a large number of alternative network structures give rise to the necessary dynamics. Here we study the discretized regulatory dynamics of the yeast cell cycle [Li et al., PNAS, 2004] and the set of networks capable of reproducing it, which we call functional. Among these, the empirical yeast wildtype network is close to optimal with respect to sparse wiring. Under point mutations, which establish or delete single interactions, the neutral space of functional networks is fragmented into ≈ 4.7 × 108 components. One of the smaller ones contains the wildtype network. On average, functional networks reachable from the wildtype by mutations are sparser, have higher noise resilience and fewer fixed point attractors as compared with networks outside of this wildtype component.

CMRegNet-An interspecies reference database for corynebacterial and mycobacterial regulatory networks

DEFF Research Database (Denmark)

Abreu, Vinicius A C; Almeida, Sintia; Tiwari, Sandeep

2015-01-01

gene regulatory network can lead to various practical applications, creating a greater understanding of how organisms control their cellular behavior. DESCRIPTION: In this work, we present a new database, CMRegNet for the gene regulatory networks of Corynebacterium glutamicum ATCC 13032......Net to date the most comprehensive database of regulatory interactions of CMNR bacteria. The content of CMRegNet is publicly available online via a web interface found at http://lgcm.icb.ufmg.br/cmregnet ....

Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice

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Shuchi eSmita

2015-12-01

Full Text Available MYB transcription factor (TF is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by top down and guide gene approaches. More than 50% of OsMYBs were strongly correlated under fifty experimental conditions with 51 hub genes via top down approach. Further, clusters were identified using Markov Clustering (MCL. To maximize the clustering performance, parameter evaluation of the MCL inflation score (I was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by guide gene approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought

Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes

DEFF Research Database (Denmark)

Zelezniak, Aleksej; Pers, Tune Hannes; Pinho Soares, Simao Pedro

2010-01-01

mechanisms underlying these transcriptional changes and their impact on the cellular metabolic phenotype is a challenging task due to the complexity of transcriptional regulation and the highly interconnected nature of the metabolic network. In this study we integrate skeletal muscle gene expression datasets...... with human metabolic network reconstructions to identify key metabolic regulatory features of T2DM. These features include reporter metabolites—metabolites with significant collective transcriptional response in the associated enzyme-coding genes, and transcription factors with significant enrichment...... factor regulatory network connecting several parts of metabolism. The identified transcription factors include members of the CREB, NRF1 and PPAR family, among others, and represent regulatory targets for further experimental analysis. Overall, our results provide a holistic picture of key metabolic...

Spatiotemporal network motif reveals the biological traits of developmental gene regulatory networks in Drosophila melanogaster

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Kim Man-Sun

2012-05-01

Full Text Available Abstract Background Network motifs provided a “conceptual tool” for understanding the functional principles of biological networks, but such motifs have primarily been used to consider static network structures. Static networks, however, cannot be used to reveal time- and region-specific traits of biological systems. To overcome this limitation, we proposed the concept of a “spatiotemporal network motif,” a spatiotemporal sequence of network motifs of sub-networks which are active only at specific time points and body parts. Results On the basis of this concept, we analyzed the developmental gene regulatory network of the Drosophila melanogaster embryo. We identified spatiotemporal network motifs and investigated their distribution pattern in time and space. As a result, we found how key developmental processes are temporally and spatially regulated by the gene network. In particular, we found that nested feedback loops appeared frequently throughout the entire developmental process. From mathematical simulations, we found that mutual inhibition in the nested feedback loops contributes to the formation of spatial expression patterns. Conclusions Taken together, the proposed concept and the simulations can be used to unravel the design principle of developmental gene regulatory networks.

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

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Baumbach Jan

2007-11-01

Full Text Available Abstract Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user can be analyzed in the context of known

Identifying noncoding risk variants using disease-relevant gene regulatory networks.

Science.gov (United States)

Gao, Long; Uzun, Yasin; Gao, Peng; He, Bing; Ma, Xiaoke; Wang, Jiahui; Han, Shizhong; Tan, Kai

2018-02-16

Identifying noncoding risk variants remains a challenging task. Because noncoding variants exert their effects in the context of a gene regulatory network (GRN), we hypothesize that explicit use of disease-relevant GRNs can significantly improve the inference accuracy of noncoding risk variants. We describe Annotation of Regulatory Variants using Integrated Networks (ARVIN), a general computational framework for predicting causal noncoding variants. It employs a set of novel regulatory network-based features, combined with sequence-based features to infer noncoding risk variants. Using known causal variants in gene promoters and enhancers in a number of diseases, we show ARVIN outperforms state-of-the-art methods that use sequence-based features alone. Additional experimental validation using reporter assay further demonstrates the accuracy of ARVIN. Application of ARVIN to seven autoimmune diseases provides a holistic view of the gene subnetwork perturbed by the combinatorial action of the entire set of risk noncoding mutations.

Modeling stochasticity and robustness in gene regulatory networks.

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Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis

2009-06-15

Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

Global regulatory roles of the cAMP/PKA pathway revealed by phenotypic, transcriptomic and phosphoproteomic analyses in a null mutant of the PKA catalytic subunit in Candida albicans.

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Cao, Chengjun; Wu, Mei; Bing, Jian; Tao, Li; Ding, Xuefen; Liu, Xiaoyun; Huang, Guanghua

2017-07-01

The conserved cAMP-dependent protein kinase (PKA) plays critical roles in the regulation of morphological transitions and virulence in the human fungal pathogen Candida albicans. It has long been thought that the PKA catalytic subunit is essential for cell viability in this fungus. Paradoxically, the single adenylyl cyclase-encoding gene, CYR1, which is required for the production of cAMP in C. albicans, is not essential for cell growth. Here, a double mutant of TPK1 and TPK2 (tpk2/tpk2 tpk1/tpk1, t2t1), which encode two isoforms of the PKA catalytic subunit was successfully generated, suggesting that this subunit is not essential for cell viability. Inactivation of the PKA catalytic subunit blocked filamentation and dramatically attenuated white-to-opaque switching, but promoted sexual mating. Comparative transcriptomic analyses demonstrated that the t2t1 and cyr1/cyr1 mutants exhibited similar global gene expression profiles. Compared with the WT strain, the general transcriptional activity and metabolism were significantly decreased in both the t2t1 and cyr1/cyr1 mutants. Using combined phosphoproteomic and bioinformatic analyses, we identified 181 potential PKA phosphorylation targets, which represent 148 unique proteins involved in a wide spectrum of biological processes. The study sheds new insights into the global regulatory features of the cAMP/PKA pathway in C. albicans. © 2017 John Wiley & Sons Ltd.

Aggregation of topological motifs in the Escherichia coli transcriptional regulatory network

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Barabási Albert-László

2004-01-01

Full Text Available Abstract Background Transcriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes and operons regulated by them.To better understand the system-level function of such networks simplification of their architecture was previously achieved by identifying the motifs present in the network, which are small, overrepresented, topologically distinct regulatory interaction patterns (subgraphs. However, the interaction of such motifs with each other, and their form of integration into the full network has not been previously examined. Results By studying the transcriptional regulatory network of the bacterium, Escherichia coli, we demonstrate that the two previously identified motif types in the network (i.e., feed-forward loops and bi-fan motifs do not exist in isolation, but rather aggregate into homologous motif clusters that largely overlap with known biological functions. Moreover, these clusters further coalesce into a supercluster, thus establishing distinct topological hierarchies that show global statistical properties similar to the whole network. Targeted removal of motif links disintegrates the network into small, isolated clusters, while random disruptions of equal number of links do not cause such an effect. Conclusion Individual motifs aggregate into homologous motif clusters and a supercluster forming the backbone of the E. coli transcriptional regulatory network and play a central role in defining its global topological organization.

SELANSI: a toolbox for simulation of stochastic gene regulatory networks.

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Pájaro, Manuel; Otero-Muras, Irene; Vázquez, Carlos; Alonso, Antonio A

2018-03-01

Gene regulation is inherently stochastic. In many applications concerning Systems and Synthetic Biology such as the reverse engineering and the de novo design of genetic circuits, stochastic effects (yet potentially crucial) are often neglected due to the high computational cost of stochastic simulations. With advances in these fields there is an increasing need of tools providing accurate approximations of the stochastic dynamics of gene regulatory networks (GRNs) with reduced computational effort. This work presents SELANSI (SEmi-LAgrangian SImulation of GRNs), a software toolbox for the simulation of stochastic multidimensional gene regulatory networks. SELANSI exploits intrinsic structural properties of gene regulatory networks to accurately approximate the corresponding Chemical Master Equation with a partial integral differential equation that is solved by a semi-lagrangian method with high efficiency. Networks under consideration might involve multiple genes with self and cross regulations, in which genes can be regulated by different transcription factors. Moreover, the validity of the method is not restricted to a particular type of kinetics. The tool offers total flexibility regarding network topology, kinetics and parameterization, as well as simulation options. SELANSI runs under the MATLAB environment, and is available under GPLv3 license at https://sites.google.com/view/selansi. antonio@iim.csic.es. © The Author(s) 2017. Published by Oxford University Press.

An electronic regulatory document management system for a clinical trial network.

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Zhao, Wenle; Durkalski, Valerie; Pauls, Keith; Dillon, Catherine; Kim, Jaemyung; Kolk, Deneil; Silbergleit, Robert; Stevenson, Valerie; Palesch, Yuko

2010-01-01

A computerized regulatory document management system has been developed as a module in a comprehensive Clinical Trial Management System (CTMS) designed for an NIH-funded clinical trial network in order to more efficiently manage and track regulatory compliance. Within the network, several institutions and investigators are involved in multiple trials, and each trial has regulatory document requirements. Some of these documents are trial specific while others apply across multiple trials. The latter causes a possible redundancy in document collection and management. To address these and other related challenges, a central regulatory document management system was designed. This manuscript shares the design of the system as well as examples of it use in current studies. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Reconstructing transcriptional regulatory networks through genomics data

OpenAIRE

Sun, Ning; Zhao, Hongyu

2009-01-01

One central problem in biology is to understand how gene expression is regulated under different conditions. Microarray gene expression data and other high throughput data have made it possible to dissect transcriptional regulatory networks at the genomics level. Owing to the very large number of genes that need to be studied, the relatively small number of data sets available, the noise in the data and the different natures of the distinct data types, network inference presents great challen...

Recurrent neural network based hybrid model for reconstructing gene regulatory network.

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Raza, Khalid; Alam, Mansaf

2016-10-01

One of the exciting problems in systems biology research is to decipher how genome controls the development of complex biological system. The gene regulatory networks (GRNs) help in the identification of regulatory interactions between genes and offer fruitful information related to functional role of individual gene in a cellular system. Discovering GRNs lead to a wide range of applications, including identification of disease related pathways providing novel tentative drug targets, helps to predict disease response, and also assists in diagnosing various diseases including cancer. Reconstruction of GRNs from available biological data is still an open problem. This paper proposes a recurrent neural network (RNN) based model of GRN, hybridized with generalized extended Kalman filter for weight update in backpropagation through time training algorithm. The RNN is a complex neural network that gives a better settlement between biological closeness and mathematical flexibility to model GRN; and is also able to capture complex, non-linear and dynamic relationships among variables. Gene expression data are inherently noisy and Kalman filter performs well for estimation problem even in noisy data. Hence, we applied non-linear version of Kalman filter, known as generalized extended Kalman filter, for weight update during RNN training. The developed model has been tested on four benchmark networks such as DNA SOS repair network, IRMA network, and two synthetic networks from DREAM Challenge. We performed a comparison of our results with other state-of-the-art techniques which shows superiority of our proposed model. Further, 5% Gaussian noise has been induced in the dataset and result of the proposed model shows negligible effect of noise on results, demonstrating the noise tolerance capability of the model. Copyright © 2016 Elsevier Ltd. All rights reserved.

On the Interplay between Entropy and Robustness of Gene Regulatory Networks

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Bor-Sen Chen

2010-05-01

Full Text Available The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.

Risk factors for fatal candidemia caused by Candida albicans and non-albicans Candida species

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Tang Ran-Bin

2005-04-01

Full Text Available Abstract Background Invasive fungal infections, such as candidemia, caused by Candida species have been increasing. Candidemia is not only associated with a high mortality (30% to 40% but also extends the length of hospital stay and increases the costs of medical care. Sepsis caused by Candida species is clinically indistinguishable from bacterial infections. Although, the clinical presentations of the patients with candidemia caused by Candida albicans and non-albicans Candida species (NAC are indistinguishable, the susceptibilities to antifungal agents of these species are different. In this study, we attempted to identify the risk factors for candidemia caused by C. albicans and NAC in the hope that this may guide initial empiric therapy. Methods A retrospective chart review was conducted during 1996 to 1999 at the Veterans General Hospital-Taipei. Results There were 130 fatal cases of candidemia, including 68 patients with C. albicans and 62 with NAC. Candidemia was the most likely cause of death in 55 of the 130 patients (42.3 %. There was no significant difference in the distribution of Candida species between those died of candidemia and those died of underlying conditions. Patients who had one of the following conditions were more likely to have C. albicans, age ≧ 65 years, immunosuppression accounted to prior use of steroids, leukocytosis, in the intensive care unit (ICU, and intravascular and urinary catheters. Patients who had undergone cancer chemotherapy often appeared less critically ill and were more likely to have NAC. Conclusion Clinical and epidemiological differences in the risk factors between candidemia caused by C. albicans and NAC may provide helpful clues to initiate empiric therapy for patients infected with C. albicans versus NAC.

Risk factors for fatal candidemia caused by Candida albicans and non-albicans Candida species

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Cheng, Ming-Fang; Yang, Yun-Liang; Yao, Tzy-Jyun; Lin, Chin-Yu; Liu, Jih-Shin; Tang, Ran-Bin; Yu, Kwok-Woon; Fan, Yu-Hua; Hsieh, Kai-Sheng; Ho, Monto; Lo, Hsiu-Jung

2005-01-01

Background Invasive fungal infections, such as candidemia, caused by Candida species have been increasing. Candidemia is not only associated with a high mortality (30% to 40%) but also extends the length of hospital stay and increases the costs of medical care. Sepsis caused by Candida species is clinically indistinguishable from bacterial infections. Although, the clinical presentations of the patients with candidemia caused by Candida albicans and non-albicans Candida species (NAC) are indistinguishable, the susceptibilities to antifungal agents of these species are different. In this study, we attempted to identify the risk factors for candidemia caused by C. albicans and NAC in the hope that this may guide initial empiric therapy. Methods A retrospective chart review was conducted during 1996 to 1999 at the Veterans General Hospital-Taipei. Results There were 130 fatal cases of candidemia, including 68 patients with C. albicans and 62 with NAC. Candidemia was the most likely cause of death in 55 of the 130 patients (42.3 %). There was no significant difference in the distribution of Candida species between those died of candidemia and those died of underlying conditions. Patients who had one of the following conditions were more likely to have C. albicans, age ≧ 65 years, immunosuppression accounted to prior use of steroids, leukocytosis, in the intensive care unit (ICU), and intravascular and urinary catheters. Patients who had undergone cancer chemotherapy often appeared less critically ill and were more likely to have NAC. Conclusion Clinical and epidemiological differences in the risk factors between candidemia caused by C. albicans and NAC may provide helpful clues to initiate empiric therapy for patients infected with C. albicans versus NAC. PMID:15813977

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-regulatory

Inferring regulatory networks from expression data using tree-based methods.

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Vân Anh Huynh-Thu

2010-09-01

Full Text Available One of the pressing open problems of computational systems biology is the elucidation of the topology of genetic regulatory networks (GRNs using high throughput genomic data, in particular microarray gene expression data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM challenge aims to evaluate the success of GRN inference algorithms on benchmarks of simulated data. In this article, we present GENIE3, a new algorithm for the inference of GRNs that was best performer in the DREAM4 In Silico Multifactorial challenge. GENIE3 decomposes the prediction of a regulatory network between p genes into p different regression problems. In each of the regression problems, the expression pattern of one of the genes (target gene is predicted from the expression patterns of all the other genes (input genes, using tree-based ensemble methods Random Forests or Extra-Trees. The importance of an input gene in the prediction of the target gene expression pattern is taken as an indication of a putative regulatory link. Putative regulatory links are then aggregated over all genes to provide a ranking of interactions from which the whole network is reconstructed. In addition to performing well on the DREAM4 In Silico Multifactorial challenge simulated data, we show that GENIE3 compares favorably with existing algorithms to decipher the genetic regulatory network of Escherichia coli. It doesn't make any assumption about the nature of gene regulation, can deal with combinatorial and non-linear interactions, produces directed GRNs, and is fast and scalable. In conclusion, we propose a new algorithm for GRN inference that performs well on both synthetic and real gene expression data. The algorithm, based on feature selection with tree-based ensemble methods, is simple and generic, making it adaptable to other types of genomic data and interactions.

Leveraging network utility management practices for regulatory purposes

International Nuclear Information System (INIS)

2009-11-01

Electric utilities around the globe are entering a phase where they must modernize and implement smart grid technologies. In order to optimize system architecture, asset replacement, and future operating costs, it the utilities must implement robust and flexible asset management structures. This report discussed the ways in which regulators assess investment plans. It focused on the implicit or explicit use of an asset management approach, including principles; processes; input and outputs; decision-making criteria and prioritization methods. The Ontario Energy Board staff were familiarized with the principles and objectives of established and emerging asset management processes and underlying analytic processes, systems and tools in order to ensure that investment information provided by network utilities regarding rates and other applications could be evaluated effectively. Specifically, the report discussed the need for and importance of asset management and provided further details of international markets and their regulatory approaches to asset management. The report also discussed regulatory approaches for review of asset management underlying investment plans as well as an overview of international regulatory practice for review of network utility asset management. It was concluded that options for strengthening regulatory guidance and assessment included utilizing appropriate and effective benchmarking to assess, promote and provide incentives for best practices and steer clear of the potential perverse incentives. 21 tabs., 17 figs., 1 appendix.

CoryneRegNet: an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks.

Science.gov (United States)

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-02-14

The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

Gene regulatory network inference by point-based Gaussian approximation filters incorporating the prior information.

Science.gov (United States)

Jia, Bin; Wang, Xiaodong

2013-12-17

: The extended Kalman filter (EKF) has been applied to inferring gene regulatory networks. However, it is well known that the EKF becomes less accurate when the system exhibits high nonlinearity. In addition, certain prior information about the gene regulatory network exists in practice, and no systematic approach has been developed to incorporate such prior information into the Kalman-type filter for inferring the structure of the gene regulatory network. In this paper, an inference framework based on point-based Gaussian approximation filters that can exploit the prior information is developed to solve the gene regulatory network inference problem. Different point-based Gaussian approximation filters, including the unscented Kalman filter (UKF), the third-degree cubature Kalman filter (CKF3), and the fifth-degree cubature Kalman filter (CKF5) are employed. Several types of network prior information, including the existing network structure information, sparsity assumption, and the range constraint of parameters, are considered, and the corresponding filters incorporating the prior information are developed. Experiments on a synthetic network of eight genes and the yeast protein synthesis network of five genes are carried out to demonstrate the performance of the proposed framework. The results show that the proposed methods provide more accurate inference results than existing methods, such as the EKF and the traditional UKF.

[Pulsatilla decoction inhibits vulvovaginal Candida albicans proliferation and reduces inflammatory cytokine levels in vulvovaginal candidiasis mice].

Science.gov (United States)

Xia, Dan; Zhang, Mengxiang; Shi, Gaoxiang; Xu, Zhiqing; Wu, Daqiang; Shao, Jing; Wang, Tianming; Wang, Changzhong

2016-02-01

To explore the possible regulatory effect of Pulsatilla decoction on Th17 cells and inflammatory cytokines of vulvovaginal candidiasis (VVC) mice. Seventy-two female Kunming mice were randomly assigned into six groups: a blank control group, a VVC model group, a fluconazole group and three Pulsatilla decoction groups (dose levels: 22.5, 15.0 and 7.5 g/kg, respectively). The VVC mouse models were established by vaginal inoculation with Candida albicans (C. albicans) in female mice in pseudoestrus state caused by estradiol injection. After 7-day treatment on VVC mice, the vaginal C. albicans burden was assessed using dilution spread plate method; the vaginal C. albicans morphology was observed by Gram staining method; the levels of interleukin 6 (IL-6), IL-17, IL-21 and tumor necrosis factor α (TNF-α) in sera were detected by ELISA. The content of the transcription factor retinoid related orphan receptor gamma t (RORγt) in vaginal tissues was detected by immunohistochemistry. The VVC mouse models were successfully developed. After treatment, the vaginal C. albicans burden of the fluconazole group and 22.5 g/kg Pulsatilla decoction group dropped significantly compared with that of the VVC model group. Gram staining showed that the VVC mice had lots of C. albicans hyphae in vaginal discharge, that 7.5 g/kg Pulsatilla decoction group remained the mycelia-phase C. albicans, and that 15.0 g/kg Pulsatilla decoction group had the majority of yeast-phase C. albicans and a few of mycelia-phase, while no hyphae and only very few of yeast-phase C. albicans were observed in 22.5 g/kg Pulsatilla decoction group and fluconazole group. After 7-day treatment, compared with the model group, the levels of IL-6, IL- 17, IL-21 and TNF-α in the sera of the fluconazole group, 15.0 and 22.5 g/kg Pulsatilla decoction groups were reduced significantly and the levels of RORγt in the vaginal tissues of the fluconazole group, 15.0 and 22.5 g/kg Pulsatilla decoction groups also decreased

Evolution of regulatory networks towards adaptability and stability in a changing environment

Science.gov (United States)

Lee, Deok-Sun

2014-11-01

Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which evolve by selectively rewiring links towards enhancing adaptability to a changing environment and stability against dynamical perturbations. We find that sparse and heterogeneous connectivity patterns emerge, which show qualitative agreement with real transcriptional regulatory networks and metabolic networks. The characteristic scaling behavior of stability reflects the balance between robustness and flexibility. The scaling of fluctuation in the perturbation spread shows a dynamic crossover, which is analyzed by investigating separately the stochasticity of internal dynamics and the network structure differences depending on the evolution pathways. Our study delineates how the ambivalent pressure of evolution shapes biological networks, which can be helpful for studying general complex systems interacting with environments.

Information processing in the transcriptional regulatory network of yeast: Functional robustness

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Dehmer Matthias

2009-03-01

Full Text Available Abstract Background Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism. Results In this paper we study the functional robustness of the transcriptional regulatory network of S. cerevisiae. We model the information processing in the network as a first order Markov chain and study the influence of single gene perturbations on the global, asymptotic communication among genes. Modification in the communication is measured by an information theoretic measure allowing to predict genes that are 'fragile' with respect to single gene knockouts. Our results demonstrate that the predicted set of fragile genes contains a statistically significant enrichment of so called essential genes that are experimentally found to be necessary to ensure vital yeast. Further, a structural analysis of the transcriptional regulatory network reveals that there are significant differences between fragile genes, hub genes and genes with a high betweenness centrality value. Conclusion Our study does not only demonstrate that a combination of graph theoretical, information theoretical and statistical methods leads to meaningful biological results but also that such methods allow to study information processing in gene networks instead of just their structural properties.

Growth of Candida albicans hyphae.

Science.gov (United States)

Sudbery, Peter E

2011-08-16

The fungus Candida albicans is often a benign member of the mucosal flora; however, it commonly causes mucosal disease with substantial morbidity and in vulnerable patients it causes life-threatening bloodstream infections. A striking feature of its biology is its ability to grow in yeast, pseudohyphal and hyphal forms. The hyphal form has an important role in causing disease by invading epithelial cells and causing tissue damage. This Review describes our current understanding of the network of signal transduction pathways that monitors environmental cues to activate a programme of hypha-specific gene transcription, and the molecular processes that drive the highly polarized growth of hyphae.

Uncovering transcription factor and microRNA risk regulatory pathways associated with osteoarthritis by network analysis.

Science.gov (United States)

Song, Zhenhua; Zhang, Chi; He, Lingxiao; Sui, Yanfang; Lin, Xiafei; Pan, Jingjing

2018-05-01

Osteoarthritis (OA) is the most common form of joint disease. The development of inflammation have been considered to play a key role during the progression of OA. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, deciphering these risk regulatory pathways is critical for elucidating the mechanisms underlying OA. We constructed an OA-specific regulatory network by integrating comprehensive curated transcription and post-transcriptional resource involving transcription factor (TF) and microRNA (miRNA). To deepen our understanding of underlying molecular mechanisms of OA, we developed an integrated systems approach to identify OA-specific risk regulatory pathways. In this study, we identified 89 significantly differentially expressed genes between normal and inflamed areas of OA patients. We found the OA-specific regulatory network was a standard scale-free network with small-world properties. It significant enriched many immune response-related functions including leukocyte differentiation, myeloid differentiation and T cell activation. Finally, 141 risk regulatory pathways were identified based on OA-specific regulatory network, which contains some known regulator of OA. The risk regulatory pathways may provide clues for the etiology of OA and be a potential resource for the discovery of novel OA-associated disease genes. Copyright © 2018 Elsevier Inc. All rights reserved.

CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

Directory of Open Access Journals (Sweden)

Czaja Lisa F

2006-02-01

Full Text Available Abstract Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

Science.gov (United States)

Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

2013-09-22

High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

Learning Gene Regulatory Networks Computationally from Gene Expression Data Using Weighted Consensus

KAUST Repository

Fujii, Chisato

2015-04-16

Gene regulatory networks analyze the relationships between genes allowing us to un- derstand the gene regulatory interactions in systems biology. Gene expression data from the microarray experiments is used to obtain the gene regulatory networks. How- ever, the microarray data is discrete, noisy and non-linear which makes learning the networks a challenging problem and existing gene network inference methods do not give consistent results. Current state-of-the-art study uses the average-ranking-based consensus method to combine and average the ranked predictions from individual methods. However each individual method has an equal contribution to the consen- sus prediction. We have developed a linear programming-based consensus approach which uses learned weights from linear programming among individual methods such that the methods have di↵erent weights depending on their performance. Our result reveals that assigning di↵erent weights to individual methods rather than giving them equal weights improves the performance of the consensus. The linear programming- based consensus method is evaluated and it had the best performance on in silico and Saccharomyces cerevisiae networks, and the second best on the Escherichia coli network outperformed by Inferelator Pipeline method which gives inconsistent results across a wide range of microarray data sets.

Fractal gene regulatory networks for robust locomotion control of modular robots

DEFF Research Database (Denmark)

Zahadat, Payam; Christensen, David Johan; Schultz, Ulrik Pagh

2010-01-01

Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed and the ......Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed...

An integer optimization algorithm for robust identification of non-linear gene regulatory networks

Directory of Open Access Journals (Sweden)

Chemmangattuvalappil Nishanth

2012-09-01

Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters

Semi-supervised prediction of gene regulatory networks using ...

Indian Academy of Sciences (India)

2015-09-28

Sep 28, 2015 ... Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging ... two types of methods differ primarily based on whether ..... negligible, allowing us to draw the qualitative conclusions .... research will be conducted to develop additional biologically.

Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks

Directory of Open Access Journals (Sweden)

Ji Wei

2010-10-01

Full Text Available Abstract Background Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are used to discretize microarray data. Selection of the discretization method is often arbitrary and no systematic comparison of different discretization has been conducted, in the context of gene regulatory network inference from time series gene expression data. Results In this study, we propose a new discretization method "bikmeans", and compare its performance with four other widely-used discretization methods using different datasets, modeling algorithms and number of intervals. Sensitivities, specificities and total accuracies were calculated and statistical analysis was carried out. Bikmeans method always gave high total accuracies. Conclusions Our results indicate that proper discretization methods can consistently improve gene regulatory network inference independent of network modeling algorithms and datasets. Our new method, bikmeans, resulted in significant better total accuracies than other methods.

Genetic Control of Conventional and Pheromone-Stimulated Biofilm Formation in Candida albicans

Science.gov (United States)

Lin, Ching-Hsuan; Kabrawala, Shail; Fox, Emily P.; Nobile, Clarissa J.; Johnson, Alexander D.; Bennett, Richard J.

2013-01-01

Candida albicans can stochastically switch between two phenotypes, white and opaque. Opaque cells are the sexually competent form of C. albicans and therefore undergo efficient polarized growth and mating in the presence of pheromone. In contrast, white cells cannot mate, but are induced – under a specialized set of conditions – to form biofilms in response to pheromone. In this work, we compare the genetic regulation of such “pheromone-stimulated” biofilms with that of “conventional” C. albicans biofilms. In particular, we examined a network of six transcriptional regulators (Bcr1, Brg1, Efg1, Tec1, Ndt80, and Rob1) that mediate conventional biofilm formation for their potential roles in pheromone-stimulated biofilm formation. We show that four of the six transcription factors (Bcr1, Brg1, Rob1, and Tec1) promote formation of both conventional and pheromone-stimulated biofilms, indicating they play general roles in cell cohesion and biofilm development. In addition, we identify the master transcriptional regulator of pheromone-stimulated biofilms as C. albicans Cph1, ortholog of Saccharomyces cerevisiae Ste12. Cph1 regulates mating in C. albicans opaque cells, and here we show that Cph1 is also essential for pheromone-stimulated biofilm formation in white cells. In contrast, Cph1 is dispensable for the formation of conventional biofilms. The regulation of pheromone- stimulated biofilm formation was further investigated by transcriptional profiling and genetic analyses. These studies identified 196 genes that are induced by pheromone signaling during biofilm formation. One of these genes, HGC1, is shown to be required for both conventional and pheromone-stimulated biofilm formation. Taken together, these observations compare and contrast the regulation of conventional and pheromone-stimulated biofilm formation in C. albicans, and demonstrate that Cph1 is required for the latter, but not the former. PMID:23637598

A Systems’ Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

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Xin Lai

2013-01-01

Full Text Available MicroRNAs (miRNAs are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts.

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.

Candida albicans versus Candida dubliniensis: Why Is C. albicans More Pathogenic?

LENUS (Irish Health Repository)

Moran, Gary P

2012-01-01

Candida albicans and Candida dubliniensis are highly related pathogenic yeast species. However, C. albicans is far more prevalent in human infection and has been shown to be more pathogenic in a wide range of infection models. Comparison of the genomes of the two species has revealed that they are very similar although there are some significant differences, largely due to the expansion of virulence-related gene families (e.g., ALS and SAP) in C. albicans, and increased levels of pseudogenisation in C. dubliniensis. Comparative global gene expression analyses have also been used to investigate differences in the ability of the two species to tolerate environmental stress and to produce hyphae, two traits that are likely to play a role in the lower virulence of C. dubliniensis. Taken together, these data suggest that C. dubliniensis is in the process of undergoing reductive evolution and may have become adapted for growth in a specialized anatomic niche.

Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.

Directory of Open Access Journals (Sweden)

Taosheng Xu

Full Text Available Identifying cancer subtypes is an important component of the personalised medicine framework. An increasing number of computational methods have been developed to identify cancer subtypes. However, existing methods rarely use information from gene regulatory networks to facilitate the subtype identification. It is widely accepted that gene regulatory networks play crucial roles in understanding the mechanisms of diseases. Different cancer subtypes are likely caused by different regulatory mechanisms. Therefore, there are great opportunities for developing methods that can utilise network information in identifying cancer subtypes.In this paper, we propose a method, weighted similarity network fusion (WSNF, to utilise the information in the complex miRNA-TF-mRNA regulatory network in identifying cancer subtypes. We firstly build the regulatory network where the nodes represent the features, i.e. the microRNAs (miRNAs, transcription factors (TFs and messenger RNAs (mRNAs and the edges indicate the interactions between the features. The interactions are retrieved from various interatomic databases. We then use the network information and the expression data of the miRNAs, TFs and mRNAs to calculate the weight of the features, representing the level of importance of the features. The feature weight is then integrated into a network fusion approach to cluster the samples (patients and thus to identify cancer subtypes. We applied our method to the TCGA breast invasive carcinoma (BRCA and glioblastoma multiforme (GBM datasets. The experimental results show that WSNF performs better than the other commonly used computational methods, and the information from miRNA-TF-mRNA regulatory network contributes to the performance improvement. The WSNF method successfully identified five breast cancer subtypes and three GBM subtypes which show significantly different survival patterns. We observed that the expression patterns of the features in some mi

Generic Properties of Random Gene Regulatory Networks.

Science.gov (United States)

Li, Zhiyuan; Bianco, Simone; Zhang, Zhaoyang; Tang, Chao

2013-12-01

Modeling gene regulatory networks (GRNs) is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits: steady state, periodic and chaotic, and how the dynamical properties change with network's topological characteristics. In this work, we first investigated these questions in random GRNs with different network sizes, connectivity, fraction of inhibitory links and transcription regulation rules. Then we searched for the core motifs that govern the dynamic behavior of large GRNs. We show that the stability of a random GRN is typically governed by a few embedding motifs of small sizes, and therefore can in general be understood in the context of these short motifs. Our results provide insights for the study and design of genetic networks.

Ground rules of the pluripotency gene regulatory network.

KAUST Repository

Li, Mo

2017-01-03

Pluripotency is a state that exists transiently in the early embryo and, remarkably, can be recapitulated in vitro by deriving embryonic stem cells or by reprogramming somatic cells to become induced pluripotent stem cells. The state of pluripotency, which is stabilized by an interconnected network of pluripotency-associated genes, integrates external signals and exerts control over the decision between self-renewal and differentiation at the transcriptional, post-transcriptional and epigenetic levels. Recent evidence of alternative pluripotency states indicates the regulatory flexibility of this network. Insights into the underlying principles of the pluripotency network may provide unprecedented opportunities for studying development and for regenerative medicine.

Ground rules of the pluripotency gene regulatory network.

KAUST Repository

Li, Mo; Belmonte, Juan Carlos Izpisua

2017-01-01

Pluripotency is a state that exists transiently in the early embryo and, remarkably, can be recapitulated in vitro by deriving embryonic stem cells or by reprogramming somatic cells to become induced pluripotent stem cells. The state of pluripotency, which is stabilized by an interconnected network of pluripotency-associated genes, integrates external signals and exerts control over the decision between self-renewal and differentiation at the transcriptional, post-transcriptional and epigenetic levels. Recent evidence of alternative pluripotency states indicates the regulatory flexibility of this network. Insights into the underlying principles of the pluripotency network may provide unprecedented opportunities for studying development and for regenerative medicine.

On the dynamics of a gene regulatory network

International Nuclear Information System (INIS)

Grammaticos, B; Carstea, A S; Ramani, A

2006-01-01

We examine the dynamics of a network of genes focusing on a periodic chain of genes, of arbitrary length. We show that within a given class of sigmoids representing the equilibrium probability of the binding of the RNA polymerase to the core promoter, the system possesses a single stable fixed point. By slightly modifying the sigmoid, introducing 'stiffer' forms, we show that it is possible to find network configurations exhibiting bistable behaviour. Our results do not depend crucially on the length of the chain considered: calculations with finite chains lead to similar results. However, a realistic study of regulatory genetic networks would require the consideration of more complex topologies and interactions

Elucidating MicroRNA Regulatory Networks Using Transcriptional, Post-transcriptional, and Histone Modification Measurements

Directory of Open Access Journals (Sweden)

Sara J.C. Gosline

2016-01-01

Full Text Available MicroRNAs (miRNAs regulate diverse biological processes by repressing mRNAs, but their modest effects on direct targets, together with their participation in larger regulatory networks, make it challenging to delineate miRNA-mediated effects. Here, we describe an approach to characterizing miRNA-regulatory networks by systematically profiling transcriptional, post-transcriptional and epigenetic activity in a pair of isogenic murine fibroblast cell lines with and without Dicer expression. By RNA sequencing (RNA-seq and CLIP (crosslinking followed by immunoprecipitation sequencing (CLIP-seq, we found that most of the changes induced by global miRNA loss occur at the level of transcription. We then introduced a network modeling approach that integrated these data with epigenetic data to identify specific miRNA-regulated transcription factors that explain the impact of miRNA perturbation on gene expression. In total, we demonstrate that combining multiple genome-wide datasets spanning diverse regulatory modes enables accurate delineation of the downstream miRNA-regulated transcriptional network and establishes a model for studying similar networks in other systems.

Deconstructing the pluripotency gene regulatory network

KAUST Repository

Li, Mo

2018-04-04

Pluripotent stem cells can be isolated from embryos or derived by reprogramming. Pluripotency is stabilized by an interconnected network of pluripotency genes that cooperatively regulate gene expression. Here we describe the molecular principles of pluripotency gene function and highlight post-transcriptional controls, particularly those induced by RNA-binding proteins and alternative splicing, as an important regulatory layer of pluripotency. We also discuss heterogeneity in pluripotency regulation, alternative pluripotency states and future directions of pluripotent stem cell research.

Deconstructing the pluripotency gene regulatory network

KAUST Repository

Li, Mo; Belmonte, Juan Carlos Izpisua

2018-01-01

Pluripotent stem cells can be isolated from embryos or derived by reprogramming. Pluripotency is stabilized by an interconnected network of pluripotency genes that cooperatively regulate gene expression. Here we describe the molecular principles of pluripotency gene function and highlight post-transcriptional controls, particularly those induced by RNA-binding proteins and alternative splicing, as an important regulatory layer of pluripotency. We also discuss heterogeneity in pluripotency regulation, alternative pluripotency states and future directions of pluripotent stem cell research.

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato; Kuwahara, Hiroyuki; Yu, Ge; Guo, Lili; Gao, Xin

2016-01-01

An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato

2016-08-25

An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

Science.gov (United States)

Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

2014-12-01

Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

Memory functions reveal structural properties of gene regulatory networks

Science.gov (United States)

Perez-Carrasco, Ruben

2018-01-01

Gene regulatory networks (GRNs) control cellular function and decision making during tissue development and homeostasis. Mathematical tools based on dynamical systems theory are often used to model these networks, but the size and complexity of these models mean that their behaviour is not always intuitive and the underlying mechanisms can be difficult to decipher. For this reason, methods that simplify and aid exploration of complex networks are necessary. To this end we develop a broadly applicable form of the Zwanzig-Mori projection. By first converting a thermodynamic state ensemble model of gene regulation into mass action reactions we derive a general method that produces a set of time evolution equations for a subset of components of a network. The influence of the rest of the network, the bulk, is captured by memory functions that describe how the subnetwork reacts to its own past state via components in the bulk. These memory functions provide probes of near-steady state dynamics, revealing information not easily accessible otherwise. We illustrate the method on a simple cross-repressive transcriptional motif to show that memory functions not only simplify the analysis of the subnetwork but also have a natural interpretation. We then apply the approach to a GRN from the vertebrate neural tube, a well characterised developmental transcriptional network composed of four interacting transcription factors. The memory functions reveal the function of specific links within the neural tube network and identify features of the regulatory structure that specifically increase the robustness of the network to initial conditions. Taken together, the study provides evidence that Zwanzig-Mori projections offer powerful and effective tools for simplifying and exploring the behaviour of GRNs. PMID:29470492

The gene regulatory network for breast cancer: Integrated regulatory landscape of cancer hallmarks

Directory of Open Access Journals (Sweden)

Frank eEmmert-Streib

2014-02-01

Full Text Available In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of $351$ patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome $21$ is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.

A reverse engineering approach to optimize experiments for the construction of biological regulatory networks.

Science.gov (United States)

Zhang, Xiaomeng; Shao, Bin; Wu, Yangle; Qi, Ouyang

2013-01-01

One of the major objectives in systems biology is to understand the relation between the topological structures and the dynamics of biological regulatory networks. In this context, various mathematical tools have been developed to deduct structures of regulatory networks from microarray expression data. In general, from a single data set, one cannot deduct the whole network structure; additional expression data are usually needed. Thus how to design a microarray expression experiment in order to get the most information is a practical problem in systems biology. Here we propose three methods, namely, maximum distance method, trajectory entropy method, and sampling method, to derive the optimal initial conditions for experiments. The performance of these methods is tested and evaluated in three well-known regulatory networks (budding yeast cell cycle, fission yeast cell cycle, and E. coli. SOS network). Based on the evaluation, we propose an efficient strategy for the design of microarray expression experiments.

Predictive minimum description length principle approach to inferring gene regulatory networks.

Science.gov (United States)

Chaitankar, Vijender; Zhang, Chaoyang; Ghosh, Preetam; Gong, Ping; Perkins, Edward J; Deng, Youping

2011-01-01

Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold that defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we propose a new inference algorithm that incorporates mutual information (MI), conditional mutual information (CMI), and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm is evaluated using both synthetic time series data sets and a biological time series data set (Saccharomyces cerevisiae). The results show that the proposed algorithm produced fewer false edges and significantly improved the precision when compared to existing MDL algorithm.

Synchronous versus asynchronous modeling of gene regulatory networks.

Science.gov (United States)

Garg, Abhishek; Di Cara, Alessandro; Xenarios, Ioannis; Mendoza, Luis; De Micheli, Giovanni

2008-09-01

In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Functional alignment of regulatory networks: a study of temperate phages.

Directory of Open Access Journals (Sweden)

Ala Trusina

2005-12-01

Full Text Available The relationship between the design and functionality of molecular networks is now a key issue in biology. Comparison of regulatory networks performing similar tasks can provide insights into how network architecture is constrained by the functions it directs. Here, we discuss methods of network comparison based on network architecture and signaling logic. Introducing local and global signaling scores for the difference between two networks, we quantify similarities between evolutionarily closely and distantly related bacteriophages. Despite the large evolutionary separation between phage lambda and 186, their networks are found to be similar when difference is measured in terms of global signaling. We finally discuss how network alignment can be used to pinpoint protein similarities viewed from the network perspective.

Daya hambat xylitol dan nistation terhadap pertumbuhan Candida albicans (in vitro (Inhibition effect of xylitol and nistatin combination on Candida albicans growth (in vitro

Directory of Open Access Journals (Sweden)

Sarah Kartimah Djajusman

2014-09-01

Full Text Available Background: The growth of Candida albicans can be controlled by using antifungal such as nystatin. These days we found that using antifungal is not enough to control Candida albicans, we also have to control the intake of sugar by using xylitol. Purpose: Purpose of the study was to determine the optimal inhibitory concentration of xylitol-nystatin in the Candida albicans growth. Methods: This was an in-vitro study using an antimicrobial test of serial dilution with xylitol-nystatin and sucrose–nystatin consentration of 1%, 3%, 5%, 7%, 9%, and 10%.Growth inhibition of C. albicans was determined by the inhibition zone of xylitol + nystatin on C. albicans culture media (in vitro Results: The result of study was the inhibitory consentration of xylitol-nystatin to inhibit Candida albicans growth was 3%-10%. Conclusion: The study showed that combination of xylitol and nystation could inhibit the growth of Candida albicans.Latar belakang: Pertumbuhan Candida albicans dapat dikontrol dengan menggunakan antijamur seperti nistatin. Penggunakan antijamur saja tidak cukup untuk mengontrol Candida albicans, namun perlu pula mengontrol asupan gula dengan menggunakan xylitol. Tujuan: Tujuan dari penelitian ini adalah untuk menentukan konsentrasi hambat optimal xylitol-nistatin dalam pertumbuhan Candida albicans. Metode: Penelitian ini merupakan penelitian in vitro menggunakan uji antimikroba pengenceran serial dengan xylitol-nistatin dan nystatin-sukrosa konsentrasi 1%, 3 %, 5 %, 7%, 9%, dan 10%. Daya hambat pertumbuhan C. albicans diukur dari zona hambat xylitol + nistatin pada media kultur C. albicans (in vitro Hasil: Konsentrasi penghambatan xylitol-nistatin untuk menghambat pertumbuhan Candida albicans adalah 3-10%. Simpulan: Hasil penelitian menunjukkan bahwa kombinasi xylitol dan nystation bisa menghambat pertumbuhan Candida albicans.

An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

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Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

2018-05-14

A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives

Data-driven integration of genome-scale regulatory and metabolic network models

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Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.

2015-01-01

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934

Inferring Gene Regulatory Networks Using Conditional Regulation Pattern to Guide Candidate Genes.

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Fei Xiao

Full Text Available Combining path consistency (PC algorithms with conditional mutual information (CMI are widely used in reconstruction of gene regulatory networks. CMI has many advantages over Pearson correlation coefficient in measuring non-linear dependence to infer gene regulatory networks. It can also discriminate the direct regulations from indirect ones. However, it is still a challenge to select the conditional genes in an optimal way, which affects the performance and computation complexity of the PC algorithm. In this study, we develop a novel conditional mutual information-based algorithm, namely RPNI (Regulation Pattern based Network Inference, to infer gene regulatory networks. For conditional gene selection, we define the co-regulation pattern, indirect-regulation pattern and mixture-regulation pattern as three candidate patterns to guide the selection of candidate genes. To demonstrate the potential of our algorithm, we apply it to gene expression data from DREAM challenge. Experimental results show that RPNI outperforms existing conditional mutual information-based methods in both accuracy and time complexity for different sizes of gene samples. Furthermore, the robustness of our algorithm is demonstrated by noisy interference analysis using different types of noise.

Large-scale modeling of condition-specific gene regulatory networks by information integration and inference.

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Ellwanger, Daniel Christian; Leonhardt, Jörn Florian; Mewes, Hans-Werner

2014-12-01

Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Anticipated Ethics and Regulatory Challenges in PCORnet: The National Patient-Centered Clinical Research Network.

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Ali, Joseph; Califf, Robert; Sugarman, Jeremy

2016-01-01

PCORnet, the National Patient-Centered Clinical Research Network, seeks to establish a robust national health data network for patient-centered comparative effectiveness research. This article reports the results of a PCORnet survey designed to identify the ethics and regulatory challenges anticipated in network implementation. A 12-item online survey was developed by leadership of the PCORnet Ethics and Regulatory Task Force; responses were collected from the 29 PCORnet networks. The most pressing ethics issues identified related to informed consent, patient engagement, privacy and confidentiality, and data sharing. High priority regulatory issues included IRB coordination, privacy and confidentiality, informed consent, and data sharing. Over 150 IRBs and five different approaches to managing multisite IRB review were identified within PCORnet. Further empirical and scholarly work, as well as practical and policy guidance, is essential if important initiatives that rely on comparative effectiveness research are to move forward.

Baicalin prevents Candida albicans infections via increasing its apoptosis rate

International Nuclear Information System (INIS)

Yang, Shulong; Fu, Yingyuan; Wu, Xiuzhen; Zhou, Zhixing; Xu, Jing; Zeng, Xiaoping; Kuang, Nanzhen; Zeng, Yurong

2014-01-01

Highlights: • Baicalin increases the ratio of the G0/G1 stages and C. albicans apoptosis. • Baicalin decreases the proliferation index of C. albicans. • Baicalin inhibits the biosynthesis of DNA, RNA and protein in C. albicans. • Baicalin depresses Succinate Dehydrogenase and Ca 2+ –Mg 2+ ATPase in C. albicans. • Baicalin increases the endocytic free Ca 2+ concentration in C. albicans. - Abstract: Background: These experiments were employed to explore the mechanisms underlying baicalin action on Candida albicans. Methodology and principal findings: We detected the baicalin inhibition effects on three isotope-labeled precursors of 3 H-UdR, 3 H-TdR and 3 H-leucine incorporation into C. albicans using the isotope incorporation technology. The activities of Succinate Dehydrogenase (SDH), cytochrome oxidase (CCO) and Ca 2+ –Mg 2+ ATPase, cytosolic Ca 2+ concentration, the cell cycle and apoptosis, as well as the ultrastructure of C.albicans were also tested. We found that baicalin inhibited 3 H-UdR, 3 H-TdR and 3 H-leucine incorporation into C.albicans (P < 0.005). The activities of the SDH and Ca 2+ –Mg 2+ ATPase of C.albicans in baicalin groups were lower than those in control group (P < 0.05). Ca 2+ concentrations of C. albicans in baicalin groups were much higher than those in control group (P < 0.05). The ratio of C.albicans at the G0/G1 stage increased in baicalin groups in dose dependent manner (P < 0.01). There were a significant differences in the apoptosis rate of C.albicans between baicalin and control groups (P < 0.01). After 12–48 h incubation with baicalin (1 mg/ml), C. albicans shown to be markedly damaged under transmission electron micrographs. Innovation and significance: Baicalin can increase the apoptosis rate of C. albicans. These effects of Baicalin may involved in its inhibiting the activities of the SDH and Ca 2+ –Mg 2+ ATPase, increasing cytosolic Ca 2+ content and damaging the ultrastructure of C. albicans

Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach

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Buer Jan

2004-12-01

Full Text Available Abstract Background Cellular functions are coordinately carried out by groups of genes forming functional modules. Identifying such modules in the transcriptional regulatory network (TRN of organisms is important for understanding the structure and function of these fundamental cellular networks and essential for the emerging modular biology. So far, the global connectivity structure of TRN has not been well studied and consequently not applied for the identification of functional modules. Moreover, network motifs such as feed forward loop are recently proposed to be basic building blocks of TRN. However, their relationship to functional modules is not clear. Results In this work we proposed a top-down approach to identify modules in the TRN of E. coli. By studying the global connectivity structure of the regulatory network, we first revealed a five-layer hierarchical structure in which all the regulatory relationships are downward. Based on this regulatory hierarchy, we developed a new method to decompose the regulatory network into functional modules and to identify global regulators governing multiple modules. As a result, 10 global regulators and 39 modules were identified and shown to have well defined functions. We then investigated the distribution and composition of the two basic network motifs (feed forward loop and bi-fan motif in the hierarchical structure of TRN. We found that most of these network motifs include global regulators, indicating that these motifs are not basic building blocks of modules since modules should not contain global regulators. Conclusion The transcriptional regulatory network of E. coli possesses a multi-layer hierarchical modular structure without feedback regulation at transcription level. This hierarchical structure builds the basis for a new and simple decomposition method which is suitable for the identification of functional modules and global regulators in the transcriptional regulatory network of E

Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

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Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P; Gerstein, Mark

2010-05-18

The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers' continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems.

Inference of gene regulatory networks with sparse structural equation models exploiting genetic perturbations.

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Xiaodong Cai

Full Text Available Integrating genetic perturbations with gene expression data not only improves accuracy of regulatory network topology inference, but also enables learning of causal regulatory relations between genes. Although a number of methods have been developed to integrate both types of data, the desiderata of efficient and powerful algorithms still remains. In this paper, sparse structural equation models (SEMs are employed to integrate both gene expression data and cis-expression quantitative trait loci (cis-eQTL, for modeling gene regulatory networks in accordance with biological evidence about genes regulating or being regulated by a small number of genes. A systematic inference method named sparsity-aware maximum likelihood (SML is developed for SEM estimation. Using simulated directed acyclic or cyclic networks, the SML performance is compared with that of two state-of-the-art algorithms: the adaptive Lasso (AL based scheme, and the QTL-directed dependency graph (QDG method. Computer simulations demonstrate that the novel SML algorithm offers significantly better performance than the AL-based and QDG algorithms across all sample sizes from 100 to 1,000, in terms of detection power and false discovery rate, in all the cases tested that include acyclic or cyclic networks of 10, 30 and 300 genes. The SML method is further applied to infer a network of 39 human genes that are related to the immune function and are chosen to have a reliable eQTL per gene. The resulting network consists of 9 genes and 13 edges. Most of the edges represent interactions reasonably expected from experimental evidence, while the remaining may just indicate the emergence of new interactions. The sparse SEM and efficient SML algorithm provide an effective means of exploiting both gene expression and perturbation data to infer gene regulatory networks. An open-source computer program implementing the SML algorithm is freely available upon request.

An algebra-based method for inferring gene regulatory networks.

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Vera-Licona, Paola; Jarrah, Abdul; Garcia-Puente, Luis David; McGee, John; Laubenbacher, Reinhard

2014-03-26

The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the

Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient.

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Mohamed Salleh, Faridah Hani; Arif, Shereena Mohd; Zainudin, Suhaila; Firdaus-Raih, Mohd

2015-12-01

A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-species biofilm of Candida albicans and non-Candida albicans Candida species on acrylic substrate

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Apurva K Pathak

2012-02-01

Full Text Available OBJECTIVE: In polymicrobial biofilms bacteria extensively interact with Candida species, but the interaction among the different species of the Candida is yet to be completely evaluated. In the present study, the difference in biofilm formation ability of clinical isolates of four species of Candida in both single-species and multi-species combinations on the surface of dental acrylic resin strips was evaluated. MATERIAL AND METHODS: The species of Candida, isolated from multiple species oral candidiasis of the neutropenic patients, were used for the experiment. Organisms were cultured on Sabouraud dextrose broth with 8% glucose (SDB. Biofilm production on the acrylic resins strips was determined by crystal violet assay. Student's t-test and ANOVA were used to compare in vitro biofilm formation for the individual species of Candida and its different multi-species combinations. RESULTS: In the present study, differences between the mean values of the biofilm-forming ability of individual species (C. glabrata>C. krusei>C. tropicalis>C. albicans and in its multi-species' combinations (the highest for C. albicans with C. glabrata and the lowest for all the four species combination were reported. CONCLUSIONS: The findings of this study showed that biofilm-forming ability was found greater for non-Candida albicans Candida species (NCAC than for C. albicans species with intra-species variation. Presence of C. albicans in multi-species biofilms increased, whereas; C. tropicalis decreased the biofilm production with all other NCAC species.

The impact of gene expression variation on the robustness and evolvability of a developmental gene regulatory network.

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David A Garfield

2013-10-01

Full Text Available Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear, allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.

Baicalin prevents Candida albicans infections via increasing its apoptosis rate

Energy Technology Data Exchange (ETDEWEB)

Yang, Shulong; Fu, Yingyuan, E-mail: yingyuanfu@126.com; Wu, Xiuzhen; Zhou, Zhixing; Xu, Jing; Zeng, Xiaoping; Kuang, Nanzhen; Zeng, Yurong

2014-08-15

Highlights: • Baicalin increases the ratio of the G0/G1 stages and C. albicans apoptosis. • Baicalin decreases the proliferation index of C. albicans. • Baicalin inhibits the biosynthesis of DNA, RNA and protein in C. albicans. • Baicalin depresses Succinate Dehydrogenase and Ca{sup 2+}–Mg{sup 2+} ATPase in C. albicans. • Baicalin increases the endocytic free Ca{sup 2+} concentration in C. albicans. - Abstract: Background: These experiments were employed to explore the mechanisms underlying baicalin action on Candida albicans. Methodology and principal findings: We detected the baicalin inhibition effects on three isotope-labeled precursors of {sup 3}H-UdR, {sup 3}H-TdR and {sup 3}H-leucine incorporation into C. albicans using the isotope incorporation technology. The activities of Succinate Dehydrogenase (SDH), cytochrome oxidase (CCO) and Ca{sup 2+}–Mg{sup 2+} ATPase, cytosolic Ca{sup 2+} concentration, the cell cycle and apoptosis, as well as the ultrastructure of C.albicans were also tested. We found that baicalin inhibited {sup 3}H-UdR, {sup 3}H-TdR and {sup 3}H-leucine incorporation into C.albicans (P < 0.005). The activities of the SDH and Ca{sup 2+}–Mg{sup 2+} ATPase of C.albicans in baicalin groups were lower than those in control group (P < 0.05). Ca{sup 2+} concentrations of C. albicans in baicalin groups were much higher than those in control group (P < 0.05). The ratio of C.albicans at the G0/G1 stage increased in baicalin groups in dose dependent manner (P < 0.01). There were a significant differences in the apoptosis rate of C.albicans between baicalin and control groups (P < 0.01). After 12–48 h incubation with baicalin (1 mg/ml), C. albicans shown to be markedly damaged under transmission electron micrographs. Innovation and significance: Baicalin can increase the apoptosis rate of C. albicans. These effects of Baicalin may involved in its inhibiting the activities of the SDH and Ca{sup 2+}–Mg{sup 2+} ATPase, increasing

Data-driven integration of genome-scale regulatory and metabolic network models

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Saheed eImam

2015-05-01

Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

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,

Trichomes: different regulatory networks lead to convergent structures.

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Serna, Laura; Martin, Cathie

2006-06-01

Sometimes, proteins, biological structures or even organisms have similar functions and appearances but have evolved through widely divergent pathways. There is experimental evidence to suggest that different developmental pathways have converged to produce similar outgrowths of the aerial plant epidermis, referred to as trichomes. The emerging picture suggests that trichomes in Arabidopsis thaliana and, perhaps, in cotton develop through a transcriptional regulatory network that differs from those regulating trichome formation in Antirrhinum and Solanaceous species. Several lines of evidence suggest that the duplication of a gene controlling anthocyanin production and subsequent divergence might be the major force driving trichome formation in Arabidopsis, whereas the multicellular trichomes of Antirrhinum and Solanaceous species appear to have a different regulatory origin.

Small RNA-Controlled Gene Regulatory Networks in Pseudomonas putida

DEFF Research Database (Denmark)

Bojanovic, Klara

evolved numerous mechanisms to controlgene expression in response to specific environmental signals. In addition to two-component systems, small regulatory RNAs (sRNAs) have emerged as major regulators of gene expression. The majority of sRNAs bind to mRNA and regulate their expression. They often have...... multiple targets and are incorporated into large regulatory networks and the RNA chaper one Hfq in many cases facilitates interactions between sRNAs and their targets. Some sRNAs also act by binding to protein targets and sequestering their function. In this PhD thesis we investigated the transcriptional....... Detailed insights into the mechanisms through which P. putida responds to different stress conditions and increased understanding of bacterial adaptation in natural and industrial settings were gained. Additionally, we identified genome-wide transcription start sites, andmany regulatory RNA elements...

Inferring the conservative causal core of gene regulatory networks

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Emmert-Streib Frank

2010-09-01

Full Text Available Abstract Background Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. Results In this paper, we introduce a novel gene regulatory network inference (GRNI algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. Conclusions For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

Inferring the conservative causal core of gene regulatory networks.

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Altay, Gökmen; Emmert-Streib, Frank

2010-09-28

Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

Singular Perturbation Analysis and Gene Regulatory Networks with Delay

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Shlykova, Irina; Ponosov, Arcady

2009-09-01

There are different ways of how to model gene regulatory networks. Differential equations allow for a detailed description of the network's dynamics and provide an explicit model of the gene concentration changes over time. Production and relative degradation rate functions used in such models depend on the vector of steeply sloped threshold functions which characterize the activity of genes. The most popular example of the threshold functions comes from the Boolean network approach, where the threshold functions are given by step functions. The system of differential equations becomes then piecewise linear. The dynamics of this system can be described very easily between the thresholds, but not in the switching domains. For instance this approach fails to analyze stationary points of the system and to define continuous solutions in the switching domains. These problems were studied in [2], [3], but the proposed model did not take into account a time delay in cellular systems. However, analysis of real gene expression data shows a considerable number of time-delayed interactions suggesting that time delay is essential in gene regulation. Therefore, delays may have a great effect on the dynamics of the system presenting one of the critical factors that should be considered in reconstruction of gene regulatory networks. The goal of this work is to apply the singular perturbation analysis to certain systems with delay and to obtain an analog of Tikhonov's theorem, which provides sufficient conditions for constracting the limit system in the delay case.

Using network component analysis to dissect regulatory networks mediated by transcription factors in yeast.

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Chun Ye

2009-03-01

Full Text Available Understanding the relationship between genetic variation and gene expression is a central question in genetics. With the availability of data from high-throughput technologies such as ChIP-Chip, expression, and genotyping arrays, we can begin to not only identify associations but to understand how genetic variations perturb the underlying transcription regulatory networks to induce differential gene expression. In this study, we describe a simple model of transcription regulation where the expression of a gene is completely characterized by two properties: the concentrations and promoter affinities of active transcription factors. We devise a method that extends Network Component Analysis (NCA to determine how genetic variations in the form of single nucleotide polymorphisms (SNPs perturb these two properties. Applying our method to a segregating population of Saccharomyces cerevisiae, we found statistically significant examples of trans-acting SNPs located in regulatory hotspots that perturb transcription factor concentrations and affinities for target promoters to cause global differential expression and cis-acting genetic variations that perturb the promoter affinities of transcription factors on a single gene to cause local differential expression. Although many genetic variations linked to gene expressions have been identified, it is not clear how they perturb the underlying regulatory networks that govern gene expression. Our work begins to fill this void by showing that many genetic variations affect the concentrations of active transcription factors in a cell and their affinities for target promoters. Understanding the effects of these perturbations can help us to paint a more complete picture of the complex landscape of transcription regulation. The software package implementing the algorithms discussed in this work is available as a MATLAB package upon request.

Regulatory Compliance in Multi-Tier Supplier Networks

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Goossen, Emray R.; Buster, Duke A.

2014-01-01

Over the years, avionics systems have increased in complexity to the point where 1st tier suppliers to an aircraft OEM find it financially beneficial to outsource designs of subsystems to 2nd tier and at times to 3rd tier suppliers. Combined with challenging schedule and budgetary pressures, the environment in which safety-critical systems are being developed introduces new hurdles for regulatory agencies and industry. This new environment of both complex systems and tiered development has raised concerns in the ability of the designers to ensure safety considerations are fully addressed throughout the tier levels. This has also raised questions about the sufficiency of current regulatory guidance to ensure: proper flow down of safety awareness, avionics application understanding at the lower tiers, OEM and 1st tier oversight practices, and capabilities of lower tier suppliers. Therefore, NASA established a research project to address Regulatory Compliance in a Multi-tier Supplier Network. This research was divided into three major study efforts: 1. Describe Modern Multi-tier Avionics Development 2. Identify Current Issues in Achieving Safety and Regulatory Compliance 3. Short-term/Long-term Recommendations Toward Higher Assurance Confidence This report presents our findings of the risks, weaknesses, and our recommendations. It also includes a collection of industry-identified risks, an assessment of guideline weaknesses related to multi-tier development of complex avionics systems, and a postulation of potential modifications to guidelines to close the identified risks and weaknesses.

A systems biology approach to construct the gene regulatory network of systemic inflammation via microarray and databases mining

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Lan Chung-Yu

2008-09-01

Full Text Available Abstract Background Inflammation is a hallmark of many human diseases. Elucidating the mechanisms underlying systemic inflammation has long been an important topic in basic and clinical research. When primary pathogenetic events remains unclear due to its immense complexity, construction and analysis of the gene regulatory network of inflammation at times becomes the best way to understand the detrimental effects of disease. However, it is difficult to recognize and evaluate relevant biological processes from the huge quantities of experimental data. It is hence appealing to find an algorithm which can generate a gene regulatory network of systemic inflammation from high-throughput genomic studies of human diseases. Such network will be essential for us to extract valuable information from the complex and chaotic network under diseased conditions. Results In this study, we construct a gene regulatory network of inflammation using data extracted from the Ensembl and JASPAR databases. We also integrate and apply a number of systematic algorithms like cross correlation threshold, maximum likelihood estimation method and Akaike Information Criterion (AIC on time-lapsed microarray data to refine the genome-wide transcriptional regulatory network in response to bacterial endotoxins in the context of dynamic activated genes, which are regulated by transcription factors (TFs such as NF-κB. This systematic approach is used to investigate the stochastic interaction represented by the dynamic leukocyte gene expression profiles of human subject exposed to an inflammatory stimulus (bacterial endotoxin. Based on the kinetic parameters of the dynamic gene regulatory network, we identify important properties (such as susceptibility to infection of the immune system, which may be useful for translational research. Finally, robustness of the inflammatory gene network is also inferred by analyzing the hubs and "weak ties" structures of the gene network

Regional and International Networking to Support the Energy Regulatory Commission of Thailand

Energy Technology Data Exchange (ETDEWEB)

Lavansiri, Direk; Bull, Trevor

2010-09-15

The Energy Regulatory Commission of Thailand is a new regulatory agency. The structure of the energy sector; the tradition of administration; and, the lack of access to experienced personnel in Thailand all pose particular challenges. The Commission is meeting these challenges through regional and international networking to assist in developing policies and procedures that allow it to meet international benchmarks.

Frequency of Candida albicans in Patients with Funguria

International Nuclear Information System (INIS)

Jamil, S.; Jamil, N.; Hafiz, S.; Siddiqui, S.; Saad, U.

2016-01-01

Objective: To determine the frequency of Candida albicans in patients with funguria. Study Design: Descriptive cross-sectional study. Place and Duration of Study: Department of Microbiology, Sindh Institute of Urology and Transplantation, from July to December 2012. Methodology: Patients urine samples with fungus/Candida were included. Candida albicans was identified by the production of tubular structures (germ tubes) on microscopy as per standard procedure followed by inoculation on Chrom agar (Oxoid) and Corn Meal-Tween 80 agar (Oxoid). The identification of other non-albicans Candida species was also done both microscopically and macroscopically as per standard procedure. Results: Out of the 289 isolates, 204 (70.6 percentage) were male patients and 85 (29.4 percentage) were female patients, with 165 (57.1 percentage) from the out-patients and 124 (42.9 percentage) from the in-patients. Five species of Candida were found to be prevalent including 87 (30.1 percentage) Candida albicans, 176 (60.9 percentage) Candida tropicalis, 14 (4.8 percentage) Candida parapsilosis, 8 (2.8 percentage) Candida glabrata and 4 (1.4 percentage) Candida lusitaniae. Majority of patients with funguria were aged above 50 years (60.2 percentage). Conclusion: In the present study, 30.1 percentage patients with funguria had Candida albicans. The most frequently isolated species was Candida tropicalis (60.9 percentage), followed by other non-albicans Candida. This study has shown the emergence of non-albicans Candida as a major cause of candiduria. (author)

In vitro modification of Candida albicans invasiveness.

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Fontenla de Petrino, S E; de Jorrat, M E; Sirena, A; Valdez, J C; Mesón, O

1986-05-01

Candida albicans produces germ-tubes (GT) when it is incubated in animal or human serum. This dimorphism is responsible for its invasive ability. The purpose of the present paper is (1) to evaluate the ability of rat peritoneal macrophages to inhibit GT production of ingested Candida albicans, obtained from immunized rats and then activated in vitro with Candida-induced lymphokines; (2) to determinate any possible alteration of phagocytic and candidacidal activities. The phagocytes were obtained from rats immunized with viable C. albicans. Some of them were exposed to Candida-induced lymphokines in order to activate the macrophages in vitro. The monolayers of activated, immune and normal macrophages were infected with a C. albicans suspension during 4 hr. Activated macrophages presented not only the highest phagocytic and candidacidal activities but a noticeable inhibition of GT formation and incremented candidacidal activity.

Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence.

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Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

2016-01-01

We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case.

Inferring the role of transcription factors in regulatory networks

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Le Borgne Michel

2008-05-01

Full Text Available Abstract Background Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple organisms up to higher eukaryotes. Admittedly, a key ingredient in developing a reconstruction method is its ability to integrate heterogeneous sources of information, as well as to comply with practical observability issues: measurements can be scarce or noisy. In this work, we show how to combine a network of genetic regulations with a set of expression profiles, in order to infer the functional effect of the regulations, as inducer or repressor. Our approach is based on a consistency rule between a network and the signs of variation given by expression arrays. Results We evaluate our approach in several settings of increasing complexity. First, we generate artificial expression data on a transcriptional network of E. coli extracted from the literature (1529 nodes and 3802 edges, and we estimate that 30% of the regulations can be annotated with about 30 profiles. We additionally prove that at most 40.8% of the network can be inferred using our approach. Second, we use this network in order to validate the predictions obtained with a compendium of real expression profiles. We describe a filtering algorithm that generates particularly reliable predictions. Finally, we apply our inference approach to S. cerevisiae transcriptional network (2419 nodes and 4344 interactions, by combining ChIP-chip data and 15 expression profiles. We are able to detect and isolate inconsistencies between the expression profiles and a significant portion of the model (15% of all the interactions. In addition, we report predictions for 14.5% of all interactions. Conclusion Our approach does not require accurate expression levels nor times series. Nevertheless, we show on both data, real and artificial, that a relatively small number of perturbation experiments are enough to determine

Genomic and Phenotypic Variation in Morphogenetic Networks of Two Candida albicans Isolates Subtends Their Different Pathogenic Potential

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Duccio Cavalieri

2018-01-01

Full Text Available The transition from commensalism to pathogenicity of Candida albicans reflects both the host inability to mount specific immune responses and the microorganism’s dimorphic switch efficiency. In this study, we used whole genome sequencing and microarray analysis to investigate the genomic determinants of the phenotypic changes observed in two C. albicans clinical isolates (YL1 and YQ2. In vitro experiments employing epithelial, microglial, and peripheral blood mononuclear cells were thus used to evaluate C. albicans isolates interaction with first line host defenses, measuring adhesion, susceptibility to phagocytosis, and induction of secretory responses. Moreover, a murine model of peritoneal infection was used to compare the in vivo pathogenic potential of the two isolates. Genome sequence and gene expression analysis of C. albicans YL1 and YQ2 showed significant changes in cellular pathways involved in environmental stress response, adhesion, filamentous growth, invasiveness, and dimorphic transition. This was in accordance with the observed marked phenotypic differences in biofilm production, dimorphic switch efficiency, cell adhesion, invasion, and survival to phagocyte-mediated host defenses. The mutations in key regulators of the hyphal growth pathway in the more virulent strain corresponded to an overall greater number of budding yeast cells released. Compared to YQ2, YL1 consistently showed enhanced pathogenic potential, since in vitro, it was less susceptible to ingestion by phagocytic cells and more efficient in invading epithelial cells, while in vivo YL1 was more effective than YQ2 in recruiting inflammatory cells, eliciting IL-1β response and eluding phagocytic cells. Overall, these results indicate an unexpected isolate-specific variation in pathways important for host invasion and colonization, showing how the genetic background of C. albicans may greatly affect its behavior both in vitro and in vivo. Based on this approach, we

On the role of sparseness in the evolution of modularity in gene regulatory networks.

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Espinosa-Soto, Carlos

2018-05-01

Modularity is a widespread property in biological systems. It implies that interactions occur mainly within groups of system elements. A modular arrangement facilitates adjustment of one module without perturbing the rest of the system. Therefore, modularity of developmental mechanisms is a major factor for evolvability, the potential to produce beneficial variation from random genetic change. Understanding how modularity evolves in gene regulatory networks, that create the distinct gene activity patterns that characterize different parts of an organism, is key to developmental and evolutionary biology. One hypothesis for the evolution of modules suggests that interactions between some sets of genes become maladaptive when selection favours additional gene activity patterns. The removal of such interactions by selection would result in the formation of modules. A second hypothesis suggests that modularity evolves in response to sparseness, the scarcity of interactions within a system. Here I simulate the evolution of gene regulatory networks and analyse diverse experimentally sustained networks to study the relationship between sparseness and modularity. My results suggest that sparseness alone is neither sufficient nor necessary to explain modularity in gene regulatory networks. However, sparseness amplifies the effects of forms of selection that, like selection for additional gene activity patterns, already produce an increase in modularity. That evolution of new gene activity patterns is frequent across evolution also supports that it is a major factor in the evolution of modularity. That sparseness is widespread across gene regulatory networks indicates that it may have facilitated the evolution of modules in a wide variety of cases.

Jimena: efficient computing and system state identification for genetic regulatory networks.

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Karl, Stefan; Dandekar, Thomas

2013-10-11

Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed. (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones). Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior.

Frequency of Candida albicans in Patients with Funguria.

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Jamil, Sana; Jamil, Naz; Saad, Uzma; Hafiz, Saleem; Siddiqui, Sualleha

2016-02-01

To determine the frequency of Candida albicansin patients with funguria. Descriptive cross-sectional study. Department of Microbiology, Sindh Institute of Urology and Transplantation, from July to December 2012. Patients’ urine samples with fungus/Candida were included. Candida albicans was identified by the production of tubular structures (germ tubes) on microscopy as per standard procedure followed by inoculation on Chrom agar (Oxoid) and Corn Meal-Tween 80 agar (Oxoid). The identification of other non-albicans Candidaspecies was also done both microscopically and macroscopically as per standard procedure. Out of the 289 isolates, 204 (70.6%) were male patients and 85 (29.4%) were female patients, with 165 (57.1%) from the out-patients and 124 (42.9%) from the in-patients. Five species of Candidawere found to be prevalent including 87 (30.1%) Candida albicans, 176 (60.9%) Candida tropicalis, 14 (4.8%) Candida parapsilosis, 8 (2.8%) Candida glabrata and 4 (1.4%) Candida lusitaniae. Majority of patients with funguria were aged above 50 years (60.2%). In the present study, 30.1% patients with funguria had Candida albicans. The most frequently isolated species was Candida tropicalis(60.9%), followed by other non-albicansCandida. This study has shown the emergence of non-albicans Candidaas a major cause of candiduria.

Integration of steady-state and temporal gene expression data for the inference of gene regulatory networks.

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Wang, Yi Kan; Hurley, Daniel G; Schnell, Santiago; Print, Cristin G; Crampin, Edmund J

2013-01-01

We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and time-series data sets can successfully be combined to identify gene regulatory interactions using the new algorithm. Inferring gene networks from combined data sets was found to be advantageous when using noisy measurements collected with either lower sampling rates or a limited number of experimental replicates. We illustrate our method by applying it to a microarray gene expression dataset from human umbilical vein endothelial cells (HUVECs) which combines time series data from treatment with growth factor TNF and steady state data from siRNA knockdown treatments. Our results suggest that the combination of steady-state and time-series datasets may provide better prediction of RNA-to-RNA interactions, and may also reveal biological features that cannot be identified from dynamic or steady state information alone. Finally, we consider the experimental design of genomics experiments for gene regulatory network inference and show that network inference can be improved by incorporating steady-state measurements with time-series data.

Dissecting microregulation of a master regulatory network

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Kaimal Vivek

2008-02-01

Full Text Available Abstract Background The master regulator p53 tumor-suppressor protein through coordination of several downstream target genes and upstream transcription factors controls many pathways important for tumor suppression. While it has been reported that some of the p53's functions are microRNA-mediated, it is not known as to how many other microRNAs might contribute to the p53-mediated tumorigenesis. Results Here, we use bioinformatics-based integrative approach to identify and prioritize putative p53-regulated miRNAs, and unravel the miRNA-based microregulation of the p53 master regulatory network. Specifically, we identify putative microRNA regulators of a transcription factors that are upstream or downstream to p53 and b p53 interactants. The putative p53-miRs and their targets are prioritized using current knowledge of cancer biology and literature-reported cancer-miRNAs. Conclusion Our predicted p53-miRNA-gene networks strongly suggest that coordinated transcriptional and p53-miR mediated networks could be integral to tumorigenesis and the underlying processes and pathways.

Interplay between Candida albicans and the Mammalian Innate Host Defense

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Cheng, Shih-Chin; Joosten, Leo A. B.; Kullberg, Bart-Jan

2012-01-01

Candida albicans is both the most common fungal commensal microorganism in healthy individuals and the major fungal pathogen causing high mortality in at-risk populations, especially immunocompromised patients. In this review, we summarize the interplay between the host innate system and C. albicans, ranging from how the host recognizes, responds, and clears C. albicans infection to how C. albicans evades, dampens, and escapes from host innate immunity. PMID:22252867

The pairwise disconnectivity index as a new metric for the topological analysis of regulatory networks

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Wingender Edgar

2008-05-01

Full Text Available Abstract Background Currently, there is a gap between purely theoretical studies of the topology of large bioregulatory networks and the practical traditions and interests of experimentalists. While the theoretical approaches emphasize the global characterization of regulatory systems, the practical approaches focus on the role of distinct molecules and genes in regulation. To bridge the gap between these opposite approaches, one needs to combine 'general' with 'particular' properties and translate abstract topological features of large systems into testable functional characteristics of individual components. Here, we propose a new topological parameter – the pairwise disconnectivity index of a network's element – that is capable of such bridging. Results The pairwise disconnectivity index quantifies how crucial an individual element is for sustaining the communication ability between connected pairs of vertices in a network that is displayed as a directed graph. Such an element might be a vertex (i.e., molecules, genes, an edge (i.e., reactions, interactions, as well as a group of vertices and/or edges. The index can be viewed as a measure of topological redundancy of regulatory paths which connect different parts of a given network and as a measure of sensitivity (robustness of this network to the presence (absence of each individual element. Accordingly, we introduce the notion of a path-degree of a vertex in terms of its corresponding incoming, outgoing and mediated paths, respectively. The pairwise disconnectivity index has been applied to the analysis of several regulatory networks from various organisms. The importance of an individual vertex or edge for the coherence of the network is determined by the particular position of the given element in the whole network. Conclusion Our approach enables to evaluate the effect of removing each element (i.e., vertex, edge, or their combinations from a network. The greatest potential value of

Phenotypic stability and plasticity in GMP-derived cells as determined by their underlying regulatory network.

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Ramírez, Carlos; Mendoza, Luis

2018-04-01

Blood cell formation has been recognized as a suitable system to study celular differentiation mainly because of its experimental accessibility, and because it shows characteristics such as hierarchical and gradual bifurcated patterns of commitment, which are present in several developmental processes. Although hematopoiesis has been extensively studied and there is a wealth of molecular and cellular data about it, it is not clear how the underlying molecular regulatory networks define or restrict cellular differentiation processes. Here, we infer the molecular regulatory network that controls the differentiation of a blood cell subpopulation derived from the granulocyte-monocyte precursor (GMP), comprising monocytes, neutrophils, eosinophils, basophils and mast cells. We integrate published qualitative experimental data into a model to describe temporal expression patterns observed in GMP-derived cells. The model is implemented as a Boolean network, and its dynamical behavior is studied. Steady states of the network can be clearly identified with the expression profiles of monocytes, mast cells, neutrophils, basophils, and eosinophils, under wild-type and mutant backgrounds. All scripts are publicly available at https://github.com/caramirezal/RegulatoryNetworkGMPModel. lmendoza@biomedicas.unam.mx. Supplementary data are available at Bioinformatics online.

Statistical identification of gene association by CID in application of constructing ER regulatory network

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Lien Huang-Chun

2009-03-01

Full Text Available Abstract Background A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID, is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs (X and their downstream genes (Y based on clinical data. More specifically, we use estrogen receptor α (ERα as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A. Results The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC, Student's t-test (STT, coefficient of determination (CoD, and mutual information (MI. When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y against a discrete variable (X, it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays. Conclusion CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the

Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees

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Chen Xiaoyu

2007-12-01

Full Text Available Abstract Background In vertebrates, a large part of gene transcriptional regulation is operated by cis-regulatory modules. These modules are believed to be regulating much of the tissue-specificity of gene expression. Results We develop a Bayesian network approach for identifying cis-regulatory modules likely to regulate tissue-specific expression. The network integrates predicted transcription factor binding site information, transcription factor expression data, and target gene expression data. At its core is a regression tree modeling the effect of combinations of transcription factors bound to a module. A new unsupervised EM-like algorithm is developed to learn the parameters of the network, including the regression tree structure. Conclusion Our approach is shown to accurately identify known human liver and erythroid-specific modules. When applied to the prediction of tissue-specific modules in 10 different tissues, the network predicts a number of important transcription factor combinations whose concerted binding is associated to specific expression.

Neural model of gene regulatory network: a survey on supportive meta-heuristics.

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Biswas, Surama; Acharyya, Sriyankar

2016-06-01

Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through various mathematical and computational schemes and reported in survey articles. Neural and neuro-fuzzy models have been the focus of attraction in bioinformatics. Predominant use of meta-heuristic algorithms in training neural models has proved its excellence. Considering these facts, this paper is organized to survey neural modelling schemes of GRN and the efficacy of meta-heuristic algorithms towards parameter learning (i.e. weighting connections) within the model. This survey paper renders two different structure-related approaches to infer GRN which are global structure approach and substructure approach. It also describes two neural modelling schemes, such as artificial neural network/recurrent neural network based modelling and neuro-fuzzy modelling. The meta-heuristic algorithms applied so far to learn the structure and parameters of neutrally modelled GRN have been reviewed here.

Detection of phospholipase activity of Candida albicans and non albicans isolated from women of reproductive age with vulvovaginal candidiasis in rural area

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S R Fule

2015-01-01

Full Text Available Background: Vulvovaginal candidiasis (VVC is most common accounting for 17 to 39% of symptomatic women. Both Candida albicans and non albicans Candida species are involved in VVC. Amongst various virulence factors proposed for Candida, extracellular phospholipases is one of the virulence factor implicated in its pathogenicity. With this background the present study was carried out to find the prevalence of different Candida species and to detect phospholipase producing strains isolated from symptomatic women with VVC. Materials and Methods: At least two vaginal swabs from 156 women of reproductive age with abnormal vaginal discharge were collected. Direct microscopy and Gram′s stained smear examined for presence of budding yeast and pseudo mycelia followed by isolation and identification of Candida species. Extracellular phospholipase activity was studied by inoculating all isolates on Sabouraud′s dextrose egg yolk agar (SDA medium. Results: Of the 156 women with curdy white discharge alone or in combination with other signs, 59 (37.82% women showed laboratory evidence of VVC. A total of 31 (52.54% women had curdy white discharge followed by 12 (20.33% with other signs and symptoms. C. albicans (62.59% and non albicans Candida (37.28% in a ratio of 1.68:1 were isolated. Of the 37 strains of C. albians 30 (81.08% showed the enzyme activity. Seventeen (56.66% strains showed higher Pz value of < 0.70 (++++. Conclusion: Although there may be typical clinical presentation of Candidiasis. all the patients did not show laboratory evidence of infection. Pregnancy was found to be major risk factor for development of VVC. C. albicans was prevalent species but non albicans species were also frequently isolated. Extracellular phospholipase activity was seen in C. albicans and not in non albicans Candida isolates.

Allergen cross-reactivity between Pityrosporum orbiculare and Candida albicans.

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Huang, X; Johansson, S G; Zargari, A; Nordvall, S L

1995-08-01

Pityrosporum orbiculare and Candida albicans extracts were separated by SDS-PAGE, and IgE binding was detected by immunoblotting with 21 patient sera that were RAST positive to both yeasts. Cross-wise inhibition was performed of IgE binding of a serum pool containing IgE antibodies to both yeasts. The pool was mixed with serial dilutions of P. orbiculare or C. albicans extracts, and incubated with strips containing separated allergen. IgE binding was quantified by densitometric scanning and percent inhibition was calculated as well as the respective ratios between required extract concentration for 50% inhibition in heterologous compared to homologous inhibition for each component (inhibition ratio). Ten components of P. orbiculare were detected by more than 60% of the sera. IgE binding to C. albicans was weak, and only to four bands was IgE binding detected by more than 30% of the sera. The most important C. albicans allergen was a 48-kDa band, to which IgE of half of the patient sera bound. There was little inhibition of IgE binding to P. orbiculare with C. albicans. Thus, all but three components exhibited an inhibition ratio higher than 100. The inhibition ratio of the 48-kDa C. albicans compound was 50, thus indicating some degree of cross-reactivity. Significant cross-reactivity was shown by C. albicans compounds of 18, 24, 26, 34, and 38 kDa, the inhibition ratios of which were less than 10. There was some degree of cross-reactivity between apparent protein allergens of the two yeasts, but IgE antibodies to C. albicans do not merely reflect sensitization to P. orbiculare.

Elderly nutritional status effection salivary anticandidal capacity against Candida albicans

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Ria Puspitawati

2011-06-01

Full Text Available Background: Elderly often suffer malnutrition and oral candidiasis. Candida albicans (C. albicans which is the most prominent cause of oral candidiasis, is one of commensal oral micro-flora. Nutritional status affect the characteristic of saliva. Saliva is the regulator in the development of C. albicans from comensal into pathogen. Purpose: The purpose of this study was to determining the correlation between elderly nutritional status with salivary total protein and its activity in inhibiting C. albicans growth and biofilm formation. Methods: Using mini nutritional assessment 30 elderly were classified into normal and malnutrition groups. Total protein of unstimulated saliva was measured using Bradford protein assay. The colony forming unit (CFU of C. albicans was counted on 72 hours on SDA cultures without (control or with 2 hour saliva exposure. Biofilm formation was analyzed from the optical density of 10–5 C. albicans suspension without saliva exposure (control or with exposure of 10.000 μg/ml saliva and incubated in 37° C for 2 days. The suspension was put into 96 well plates, stained with crystal-violet dye, and analyzed using microplate reader. Differences between groups were analyzed using independent t-test or Kruskall-Wallis. Correlation between variables was analyzed using Spearman test. Results: Salivary total protein of normal elderly (1.113.5 ± 1.1143.3 was higher than those of malnutrition (613.6 ± 253.6 but not statistically significant (p > 0.05. The CFU of C. albicans exposed to saliva of normal samples (2.060 cfu/ml was significantly lower than control (24.100 cfu/ml and those exposed to malnutrition saliva (5.513.3 cfu/ml. C. albicans biofilm formation is highest in controls (0.177, lower in those exposed to malnourished saliva (0.151 and lowest in those exposed to saliva of good nourished elderly (0.133. Conclusion: Although does not cause significant decrease of salivary total protein, malnutrition in elderly results

The Candida albicans Biofilm Matrix: Composition, Structure and Function.

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Pierce, Christopher G; Vila, Taissa; Romo, Jesus A; Montelongo-Jauregui, Daniel; Wall, Gina; Ramasubramanian, Anand; Lopez-Ribot, Jose L

2017-03-01

A majority of infections caused by Candida albicans -the most frequent fungal pathogen-are associated with biofilm formation. A salient feature of C. albicans biofilms is the presence of the biofilm matrix. This matrix is composed of exopolymeric materials secreted by sessile cells within the biofilm, in which all classes of macromolecules are represented, and provides protection against environmental challenges. In this review, we summarize the knowledge accumulated during the last two decades on the composition, structure, and function of the C. albicans biofilm matrix. Knowledge of the matrix components, its structure, and function will help pave the way to novel strategies to combat C. albicans biofilm infections.

Comparative transcript profiling of Candida albicans and Candida dubliniensis identifies SFL2, a C. albicans gene required for virulence in a reconstituted epithelial infection model.

LENUS (Irish Health Repository)

Spiering, Martin J

2010-02-01

Candida albicans and Candida dubliniensis are closely related species displaying differences in virulence and genome content, therefore providing potential opportunities to identify novel C. albicans virulence genes. C. albicans gene arrays were used for comparative analysis of global gene expression in the two species in reconstituted human oral epithelium (RHE). C. albicans (SC5314) showed upregulation of hypha-specific and virulence genes within 30 min postinoculation, coinciding with rapid induction of filamentation and increased RHE damage. C. dubliniensis (CD36) showed no detectable upregulation of hypha-specific genes, grew as yeast, and caused limited RHE damage. Several genes absent or highly divergent in C. dubliniensis were upregulated in C. albicans. One such gene, SFL2 (orf19.3969), encoding a putative heat shock factor, was deleted in C. albicans. DeltaDeltasfl2 cells failed to filament under a range of hypha-inducing conditions and exhibited greatly reduced RHE damage, reversed by reintroduction of SFL2 into the DeltaDeltasfl2 strain. Moreover, SFL2 overexpression in C. albicans triggered hyphal morphogenesis. Although SFL2 deletion had no apparent effect on host survival in the murine model of systemic infection, DeltaDeltasfl2 strain-infected kidney tissues contained only yeast cells. These results suggest a role for SFL2 in morphogenesis and an indirect role in C. albicans pathogenesis in epithelial tissues.

Modulation of Candida albicans virulence by bacterial biofilms on titanium surfaces.

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Cavalcanti, Yuri Wanderley; Wilson, Melanie; Lewis, Michael; Del-Bel-Cury, Altair Antoninha; da Silva, Wander José; Williams, David W

2016-01-01

Whilst Candida albicans occurs in peri-implant biofilms, its role in peri-implantitis remains unclear. This study therefore examined the virulence of C. albicans in mixed-species biofilms on titanium surfaces. Biofilms of C. albicans (Ca), C. albicans with streptococci (Streptococcus sanguinis, S. mutans) (Ca-Ss-Sm) and those incorporating Porphyromonas gingivalis (Ca-Pg and Ca-Ss-Sm-Pg) were developed. Expression of C. albicans genes associated with adhesion (ALS1, ALS3, HWP1) and hydrolytic enzymes (SAP2, SAP4, SAP6, PLD1) was measured and hyphal production by C. albicans quantified. Compared with Ca biofilms, significant (pbiofilms containing streptococci (Ca-Ss-Sm). In Ca-Pg biofilms, down-regulation of HWP1 and SAP4 expression, with reduced hyphal production occurred. Ca-Ss-Sm-Pg biofilms had increased hyphal proportions and up-regulation of ALS3, SAP2 and SAP6. In conclusion, C. albicans expressed virulence factors in biofilms that could contribute to peri-implantitis, but this was dependent on associated bacterial species.

Network regulation and regulatory institutional reform: Revisiting the case of Australia

International Nuclear Information System (INIS)

Nepal, Rabindra; Menezes, Flavio; Jamasb, Tooraj

2014-01-01

It is well-understood that the success of liberalizing the electricity supply industry depends crucially on the quality and design of the regulatory and institutional framework. This paper analyses the regulatory arrangements that underpin the work of the Australian Energy Regulator (AER). These arrangements are contrasted with the regulatory structure of electricity provision in Norway. A key difference between the reform processes in the two countries relates to the lack of privatization in Norway and the co-existence of private and publicly owned generators and distributors in Australia. This comparative analysis allows us to make several recommendations to improve regulatory arrangements in Australia. These include greater independence for the AER, better coordination among regulatory institutions, greater use of benchmarking analysis, greater customer involvement, and improving market transparency and privatization of government-owned corporations. However, the success of privatization will hinge upon the effectiveness of the regulatory environment. - Highlights: • Rising electricity prices and network costs is of great concern in Australia. • Flaws in the existing regulatory environment and economic efficiency exist. • The AER should be provided with adequate resources (financial and staff experts) and discretion. • Robust benchmarking techniques should be adopted in the incentive regulation framework for cost efficiency. • Privatization of the state-owned assets also remains an option

Budding off: bringing functional genomics to Candida albicans

Science.gov (United States)

Anderson, Matthew Z.

2016-01-01

Candida species are the most prevalent human fungal pathogens, with Candida albicans being the most clinically relevant species. Candida albicans resides as a commensal of the human gastrointestinal tract but is a frequent cause of opportunistic mucosal and systemic infections. Investigation of C. albicans virulence has traditionally relied on candidate gene approaches, but recent advances in functional genomics have now facilitated global, unbiased studies of gene function. Such studies include comparative genomics (both between and within Candida species), analysis of total RNA expression, and regulation and delineation of protein–DNA interactions. Additionally, large collections of mutant strains have begun to aid systematic screening of clinically relevant phenotypes. Here, we will highlight the development of functional genomics in C. albicans and discuss the use of these approaches to addressing both commensalism and pathogenesis in this species. PMID:26424829

Deciphering Fur transcriptional regulatory network highlights its complex role beyond iron metabolism in Escherichia coli

DEFF Research Database (Denmark)

Seo, Sang Woo; Kim, Donghyuk; Latif, Haythem

2014-01-01

The ferric uptake regulator (Fur) plays a critical role in the transcriptional regulation of iron metabolism. However, the full regulatory potential of Fur remains undefined. Here we comprehensively reconstruct the Fur transcriptional regulatory network in Escherichia coli K-12 MG1655 in response...

Farnesol signalling in Candida albicans - more than just communication.

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Polke, Melanie; Leonhardt, Ines; Kurzai, Oliver; Jacobsen, Ilse D

2018-03-01

Candida albicans is a successful colonizer of the human host, which can, under certain circumstances cause a range of clinically diverse infections. Important virulence-associated traits of the fungus, such as the dimorphic switch and biofilm formation, are controlled by the quorum sensing molecule farnesol. Given the potential of farnesol as a novel antifungal drug, there has been increasing research into the mechanism underlying farnesol sensing and action in C. albicans. However, despite the identification of various factors involved in farnesol signalling, its exact mode of action remains largely unclear. This review provides an overview of the currently known aspects of farnesol production, sensing and action within C. albicans. We also illustrate the characteristic of C. albicans to simultaneously produce and tolerate high farnesol concentrations that are lethal to other microbes. Furthermore, we summarize new literature on the role of farnesol in the interaction of C. albicans with the human host and highlight its action as a potent immunomodulatory molecule.

A network of paralogous stress response transcription factors in the human pathogen Candida glabrata.

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Jawad eMerhej

2016-05-01

Full Text Available The yeast Candida glabrata has become the second cause of systemic candidemia in humans. However, relatively few genome-wide studies have been conducted in this organism and our knowledge of its transcriptional regulatory network is quite limited. In the present work, we combined genome-wide chromatin immunoprecipitation (ChIP-seq, transcriptome analyses and DNA binding motif predictions to describe the regulatory interactions of the seven Yap (Yeast AP1 transcription factors of C. glabrata. We described a transcriptional network containing 255 regulatory interactions and 309 potential target genes. We predicted with high confidence the preferred DNA binding sites for 5 of the 7 CgYaps and showed a strong conservation of the Yap DNA binding properties between S. cerevisiae and C. glabrata. We provided reliable functional annotation for 3 of the 7 Yaps and identified for Yap1 and Yap5 a core regulon which is conserved in S. cerevisiae, C. glabrata and C. albicans. We uncovered new roles for CgYap7 in the regulation of iron-sulfur cluster biogenesis, for CgYap1 in the regulation of heme biosynthesis and for CgYap5 in the repression of GRX4 in response to iron starvation. These transcription factors define an interconnected transcriptional network at the cross-roads between redox homeostasis, oxygen consumption and iron metabolism.

The vertebrate Hox gene regulatory network for hindbrain segmentation: Evolution and diversification: Coupling of a Hox gene regulatory network to hindbrain segmentation is an ancient trait originating at the base of vertebrates.

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Parker, Hugo J; Bronner, Marianne E; Krumlauf, Robb

2016-06-01

Hindbrain development is orchestrated by a vertebrate gene regulatory network that generates segmental patterning along the anterior-posterior axis via Hox genes. Here, we review analyses of vertebrate and invertebrate chordate models that inform upon the evolutionary origin and diversification of this network. Evidence from the sea lamprey reveals that the hindbrain regulatory network generates rhombomeric compartments with segmental Hox expression and an underlying Hox code. We infer that this basal feature was present in ancestral vertebrates and, as an evolutionarily constrained developmental state, is fundamentally important for patterning of the vertebrate hindbrain across diverse lineages. Despite the common ground plan, vertebrates exhibit neuroanatomical diversity in lineage-specific patterns, with different vertebrates revealing variations of Hox expression in the hindbrain that could underlie this diversification. Invertebrate chordates lack hindbrain segmentation but exhibit some conserved aspects of this network, with retinoic acid signaling playing a role in establishing nested domains of Hox expression. © 2016 WILEY Periodicals, Inc.

Computational Genetic Regulatory Networks Evolvable, Self-organizing Systems

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Knabe, Johannes F

2013-01-01

Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting fr...

Candida albicans survival and biofilm formation under starvation conditions.

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Ning, Y; Hu, X; Ling, J; Du, Y; Liu, J; Liu, H; Peng, Z

2013-01-01

To investigate the survival and biofilm formation capacity of Candida albicans in starvation and under anaerobic conditions. Candida albicans growth and survival were monitored in vitro for up to 8 months. Fungal suspensions from late exponential, stationary and starvation phases were incubated on human dentine, polystyrene and glass slides. Scanning electron microscopy (SEM) was used to observe the process of biofilm formation. 2,3-bis(2-Methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxyanilide inner salt (XTT) reduction assay was performed to quantify the biofilm formation capability, and confocal laser scanning microscopy (CLSM) was used to study and make semi-quantitative comparisons of the ultrastructure of biofilms formed on human dentine. 'XTT bioactivity' and 'COMSTAT results' were analysed by two-way analysis of variance (ANOVA) and one-way ANOVA, respectively. Candida albicans survived for over six months. SEM demonstrated that starving C. albicans produced mature biofilms on different substrata. C. albicans of the same growth phase incubated on human dentine displayed significantly higher biofilm formation capability than on polystyrene or glass slides (P roughness coefficient and surface/volume ratio (P < 0.05). Candida albicans cells can survive and form biofilms in anaerobic and nutrient-limited conditions and may pose a treatment challenge. © 2012 International Endodontic Journal.

The Tlo Proteins Are Stoichiometric Components of Candida albicans Mediator Anchored via the Med3 Subunit

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Zhang, Anda; Petrov, Kostadin O.; Hyun, Emily R.; Liu, Zhongle; Gerber, Scott A.

2012-01-01

The amplification of the TLO (for telomere-associated) genes in Candida albicans, compared to its less pathogenic, close relative Candida dubliniensis, suggests a role in virulence. Little, however, is known about the function of the Tlo proteins. We have purified the Mediator coactivator complex from C. albicans (caMediator) and found that Tlo proteins are a stoichiometric component of caMediator. Many members of the Tlo family are expressed, and each is a unique member of caMediator. Protein expression analysis of individual Tlo proteins, as well as the purification of tagged Tlo proteins, demonstrate that there is a large free population of Tlo proteins in addition to the Mediator-associated population. Coexpression and copurification of Tloα12 and caMed3 in Escherichia coli established a direct physical interaction between the two proteins. We have also made a C. albicans med3Δ/Δ strain and purified an intact Mediator from this strain. The analysis of the composition of the med3Δ Mediator shows that it lacks a Tlo subunit. Regarding Mediator function, the med3Δ/Δ strain serves as a substitute for the difficult-to-make tloΔ/Δ C. albicans strain. A potential role of the TLO and MED3 genes in virulence is supported by the inability of the med3Δ/Δ strain to form normal germ tubes. This study of caMediator structure provides initial clues to the mechanism of action of the Tlo genes and a platform for further mechanistic studies of caMediator's involvement in gene regulatory patterns that underlie pathogenesis. PMID:22562472

Using consensus bayesian network to model the reactive oxygen species regulatory pathway.

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Liangdong Hu

Full Text Available Bayesian network is one of the most successful graph models for representing the reactive oxygen species regulatory pathway. With the increasing number of microarray measurements, it is possible to construct the bayesian network from microarray data directly. Although large numbers of bayesian network learning algorithms have been developed, when applying them to learn bayesian networks from microarray data, the accuracies are low due to that the databases they used to learn bayesian networks contain too few microarray data. In this paper, we propose a consensus bayesian network which is constructed by combining bayesian networks from relevant literatures and bayesian networks learned from microarray data. It would have a higher accuracy than the bayesian networks learned from one database. In the experiment, we validated the bayesian network combination algorithm on several classic machine learning databases and used the consensus bayesian network to model the Escherichia coli's ROS pathway.

Localizing potentially active post-transcriptional regulations in the Ewing's sarcoma gene regulatory network

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Delyon Bernard

2010-11-01

Full Text Available Abstract Background A wide range of techniques is now available for analyzing regulatory networks. Nonetheless, most of these techniques fail to interpret large-scale transcriptional data at the post-translational level. Results We address the question of using large-scale transcriptomic observation of a system perturbation to analyze a regulatory network which contained several types of interactions - transcriptional and post-translational. Our method consisted of post-processing the outputs of an open-source tool named BioQuali - an automatic constraint-based analysis mimicking biologist's local reasoning on a large scale. The post-processing relied on differences in the behavior of the transcriptional and post-translational levels in the network. As a case study, we analyzed a network representation of the genes and proteins controlled by an oncogene in the context of Ewing's sarcoma. The analysis allowed us to pinpoint active interactions specific to this cancer. We also identified the parts of the network which were incomplete and should be submitted for further investigation. Conclusions The proposed approach is effective for the qualitative analysis of cancer networks. It allows the integrative use of experimental data of various types in order to identify the specific information that should be considered a priority in the initial - and possibly very large - experimental dataset. Iteratively, new dataset can be introduced into the analysis to improve the network representation and make it more specific.

Candida albicans infection of Caenorhabditis elegans induces antifungal immune defenses.

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Read Pukkila-Worley

2011-06-01

Full Text Available Candida albicans yeast cells are found in the intestine of most humans, yet this opportunist can invade host tissues and cause life-threatening infections in susceptible individuals. To better understand the host factors that underlie susceptibility to candidiasis, we developed a new model to study antifungal innate immunity. We demonstrate that the yeast form of C. albicans establishes an intestinal infection in Caenorhabditis elegans, whereas heat-killed yeast are avirulent. Genome-wide, transcription-profiling analysis of C. elegans infected with C. albicans yeast showed that exposure to C. albicans stimulated a rapid host response involving 313 genes (124 upregulated and 189 downregulated, ~1.6% of the genome many of which encode antimicrobial, secreted or detoxification proteins. Interestingly, the host genes affected by C. albicans exposure overlapped only to a small extent with the distinct transcriptional responses to the pathogenic bacteria Pseudomonas aeruginosa or Staphylococcus aureus, indicating that there is a high degree of immune specificity toward different bacterial species and C. albicans. Furthermore, genes induced by P. aeruginosa and S. aureus were strongly over-represented among the genes downregulated during C. albicans infection, suggesting that in response to fungal pathogens, nematodes selectively repress the transcription of antibacterial immune effectors. A similar phenomenon is well known in the plant immune response, but has not been described previously in metazoans. Finally, 56% of the genes induced by live C. albicans were also upregulated by heat-killed yeast. These data suggest that a large part of the transcriptional response to C. albicans is mediated through "pattern recognition," an ancient immune surveillance mechanism able to detect conserved microbial molecules (so-called pathogen-associated molecular patterns or PAMPs. This study provides new information on the evolution and regulation of the innate

Dynamic Regulatory Network Reconstruction for Alzheimer’s Disease Based on Matrix Decomposition Techniques

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Wei Kong

2014-01-01

Full Text Available Alzheimer’s disease (AD is the most common form of dementia and leads to irreversible neurodegenerative damage of the brain. Finding the dynamic responses of genes, signaling proteins, transcription factor (TF activities, and regulatory networks of the progressively deteriorative progress of AD would represent a significant advance in discovering the pathogenesis of AD. However, the high throughput technologies of measuring TF activities are not yet available on a genome-wide scale. In this study, based on DNA microarray gene expression data and a priori information of TFs, network component analysis (NCA algorithm is applied to determining the TF activities and regulatory influences on TGs of incipient, moderate, and severe AD. Based on that, the dynamical gene regulatory networks of the deteriorative courses of AD were reconstructed. To select significant genes which are differentially expressed in different courses of AD, independent component analysis (ICA, which is better than the traditional clustering methods and can successfully group one gene in different meaningful biological processes, was used. The molecular biological analysis showed that the changes of TF activities and interactions of signaling proteins in mitosis, cell cycle, immune response, and inflammation play an important role in the deterioration of AD.

NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

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Joeri Ruyssinck

Full Text Available One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made

Effect of Xylitol on Candida albicans resistance in serum (in vitro study

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Ria Puspitawati

2013-07-01

Full Text Available Xylitol is reported to inhibit the growth of C. albicans. Objectives: Investigating serum factor role in inhibiting the growth of C. albicans and the effect of 1%, 5%, 10% xylitol on C. albicans resistance in serum in vitro. Methods: Identification of C. albicans (oral swab of candidiasis patient was conducted using CHROMAgar, confirmed by germ tube test. The cultures were serially diluted, inoculated in Saburoud Dextrose Broth (SDB contained 0% (control, 1%, 5%, or 10% xylitol, and kept for 3 or 7 days. These inoculations were then exposed to either active or inactive serum (Fetal Bovine Serum heated in 65ºC for 30 minutes for 2 hours in 37ºC. The colony forming unit (CFU of C. albicans in Saburoud Dextrose Agar (SDA were counted after 2 days. C. albicans ATCC 10231 strain was used as a comparison. One-way ANOVA with 0.05 was used. Results: After 3 days cultured in media with or without xylitol, the CFU of C. albicans exposed to active serum were significantly lower than those exposed to inactive serum (p=0.032. Although not statistically significant (p=0.689, increased concentration of xylitol lead to increased resistance of C. albicans in active serum. Only 7 day exposure of 10% xylitol resulted in significantly higher growth of C. albicans (p=0.034. No significant difference of C. albicans CFU in active or inactive serum (p=0.404. Conclusion: Serum factor has role in inhibiting C. albicans growth in vitro. Exposure of 1%, 5%, or 10% xylitol for 3 or 7 days has no significant effect on C. albicans resistance in serum.DOI: 10.14693/jdi.v16i2.98

Molecular genetic techniques for gene manipulation in Candida albicans.

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Xu, Qiu-Rong; Yan, Lan; Lv, Quan-Zhen; Zhou, Mi; Sui, Xue; Cao, Yong-Bing; Jiang, Yuan-Ying

2014-05-15

Candida albicans is one of the most common fungal pathogen in humans due to its high frequency as an opportunistic and pathogenic fungus causing superficial as well as invasive infections in immunocompromised patients. An understanding of gene function in C. albicans is necessary to study the molecular basis of its pathogenesis, virulence and drug resistance. Several manipulation techniques have been used for investigation of gene function in C. albicans, including gene disruption, controlled gene expression, protein tagging, gene reintegration, and overexpression. In this review, the main cassettes containing selectable markers used for gene manipulation in C. albicans are summarized; the advantages and limitations of these cassettes are discussed concerning the influences on the target gene expression and the virulence of the mutant strains.

Construction of an integrated gene regulatory network link to stress-related immune system in cattle.

Science.gov (United States)

Behdani, Elham; Bakhtiarizadeh, Mohammad Reza

2017-10-01

The immune system is an important biological system that is negatively impacted by stress. This study constructed an integrated regulatory network to enhance our understanding of the regulatory gene network used in the stress-related immune system. Module inference was used to construct modules of co-expressed genes with bovine leukocyte RNA-Seq data. Transcription factors (TFs) were then assigned to these modules using Lemon-Tree algorithms. In addition, the TFs assigned to each module were confirmed using the promoter analysis and protein-protein interactions data. Therefore, our integrated method identified three TFs which include one TF that is previously known to be involved in immune response (MYBL2) and two TFs (E2F8 and FOXS1) that had not been recognized previously and were identified for the first time in this study as novel regulatory candidates in immune response. This study provides valuable insights on the regulatory programs of genes involved in the stress-related immune system.

Candida Albicans and Non-Albicans Species as Etiological Agent of Vaginitis in Pregnant and Non-Pregnant Women

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Mirela Babić

2010-02-01

Full Text Available Pregnancy represents a risk factor in the occurrence of vaginal candidosis. The objectives of our study were: to make determination of the microscopic findings of vaginal swab, frequency of Candida species in the culture of pregnant women and patients who are not pregnant, determine the Candida species in all cultures, and to determine the frequency and differences in the frequency of C. albicans and other non-albicans species. In one year study performed during 2006 year, we tested patients of Gynaecology and Obstetrics clinic of the Clinical Centre in Sarajevo and Gynaecology department of the General hospital in Sarajevo. 447 woman included in the study were separated in two groups: 203 pregnant (in the last trimester of pregnancy, and 244 non-pregnant woman in period of fertility. Each vaginal swab was examined microscopically. The yeast, number of colonies, and the species of Candida were determined on Sabouraud dextrose agar with presence of antibiotics. For determination of Candida species, we used germ tube test for detection of C. albicans, and cultivation on the selective medium and assimilation tests for detection of non-albicans species. The results indicated positive microscopic findings in the test group (40,9%, as well as greater number of positive cultures (46,8%. The most commonly detected species for both groups was C. albicans (test group 40.9% and control group 23,0%. The most commonly detected non-albicans species for the test group were C. glabrata (4,2 % and C. krusei (3,2%, and for the control group were C. glabrata (3,2% and C. parapsilosis (3,2%. The microscopic findings correlated with the number of colonies in positive cultures. In the test group, we found an increased number of yeasts (64,3%, and the pseudopyphae and blastopores by microscopic examination as an indication of infection. In the control group, we found a small number of yeasts (64,6%, in the form of blastopores, as an indication of the candida

Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors.

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Sun, Mengyang; Cheng, Xianrui; Socolar, Joshua E S

2013-06-01

A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.

AI-2 of Aggregatibacter actinomycetemcomitans Inhibits Candida albicans Biofilm Formation

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Endang W. Bachtiar

2014-07-01

Full Text Available Aggregatibacter actinomycetemcomitans, a Gram-negative bacterium, and Candida albicans, a polymorphic fungus, are both commensals of the oral cavity but both are opportunistic pathogens that can cause oral diseases. A. actinomycetemcomitans produces a quorum-sensing molecule called autoinducer-2 (AI-2, synthesized by LuxS, that plays an important role in expression of virulence factors, in intra- but also in interspecies communication. The aim of this study was to investigate the role of AI-2 based signaling in the interactions between C. albicans and A. actinomycetemcomitans. A. actinomycetemcomitans adhered to C. albicans and inhibited biofilm formation by means of a molecule that was secreted during growth. C. albicans biofilm formation increased significantly when co-cultured with A. actinomycetemcomitans luxS, lacking AI-2 production. Addition of wild-type-derived spent medium or synthetic AI-2 to spent medium of the luxS strain, restored inhibition of C. albicans biofilm formation to wild-type levels. Addition of synthetic AI-2 significantly inhibited hypha formation of C. albicans possibly explaining the inhibition of biofilm formation. AI-2 of A. actinomycetemcomitans is synthesized by LuxS, accumulates during growth and inhibits C. albicans hypha- and biofilm formation. Identifying the molecular mechanisms underlying the interaction between bacteria and fungi may provide important insight into the balance within complex oral microbial communities.

Live Candida albicans Suppresses Production of Reactive Oxygen Species in Phagocytes▿ †

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Wellington, Melanie; Dolan, Kristy; Krysan, Damian J.

2009-01-01

Production of reactive oxygen species (ROS) is an important aspect of phagocyte-mediated host responses. Since phagocytes play a crucial role in the host response to Candida albicans, we examined the ability of Candida to modulate phagocyte ROS production. ROS production was measured in the murine macrophage cell line J774 and in primary phagocytes using luminol-enhanced chemiluminescence. J774 cells, murine polymorphonuclear leukocytes (PMN), human monocytes, and human PMN treated with live C. albicans produced significantly less ROS than phagocytes treated with heat-killed C. albicans. Live C. albicans also suppressed ROS production in murine bone marrow-derived macrophages from C57BL/6 mice, but not from BALB/c mice. Live C. albicans also suppressed ROS in response to external stimuli. C. albicans and Candida glabrata suppressed ROS production by phagocytes, whereas Saccharomyces cerevisiae stimulated ROS production. The cell wall is the initial point of contact between Candida and phagocytes, but isolated cell walls from both heat-killed and live C. albicans stimulated ROS production. Heat-killed C. albicans has increased surface exposure of 1,3-β-glucan, a cell wall component that can stimulate phagocytes. To determine whether surface 1,3-β-glucan exposure accounted for the difference in ROS production, live C. albicans cells were treated with a sublethal dose of caspofungin to increase surface 1,3-β-glucan exposure. Caspofungin-treated C. albicans was fully able to suppress ROS production, indicating that suppression of ROS overrides stimulatory signals from 1,3-β-glucan. These studies indicate that live C. albicans actively suppresses ROS production in phagocytes in vitro, which may represent an important immune evasion mechanism. PMID:18981256

Social insect colony as a biological regulatory system: modelling information flow in dominance networks.

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Nandi, Anjan K; Sumana, Annagiri; Bhattacharya, Kunal

2014-12-06

Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the 'feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Inferring nonlinear gene regulatory networks from gene expression data based on distance correlation.

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Xiaobo Guo

Full Text Available Nonlinear dependence is general in regulation mechanism of gene regulatory networks (GRNs. It is vital to properly measure or test nonlinear dependence from real data for reconstructing GRNs and understanding the complex regulatory mechanisms within the cellular system. A recently developed measurement called the distance correlation (DC has been shown powerful and computationally effective in nonlinear dependence for many situations. In this work, we incorporate the DC into inferring GRNs from the gene expression data without any underling distribution assumptions. We propose three DC-based GRNs inference algorithms: CLR-DC, MRNET-DC and REL-DC, and then compare them with the mutual information (MI-based algorithms by analyzing two simulated data: benchmark GRNs from the DREAM challenge and GRNs generated by SynTReN network generator, and an experimentally determined SOS DNA repair network in Escherichia coli. According to both the receiver operator characteristic (ROC curve and the precision-recall (PR curve, our proposed algorithms significantly outperform the MI-based algorithms in GRNs inference.

Distribution of Candida albicans and non-albicans Candida species in oral candidiasis patients: Correlation between cell surface hydrophobicity and biofilm forming activities.

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Muadcheingka, Thaniya; Tantivitayakul, Pornpen

2015-06-01

The purposes of this investigation were to study the prevalence of Candida albicans and non-albicans Candida (NAC) species from oral candidiasis patients and evaluate the cell surface hydrophobicity (CSH) and biofilm forming capacity of the clinical isolates Candida species from oral cavity. This study identified a total of 250 Candida strains isolated from 207 oral candidiasis patients with PCR-RFLP technique. CSH value, total biomass of biofilm and biofilm forming ability of 117 oral Candida isolates were evaluated. C. albicans (61.6%) was still the predominant species in oral candidiasis patients with and without denture wearer, respectively, followed by C. glabrata (15.2%), C. tropicalis (10.4%), C. parapsilosis (3.2%), C. kefyr (3.6%), C. dubliniensis (2%), C. lusitaniae (2%), C. krusei (1.6%), and C. guilliermondii (0.4%). The proportion of mixed colonization with more than one Candida species was 18% from total cases. The relative CSH value and biofilm biomass of NAC species were greater than C. albicans (poral isolates NAC species had biofilm forming ability, whereas 78% of C. albicans were biofilm formers. Furthermore, the significant difference of relative CSH values between biofilm formers and non-biofilm formers was observed in the NAC species (poral cavity was gradually increasing. The possible contributing factors might be high cell surface hydrophobicity and biofilm forming ability. The relative CSH value could be a putative factor for determining biofilm formation ability of the non-albicans Candida species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Algebraic model checking for Boolean gene regulatory networks.

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Tran, Quoc-Nam

2011-01-01

We present a computational method in which modular and Groebner bases (GB) computation in Boolean rings are used for solving problems in Boolean gene regulatory networks (BN). In contrast to other known algebraic approaches, the degree of intermediate polynomials during the calculation of Groebner bases using our method will never grow resulting in a significant improvement in running time and memory space consumption. We also show how calculation in temporal logic for model checking can be done by means of our direct and efficient Groebner basis computation in Boolean rings. We present our experimental results in finding attractors and control strategies of Boolean networks to illustrate our theoretical arguments. The results are promising. Our algebraic approach is more efficient than the state-of-the-art model checker NuSMV on BNs. More importantly, our approach finds all solutions for the BN problems.

Candida glabrata Binding to Candida albicans Hyphae Enables Its Development in Oropharyngeal Candidiasis.

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Tati, Swetha; Davidow, Peter; McCall, Andrew; Hwang-Wong, Elizabeth; Rojas, Isolde G; Cormack, Brendan; Edgerton, Mira

2016-03-01

Pathogenic mechanisms of Candida glabrata in oral candidiasis, especially because of its inability to form hyphae, are understudied. Since both Candida albicans and C. glabrata are frequently co-isolated in oropharyngeal candidiasis (OPC), we examined their co-adhesion in vitro and observed adhesion of C. glabrata only to C. albicans hyphae microscopically. Mice were infected sublingually with C. albicans or C. glabrata individually, or with both species concurrently, to study their ability to cause OPC. Infection with C. glabrata alone resulted in negligible infection of tongues; however, colonization by C. glabrata was increased by co-infection or a pre-established infection with C. albicans. Furthermore, C. glabrata required C. albicans for colonization of tongues, since decreasing C. albicans burden with fluconazole also reduced C. glabrata. C. albicans hyphal wall adhesins Als1 and Als3 were important for in vitro adhesion of C. glabrata and to establish OPC. C. glabrata cell wall protein coding genes EPA8, EPA19, AWP2, AWP7, and CAGL0F00181 were implicated in mediating adhesion to C. albicans hyphae and remarkably, their expression was induced by incubation with germinated C. albicans. Thus, we found a near essential requirement for the presence of C. albicans for both initial colonization and establishment of OPC infection by C. glabrata.

Treatment of serum with supernatants from cultures of Candida albicans reduces its serum-dependent phagocytosis Tratamento de soro com sobrenadante de cultura de Candida albicans reduz a fagocitose soro-dependente

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Aderbal Antonio dos Santos

2002-01-01

Full Text Available Candida albicans is a potent activator of the complement system, and heat labile opsonins produced by activation of C3 (C3b and iC3b enhance phagocytosis of C. albicans mediated by complement receptors. In this study we treated mouse serum with supernatants from cultures of a protease producer strain of C. albicans and evaluated the ability of this serum to enhance phagocytosis of C. albicans. Cell-free supernatants from cultures of C. albicans were concentrated 5 fold and added to mouse serum for 30 min at 37ºC, before using this serum for opsonization of glutaraldehyde-fixed yeast cells. We observed that normal mouse serum increased about 3 fold the phagocytosis of C. albicans by mice peritoneal macrophages, whereas supernatant-treated serum did not increase phagocytosis. This effect of supernatants on serum was prevented by addition of pepstatin (5 µg/ ml; an inhibitor of C. albicans acid proteases to the medium. Serum treated with supernatants from cultures of a protease-deficient mutant of C. albicans also increased about 3 fold phagocytosis of the yeast. These results suggest that a protease produced by C. albicans causes proteolysis of serum opsonins, thereby reducing the phagocytosis of the yeast.Candida albicans é um potente ativador do sistema complemento, e opsoninas lábeis ao calor produzidas por ativação de C3 (C3b e iC3b aumentam a fagocitose de C. albicans mediada por receptores de complemento. Neste estudo, tratamos o soro de camundongo com sobrenadante de culturas de uma cepa de C. albicans produtora de proteases e avaliamos a capacidade deste soro reduzir a fagocitose de C. albicans. Sobrenadantes livres de células obtidos de cultura de C. albicans foram concentrados 5 vezes e adicionados ao soro de camundongo por 30 minutos a 37ºC, antes deste soro ser usado para opsonização de C. albicans na forma de levedura e fixadas em glutaraldeido. Nós observamos que soro normal aumentou 3 vezes a fagocitose de C. albicans por

Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks

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Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...

Streptococcus mutans competence-stimulating peptide inhibits Candida albicans hypha formation.

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Jarosz, Lucja M; Deng, Dong Mei; van der Mei, Henny C; Crielaard, Wim; Krom, Bastiaan P

2009-11-01

The oral cavity is colonized by microorganisms growing in biofilms in which interspecies interactions take place. Streptococcus mutans grows in biofilms on enamel surfaces and is considered one of the main etiological agents of human dental caries. Candida albicans is also commonly found in the human oral cavity, where it interacts with S. mutans. C. albicans is a polymorphic fungus, and the yeast-to-hypha transition is involved in virulence and biofilm formation. The aim of this study was to investigate interkingdom communication between C. albicans and S. mutans based on the production of secreted molecules. S. mutans UA159 inhibited C. albicans germ tube (GT) formation in cocultures even when physically separated from C. albicans. Only S. mutans spent medium collected in the early exponential phase (4-h-old cultures) inhibited the GT formation of C. albicans. During this phase, S. mutans UA159 produces a quorum-sensing molecule, competence-stimulating peptide (CSP). The role of CSP in inhibiting GT formation was confirmed by using synthetic CSP and a comC deletion strain of S. mutans UA159, which lacks the ability to produce CSP. Other S. mutans strains and other Streptococcus spp. also inhibited GT formation but to different extents, possibly reflecting differences in CSP amino acid sequences among Streptococcus spp. or differences in CSP accumulation in the media. In conclusion, CSP, an S. mutans quorum-sensing molecule secreted during the early stages of growth, inhibits the C. albicans morphological switch.

Oral candidosis by Candida albicans in normal and xerostomic mice Candidose oral por Candida albicans em camundongos normais e xerostômicos

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Marilda Aparecida Gonçalves Totti

2004-09-01

Full Text Available The aim of this study was to analyze the effect of sialoadenectomy on the development of oral candidosis after one or four inoculations of Candida albicans. Initially, a suspension containing 10(8 cells/ml of C. albicans ATCC 36801 was prepared. Seventy-eight sialoadenectomized mice and a similar amount of mice with normal salivary flow received a single inoculation of C. albicans suspension. Another group with a similar number of mice received 4 inoculations. The control group consisted of 6 sialoadenectomized mice and 6 mice with normal salivary flow that were not inoculated with C. albicans. Candidosis development was studied histologically in the tongue of the animals 1, 2, 3, 5, and 8 days after inoculation and at 15-day intervals up to 165 days. According to the results obtained, it could be concluded that sialoadenectomy and a higher frequency of yeast inoculation influenced the presence and extension of candidosis lesions.O objetivo deste estudo foi analisar o efeito da sialoadenectomia sobre o desenvolvimento da candidose oral após uma ou quatro inoculações de Candida albicans. Inicialmente, uma suspensão contendo 10(8 células/ml de C. albicans ATCC 36801 foi preparada. Setenta e oito camundongos sialoadenectomizados e mesma quantidade de camundongos com fluxo salivar normal receberam uma única inoculação de suspensão de C. albicans. Outro grupo, com o mesmo número de camundongos, recebeu 4 inoculações. O grupo controle consistiu de 6 camundongos sialoadenectomizados e 6 com fluxo salivar normal que não foram inoculados com C. albicans. O desenvolvimento de candidose foi estudado histologicamente na língua dos animais em períodos de 1, 2, 3, 5 e 8 dias após a inoculação e em intervalos de 15 dias até 165 dias. De acordo com os resultados obtidos, conclui-se que a sialoadenectomia e uma maior freqüência de inoculação influenciaram na presença e extensão das lesões de candidose.

The interplay between NSAIDs and Candida albicans on the gastrointestinal tract of guinea pigs.

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Nadăş, George C; Taulescu, Marian A; Ciobanu, Lidia; Fiţ, Nicodim I; Flore, Chirilă; Răpuntean, Sorin; Bouari, Cosmina M; Catoi, Cornel

2013-04-01

Recent studies suggest that Candida albicans colonization is associated with several gastrointestinal inflammatory disorders and is also responsible for the delay in ulcer healing. No data are reported about the effects of C. albicans on the nonsteroidal anti-inflammatory drugs (NSAIDs)-induced necroinflammatory lesions. On the other hand, beneficial effects of NSAIDs regarding the colonization potential with C. albicans have been reported. Our aim was to investigate whether the association between NSAIDs and C. albicans could potentially induce necroinflammatory lesions in the guinea pigs gastric and enteral mucosa. Three interventional groups of 11 guinea pigs each were investigated after 5 days of receiving indomethacin, C. albicans or the association of both. C. albicans and necroinflammatory lesions were graded based on histological examinations. Statistical analysis used Mann-Whitney nonparametric test. NSAIDs did not significantly decrease C. albicans colonization grades on gastrointestinal mucosa. Administration of indomethacin subsequent to C. albicans determined significantly more severe necroinflammatory lesions compared to group that only received C. albicans. The association of NSAIDs and C. albicans did not cause significantly more severe degenerative or inflammatory lesions compared to the administration of only NSAIDs in this experimental model. Associations between NSAIDs and C. albicans caused significantly more severe necroinflammatory injuries than the lesions produced by C. albicans, without enhancing the mucosal injury or inflammation caused by NSAIDs.

Emerging azole resistance among Candida albicans from clinical ...

African Journals Online (AJOL)

Candida albicans is one of the most frequently isolated yeasts in clinical laboratories and accounts for up to 80 % of the yeasts recovered from sites of infection. The study was set out to determine antifungal susceptibility of clinical isolates of Candida albicans and to establish the Minimum Inhibitory Concentrations (MIC) to ...

Comparison of evolutionary algorithms in gene regulatory network model inference.

LENUS (Irish Health Repository)

2010-01-01

ABSTRACT: BACKGROUND: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very difficult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insufficient. RESULTS: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and offer a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. CONCLUSIONS: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identified and a platform for development of appropriate model formalisms is established.

Inferring regulatory networks from experimental morphological phenotypes: a computational method reverse-engineers planarian regeneration.

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Daniel Lobo

2015-06-01

Full Text Available Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature; By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method

Azole Antifungal Resistance in Candida albicans and Emerging Non-albicans Candida Species

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Whaley, Sarah G.; Berkow, Elizabeth L.; Rybak, Jeffrey M.; Nishimoto, Andrew T.; Barker, Katherine S.; Rogers, P. David

2017-01-01

Within the limited antifungal armamentarium, the azole antifungals are the most frequent class used to treat Candida infections. Azole antifungals such as fluconazole are often preferred treatment for many Candida infections as they are inexpensive, exhibit limited toxicity, and are available for oral administration. There is, however, extensive documentation of intrinsic and developed resistance to azole antifungals among several Candida species. As the frequency of azole resistant Candida isolates in the clinical setting increases, it is essential to elucidate the mechanisms of such resistance in order to both preserve and improve upon the azole class of antifungals for the treatment of Candida infections. This review examines azole resistance in infections caused by C. albicans as well as the emerging non-albicans Candida species C. parapsilosis, C. tropicalis, C. krusei, and C. glabrata and in particular, describes the current understanding of molecular basis of azole resistance in these fungal species. PMID:28127295

Mechanistically Distinct Pathways of Divergent Regulatory DNA Creation Contribute to Evolution of Human-Specific Genomic Regulatory Networks Driving Phenotypic Divergence of Homo sapiens.

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Glinsky, Gennadi V

2016-09-19

Thousands of candidate human-specific regulatory sequences (HSRS) have been identified, supporting the hypothesis that unique to human phenotypes result from human-specific alterations of genomic regulatory networks. Collectively, a compendium of multiple diverse families of HSRS that are functionally and structurally divergent from Great Apes could be defined as the backbone of human-specific genomic regulatory networks. Here, the conservation patterns analysis of 18,364 candidate HSRS was carried out requiring that 100% of bases must remap during the alignments of human, chimpanzee, and bonobo sequences. A total of 5,535 candidate HSRS were identified that are: (i) highly conserved in Great Apes; (ii) evolved by the exaptation of highly conserved ancestral DNA; (iii) defined by either the acceleration of mutation rates on the human lineage or the functional divergence from non-human primates. The exaptation of highly conserved ancestral DNA pathway seems mechanistically distinct from the evolution of regulatory DNA segments driven by the species-specific expansion of transposable elements. Genome-wide proximity placement analysis of HSRS revealed that a small fraction of topologically associating domains (TADs) contain more than half of HSRS from four distinct families. TADs that are enriched for HSRS and termed rapidly evolving in humans TADs (revTADs) comprise 0.8-10.3% of 3,127 TADs in the hESC genome. RevTADs manifest distinct correlation patterns between placements of human accelerated regions, human-specific transcription factor-binding sites, and recombination rates. There is a significant enrichment within revTAD boundaries of hESC-enhancers, primate-specific CTCF-binding sites, human-specific RNAPII-binding sites, hCONDELs, and H3K4me3 peaks with human-specific enrichment at TSS in prefrontal cortex neurons (P sapiens is driven by the evolution of human-specific genomic regulatory networks via at least two mechanistically distinct pathways of creation of

The origins and evolutionary history of human non-coding RNA regulatory networks.

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Sherafatian, Masih; Mowla, Seyed Javad

2017-04-01

The evolutionary history and origin of the regulatory function of animal non-coding RNAs are not well understood. Lack of conservation of long non-coding RNAs and small sizes of microRNAs has been major obstacles in their phylogenetic analysis. In this study, we tried to shed more light on the evolution of ncRNA regulatory networks by changing our phylogenetic strategy to focus on the evolutionary pattern of their protein coding targets. We used available target databases of miRNAs and lncRNAs to find their protein coding targets in human. We were able to recognize evolutionary hallmarks of ncRNA targets by phylostratigraphic analysis. We found the conventional 3'-UTR and lesser known 5'-UTR targets of miRNAs to be enriched at three consecutive phylostrata. Firstly, in eukaryata phylostratum corresponding to the emergence of miRNAs, our study revealed that miRNA targets function primarily in cell cycle processes. Moreover, the same overrepresentation of the targets observed in the next two consecutive phylostrata, opisthokonta and eumetazoa, corresponded to the expansion periods of miRNAs in animals evolution. Coding sequence targets of miRNAs showed a delayed rise at opisthokonta phylostratum, compared to the 3' and 5' UTR targets of miRNAs. LncRNA regulatory network was the latest to evolve at eumetazoa.

Inference of hierarchical regulatory network of estrogen-dependent breast cancer through ChIP-based data

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Parvin Jeffrey

2010-12-01

Full Text Available Abstract Background Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks. Results In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2 were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM. A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes. We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes and targeted TFs (25% of common TFs. The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells. Conclusions Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to

Phylogeography of the Neotropical catfish Pimelodus albicans (Siluriformes: Pimelodidae from río de la Plata basin, South America, and conservation remarks

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Julia Vergara

Full Text Available Pimelodus albicans Valenciennes, 1840 (common name "moncholo" or "bagre blanco" is an endemic species of the family Pimelodidae in the río de la Plata basin. Phylogenetic approach based on cytochrome b sequences was performed to test the existence of a unique evolutionary lineage in P. albicans and to discriminate populations units or subpopulations related to a migration behavior of this taxon in the río de la Plata basin. This study included 34 samples of P. albicans of different collecting sites in the río de la Plata estuary and in the río Arrecifes belonging to the río Paraná basin. Among 614 base pairs in the cytochrome b sequence data set, 203 were variable and 120 were phylogenetically informative sites in P. albicans. A total of twenty haplotypes, nucleotide diversity (p = 0.032 and haplotype diversity = 0.941 were found. Tajima's test showed significant value D= -1.88 (p<0.05 rejecting the neutral mutation hypothesis for the P. albicans data set. All phylogenetic approaches showed that P. albicans included four monophyletic assemblages that were supported by high bootstrap and Bayesian posterior probability values. Minimum spanning network corroborated these groups for P. albicans haplotypes. High genetic structure was found in P. albicans by means of AMOVA analysis showing that the río Arrecifes samples constitute an isolated lineage. Moreover, the high value of genetic divergence (10% between the río de la Plata and the río Arrecifes populations could suggest that P. albicans may be conformed by a sibling species complex. On the other hand, a degree of genetic structuring was detected among different sites of the río de la Plata. A partial isolation of the 760 site may suggest that P. albicans could migrates to different tributaries for reproduction, generating different schools of haplotypes which could mix in the río de la Plata estuary. The high nucleotide diversity found in the 765 site and the existence of gene flow

The effect of denture adhesives on Candida albicans growth in vitro.

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Sampaio-Maia, Benedita; Figueiral, Maria Helena; Sousa-Rodrigues, Patricia; Fernandes, Maria Helena; Scully, Crispian

2012-06-01

Denture-wearing favours the growth of Candida. In view of the fact that many denture wearers regularly use adhesives to enhance denture retention, stability and function, the aim of this work was to study the effect of denture adhesives on Candida albicans growth in vitro. The denture adhesives tested were Corega(®) cream, Kukident(®) cream, Novafix(®) cream, Polident(®) cream, Protefix(®) cream, Steradent(®) cream, Aderyn(®) powder, Corega(®) ultra powder, Protefix(®) powder and Corega(®) strip. C. albicans growth curves were obtained in the presence or absence of a 1% solution of the denture adhesive diluted in Sabouraud broth. Macro- and microscopic morphological changes in C. albicans were analysed, as was microbial contamination of the denture adhesive. Most of the denture adhesives studied induced morphological changes in C. albicans cells and colonies, but only two had any significant inhibitory effect on yeast growth. Kukident(®) cream markedly inhibited C. albicans growth in a concentration-dependent way, reducing the growth rate by 95%, whereas Corega(®) cream also inhibited C. albicans growth but in a non-concentration-dependent way, reducing the growth rate by 37%. In addition, denture adhesives available as powders had detectable microbial contamination. Some commercially available denture adhesives showed microbial contamination and some had significant inhibitory effect on C. albicans growth. © 2011 The Gerodontology Society and John Wiley & Sons A/S.

Oxidative Stress Responses in the Human Fungal Pathogen, Candida albicans

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da Silva Dantas, Alessandra; Day, Alison; Ikeh, Mélanie; Kos, Iaroslava; Achan, Beatrice; Quinn, Janet

2015-01-01

Candida albicans is a major fungal pathogen of humans, causing approximately 400,000 life-threatening systemic infections world-wide each year in severely immunocompromised patients. An important fungicidal mechanism employed by innate immune cells involves the generation of toxic reactive oxygen species (ROS), such as superoxide and hydrogen peroxide. Consequently, there is much interest in the strategies employed by C. albicans to evade the oxidative killing by macrophages and neutrophils. Our understanding of how C. albicans senses and responds to ROS has significantly increased in recent years. Key findings include the observations that hydrogen peroxide triggers the filamentation of this polymorphic fungus and that a superoxide dismutase enzyme with a novel mode of action is expressed at the cell surface of C. albicans. Furthermore, recent studies have indicated that combinations of the chemical stresses generated by phagocytes can actively prevent C. albicans oxidative stress responses through a mechanism termed the stress pathway interference. In this review, we present an up-date of our current understanding of the role and regulation of oxidative stress responses in this important human fungal pathogen. PMID:25723552

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.

Pathogenesis of Candida albicans infections in the alternative chorio-allantoic membrane chicken embryo model resembles systemic murine infections.

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Ilse D Jacobsen

Full Text Available Alternative models of microbial infections are increasingly used to screen virulence determinants of pathogens. In this study, we investigated the pathogenesis of Candida albicans and C. glabrata infections in chicken embryos infected via the chorio-allantoic membrane (CAM and analyzed the virulence of deletion mutants. The developing immune system of the host significantly influenced susceptibility: With increasing age, embryos became more resistant and mounted a more balanced immune response, characterized by lower induction of proinflammatory cytokines and increased transcription of regulatory cytokines, suggesting that immunopathology contributes to pathogenesis. While many aspects of the chicken embryo response resembled murine infections, we also observed significant differences: In contrast to systemic infections in mice, IL-10 had a beneficial effect in chicken embryos. IL-22 and IL-17A were only upregulated after the peak mortality in the chicken embryo model occurred; thus, the role of the Th17 response in this model remains unclear. Abscess formation occurs frequently in murine models, whereas the avian response was dominated by granuloma formation. Pathogenicity of the majority of 15 tested C. albicans deletion strains was comparable to the virulence in mouse models and reduced virulence was associated with significantly lower transcription of proinflammatory cytokines. However, fungal burden did not correlate with virulence and for few mutants like bcr1Δ and tec1Δ different outcomes in survival compared to murine infections were observed. C. albicans strains locked in the yeast stage disseminated significantly more often from the CAM into the embryo, supporting the hypothesis that the yeast morphology is responsible for dissemination in systemic infections. These data suggest that the pathogenesis of C. albicans infections in the chicken embryo model resembles systemic murine infections but also differs in some aspects. Despite

Streptococcus mutans Can Modulate Biofilm Formation and Attenuate the Virulence of Candida albicans

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Barbosa, Júnia Oliveira; Rossoni, Rodnei Dennis; Vilela, Simone Furgeri Godinho; de Alvarenga, Janaína Araújo; Velloso, Marisol dos Santos; Prata, Márcia Cristina de Azevedo; Jorge, Antonio Olavo Cardoso; Junqueira, Juliana Campos

2016-01-01

Streptococcus mutans and Candida albicans are found together in the oral biofilms on dental surfaces, but little is known about the ecological interactions between these species. Here, we studied the effects of S. mutans UA159 on the growth and pathogencity of C. albicans. Initially, the effects of S. mutans on the biofilm formation and morphogenesis of C. albicans were tested in vitro. Next, we investigate the influence of S. mutans on pathogenicity of C. albicans using in vivo host models, in which the experimental candidiasis was induced in G. mellonella larvae and analyzed by survival curves, C. albicans count in hemolymph, and quantification of hyphae in the host tissues. In all the tests, we evaluated the direct effects of S. mutans cells, as well as the indirect effects of the subproducts secreted by this microorganism using a bacterial culture filtrate. The in vitro analysis showed that S. mutans cells favored biofilm formation by C. albicans. However, a reduction in biofilm viable cells and inhibition of hyphal growth was observed when C. albicans was in contact with the S. mutans culture filtrate. In the in vivo study, injection of S. mutans cells or S. mutans culture filtrate into G. mellonella larvae infected with C. albicans increased the survival of these animals. Furthermore, a reduction in hyphal formation was observed in larval tissues when C. albicans was associated with S. mutans culture filtrate. These findings suggest that S. mutans can secrete subproducts capable to inhibit the biofilm formation, morphogenesis and pathogenicity of C. albicans, attenuating the experimental candidiasis in G. mellonella model. PMID:26934196

Oral candidiasis-adhesion of non-albicans Candida species

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Bokor-Bratić Marija B.

2008-01-01

Full Text Available Oral candidiasis is an opportunistic infection caused primarily by Candida albicans. However, in recent years, species of non-albicans Candida have been implicated more frequently in mucosal infection. Candida species usually reside as commensal organisms and are part of normal oral microflora. Determining exactly how transformation from commensal to pathogen takes place and how it can be prevented is continuous challenge for clinical doctors. Candidal adherence to mucosal surfaces is considered as a critical initial step in the pathogenesis of oral candidiasis. Acrylic dentures, acting as reservoirs, play an important role in increasing the risk from Candida colonisation. Thus, this review discusses what is currently known about the adhesion of non-albicans Candida species of oral origin to buccal epithelial cells and denture acrylics.

Rac1 dynamics in the human opportunistic fungal pathogen Candida albicans.

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Romain Vauchelles

Full Text Available The small Rho G-protein Rac1 is highly conserved from fungi to humans, with approximately 65% overall sequence identity in Candida albicans. As observed with human Rac1, we show that C. albicans Rac1 can accumulate in the nucleus, and fluorescence recovery after photobleaching (FRAP together with fluorescence loss in photobleaching (FLIP studies indicate that this Rho G-protein undergoes nucleo-cytoplasmic shuttling. Analyses of different chimeras revealed that nuclear accumulation of C. albicans Rac1 requires the NLS-motifs at its carboxyl-terminus, which are blocked by prenylation of the adjacent cysteine residue. Furthermore, we show that C. albicans Rac1 dynamics, both at the plasma membrane and in the nucleus, are dependent on its activation state and in particular that the inactive form accumulates faster in the nucleus. Heterologous expression of human Rac1 in C. albicans also results in nuclear accumulation, yet accumulation is more rapid than that of C. albicans Rac1. Taken together our results indicate that Rac1 nuclear accumulation is an inherent property of this G-protein and suggest that the requirements for its nucleo-cytoplasmic shuttling are conserved from fungi to humans.

Hyphal formation of Candida albicans is controlled by electron transfer system

International Nuclear Information System (INIS)

Watanabe, Toshihiko; Ogasawara, Ayako; Mikami, Takeshi; Matsumoto, Tatsuji

2006-01-01

Most Candida albicans cells cultured in RPMI1640 medium at 37 deg. C grow in hyphal form in aerobic conditions, but they grow in yeast form in anaerobic conditions. The hyphal growth of C. albicans was inhibited in glucose-deficient conditions. Malonic acid, an inhibitor of succinate dehydrogenase, enhanced the yeast proliferation of C. albicans, indicating that the hyphal-formation signal was derived from the glycolysis system and the signal was transmitted to the electron transfer system via the citric acid cycle. Thenoyl trifluoro acetone (TTFA), an inhibitor of the signal transmission between complex II and Co Q, significantly inhibited the hyphal growth of C. albicans. Antimycin, KCN, and oligomycin, inhibitors of complex III, IV, and V, respectively, did not inhibit the hyphal growth of C. albicans. The production of mRNAs for the hyphal formation signal was completely inhibited in anaerobic conditions. These results indicate that the electron transfer system functions upstream of the RAS1 signal pathway and activates the expression of the hyphal formation signal. Since the electron transfer system is inactivated in anaerobic conditions, C. albicans grew in yeast form in this condition

[The effects of an aroma candy on oral Candida albicans colony-forming units (CFU) and oral hygiene states in healthy elderly carrying Candida albicans].

Science.gov (United States)

Suzuki, Motofumi; Hayama, Kazumi; Takahashi, Miki; Ezawa, Kunio; Yamazaki, Masatoshi; Matsukawa, Taiji; Kishi, Akinobu; Satou, Nobuya; Abe, Shigeru

2015-01-01

In a preceding paper, we showed that aroma candy containing oligonol, capric acid, and cinnamon (cassia) powder had potent inhibitory activity against mycelial growth of Candida albicans in vitro and protective activity against murine oral candidiasis. In order to assess the effects of this candy (the test candy) on oral C. albicans colony-forming units (CFU) and oral hygiene states, a placebo-controlled double-blind crossover comparative study was performed. Twenty subjects were divided into two groups. One group ingested the test candy in the first 7 days followed by 2 weeks washing-off period, then ingested the placebo candy (control candy) for 7 days. The other group was vice versa. C. albicans CFU in all oral rinse samples from the subjects before and after 7 days ingestion of candy was measured. The degree of oral malodor in all subjects was monitored using a portable measuring instrument. The results showed no statistically significant difference between test-candy group and placebo group for C. albicans CFU. However, C. albicans CFU in test-candy group with>4,000 CFUs was significantly decreased after 7 days ingestion of test-candy (poral malodor in the test-candy group was significantly decreased after 7 days ingestion of test-candy (poral hygiene states indicated that in the test-candy group, oral malodor, glutinous feeling, and refreshing feeling significantly improved in comparison with control-candy group (poral health care of elderly carrying C. albicans.

Detecting Candida albicans in human milk.

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Morrill, Jimi Francis; Pappagianis, Demosthenes; Heinig, M Jane; Lönnerdal, Bo; Dewey, Kathryn G

2003-01-01

Procedures for diagnosis of mammary candidosis, including laboratory confirmation, are not well defined. Lactoferrin present in human milk can inhibit growth of Candida albicans, thereby limiting the ability to detect yeast infections. The inhibitory effect of various lactoferrin concentrations on the growth of C. albicans in whole human milk was studied. The addition of iron to the milk led to a two- to threefold increase in cell counts when milk contained 3.0 mg of lactoferrin/ml and markedly reduced the likelihood of false-negative culture results. This method may provide the necessary objective support needed for diagnosis of mammary candidosis.

Short peptides allowing preferential detection of Candida albicans hyphae.

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Kaba, Hani E J; Pölderl, Antonia; Bilitewski, Ursula

2015-09-01

Whereas the detection of pathogens via recognition of surface structures by specific antibodies and various types of antibody mimics is frequently described, the applicability of short linear peptides as sensor molecules or diagnostic tools is less well-known. We selected peptides which were previously reported to bind to recombinant S. cerevisiae cells, expressing members of the C. albicans Agglutinin-Like-Sequence (ALS) cell wall protein family. We slightly modified amino acid sequences to evaluate peptide sequence properties influencing binding to C. albicans cells. Among the selected peptides, decamer peptides with an "AP"-N-terminus were superior to shorter peptides. The new decamer peptide FBP4 stained viable C. albicans cells more efficiently in their mature hyphal form than in their yeast form. Moreover, it allowed distinction of C. albicans from other related Candida spp. and could thus be the basis for the development of a useful tool for the diagnosis of invasive candidiasis.

Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method.

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Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui

2017-10-06

Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli , and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.

Effect of salivary secretory IgA on the adhesion of Candida albicans to polystyrene.

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San Millán, R; Elguezabal, N; Regúlez, P; Moragues, M D; Quindós, G; Pontón, J

2000-09-01

Attachment of Candida albicans to plastic materials of dental prostheses or to salivary macromolecules adsorbed on their surface is believed to be a critical event in the development of denture stomatitis. In an earlier study, it was shown that adhesion of C. albicans to polystyrene, a model system to study the adhesion of C. albicans to plastic materials, can be partially inhibited with an mAb directed against cell wall polysaccharides of C. albicans. In the present study, the role of whole saliva in the adhesion of C. albicans to polystyrene has been investigated, and three mAbs directed against epitopes of cell wall mannoproteins have been used to mimic the inhibitory effect observed with salivary secretory IgA (sIgA) on the adhesion of C. albicans to polystyrene. In the absence of whole saliva, adherence of C. albicans 3153 increased with germination. However, the presence of whole saliva enhanced the adhesion to polystyrene of C. albicans 3153 yeast cells but decreased the adhesion of germinated cells. The enhancement of adhesion of yeast cells to polystyrene mediated by saliva was confirmed with an agerminative mutant of C. albicans 3153. The inhibition of the adhesion of C. albicans 3153 germ tubes to polystyrene was due to the salivary sIgA since sIgA-depleted saliva enhanced the adhesion of C. albicans 3153 to polystyrene. The inhibitory effect mediated by sIgA was not related to the inhibition of germination but to the blockage of adhesins expressed on the cell wall surface of the germ tubes. The three mAbs studied reduced the adhesion of C. albicans 3153 to polystyrene at levels equivalent to those for purified sIgA. The highest reduction in the adhesion was obtained with the IgA mAb N3B. The best results were obtained when the three mAbs were combined. The results suggest that whole saliva plays a different role in the adhesion of C. albicans to polystyrene depending on the morphological phase of C. albicans. These results may give new insights into the

Model checking optimal finite-horizon control for probabilistic gene regulatory networks.

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Wei, Ou; Guo, Zonghao; Niu, Yun; Liao, Wenyuan

2017-12-14

Probabilistic Boolean networks (PBNs) have been proposed for analyzing external control in gene regulatory networks with incorporation of uncertainty. A context-sensitive PBN with perturbation (CS-PBNp), extending a PBN with context-sensitivity to reflect the inherent biological stability and random perturbations to express the impact of external stimuli, is considered to be more suitable for modeling small biological systems intervened by conditions from the outside. In this paper, we apply probabilistic model checking, a formal verification technique, to optimal control for a CS-PBNp that minimizes the expected cost over a finite control horizon. We first describe a procedure of modeling a CS-PBNp using the language provided by a widely used probabilistic model checker PRISM. We then analyze the reward-based temporal properties and the computation in probabilistic model checking; based on the analysis, we provide a method to formulate the optimal control problem as minimum reachability reward properties. Furthermore, we incorporate control and state cost information into the PRISM code of a CS-PBNp such that automated model checking a minimum reachability reward property on the code gives the solution to the optimal control problem. We conduct experiments on two examples, an apoptosis network and a WNT5A network. Preliminary experiment results show the feasibility and effectiveness of our approach. The approach based on probabilistic model checking for optimal control avoids explicit computation of large-size state transition relations associated with PBNs. It enables a natural depiction of the dynamics of gene regulatory networks, and provides a canonical form to formulate optimal control problems using temporal properties that can be automated solved by leveraging the analysis power of underlying model checking engines. This work will be helpful for further utilization of the advances in formal verification techniques in system biology.

Comparative genomics of the fungal pathogens Candida dubliniensis and Candida albicans.

LENUS (Irish Health Repository)

Jackson, Andrew P

2009-12-01

Candida dubliniensis is the closest known relative of Candida albicans, the most pathogenic yeast species in humans. However, despite both species sharing many phenotypic characteristics, including the ability to form true hyphae, C. dubliniensis is a significantly less virulent and less versatile pathogen. Therefore, to identify C. albicans-specific genes that may be responsible for an increased capacity to cause disease, we have sequenced the C. dubliniensis genome and compared it with the known C. albicans genome sequence. Although the two genome sequences are highly similar and synteny is conserved throughout, 168 species-specific genes are identified, including some encoding known hyphal-specific virulence factors, such as the aspartyl proteinases Sap4 and Sap5 and the proposed invasin Als3. Among the 115 pseudogenes confirmed in C. dubliniensis are orthologs of several filamentous growth regulator (FGR) genes that also have suspected roles in pathogenesis. However, the principal differences in genomic repertoire concern expansion of the TLO gene family of putative transcription factors and the IFA family of putative transmembrane proteins in C. albicans, which represent novel candidate virulence-associated factors. The results suggest that the recent evolutionary histories of C. albicans and C. dubliniensis are quite different. While gene families instrumental in pathogenesis have been elaborated in C. albicans, C. dubliniensis has lost genomic capacity and key pathogenic functions. This could explain why C. albicans is a more potent pathogen in humans than C. dubliniensis.

Directed partial correlation: inferring large-scale gene regulatory network through induced topology disruptions.

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Yinyin Yuan

Full Text Available Inferring regulatory relationships among many genes based on their temporal variation in transcript abundance has been a popular research topic. Due to the nature of microarray experiments, classical tools for time series analysis lose power since the number of variables far exceeds the number of the samples. In this paper, we describe some of the existing multivariate inference techniques that are applicable to hundreds of variables and show the potential challenges for small-sample, large-scale data. We propose a directed partial correlation (DPC method as an efficient and effective solution to regulatory network inference using these data. Specifically for genomic data, the proposed method is designed to deal with large-scale datasets. It combines the efficiency of partial correlation for setting up network topology by testing conditional independence, and the concept of Granger causality to assess topology change with induced interruptions. The idea is that when a transcription factor is induced artificially within a gene network, the disruption of the network by the induction signifies a genes role in transcriptional regulation. The benchmarking results using GeneNetWeaver, the simulator for the DREAM challenges, provide strong evidence of the outstanding performance of the proposed DPC method. When applied to real biological data, the inferred starch metabolism network in Arabidopsis reveals many biologically meaningful network modules worthy of further investigation. These results collectively suggest DPC is a versatile tool for genomics research. The R package DPC is available for download (http://code.google.com/p/dpcnet/.

GRN2SBML: automated encoding and annotation of inferred gene regulatory networks complying with SBML.

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Vlaic, Sebastian; Hoffmann, Bianca; Kupfer, Peter; Weber, Michael; Dräger, Andreas

2013-09-01

GRN2SBML automatically encodes gene regulatory networks derived from several inference tools in systems biology markup language. Providing a graphical user interface, the networks can be annotated via the simple object access protocol (SOAP)-based application programming interface of BioMart Central Portal and minimum information required in the annotation of models registry. Additionally, we provide an R-package, which processes the output of supported inference algorithms and automatically passes all required parameters to GRN2SBML. Therefore, GRN2SBML closes a gap in the processing pipeline between the inference of gene regulatory networks and their subsequent analysis, visualization and storage. GRN2SBML is freely available under the GNU Public License version 3 and can be downloaded from http://www.hki-jena.de/index.php/0/2/490. General information on GRN2SBML, examples and tutorials are available at the tool's web page.

NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference.

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Bellot, Pau; Olsen, Catharina; Salembier, Philippe; Oliveras-Vergés, Albert; Meyer, Patrick E

2015-09-29

In the last decade, a great number of methods for reconstructing gene regulatory networks from expression data have been proposed. However, very few tools and datasets allow to evaluate accurately and reproducibly those methods. Hence, we propose here a new tool, able to perform a systematic, yet fully reproducible, evaluation of transcriptional network inference methods. Our open-source and freely available Bioconductor package aggregates a large set of tools to assess the robustness of network inference algorithms against different simulators, topologies, sample sizes and noise intensities. The benchmarking framework that uses various datasets highlights the specialization of some methods toward network types and data. As a result, it is possible to identify the techniques that have broad overall performances.

Female genital tract bacterial coisolates with Candida albicans in patients without clinical vaginitis.

Science.gov (United States)

Monif, G R; Carson, H J

1998-01-01

In vitro, Candida albicans has demonstrated the ability to inhibit replication of selected bacteria. Little information exists on the impact of C. albicans on the vaginal bacterial flora in vivo. The purpose of this study is to identify the coexisting bacterial flora when C. albicans is isolated from vaginal cultures submitted to a hospital-based testing facility for reasons other than vulvovaginitis. All specimens (240) received from ambulatory care clinics over a six-month period were cultured for aerobic and anaerobic bacteria and Candida species. Those specimens submitted for cervicitis, vaginitis, or vaginal discharge and those from which yeasts other than C. albicans were isolated were eliminated. To control for sample biases, a subgroup composed of all pregnant women for whom cultures were done as screening procedures was similarly studied. Chi-square analyses, comparing the prevalence of individual bacteria isolated with and without the presence of C. albicans, were done for all study populations using SPSS for Windows software (1994). Two hundred and forty consecutive specimens were bacteriologically analyzed. Of the 220 vaginal samples used in the study, C. albicans was isolated in 44 instances (20%). Neither the presence of the lactobacilli nor the presence of Gardnerella vaginalis markedly influenced the isolation rate of C. albicans. The group B streptococci had a greater probability of coisolation when C. albicans was present (27.3% verses 16%), but this was not statistically significant (P aerobic bacilli was reduced in the presence of C. albicans (30/176 [17.1%] versus 6/44 [13.6%]), this reduced incidence was not statistically significant. Isolation data of the subgroup of pregnant women supported these observations. Within the limitations of the study, statistically, the data suggests that an inverse relationship exists between the presence of C. albicans and recovery of Peptostreptococcus and anaerobic gram-positive cocci and bacilli.

Control of Metastatic Progression by microRNA Regulatory Networks

Science.gov (United States)

Pencheva, Nora; Tavazoie, Sohail F.

2015-01-01

Aberrant microRNA (miRNA) expression is a defining feature of human malignancy. Specific miRNAs have been identified as promoters or suppressors of metastatic progression. These miRNAs control metastasis through divergent or convergent regulation of metastatic gene pathways. Some miRNA regulatory networks govern cell-autonomous cancer phenotypes, while others modulate the cell-extrinsic composition of the metastatic microenvironment. The use of small RNAs as probes into the molecular and cellular underpinnings of metastasis holds promise for the identification of candidate genes for potential therapeutic intervention. PMID:23728460

Developmental evolution in social insects: regulatory networks from genes to societies.

Science.gov (United States)

Linksvayer, Timothy A; Fewell, Jennifer H; Gadau, Jürgen; Laubichler, Manfred D

2012-05-01

The evolution and development of complex phenotypes in social insect colonies, such as queen-worker dimorphism or division of labor, can, in our opinion, only be fully understood within an expanded mechanistic framework of Developmental Evolution. Conversely, social insects offer a fertile research area in which fundamental questions of Developmental Evolution can be addressed empirically. We review the concept of gene regulatory networks (GRNs) that aims to fully describe the battery of interacting genomic modules that are differentially expressed during the development of individual organisms. We discuss how distinct types of network models have been used to study different levels of biological organization in social insects, from GRNs to social networks. We propose that these hierarchical networks spanning different organizational levels from genes to societies should be integrated and incorporated into full GRN models to elucidate the evolutionary and developmental mechanisms underlying social insect phenotypes. Finally, we discuss prospects and approaches to achieve such an integration. © 2012 WILEY PERIODICALS, INC.

A developmental systems perspective on epistasis: computational exploration of mutational interactions in model developmental regulatory networks.

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Jayson Gutiérrez

2009-09-01

Full Text Available The way in which the information contained in genotypes is translated into complex phenotypic traits (i.e. embryonic expression patterns depends on its decoding by a multilayered hierarchy of biomolecular systems (regulatory networks. Each layer of this hierarchy displays its own regulatory schemes (i.e. operational rules such as +/- feedback and associated control parameters, resulting in characteristic variational constraints. This process can be conceptualized as a mapping issue, and in the context of highly-dimensional genotype-phenotype mappings (GPMs epistatic events have been shown to be ubiquitous, manifested in non-linear correspondences between changes in the genotype and their phenotypic effects. In this study I concentrate on epistatic phenomena pervading levels of biological organization above the genetic material, more specifically the realm of molecular networks. At this level, systems approaches to studying GPMs are specially suitable to shed light on the mechanistic basis of epistatic phenomena. To this aim, I constructed and analyzed ensembles of highly-modular (fully interconnected networks with distinctive topologies, each displaying dynamic behaviors that were categorized as either arbitrary or functional according to early patterning processes in the Drosophila embryo. Spatio-temporal expression trajectories in virtual syncytial embryos were simulated via reaction-diffusion models. My in silico mutational experiments show that: 1 the average fitness decay tendency to successively accumulated mutations in ensembles of functional networks indicates the prevalence of positive epistasis, whereas in ensembles of arbitrary networks negative epistasis is the dominant tendency; and 2 the evaluation of epistatic coefficients of diverse interaction orders indicates that, both positive and negative epistasis are more prevalent in functional networks than in arbitrary ones. Overall, I conclude that the phenotypic and fitness effects of

The metabolic response of Candida albicans to farnesol under hyphae-inducing conditions.

Science.gov (United States)

Han, Ting-Li; Cannon, Richard D; Villas-Bôas, Silas G

2012-12-01

Farnesol is a quorum-sensing molecule (QSM) produced, and sensed, by the polymorphic fungus, Candida albicans. This cell-to-cell communication molecule is known to suppress the hyphal formation of C. albicans at high cell density. Despite many studies investigating the signalling mechanisms by which QSMs influence the morphogenesis of C. albicans, the downstream metabolic effect of these signalling pathways in response to farnesol-mediated morphogenesis remains obscure. Here, we have used metabolomics to investigate the metabolic response of C. albicans upon exposure to farnesol under hyphae-inducing conditions. We have found a general up-regulation of central carbon metabolic pathways when hyphal formation was suppressed by farnesol evidenced by a considerably larger number of central carbon metabolic intermediates detected under this condition at an overall lower intracellular level. By combining the metabolic profiles from farnesol-exposed cells with previous metabolomics data for C. albicans undergoing morphogenesis, we have identified several metabolic pathways that are likely to be associated with the morphogenetic process of C. albicans, as well as metabolic pathways such as those involved in lipid metabolism that appeared to be specifically affected by farnesol. Therefore, our results provide important new insights into the metabolic role of farnesol in C. albicans metabolism. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

Heart morphogenesis gene regulatory networks revealed by temporal expression analysis.

Science.gov (United States)

Hill, Jonathon T; Demarest, Bradley; Gorsi, Bushra; Smith, Megan; Yost, H Joseph

2017-10-01

During embryogenesis the heart forms as a linear tube that then undergoes multiple simultaneous morphogenetic events to obtain its mature shape. To understand the gene regulatory networks (GRNs) driving this phase of heart development, during which many congenital heart disease malformations likely arise, we conducted an RNA-seq timecourse in zebrafish from 30 hpf to 72 hpf and identified 5861 genes with altered expression. We clustered the genes by temporal expression pattern, identified transcription factor binding motifs enriched in each cluster, and generated a model GRN for the major gene batteries in heart morphogenesis. This approach predicted hundreds of regulatory interactions and found batteries enriched in specific cell and tissue types, indicating that the approach can be used to narrow the search for novel genetic markers and regulatory interactions. Subsequent analyses confirmed the GRN using two mutants, Tbx5 and nkx2-5 , and identified sets of duplicated zebrafish genes that do not show temporal subfunctionalization. This dataset provides an essential resource for future studies on the genetic/epigenetic pathways implicated in congenital heart defects and the mechanisms of cardiac transcriptional regulation. © 2017. Published by The Company of Biologists Ltd.

Global Stability of Complex-Valued Genetic Regulatory Networks with Delays on Time Scales

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Wang Yajing

2016-01-01

Full Text Available In this paper, the global exponential stability of complex-valued genetic regulatory networks with delays is investigated. Besides presenting conditions guaranteeing the existence of a unique equilibrium pattern, its global exponential stability is discussed. Some numerical examples for different time scales.

Recurrent neural network for non-smooth convex optimization problems with application to the identification of genetic regulatory networks.

Science.gov (United States)

Cheng, Long; Hou, Zeng-Guang; Lin, Yingzi; Tan, Min; Zhang, Wenjun Chris; Wu, Fang-Xiang

2011-05-01

A recurrent neural network is proposed for solving the non-smooth convex optimization problem with the convex inequality and linear equality constraints. Since the objective function and inequality constraints may not be smooth, the Clarke's generalized gradients of the objective function and inequality constraints are employed to describe the dynamics of the proposed neural network. It is proved that the equilibrium point set of the proposed neural network is equivalent to the optimal solution of the original optimization problem by using the Lagrangian saddle-point theorem. Under weak conditions, the proposed neural network is proved to be stable, and the state of the neural network is convergent to one of its equilibrium points. Compared with the existing neural network models for non-smooth optimization problems, the proposed neural network can deal with a larger class of constraints and is not based on the penalty method. Finally, the proposed neural network is used to solve the identification problem of genetic regulatory networks, which can be transformed into a non-smooth convex optimization problem. The simulation results show the satisfactory identification accuracy, which demonstrates the effectiveness and efficiency of the proposed approach.

Regulatory network of GATA3 in pediatric acute lymphoblastic leukemia

OpenAIRE

Hou, Qianqian; Liao, Fei; Zhang, Shouyue; Zhang, Duyu; Zhang, Yan; Zhou, Xueyan; Xia, Xuyang; Ye, Yuanxin; Yang, Hanshuo; Li, Zhaozhi; Wang, Leiming; Wang, Xi; Ma, Zhigui; Zhu, Yiping; Ouyang, Liang

2017-01-01

GATA3 polymorphisms were reported to be significantly associated with susceptibility of pediatric B-lineage acute lymphoblastic leukemia (ALL), by impacting on GATA3 expression. We noticed that ALL-related GATA3 polymorphism located around in the tissue-specific enhancer, and significantly associated with GATA3 expression. Although the regulatory network of GATA3 has been well reported in T cells, the functional status of GATA3 is poorly understood in B-ALL. We thus conducted genome-wide gene...

LmSmdB: an integrated database for metabolic and gene regulatory network in Leishmania major and Schistosoma mansoni

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Priyanka Patel

2016-03-01

Full Text Available A database that integrates all the information required for biological processing is essential to be stored in one platform. We have attempted to create one such integrated database that can be a one stop shop for the essential features required to fetch valuable result. LmSmdB (L. major and S. mansoni database is an integrated database that accounts for the biological networks and regulatory pathways computationally determined by integrating the knowledge of the genome sequences of the mentioned organisms. It is the first database of its kind that has together with the network designing showed the simulation pattern of the product. This database intends to create a comprehensive canopy for the regulation of lipid metabolism reaction in the parasite by integrating the transcription factors, regulatory genes and the protein products controlled by the transcription factors and hence operating the metabolism at genetic level. Keywords: L.major, S.mansoni, Regulatory networks, Transcription factors, Database

A Process Perspective on Regulation: A Grounded Theory Study into Regulatory Practice in Newly Liberalized Network-Based Markets

NARCIS (Netherlands)

Ubacht, J.

The transition from a former monopolistic towards a more competitive market in
newly liberalized network-based markets raises regulatory issues. National Regulatory Authorities (NRA) face the challenge to deal with these issues in order to guide the transition process. Although this transition

Acid production by oral strains of Candida albicans and Lactobacilli

NARCIS (Netherlands)

Klinke, T.; Kneist, S.; de Soet, J.J.; Kuhlisch, E.; Mauersberger, S.; Forster, A.; Klimm, W.

2009-01-01

Both Candida albicans and lactobacilli are common colonizers of carious lesions in children and adolescents. The purpose of this study is to compare the velocity of acid production between C. albicans and several Lactobacillus species at different pH levels and concentrations of glucose. Washed,

Integrating external biological knowledge in the construction of regulatory networks from time-series expression data

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Lo Kenneth

2012-08-01

Full Text Available Abstract Background Inference about regulatory networks from high-throughput genomics data is of great interest in systems biology. We present a Bayesian approach to infer gene regulatory networks from time series expression data by integrating various types of biological knowledge. Results We formulate network construction as a series of variable selection problems and use linear regression to model the data. Our method summarizes additional data sources with an informative prior probability distribution over candidate regression models. We extend the Bayesian model averaging (BMA variable selection method to select regulators in the regression framework. We summarize the external biological knowledge by an informative prior probability distribution over the candidate regression models. Conclusions We demonstrate our method on simulated data and a set of time-series microarray experiments measuring the effect of a drug perturbation on gene expression levels, and show that it outperforms leading regression-based methods in the literature.

Candida não albicans como patogénicos emergentes

OpenAIRE

Vieira, Francisca Moreira Raposo de Mello

2016-01-01

Dissertação para obtenção do grau de Mestre no Instituto Superior de Ciências da Saúde Egas Moniz As espécies do género Candida, comensais no Homem, podem tornar-se patogénicas quando existe um desequilíbrio na resposta do sistema imunitário, desencadeando infecções superficiais ou sistémicas. Embora Candida albicans (C. albicans) seja considerada a espécie com maior patogenicidade, dados epidemiológicos apontam para a emergência das espécies de Candida não-albicans (CNA), nomeadamente em ...

Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

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Frank Emmert-Streib

2013-02-01

Full Text Available The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I observational gene expression data: normal environmental condition, (II interventional gene expression data: growth in rich media, (III interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.

Nicotine Enhances Interspecies Relationship between Streptococcus mutans and Candida albicans.

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Liu, Shiyu; Qiu, Wei; Zhang, Keke; Zhou, Xuedong; Ren, Biao; He, Jinzhi; Xu, Xin; Cheng, Lei; Li, Mingyun

2017-01-01

Streptococcus mutans and Candida albicans are common microorganisms in the human oral cavity. The synergistic relationship between these two species has been deeply explored in many studies. In the present study, the effect of alkaloid nicotine on the interspecies between S. mutans and C. albicans is explored. We developed a dual-species biofilm model and studied biofilm biomass, biofilm structure, synthesis of extracellular polysaccharides (EPS), and expression of glucosyltransferases (Gtfs). Biofilm formation and bacterial and fungal cell numbers in dual-species biofilms increased in the presence of nicotine. More C. albicans cells were present in the dual-species biofilms in the nicotine-treated groups as determined by scanning electron microscopy. The synthesis of EPS was increased by 1 mg/ml of nicotine as detected by confocal laser scanning microscopy. The result of qRT-PCR showed gtfs expression was upregulated when 1 mg/ml of nicotine was used. We speculate that nicotine promoted the growth of S. mutans , and more S. mutans cells attracted more C. albicans cells due to the interaction between two species. Since S. mutans and C. albicans are putative pathogens for dental caries, the enhancement of the synergistic relationship by nicotine may contribute to caries development in smokers.

Microevolution of Candida albicans in macrophages restores filamentation in a nonfilamentous mutant.

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Anja Wartenberg

2014-12-01

Full Text Available Following antifungal treatment, Candida albicans, and other human pathogenic fungi can undergo microevolution, which leads to the emergence of drug resistance. However, the capacity for microevolutionary adaptation of fungi goes beyond the development of resistance against antifungals. Here we used an experimental microevolution approach to show that one of the central pathogenicity mechanisms of C. albicans, the yeast-to-hyphae transition, can be subject to experimental evolution. The C. albicans cph1Δ/efg1Δ mutant is nonfilamentous, as central signaling pathways linking environmental cues to hyphal formation are disrupted. We subjected this mutant to constant selection pressure in the hostile environment of the macrophage phagosome. In a comparatively short time-frame, the mutant evolved the ability to escape macrophages by filamentation. In addition, the evolved mutant exhibited hyper-virulence in a murine infection model and an altered cell wall composition compared to the cph1Δ/efg1Δ strain. Moreover, the transcriptional regulation of hyphae-associated, and other pathogenicity-related genes became re-responsive to environmental cues in the evolved strain. We went on to identify the causative missense mutation via whole genome- and transcriptome-sequencing: a single nucleotide exchange took place within SSN3 that encodes a component of the Cdk8 module of the Mediator complex, which links transcription factors with the general transcription machinery. This mutation was responsible for the reconnection of the hyphal growth program with environmental signals in the evolved strain and was sufficient to bypass Efg1/Cph1-dependent filamentation. These data demonstrate that even central transcriptional networks can be remodeled very quickly under appropriate selection pressure.

Difunctional bacteriophage conjugated with photosensitizers for Candida albicans-targeting photodynamic inactivation.

Science.gov (United States)

Dong, Shuai; Shi, Hongxi; Zhang, Xintong; Chen, Xi; Cao, Donghui; Mao, Chuanbin; Gao, Xiang; Wang, Li

2018-01-01

Candida albicans is the most prevalent fungal pathogen of the human microbiota, causing infections ranging from superficial infections of the skin to life-threatening systemic infections. Due to the increasing occurrence of antibiotic-resistant C. albicans strains, new approaches to control this pathogen are needed. Photodynamic inactivation is an emerging alternative to treat infections based on the interactions between visible light and photosensitisers, in which pheophorbide a (PPA) is a chlorophyll-based photosensitizer that could induce cell death after light irradiation. Due to PPA's phototoxicity and low efficiency, the main challenge is to implement photosensitizer cell targeting and attacking. In this study, PPA was conjugated with JM-phage by EDC/NHS crosslinking. UV-Vis spectra was used to determine the optimum conjugation percentages of PPA and JM-phage complex for photodynamic inactivation. After photodynamic inactivation, the efficacy of PPA-JM-phage was assessed by performing in vitro experiments, such as MTS assay, scanning electron microscopy, measurement of dysfunctional mitochondria, ROS accumulation, S cell arrest and apoptotic pathway. A single-chain variable-fragment phage (JM) with high affinity to MP65 was screened from human single-fold single-chain variable-fragment libraries and designed as a binding target for C. albicans cells. Subsequently, PPa was integrated into JM phage to generate a combined nanoscale material, which was called PPA-JM-phage. After photodynamic inactivation, the growth of C. albicans was inhibited by PPA-JM-phage and apoptosis was observed. Scanning electron microscopy analysis revealed shrinking and rupturing of C. albicans . We also found that depolarization of mitochondrial membrane potential was decreased and intracellular reactive oxygen species levels were elevated significantly in C. albicans inhibited by PPA-JM-phage. Additionally, PPA-JM-phage also lead to S-phase arrest, and metacaspase activation

Triclosan antagonizes fluconazole activity against Candida albicans.

LENUS (Irish Health Repository)

Higgins, J

2012-01-01

Triclosan is a broad-spectrum antimicrobial compound commonly used in oral hygiene products. Investigation of its activity against Candida albicans showed that triclosan was fungicidal at concentrations of 16 mg\\/L. However, at subinhibitory concentrations (0.5-2 mg\\/L), triclosan antagonized the activity of fluconazole. Although triclosan induced CDR1 expression in C. albicans, antagonism was still observed in cdr1Δ and cdr2Δ strains. Triclosan did not affect fluconazole uptake or alter total membrane sterol content, but did induce the expression of FAS1 and FAS2, indicating that its mode of action may involve inhibition of fatty acid synthesis, as it does in prokaryotes. However, FAS2 mutants did not exhibit increased susceptibility to triclosan, and overexpression of both FAS1 and FAS2 alleles did not alter triclosan susceptibility. Unexpectedly, the antagonistic effect was specific for C. albicans under hypha-inducing conditions and was absent in the non-filamentous efg1Δ strain. This antagonism may be due to the membranotropic activity of triclosan and the unique composition of hyphal membranes.

International STakeholder NETwork (ISTNET): creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes.

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Bal-Price, Anna; Crofton, Kevin M; Leist, Marcel; Allen, Sandra; Arand, Michael; Buetler, Timo; Delrue, Nathalie; FitzGerald, Rex E; Hartung, Thomas; Heinonen, Tuula; Hogberg, Helena; Bennekou, Susanne Hougaard; Lichtensteiger, Walter; Oggier, Daniela; Paparella, Martin; Axelstad, Marta; Piersma, Aldert; Rached, Eva; Schilter, Benoît; Schmuck, Gabriele; Stoppini, Luc; Tongiorgi, Enrico; Tiramani, Manuela; Monnet-Tschudi, Florianne; Wilks, Martin F; Ylikomi, Timo; Fritsche, Ellen

2015-02-01

A major problem in developmental neurotoxicity (DNT) risk assessment is the lack of toxicological hazard information for most compounds. Therefore, new approaches are being considered to provide adequate experimental data that allow regulatory decisions. This process requires a matching of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISTNET) in DNT testing. The first meeting of ISTNET was held in Zurich on 23-24 January 2014 in order to explore the concept of adverse outcome pathway (AOP) to practical DNT testing. AOPs were considered promising tools to promote test systems development according to regulatory needs. Moreover, the AOP concept was identified as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a road map towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment. Next steps to be considered in follow-up activities are the use of case studies to further apply the AOP concept in regulatory DNT testing, making use of AOP intersections (common key events) for economic development of screening assays, and addressing the transition from qualitative descriptions to quantitative network modelling.

A new method for discovering disease-specific MiRNA-target regulatory networks.

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Miriam Baglioni

Full Text Available Genes and their expression regulation are among the key factors in the comprehension of the genesis and development of complex diseases. In this context, microRNAs (miRNAs are post-transcriptional regulators that play an important role in gene expression since they are frequently deregulated in pathologies like cardiovascular disease and cancer. In vitro validation of miRNA--targets regulation is often too expensive and time consuming to be carried out for every possible alternative. As a result, a tool able to provide some criteria to prioritize trials is becoming a pressing need. Moreover, before planning in vitro experiments, the scientist needs to evaluate the miRNA-target genes interaction network. In this paper we describe the miRable method whose purpose is to identify new potentially relevant genes and their interaction networks associate to a specific pathology. To achieve this goal miRable follows a system biology approach integrating together general-purpose medical knowledge (literature, Protein-Protein Interaction networks, prediction tools and pathology specific data (gene expression data. A case study on Prostate Cancer has shown that miRable is able to: 1 find new potential miRNA-targets pairs, 2 highlight novel genes potentially involved in a disease but never or little studied before, 3 reconstruct all possible regulatory subnetworks starting from the literature to expand the knowledge on the regulation of miRNA regulatory mechanisms.

Interplay between the gastric bacterial microbiota and Candida albicans during postantibiotic recolonization and gastritis.

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Mason, Katie L; Erb Downward, John R; Falkowski, Nicole R; Young, Vincent B; Kao, John Y; Huffnagle, Gary B

2012-01-01

The indigenous bacterial microbiome of the stomach, including lactobacilli, is vital in promoting colonization resistance against Candida albicans. However, there are gaps in our understanding about C. albicans gastric colonization versus disease, especially during the postantibiotic recovery phase. This study compared the gastric responses to C. albicans strains CHN1 and SC5314 in microbiome-disturbed and germfree mice to elucidate the contribution of the indigenous microbiota in C. albicans colonization versus disease and yeast-bacterium antagonism during the post-cefoperazone recolonization period. C. albicans can prevent the regrowth of Lactobacillus spp. in the stomach after cefoperazone and promote increased colonization by Enterococcus spp. Using a culture-independent analysis, the effects of oral cefoperazone on the gastric bacterial microbiota were observed to last at least 3 weeks after the cessation of the antibiotic. Disturbance of the gastric bacterial community by cefoperazone alone was not sufficient to cause gastritis, C. albicans colonization was also needed. Gastritis was not evident until after day 7 in cefoperazone-treated infected mice. In contrast, in germfree mice which lack a gastric microbiota, C. albicans induced gastric inflammation within 1 week of inoculation. Therefore, the gastric bacterial community in cefoperazone-treated mice during the first week of postantibiotic recolonization was sufficient to prevent the development of gastritis, despite being ineffective at conferring colonization resistance against C. albicans. Altogether, these data implicate a dichotomy between C. albicans colonization and gastric disease that is bacterial microbiome dependent.

Efek Penambahan Glukosa pada Saburoud Dextrose Broth terhadap Pertumbuhan Candida albicans (Uji In Vitro

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Lakshmi A. Leepel

2012-10-01

Full Text Available High carbohydrate intake is one of predisposing factors of oral candidiasis. Objective: Investigating the effect of 1%,5%,10% glucose addition on the growth of C.albicans in vitro. Method: C.albicans sample was taken from oral swab of a male oral candidiasis patient. Identification of C.albicans was conducted using CHROMagar and confirmed by germ tube formation in serum. As a comparison, C.albicans ATCC10231 was used. After 2 days the cultures were serially diluted and inoculated in SDB without glucose, and with 1%,5%,10% addditional glucose, kept for 3 and 7 days in room temperature, then inoculated in SDA. The CFU/ml were counted after 2 days. ANOVA with α0.05 was used. Result: Statisticaly, additional 1% glucose for 3 days lead to significant decreased of growth of both clinical strain and ATCC 10231 C. albicans. However, only additional 5% and 10% glucose in clinical isolate for 7 days increased the growth of C.albicans significantly. Conclusion: The effect of additional glucose on the increased growth of C.albicans in vitro is influenced by the concentration, exposure duration of glucose, and by the strain of C.albicans.DOI: 10.14693/jdi.v16i1.14

Cigarette Smoke-Exposed Candida albicans Increased Chitin Production and Modulated Human Fibroblast Cell Responses

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Humidah Alanazi

2014-01-01

Full Text Available The predisposition of cigarette smokers for development of respiratory and oral bacterial infections is well documented. Cigarette smoke can also contribute to yeast infection. The aim of this study was to investigate the effect of cigarette smoke condensate (CSC on C. albicans transition, chitin content, and response to environmental stress and to examine the interaction between CSC-pretreated C. albicans and normal human gingival fibroblasts. Following exposure to CSC, C. albicans transition from blastospore to hyphal form increased. CSC-pretreated yeast cells became significantly (P<0.01 sensitive to oxidation but significantly (P<0.01 resistant to both osmotic and heat stress. CSC-pretreated C. albicans expressed high levels of chitin, with 2- to 8-fold recorded under hyphal conditions. CSC-pretreated C. albicans adhered better to the gingival fibroblasts, proliferated almost three times more and adapted into hyphae, while the gingival fibroblasts recorded a significantly (P<0.01 slow growth rate but a significantly higher level of IL-1β when in contact with CSC-pretreated C. albicans. CSC was thus able to modulate both C. albicans transition through the cell wall chitin content and the interaction between C. albicans and normal human gingival fibroblasts. These findings may be relevant to fungal infections in the oral cavity in smokers.

Differentiation between Candida albicans and Candida dubliniensis using hypertonic Sabouraud broth and tobacco agar.

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Silveira-Gomes, Fabíola; Sarmento, Dayse Nogueira; Espírito-Santo, Elaine Patrícia Tavares do; Souza, Nádia de Oliveira; Pinto, Thifany Mendes; Marques-da-Silva, Silvia Helena

2011-01-01

Opportunistic fungal infections in immunocompromised hosts are caused by Candida species, and the majority of such infections are due to Candida albicans. However, the emerging pathogen Candida dubliniensis demonstrates several phenotypic characteristics in common with C. albicans, such as production of germ tubes and chlamydospores, calling attention to the development of stable resistance to fluconazole in vitro. The aim of this study was to evaluate the performance of biochemistry identification in the differentiating between C. albicans and C. dubliniensis, by phenotyping of yeast identified as C. albicans. Seventy-nine isolates identified as C. albicans by the API system ID 32C were grown on Sabouraud dextrose agar at 30°C for 24-48h and then inoculated on hypertonic Sabouraud broth and tobacco agar. Our results showed that 17 (21.5%) isolates were growth-inhibited on hypertonic Sabouraud broth, a phenotypic trait inconsistent with C. albicans in this medium. However, the results observed on tobacco agar showed that only 9 (11.4%) of the growth-inhibited isolates produced characteristic colonies of C. dubliniensis (rough colonies, yellowish-brown with abundant fragments of hyphae and chlamydospores). The results suggest that this method is a simple tool for screening C. albicans and non-albicans yeast and for verification of automated identification.

Spaceflight enhances cell aggregation and random budding in Candida albicans.

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Aurélie Crabbé

Full Text Available This study presents the first global transcriptional profiling and phenotypic characterization of the major human opportunistic fungal pathogen, Candida albicans, grown in spaceflight conditions. Microarray analysis revealed that C. albicans subjected to short-term spaceflight culture differentially regulated 452 genes compared to synchronous ground controls, which represented 8.3% of the analyzed ORFs. Spaceflight-cultured C. albicans-induced genes involved in cell aggregation (similar to flocculation, which was validated by microscopic and flow cytometry analysis. We also observed enhanced random budding of spaceflight-cultured cells as opposed to bipolar budding patterns for ground samples, in accordance with the gene expression data. Furthermore, genes involved in antifungal agent and stress resistance were differentially regulated in spaceflight, including induction of ABC transporters and members of the major facilitator family, downregulation of ergosterol-encoding genes, and upregulation of genes involved in oxidative stress resistance. Finally, downregulation of genes involved in actin cytoskeleton was observed. Interestingly, the transcriptional regulator Cap1 and over 30% of the Cap1 regulon was differentially expressed in spaceflight-cultured C. albicans. A potential role for Cap1 in the spaceflight response of C. albicans is suggested, as this regulator is involved in random budding, cell aggregation, and oxidative stress resistance; all related to observed spaceflight-associated changes of C. albicans. While culture of C. albicans in microgravity potentiates a global change in gene expression that could induce a virulence-related phenotype, no increased virulence in a murine intraperitoneal (i.p. infection model was observed under the conditions of this study. Collectively, our data represent an important basis for the assessment of the risk that commensal flora could play during human spaceflight missions. Furthermore, since the

Dental Caries in Rats Associated with Candida albicans

OpenAIRE

Klinke, Thomas; Guggenheim, Bernhard; Klimm, Wolfgang; Thurnheer, Thomas

2014-01-01

In addition to occasional opportunistic colonization of the oral mucosa, Candida albicans is frequently found in carious dentin. The yeast’s potential to induce dental caries as a consequence of its pronounced ability to produce and tolerate acids was investigated. Eighty caries-active Osborne-Mendel rats were raised on an ampicillin-supplemented diet and exposed to C. albicans and/or Streptococcus mutans, except for controls. Throughout the 28-day test period, the animals were offered the mo...

Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.

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Gong, Wuming; Koyano-Nakagawa, Naoko; Li, Tongbin; Garry, Daniel J

2015-03-07

Decoding the temporal control of gene expression patterns is key to the understanding of the complex mechanisms that govern developmental decisions during heart development. High-throughput methods have been employed to systematically study the dynamic and coordinated nature of cardiac differentiation at the global level with multiple dimensions. Therefore, there is a pressing need to develop a systems approach to integrate these data from individual studies and infer the dynamic regulatory networks in an unbiased fashion. We developed a two-step strategy to integrate data from (1) temporal RNA-seq, (2) temporal histone modification ChIP-seq, (3) transcription factor (TF) ChIP-seq and (4) gene perturbation experiments to reconstruct the dynamic network during heart development. First, we trained a logistic regression model to predict the probability (LR score) of any base being bound by 543 TFs with known positional weight matrices. Second, four dimensions of data were combined using a time-varying dynamic Bayesian network model to infer the dynamic networks at four developmental stages in the mouse [mouse embryonic stem cells (ESCs), mesoderm (MES), cardiac progenitors (CP) and cardiomyocytes (CM)]. Our method not only infers the time-varying networks between different stages of heart development, but it also identifies the TF binding sites associated with promoter or enhancers of downstream genes. The LR scores of experimentally verified ESCs and heart enhancers were significantly higher than random regions (p network inference model identified a region with an elevated LR score approximately -9400 bp upstream of the transcriptional start site of Nkx2-5, which overlapped with a previously reported enhancer region (-9435 to -8922 bp). TFs such as Tead1, Gata4, Msx2, and Tgif1 were predicted to bind to this region and participate in the regulation of Nkx2-5 gene expression. Our model also predicted the key regulatory networks for the ESC-MES, MES-CP and CP

Piecing together cis-regulatory networks: insights from epigenomics studies in plants.

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Huang, Shao-Shan C; Ecker, Joseph R

2018-05-01

5-Methylcytosine, a chemical modification of DNA, is a covalent modification found in the genomes of both plants and animals. Epigenetic inheritance of phenotypes mediated by DNA methylation is well established in plants. Most of the known mechanisms of establishing, maintaining and modifying DNA methylation have been worked out in the reference plant Arabidopsis thaliana. Major functions of DNA methylation in plants include regulation of gene expression and silencing of transposable elements (TEs) and repetitive sequences, both of which have parallels in mammalian biology, involve interaction with the transcriptional machinery, and may have profound effects on the regulatory networks in the cell. Methylome and transcriptome dynamics have been investigated in development and environmental responses in Arabidopsis and agriculturally and ecologically important plants, revealing the interdependent relationship among genomic context, methylation patterns, and expression of TE and protein coding genes. Analyses of methylome variation among plant natural populations and species have begun to quantify the extent of genetic control of methylome variation vs. true epimutation, and model the evolutionary forces driving methylome evolution in both short and long time scales. The ability of DNA methylation to positively or negatively modulate binding affinity of transcription factors (TFs) provides a natural link from genome sequence and methylation changes to transcription. Technologies that allow systematic determination of methylation sensitivities of TFs, in native genomic and methylation context without confounding factors such as histone modifications, will provide baseline datasets for building cell-type- and individual-specific regulatory networks that underlie the establishment and inheritance of complex traits. This article is categorized under: Laboratory Methods and Technologies > Genetic/Genomic Methods Biological Mechanisms > Regulatory Biology. © 2017 Wiley

Determining Regulatory Networks Governing the Differentiation of Embryonic Stem Cells to Pancreatic Lineage

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Banerjee, Ipsita

2009-03-01

Knowledge of pathways governing cellular differentiation to specific phenotype will enable generation of desired cell fates by careful alteration of the governing network by adequate manipulation of the cellular environment. With this aim, we have developed a novel method to reconstruct the underlying regulatory architecture of a differentiating cell population from discrete temporal gene expression data. We utilize an inherent feature of biological networks, that of sparsity, in formulating the network reconstruction problem as a bi-level mixed-integer programming problem. The formulation optimizes the network topology at the upper level and the network connectivity strength at the lower level. The method is first validated by in-silico data, before applying it to the complex system of embryonic stem (ES) cell differentiation. This formulation enables efficient identification of the underlying network topology which could accurately predict steps necessary for directing differentiation to subsequent stages. Concurrent experimental verification demonstrated excellent agreement with model prediction.

Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

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Watson, Emma; MacNeil, Lesley T; Arda, H Efsun; Zhu, Lihua Julie; Walhout, Albertha J M

2013-03-28

Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus. Copyright © 2013 Elsevier Inc. All rights reserved.

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

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Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier

Differentiation between Candida albicans and Candida dubliniensis using hypertonic Sabouraud broth and tobacco agar

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Fabíola Silveira-Gomes

2011-08-01

Full Text Available INTRODUCTION: Opportunistic fungal infections in immunocompromised hosts are caused by Candida species, and the majority of such infections are due to Candida albicans. However, the emerging pathogen Candida dubliniensis demonstrates several phenotypic characteristics in common with C. albicans, such as production of germ tubes and chlamydospores, calling attention to the development of stable resistance to fluconazole in vitro. The aim of this study was to evaluate the performance of biochemistry identification in the differentiating between C. albicans and C. dubliniensis, by phenotyping of yeast identified as C. albicans. METHODS: Seventy-nine isolates identified as C. albicans by the API system ID 32C were grown on Sabouraud dextrose agar at 30°C for 24-48h and then inoculated on hypertonic Sabouraud broth and tobacco agar. RESULTS: Our results showed that 17 (21.5% isolates were growth-inhibited on hypertonic Sabouraud broth, a phenotypic trait inconsistent with C. albicans in this medium. However, the results observed on tobacco agar showed that only 9 (11.4% of the growth-inhibited isolates produced characteristic colonies of C. dubliniensis (rough colonies, yellowish-brown with abundant fragments of hyphae and chlamydospores. CONCLUSIONS: The results suggest that this method is a simple tool for screening C. albicans and non-albicans yeast and for verification of automated identification.

Relationship between salivary flow rates and Candida albicans counts.

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Navazesh, M; Wood, G J; Brightman, V J

1995-09-01

Seventy-one persons (48 women, 23 men; mean age, 51.76 years) were evaluated for salivary flow rates and Candida albicans counts. Each person was seen on three different occasions. Samples of unstimulated whole, chewing-stimulated whole, acid-stimulated parotid, and candy-stimulated parotid saliva were collected under standardized conditions. An oral rinse was also obtained and evaluated for Candida albicans counts. Unstimulated and chewing-stimulated whole flow rates were negatively and significantly (p Candida counts. Unstimulated whole saliva significantly (p Candida counts of 0 versus or = 500 count. Differences in stimulated parotid flow rates were not significant among different levels of Candida counts. The results of this study reveal that whole saliva is a better predictor than parotid saliva in identification of persons with high Candida albicans counts.

Dissection of regulatory networks that are altered in disease via differential co-expression.

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David Amar

Full Text Available Comparing the gene-expression profiles of sick and healthy individuals can help in understanding disease. Such differential expression analysis is a well-established way to find gene sets whose expression is altered in the disease. Recent approaches to gene-expression analysis go a step further and seek differential co-expression patterns, wherein the level of co-expression of a set of genes differs markedly between disease and control samples. Such patterns can arise from a disease-related change in the regulatory mechanism governing that set of genes, and pinpoint dysfunctional regulatory networks. Here we present DICER, a new method for detecting differentially co-expressed gene sets using a novel probabilistic score for differential correlation. DICER goes beyond standard differential co-expression and detects pairs of modules showing differential co-expression. The expression profiles of genes within each module of the pair are correlated across all samples. The correlation between the two modules, however, differs markedly between the disease and normal samples. We show that DICER outperforms the state of the art in terms of significance and interpretability of the detected gene sets. Moreover, the gene sets discovered by DICER manifest regulation by disease-specific microRNA families. In a case study on Alzheimer's disease, DICER dissected biological processes and protein complexes into functional subunits that are differentially co-expressed, thereby revealing inner structures in disease regulatory networks.

Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset

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Gidrol Xavier

2008-02-01

Full Text Available Abstract Background Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interactions may be modelled by a Bayesian Network (BN that represents the presence of direct interactions from regulators to regulees by conditional probability distributions. We used enhanced evolutionary algorithms to stochastically evolve a set of candidate BN structures and found the model that best fits data without prior knowledge. Results We proposed various evolutionary strategies suitable for the task and tested our choices using simulated data drawn from a given bio-realistic network of 35 nodes, the so-called insulin network, which has been used in the literature for benchmarking. We assessed the inferred models against this reference to obtain statistical performance results. We then compared performances of evolutionary algorithms using two kinds of recombination operators that operate at different scales in the graphs. We introduced a niching strategy that reinforces diversity through the population and avoided trapping of the algorithm in one local minimum in the early steps of learning. We show the limited effect of the mutation operator when niching is applied. Finally, we compared our best evolutionary approach with various well known learning algorithms (MCMC, K2, greedy search, TPDA, MMHC devoted to BN structure learning. Conclusion We studied the behaviour of an evolutionary approach enhanced by niching for the learning of gene regulatory networks with BN. We show that this approach outperforms classical structure learning methods in elucidating the original model. These results were obtained for the learning of a bio-realistic network and, more importantly, on various small datasets. This is a suitable approach for learning transcriptional regulatory networks from real datasets without prior knowledge.

C. albicans growth, transition, biofilm formation, and gene expression modulation by antimicrobial decapeptide KSL-W

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2013-01-01

Background Antimicrobial peptides have been the focus of much research over the last decade because of their effectiveness and broad-spectrum activity against microbial pathogens. These peptides also participate in inflammation and the innate host defense system by modulating the immune function that promotes immune cell adhesion and migration as well as the respiratory burst, which makes them even more attractive as therapeutic agents. This has led to the synthesis of various antimicrobial peptides, including KSL-W (KKVVFWVKFK-NH2), for potential clinical use. Because this peptide displays antimicrobial activity against bacteria, we sought to determine its antifungal effect on C. albicans. Growth, hyphal form, biofilm formation, and degradation were thus examined along with EFG1, NRG1, EAP1, HWP1, and SAP 2-4-5-6 gene expression by quantitative RT-PCR. Results This study demonstrates that KSL-W markedly reduced C. albicans growth at both early and late incubation times. The significant effect of KSL-W on C. albicans growth was observed beginning at 10 μg/ml after 5 h of contact by reducing C. albicans transition and at 25 μg/ml by completely inhibiting C. albicans transition. Cultured C. albicans under biofilm-inducing conditions revealed that both KSL-W and amphotericin B significantly decreased biofilm formation at 2, 4, and 6 days of culture. KSL-W also disrupted mature C. albicans biofilms. The effect of KSL-W on C. albicans growth, transition, and biofilm formation/disruption may thus occur through gene modulation, as the expression of various genes involved in C. albicans growth, transition and biofilm formation were all downregulated when C. albicans was treated with KSL-W. The effect was greater when C. albicans was cultured under hyphae-inducing conditions. Conclusions These data provide new insight into the efficacy of KSL-W against C. albicans and its potential use as an antifungal therapy. PMID:24195531

Complex Regulatory Networks Governing Production of the Glycopeptide A40926

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Rosa Alduina

2018-04-01

Full Text Available Glycopeptides (GPAs are an important class of antibiotics, with vancomycin and teicoplanin being used in the last 40 years as drugs of last resort to treat infections caused by Gram-positive pathogens, including methicillin-resistant Staphylococcus aureus. A few new GPAs have since reached the market. One of them is dalbavancin, a derivative of A40926 produced by the actinomycete Nonomuraea sp. ATCC 39727, recently classified as N. gerenzanensis. This review summarizes what we currently know on the multilevel regulatory processes governing production of the glycopeptide A40926 and the different approaches used to increase antibiotic yields. Some nutrients, e.g., valine, l-glutamine and maltodextrin, and some endogenous proteins, e.g., Dbv3, Dbv4 and RpoBR, have a positive role on A40926 biosynthesis, while other factors, e.g., phosphate, ammonium and Dbv23, have a negative effect. Overall, the results available so far point to a complex regulatory network controlling A40926 in the native producing strain.

Complex Regulatory Networks Governing Production of the Glycopeptide A40926.

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Alduina, Rosa; Sosio, Margherita; Donadio, Stefano

2018-04-05

Glycopeptides (GPAs) are an important class of antibiotics, with vancomycin and teicoplanin being used in the last 40 years as drugs of last resort to treat infections caused by Gram-positive pathogens, including methicillin-resistant Staphylococcus aureus . A few new GPAs have since reached the market. One of them is dalbavancin, a derivative of A40926 produced by the actinomycete Nonomuraea sp. ATCC 39727, recently classified as N. gerenzanensis . This review summarizes what we currently know on the multilevel regulatory processes governing production of the glycopeptide A40926 and the different approaches used to increase antibiotic yields. Some nutrients, e.g., valine, l-glutamine and maltodextrin, and some endogenous proteins, e.g., Dbv3, Dbv4 and RpoB R , have a positive role on A40926 biosynthesis, while other factors, e.g., phosphate, ammonium and Dbv23, have a negative effect. Overall, the results available so far point to a complex regulatory network controlling A40926 in the native producing strain.

Candida albicans and bacterial microbiota interactions in the cecum during recolonization following broad-spectrum antibiotic therapy.

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Mason, Katie L; Erb Downward, John R; Mason, Kelly D; Falkowski, Nicole R; Eaton, Kathryn A; Kao, John Y; Young, Vincent B; Huffnagle, Gary B

2012-10-01

Candida albicans is a normal member of the gastrointestinal (GI) tract microbiota of healthy humans, but during host immunosuppression or alterations in the bacterial microbiota, C. albicans can disseminate and cause life-threatening illness. The bacterial microbiome of the GI tract, including lactic acid bacteria (LAB), plays a vital role in preventing fungal invasion. However, little is known about the role of C. albicans in shaping the bacterial microbiota during antibiotic recovery. We investigated the fungal burdens in the GI tracts of germfree mice and mice with a disturbed microbiome to demonstrate the role of the microbiota in preventing C. albicans colonization. Histological analysis demonstrated that colonization with C. albicans during antibiotic treatment does not trigger overt inflammation in the murine cecum. Bacterial diversity is reduced long term following cefoperazone treatment, but the presence of C. albicans during antibiotic recovery promoted the recovery of bacterial diversity. Cefoperazone diminishes Bacteroidetes populations long term in the ceca of mice, but the presence of C. albicans during cefoperazone recovery promoted Bacteroidetes population recovery. However, the presence of C. albicans resulted in a long-term reduction in Lactobacillus spp. and promoted Enterococcus faecalis populations. Previous studies have focused on the ability of bacteria to alter C. albicans; this study addresses the ability of C. albicans to alter the bacterial microbiota during nonpathogenic colonization.

Rheumatoid arthritis patients exhibit impaired Candida albicans-specific Th17 responses.

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Bishu, Shrinivas; Su, Ee Wern; Wilkerson, Erich R; Reckley, Kelly A; Jones, Donald M; McGeachy, Mandy J; Gaffen, Sarah L; Levesque, Marc C

2014-02-11

Accumulating data implicate the CD4+ T cell subset (Th17 cells) in rheumatoid arthritis (RA). IL-17 is an inflammatory cytokine that induces tumor necrosis factor (TNF)α, IL-1β and IL-6, all of which are targets of biologic therapies used to treat RA. RA patients are well documented to experience more infections than age-matched controls, and biologic therapies further increase the risk of infection. The Th17/IL-17 axis is vital for immunity to fungi, especially the commensal fungus Candida albicans. Therefore, we were prompted to examine the relationship between RA and susceptibility to C. albicans because of the increasing interest in Th17 cells and IL-17 in driving autoimmunity, and the advent of new biologics that target this pathway. We analyzed peripheral blood and saliva from 48 RA and 33 healthy control subjects. To assess C. albicans-specific Th17 responses, PBMCs were co-cultured with heat-killed C. albicans extract, and IL-17A levels in conditioned supernatants were measured by ELISA. The frequency of Th17 and Th1 cells was determined by flow cytometry. As a measure of IL-17A-mediated effector responses, we evaluated C. albicans colonization rates in the oral cavity, salivary fungicidal activity and levels of the antimicrobial peptide β-defensin 2 (BD2) in saliva. Compared to controls, PBMCs from RA subjects exhibited elevated baseline production of IL-17A (P = 0.004), although they had similar capacity to produce IL-17A in response to Th17 cell differentiating cytokines (P = 0.91). However RA PBMCs secreted less IL-17A in response to C. albicans antigens (P = 0.006). Significantly more RA patients were colonized with C. albicans in the oral cavity than healthy subjects (P = 0.02). Concomitantly, RA saliva had reduced concentrations of salivary BD2 (P = 0.02). Nonetheless, salivary fungicidal activity was preserved in RA subjects (P = 0.70). RA subjects exhibit detectable impairments in oral immune responses to C. albicans, a

Multi-tissue omics analyses reveal molecular regulatory networks for puberty in composite beef cattle

Science.gov (United States)

Puberty is a complex physiological event by which animals mature into an adult capable of sexual reproduction. In order to enhance our understanding of the genes and regulatory pathways and networks involved in puberty, we characterized the transcriptome of five reproductive tissues (i.e., hypothal...

Recurrent neural network-based modeling of gene regulatory network using elephant swarm water search algorithm.

Science.gov (United States)

Mandal, Sudip; Saha, Goutam; Pal, Rajat Kumar

2017-08-01

Correct inference of genetic regulations inside a cell from the biological database like time series microarray data is one of the greatest challenges in post genomic era for biologists and researchers. Recurrent Neural Network (RNN) is one of the most popular and simple approach to model the dynamics as well as to infer correct dependencies among genes. Inspired by the behavior of social elephants, we propose a new metaheuristic namely Elephant Swarm Water Search Algorithm (ESWSA) to infer Gene Regulatory Network (GRN). This algorithm is mainly based on the water search strategy of intelligent and social elephants during drought, utilizing the different types of communication techniques. Initially, the algorithm is tested against benchmark small and medium scale artificial genetic networks without and with presence of different noise levels and the efficiency was observed in term of parametric error, minimum fitness value, execution time, accuracy of prediction of true regulation, etc. Next, the proposed algorithm is tested against the real time gene expression data of Escherichia Coli SOS Network and results were also compared with others state of the art optimization methods. The experimental results suggest that ESWSA is very efficient for GRN inference problem and performs better than other methods in many ways.

Tissue-specific expression and regulatory networks of pig microRNAome.

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Paolo Martini

Full Text Available BACKGROUND: Despite the economic and medical importance of the pig, knowledge about its genome organization, gene expression regulation, and molecular mechanisms involved in physiological processes is far from that achieved for mouse and rat, the two most used model organisms in biomedical research. MicroRNAs (miRNAs are a wide class of molecules that exert a recognized role in gene expression modulation, but only 280 miRNAs in pig have been characterized to date. RESULTS: We applied a novel computational approach to predict species-specific and conserved miRNAs in the pig genome, which were then subjected to experimental validation. We experimentally identified candidate miRNAs sequences grouped in high-confidence (424 and medium-confidence (353 miRNAs according to RNA-seq results. A group of miRNAs was also validated by PCR experiments. We established the subtle variability in expression of isomiRs and miRNA-miRNA star couples supporting a biological function for these molecules. Finally, miRNA and mRNA expression profiles produced from the same sample of 20 different tissue of the animal were combined, using a correlation threshold to filter miRNA-target predictions, to identify tissue-specific regulatory networks. CONCLUSIONS: Our data represent a significant progress in the current understanding of miRNAome in pig. The identification of miRNAs, their target mRNAs, and the construction of regulatory circuits will provide new insights into the complex biological networks in several tissues of this important animal model.

Efek Antijamur Minyak Atsiri Jahe Merah (Zingiber officinale Var. Rubrum terhadap Candida albicans

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Hermina Karuna Atmaja

2015-10-01

Full Text Available The prevalence of Candida albicans infections is increasing in the society. Therefore, an effective and affordable antifungal drug with minimal side effect is needed. Ginger (Zingiber officinale is a traditional herb which has an antifungal effect in its volatile oil. Objective: To investigate antifungal effect of volatile oil from Zingiber officinale var rubrum against C. albicans in vitro, to determine the optimum concentration, and finally to determine the correlation between the various concentrations of the oil and the inhibition zone. Material and method: Strain C. albicans tested was obtained from the Department of Parasitology, Medical Faculty, University of Indonesia. Volatile oil of Zingiber officinale var. rubrum was produced from water and steam distillation of fresh ginger in BALLITRO, Bogor. Concentrations of the volatile oil used were 100%, 50%, 25%, 12,5% 6.25%, 3.125%, 1.56% and 0.78%. Methods used were colony counting and disk diffusion method (by using 6 mm blank disk. The specimens were divided into two groups, treatment group (C. albicans with application of volatile oil and control group (C. albicans without application of volatile oil. Result: There was a significant decrease in the amount of C. albicans colonies from 3.125% to 6.25% of concentration. The amount of C. albicans colonies at concentration 6.25% was also significantly lower than in the control group. Moreover, there was strong and positive correlation between the concentration of the volatile oil and the inhibition zone. Conclusion: Volatile oil from Zingiber officinale var. rubrum has an antifungal effect against C. albicans in vitro with optimum concentration at 6.25%. Increasing concentrations of the oil correlates with increasing inhibition zome.

Generation of intervention strategy for a genetic regulatory network represented by a family of Markov Chains.

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Berlow, Noah; Pal, Ranadip

2011-01-01

Genetic Regulatory Networks (GRNs) are frequently modeled as Markov Chains providing the transition probabilities of moving from one state of the network to another. The inverse problem of inference of the Markov Chain from noisy and limited experimental data is an ill posed problem and often generates multiple model possibilities instead of a unique one. In this article, we address the issue of intervention in a genetic regulatory network represented by a family of Markov Chains. The purpose of intervention is to alter the steady state probability distribution of the GRN as the steady states are considered to be representative of the phenotypes. We consider robust stationary control policies with best expected behavior. The extreme computational complexity involved in search of robust stationary control policies is mitigated by using a sequential approach to control policy generation and utilizing computationally efficient techniques for updating the stationary probability distribution of a Markov chain following a rank one perturbation.

Otite externe maligne à Candida Albicans

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Elayoubi, Fahd; Lachkar, Azeddine; Aabach, Ahmed; Chouai, Mohamed; Ghailan, Mohamed Rachid

2016-01-01

L’otite externe maligne est une ostéomyélite de la base du crane. Le Pseudomonas aeruginosa est le germe le plus incriminé. Cependant l’origine fongique n’est pas rare. Patiente âgée de 80 ans avait présenté une otalgie gauche persistante depuis deux mois malgré un traitement bien conduit. L’examen otologique mettait en évidence des signes inflammatoires au niveau du pavillon, une sténose du conduit avec des granulomes, et otorrhée d’allure purulente. Le scanner montrait un comblement otomastoïdien, un processus inflammatoire extensif des tissus pré et rétro-auriculaire et une lyse du tympanal. Vu l’absence d’amélioration un examen mycologique a été réalisé et qui a révélé la présence de Candida Albicans. Les cas d’otite externe maligne à Candida Albicans sont rarement rapportés. L’origine fongique doit être suspecté devant la négativité des prélèvements bactériologiques et la non amélioration malgré un traitement antibiotique bien conduit, et confirmée par des prélèvements mycologiques parfois multiples. L’otite externe maligne à Candida Albicans est une infection rare potentiellement mortelle. PMID:28154677

Diversity and plasticity of Th cell types predicted from regulatory network modelling.

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Aurélien Naldi

Full Text Available Alternative cell differentiation pathways are believed to arise from the concerted action of signalling pathways and transcriptional regulatory networks. However, the prediction of mammalian cell differentiation from the knowledge of the presence of specific signals and transcriptional factors is still a daunting challenge. In this respect, the vertebrate hematopoietic system, with its many branching differentiation pathways and cell types, is a compelling case study. In this paper, we propose an integrated, comprehensive model of the regulatory network and signalling pathways controlling Th cell differentiation. As most available data are qualitative, we rely on a logical formalism to perform extensive dynamical analyses. To cope with the size and complexity of the resulting network, we use an original model reduction approach together with a stable state identification algorithm. To assess the effects of heterogeneous environments on Th cell differentiation, we have performed a systematic series of simulations considering various prototypic environments. Consequently, we have identified stable states corresponding to canonical Th1, Th2, Th17 and Treg subtypes, but these were found to coexist with other transient hybrid cell types that co-express combinations of Th1, Th2, Treg and Th17 markers in an environment-dependent fashion. In the process, our logical analysis highlights the nature of these cell types and their relationships with canonical Th subtypes. Finally, our logical model can be used to explore novel differentiation pathways in silico.

Comparison of the adhesion ability of Candida albicans strains to ...

African Journals Online (AJOL)

The purpose of the present study is to investigate the ability of oral Candida albicans strains to adhere to Caco-2 and Hep-2 epithelial cells, to produce slime using Congo red and Safranin methods and to form a biofilm on polymethylmethacrylate. A total of 20 C. albicans strains were tested in the present work. The biofilm ...

Policy and Regulatory Roadmaps for the Integration of Distributed Generation and the Development of Sustainable Electricity Networks. Final Report of the SUSTELNET project

International Nuclear Information System (INIS)

Scheepers, M.J.J.

2004-08-01

The SUSTELNET project has been created to identify criteria for a regulatory framework for future electricity markets and network structures that create a level playing field between centralised and decentralised generation and facilitate the integration of renewable energy sources (RES). Furthermore, the objective of the project was to develop regulatory roadmaps for the transition to a sustainable electricity market and network structure. This report summarizes the results of the project. These results consist of: criteria, guidelines and rationales for a future electricity policy and regulatory framework, an outline for the development of regulatory roadmaps and nine national regulatory roadmaps (for Denmark, Germany, Italy, the Netherlands, United Kingdom, Czech Republic, Poland, Hungary and Slovakia), recommendations for a European regulatory policy on distributed generation and a benchmark study of current Member States policies towards distributed generation

EFEITO ANTIFÚNGICO DO RESVERATROL SOBRE A CANDIDA ALBICANS

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Bruna Graziele Marques da Silva

2017-05-01

Full Text Available A Candida albicans é um fungo comensal da microbiota normal, sendo capaz de produzir infecções em pacientes imunocomprometidos. As infecções estão apresentando resistência às terapias convencionais. Recentemente diversos compostos derivados de produtos naturais vêm sendo testados, destacando o polifenol Resveratrol que possui efeitos farmacológicos. Desse modo o objetivo deste estudo foi avaliar os efeitos do polifenol sobre o crescimento e a viabilidade do biofilme da C. albicans. Foram utilizadas as concentrações do Resveratrol em 5 μΜ, 10 μΜ, 20 μΜ, 50 μΜ, 100 μΜ, 200 μΜ, 300μΜ, 400μΜ e 500μΜ e a densidade de C.albicans foram de 105, 106 e 107 células viáveis/ml, e ainda, foi analisada a morfologia. Os resultados obtidos demonstram maior inibição no crescimento e viabilidade do biofilme na concentração de 500μΜ de polifenol, em comparação ao controle. Dessa forma, o polifenol Resveratrol foi capaz de alterar a morfologia das células e reduzir a viabilidade do biofilme da Candida albicans.

Sputum Candida albicans presages FEV₁ decline and hospital-treated exacerbations in cystic fibrosis.

LENUS (Irish Health Repository)

Chotirmall, Sanjay H

2010-11-01

The role of Candida albicans in the cystic fibrosis (CF) airway is underexplored. Considered a colonizer, few question its pathogenic potential despite high isolation frequencies from sputum culture. We evaluated the frequency and identified the strongest predictors of C albicans colonization in CF. Independent associations of colonization with clinical outcomes were determined, and the longitudinal effects of C albicans acquisition on BMI and FEV₁ were evaluated.

[Sporulation or competence development? A genetic regulatory network model of cell-fate determination in Bacillus subtilis].

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Lu, Zhenghui; Zhou, Yuling; Zhang, Xiaozhou; Zhang, Guimin

2015-11-01

Bacillus subtilis is a generally recognized as safe (GRAS) strain that has been widely used in industries including fodder, food, and biological control. In addition, B. subtilis expression system also plays a significant role in the production of industrial enzymes. However, its application is limited by its low sporulation frequency and transformation efficiency. Immense studies have been done on interpreting the molecular mechanisms of sporulation and competence development, whereas only few of them were focused on improving sporulation frequency and transformation efficiency of B. subtilis by genetic modification. The main challenge is that sporulation and competence development, as the two major developmental events in the stationary phase of B. subtilis, are regulated by the complicated intracellular genetic regulatory systems. In addition, mutual regulatory mechanisms also exist in these two developmental events. With the development of genetic and metabolic engineering, constructing genetic regulatory networks is currently one of the most attractive research fields, together with the genetic information of cell growth, metabolism, and development, to guide the industrial application. In this review, the mechanisms of sporulation and competence development of B. subtilis, their interactions, and the genetic regulation of cell growth were interpreted. In addition, the roles of these regulatory networks in guiding basic and applied research of B. subtilis and its related species were discussed.

Evaluation of adhesion forces of Staphylococcus aureus along the length of Candida albicans hyphae.

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Ovchinnikova, Ekaterina S; Krom, Bastiaan P; Busscher, Henk J; van der Mei, Henny C

2012-11-27

Candida albicans is a human fungal pathogen, able to cause both superficial and serious, systemic diseases and is able to switch from yeast cells to long, tube-like hyphae, depending on the prevailing environmental conditions. Both morphological forms of C. albicans are found in infected tissue, often in combination with Staphylococcus aureus. Although bacterial adhesion to the different morphologies of C. albicans has been amply studied, possible differences in staphylococcal adhesion forces along the length of C. albicans hyphae have never been determined. In this study, we aim to verify the hypothesis that the forces mediating S. aureus NCTC8325-4GFP adhesion to hyphae vary along the length of C. albicans SC5314 and MB1 hyphae, as compared with adhesion to yeast cells. C. albicans hyphae were virtually divided into a "tip" (the growing and therefore youngest part of the hyphae), a "middle" and a so-called "head" region (the yeast cell from which germination started). Adhesion forces between S. aureus NCTC8325-4GFP and the different regions of C. albicans SC5314 hyphae were measured using atomic force microscopy. Strong adhesion forces were found at the tip and middle regions of C. albicans hyphae (-4.1 nN and -4.0 nN, respectively), while much smaller adhesion forces were measured at the head region (-0.3 nN). Adhesion forces exerted by the head region were comparable with the forces arising from budding yeast cells (-0.5 nN). A similar regional dependence of the staphylococcal adhesion forces was found for the clinical isolate involved in this study, C. albicans MB1. This is the first time that differences in adhesion forces between S. aureus and different regions of C. albicans hyphae have been demonstrated on a quantitative basis, supporting the view that the head region is different from the remainder of the hyphae. Notably it can be concluded that the properties of the hyphal head region are similar to those of budding yeast cells. These novel findings

Susceptibility of Candida albicans Isolated from Blood to Wickerhamomyces anomalous Mycocins.

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Paris, Ana Paula; Persel, Cristiane; Serafin, Cleber Fernando; de Cássia Garcia Simão, Rita; Gandra, Rinaldo Ferreira

2016-12-01

The occurrence of infections caused by Candida albicans in developed and developing countries and their resistance to some available antifungal drugs have been viewed as causing a great problem to human health worldwide. In order to find new researched molecules, there are some mycoses secreted by yeasts, especially mycocins produced by Wickerhamomyces anomalus with a broad antimicrobial spectrum of activity. Thus, this trial aimed at evaluating mycocins' activity obtained from environmental W. anomalus cell wall compared to thirty C. albicans strains isolated from blood. Mycocins were extracted from cell walls of three W. anomalus strains (WA40, WA45, and WA92). The 400 μg mL -1 concentration of WA40M1, WA45M2, and WA92M3 mycocin extracts showed the following respective activity results: 96.6, 96.6, and 90.0 % C. albicans strains. WA45M2 and WA92M3 mycocin extracts showed some activity in 3.3 % of C. albicans strains at 50 μg mL -1 concentration. Mycocins extracted from cell walls of three W. anomalus strains named as WA40, WA45, and WA92 showed antifungal activity compared to C. albicans and low degree of hemolysis.

Competitive Interactions between C. albicans, C. glabrata and C. krusei during Biofilm Formation and Development of Experimental Candidiasis

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Rossoni, Rodnei Dennis; Barbosa, Júnia Oliveira; Vilela, Simone Furgeri Godinho; dos Santos, Jéssica Diane; de Barros, Patrícia Pimentel; Prata, Márcia Cristina de Azevedo; Anbinder, Ana Lia; Fuchs, Beth Burgwyn; Jorge, Antonio Olavo Cardoso; Mylonakis, Eleftherios; Junqueira, Juliana Campos

2015-01-01

In this study, we evaluated the interactions between Candida albicans, Candida krusei and Candida glabrata in mixed infections. Initially, these interactions were studied in biofilms formed in vitro. CFU/mL values of C. albicans were lower in mixed biofilms when compared to the single biofilms, verifying 77% and 89% of C. albicans reduction when this species was associated with C. glabrata and C. krusei, respectively. After that, we expanded this study for in vivo host models of experimental candidiasis. G. mellonella larvae were inoculated with monotypic and heterotypic Candida suspensions for analysis of survival rate and quantification of fungal cells in the haemolymph. In the groups with single infections, 100% of the larvae died within 18 h after infection with C. albicans. However, interaction groups achieved 100% mortality after 72 h of infection by C. albicans-C. glabrata and 96 h of infection by C. albicans-C. krusei. C. albicans CFU/mL values from larvae hemolymph were lower in the interacting groups compared with the monoespecies group after 12 h of infection. In addition, immunosuppressed mice were also inoculated with monotypic and heterotypic microbial suspensions to induce oral candidiasis. C. albicans CFU/mL values recovered from oral cavity of mice were higher in the group with single infection by C. albicans than the groups with mixed infections by C. albicans-C. glabrata and C. albicans-C. krusei. Moreover, the group with single infection by C. albicans had a higher degree of hyphae and epithelial changes in the tongue dorsum than the groups with mixed infections. We concluded that single infections by C. albicans were more harmful for animal models than mixed infections with non-albicans species, suggesting that C. albicans establish competitive interactions with C. krusei and C. glabrata during biofilm formation and development of experimental candidiasis. PMID:26146832

Competitive Interactions between C. albicans, C. glabrata and C. krusei during Biofilm Formation and Development of Experimental Candidiasis.

Science.gov (United States)

Rossoni, Rodnei Dennis; Barbosa, Júnia Oliveira; Vilela, Simone Furgeri Godinho; dos Santos, Jéssica Diane; de Barros, Patrícia Pimentel; Prata, Márcia Cristina de Azevedo; Anbinder, Ana Lia; Fuchs, Beth Burgwyn; Jorge, Antonio Olavo Cardoso; Mylonakis, Eleftherios; Junqueira, Juliana Campos

2015-01-01

In this study, we evaluated the interactions between Candida albicans, Candida krusei and Candida glabrata in mixed infections. Initially, these interactions were studied in biofilms formed in vitro. CFU/mL values of C. albicans were lower in mixed biofilms when compared to the single biofilms, verifying 77% and 89% of C. albicans reduction when this species was associated with C. glabrata and C. krusei, respectively. After that, we expanded this study for in vivo host models of experimental candidiasis. G. mellonella larvae were inoculated with monotypic and heterotypic Candida suspensions for analysis of survival rate and quantification of fungal cells in the haemolymph. In the groups with single infections, 100% of the larvae died within 18 h after infection with C. albicans. However, interaction groups achieved 100% mortality after 72 h of infection by C. albicans-C. glabrata and 96 h of infection by C. albicans-C. krusei. C. albicans CFU/mL values from larvae hemolymph were lower in the interacting groups compared with the monoespecies group after 12 h of infection. In addition, immunosuppressed mice were also inoculated with monotypic and heterotypic microbial suspensions to induce oral candidiasis. C. albicans CFU/mL values recovered from oral cavity of mice were higher in the group with single infection by C. albicans than the groups with mixed infections by C. albicans-C. glabrata and C. albicans-C. krusei. Moreover, the group with single infection by C. albicans had a higher degree of hyphae and epithelial changes in the tongue dorsum than the groups with mixed infections. We concluded that single infections by C. albicans were more harmful for animal models than mixed infections with non-albicans species, suggesting that C. albicans establish competitive interactions with C. krusei and C. glabrata during biofilm formation and development of experimental candidiasis.

Proper Sterol Distribution Is Required for Candida albicans Hyphal Formation and Virulence

OpenAIRE

McCourt, Paula; Liu, Hsing-Yin; Parker, Josie E.; Gallo-Ebert, Christina; Donigan, Melissa; Bata, Adam; Giordano, Caroline; Kelly, Steven L.; Nickels, Joseph T.

2016-01-01

Candida albicans is an opportunistic fungus responsible for the majority of systemic fungal infections. Multiple factors contribute to C. albicans pathogenicity. C. albicans strains lacking CaArv1 are avirulent. Arv1 has a conserved Arv1 homology domain (AHD) that has a zinc-binding domain containing two cysteine clusters. Here, we explored the role of the CaAHD and zinc-binding motif in CaArv1-dependent virulence. Overall, we found that the CaAHD was necessary but not sufficient for cells to...

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.

Sieve-based relation extraction of gene regulatory networks from biological literature.

Science.gov (United States)

Žitnik, Slavko; Žitnik, Marinka; Zupan, Blaž; Bajec, Marko

2015-01-01

Relation extraction is an essential procedure in literature mining. It focuses on extracting semantic relations between parts of text, called mentions. Biomedical literature includes an enormous amount of textual descriptions of biological entities, their interactions and results of related experiments. To extract them in an explicit, computer readable format, these relations were at first extracted manually from databases. Manual curation was later replaced with automatic or semi-automatic tools with natural language processing capabilities. The current challenge is the development of information extraction procedures that can directly infer more complex relational structures, such as gene regulatory networks. We develop a computational approach for extraction of gene regulatory networks from textual data. Our method is designed as a sieve-based system and uses linear-chain conditional random fields and rules for relation extraction. With this method we successfully extracted the sporulation gene regulation network in the bacterium Bacillus subtilis for the information extraction challenge at the BioNLP 2013 conference. To enable extraction of distant relations using first-order models, we transform the data into skip-mention sequences. We infer multiple models, each of which is able to extract different relationship types. Following the shared task, we conducted additional analysis using different system settings that resulted in reducing the reconstruction error of bacterial sporulation network from 0.73 to 0.68, measured as the slot error rate between the predicted and the reference network. We observe that all relation extraction sieves contribute to the predictive performance of the proposed approach. Also, features constructed by considering mention words and their prefixes and suffixes are the most important features for higher accuracy of extraction. Analysis of distances between different mention types in the text shows that our choice of transforming

HiDi: an efficient reverse engineering schema for large-scale dynamic regulatory network reconstruction using adaptive differentiation

KAUST Repository

Deng, Yue

2017-08-05

Motivation: The use of differential equations (ODE) is one of the most promising approaches to network inference. The success of ODE-based approaches has, however, been limited, due to the difficulty in estimating parameters and by their lack of scalability. Here, we introduce a novel method and pipeline to reverse engineer gene regulatory networks from gene expression of time series and perturbation data based upon an improvement on the calculation scheme of the derivatives and a pre-filtration step to reduce the number of possible links. The method introduces a linear differential equation model with adaptive numerical differentiation that is scalable to extremely large regulatory networks. Results: We demonstrate the ability of this method to outperform current state-of-the-art methods applied to experimental and synthetic data using test data from the DREAM4 and DREAM5 challenges. Our method displays greater accuracy and scalability. We benchmark the performance of the pipeline with respect to dataset size and levels of noise. We show that the computation time is linear over various network sizes.

Candida krusei and Candida glabrata reduce the filamentation of Candida albicans by downregulating expression of HWP1 gene.

Science.gov (United States)

de Barros, Patrícia Pimentel; Freire, Fernanda; Rossoni, Rodnei Dennis; Junqueira, Juliana Campos; Jorge, Antonio Olavo Cardoso

2017-07-01

Pathogenicity of Candida albicans is associated with its capacity switch from yeast-like to hyphal growth. The hyphal form is capable to penetrate the epithelial surfaces and to damage the host tissues. Therefore, many investigations have focused on mechanisms that control the morphological transitions of C. albicans. Recently, certain studies have showed that non-albicans Candida species can reduce the capacity of C. albicans to form biofilms and to develop candidiasis in animal models. Then, the objective of this study was to evaluate the effects of Candida krusei and Candida glabrata on the morphogenesis of C. albicans. Firstly, the capacity of reference and clinical strains of C. albicans in forming hyphae was tested in vitro. After that, the expression of HWP1 (hyphal wall protein 1) gene was determined by quantitative real-time PCR (polymerase chain reaction) assay. For both reference and clinical strains, a significant inhibition of the hyphae formation was observed when C. albicans was incubated in the presence of C. krusei or C. glabrata compared to the control group composed only by C. albicans. In addition, the culture mixed of C. albicans-C. krusei or C. albicans-C. glabrata reduced significantly the expression of HWP1 gene of C. albicans in relation to single cultures of this specie. In both filamentation and gene expression assays, C. krusei showed the higher inhibitory activity on the morphogenesis of C. albicans compared to C. glabrata. C. krusei and C. glabrata are capable to reduce the filamentation of C. albicans and consequently decrease the expression of the HWP1 gene.

A Kalman-filter based approach to identification of time-varying gene regulatory networks.

Directory of Open Access Journals (Sweden)

Jie Xiong

Full Text Available MOTIVATION: Conventional identification methods for gene regulatory networks (GRNs have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs. RESULTS: It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem.

New Clox Systems for rapid and efficient gene disruption in Candida albicans.

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Shahida Shahana

Full Text Available Precise genome modification is essential for the molecular dissection of Candida albicans, and is yielding invaluable information about the roles of specific gene functions in this major fungal pathogen of humans. C. albicans is naturally diploid, unable to undergo meiosis, and utilizes a non-canonical genetic code. Hence, specialized tools have had to be developed for gene disruption in C. albicans that permit the deletion of both target alleles, and in some cases, the recycling of the Candida-specific selectable markers. Previously, we developed a tool based on the Cre recombinase, which recycles markers in C. albicans with 90-100% efficiency via site-specific recombination between loxP sites. Ironically, the utility of this system was hampered by the extreme efficiency of Cre, which prevented the construction in Escherichia coli of stable disruption cassettes carrying a methionine-regulatable CaMET3p-cre gene flanked by loxP sites. Therefore, we have significantly enhanced this system by engineering new Clox cassettes that carry a synthetic, intron-containing cre gene. The Clox kit facilitates efficient transformation and marker recycling, thereby simplifying and accelerating the process of gene disruption in C. albicans. Indeed, homozygous mutants can be generated and their markers resolved within two weeks. The Clox kit facilitates strategies involving single marker recycling or multi-marker gene disruption. Furthermore, it includes the dominant NAT1 marker, as well as URA3, HIS1 and ARG4 cassettes, thereby permitting the manipulation of clinical isolates as well as genetically marked strains of C. albicans. The accelerated gene disruption strategies afforded by this new Clox system are likely to have a profound impact on the speed with which C. albicans pathobiology can be dissected.

Commensal Protection of Staphylococcus aureus against Antimicrobials by Candida albicans Biofilm Matrix

Science.gov (United States)

Kong, Eric F.; Tsui, Christina; Kucharíková, Sona; Andes, David

2016-01-01

ABSTRACT Biofilm-associated polymicrobial infections, particularly those involving fungi and bacteria, are responsible for significant morbidity and mortality and tend to be challenging to treat. Candida albicans and Staphylococcus aureus specifically are considered leading opportunistic fungal and bacterial pathogens, respectively, mainly due to their ability to form biofilms on catheters and indwelling medical devices. However, the impact of mixed-species biofilm growth on therapy remains largely understudied. In this study, we investigated the influence of C. albicans secreted cell wall polysaccharides on the response of S. aureus to antibacterial agents in biofilm. Results demonstrated significantly enhanced tolerance for S. aureus to drugs in the presence of C. albicans or its secreted cell wall polysaccharide material. Fluorescence confocal time-lapse microscopy revealed impairment of drug diffusion through the mixed biofilm matrix. Using C. albicans mutant strains with modulated cell wall polysaccharide expression, exogenous supplementation, and enzymatic degradation, the C. albicans-secreted β-1,3-glucan cell wall component was identified as the key matrix constituent providing the bacteria with enhanced drug tolerance. Further, antibody labeling demonstrated rapid coating of the bacteria by the C. albicans matrix material. Importantly, via its effect on the fungal biofilm matrix, the antifungal caspofungin sensitized the bacteria to the drugs. Understanding such symbiotic interactions with clinical relevance between microbial species in biofilms will greatly aid in overcoming the limitations of current therapies and in defining potential new targets for treating polymicrobial infections. PMID:27729510

Metabolic response of Candida albicans to phenylethyl alcohol under hyphae-inducing conditions.

Science.gov (United States)

Han, Ting-Li; Tumanov, Sergey; Cannon, Richard D; Villas-Boas, Silas G

2013-01-01

Phenylethyl alcohol was one of the first quorum sensing molecules (QSMs) identified in C. albicans. This extracellular signalling molecule inhibits the hyphal formation of C. albicans at high cell density. Little is known, however, about the underlying mechanisms by which this QSM regulates the morphological switches of C. albicans. Therefore, we have applied metabolomics and isotope labelling experiments to investigate the metabolic changes that occur in C. albicans in response to phenylethyl alcohol under defined hyphae-inducing conditions. Our results showed a global upregulation of central carbon metabolism when hyphal development was suppressed by phenylethyl alcohol. By comparing the metabolic changes in response to phenylethyl alcohol to our previous metabolomic studies, we were able to short-list 7 metabolic pathways from central carbon metabolism that appear to be associated with C. albicans morphogenesis. Furthermore, isotope-labelling data showed that phenylethyl alcohol is indeed taken up and catabolised by yeast cells. Isotope-labelled carbon atoms were found in the majority of amino acids as well as in lactate and glyoxylate. However, isotope-labelled carbon atoms from phenylethyl alcohol accumulated mainly in the pyridine ring of NAD(+)/NADH and NADP(-/)NADPH molecules, showing that these nucleotides were the main products of phenylethyl alcohol catabolism. Interestingly, two metabolic pathways where these nucleotides play an important role, nitrogen metabolism and nicotinate/nicotinamide metabolism, were also short-listed through our previous metabolomics works as metabolic pathways likely to be closely associated with C. albicans morphogenesis.

Genetic structure of typical and atypical populations of Candida albicans from Africa.

Science.gov (United States)

Forche, A; Schönian, G; Gräser, Y; Vilgalys, R; Mitchell, T G

1999-11-01

Atypical isolates of the pathogenic yeast Candida albicans have been reported with increasing frequency. To investigate the origin of a set of atypical isolates and their relationship to typical isolates, we employed a combination of molecular phylogenetic and population genetic analyses using rDNA sequencing, PCR fingerprinting, and analysis of co-dominant DNA nucleotide polymorphisms to characterize the population structure of one typical and two atypical populations of C. albicans from Angola and Madagascar. The extent of clonality and recombination was assessed in each population. The analyses revealed that the structure of all three populations of C. albicans was predominantly clonal but, as in previous studies, there was also evidence for recombination. Allele frequencies differed significantly between the typical and the atypical populations, suggesting very low levels of gene flow between them. However, allele frequencies were quite similar in the two atypical C. albicans populations, suggesting that they are closely related. Phylogenetic analysis of partial sequences encoding the nuclear 26S rDNA demonstrated that all three populations belong to a single monophyletic group, which includes the type strain of C. albicans. Copyright 1999 Academic Press.

Menadione 処理した Candida albicans ROS 生産機構の解析

OpenAIRE

上野, 将明; 小笠原, 綾子; 渡部, 俊彦; 三上, 健; 松本, 達二; ウエノ, ユキヒロ; オガサワラ, アヤコ; ワタナベ, トシユキ; ミカミ, タケシ; マツモト, タツジ; Yukihiro, UENO; Ayako, OGASAWARA; Toshihiko, WATANABE; Takeshi, MIKAMI; Tatsuji, MATSUMOTO

2008-01-01

Menadione shows anti Condida activity by promoting ROS production. However, the ROS production mechanism has not been clarifield. Thus, in this study, we studied thr relation between anti Candida activity of menadione and ROS production. Menadione inhibited the growth of C. albicans BWP17 strain, the growth of C. albicans JM02 strain was not inhibited. ROS production in C. albicans BWP17 strain was enhanced by addition of menadione. The ROS production in C. albicans JM02 strain was also enhan...

Deoxyribonucleic acid-deficient strains of Candida albicans.

Science.gov (United States)

Olaiya, A F; Steed, J R; Sogin, S J

1980-03-01

We analyzed a series of germ tube-negative variants isolated from Candida albicans 3153A for deoxyribonucleic acid content. As analyzed by flow microfluorometry, the deoxyribonucleic acid level in these variant strains was 50% of that of the parental strain and equivalent to that of haploid Saccharomyces cerevisiae. This finding was confirmed by comparison of survival rates when exposed to the mutagens ultraviolet light, ethyl methane sulfonate, and methyl methane sulfonate. The diameter of the variant cells as compared to the diameter of the parental 3153A strain showed a relationship similar to that of the diameters of haploid versus diploid S. cerevisiae. These results indicate that those strains may be representative of the imperfect stage of C. albicans.

The efficacy of crude extract of Aloe secundiflora on Candida Albicans

African Journals Online (AJOL)

In- vitro studies on the efficacy of crude extracts of Aloe secundiflora on Candida albicans was conducted. Five mature leaves of Aloe secundiflora were collected and the crude extract was prepared, then autoclaved. The extract was then tested on Candida albicans grown on solid media. The results from these studies ...

The effect of squalene on inflammation factors induced by candida albicans in vivo studies

Energy Technology Data Exchange (ETDEWEB)

Lee, Jun Haeng [Dept. of Radiology, Nambu University, Gwangju (Korea, Republic of)

2016-09-15

In the present study, whether squalene treatment relives inflammatory reactions induced by Candida albicans was checked. The experiment was conducted in vivo using seven experimental animals (ICR mice) per experimental group. Among C. albicans-induced inflammatory factors, TNF-α, IL-6, and NO were observed using the ELISA kits method. Through the experiment, the following conclusions were obtained. 1. In the group infected with C. albicans, it could be identified that squalene treatment was inducing NO generation in renal tissues both on the 1st and 3rd days (p < 0.05). 2. In the group pre-treated(intraperitoneal administration) with SQ (80ml/kg) once per day for seven days and infected with C. albicans, it could be identified that squalene treatment was inducing TNF-α generation in renal tissues only on the 3rd day(p < 0.05). 3. In the group pre-treated(intraperitoneal administration) with SQ (80ml/kg) once per day for seven days and infected with C. albicans, it could be identified that squalene treatment was inducing IL-6 generation in renal tissues only on the 3rd day(p < 0.05). In conclusion, it could be seen that for squalene to suppress C. albicans-induced inflammatory factors, preemptively supplying SQ should be effective. Therefore, effects for recovery from C. albicans-induced immunodepression can be expected from SQ treatment.

Antifungal activity of Piper aduncum and Peperomia pellucida leaf ethanol extract against Candida albicans

Science.gov (United States)

Hastuti, Utami Sri; Ummah, Yunita Putri Irsadul; Khasanah, Henny Nurul

2017-05-01

This research was done to 1) examine the effect of Piper aduncum leaf ethanol extract at certain concentrations against Candida albicans colony growth inhibition in vitro; 2) examine the effect of Peperomia pellucida leaf ethanol extract at certain concentrations toward Candida albicans colony growth inhibition in vitro; and 3) determine the most effective concentration of P. aduncum and P. pellucida leaves ethanol extract against C. albicans colony growth inhibition in vitro. These plant extracts were prepared by the maceration technique using 95% ethanol, and then sterile filtered and evaporated to obtain the filtrate. The filtrate was diluted with sterile distilled water at certain concentrations, i.e.: 0%, 10%, 20%, 30%, 405, 50%, 60%, 70%, 80%, and 90%. The antifungal effect of each leaf extract concentration was examined by the agar diffusion method on Sabouraud Dextrose Agar medium. The research results are: 1) the P.aduncum leaf ethanol extract at some concentrations has an effect against C. albicans colony growth inhibition in vitro; 2) the P.pellucida leaf ethanol extract at some concentrations has an effect against C. albicans colony growth inhibition in vitro; 3) the P. aduncum leaf ethanol extract at 80% is the most effective for C. albicans colony growth inhibition in vitro; and 4) the P. pellucida leaf ethanol extract at 70% is the most effective for C. albicans colony growth inhibition in vitro.

Candida albicans adherence to resin-composite restorative dental material: influence of whole human saliva.

Science.gov (United States)

Maza, José Luis; Elguezabal, Natalia; Prado, Carlota; Ellacuría, Joseba; Soler, Iñaki; Pontón, José

2002-11-01

Attachment of Candida albicans to oral surfaces is believed to be a critical event in the colonization of the oral cavity and in the development of oral diseases such as Candida-associated denture stomatitis. Although there is considerable information about the adhesion of C albicans to buccal epithelial cells and prosthetic materials, there is very little information about the adhesion of C albicans to composite restorative materials. The purpose of this study was to investigate the degree of adhesion of C albicans to a resin-composite restorative material (Herculite). The adhesion of 2 strains of C albicans, a germinative and a germ tube-deficient mutant, was studied by a visual method after incubating the fungus and the resin with and without human whole saliva. In absence of saliva, the adhesion of the C albicans germinative isolate to the resin showed an increase in parallel with the germination, reaching a maximum at the end of the experiment (120 minutes). However, no significant differences were observed in the adhesion of the agerminative mutant during the period of time studied. In the presence of saliva, the adhesion of both isolates to the resin was significantly lowered. Germination and the presence of human whole saliva are important factors in the adhesion of C albicans to the resin-composite restorative material Herculite.

Perbandingan Daya Hambat Larutan Antiseptik Povidone iodine dengan Ekstrak Daun Sirih terhadap Candida albicans secara In Vitro

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Septriana Putri

2015-09-01

Full Text Available Abstrak Candida albicansb (C. albicans adalah salah satu mikroorganisme penyebab masalah kesehatan reproduksi wanita, yaitu keputihan (fluor albus. Penggunaan larutan povidone iodine dan bahan alam seperti ekstrak daun sirih menjadi pilihan masyarakat sebagai pembersih alat kewanitaan. Tujuan penelitian ini adalah untuk membandingkandaya hambat larutan antiseptik povidone iodine dan ekstrak daun sirih terhadap jamur C. albicans secara in vitro. Penelitian dilakukan terhadap lima isolat jamur C. albicans dengan larutan kontrol akuades.Perlakuan terdiri dari povidone iodine, ekstrak daun sirih dengan konsentrasi 5%, 10%, dan 20%.Hasil penelitian menunjukkan bahwa povidone iodine memiliki daya hambat terhadap C. albicans. Ekstrak daun sirih dengan konsentrasi 5% dan 10% tidak memiliki daya hambat terhadap C. albicans, namun ekstrak daun sirih konsentrasi 20% memiliki daya hambat terhadap C. albicans. Analisis statistik dengan uji ANOVA yang dilanjutkan dengan uji Post-hoc menunjukkan perbedaan bermakna antara daya hambat larutan povidone iodine dan ekstrak daun sirih 20% terhadap kontrol(p < 0.05.Larutan povidone iodine memiliki daya hambat dua kali lebih besar terhadap pertumbuhan C. albicans dibandingkan ekstrak daun sirih 20%. Dari penelitian ini dapat disimpulkan bahwa larutan povidone iodine dan ekstrak daun sirih 20% dapat menghambat pertumbuhan jamur C. albicans secara in vitro. Kata kunci: povidone iodine, ekstrak daun sirih, Candida albicansAbstract Candida albicans (C. albicans is one of the frequent causes of  reproductive health problems in women, namely vaginal discharge (fluor albus. The antiseptic solution, povidone iodine, is still an option to overcome vaginal discharge. The use of natural materials such as betel (Piper betle L. leaves extract also become a popular choice as adouche for women. The objective of this study was to compare the inhibitory activity of povidone iodine solution and betel leaf extract against the growth of

Streptococcus agalactiae Inhibits Candida albicans Hyphal Development and Diminishes Host Vaginal Mucosal TH17 Response.

Science.gov (United States)

Yu, Xiao-Yu; Fu, Fei; Kong, Wen-Na; Xuan, Qian-Kun; Wen, Dong-Hua; Chen, Xiao-Qing; He, Yong-Ming; He, Li-Hua; Guo, Jian; Zhou, Ai-Ping; Xi, Yang-Hong; Ni, Li-Jun; Yao, Yu-Feng; Wu, Wen-Juan

2018-01-01

Streptococcus agalactiae and Candida albicans often co-colonize the female genital tract, and under certain conditions induce mucosal inflammation. The role of the interaction between the two organisms in candidal vaginitis is not known. In this study, we found that co-infection with S. agalactiae significantly attenuated the hyphal development of C. albicans , and that EFG1 -Hwp1 signal pathway of C. albicans was involved in this process. In a mouse model of vulvovaginal candidiasis (VVC), the fungal burden and the levels of pro-inflammatory cytokines, IL-1β, IL-6 and TNF-α showed a increase on co-infection with S. agalactiae , while the level of TH17 T cells and IL-17 in the cervicovaginal lavage fluid were significantly decreased. Our results indicate that S. agalactiae inhibits C. albicans hyphal development by downregulating the expression of EFG1 -Hwp1. The interaction between S. agalactiae and C. albicans may attenuate host vaginal mucosal TH17 immunity and contribute to mucosal colonization by C. albicans .

A genomic approach to identify regulatory nodes in the transcriptional network of systemic acquired resistance in plants.

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Dong Wang

2006-11-01

Full Text Available Many biological processes are controlled by intricate networks of transcriptional regulators. With the development of microarray technology, transcriptional changes can be examined at the whole-genome level. However, such analysis often lacks information on the hierarchical relationship between components of a given system. Systemic acquired resistance (SAR is an inducible plant defense response involving a cascade of transcriptional events induced by salicylic acid through the transcription cofactor NPR1. To identify additional regulatory nodes in the SAR network, we performed microarray analysis on Arabidopsis plants expressing the NPR1-GR (glucocorticoid receptor fusion protein. Since nuclear translocation of NPR1-GR requires dexamethasone, we were able to control NPR1-dependent transcription and identify direct transcriptional targets of NPR1. We show that NPR1 directly upregulates the expression of eight WRKY transcription factor genes. This large family of 74 transcription factors has been implicated in various defense responses, but no specific WRKY factor has been placed in the SAR network. Identification of NPR1-regulated WRKY factors allowed us to perform in-depth genetic analysis on a small number of WRKY factors and test well-defined phenotypes of single and double mutants associated with NPR1. Among these WRKY factors we found both positive and negative regulators of SAR. This genomics-directed approach unambiguously positioned five WRKY factors in the complex transcriptional regulatory network of SAR. Our work not only discovered new transcription regulatory components in the signaling network of SAR but also demonstrated that functional studies of large gene families have to take into consideration sequence similarity as well as the expression patterns of the candidates.

Disruption of Sphingolipid Biosynthesis Blocks Phagocytosis of Candida albicans.

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Fikadu G Tafesse

2015-10-01

Full Text Available The ability of phagocytes to clear pathogens is an essential attribute of the innate immune response. The role of signaling lipid molecules such as phosphoinositides is well established, but the role of membrane sphingolipids in phagocytosis is largely unknown. Using a genetic approach and small molecule inhibitors, we show that phagocytosis of Candida albicans requires an intact sphingolipid biosynthetic pathway. Blockade of serine-palmitoyltransferase (SPT and ceramide synthase-enzymes involved in sphingolipid biosynthesis- by myriocin and fumonisin B1, respectively, impaired phagocytosis by phagocytes. We used CRISPR/Cas9-mediated genome editing to generate Sptlc2-deficient DC2.4 dendritic cells, which lack serine palmitoyl transferase activity. Sptlc2-/- DC2.4 cells exhibited a stark defect in phagocytosis, were unable to bind fungal particles and failed to form a normal phagocytic cup to engulf C. albicans. Supplementing the growth media with GM1, the major ganglioside present at the cell surface, restored phagocytic activity of Sptlc2-/- DC2.4 cells. While overall membrane trafficking and endocytic pathways remained functional, Sptlc2-/- DC2.4 cells express reduced levels of the pattern recognition receptors Dectin-1 and TLR2 at the cell surface. Consistent with the in vitro data, compromised sphingolipid biosynthesis in mice sensitizes the animal to C. albicans infection. Sphingolipid biosynthesis is therefore critical for phagocytosis and in vivo clearance of C. albicans.

The future of genome-scale modeling of yeast through integration of a transcriptional regulatory network

DEFF Research Database (Denmark)

Liu, Guodong; Marras, Antonio; Nielsen, Jens

2014-01-01

regulatory information is necessary to improve the accuracy and predictive ability of metabolic models. Here we review the strategies for the reconstruction of a transcriptional regulatory network (TRN) for yeast and the integration of such a reconstruction into a flux balance analysis-based metabolic model......Metabolism is regulated at multiple levels in response to the changes of internal or external conditions. Transcriptional regulation plays an important role in regulating many metabolic reactions by altering the concentrations of metabolic enzymes. Thus, integration of the transcriptional....... While many large-scale TRN reconstructions have been reported for yeast, these reconstructions still need to be improved regarding the functionality and dynamic property of the regulatory interactions. In addition, mathematical modeling approaches need to be further developed to efficiently integrate...

Species-specific activation of Cu/Zn SOD by its CCS copper chaperone in the pathogenic yeast Candida albicans.

Science.gov (United States)

Gleason, Julie E; Li, Cissy X; Odeh, Hana M; Culotta, Valeria C

2014-06-01

Candida albicans is a pathogenic yeast of important public health relevance. Virulence of C. albicans requires a copper and zinc containing superoxide dismutase (SOD1), but the biology of C. albicans SOD1 is poorly understood. To this end, C. albicans SOD1 activation was examined in baker's yeast (Saccharomyces cerevisiae), a eukaryotic expression system that has proven fruitful for the study of SOD1 enzymes from invertebrates, plants, and mammals. In spite of the 80% similarity between S. cerevisiae and C. albicans SOD1 molecules, C. albicans SOD1 is not active in S. cerevisiae. The SOD1 appears incapable of productive interactions with the copper chaperone for SOD1 (CCS1) of S. cerevisiae. C. albicans SOD1 contains a proline at position 144 predicted to dictate dependence on CCS1. By mutation of this proline, C. albicans SOD1 gained activity in S. cerevisiae, and this activity was independent of CCS1. We identified a putative CCS1 gene in C. albicans and created heterozygous and homozygous gene deletions at this locus. Loss of CCS1 resulted in loss of SOD1 activity, consistent with its role as a copper chaperone. C. albicans CCS1 also restored activity to C. albicans SOD1 expressed in S. cerevisiae. C. albicans CCS1 is well adapted for activating its partner SOD1 from C. albicans, but not SOD1 from S. cerevisiae. In spite of the high degree of homology between the SOD1 and CCS1 molecules in these two fungal species, there exists a species-specific barrier in CCS-SOD interactions which may reflect the vastly different lifestyles of the pathogenic versus the noninfectious yeast.

Candida albicans orf19.3727 encodes phytase activity and is essential for human tissue damage

Science.gov (United States)

Fong, Wing-Ping; Samaranayake, Lakshman Perera

2017-01-01

Candida albicans is a clinically important human fungal pathogen. We previously identified the presence of cell-associated phytase activity in C. albicans. Here, we reveal for the first time, that orf19.3727 contributes to phytase activity in C. albicans and ultimately to its virulence potency. Compared with its wild type counterpart, disruption of C. albicans orf19.3727 led to decreased phytase activity, reduced ability to form hyphae, attenuated in vitro adhesion, and reduced ability to penetrate human epithelium, which are the major virulence attributes of this yeast. Thus, orf19.3727 of C. albicans plays a key role in fungal pathogenesis. Further, our data uncover a putative novel strategy for anti-Candidal drug design through inhibition of phytase activity of this common pathogen. PMID:29216308

Phenotypic aspects of oral strains of Candida albicans in children with down's syndrome

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E. L. Ribeiro

Full Text Available The aim of this article is to characterize the biological aspects of oral strains of C. albicans in children with Down's syndrome. These yeasts were analyzed as to their macromorphological and enzymatic aspects and were tested as to their in vitro susceptibility to antifungal drugs using broth microdilution to determine the minimum inhibitory concentration (MIC. The morphotyping revealed that all oral C. albicans isolates from children with Down's syndrome promoted the formation of fringes regardless of size, while the control group presented smaller fringes. All oral C. albicans strains produced proteinase, but those with phospholipolytic activity showed greater enzyme capacity in the test group. In vitro susceptibility showed that all oral C. albicans isolates were sensitive to the drugs used.

Reduction of regulatory risk: a network economic approach

OpenAIRE

Knieps, Günter; Weiß, Hans-Jörg

2007-01-01

Several definitions of regulatory risk are known from the literature. From the perspective of regulatory reform it is important to differentiate between the impact of a given regulatory scheme on the firm's risk exposure and the risk arising from discretionary behavior of regulatory agencies. Whereas the conse-quences of effective regulation in principle are known and accepted, excessive regulatory discretion may cause a strong need for regulatory reform. Regulatory reform focussing on the re...

A complex regulatory network coordinating cell cycles during C. elegans development is revealed by a genome-wide RNAi screen.

Science.gov (United States)

Roy, Sarah H; Tobin, David V; Memar, Nadin; Beltz, Eleanor; Holmen, Jenna; Clayton, Joseph E; Chiu, Daniel J; Young, Laura D; Green, Travis H; Lubin, Isabella; Liu, Yuying; Conradt, Barbara; Saito, R Mako

2014-02-28

The development and homeostasis of multicellular animals requires precise coordination of cell division and differentiation. We performed a genome-wide RNA interference screen in Caenorhabditis elegans to reveal the components of a regulatory network that promotes developmentally programmed cell-cycle quiescence. The 107 identified genes are predicted to constitute regulatory networks that are conserved among higher animals because almost half of the genes are represented by clear human orthologs. Using a series of mutant backgrounds to assess their genetic activities, the RNA interference clones displaying similar properties were clustered to establish potential regulatory relationships within the network. This approach uncovered four distinct genetic pathways controlling cell-cycle entry during intestinal organogenesis. The enhanced phenotypes observed for animals carrying compound mutations attest to the collaboration between distinct mechanisms to ensure strict developmental regulation of cell cycles. Moreover, we characterized ubc-25, a gene encoding an E2 ubiquitin-conjugating enzyme whose human ortholog, UBE2Q2, is deregulated in several cancers. Our genetic analyses suggested that ubc-25 acts in a linear pathway with cul-1/Cul1, in parallel to pathways employing cki-1/p27 and lin-35/pRb to promote cell-cycle quiescence. Further investigation of the potential regulatory mechanism demonstrated that ubc-25 activity negatively regulates CYE-1/cyclin E protein abundance in vivo. Together, our results show that the ubc-25-mediated pathway acts within a complex network that integrates the actions of multiple molecular mechanisms to control cell cycles during development. Copyright © 2014 Roy et al.

Miltefosine inhibits Candida albicans and non-albicans Candida spp. biofilms and impairs the dispersion of infectious cells.

Science.gov (United States)

Vila, Taissa; Ishida, Kelly; Seabra, Sergio Henrique; Rozental, Sonia

2016-11-01

Candida spp. can adhere to and form biofilms over different surfaces, becoming less susceptible to antifungal treatment. Resistance of biofilms to antifungal agents is multifactorial and the extracellular matrix (ECM) appears to play an important role. Among the few available antifungals for treatment of candidaemia, only the lipid formulations of amphotericin B (AmB) and the echinocandins are effective against biofilms. Our group has previously demonstrated that miltefosine has an important effect against Candida albicans biofilms. Thus, the aim of this work was to expand the analyses of the in vitro antibiofilm activity of miltefosine to non-albicans Candida spp. Miltefosine had significant antifungal activity against planktonic cells and the development of biofilms of C. albicans, Candida parapsilosis, Candida tropicalis and Candida glabrata. The activity profile in biofilms was superior to fluconazole and was similar to that of AmB and caspofungin. Biofilm-derived cells with their ECM extracted became as susceptible to miltefosine as planktonic cells, confirming the importance of the ECM in the biofilm resistant behaviour. Miltefosine also inhibited biofilm dispersion of cells at the same concentration needed to inhibit planktonic cell growth. The data obtained in this work reinforce the potent inhibitory activity of miltefosine on biofilms of the four most pathogenic Candida spp. and encourage further studies for the utilisation of this drug and/or structural analogues on biofilm-related infections. Copyright © 2016 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

Modularity of gene-regulatory networks revealed in sea-star development

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Degnan Bernard M

2011-01-01

Full Text Available Abstract Evidence that conserved developmental gene-regulatory networks can change as a unit during deutersostome evolution emerges from a study published in BMC Biology. This shows that genes consistently expressed in anterior brain patterning in hemichordates and chordates are expressed in a similar spatial pattern in another deuterostome, an asteroid echinoderm (sea star, but in a completely different developmental context (the animal-vegetal axis. This observation has implications for hypotheses on the type of development present in the deuterostome common ancestor. See research article: http://www.biomedcentral.com/1741-7007/8/143/abstract

A Case Report of Penile Infection Caused by Fluconazole- and Terbinafine-Resistant Candida albicans.

Science.gov (United States)

Hu, Yongxuan; Hu, Yanqing; Lu, Yan; Huang, Shiyun; Liu, Kangxing; Han, Xue; Mao, Zuhao; Wu, Zhong; Zhou, Xianyi

2017-04-01

Candida albicans is the most common pathogen that causes balanoposthitis. It often causes recurrence of symptoms probably due to its antifungal resistance. A significant number of balanitis Candida albicans isolates are resistant to azole and terbinafine antifungal agents in vitro. However, balanoposthitis caused by fluconazole- and terbinafine-resistant Candida albicans has rarely been reported. Here, we describe a case of a recurrent penile infection caused by fluconazole- and terbinafine-resistant Candida albicans, as well as the treatments administered to this patient. The isolate from the patient was tested for drug susceptibility in vitro. It was sensitive to itraconazole, voriconazole, clotrimazole and amphotericin B, but not to terbinafine and fluconazole. Thus, oral itraconazole was administrated to this patient with resistant Candida albicans penile infection. The symptoms were improved, and mycological examination result was negative. Follow-up treatment of this patient for 3 months showed no recurrence.

Small Rna Regulatory Networks In Pseudomonas Putida

DEFF Research Database (Denmark)

Bojanovic, Klara; Long, Katherine

2015-01-01

chemicals and has a potential to be used as an efficient cell factory for various products. P. putida KT2240 is a genome-sequenced strain and a well characterized pseudomonad. Our major aim is to identify small RNA molecules (sRNAs) and their regulatory networks. A previous study has identified 37 sRNAs...... in this strain, while in other pseudomonads many more sRNAs have been found so far.P. putida KT2440 has been grown in different conditions which are likely to be encountered in industrial fermentations with the aim of using sRNAs for generation of improved cell factories. For that, cells have been grown in LB......Pseudomonas putida is a ubiquitous Gram-negative soil bacterium with a versatile metabolism and ability to degrade various toxic compounds. It has a high tolerance to different future biobased building blocks and various other stringent conditions. It is used in industry to produce some important...

Antimicrobial activity of plant extracts on Candida albicans: An in vitro study

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Sunitha Jagalur Doddanna

2013-01-01

Full Text Available Background and Objectives: Plants as sources of medicinal compounds have continued to play a predominant role in the maintenance of human health since ancient times. Even though several effective antifungal agents are available for oral candida infections, the failure is not uncommon because isolates of Candida albicans may exhibits resistance to the drug during therapy. The present study was conducted to evaluate the antimicrobial effects of few plant extracts on Candida albicans. An additional objective was to identify an alternative, inexpensive, simple, and effective method of preventing and controlling Candida albicans. Materials and Methods: Fine texture powder or paste form of leaves was soaked in sterile distilled water and 100% ethyl alcohol, which were kept in refrigerator at 4°C for 24 h. Then filtrates were prepared and kept in a hot air oven to get a black shining crystal powder/paste form. Stock solutions of plant extracts were inoculated on petri plates containing species of Candida albicans and incubated at 25 ± 2°C for 72 h. Results: Alcoholic curry leaves showed the maximum zone of inhibition on Candida albicans followed by aqueous tea leaves. The other plant extracts like alcoholic onion leaves, alcoholic tea leaves, alcoholic onion bulb, alcoholic aloe vera, and alcoholic mint leaves also inhibited the growth of Candida albicans but lesser extent. Conclusion: The present study renders few medicinal plants as an alternative medicines to the field of dentistry which can be used adjunct to conventional therapy of oral candidasis.

Antifungal activity of fluconazole-loaded natural rubber latex against Candida albicans.

Science.gov (United States)

Yonashiro Marcelino, Mônica; Azevedo Borges, Felipe; Martins Costa, Ana Flávia; de Lacorte Singulani, Junya; Ribeiro, Nathan Vinícius; Barcelos Costa-Orlandi, Caroline; Garms, Bruna Cambraia; Soares Mendes-Giannini, Maria José; Herculano, Rondinelli Donizetti; Fusco-Almeida, Ana Marisa

2018-03-01

This work aimed to produce a membrane based on fluconazole-loaded natural rubber latex (NRL), and study their interaction, drug release and antifungal susceptibility against Candida albicans. Fluconazole-loaded NRL membrane was obtained by casting method. The Fourier Transform Infrared Spectroscopy showed no modifications either in NRL or fluconazole after the incorporation. Mechanical test presented low Young's modulus and high strain, indicating the membranes have sufficient elasticity for biomedical application. The bio-membrane was able to release the drug and inhibit the growth of C. albicans as demonstrated by disk diffusion and macrodilution assays. The biomembrane was able to release fluconazole and inhibit the growth of C. albicans, representing a promising biomaterial for skin application.

A novel immune evasion strategy of candida albicans: proteolytic cleavage of a salivary antimicrobial peptide.

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Timothy F Meiller

Full Text Available Oropharyngeal candidiasis is an opportunistic infection considered to be a harbinger of AIDS. The etiologic agent Candida albicans is a fungal species commonly colonizing human mucosal surfaces. However, under conditions of immune dysfunction, colonizing C. albicans can become an opportunistic pathogen causing superficial or even life-threatening infections. The reasons behind this transition, however, are not clear. In the oral cavity, salivary antimicrobial peptides are considered to be an important part of the host innate defense system in the prevention of microbial colonization. Histatin-5 specifically has exhibited potent activity against C. albicans. Our previous studies have shown histatin-5 levels to be significantly reduced in the saliva of HIV+ individuals, indicating an important role for histatin-5 in keeping C. albicans in its commensal stage. The versatility in the pathogenic potential of C. albicans is the result of its ability to adapt through the regulation of virulence determinants, most notably of which are proteolytic enzymes (Saps, involved in tissue degradation. In this study, we show that C. albicans cells efficiently and rapidly degrade histatin-5, resulting in loss of its anti-candidal potency. In addition, we demonstrate that this cellular activity is due to proteolysis by a member of the secreted aspartic proteases (Sap family involved in C. albicans pathogenesis. Specifically, the proteolysis was attributed to Sap9, in turn identifying histatin-5 as the first host-specific substrate for that isoenzyme. These findings demonstrate for the first time the ability of a specific C. albicans enzyme to degrade and deactivate a host antimicrobial peptide involved in the protection of the oral mucosa against C. albicans, thereby providing new insights into the factors directing the transition of C. albicans from commensal to pathogen, with important clinical implications for alternative therapy. This report characterizes the

In vitro sensitivity of Trichomonas vaginalis and Candida albicans to chemotherapeutic agents.

Science.gov (United States)

Lövgren, T; Salmela, I

1978-06-01

Strains of fresh clinical isolates of Trichomonas vaginalis and Candida albicans have been tested in vitro for their sensitivity to eight drugs used in the therapy of monilial and trichomonal vaginitis. Three of the chemotherapeutic agents, chlorchinaldol, clotrimazole and broxyquinoline were effective against both organisms. Tinidazole and metronidazole were active against T. vaginalis. The strains of C. albicans were also sensitive to trichomycin, natamycin and nystatin. Tinidazole was the most effective trichomonacide, clotrimazole and chlorchinaldol were most effective against C. albicans, while chlorchinaldol had the best in vitro effect against both organisms. The ranges of the MICs are compared to values previously reported.

Adhesion of Candida albicans to Vanillin Incorporated Self-Curing Orthodontic PMMA Resin.

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Zam, K.; Sawaengkit, P.; Thaweboon, S.; Thaweboon, B.

2018-02-01

It has been observed that there is an increase in Candida carriers during the treatment with orthodontic removable appliance. Vanillin is flavouring agent, which is known to have antioxidant and antimicrobial properties. The aim of this study was to evaluate the effect of vanillin incorporated PMMA on adhesion of Candida albicans. A total of 36 orthodontic self-curing PMMA resin samples were fabricated. The samples were divided into 3 groups depending on percentage of vanillin incorporated (0.1%, 0.5% and PMMA without vanillin as control). PMMA samples were coated with saliva. The adhesion assay was performed with C. albicans (ATCC 10231). The adherent yeast cells were stained with crystal violet and counted under microscope by random selection of 3 fields at 10X magnification. The statistical analyses performed by Kruskal Wallis and Mann Whitney non-parametric test. It was found that the PMMA resin samples with vanillin incorporation significantly reduced the adhesion of C. albicans as compared to the control group. This study indicates that vanillin incorporated resin can impede the adhesion of C. albicans to about 45 - 56 %. With further testing and development, vanillin can be employed as an antifungal agent to prevent adhesion of C. albicans to orthodontic self-curing PMMA resin.

Streptococcus agalactiae Inhibits Candida albicans Hyphal Development and Diminishes Host Vaginal Mucosal TH17 Response

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Xiao-Yu Yu

2018-02-01

Full Text Available Streptococcus agalactiae and Candida albicans often co-colonize the female genital tract, and under certain conditions induce mucosal inflammation. The role of the interaction between the two organisms in candidal vaginitis is not known. In this study, we found that co-infection with S. agalactiae significantly attenuated the hyphal development of C. albicans, and that EFG1-Hwp1 signal pathway of C. albicans was involved in this process. In a mouse model of vulvovaginal candidiasis (VVC, the fungal burden and the levels of pro-inflammatory cytokines, IL-1β, IL-6 and TNF-α showed a increase on co-infection with S. agalactiae, while the level of TH17 T cells and IL-17 in the cervicovaginal lavage fluid were significantly decreased. Our results indicate that S. agalactiae inhibits C. albicans hyphal development by downregulating the expression of EFG1-Hwp1. The interaction between S. agalactiae and C. albicans may attenuate host vaginal mucosal TH17 immunity and contribute to mucosal colonization by C. albicans.

Antimicrobial effects of Coleus amboinicus, Lour folium infusum towards Candida albicans and Streptococcus mutans

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Devi Rianti

2006-03-01

Full Text Available A laboratory experimental study conducted on antimicrobial effects of Coleus amboinicus, Lour folium Infusum towards Candida albicans and Streptococcus mutans (S. mutans. Effective concentration of Coleus amboinicus, Lour to decrease the quantities Candida albicans and S. mutans colonies is expected to be found out in this study. This study was using Coleus Amboinicus, Lour folium infusum with 12.5%, 15%, 17.5%, 20%, and 22.5% concentrations. Sterilized aquadest used as a control. Candida albicans and S. mutans quantities was enumerated by counting the amount of Candida albicans and S. mutans growth in the Sabouraud ,s dextrose agar and Tryptone and yeast Agar media, using Colony Forming Unit per milliliter (CFU/ ml unit. Data analysis was using a One-Way ANOVA and LSD with 5% degree of significance. The result showed 22.5% concentration of CAL folium infusum was the most effective in decreasing the quantity Candida albicans and S. mutans colonies.

Whole Saliva has a Dual Role on the Adherence of Candida albicans to Polymethylmetacrylate.

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Elguezabal, N; Maza, J L; Dorronsoro, S; Pontón, J

2008-01-01

Adhesion of Candida albicans to acrylic of dental prostheses or to salivary macromolecules adsorbed on their surface is believed to be a critical event in the development of denture stomatitis. In previous studies our group has shown that adhesion of C. albicans germ tubes to polystyrene is decreased by saliva whereas C. albicans yeast cells adhesion to the same material is enhanced. The results presented in this study confirm this dual role played by whole saliva, since it decreased the adhesion of germ tubes but increased the adhesion of yeast cells to polymethylmetacrylate (PMMA). These effects mediated by whole saliva do not seem to be related to an inhibition of the germination of C. albicans, since similar levels of filamentation were observed in presence and absence of saliva. These results may give new insights into the conflicting role of saliva in the adhesion of C. albicans to acrylic resins of dental prostheses.

Regulatory Improvements for Effective Integration of Distributed Generation into Electricity Distribution Networks

International Nuclear Information System (INIS)

Scheepers, M.J.J.; Jansen, J.C.; De Joode, J.; Bauknecht, D.; Gomez, T.; Pudjianto, D.; Strbac, G.; Ropenus, S.

2007-11-01

The growth of distributed electricity supply of renewable energy sources (RES-E) and combined heat and power (CHP) - so called distributed generation (DG) - can cause technical problems for electricity distribution networks. These integration problems can be overcome by reinforcing the network. Many European Member States apply network regulation that does not account for the impact of DG growth on the network costs. Passing on network integration costs to the DG-operator who is responsible for these extra costs may result in discrimination between different DG plants and between DG and large power generation. Therefore, in many regulatory systems distribution system operators (DSOs) are not being compensated for the DG integration costs. The DG-GRID project analysed technical and economical barriers for integration of distributed generation into electricity distribution networks. The project looked into the impact of a high DG deployment on the electricity distribution system costs and the impact on the financial position of the DSO. Several ways for improving network regulation in order to compensate DSOs for the increasing DG penetration were identified and tested. The DG-GRID project looked also into stimulating network innovations through economic regulation. The project was co-financed by the European Commission and carried out by nine European universities and research institutes. This report summarises the project results and is based on a number of DG-GRID reports that describe the conducted analyses and their results

Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli.

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Carsten Marr

Full Text Available The set of regulatory interactions between genes, mediated by transcription factors, forms a species' transcriptional regulatory network (TRN. By comparing this network with measured gene expression data, one can identify functional properties of the TRN and gain general insight into transcriptional control. We define the subnet of a node as the subgraph consisting of all nodes topologically downstream of the node, including itself. Using a large set of microarray expression data of the bacterium Escherichia coli, we find that the gene expression in different subnets exhibits a structured pattern in response to environmental changes and genotypic mutation. Subnets with fewer changes in their expression pattern have a higher fraction of feed-forward loop motifs and a lower fraction of small RNA targets within them. Our study implies that the TRN consists of several scales of regulatory organization: (1 subnets with more varying gene expression controlled by both transcription factors and post-transcriptional RNA regulation and (2 subnets with less varying gene expression having more feed-forward loops and less post-transcriptional RNA regulation.

Difunctional bacteriophage conjugated with photosensitizers for Candida albicans-targeting photodynamic inactivation

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Dong S

2018-04-01

Full Text Available Shuai Dong,1,2 Hongxi Shi,1 Xintong Zhang,1,2 Xi Chen,1 Donghui Cao,2 Chuanbin Mao,3,4 Xiang Gao,1 Li Wang1 1Key Laboratory of Molecular Epigenetics of Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, 2First Hospital of Jilin University, Changchun, Jilin, 3School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China; 4Department of Chemistry and Biochemistry, Stephenson Life Science Research Center, University of Oklahoma, Norman, OK, USA Background: Candida albicans is the most prevalent fungal pathogen of the human microbiota, causing infections ranging from superficial infections of the skin to life-threatening systemic infections. Due to the increasing occurrence of antibiotic-resistant C. albicans strains, new approaches to control this pathogen are needed. Photodynamic inactivation is an emerging alternative to treat infections based on the interactions between visible light and photosensitisers, in which pheophorbide a (PPA is a chlorophyll-based photosensitizer that could induce cell death after light irradiation. Due to PPA’s phototoxicity and low efficiency, the main challenge is to implement photosensitizer cell targeting and attacking. Methods: In this study, PPA was conjugated with JM-phage by EDC/NHS crosslinking. UV-Vis spectra was used to determine the optimum conjugation percentages of PPA and JM-phage complex for photodynamic inactivation. After photodynamic inactivation, the efficacy of PPA-JM-phage was assessed by performing in vitro experiments, such as MTS assay, scanning electron microscopy, measurement of dysfunctional mitochondria, ROS accumulation, S cell arrest and apoptotic pathway.Results: A single-chain variable-fragment phage (JM with high affinity to MP65 was screened from human single-fold single-chain variable-fragment libraries and designed as a binding target for C. albicans cells. Subsequently, PPa was integrated into JM phage to generate

Limonene inhibits Candida albicans growth by inducing apoptosis.

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Thakre, Archana; Zore, Gajanan; Kodgire, Santosh; Kazi, Rubina; Mulange, Shradha; Patil, Rajendra; Shelar, Amruta; Santhakumari, Bayitigeri; Kulkarni, Mahesh; Kharat, Kiran; Karuppayil, Sankunny Mohan

2018-07-01

Anti-Candida potential of limonene was evaluated against planktonic growth, biofilm (adhesion, development and maturation) and morphogenesis of Candida albicans in this study. Limonene is a major constituent of citrus oil and most frequently used terpene in food and beverage industry due to its pleasant fragrance, nontoxic, and is generally recognized as safe (GRAS) flavoring agent as well as treatment option in many gastrointestinal diseases.Limonene exhibited excellent anti-Candida activity and was equally effective against planktonic growth of C. albicans isolates differentially susceptible to FLC (N = 35). Limonene inhibited morphogenesis significantly at low concentration. However, it showed stage dependent activity against biofilm formation, that is, it was more effective against adhesion followed by development and maturation. Limonene also exhibited excellent synergy with FLC against planktonic and biofilm growth. SWATH-MS analysis led to identification of limonene responsive proteins that provided molecular insight of its anti-Candida activity. Proteomic analysis revealed upregulation of proteins involved in cell wall glucan synthesis (Kre6); oxidative stress (Rhr2, Adh7 and Ebp1); DNA damage stress (Mbf1 and Npl3); nucleolar stress (Rpl11, Rpl7, Rpl29, Rpl15) and down regulation of cytoskeleton organization (Crn1, Pin3, Cct8, Rbl2), and so forth, in response to limonene. Limonene mediated down regulation of Tps3 indicates activation of caspase (CaMca1) and induction of apoptosis in C. albicans. These results suggest that limonene inhibits C. albicans growth by cell wall/membrane damage induced oxidative stress that leads to DNA damage resulting into modulation of cell cycle and induction of apoptosis through nucleolar stress and metacaspase dependent pathway.

Candida albicans septicemia in a premature infant successfully treated with oral fluconazole

DEFF Research Database (Denmark)

Bodé, S; Pedersen-Bjergaard, Lars; Hjelt, K

1992-01-01

A premature male infant, birth-weight 1460 g, was treated successfully for a Candida albicans septicemia with orally administered fluconazole for 20 days. Dosage was 5 mg/kg/day. No side effects were seen. Fluconazole may present a major progress in treatment of invasive C. albicans infections...

Influence of culture conditions for clinically isolated non-albicans Candida biofilm formation.

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Tan, Yulong; Leonhard, Matthias; Ma, Su; Schneider-Stickler, Berit

2016-11-01

Non-albicans Candida species have been isolated in increasing numbers in patients. Moreover, they are adept at forming biofilms. This study analyzed biofilm formation of clinically isolated non-albicans Candida, including Candida tropicalis, Candida krusei and Candida parapsilosis under the influence of different growth media (RPMI 1640, YPD and BHI) and several culture variables (inoculum concentration, incubation period and feeding conditions). The results showed that culture conditions strongly influenced non-albicans Candida species biofilm formation. YPD and BHI resulted in larger amount of biofilm formation with higher metabolic activity of biofilms. Furthermore, the growth media seems to have varying effects on adhesion and biofilm development. Growth conditions may also influence biofilm formation, which was enhanced when starting the culture with a larger inoculum, longer incubation period and using a fed-batch system. Therefore, the potential influences of external environmental factors should be considered when studying the non-albicans Candida biofilms in vitro. Copyright © 2016 Elsevier B.V. All rights reserved.

New milk medium for germ tube and chlamydoconidia production by Candida albicans.

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Jitsurong, S; Kiamsiri, S; Pattararangrong, N

1993-08-01

A new medium consisting of UHT milk, tween 80 and agar is described for the development of both germ tube and chlamydoconidia by Candida albicans. In total 172 isolates from clinical specimens, including C. albicans (112), C. guilliermondii (4), C. krusei (3), C. parasilopsis (16). C. tropicalis (28), Torulopsis glabrata (6) and Trichosporon beigellii (3), were examined in this medium by using the standard method. A higher percentage (98.2%) of germ tube production by C. albicans was found in this medium than in undiluted serum (90.2%). In addition, only C. albicans was found to be able to produce a high percentage of chlamydoconidia (95.5%) after 48 hours' incubation. In comparison with the conventional medium, corn meal tween 80 agar (21.4%), this new medium gives a significantly higher percentage and abundance of chlamydoconidia production. Being simple, cheap and easy to prepare, the new milk medium is proposed as very practical in the clinical mycology laboratory.

Aktivitas Antijamur Senyawa Bioaktif Ekstrak Gelidium Latifolium Terhadap Candida Albicans

OpenAIRE

Lutfiyanti, Rosiska; Ma'ruf, Widodo Farid; Dewi, Eko Nurcahya

2012-01-01

Gelidium sp. has bioactive compounds which is estimated has potential activity as antifungal. The aim of this study were to know bioactive compounds from Gelidium latifolium with different solvent, to know the potency of Gelidium latifolium extract as antifungal towards C. albicans and to know the effect of different concentration of Gelidium latifolium extract towards antifungal activity. The result showed that the methanol extract is able to produce inhibition zones toward Candida albicans,...

Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

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Guo Zheng

2006-01-01

Full Text Available Abstract Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network to address the underlying regulations of genes that can span any unit(s of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex

Genome-wide identification of regulatory elements and reconstruction of gene regulatory networks of the green alga Chlamydomonas reinhardtii under carbon deprivation.

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Flavia Vischi Winck

Full Text Available The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO2], a carbon concentrating mechanism (CCM is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1 gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF and transcription regulator (TR genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO 2 response regulator 1 and Lcr2 (Low-CO2 response regulator 2, may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome

Establishment of the National Nuclear Regulatory Portal (NNRP) as the key element of the Global Nuclear Safety and Security Network and Regulatory Network (GNSSN/RegNet) for sharing of nuclear safety information and knowledge among the Global Expert Community

International Nuclear Information System (INIS)

Kuvshinnikov, A.V.

2011-01-01

The Global Nuclear Safety and Security Network (GNSSN) implements the concept of the Global Nuclear Safety and Security Framework (GNSSF) as outlined in INSAG 21. This is the framework of instruments and resources for achieving and maintaining worldwide a high level of safety and security at nuclear facilities and activities as stated in SF-1 and supporting safety standards or recommendations such as INSAG-12. National efforts are and should be augmented by the activities of a variety of international enterprises that facilitate safety and security. The IAEA standard GS-R-3 requires that information and knowledge is managed as a resource. Further strengthening of GNSSN in particular regulatory networking as intended by GNSSN/RegNet has to be based on current national priorities, on existing regional and thematic networks and on the established mechanisms of international co-operation as presented for example on the websites of the IAEA or the OECD-NEA. Current design and operation of RegNet are flexible enough to accommodate differences in national and international approaches and practices and to facilitate exchange and cooperation on regulatory matters. The main role of GNSSN/RegNet is sharing knowledge and bringing people together to enhance and promote nuclear safety and security. The objectives of GNSSN/RegNet: enhancing safety and security by international cooperation, sharing information and best practices, enabling adequate access to relevant safety and security information and promoting the dissemination of this information, implementing active collaboration in the relevant areas related to safety and security, such as joint projects, peer reviews, enabling synergies among existing networks and initiatives, informing the public on the relevant safety and security areas and the related international collaboration. In the RegNet part of the GNSSN exist the National Nuclear Regulatory Portal (NNRP) which is on one hand a part of the global RegNet and on the

Candida albicans escapes from mouse neutrophils

DEFF Research Database (Denmark)

Ermert, David; Niemiec, Maria J; Röhm, Marc

2013-01-01

is the most widely used model organism. Neutrophils are essential immune cells to prevent opportunistic mycoses. To explore potential differences between the rodent infection model and the human host, we compared the interactions of C. albicans with neutrophil granulocytes from mice and humans. We revealed...

Comparative Phenotypic Analysis of the Major Fungal Pathogens Candida parapsilosis and Candida albicans

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Holland, Linda M.; Schröder, Markus S.; Turner, Siobhán A.; Taff, Heather; Andes, David; Grózer, Zsuzsanna; Gácser, Attila; Ames, Lauren; Haynes, Ken; Higgins, Desmond G.; Butler, Geraldine

2014-01-01

Candida parapsilosis and Candida albicans are human fungal pathogens that belong to the CTG clade in the Saccharomycotina. In contrast to C. albicans, relatively little is known about the virulence properties of C. parapsilosis, a pathogen particularly associated with infections of premature neonates. We describe here the construction of C. parapsilosis strains carrying double allele deletions of 100 transcription factors, protein kinases and species-specific genes. Two independent deletions were constructed for each target gene. Growth in >40 conditions was tested, including carbon source, temperature, and the presence of antifungal drugs. The phenotypes were compared to C. albicans strains with deletions of orthologous transcription factors. We found that many phenotypes are shared between the two species, such as the role of Upc2 as a regulator of azole resistance, and of CAP1 in the oxidative stress response. Others are unique to one species. For example, Cph2 plays a role in the hypoxic response in C. parapsilosis but not in C. albicans. We found extensive divergence between the biofilm regulators of the two species. We identified seven transcription factors and one protein kinase that are required for biofilm development in C. parapsilosis. Only three (Efg1, Bcr1 and Ace2) have similar effects on C. albicans biofilms, whereas Cph2, Czf1, Gzf3 and Ume6 have major roles in C. parapsilosis only. Two transcription factors (Brg1 and Tec1) with well-characterized roles in biofilm formation in C. albicans do not have the same function in C. parapsilosis. We also compared the transcription profile of C. parapsilosis and C. albicans biofilms. Our analysis suggests the processes shared between the two species are predominantly metabolic, and that Cph2 and Bcr1 are major biofilm regulators in C. parapsilosis. PMID:25233198

Global Transcriptome Sequencing Identifies Chlamydospore Specific Markers in Candida albicans and Candida dubliniensis

LENUS (Irish Health Repository)

Palige, Katja

2013-04-15

Candida albicans and Candida dubliniensis are pathogenic fungi that are highly related but differ in virulence and in some phenotypic traits. During in vitro growth on certain nutrient-poor media, C. albicans and C. dubliniensis are the only yeast species which are able to produce chlamydospores, large thick-walled cells of unknown function. Interestingly, only C. dubliniensis forms pseudohyphae with abundant chlamydospores when grown on Staib medium, while C. albicans grows exclusively as a budding yeast. In order to further our understanding of chlamydospore development and assembly, we compared the global transcriptional profile of both species during growth in liquid Staib medium by RNA sequencing. We also included a C. albicans mutant in our study which lacks the morphogenetic transcriptional repressor Nrg1. This strain, which is characterized by its constitutive pseudohyphal growth, specifically produces masses of chlamydospores in Staib medium, similar to C. dubliniensis. This comparative approach identified a set of putatively chlamydospore-related genes. Two of the homologous C. albicans and C. dubliniensis genes (CSP1 and CSP2) which were most strongly upregulated during chlamydospore development were analysed in more detail. By use of the green fluorescent protein as a reporter, the encoded putative cell wall related proteins were found to exclusively localize to C. albicans and C. dubliniensis chlamydospores. Our findings uncover the first chlamydospore specific markers in Candida species and provide novel insights in the complex morphogenetic development of these important fungal pathogens.

Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities

DEFF Research Database (Denmark)

Fang, Xin; Sastry, Anand; Mih, Nathan

2017-01-01

Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the Escherichia coli TRN-probably the best characterized TRN-several questions remain. Here, we address three questions: (i) How complete is our knowledge of the E. coli TRN; (ii) how well can we predi...

Postantifungal Effect of Micafungin against the Species Complexes of Candida albicans and Candida parapsilosis.

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Sandra Gil-Alonso

Full Text Available Micafungin is an effective antifungal agent useful for the therapy of invasive candidiasis. Candida albicans is the most common cause of invasive candidiasis; however, infections due to non-C. albicans species, such as Candida parapsilosis, are rising. Killing and postantifungal effects (PAFE are important factors in both dose interval choice and infection outcome. The aim of this study was to determinate the micafungin PAFE against 7 C. albicans strains, 5 Candida dubliniensis, 2 Candida Africana, 3 C. parapsilosis, 2 Candida metapsilosis and 2 Candida orthopsilosis. For PAFE studies, cells were exposed to micafungin for 1 h at concentrations ranging from 0.12 to 8 μg/ml. Time-kill experiments (TK were conducted at the same concentrations. Samples were removed at each time point (0-48 h and viable counts determined. Micafungin (2 μg/ml was fungicidal (≥ 3 log10 reduction in TK against 5 out of 14 (36% strains of C. albicans complex. In PAFE experiments, fungicidal endpoint was achieved against 2 out of 14 strains (14%. In TK against C. parapsilosis, 8 μg/ml of micafungin turned out to be fungicidal against 4 out 7 (57% strains. Conversely, fungicidal endpoint was not achieved in PAFE studies. PAFE results for C. albicans complex (41.83 ± 2.18 h differed from C. parapsilosis complex (8.07 ± 4.2 h at the highest tested concentration of micafungin. In conclusion, micafungin showed significant differences in PAFE against C. albicans and C. parapsilosis complexes, being PAFE for the C. albicans complex longer than for the C. parapsilosis complex.

Minocycline Inhibits Candida albicans Budded-to-Hyphal-Form Transition and Biofilm Formation.

Science.gov (United States)

Kurakado, Sanae; Takatori, Kazuhiko; Sugita, Takashi

2017-09-25

Candida albicans frequently causes bloodstream infections; its budded-to-hyphalform transition (BHT) and biofilm formation are major contributors to virulence. During an analysis of antibacterial compounds that inhibit C. albicans BHT, we found that the tetracycline derivative minocycline inhibited BHT and subsequent biofilm formation. Minocycline decreased expression of hypha-specific genes HWP1 and ECE1, and adhesion factor gene ALS3 of C. albicans. In addition, minocycline decreased cell surface hydrophobicity and the extracellular β-glucan level in biofilms. Minocycline has been widely used for catheter antibiotic lock therapy to prevent bacterial infection; this compound may also be prophylactically effective against Candida infection.

Phospholipid biosynthesis in Candida albicans: Regulation by the precursors inositol and choline

International Nuclear Information System (INIS)

Klig, L.S.; Friedli, L.; Schmid, E.

1990-01-01

Phospholipid metabolism in the pathogenic fungus Candida albicans was examined. The phospholipid biosynthetic pathways of C. albicans were elucidated and were shown to be similar to those of Saccharomyces cerevisiae. However, marked differences were seen between these two fungi in the regulation of the pathways in response to exogenously provided precursors inositol and choline. In S. cerevisiae, the biosynthesis of phosphatidylcholine via methylation of phosphatidylethanolamine appears to be regulated in response to inositol and choline; provision of choline alone does not repress the activity of this pathway. The same pathway in C. albicans responds to the exogenous provision of choline. Possible explanations for the observed differences in regulation are discussed

Influence of radiation therapy on oral Candida albicans colonization: a quantitative assessment

International Nuclear Information System (INIS)

Rossie, K.M.; Taylor, J.; Beck, F.M.; Hodgson, S.E.; Blozis, G.G.

1987-01-01

An increase in quantity of oral Candida albicans was documented in patients receiving head and neck radiation therapy during and after therapy, as assessed by an oral-rinse culturing technique. The amount of the increase was greater in denture wearers and directly related to increasing radiation dose and increasing volume of parotid gland included in the radiation portal. A significant number of patients who did not carry C. albicans prior to radiation therapy developed positive cultures by 1 month after radiation therapy. The percentage of patients receiving head and neck radiation therapy who carried C. albicans prior to radiation therapy did not differ significantly from matched dental patient controls

Particular Candida albicans strains in the digestive tract of dyspeptic patients, identified by multilocus sequence typing.

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Yan-Bing Gong

Full Text Available BACKGROUND: Candida albicans is a human commensal that is also responsible for chronic gastritis and peptic ulcerous disease. Little is known about the genetic profiles of the C. albicans strains in the digestive tract of dyspeptic patients. The aim of this study was to evaluate the prevalence, diversity, and genetic profiles among C. albicans isolates recovered from natural colonization of the digestive tract in the dyspeptic patients. METHODS AND FINDINGS: Oral swab samples (n = 111 and gastric mucosa samples (n = 102 were obtained from a group of patients who presented dyspeptic symptoms or ulcer complaints. Oral swab samples (n = 162 were also obtained from healthy volunteers. C. albicans isolates were characterized and analyzed by multilocus sequence typing. The prevalence of Candida spp. in the oral samples was not significantly different between the dyspeptic group and the healthy group (36.0%, 40/111 vs. 29.6%, 48/162; P > 0.05. However, there were significant differences between the groups in the distribution of species isolated and the genotypes of the C. albicans isolates. C. albicans was isolated from 97.8% of the Candida-positive subjects in the dyspeptic group, but from only 56.3% in the healthy group (P < 0.001. DST1593 was the dominant C. albicans genotype from the digestive tract of the dyspeptic group (60%, 27/45, but not the healthy group (14.8%, 4/27 (P < 0.001. CONCLUSIONS: Our data suggest a possible link between particular C. albicans strain genotypes and the host microenvironment. Positivity for particular C. albicans genotypes could signify susceptibility to dyspepsia.

TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

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Jensen Paul A

2011-09-01

Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

Antifungal activity of four honeys of different types from Algeria against pathogenic yeast: Candida albicans and Rhodotorula sp.

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Moussa, Ahmed; Noureddine, Djebli; Saad, Aissat; Abdelmelek, Meslem; Abdelkader, Benhalima

2012-07-01

To evaluate the antifungal activity of four honeys of different types from Algeria against pathogenic yeast i.e. Candida albicans (C. albicans) and Rhodotorula sp. Four Algeria honeys of different botanical origin were analyzed to test antifungal effect against C. albicans, and Rhodotorula sp. Different concentrations (undiluted, 10%, 30%, 50% and 70% w/v) of honey were studied in vitro for their antifugal activity using C. albicans and Rhodotorula sp. as fungal strains. The range of the diameter of zone of inhibition of various concentrations of tested honeys was (7-23 mm) for Rhodotorula sp., while C. albicans showed clearly resistance towards all concentrations used. The MICs of tested honey concentrations against C. albicans and Rhodotorula sp. were (70.09-93.48)% and (4.90-99.70)% v/v, respectively. This study demonstrates that, in vitro, these natural products have clearly an antifungal activity against Rhodotorula sp. and C. albicans.

Do motifs reflect evolved function?--No convergent evolution of genetic regulatory network subgraph topologies.

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Knabe, Johannes F; Nehaniv, Chrystopher L; Schilstra, Maria J

2008-01-01

Methods that analyse the topological structure of networks have recently become quite popular. Whether motifs (subgraph patterns that occur more often than in randomized networks) have specific functions as elementary computational circuits has been cause for debate. As the question is difficult to resolve with currently available biological data, we approach the issue using networks that abstractly model natural genetic regulatory networks (GRNs) which are evolved to show dynamical behaviors. Specifically one group of networks was evolved to be capable of exhibiting two different behaviors ("differentiation") in contrast to a group with a single target behavior. In both groups we find motif distribution differences within the groups to be larger than differences between them, indicating that evolutionary niches (target functions) do not necessarily mold network structure uniquely. These results show that variability operators can have a stronger influence on network topologies than selection pressures, especially when many topologies can create similar dynamics. Moreover, analysis of motif functional relevance by lesioning did not suggest that motifs were of greater importance to the functioning of the network than arbitrary subgraph patterns. Only when drastically restricting network size, so that one motif corresponds to a whole functionally evolved network, was preference for particular connection patterns found. This suggests that in non-restricted, bigger networks, entanglement with the rest of the network hinders topological subgraph analysis.

Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

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Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

2009-01-01

Background: Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori

A flexible regulatory framework

International Nuclear Information System (INIS)

Silvennoinen, T.

2000-01-01

Regulatory reform of the Finnish electricity market meant opening up potentially competitive parts of the electricity sector to competition and eliminating all unnecessary forms of regulation covering generation, wholesale supply, retail supply, and foreign trade in electricity. New types of control and regulatory mechanisms and institutions were set up for those parts of the electricity industry that were excluded from competition, such as network operations. Network activities now have to be licensed, whereas no licence is needed for generation or supply. A new sector-specific regulatory authority was established in 1995 to coincide with the implementation of the Electricity Market Act, known as the Electricity Market Authority. This is responsible for regulating network activities and retail supply to captive customers. The core function of the authority, which employs some 14 people, is to promote the smooth operation of the Finnish electricity market and to oversee the implementation of the Electricity Market Act and its provisions. Its most important duties are linked to overseeing the process by which network companies price their electricity. As price regulation no longer exists, all the companies in the electricity sector set their tariffs independently, even network companies. The job of controlling the pricing of network services is handed by the Electricity Market Authority, following the principles of competition control. Pricing control takes place ex post - after a pricing system has been adopted by a company and concentrates on individual cases and companies. There is no ex ante system of setting or approving prices and tariffs by the regulator. The tariffs and pricing of network services can be evaluated, however, by both the Electricity Market Authority and the Finnish Competition Authority, which have overlapping powers as regards the pricing of network activities. The Finnish regulatory framework can be described as a system of light

Bilateral endogenous Candida albicans subretinal abscess with suspected mixed bacterial infection

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Arai Y

2014-10-01

Full Text Available Yusuke Arai,1 Yukihiro Sato,1 Atsushi Yoshida,1 Hidetoshi Kawashima,1 Toshikatsu Kaburaki,2 Harumi Gomi3 1Department of Ophthalmology, Jichi Medical University, Tochigi, Japan; 2Department of Ophthalmology, The University of Tokyo, Graduate School of Medicine, Tokyo, Japan; 3Center for Clinical Infectious Diseases, Jichi Medical University, Tochigi, Japan Purpose: Candida albicans subretinal abscess is extremely rare. To our knowledge, only one unilateral case has been reported. Herein, we report one bilateral case. Mixed bacterial infection was also suspected based on broad-range real-time polymerase chain reaction.Methods: A 64-year-old man being treated with oral corticosteroids for interstitial pneumonia visited us for visual loss in the left eye. Best corrected visual acuity (BCVA was 20/20 in the right eye and 8/200 in the left eye. Funduscopy revealed round yellowish-white subretinal lesions with retinal hemorrhage in both eyes.Results: Broad-range polymerase chain reaction of the vitreous fluid from the left eye showed a high copy count of bacterial 16s ribosome RNA. Despite large doses of antibiotics, the abscess expanded and vision decreased to light perception in the left eye. Exenteration of the left eye was performed followed by microscopic examination showing Gram-negative bacilli, and C. albicans was also cultured. Antibiotics and the maximum doses of antifungal drugs were administered. However, the abscess in the right eye expanded, and BCVA decreased to 2/200. Vitrectomy and silicone oil tamponade were performed. Vitreous fluid culture revealed C. albicans. At 16 months follow-up, BCVA was stable at 4/200 with healing of the subretinal abscess under silicone oil.Conclusion: Since C. albicans subretinal abscess is extremely rare and there was a concurrent mixed bacterial infection, diagnostic procedures in our bilateral case were more complicated than usual. C. albicans infection should be included in the differential diagnosis

Systematic Analysis of RNA Regulatory Network in Rat Brain after Ischemic Stroke

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Juan Liu

2018-01-01

Full Text Available Although extensive studies have identified large number of microRNAs (miRNAs and long noncoding RNAs (lncRNAs in ischemic stroke, the RNA regulation network response to focal ischemia remains poorly understood. In this study, we simultaneously interrogate the expression profiles of lncRNAs, miRNAs, and mRNAs changes during focal ischemia induced by transient middle cerebral artery occlusion. A set of 1924 novel lncRNAs were identified and may involve brain injury and DNA repair as revealed by coexpression network analysis. Furthermore, many short interspersed elements (SINE mediated lncRNA:mRNA duplexes were identified, implying that lncRNAs mediate Staufen1-mediated mRNA decay (SMD which may play a role during focal ischemia. Moreover, based on the competitive endogenous RNA (ceRNA hypothesis, a stroke regulatory ceRNA network which reveals functional lncRNA:miRNA:mRNA interactions was revealed in ischemic stroke. In brief, this work reports a large number of novel lncRNAs responding to focal ischemia and constructs a systematic RNA regulation network which highlighted the role of ncRNAs in ischemic stroke.

Core regulatory network motif underlies the ocellar complex patterning in Drosophila melanogaster

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Aguilar-Hidalgo, D.; Lemos, M. C.; Córdoba, A.

2015-03-01

During organogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of living organisms. Robustness, thus, is an essential characteristic that GRNs need to fulfill in order to maintain viability and reproducibility in a species. In the present work we analyze the robustness of the patterning for the ocellar complex formation in Drosophila melanogaster fly. We have systematically pruned the GRN that drives the development of this visual system to obtain the minimum pathway able to satisfy this pattern. We found that the mechanism underlying the patterning obeys to the dynamics of a 3-nodes network motif with a double negative feedback loop fed by a morphogenetic gradient that triggers the inhibition in a French flag problem fashion. A Boolean modeling of the GRN confirms robustness in the patterning mechanism showing the same result for different network complexity levels. Interestingly, the network provides a steady state solution in the interocellar part of the patterning and an oscillatory regime in the ocelli. This theoretical result predicts that the ocellar pattern may underlie oscillatory dynamics in its genetic regulation.

Functional architecture and global properties of the Corynebacterium glutamicum regulatory network: Novel insights from a dataset with a high genomic coverage.

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Freyre-González, Julio A; Tauch, Andreas

2017-09-10

Corynebacterium glutamicum is a Gram-positive, anaerobic, rod-shaped soil bacterium able to grow on a diversity of carbon sources like sugars and organic acids. It is a biotechnological relevant organism because of its highly efficient ability to biosynthesize amino acids, such as l-glutamic acid and l-lysine. Here, we reconstructed the most complete C. glutamicum regulatory network to date and comprehensively analyzed its global organizational properties, systems-level features and functional architecture. Our analyses show the tremendous power of Abasy Atlas to study the functional organization of regulatory networks. We created two models of the C. glutamicum regulatory network: all-evidences (containing both weak and strong supported interactions, genomic coverage=73%) and strongly-supported (only accounting for strongly supported evidences, genomic coverage=71%). Using state-of-the-art methodologies, we prove that power-law behaviors truly govern the connectivity and clustering coefficient distributions. We found a non-previously reported circuit motif that we named complex feed-forward motif. We highlighted the importance of feedback loops for the functional architecture, beyond whether they are statistically over-represented or not in the network. We show that the previously reported top-down approach is inadequate to infer the hierarchy governing a regulatory network because feedback bridges different hierarchical layers, and the top-down approach disregards the presence of intermodular genes shaping the integration layer. Our findings all together further support a diamond-shaped, three-layered hierarchy exhibiting some feedback between processing and coordination layers, which is shaped by four classes of systems-level elements: global regulators, locally autonomous modules, basal machinery and intermodular genes. Copyright © 2016 Elsevier B.V. All rights reserved.

The cell envelope stress response of Bacillus subtilis: from static signaling devices to dynamic regulatory network.

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Radeck, Jara; Fritz, Georg; Mascher, Thorsten

2017-02-01

The cell envelope stress response (CESR) encompasses all regulatory events that enable a cell to protect the integrity of its envelope, an essential structure of any bacterial cell. The underlying signaling network is particularly well understood in the Gram-positive model organism Bacillus subtilis. It consists of a number of two-component systems (2CS) and extracytoplasmic function σ factors that together regulate the production of both specific resistance determinants and general mechanisms to protect the envelope against antimicrobial peptides targeting the biogenesis of the cell wall. Here, we summarize the current picture of the B. subtilis CESR network, from the initial identification of the corresponding signaling devices to unraveling their interdependence and the underlying regulatory hierarchy within the network. In the course of detailed mechanistic studies, a number of novel signaling features could be described for the 2CSs involved in mediating CESR. This includes a novel class of so-called intramembrane-sensing histidine kinases (IM-HKs), which-instead of acting as stress sensors themselves-are activated via interprotein signal transfer. Some of these IM-HKs are involved in sensing the flux of antibiotic resistance transporters, a unique mechanism of responding to extracellular antibiotic challenge.

Candida albicans response to spaceflight (NASA STS-115)

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National Aeronautics and Space Administration — This study presents the first global transcriptional profiling and phenotypic characterization of the major human opportunistic fungal pathogen Candida albicans...

Antagonistic Coevolution Drives Whack-a-Mole Sensitivity in Gene Regulatory Networks.

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Jeewoen Shin

2015-10-01

Full Text Available Robustness, defined as tolerance to perturbations such as mutations and environmental fluctuations, is pervasive in biological systems. However, robustness often coexists with its counterpart, evolvability--the ability of perturbations to generate new phenotypes. Previous models of gene regulatory network evolution have shown that robustness evolves under stabilizing selection, but it is unclear how robustness and evolvability will emerge in common coevolutionary scenarios. We consider a two-species model of coevolution involving one host and one parasite population. By using two interacting species, key model parameters that determine the fitness landscapes become emergent properties of the model, avoiding the need to impose these parameters externally. In our study, parasites are modeled on species such as cuckoos where mimicry of the host phenotype confers high fitness to the parasite but lower fitness to the host. Here, frequent phenotype changes are favored as each population continually adapts to the other population. Sensitivity evolves at the network level such that point mutations can induce large phenotype changes. Crucially, the sensitive points of the network are broadly distributed throughout the network and continually relocate. Each time sensitive points in the network are mutated, new ones appear to take their place. We have therefore named this phenomenon "whack-a-mole" sensitivity, after a popular fun park game. We predict that this type of sensitivity will evolve under conditions of strong directional selection, an observation that helps interpret existing experimental evidence, for example, during the emergence of bacterial antibiotic resistance.

Anaerobic bacteria grow within Candida albicans biofilms and induce biofilm formation in suspension cultures.

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Fox, Emily P; Cowley, Elise S; Nobile, Clarissa J; Hartooni, Nairi; Newman, Dianne K; Johnson, Alexander D

2014-10-20

The human microbiome contains diverse microorganisms, which share and compete for the same environmental niches. A major microbial growth form in the human body is the biofilm state, where tightly packed bacterial, archaeal, and fungal cells must cooperate and/or compete for resources in order to survive. We examined mixed biofilms composed of the major fungal species of the gut microbiome, Candida albicans, and each of five prevalent bacterial gastrointestinal inhabitants: Bacteroides fragilis, Clostridium perfringens, Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis. We observed that biofilms formed by C. albicans provide a hypoxic microenvironment that supports the growth of two anaerobic bacteria, even when cultured in ambient oxic conditions that are normally toxic to the bacteria. We also found that coculture with bacteria in biofilms induces massive gene expression changes in C. albicans, including upregulation of WOR1, which encodes a transcription regulator that controls a phenotypic switch in C. albicans, from the "white" cell type to the "opaque" cell type. Finally, we observed that in suspension cultures, C. perfringens induces aggregation of C. albicans into "mini-biofilms," which allow C. perfringens cells to survive in a normally toxic environment. This work indicates that bacteria and C. albicans interactions modulate the local chemistry of their environment in multiple ways to create niches favorable to their growth and survival. Copyright © 2014 Elsevier Ltd. All rights reserved.

Novel insight into neutrophil immune responses by dry mass determination of Candida albicans morphotypes.

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Ava Hosseinzadeh

Full Text Available The common fungal pathogen Candida albicans has the ability to grow as a yeast or as a hypha and can alternate between these morphotypes. The overall biomass of both morphotypes increases with growth. However, only yeasts, but not hyphae, exist as discrete cellular entities. Multiplicity of infection (MOI is a useful parameter to determine the initial inoculum of yeasts for in vitro infection assays. Since the amount of hyphae is difficult to quantify, comparable starting conditions in such assays cannot be determined accurately for yeasts and hyphae using MOI. To circumvent this problem, we have established a set of correlation coefficients to convert fungal metabolic activity and optical density to dry mass. Using these correlations, we were able to accurately compare ROS production and IL-8 release by polymorphonuclear neutrophils upon infection with equal dry mass amounts of yeast and hyphal morphotypes. Neutrophil responses depended on the initial form of infection, irrespective of C. albicans wild-type yeasts transforming to hyphal growth during the assay. Infection with a high mass of live C. albicans yeasts resulted in lower neutrophil ROS and this decrease stems from efficient ROS detoxification by C. albicans without directly affecting the phagocyte ROS machinery. Moreover, we show that dead C. albicans induces significantly less ROS and IL-8 release than live fungi, but thimerosal-killed C. albicans were still able to detoxify neutrophil ROS. Thus, the dry mass approach presented in this study reveals neutrophil responses to different amounts and morphotypes of C. albicans and serves as a template for studies that aim to identify morphotype-specific responses in a variety of immune cells.

Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks.

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Beal, Jacob; Lu, Ting; Weiss, Ron

2011-01-01

The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes (~ 50%) and latency of the optimized engineered gene networks. Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.

Induction of the immune response suppression in mice inoculated with Candida albicans.

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Valdez, J C; Mesón, D E; Sirena, A; de Petrino, S F; Eugenia, M; de Jorrat, B B; de Valdex, M G

1986-03-01

There is a controversy in respect to the immunological response (humoral or cellular) concerning the defense against Candida albicans. Candidosis would induce sub-populations of suppressor cells in the host cell-immune response. This report tries to show the effect of different doses of C. albicans (alive or heat-killed) on the expression of cell-mediated and humoral immunity. The effect upon cell immunity was determined by inoculating different lots of singeneic mice, doses of varied concentration of C. albicans and checking for delayed-type hipersensitivity (D.T.H.). D.T.H. was also controlled in syngeneic normal mice which had previously been injected with inoculated mice spleen cells. Humoral immunity was assayed by measuring the induced blastogenesis by Pokeweed Mitogen on spleen mononuclear cells with different doses of C. albicans. Results obtained show that the different doses gave origin to: Suppression of humoral and cell response (10(8) alive); Suppression of only humoral response (10(6) alive); Suppression of cell response and increase of humoral response (10(9) dead); Increase of both responses (10(8) dead).

Central Role for Dermal Fibroblasts in Skin Model Protection against Candida albicans.

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Kühbacher, Andreas; Henkel, Helena; Stevens, Philip; Grumaz, Christian; Finkelmeier, Doris; Burger-Kentischer, Anke; Sohn, Kai; Rupp, Steffen

2017-06-01

The fungal pathogen Candida albicans colonizes basically all human epithelial surfaces, including the skin. Under certain conditions, such as immunosuppression, invasion of the epithelia occurs. Not much is known about defense mechanisms against C. albicans in subepithelial layers such as the dermis. Using immune cell-supplemented 3D skin models we defined a new role for fibroblasts in the dermis and identified a minimal set of cell types for skin protection against C. albicans invasion. Dual RNA sequencing of individual host cell populations and C. albicans revealed that dermal invasion is directly impeded by dermal fibroblasts. They are able to integrate signals from the pathogen and CD4+ T cells and shift toward an antimicrobial phenotype with broad specificity that is dependent on Toll-like receptor 2 and interleukin 1β. These results highlight a central function of dermal fibroblasts for skin protection, opening new possibilities for treatment of infectious diseases. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

17-beta-estradiol upregulates the stress response in Candida albicans: implications for microbial virulence.

OpenAIRE

O'Connor, C; Essmann, M; Larsen, B

1998-01-01

OBJECTIVE: The influence of 17-beta-estradiol on the stress response of Candida albicans was studied. METHODS: The survival of clinical isolates of C. albicans treated with 17-beta-estradiol after heat and oxidative stress was measured by viable plate counts. Cellular proteins were analyzed via SDS-PAGE. RESULTS: The heat stress response induced by 17-beta-estradiol in C. albicans grown at 25 degrees C protected the organisms against the lethal temperature of 48.5 degrees C, as shown by viabl...

Whole Saliva has a Dual Role on the Adherence of Candida albicans to Polymethylmetacrylate

OpenAIRE

Elguezabal, N; Maza, J.L.; Dorronsoro, S.; Pont?n, J.

2008-01-01

Adhesion of Candida albicans to acrylic of dental prostheses or to salivary macromolecules adsorbed on their surface is believed to be a critical event in the development of denture stomatitis. In previous studies our group has shown that adhesion of C. albicans germ tubes to polystyrene is decreased by saliva whereas C. albicans yeast cells adhesion to the same material is enhanced. The results presented in this study confirm this dual role played by whole saliva, since it decreased the adhe...

Adding Biotin to Parenteral Nutrition Solutions Without Lipid Accelerates the Growth of Candida albicans.

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Kuwahara, Takashi; Kaneda, Shinya; Shimono, Kazuyuki

2016-01-01

We have previously demonstrated that Candida albicans requires multivitamins (MVs) or lipid to increase rapidly in parenteral nutrition (PN) solutions. In this study, in detail, the effects of vitamins on the growth of C. albicans in PN solutions without lipid were investigated. In the 1st experiment, a commercial PN solution without lipid was supplemented with water-soluble vitamins (SVs: vitamins B1, B2, B6, B12 and C, folic acid, nicotinamide, biotin and panthenol), water-insoluble vitamins (IVs: vitamins A, D, E and K) or both (MVs). In the 2nd experiment, the test solutions were prepared by supplementing the PN solution with one of each or all of the SVs. In the 3rd experiment, another commercial peripheral PN (PPN) solution without lipid was supplemented with SVs, nicotinic acid, biotin or both nicotinic acid and biotin. In each of the experiments, a specified number of C. albicans organisms was added to each test solution, and all of the test solutions were allowed to stand at room temperature (23-26ºC). The number of C. albicans was counted at 0, 24, 48 and 72 hours after the addition of the organism. In the 1st experiment, the C. albicans increased rapidly in the PN solution supplemented with the SVs, but increased slowly without the SVs, regardless of the addition of the IVs. In the 2nd experiment, the C. albicans increased rapidly in the PN solution supplemented with the SVs or biotin, but increased slowly with each of the other water-soluble vitamins. In the 3rd experiment, the C. albicans increased rapidly in the PPN solution supplemented with the SVs or biotin, but increased slowly with the addition of nicotinic acid. These results suggested that adding MVs or SVs to PN solutions without lipid promotes the growth of C. albicans, and that this effect is mostly attributable to biotin.

Antibiofilm and Antihyphal Activities of Cedar Leaf Essential Oil, Camphor, and Fenchone Derivatives against Candida albicans

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Ranjith Kumar Manoharan

2017-08-01

Full Text Available Candida albicans can form biofilms composed of yeast, hyphal, and pseudohyphal elements, and C. albicans cells in the hyphal stage could be a virulence factor. The present study describes the chemical composition, antibiofilm, and antihyphal activities of cedar leaf essential oil (CLEO, which was found to possess remarkable antibiofilm activity against C. albicans but not to affect its planktonic cell growth. Nineteen components were identified in CLEO by gas chromatography/mass spectrometry, and phenolics were the main constituents. Of these, camphor, fenchone, fenchyl alcohol, α-thujone, and borneol significantly reduced C. albicans biofilm formation. Notably, treatments with CLEO, camphor, or fenchyl alcohol at 0.01% clearly inhibited hyphal formation, and this inhibition appeared to be largely responsible for their antibiofilm effects. Transcriptomic analyses indicated that camphor and fenchyl alcohol downregulated some hypha-specific and biofilm related genes (ECE1, ECE2, RBT1, and EED1. Furthermore, camphor and fenchyl alcohol reduced C. albicans virulence in a Caenorhabditis elegans nematode model. These results demonstrate CLEO, camphor, and fenchyl alcohol might be useful for controlling C. albicans infections.

Modeling genome-wide dynamic regulatory network in mouse lungs with influenza infection using high-dimensional ordinary differential equations.

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Wu, Shuang; Liu, Zhi-Ping; Qiu, Xing; Wu, Hulin

2014-01-01

The immune response to viral infection is regulated by an intricate network of many genes and their products. The reverse engineering of gene regulatory networks (GRNs) using mathematical models from time course gene expression data collected after influenza infection is key to our understanding of the mechanisms involved in controlling influenza infection within a host. A five-step pipeline: detection of temporally differentially expressed genes, clustering genes into co-expressed modules, identification of network structure, parameter estimate refinement, and functional enrichment analysis, is developed for reconstructing high-dimensional dynamic GRNs from genome-wide time course gene expression data. Applying the pipeline to the time course gene expression data from influenza-infected mouse lungs, we have identified 20 distinct temporal expression patterns in the differentially expressed genes and constructed a module-based dynamic network using a linear ODE model. Both intra-module and inter-module annotations and regulatory relationships of our inferred network show some interesting findings and are highly consistent with existing knowledge about the immune response in mice after influenza infection. The proposed method is a computationally efficient, data-driven pipeline bridging experimental data, mathematical modeling, and statistical analysis. The application to the influenza infection data elucidates the potentials of our pipeline in providing valuable insights into systematic modeling of complicated biological processes.

Neutral forces acting on intragenomic variability shape the Escherichia coli regulatory network topology.

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Ruths, Troy; Nakhleh, Luay

2013-05-07

Cis-regulatory networks (CRNs) play a central role in cellular decision making. Like every other biological system, CRNs undergo evolution, which shapes their properties by a combination of adaptive and nonadaptive evolutionary forces. Teasing apart these forces is an important step toward functional analyses of the different components of CRNs, designing regulatory perturbation experiments, and constructing synthetic networks. Although tests of neutrality and selection based on molecular sequence data exist, no such tests are currently available based on CRNs. In this work, we present a unique genotype model of CRNs that is grounded in a genomic context and demonstrate its use in identifying portions of the CRN with properties explainable by neutral evolutionary forces at the system, subsystem, and operon levels. We leverage our model against experimentally derived data from Escherichia coli. The results of this analysis show statistically significant and substantial neutral trends in properties previously identified as adaptive in origin--degree distribution, clustering coefficient, and motifs--within the E. coli CRN. Our model captures the tightly coupled genome-interactome of an organism and enables analyses of how evolutionary events acting at the genome level, such as mutation, and at the population level, such as genetic drift, give rise to neutral patterns that we can quantify in CRNs.

Genoma de Candida albicans y resistencia a las drogas

OpenAIRE

Cruz Quintana, Sandra; Díaz Sjostrom, Pedro; Mazón Baldeón, Gloria; Arias Socarrás, Dunier; Calderón Paz, María; Herrera Molina, Angélica

2017-01-01

Resumen Candida albicans es un importante patógeno fúngico en los humanos tanto por su importancia clínica como por su uso como un modelo experimental para la investigación científica. La comprensión de la biología de este patógeno es un requisito importante para la identificación de nuevas dianas de medicamentos para la terapia antifúngica. En esta revisión nos proponemos profundizar en las características del genoma de Candida albicans, su relación con la virulencia y cómo influye en la res...

DAYA ANTIMIKROBA EKSTRAK COLEUS AMBOINICUS, LOUR TERHADAP CANDIDA ALBICANS PADA RESIN AKRILIK

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Devi Rianti

2015-08-01

Full Text Available A laboratory experimental study conducted on antimicrobial effects of Coleus amboinicus, Lour concentrate towards Candida albicans on acrylic resin. Samples of this study are 10x10x1 mm heat cured acrylic plates immersed in 15%, 12.5%, 10%, 7.5% of Coleus amboinicus, Lour concentrate solution. Sterilized aquadest was used as control. 16 samples were used for each exercise. Statistical analyses used are One-way Anova and LSD with 5% significance degree. The result showed that increasing Coleus amboinicus, Lour concentrate solution i.e. 7.5%, 10%, 12.5%, 15% will increased the antimicrobial effects towards Candida albicans. The most effective concentrate solution in reducing Candida albicans colonies is 15%.

A canonical correlation analysis-based dynamic bayesian network prior to infer gene regulatory networks from multiple types of biological data.

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Baur, Brittany; Bozdag, Serdar

2015-04-01

One of the challenging and important computational problems in systems biology is to infer gene regulatory networks (GRNs) of biological systems. Several methods that exploit gene expression data have been developed to tackle this problem. In this study, we propose the use of copy number and DNA methylation data to infer GRNs. We developed an algorithm that scores regulatory interactions between genes based on canonical correlation analysis. In this algorithm, copy number or DNA methylation variables are treated as potential regulator variables, and expression variables are treated as potential target variables. We first validated that the canonical correlation analysis method is able to infer true interactions in high accuracy. We showed that the use of DNA methylation or copy number datasets leads to improved inference over steady-state expression. Our results also showed that epigenetic and structural information could be used to infer directionality of regulatory interactions. Additional improvements in GRN inference can be gleaned from incorporating the result in an informative prior in a dynamic Bayesian algorithm. This is the first study that incorporates copy number and DNA methylation into an informative prior in dynamic Bayesian framework. By closely examining top-scoring interactions with different sources of epigenetic or structural information, we also identified potential novel regulatory interactions.

Selection of aptamers for Candida albicans by cell-SELEX; Selecao de aptameros para Candida albicans por cell-SELEX

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Miranda, Alessandra Nunes Duarte

2017-07-01

The growing concern with invasive fungal infections, responsible for an alarming mortality rate of immunosuppressed patients and in Intensive Care Units, evidences the need for a fast and specific method for the Candida albicans detection, since this species is identified as one of the main causes of septicemia. Commonly, it is a challenge for clinicians to determine the primary infection foci, the dissemination degree, or whether the site of a particular surgery is involved. Although scintigraphic imaging represents a promising tool for infectious foci detection, it still lacks a methodology for C. albicans diagnosis due to the absence of specific radiotracers for this microorganism. Aptamers are molecules that have almost ideal properties for use as diagnostic radiopharmaceuticals, such as high specificity for their molecular targets, lack of immunogenicity and toxicity, high tissue penetration and rapid blood clearance. Aptamers can also be labeled with different radionuclides. This work aims to obtain aptamers for specific binding to C. albicans cells for future application as a radiopharmaceutical. It was used a variation of the SELEX (Systematic Evolution of Ligands by EXponential Enrichment) technique, termed cell-SELEX, in which cells are the targets for selection. A selection protocol was standardized using a random library of single-stranded oligonucleotides, each containing two fixed regions flanking a sequence of 40 random nucleotides. This library was incubated with C. albicans cells in the presence of competitors. Then, the binding sequences were separated by centrifugation, resuspended and amplified by PCR. The amplification was confirmed by agarose gel electrophoresis. After that, the ligands were purified to obtain a new pool of ssDNA, from which a new incubation was carried out. The selection parameters were gradually modified in order to increase stringency. This cycle was repeated 12 times to allow the selection of sequences with the maximum

The Extracellular Matrix of Candida albicans Biofilms Impairs Formation of Neutrophil Extracellular Traps.

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Johnson, Chad J; Cabezas-Olcoz, Jonathan; Kernien, John F; Wang, Steven X; Beebe, David J; Huttenlocher, Anna; Ansari, Hamayail; Nett, Jeniel E

2016-09-01

Neutrophils release extracellular traps (NETs) in response to planktonic C. albicans. These complexes composed of DNA, histones, and proteins inhibit Candida growth and dissemination. Considering the resilience of Candida biofilms to host defenses, we examined the neutrophil response to C. albicans during biofilm growth. In contrast to planktonic C. albicans, biofilms triggered negligible release of NETs. Time lapse imaging confirmed the impairment in NET release and revealed neutrophils adhering to hyphae and migrating on the biofilm. NET inhibition depended on an intact extracellular biofilm matrix as physical or genetic disruption of this component resulted in NET release. Biofilm inhibition of NETosis could not be overcome by protein kinase C activation via phorbol myristate acetate (PMA) and was associated with suppression of neutrophil reactive oxygen species (ROS) production. The degree of impaired NET release correlated with resistance to neutrophil attack. The clinical relevance of the role for extracellular matrix in diminishing NET production was corroborated in vivo using a rat catheter model. The C. albicans pmr1Δ/Δ, defective in production of matrix mannan, appeared to elicit a greater abundance of NETs by scanning electron microscopy imaging, which correlated with a decreased fungal burden. Together, these findings show that C. albicans biofilms impair neutrophil response through an inhibitory pathway induced by the extracellular matrix.

Psd1 Effects on Candida albicans Planktonic Cells and Biofilms

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Sónia Gonçalves

2017-06-01

Full Text Available Candida albicans is an important human pathogen, causing opportunistic infections. The adhesion of planktonic cells to a substrate is the first step for biofilm development. The antimicrobial peptide (AMP Psd1 is a defensin isolated from Pisum sativum seeds. We tested the effects of this AMP on C. albicans biofilms and planktonic cells, comparing its activity with amphotericin B and fluconazole. Three C. albicans variants were studied, one of them a mutant deficient in glucosylceramide synthase, conferring resistance to Psd1 antifungal action. Atomic force microscopy (AFM was used to assess morphological and biomechanical changes on fungal cells. Surface alterations, with membrane disruption and leakage of cellular contents, were observed. Cytometry assays and confocal microscopy imaging showed that Psd1 causes cell death, in a time and concentration-dependent manner. These results demonstrate Psd1 pleiotropic action against a relevant fungal human pathogen, suggesting its use as natural antimycotic agent.

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

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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

Biochemical characterization of recombinant dihydroorotate dehydrogenase from the opportunistic pathogenic yeast Candida albicans

DEFF Research Database (Denmark)

Zameitat, E.; Gojkovic, Zoran; Knecht, Wolfgang

2006-01-01

Candida albicans is the most prevalent yeast pathogen in humans, and recently it has become increasingly resistant to the current antifungal agents. In this study we investigated C. albicans dihydroorotate dehydrogenase (DHODH, EC 1.3.99.11), which catalyzes the fourth step of de novo pyrimidine...

Inhibitors of the glyoxylate cycle enzyme ICL1 in Candida albicans for potential use as antifungal agents.

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Hong-Leong Cheah

Full Text Available Candida albicans is an opportunistic pathogen that causes candidiasis in humans. In recent years, metabolic pathways in C. albicans have been explored as potential antifungal targets to treat candidiasis. The glyoxylate cycle, which enables C. albicans to survive in nutrient-limited host niches and its. Key enzymes (e.g., isocitrate lyase (ICL1, are particularly attractive antifungal targets for C. albicans. In this study, we used a new screening approach that better reflects the physiological environment that C. albicans cells experience during infection to identify potential inhibitors of ICL. Three compounds (caffeic acid (CAFF, rosmarinic acid (ROS, and apigenin (API were found to have antifungal activity against C. albicans when tested under glucose-depleted conditions. We further confirmed the inhibitory potential of these compounds against ICL using the ICL enzyme assay. Lastly, we assessed the bioavailability and toxicity of these compounds using Lipinski's rule-of-five and ADMET analysis.

An overview of the gene regulatory network controlling trichome development in the model plant, Arabidopsis

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Sitakanta ePattanaik

2014-06-01

Full Text Available Trichomes are specialized epidermal cells located on aerial parts of plants and are associated with a wide array of biological processes. Trichomes protect plants from adverse conditions including UV light and herbivore attack and are also an important source of a number of phytochemicals. The simple unicellular trichomes of Arabidopsis serve as an excellent model to study molecular mechanism of cell differentiation and pattern formation in plants. The emerging picture suggests that the developmental process is controlled by a transcriptional network involving three major groups of transcription factors: the R2R3 MYB, basic helix-loop-helix (bHLH and WD40 repeat (WDR protein. These regulatory proteins form a trimeric activator complex that positively regulates trichome development. The single repeat R3 MYBs act as negative regulators of trichome development. They compete with the R2R3 MYBs to bind the bHLH factor and form a repressor complex. In addition to activator-repressor mechanism, a depletion mechanism may operate in parallel during trichome development. In this mechanism, the bHLH factor traps the WDR protein which results in depletion of WDR protein in neighboring cells. Consequently, the cells with high levels of bHLH and WDR proteins are developed into trichomes. A group of C2H2 zinc finger TFs has also been implicated in trichome development. Phytohormones, including gibberellins and jasmonic acid, play significant roles in this developmental process. Recently, microRNAs have been shown to be involved in trichome development. Furthermore, it has been demonstrated that the activities of the key regulatory proteins involved in trichome development are controlled by the 26S/ubiquitin proteasome system (UPS, highlighting the complexity of the regulatory network controlling this developmental process. To complement several excellent recent relevant reviews, this review focuses on the transcriptional network and hormonal interplay

E3Net: a system for exploring E3-mediated regulatory networks of cellular functions.

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Han, Youngwoong; Lee, Hodong; Park, Jong C; Yi, Gwan-Su

2012-04-01

Ubiquitin-protein ligase (E3) is a key enzyme targeting specific substrates in diverse cellular processes for ubiquitination and degradation. The existing findings of substrate specificity of E3 are, however, scattered over a number of resources, making it difficult to study them together with an integrative view. Here we present E3Net, a web-based system that provides a comprehensive collection of available E3-substrate specificities and a systematic framework for the analysis of E3-mediated regulatory networks of diverse cellular functions. Currently, E3Net contains 2201 E3s and 4896 substrates in 427 organisms and 1671 E3-substrate specific relations between 493 E3s and 1277 substrates in 42 organisms, extracted mainly from MEDLINE abstracts and UniProt comments with an automatic text mining method and additional manual inspection and partly from high throughput experiment data and public ubiquitination databases. The significant functions and pathways of the extracted E3-specific substrate groups were identified from a functional enrichment analysis with 12 functional category resources for molecular functions, protein families, protein complexes, pathways, cellular processes, cellular localization, and diseases. E3Net includes interactive analysis and navigation tools that make it possible to build an integrative view of E3-substrate networks and their correlated functions with graphical illustrations and summarized descriptions. As a result, E3Net provides a comprehensive resource of E3s, substrates, and their functional implications summarized from the regulatory network structures of E3-specific substrate groups and their correlated functions. This resource will facilitate further in-depth investigation of ubiquitination-dependent regulatory mechanisms. E3Net is freely available online at http://pnet.kaist.ac.kr/e3net.

17-β-Estradiol Upregulates the Stress Response in Candida albicans: Implications for Microbial Virulence

OpenAIRE

C. O’Connor; M. Essmann; B. Larsen

1998-01-01

Objective: The influence of 17-β-estradiol on the stress response of Candida albicans was studied.Methods: The survival of clinical isolates of C. albicans treated with 17-β-estradiol after heat and oxidative stress was measured by viable plate counts. Cellular proteins were analyzed via SDSPAGE.Results: The heat stress response induced by 17-β-estradiol in C. albicans grown at 25 ℃ protected the organisms against the lethal temperature of 48.5 ℃, as shown by viable plate counts. 17-β-estradi...

Dissecting Candida albicans Infection from the Perspective of C. albicans Virulence and Omics Approaches on Host–Pathogen Interaction: A Review

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Voon Kin Chin

2016-10-01

Full Text Available Candida bloodstream infections remain the most frequent life-threatening fungal disease, with Candida albicans accounting for 70% to 80% of the Candida isolates recovered from infected patients. In nature, Candida species are part of the normal commensal flora in mammalian hosts. However, they can transform into pathogens once the host immune system is weakened or breached. More recently, mortality attributed to Candida infections has continued to increase due to both inherent and acquired drug resistance in Candida, the inefficacy of the available antifungal drugs, tedious diagnostic procedures, and a rising number of immunocompromised patients. Adoption of animal models, viz. minihosts, mice, and zebrafish, has brought us closer to unraveling the pathogenesis and complexity of Candida infection in human hosts, leading towards the discovery of biomarkers and identification of potential therapeutic agents. In addition, the advancement of omics technologies offers a holistic view of the Candida-host interaction in a non-targeted and non-biased manner. Hence, in this review, we seek to summarize past and present milestone findings on C. albicans virulence, adoption of animal models in the study of C. albicans infection, and the application of omics technologies in the study of Candida–host interaction. A profound understanding of the interaction between host defense and pathogenesis is imperative for better design of novel immunotherapeutic strategies in future.

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

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Yeh Cheng-Yu

2009-12-01

Full Text Available Abstract Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2 regulated by RUNX1 and STAT3 is correlated to the pathological stage

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

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Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

2009-12-21

Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

Radiotherapy Reduced Salivary Flow Rate and Might Induced C. albicans Infection

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Nadia Surjadi

2013-07-01

Full Text Available Radiotherapy has impact in oral health especially on the secretion capacity of the salivary glands. Another impact is the increase of Candida albicans colony. Objectives: To evaluate salivary flow in relation with Candida albicans colony in head and neck cancer patients during and after radiotherapy. Methods: Twenty-four head and neck cancer patients in Dharmais Cancer Hospital, Jakarta who were undergoing radiotherapy or had undergone radiotherapy and 24 match healthy volunteers were included in the study. Clinical observation carried out by collecting unstimulated salivary flow rate and followed by culture of Candida in Saboraud agar medium. Data were analyzed statistically by Chi-square. Results: Nasopharynx cancer was the most frequent type of head and neck cancers (87.5% followed by tongue cancer (12.5% and and found in 41-50 years old patients and 51-60 years old patients respectively, with male predilection compare to female (17:7. Approxiamtely 87.5% of subjects showed decreased salivary flow rate (1.01-1.50mL/10min during and after radiotherapy. However, 91.7% of cancer patients had increased C.albicans colony during and after radiotherapy compared to control (p=0.00. Conclusion: This study showed that radiotherapy induced hyposalivation and might increase the C.albicans colony.  

Systemic non-albicans infections presented as meningitis in chronic hepatitis B patient: a case report

OpenAIRE

Wen-Jing Lv; Hui Bu; Jun-Ying He; Ran-Ran Sun; Yue-Li Zou

2014-01-01

Non-albicans candida meningitis is a relatively rare disease, with nonspecific clinical manifestation, which makes the misdiagnosis occur sometimes, especially in the early stage of the disease. Abuse of broad-spectrum antibiotics, corticosteroids, central vein cannulas, senility, big operation, malignancy, and total parenteral alimentation were all the susceptible factors of non-albicans candida infection. We present a case of this type of non-albicans infection in a 42-year-old woman who wa...

Candida albicans Hom6 is a homoserine dehydrogenase involved in protein synthesis and cell adhesion

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Pei-Wen Tsai

2017-12-01

Full Text Available Background/Purpose: Candida albicans is a common fungal pathogen in humans. In healthy individuals, C. albicans represents a harmless commensal organism, but infections can be life threatening in immunocompromised patients. The complete genome sequence of C. albicans is extremely useful for identifying genes that may be potential drug targets and important for pathogenic virulence. However, there are still many uncharacterized genes in the Candida genome database. In this study, we investigated C. albicans Hom6, the functions of which remain undetermined experimentally. Methods: HOM6-deleted and HOM6-reintegrated mutant strains were constructed. The mutant strains were compared with wild-type in their growth in various media and enzyme activity. Effects of HOM6 deletion on translation were further investigated by cell susceptibility to hygromycin B or cycloheximide, as well as by polysome profiling, and cell adhesion to polystyrene was also determined. Results: C. albicans Hom6 exhibits homoserine dehydrogenase activity and is involved in the biosynthesis of methionine and threonine. HOM6 deletion caused translational arrest in cells grown under amino acid starvation conditions. Additionally, Hom6 protein was found in both cytosolic and cell-wall fractions of cultured cells. Furthermore, HOM6 deletion reduced C. albicans cell adhesion to polystyrene, which is a common plastic used in many medical devices. Conclusion: Given that there is no Hom6 homologue in mammalian cells, our results provided an important foundation for future development of new antifungal drugs. Keywords: Candida albicans, cell adhesion, Hom6, homoserine dehydrogenase, protein synthesis

The role of candida albicans in the pathogenesis of psoriasis vulgaris: a systematic literature review

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Sona Sepahi

2016-07-01

Full Text Available Introduction: Psoriasis is a chronic, inflammatory skin disease that is related to many genetic, and environmental factors, as well as infectious pathogens. Findings suggest that the Candida species, particularly Candida albicans, may play a role in the pathogenesis of psoriasis vulgaris. In this study, we aimed to systematically review the possible association between C. albicans and the prevalence of psoriasis. Methods: A systematic search of existing literature was performed in the PubMed, Scopus and Google Scholar databases and the Google search engine using the following search strategy ((Candida albicans OR C. albicans OR Candida AND (psoriasis vulgaris OR plaque psoriasis OR psoriasis to find relevant articles that described a possible positive or negative association between C. albicans and the incidence or progression of psoriasis. The search was not limited to articles that were published within a specific time period; however, only those written in the English language were included in the review.Result: Of the 499 articles in total that were identified during the initial database search, 491 were excluded from the review because they failed to meet the inclusion/exclusion criteria. The total number of people involved in the selected studies, including both patients and healthy controls, was 1260. The analysis of the results of the included documents showed that the colonization of C. albicans is more prevalent in biological specimens taken from psoriatic patients.Conclusion: Studies show that C. albicans, opportunistic yeast, like diploid fungus, may be involved in the pathogenesis of psoriasis.

Antifungal Activity of Bee Venom and Sweet Bee Venom against Clinically Isolated Candida albicans

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Seung-Bae Lee

2016-03-01

Full Text Available Objectives: The purpose of this study was to investigate the antifungal effect of bee venom (BV and sweet bee venom (SBV against Candida albicans (C. albicans clinical isolates. Methods: In this study, BV and SBV were examined for antifungal activities against the Korean Collection for Type Cultures (KCTC strain and 10 clinical isolates of C. albicans. The disk diffusion method was used to measure the antifungal activity and minimum inhibitory concentration (MIC assays were performed by using a broth microdilution method. Also, a killing curve assay was conducted to investigate the kinetics of the anti- fungal action. Results: BV and SBV showed antifungal activity against 10 clinical isolates of C. albicans that were cultured from blood and the vagina by using disk diffusion method. The MIC values obtained for clinical isolates by using the broth microdilution method varied from 62.5 μg/ mL to 125 μg/mL for BV and from 15.63 μg/mL to 62.5 μg/mL for SBV. In the killing-curve assay, SBV behaved as amphotericin B, which was used as positive control, did. The antifungal efficacy of SBV was much higher than that of BV. Conclusion: BV and SBV showed antifungal activity against C. albicans clinical strains that were isolated from blood and the vagina. Especially, SBV might be a candidate for a new antifungal agent against C. albicans clinical isolates.

Effect of emodin on Candida albicans growth investigated by microcalorimetry combined with chemometric analysis.

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Kong, W J; Wang, J B; Jin, C; Zhao, Y L; Dai, C M; Xiao, X H; Li, Z L

2009-07-01

Using the 3114/3115 thermal activity monitor (TAM) air isothermal microcalorimeter, ampoule mode, the heat output of Candida albicans growth at 37 degrees C was measured, and the effect of emodin on C. albicans growth was evaluated by microcalorimetry coupled with chemometric methods. The similarities between the heat flow power (HFP)-time curves of C. albicans growth affected by different concentrations of emodin were calculated by similarity analysis (SA). In the correspondence analysis (CA) diagram of eight quantitative parameters taken from the HFP-time curves, it could be deduced that emodin had definite dose-effect relationship as the distance between different concentrations of it increased along with the dosage and the effect. From the principal component analysis (PCA) on eight quantitative parameters, the action of emodin on C. albicans growth could be easily evaluated by analyzing the change of values of the main two parameters, growth rate constant k (2) and maximum power output P(2)(m). The coherent results of SA, CA, and PCA showed that emodin at different concentrations had different effects on C. albicans growth metabolism: A low concentration (0-10 microg ml(-1)) poorly inhibited the growth of C. albicans, and a high concentration (15-35 microg ml(-1)) could notably inhibit growth of this fungus. This work provided a useful idea of the combination of microcalorimetry and chemometric analysis for investigating the effect of drug and other compounds on microbes.

Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

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Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

2017-01-01

Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

RNA regulatory networks in animals and plants: a long noncoding RNA perspective.

Science.gov (United States)

Bai, Youhuang; Dai, Xiaozhuan; Harrison, Andrew P; Chen, Ming

2015-03-01

A recent highlight of genomics research has been the discovery of many families of transcripts which have function but do not code for proteins. An important group is long noncoding RNAs (lncRNAs), which are typically longer than 200 nt, and whose members originate from thousands of loci across genomes. We review progress in understanding the biogenesis and regulatory mechanisms of lncRNAs. We describe diverse computational and high throughput technologies for identifying and studying lncRNAs. We discuss the current knowledge of functional elements embedded in lncRNAs as well as insights into the lncRNA-based regulatory network in animals. We also describe genome-wide studies of large amount of lncRNAs in plants, as well as knowledge of selected plant lncRNAs with a focus on biotic/abiotic stress-responsive lncRNAs. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

The transcriptional and gene regulatory network of Lactococcus lactis MG1363 during growth in milk.

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Anne de Jong

Full Text Available In the present study we examine the changes in the expression of genes of Lactococcus lactis subspecies cremoris MG1363 during growth in milk. To reveal which specific classes of genes (pathways, operons, regulons, COGs are important, we performed a transcriptome time series experiment. Global analysis of gene expression over time showed that L. lactis adapted quickly to the environmental changes. Using upstream sequences of genes with correlated gene expression profiles, we uncovered a substantial number of putative DNA binding motifs that may be relevant for L. lactis fermentative growth in milk. All available novel and literature-derived data were integrated into network reconstruction building blocks, which were used to reconstruct and visualize the L. lactis gene regulatory network. This network enables easy mining in the chrono-transcriptomics data. A freely available website at http://milkts.molgenrug.nl gives full access to all transcriptome data, to the reconstructed network and to the individual network building blocks.

Thiazolidinedione-8 alters symbiotic relationship in C. albicans-S. mutans dual species biofilm

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Mark eFeldman

2016-02-01

Full Text Available The small molecule, thiazolidinedione-8 (S-8 was shown to impair biofilm formation of various microbial pathogens, including the fungus Candida albicans and Streptococcus mutans. Previously, we have evaluated the specific molecular mode of S-8 action against C. albicans biofilm-associated pathogenicity. In this study we investigated the influence of S-8 on dual species, C. albicans-S. mutans biofilm. We show that in the presence of S-8 a reduction of the co-species biofilm formation occurred with a major effect on C. albicans. Biofilm biomass and exopolysaccharide (EPS production were significantly reduced by S-8. Moreover, the agent caused oxidative stress associated with a strong induction of reactive oxygen species (ROS and hydrogen peroxide uptake inhibition by a mixed biofilm. In addition, S-8 altered symbiotic relationship between these species by a complex mechanism. Streptococcal genes associated with quorum sensing (comDE and luxS, EPS production (gtfBCD and gbpB, as well as genes related to protection against oxidative stress (nox and sodA were markedly upregulated by S-8. In contrast, fungal genes related to hyphae formation (hwp1, adhesion (als3, hydrophobicity (csh1 and oxidative stress response (sod1, sod2 and cat1 were downregulated in the presence of S-8. In addition, ywp1 gene associated with yeast form of C. albicans was induced by S-8, which is correlated with appearance of mostly yeast cells in S-8 treated dual species biofilms. We concluded that S-8 disturbs symbiotic balance between C. albicans and S. mutans in dual species biofilm.

Antifungal activity of four honeys of different types from Algeria against pathogenic yeast: Candida albicans and Rhodotorula sp.

OpenAIRE

Ahmed Moussa; Djebli Noureddine; Aissat Saad; Meslem Abdelmelek; Benhalima Abdelkader

2012-01-01

Objective: To evaluate the antifungal activity of four honeys of different types from Algeria against pathogenic yeast i.e. Candida albicans (C. albicans) and Rhodotorula sp. Methods: Four Algeria honeys of different botanical origin were analyzed to test antifungal effect against C. albicans, and Rhodotorula sp. Different concentrations (undiluted, 10%, 30%, 50% and 70% w/v) of honey were studied in vitro for their antifugal activity using C. albicans and Rhodotorula sp. as fungal strains...

PKC signaling regulates drug resistance of the fungal pathogen Candida albicans via circuitry comprised of Mkc1, calcineurin, and Hsp90.

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Shantelle L LaFayette

2010-08-01

Full Text Available Fungal pathogens exploit diverse mechanisms to survive exposure to antifungal drugs. This poses concern given the limited number of clinically useful antifungals and the growing population of immunocompromised individuals vulnerable to life-threatening fungal infection. To identify molecules that abrogate resistance to the most widely deployed class of antifungals, the azoles, we conducted a screen of 1,280 pharmacologically active compounds. Three out of seven hits that abolished azole resistance of a resistant mutant of the model yeast Saccharomyces cerevisiae and a clinical isolate of the leading human fungal pathogen Candida albicans were inhibitors of protein kinase C (PKC, which regulates cell wall integrity during growth, morphogenesis, and response to cell wall stress. Pharmacological or genetic impairment of Pkc1 conferred hypersensitivity to multiple drugs that target synthesis of the key cell membrane sterol ergosterol, including azoles, allylamines, and morpholines. Pkc1 enabled survival of cell membrane stress at least in part via the mitogen activated protein kinase (MAPK cascade in both species, though through distinct downstream effectors. Strikingly, inhibition of Pkc1 phenocopied inhibition of the molecular chaperone Hsp90 or its client protein calcineurin. PKC signaling was required for calcineurin activation in response to drug exposure in S. cerevisiae. In contrast, Pkc1 and calcineurin independently regulate drug resistance via a common target in C. albicans. We identified an additional level of regulatory control in the C. albicans circuitry linking PKC signaling, Hsp90, and calcineurin as genetic reduction of Hsp90 led to depletion of the terminal MAPK, Mkc1. Deletion of C. albicans PKC1 rendered fungistatic ergosterol biosynthesis inhibitors fungicidal and attenuated virulence in a murine model of systemic candidiasis. This work establishes a new role for PKC signaling in drug resistance, novel circuitry through which

Clinical strains of Lactobacillus reduce the filamentation of Candida albicans and protect Galleria mellonella against experimental candidiasis.

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Rossoni, Rodnei Dennis; Dos Santos Velloso, Marisol; Figueiredo, Lívia Mara Alves; Martins, Carolina Pistille; Jorge, Antonio Olavo Cardoso; Junqueira, Juliana Campos

2018-05-01

Candida albicans is the most common human fungal pathogen and can grow as yeast or filaments, depending on the environmental conditions. The filamentous form is of particular interest because it can play a direct role in adherence and pathogenicity. Therefore, the purpose of this study was to evaluate the effects of three clinical strains of Lactobacillus on C. albicans filamentation as well as their probiotic potential in pathogen-host interactions via an experimental candidiasis model study in Galleria mellonella. We used the reference strain Candida albicans ATCC 18804 and three clinical strains of Lactobacillus: L. rhamnosus strain 5.2, L. paracasei strain 20.3, and L. fermentum strain 20.4. First, the capacity of C. albicans to form hyphae was tested in vitro through association with the Lactobacillus strains. After that, we verified the ability of these strains to attenuate experimental candidiasis in a Galleria mellonella model through a survival curve assay. Regarding the filamentation assay, a significant reduction in hyphae formation of up to 57% was observed when C. albicans was incubated in the presence of the Lactobacillus strains, compared to a control group composed of only C. albicans. In addition, when the larvae were pretreated with Lactobacillus spp. prior to C. albicans infection, the survival rate of G. mellonela increased in all experimental groups. We concluded that Lactobacillus influences the growth and expression C. albicans virulence factors, which may interfere with the pathogenicity of these microorganisms.

GRNsight: a web application and service for visualizing models of small- to medium-scale gene regulatory networks

Directory of Open Access Journals (Sweden)

Kam D. Dahlquist

2016-09-01

Full Text Available GRNsight is a web application and service for visualizing models of gene regulatory networks (GRNs. A gene regulatory network (GRN consists of genes, transcription factors, and the regulatory connections between them which govern the level of expression of mRNA and protein from genes. The original motivation came from our efforts to perform parameter estimation and forward simulation of the dynamics of a differential equations model of a small GRN with 21 nodes and 31 edges. We wanted a quick and easy way to visualize the weight parameters from the model which represent the direction and magnitude of the influence of a transcription factor on its target gene, so we created GRNsight. GRNsight automatically lays out either an unweighted or weighted network graph based on an Excel spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows, a Simple Interaction Format (SIF text file, or a GraphML XML file. When a user uploads an input file specifying an unweighted network, GRNsight automatically lays out the graph using black lines and pointed arrowheads. For a weighted network, GRNsight uses pointed and blunt arrowheads, and colors the edges and adjusts their thicknesses based on the sign (positive for activation or negative for repression and magnitude of the weight parameter. GRNsight is written in JavaScript, with diagrams facilitated by D3.js, a data visualization library. Node.js and the Express framework handle server-side functions. GRNsight’s diagrams are based on D3.js’s force graph layout algorithm, which was then extensively customized to support the specific needs of GRNs. Nodes are rectangular and support gene labels of up to 12 characters. The edges are arcs, which become straight lines when the nodes are close together. Self-regulatory edges are indicated by a loop. When a user mouses over an edge, the numerical value of the weight parameter is displayed. Visualizations can

A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

Science.gov (United States)

Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

2016-06-01

Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs. Copyright © 2016 Elsevier Inc. All rights reserved.

Competitive Fitness of Fluconazole-Resistant Clinical Candida albicans Strains.

Science.gov (United States)

Popp, Christina; Hampe, Irene A I; Hertlein, Tobias; Ohlsen, Knut; Rogers, P David; Morschhäuser, Joachim

2017-07-01

The pathogenic yeast Candida albicans can develop resistance to the widely used antifungal agent fluconazole, which inhibits ergosterol biosynthesis. Resistance is often caused by gain-of-function mutations in the transcription factors Mrr1 and Tac1, which result in constitutive overexpression of multidrug efflux pumps, and Upc2, which result in constitutive overexpression of ergosterol biosynthesis genes. However, the deregulated gene expression that is caused by hyperactive forms of these transcription factors also reduces the fitness of the cells in the absence of the drug. To investigate whether fluconazole-resistant clinical C. albicans isolates have overcome the fitness costs of drug resistance, we assessed the relative fitness of C. albicans isolates containing resistance mutations in these transcription factors in competition with matched drug-susceptible isolates from the same patients. Most of the fluconazole-resistant isolates were outcompeted by the corresponding drug-susceptible isolates when grown in rich medium without fluconazole. On the other hand, some resistant isolates with gain-of-function mutations in MRR1 did not exhibit reduced fitness under these conditions. In a mouse model of disseminated candidiasis, three out of four tested fluconazole-resistant clinical isolates did not exhibit a significant fitness defect. However, all four fluconazole-resistant isolates were outcompeted by the matched susceptible isolates in a mouse model of gastrointestinal colonization, demonstrating that the effects of drug resistance on in vivo fitness depend on the host niche. Collectively, our results indicate that the fitness costs of drug resistance in C. albicans are not easily remediated, especially when proper control of gene expression is required for successful adaptation to life within a mammalian host. Copyright © 2017 American Society for Microbiology.

An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series.

Science.gov (United States)

Wang, Zidong; Liu, Xiaohui; Liu, Yurong; Liang, Jinling; Vinciotti, Veronica

2009-01-01

In this paper, the extended Kalman filter (EKF) algorithm is applied to model the gene regulatory network from gene time series data. The gene regulatory network is considered as a nonlinear dynamic stochastic model that consists of the gene measurement equation and the gene regulation equation. After specifying the model structure, we apply the EKF algorithm for identifying both the model parameters and the actual value of gene expression levels. It is shown that the EKF algorithm is an online estimation algorithm that can identify a large number of parameters (including parameters of nonlinear functions) through iterative procedure by using a small number of observations. Four real-world gene expression data sets are employed to demonstrate the effectiveness of the EKF algorithm, and the obtained models are evaluated from the viewpoint of bioinformatics.

Transcriptional regulatory network triggered by oxidative signals configures the early response mechanisms of japonica rice to chilling stress

KAUST Repository

Yun, Kil-Young; Park, Myoung Ryoul; Mohanty, Bijayalaxmi; Herath, Venura; Xu, Fuyu; Mauleon, Ramil; Wijaya, Edward; Bajic, Vladimir B.; Bruskiewich, Richard; de los Reyes, Benildo G

2010-01-01

-plant level analyses established a holistic view of chilling stress response mechanism of japonica rice. Early response regulatory network triggered by oxidative signals is critical for prolonged survival under sub-optimal temperature. Integration of stress

Streptococcus agalactiae Inhibits Candida albicans Hyphal Development and Diminishes Host Vaginal Mucosal TH17 Response

OpenAIRE

Xiao-Yu Yu; Fei Fu; Wen-Na Kong; Qian-Kun Xuan; Dong-Hua Wen; Xiao-Qing Chen; Yong-Ming He; Li-Hua He; Jian Guo; Ai-Ping Zhou; Yang-Hong Xi; Li-Jun Ni; Yu-Feng Yao; Wen-Juan Wu

2018-01-01

Streptococcus agalactiae and Candida albicans often co-colonize the female genital tract, and under certain conditions induce mucosal inflammation. The role of the interaction between the two organisms in candidal vaginitis is not known. In this study, we found that co-infection with S. agalactiae significantly attenuated the hyphal development of C. albicans, and that EFG1-Hwp1 signal pathway of C. albicans was involved in this process. In a mouse model of vulvovaginal candidiasis (VVC), the...

Genoma de Candida albicans y resistencia a las drogas

OpenAIRE

Sandra Cruz Quintana; Pedro Díaz Sjostrom; Gloria Mazón Baldeón; Dunier Arias Socarrás; María Calderón Paz; Angélica Herrera Molina

2017-01-01

Candida albicans es un importante patógeno fúngico en los humanos tanto por su importan - cia clínica como por su uso como un modelo experimental para la investigación científica. La comprensión de la biología de este patógeno es un requisito importante para la identificación de nuevas dianas de medicamentos para la terapia antifúngica. En esta revisión nos proponemos profundizar en las características del genoma de Candida albicans, su relación con la virulen - cia y cómo influye en la re...

The PHR Family: The Role of Extracellular Transglycosylases in Shaping Candida albicans Cells

Directory of Open Access Journals (Sweden)

Laura Popolo

2017-10-01

Full Text Available Candida albicans is an opportunistic microorganism that can become a pathogen causing mild superficial mycosis or more severe invasive infections that can be life-threatening for debilitated patients. In the etiology of invasive infections, key factors are the adaptability of C. albicans to the different niches of the human body and the transition from a yeast form to hypha. Hyphal morphology confers high adhesiveness to the host cells, as well as the ability to penetrate into organs. The cell wall plays a crucial role in the morphological changes C. albicans undergoes in response to specific environmental cues. Among the different categories of enzymes involved in the formation of the fungal cell wall, the GH72 family of transglycosylases plays an important assembly role. These enzymes cut and religate β-(1,3-glucan, the major determinant of cell shape. In C. albicans, the PHR family encodes GH72 enzymes, some of which work in specific environmental conditions. In this review, we will summarize the work from the initial discovery of PHR genes to the study of the pH-dependent expression of PHR1 and PHR2, from the characterization of the gene products to the recent findings concerning the stress response generated by the lack of GH72 activity in C. albicans hyphae.

Quantitative assessment of S. mutans and C. albicans in patients with Haas and Hyrax expanders

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Matheus Melo Pithon

2012-06-01

Full Text Available OBJECTIVE: To assess and compare the number of Streptococcus mutans and Candida albicans colonies in patients with Haas and Hyrax appliances before and after insertion. METHODS: The sample consisted of 84 patients requiring orthodontic treatment. For all patients a midpalatal suture expansion was indicated. Patients were randomly divided into Group HA, who used the Haas appliance (n = 42 and Group HY, who used the Hyrax appliance (n = 42. Initially and thirty days after appliance insertion all patients were submitted to saliva collections. The saliva was diluted followed by seeding in Mitis Salivarius and CHROMagar media, for growth of S. mutans and C. albicans respectively. RESULTS: Results showed statistically significant difference between groups HA and HY for Streptococcus mutans and Candida albicans (p <0.05. Haas appliance promoted greater S. mutans and C. albicans proliferation when compared to Hyrax appliance. CONCLUSION: The Haas appliance favored greater proliferation of S. mutans and C. albicans when compared with the Hyrax appliance. Insertion of the appliances resulted in greater buildup of microorganisms.

A novel small molecule methyltransferase is important for virulence in Candida albicans.