The temporal response of the
            <i>Mycobacterium tuberculosis</i>
            gene regulatory network during growth arrest

Balázsi, Gábor; Heath, Allison P.; Shi, Lanbo; Gennaro, Maria Laura

doi:10.1038/msb.2008.63

Cited by 116 publications

(153 citation statements)

References 48 publications

(65 reference statements)

Supporting

Mentioning

148

Contrasting

Unclassified

Order By: Relevance

“…Our result is in sharp contrast with what would arise in a model without molecular modeling of the interactions. Sparseness would then have to be enforced in an ad-hoc way because biological networks are indeed sparse experimentally (41,42).…”

Section: Resultsmentioning

confidence: 99%

Motifs emerge from function in model gene regulatory networks

Burda

Krzywicki

Martin

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Gene regulatory networks allow the control of gene expression patterns in living cells. The study of network topology has revealed that certain subgraphs of interactions or "motifs" appear at anomalously high frequencies. We ask here whether this phenomenon may emerge because of the functions carried out by these networks. Given a framework for describing regulatory interactions and dynamics, we consider in the space of all regulatory networks those that have prescribed functional capabilities. Markov Chain Monte Carlo sampling is then used to determine how these functional networks lead to specific motif statistics in the interactions. In the case where the regulatory networks are constrained to exhibit multistability, we find a high frequency of gene pairs that are mutually inhibitory and self-activating. In contrast, networks constrained to have periodic gene expression patterns (mimicking for instance the cell cycle) have a high frequency of bifan-like motifs involving four genes with at least one activating and one inhibitory interaction.essential interactions | genetic switch | transcription factors E volutionary forces have shaped living organisms since the beginning of life. It is thus not surprising that the framework for understanding features in today's organisms is often based on considering the history of these organisms: a remarkable feature found today may be the trace of an evolutionary trajectory. But one can also take a different perspective, one in which design constraints may play a significant role. The expectation is then that the architecture of living organisms depends not just on their origin, but also on their functional capabilities. In the present context, we are concerned with biological networks. Are the constraints associated with network functionality major determinants of network architecture? We address this question in this paper, albeit using a somewhat narrow notion of functionality based on the output patterns produced by networks.Our focus here is on gene regulatory networks (GRN), the set of interactions between genes. These interactions along with the gene expression machinery allow living cells to control their gene expression patterns. In the last decade, genetic interactions have been measured, modified, engineered, etc., and so quite a lot is known about how any given gene can affect another's expression. Furthermore, small gene networks have been designed to implement simple functions in vivo (1, 2), and much larger sets of interactions have been reconstructed in a number of organisms (3-5). From these large networks it has been possible to show that several "motifs"-subgraphs with given interactions-arise far more often than might be expected (6-9). One of the most studied motif is the so called Feed Forward Loop or FFL, a graph based on three genes where the first regulates the second, and both the first and the second regulate the third. Another example is the bifan motif in which two genes control two others. Biological functions have been proposed for these moti...

show abstract

Section: Resultsmentioning

confidence: 99%

Motifs emerge from function in model gene regulatory networks

Burda

Krzywicki

Martin

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

show abstract

“…It has been shown that distinct topological units (called origons) at the root of these hierarchies are significantly affected by environmental signals (8). These origons have been shown to be responsive at various stages of adaptation of Mycobacterium tuberculosis allowing a gradual progression of network under both replicative (growth) and nonreplicative (dormancy) states (9). Evolutionary analysis of Escherichia coli showed that transcriptional networks tend to grow by expansion of existing hierarchical layers, rather than addition of new layers (10).…”

mentioning

confidence: 99%

Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels

Bhardwaj

Yan

Gerstein

2010

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Gene regulatory networks have been shown to share some common aspects with commonplace social governance structures. Thus, we can get some intuition into their organization by arranging them into well-known hierarchical layouts. These hierarchies, in turn, can be placed between the extremes of autocracies, with welldefined levels and clear chains of command, and democracies, without such defined levels and with more co-regulatory partnerships between regulators. In general, the presence of partnerships decreases the variation in information flow amongst nodes within a level, more evenly distributing stress. Here we study various regulatory networks (transcriptional, modification, and phosphorylation) for five diverse species, Escherichia coli to human. We specify three levels of regulators-top, middle, and bottom-which collectively govern the non-regulator targets lying in the lowest fourth level. We define quantities for nodes, levels, and entire networks that measure their degree of collaboration and autocratic vs. democratic character. We show individual regulators have a range of partnership tendencies: Some regulate their targets in combination with other regulators in local instantiations of democratic structure, whereas others regulate mostly in isolation, in more autocratic fashion. Overall, we show that in all networks studied the middle level has the highest collaborative propensity and coregulatory partnerships occur most frequently amongst midlevel regulators, an observation that has parallels in corporate settings where middle managers must interact most to ensure organizational effectiveness. There is, however, one notable difference between networks in different species: The amount of collaborative regulation and democratic character increases markedly with overall genomic complexity.coregulatory partnerships | hierarchy | middle managers | autocracy | democracy

show abstract

“…Understanding the environmental cues that are important during infection, and the regulatory cascades that are triggered, will precipitate novel intervention strategies for combating M.tuberculosis disease. A major benefit of these global profiling datasets is the ability to attribute predicted action to genes of unknown function using gene regulatory or protein network modelling [24,50]. Such interaction networks, together with metabolic models of M.tb [51], will be required to map and digest the huge quantity of mRNA abundance data generated from microarray and sequencing projects.…”

Section: Regulation Of Gene Expressionmentioning

confidence: 99%

Reprogramming the Mycobacterium tuberculosis transcriptome during pathogenesis

Waddell

2010

Drug Discovery Today: Disease Mechanisms

View full text Add to dashboard Cite

Transcriptional profiling has revealed that Mycobacterium tuberculosis adapts both its metabolic and respiratory states during infection, utilising lipids as a carbon source and switching to alternative electron acceptors. These global gene expression datasets may be exploited to identify virulence determinants and to screen for new targets for rational drug design. Characterising the changing physiological predicament of distinct M.tb populations during infection will help expose the fundamental biology of M.tb; highlighting mechanisms that influence tuberculosis pathogenicity.

show abstract

The temporal response of the Mycobacterium tuberculosis gene regulatory network during growth arrest

Cited by 116 publications

References 48 publications

Motifs emerge from function in model gene regulatory networks

Motifs emerge from function in model gene regulatory networks

Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels

Reprogramming the Mycobacterium tuberculosis transcriptome during pathogenesis

Contact Info

Product

Resources

About