Strategies for cellular decision‐making

Perkins, Theodore J.; Swain, Peter S.

doi:10.1038/msb.2009.83

Cited by 303 publications

(259 citation statements)

References 103 publications

(142 reference statements)

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“…Recent work has shown that biochemical networks have evolved to capture the multidimensional structure of diverse environments and thus form internal representations (through regulatory networks) that allow the prediction of environmental changes. For example, Tagkopoulos et al (17) provided evidence of anticipatory behavior of E. coli to changes in temperature and oxygen levels that occurred over evolutionary time scales (21,22). We examined the anticipatory ability of our rewired GTRNs by computing their optimality using transcriptomic fitness with the same set of genes used in the in silico evolutionary process.…”

Section: Discussionmentioning

confidence: 99%

Computational design of genomic transcriptional networks with adaptation to varying environments

Carrera

Elena

Jaramillo

2012

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

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Transcriptional profiling has been widely used as a tool for unveiling the coregulations of genes in response to genetic and environmental perturbations. These coregulations have been used, in a few instances, to infer global transcriptional regulatory models. Here, using the large amount of transcriptomic information available for the bacterium Escherichia coli, we seek to understand the design principles determining the regulation of its transcriptome. Combining transcriptomic and signaling data, we develop an evolutionary computational procedure that allows obtaining alternative genomic transcriptional regulatory network (GTRN) that still maintains its adaptability to dynamic environments. We apply our methodology to an E. coli GTRN and show that it could be rewired to simpler transcriptional regulatory structures. These rewired GTRNs still maintain the global physiological response to fluctuating environments. Rewired GTRNs contain 73% fewer regulated operons. Genes with similar functions and coordinated patterns of expression across environments are clustered into longer regulated operons. These synthetic GTRNs are more sensitive and show a more robust response to challenging environments. This result illustrates that the natural configuration of E. coli GTRN does not necessarily result from selection for robustness to environmental perturbations, but that evolutionary contingencies may have been important as well. We also discuss the limitations of our methodology in the context of the demand theory. Our procedure will be useful as a novel way to analyze global transcription regulation networks and in synthetic biology for the de novo design of genomes.automated design | synthetic genomics | genome refactoring | evolutionary computation O rganisms have evolved mechanisms for regulating transcription to better adapt to changing environments. Could such regulation be engineered in a different way (1, 2)? Recent experiments investigating the evolvability of bacterial transcriptional regulatory networks (TRNs) have shown that the massive addition of new links to the network does not significantly alter cell growth. Isalan et al. (3) added transcriptional fusions of promoters with different master transcriptional regulators and showed that Escherichia coli (E. coli) tolerated almost all rewired networks; however, growth was perturbed by as much as 5% (3). This inherent predisposition of E. coli networks to dampen extreme changes in their circuitry enables the possibility of conducting genome-wide rewiring (4). Global transcription regulation could also be analyzed by comparing the regulatory models from distant organisms, provided they show a similar response to the set of studied environments. In this way, they could provide alternative regulatory models, although the lack of knowledge of species-specific selective pressures may blur the conclusions. We will propose here an alternative evolution experiment, which will be conducted computationally thanks to the availability of a quantitative model for the genom...

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Section: Discussionmentioning

confidence: 99%

Computational design of genomic transcriptional networks with adaptation to varying environments

Carrera

Elena

Jaramillo

2012

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

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“…cheaters), particularly in spatially unstructured populations [28]. Within a structured population of closely related individuals, however, cooperative traits can be favoured as a public good and facilitate the success of the entire population [29][30][31][32]. This principle of facilitation [33,34] has been shown in populations of various organisms, including bacteria [35], toxigenic cyanobacteria [36], amoeba [37] and yeast [38].…”

Section: Introductionmentioning

confidence: 99%

Intraspecific facilitation by allelochemical mediated grazing protection within a toxigenic dinoflagellate population

et al. 2015

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Dinoflagellates are a major cause of harmful algal blooms (HABs), with consequences for coastal marine ecosystem functioning and services. Alexandrium fundyense (previously Alexandrium tamarense) is one of the most abundant and widespread toxigenic species in the temperate Northern and Southern Hemisphere and produces paralytic shellfish poisoning toxins as well as lytic allelochemical substances. These bioactive compounds may support the success of A. fundyense and its ability to form blooms. Here we investigate the impact of grazing on monoclonal and mixed set-ups of highly (Alex2) and moderately (Alex4) allelochemically active A. fundyense strains and a non-allelochemically active conspecific (Alex5) by the heterotrophic dinoflagellate Polykrikos kofoidii. While Alex4 and particularly Alex5 were strongly grazed by P. kofoidii when offered alone, both strains grew well in the mixed assemblages (Alex4 þ Alex5 and Alex2 þ Alex5). Hence, the allelochemical active strains facilitated growth of the non-active strain by protecting the population as a whole against grazing. Based on our results, we argue that facilitation among clonal lineages within a species may partly explain the high genotypic and phenotypic diversity of Alexandrium populations. Populations of Alexandrium may comprise multiple cooperative traits that act in concert with intraspecific facilitation, and hence promote the success of this notorious HAB species.

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“…diffusion sensing | bacterial signaling | efficiency sensing | collective behavior | bacterial cooperation B acteria must often make regulatory decisions on the basis of limited information about their external world (1). In many bacteria, these decisions are aided by the secretion and detection of small diffusible molecules, in a process called quorum sensing (QS) (2,3).…”

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confidence: 99%

Combinatorial quorum sensing allows bacteria to resolve their social and physical environment

Cornforth

Popat

McNally

et al. 2014

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

173

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Quorum sensing (QS) is a cell-cell communication system that controls gene expression in many bacterial species, mediated by diffusible signal molecules. Although the intracellular regulatory mechanisms of QS are often well-understood, the functional roles of QS remain controversial. In particular, the use of multiple signals by many bacterial species poses a serious challenge to current functional theories. Here, we address this challenge by showing that bacteria can use multiple QS signals to infer both their social (density) and physical (mass-transfer) environment. Analytical and evolutionary simulation models show that the detection of, and response to, complex social/physical contrasts requires multiple signals with distinct half-lives and combinatorial (nonadditive) responses to signal concentrations. We test these predictions using the opportunistic pathogen Pseudomonas aeruginosa and demonstrate significant differences in signal decay between its two primary signal molecules, as well as diverse combinatorial responses to dual-signal inputs. QS is associated with the control of secreted factors, and we show that secretome genes are preferentially controlled by synergistic "AND-gate" responses to multiple signal inputs, ensuring the effective expression of secreted factors in high-density and low mass-transfer environments. Our results support a new functional hypothesis for the use of multiple signals and, more generally, show that bacteria are capable of combinatorial communication.diffusion sensing | bacterial signaling | efficiency sensing | collective behavior | bacterial cooperation

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Strategies for cellular decision‐making

Cited by 303 publications

References 103 publications

Computational design of genomic transcriptional networks with adaptation to varying environments

Computational design of genomic transcriptional networks with adaptation to varying environments

Intraspecific facilitation by allelochemical mediated grazing protection within a toxigenic dinoflagellate population

Combinatorial quorum sensing allows bacteria to resolve their social and physical environment

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