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Optimality and thermodynamics determine the evolution of transcriptional regulatory networks.

ABSTRACT: Transcriptional motifs are small regulatory interaction patterns that regulate biological functions in highly-interacting cellular networks. Recently, attempts have been made to explain the significance of transcriptional motifs through dynamic function. However, fundamental questions remain unanswered. Why are certain transcriptional motifs with similar dynamic function abundant while others occur rarely? What are the criteria for topological generalization of these motifs into complex networks? Here, we present a novel paradigm that combines non-equilibrium thermodynamics with multiobjective-optimality for network analysis. We found that energetic cost, defined herein as specific dissipation energy, is minimal at the optimal environmental conditions and it correlates inversely with the abundance of the network motifs obtained experimentally for E. coli and S. cerevisiae. This yields evidence that dissipative energetics is the underlying criteria used during evolution for motif selection and that biological systems during transcription tend towards evolutionary selection of subgraphs which produces minimum specific heat dissipation under optimal conditions, thereby explaining the abundance/rare occurrence of some motifs. We show that although certain motifs had similar dynamical functionality, they had significantly different energetic cost, thus explaining the abundance/rare occurrence of these motifs. The presented insights may establish global thermodynamic analysis as a backbone in designing and understanding complex networks systems, such as metabolic and protein interaction networks.

SUBMITTER: Avila-Elchiver M

PROVIDER: S-EPMC3964374 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Optimality and thermodynamics determine the evolution of transcriptional regulatory networks.

Avila-Elchiver Marco M Nagrath Deepak D Yarmush Martin L ML

Molecular bioSystems 20111110 2

Transcriptional motifs are small regulatory interaction patterns that regulate biological functions in highly-interacting cellular networks. Recently, attempts have been made to explain the significance of transcriptional motifs through dynamic function. However, fundamental questions remain unanswered. Why are certain transcriptional motifs with similar dynamic function abundant while others occur rarely? What are the criteria for topological generalization of these motifs into complex networks ...[more]

PMID: 22076617

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Project description:Organisms regulate gene expression in response to the environment to coordinate metabolic reactions. Clostridium thermocellum expresses enzymes for both lignocellulose solubilization and its fermentation to produce ethanol. One LacI regulator termed GlyR3 in C. thermocellum ATCC 27405 was previously identified as a repressor of neighboring genes with repression relieved by laminaribiose (a ?-1,3 disaccharide). To better understand the three C. thermocellum LacI regulons, deletion mutants were constructed using the genetically tractable DSM1313 strain. DSM1313 lacI genes Clo1313_2023, Clo1313_0089, and Clo1313_0396 encode homologs of GlyR1, GlyR2, and GlyR3 from strain ATCC 27405, respectively. Growth on cellobiose or pretreated switchgrass was unaffected by any of the gene deletions under controlled-pH fermentations. Global gene expression patterns from time course analyses identified glycoside hydrolase genes encoding hemicellulases, including cellulosomal enzymes, that were highly upregulated (5- to 100-fold) in the absence of each LacI regulator, suggesting that these were repressed under wild-type conditions and that relatively few genes were controlled by each regulator under the conditions tested. Clo1313_2022, encoding lichenase enzyme LicB, was derepressed in a ?glyR1 strain. Higher expression of Clo1313_1398, which encodes the Man5A mannanase, was observed in a ?glyR2 strain, and ?-mannobiose was identified as a probable inducer for GlyR2-regulated genes. For the ?glyR3 strain, upregulation of the two genes adjacent to glyR3 in the celC-glyR3-licA operon was consistent with earlier studies. Electrophoretic mobility shift assays have confirmed LacI transcription factor binding to specific regions of gene promoters.IMPORTANCE Understanding C. thermocellum gene regulation is of importance for improved fundamental knowledge of this industrially relevant bacterium. Most LacI transcription factors regulate local genomic regions; however, a small number of those genes encode global regulatory proteins with extensive regulons. This study indicates that there are small specific C. thermocellum LacI regulons. The identification of LacI repressor activity for hemicellulase gene expression is a key result of this work and will add to the small body of existing literature on the area of gene regulation in C. thermocellum.

Project description:BackgroundComparative genomics methods enable the reconstruction of bacterial regulatory networks using available experimental data. In spite of their potential for accelerating research into the composition and evolution of bacterial regulons, few comparative genomics suites have been developed for the automated analysis of these regulatory systems. Available solutions typically rely on precomputed databases for operon and ortholog predictions, limiting the scope of analyses to processed complete genomes, and several key issues such as the transfer of experimental information or the integration of regulatory information in a probabilistic setting remain largely unaddressed.ResultsHere we introduce CGB, a flexible platform for comparative genomics of prokaryotic regulons. CGB has few external dependencies and enables fully customized analyses of newly available genome data. The platform automates the merging of experimental information and uses a gene-centered, Bayesian framework to generate and integrate easily interpretable results. We demonstrate its flexibility and power by analyzing the evolution of type III secretion system regulation in pathogenic Proteobacteria and by characterizing the SOS regulon of a new bacterial phylum, the Balneolaeota.ConclusionsOur results demonstrate the applicability of the CGB pipeline in multiple settings. CGB's ability to automatically integrate experimental information from multiple sources and use complete and draft genomic data, coupled with its non-reliance on precomputed databases and its easily interpretable display of gene-centered posterior probabilities of regulation provide users with an unprecedented level of flexibility in launching comparative genomics analyses of prokaryotic transcriptional regulatory networks. The analyses of type III secretion and SOS response regulatory networks illustrate instances of convergent and divergent evolution of these regulatory systems, showcasing the power of formal ancestral state reconstruction at inferring the evolutionary history of regulatory networks.

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Optimality and thermodynamics determine the evolution of transcriptional regulatory networks.

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Optimality and thermodynamics determine the evolution of transcriptional regulatory networks.

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