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The evolution of MarR family transcription factors as counter-silencers in regulatory networks.

ABSTRACT: Gene duplication facilitates the evolution of biological complexity, as one copy of a gene retains its original function while a duplicate copy can acquire mutations that would otherwise diminish fitness. Duplication has played a particularly important role in the evolution of regulatory networks by permitting novel regulatory interactions and responses to stimuli. The diverse MarR family of transcription factors (MFTFs) illustrate this concept, ranging from highly specific repressors of single operons to pleiotropic global regulators controlling hundreds of genes. MFTFs are often genetically and functionally linked to antimicrobial efflux systems. However, the SlyA MFTF lineage in the Enterobacteriaceae plays little or no role in regulating efflux but rather functions as transcriptional counter-silencers, which alleviate xenogeneic silencing of horizontally acquired genes and facilitate bacterial evolution by horizontal gene transfer. This review will explore recent advances in our understanding of MFTF traits that have contributed to their functional evolution.

SUBMITTER: Will WR

PROVIDER: S-EPMC7311280 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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The evolution of MarR family transcription factors as counter-silencers in regulatory networks.

Will William Ryan WR Fang Ferric C FC

Current opinion in microbiology 20200207

Gene duplication facilitates the evolution of biological complexity, as one copy of a gene retains its original function while a duplicate copy can acquire mutations that would otherwise diminish fitness. Duplication has played a particularly important role in the evolution of regulatory networks by permitting novel regulatory interactions and responses to stimuli. The diverse MarR family of transcription factors (MFTFs) illustrate this concept, ranging from highly specific repressors of single ...[more]

PMID: 32044654

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Project description:BackgroundTranscription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes.ResultsBy computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks.ConclusionwTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function.

Project description:DNA-binding transcription factors (TFs) are essential components of transcriptional regulatory networks in bacteria. LacI-family TFs (LacI-TFs) are broadly distributed among certain lineages of bacteria. The majority of characterized LacI-TFs sense sugar effectors and regulate carbohydrate utilization genes. The comparative genomics approaches enable in silico identification of TF-binding sites and regulon reconstruction. To study the function and evolution of LacI-TFs, we performed genomics-based reconstruction and comparative analysis of their regulons. For over 1300 LacI-TFs from over 270 bacterial genomes, we predicted their cognate DNA-binding motifs and identified target genes. Using the genome context and metabolic subsystem analyses of reconstructed regulons, we tentatively assigned functional roles and predicted candidate effectors for 78 and 67% of the analyzed LacI-TFs, respectively. Nearly 90% of the studied LacI-TFs are local regulators of sugar utilization pathways, whereas the remaining 125 global regulators control large and diverse sets of metabolic genes. The global LacI-TFs include the previously known regulators CcpA in Firmicutes, FruR in Enterobacteria, and PurR in Gammaproteobacteria, as well as the three novel regulators-GluR, GapR, and PckR-that are predicted to control the central carbohydrate metabolism in three lineages of Alphaproteobacteria. Phylogenetic analysis of regulators combined with the reconstructed regulons provides a model of evolutionary diversification of the LacI protein family. The obtained genomic collection of in silico reconstructed LacI-TF regulons in bacteria is available in the RegPrecise database (http://regprecise.lbl.gov). It provides a framework for future structural and functional classification of the LacI protein family and identification of molecular determinants of the DNA and ligand specificity. The inferred regulons can be also used for functional gene annotation and reconstruction of sugar catabolic networks in diverse bacterial lineages.

Dataset Information

The evolution of MarR family transcription factors as counter-silencers in regulatory networks.

Publications

The evolution of MarR family transcription factors as counter-silencers in regulatory networks.

Similar Datasets

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