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      A Model for Sigma Factor Competition in Bacterial Cells

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      PLoS Computational Biology
      Public Library of Science

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          Abstract

          Sigma factors control global switches of the genetic expression program in bacteria. Different sigma factors compete for binding to a limited pool of RNA polymerase (RNAP) core enzymes, providing a mechanism for cross-talk between genes or gene classes via the sharing of expression machinery. To analyze the contribution of sigma factor competition to global changes in gene expression, we develop a theoretical model that describes binding between sigma factors and core RNAP, transcription, non-specific binding to DNA and the modulation of the availability of the molecular components. The model is validated by comparison with in vitro competition experiments, with which excellent agreement is found. Transcription is affected via the modulation of the concentrations of the different types of holoenzymes, so saturated promoters are only weakly affected by sigma factor competition. However, in case of overlapping promoters or promoters recognized by two types of sigma factors, we find that even saturated promoters are strongly affected. Active transcription effectively lowers the affinity between the sigma factor driving it and the core RNAP, resulting in complex cross-talk effects. Sigma factor competition is not strongly affected by non-specific binding of core RNAPs, sigma factors and holoenzymes to DNA. Finally, we analyze the role of increased core RNAP availability upon the shut-down of ribosomal RNA transcription during the stringent response. We find that passive up-regulation of alternative sigma-dependent transcription is not only possible, but also displays hypersensitivity based on the sigma factor competition. Our theoretical analysis thus provides support for a significant role of passive control during that global switch of the gene expression program.

          Author Summary

          Bacteria respond to changing environmental conditions by switching the global pattern of expressed genes. A key mechanism for global switches of the transcriptional program depends on alternative sigma factors that bind the RNA polymerase core enzyme and direct it towards the appropriate stress response genes. Competition of different sigma factors for a limited amount of RNA polymerase is believed to play a central role in this global switch. Here, a theoretical approach is used towards a quantitative understanding of sigma factor competition and its effects on gene expression. The model is used to quantitatively describe in vitro competition assays and to address the question of indirect or passive control in the stringent response upon amino acids starvation. We show that sigma factor competition provides a mechanism for a passive up-regulation of the stress specific sigma-driven genes due to the increased availability of RNA polymerase in the stringent response. Moreover, we find that active separation of sigma factor from the RNA polymerase during early transcript elongation weakens the sigma factor-RNA polymerase equilibrium constant, raising the question of how their in vitro measure is relevant in the cell.

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          Most cited references66

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          (p)ppGpp: still magical?

          The fundamental details of how nutritional stress leads to elevating (p)ppGpp are questionable. By common usage, the meaning of the stringent response has evolved from the specific response to (p)ppGpp provoked by amino acid starvation to all responses caused by elevating (p)ppGpp by any means. Different responses have similar as well as dissimilar positive and negative effects on gene expression and metabolism. The different ways that different bacteria seem to exploit their capacities to form and respond to (p)ppGpp are already impressive despite an early stage of discovery. Apparently, (p)ppGpp can contribute to regulation of many aspects of microbial cell biology that are sensitive to changing nutrient availability: growth, adaptation, secondary metabolism, survival, persistence, cell division, motility, biofilms, development, competence, and virulence. Many basic questions still exist. This review tries to focus on some issues that linger even for the most widely characterized bacterial strains.
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            Transcriptional regulation by the numbers: models.

            The expression of genes is regularly characterized with respect to how much, how fast, when and where. Such quantitative data demands quantitative models. Thermodynamic models are based on the assumption that the level of gene expression is proportional to the equilibrium probability that RNA polymerase (RNAP) is bound to the promoter of interest. Statistical mechanics provides a framework for computing these probabilities. Within this framework, interactions of activators, repressors, helper molecules and RNAP are described by a single function, the "regulation factor". This analysis culminates in an expression for the probability of RNA polymerase binding at the promoter of interest as a function of the number of regulatory proteins in the cell.
              • Record: found
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              RNA polymerase is poised for activation across the genome.

              Regulation of gene expression is integral to the development and survival of all organisms. Transcription begins with the assembly of a pre-initiation complex at the gene promoter, followed by initiation of RNA synthesis and the transition to productive elongation. In many cases, recruitment of RNA polymerase II (Pol II) to a promoter is necessary and sufficient for activation of genes. However, there are a few notable exceptions to this paradigm, including heat shock genes and several proto-oncogenes, whose expression is attenuated by regulated stalling of polymerase elongation within the promoter-proximal region. To determine the importance of polymerase stalling for transcription regulation, we carried out a genome-wide search for Drosophila melanogaster genes with Pol II stalled within the promoter-proximal region. Our data show that stalling is widespread, occurring at hundreds of genes that respond to stimuli and developmental signals. This finding indicates a role for regulation of polymerase elongation in the transcriptional responses to dynamic environmental and developmental cues.

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                October 2014
                9 October 2014
                : 10
                : 10
                : e1003845
                Affiliations
                [1]Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
                University of Illinois at Urbana-Champaign, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Wrote the paper: MM SK. Conceived and designed the study: MM SK. Performed theoretical analysis: MM.

                Article
                PCOMPBIOL-D-14-00627
                10.1371/journal.pcbi.1003845
                4191881
                25299042
                5f08dfa4-ed69-4cf7-acc9-207ec98ad8f2
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 April 2014
                : 4 August 2014
                Page count
                Pages: 16
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Cell Biology
                Cell Processes
                Cellular Stress Responses
                Computational Biology
                Gene Regulatory Networks
                Genetics
                Gene Expression
                Gene Regulation
                Systems Biology
                Computer and Information Sciences
                Systems Science
                Physical Sciences
                Mathematics
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.

                Quantitative & Systems biology
                Quantitative & Systems biology

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