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Transcriptional Regulation by Competing Transcription Factor Modules

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  • Rutger Hermsen
  • Sander Tans
  • Pieter Rein ten Wolde

Abstract

Gene regulatory networks lie at the heart of cellular computation. In these networks, intracellular and extracellular signals are integrated by transcription factors, which control the expression of transcription units by binding to cis-regulatory regions on the DNA. The designs of both eukaryotic and prokaryotic cis-regulatory regions are usually highly complex. They frequently consist of both repetitive and overlapping transcription factor binding sites. To unravel the design principles of these promoter architectures, we have designed in silico prokaryotic transcriptional logic gates with predefined input–output relations using an evolutionary algorithm. The resulting cis-regulatory designs are often composed of modules that consist of tandem arrays of binding sites to which the transcription factors bind cooperatively. Moreover, these modules often overlap with each other, leading to competition between them. Our analysis thus identifies a new signal integration motif that is based upon the interplay between intramodular cooperativity and intermodular competition. We show that this signal integration mechanism drastically enhances the capacity of cis-regulatory domains to integrate signals. Our results provide a possible explanation for the complexity of promoter architectures and could be used for the rational design of synthetic gene circuits.Synopsis: Transcription regulatory networks are the central processing units of living cells. They allow cells to integrate different intracellular and extracellular signals to recognize patterns in, for instance, the food supply of the organism. The elementary calculations are performed at the cis-regulatory domains of genes, where transcription factors bind to the DNA to regulate the expression level of the genes. The logic of the computations that are performed depends upon the design of the cis-regulatory region. Not only in eukaryotic cells, but also in prokaryotic cells, the architectures of the cis-regulatory regions are often highly complex. They often contain long arrays of transcription factor binding sites. Moreover, the binding sites often overlap with one another. Hermsen, Tans, and ten Wolde discuss whether such complex architectures can be explained from the basic function of cis-regulatory regions to integrate signals. The authors combine a physicochemical model of prokaryotic transcription regulation with an evolutionary algorithm to design cis-regulatory constructs with predefined elementary functions. The resulting architectures make extensive use of repeating binding sites that are organized into cooperative modules. More surprisingly, these modules often overlap with each other, leading to competition between them. This interplay between intramodular cooperativity and intermodular competition is a powerful mechanism to achieve complex functionality, which may explain the daunting complexity of promoter architectures found in nature.

Suggested Citation

  • Rutger Hermsen & Sander Tans & Pieter Rein ten Wolde, 2006. "Transcriptional Regulation by Competing Transcription Factor Modules," PLOS Computational Biology, Public Library of Science, vol. 2(12), pages 1-9, December.
  • Handle: RePEc:plo:pcbi00:0020164
    DOI: 10.1371/journal.pcbi.0020164
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    Cited by:

    1. Amir Shahein & Maria López-Malo & Ivan Istomin & Evan J. Olson & Shiyu Cheng & Sebastian J. Maerkl, 2022. "Systematic analysis of low-affinity transcription factor binding site clusters in vitro and in vivo establishes their functional relevance," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    2. Rutger Hermsen & Bas Ursem & Pieter Rein ten Wolde, 2010. "Combinatorial Gene Regulation Using Auto-Regulation," PLOS Computational Biology, Public Library of Science, vol. 6(6), pages 1-13, June.
    3. Rutger Hermsen & David W Erickson & Terence Hwa, 2011. "Speed, Sensitivity, and Bistability in Auto-activating Signaling Circuits," PLOS Computational Biology, Public Library of Science, vol. 7(11), pages 1-9, November.

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