Inherent regulatory asymmetry emanating from network architecture in a prevalent autoregulatory motif

  1. Md Zulfikar Ali
  2. Vinuselvi Parisutham
  3. Sandeep Choubey
  4. Robert C Brewster  Is a corresponding author
  1. University of Massachusetts Medical School, United States
  2. Max Planck Institute for the Physics of Complex Systems, Germany

Abstract

Predicting gene expression from DNA sequence remains a major goal in the field of gene regulation. A challenge to this goal is the connectivity of the network, whose role in altering gene expression remains unclear. Here, we study a common autoregulatory network motif, the negative single-input module, to explore the regulatory properties inherited from the motif. Using stochastic simulations and a synthetic biology approach in E. coli, we find that the TF gene and its target genes have inherent asymmetry in regulation, even when their promoters are identical; the TF gene being more repressed than its targets. The magnitude of asymmetry depends on network features such as network size and TF binding affinities. Intriguingly, asymmetry disappears when the growth rate is too fast or too slow and is most significant for typical growth conditions. These results highlight the importance of accounting for network architecture in quantitative models of gene expression.

Data availability

Data was deposited to the Image Data Resource (https://idr.openmicroscopy.org) under accession number idr0095. Code used to generate figures and simulation code is available on github at https://github.com/zulfikgp/Autoregulation.

The following data sets were generated

Article and author information

Author details

  1. Md Zulfikar Ali

    Program in Systems Biology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7054-0059
  2. Vinuselvi Parisutham

    Program in Systems Biology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0349-4072
  3. Sandeep Choubey

    Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7387-6148
  4. Robert C Brewster

    Program in Systems Biology, University of Massachusetts Medical School, Worcester, United States
    For correspondence
    Robert.brewster@umassmed.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7656-4086

Funding

National Institute of General Medical Sciences (R35GM128797)

  • Md Zulfikar Ali
  • Vinuselvi Parisutham
  • Robert C Brewster

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Sandeep Krishna, National Centre for Biological Sciences­‐Tata Institute of Fundamental Research, India

Version history

  1. Received: March 1, 2020
  2. Accepted: August 7, 2020
  3. Accepted Manuscript published: August 18, 2020 (version 1)
  4. Version of Record published: September 21, 2020 (version 2)

Copyright

© 2020, Ali et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Md Zulfikar Ali
  2. Vinuselvi Parisutham
  3. Sandeep Choubey
  4. Robert C Brewster
(2020)
Inherent regulatory asymmetry emanating from network architecture in a prevalent autoregulatory motif
eLife 9:e56517.
https://doi.org/10.7554/eLife.56517

Share this article

https://doi.org/10.7554/eLife.56517

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