Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Theoretical Design of Paradoxical Signaling-Based Synthetic Population Control Circuit in E. coli

View ORCID ProfileMichaëlle N. Mayalu, Richard M. Murray
doi: https://doi.org/10.1101/2020.01.27.921734
Michaëlle N. Mayalu
1Department of Computing and Mathematical Sciences, California Institute of Technology, 1200 E California Blvd, Pasadena, CA, 91125
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Michaëlle N. Mayalu
  • For correspondence: mmayalu@caltech.edu
Richard M. Murray
1Department of Computing and Mathematical Sciences, California Institute of Technology, 1200 E California Blvd, Pasadena, CA, 91125
2Division of Biology and Biological Engineering, California Institute of Technology, 1200 E California Blvd, Pasadena, CA, 91125
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Summary

We have developed a mathematical framework to analyze the cooperative control of cell population homeostasis via paradoxical signaling in synthetic contexts. Paradoxical signaling functions through quorum sensing (where cells produce and release a chemical signal as a function of cell density). Precisely, the same quorum sensing signal provides both positive (proliferation) and negative (death) feedback in different signal concentration regimes. As a consequence, the relationship between intercellular quorum sensing signal concentration and net growth rate (cell proliferation minus death rates) can be non-monotonic. This relationship is a condition for robustness to certain cell mutational overgrowths and allows for increased stability in the presence of environmental perturbations. Here, we explore stability and robustness of a conceptualized synthetic circuit. Furthermore, we asses possible design principles that could exist among a subset of paradoxical circuit implementations. This analysis sparks the development a bio-molecular control theory to identify ideal underlying characteristics for paradoxical signaling control systems.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
Back to top
PreviousNext
Posted January 28, 2020.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Theoretical Design of Paradoxical Signaling-Based Synthetic Population Control Circuit in E. coli
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Theoretical Design of Paradoxical Signaling-Based Synthetic Population Control Circuit in E. coli
Michaëlle N. Mayalu, Richard M. Murray
bioRxiv 2020.01.27.921734; doi: https://doi.org/10.1101/2020.01.27.921734
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Theoretical Design of Paradoxical Signaling-Based Synthetic Population Control Circuit in E. coli
Michaëlle N. Mayalu, Richard M. Murray
bioRxiv 2020.01.27.921734; doi: https://doi.org/10.1101/2020.01.27.921734

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Systems Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (3502)
  • Biochemistry (7343)
  • Bioengineering (5319)
  • Bioinformatics (20258)
  • Biophysics (10008)
  • Cancer Biology (7735)
  • Cell Biology (11293)
  • Clinical Trials (138)
  • Developmental Biology (6434)
  • Ecology (9947)
  • Epidemiology (2065)
  • Evolutionary Biology (13315)
  • Genetics (9359)
  • Genomics (12579)
  • Immunology (7696)
  • Microbiology (19008)
  • Molecular Biology (7437)
  • Neuroscience (41011)
  • Paleontology (300)
  • Pathology (1228)
  • Pharmacology and Toxicology (2134)
  • Physiology (3155)
  • Plant Biology (6858)
  • Scientific Communication and Education (1272)
  • Synthetic Biology (1895)
  • Systems Biology (5311)
  • Zoology (1087)