Phenotypic diversity and temporal variability in a bacterial signaling network revealed by single-cell FRET
Abstract
We present in vivo single-cell FRET measurements in the Escherichia coli chemotaxis system that reveal pervasive signaling variability, both across cells in isogenic populations and within individual cells over time. We quantify cell-to-cell variability of adaptation, ligand response, as well as steady-state output level, and analyze the role of network design in shaping this diversity from gene expression noise. In the absence of changes in gene expression, we find that single cells demonstrate strong temporal fluctuations. We provide evidence that such signaling noise can arise from at least two sources: (i) stochastic activities of adaptation enzymes, and (ii) receptor-kinase dynamics in the absence of adaptation. We demonstrate that under certain conditions, (ii) can generate giant fluctuations that drive signaling activity of the entire cell into a stochastic two-state switching regime. Our findings underscore the importance of molecular noise, arising not only in gene expression but also in protein networks.
Article and author information
Author details
Funding
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO Vidi 680-47-515)
- Thomas S Shimizu
Stichting voor Fundamenteel Onderzoek der Materie (FOM Projectruimte 11PR2958)
- Thomas S Shimizu
Paul G. Allen Family Foundation (11562)
- Thierry Emonet
- Thomas S Shimizu
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Naama Barkai, Weizmann Institute of Science, Israel
Version history
- Received: April 4, 2017
- Accepted: November 17, 2017
- Accepted Manuscript published: December 12, 2017 (version 1)
- Accepted Manuscript updated: December 14, 2017 (version 2)
- Version of Record published: February 12, 2018 (version 3)
Copyright
© 2017, Keegstra 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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