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Published November 2018 | Supplemental Material + Published + Submitted
Journal Article Open

Connecting the dots between mechanosensitive channel abundance, osmotic shock, and survival at single-cell resolution

Abstract

Rapid changes in extracellular osmolarity are one of many insults microbial cells face on a daily basis. To protect against such shocks, Escherichia coli and other microbes express several types of transmembrane channels that open and close in response to changes in membrane tension. In E. coli, one of the most abundant channels is the mechanosensitive channel of large conductance (MscL). While this channel has been heavily characterized through structural methods, electrophysiology, and theoretical modeling, our understanding of its physiological role in preventing cell death by alleviating high membrane tension remains tenuous. In this work, we examine the contribution of MscL alone to cell survival after osmotic shock at single-cell resolution using quantitative fluorescence microscopy. We conducted these experiments in an E. coli strain which is lacking all mechanosensitive channel genes save for MscL, whose expression was tuned across 3 orders of magnitude through modifications of the Shine-Dalgarno sequence. While theoretical models suggest that only a few MscL channels would be needed to alleviate even large changes in osmotic pressure, we find that between 500 and 700 channels per cell are needed to convey upwards of 80% survival. This number agrees with the average MscL copy number measured in wild-type E. coli cells through proteomic studies and quantitative Western blotting. Furthermore, we observed zero survival events in cells with fewer than ∼100 channels per cell. This work opens new questions concerning the contribution of other mechanosensitive channels to survival, as well as regulation of their activity.

Additional Information

© 2018 Chure et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license. Received 1 August 2018 Accepted 5 August 2018; Published online September 10, 2018. Data and software availability: All raw image data are freely available and are stored on the CaltechDATA Research Data Repository (47). The raw Markov chain Monte Carlo samples are stored as .csv files on CaltechDATA (48). All processed experimental data and Python and Stan code used in this work are freely available through our GitHub repository (http://github.com/rpgroup-pboc/mscl_survival) (49), accessible through https://doi.org/10.5281/zenodo.1252524. The scientific community is invited to fork our repository and open constructive issues. We thank Nathan Belliveau, Maja Bialecka-Fornal, Justin Bois, Soichi Hirokawa, Jaspar Landman, Manuel Razo-Mejia, Muir Morrison, and Shyam Saladi for useful advice and discussion. We thank Don Court for strain XTL298, as well as Samantha Miller and Ian Booth at the University of Aberdeen for strain MJF641. This work was supported by the National Institutes of Health grants number DP1 OD000217 (Director's Pioneer award), R01 GM085286, GM084211-A1, and GM118043-01 and by La Fondation Pierre Gilles de Gennes.

Attached Files

Published - e00460-18.full.pdf

Submitted - 1806.00897.pdf

Submitted - 339259.full.pdf

Supplemental Material - zjb999094913s1.pdf

Supplemental Material - zjb999094913sm1.avi

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Created:
September 22, 2023
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