A Brauner

A Harms

A Solopova

AM Adiciptaningrum

AW Covert

BR Levin

C Pál

D Weinreich

D Weissman

DB Kearns

DM Weinreich

DT Gillespie

E Drenkard

E Kussell

EBM Breidenstein

EM Ozbudak

FD Klironomos

FJ Poelwijk

FK Balagaddé

H Hasman

H Lee

H Maamar

HJE Beaumont

I Kronholm

IG Szendro

J Bos

J Franke

JAGM Visser de

JL Geoghegan

JW Drake

K Kemper

LL Marcusson

M Ackermann

M Kirkpatrick

MJ Kerner

MW Woude van der

N Cohen

N Dhar

NQ Balaban

OG McDonald

P Patra

PD Sniegowski

Q Zhang

R Korona

RT Cirz

S Maisnier-Patin

SF Elena

SH Gillespie

SJ Schrag

Sumedha

T Day

Y Wakamoto

Z Yao

Scientific Reports

AbstractStochastic phenotype switching has been suggested to play a beneficial role in microbial populations by leading to the division of labour among cells, or ensuring that at least some of the population survives an unexpected change in environmental conditions. Here we use a computational model to investigate an alternative possible function of stochastic phenotype switching: as a way to adapt more quickly even in a static environment. We show that when a genetic mutation causes a population to become less fit, switching to an alternative phenotype with higher fitness (growth rate) may give the population enough time to develop compensatory mutations that increase the fitness again. The possibility of switching phenotypes can reduce the time to adaptation by orders of magnitude if the “fitness valley” caused by the deleterious mutation is deep enough. Our work has important implications for the emergence of antibiotic-resistant bacteria. In line with recent experimental findings, we hypothesise that switching to a slower growing — but less sensitive — phenotype helps bacteria to develop resistance by providing alternative, faster evolutionary routes to resistance.</jats:p

Andrew C. Tadrowski

Martin R. Evans

Bartlomiej Waclaw

Crossref

Phenotypic Switching Can Speed up Microbial Evolution

Stochastic phenotype switching has been suggested to play a beneficial role in microbial populations by leading to the division of labour among cells, or ensuring that at least some of the population survives an unexpected change in environmental conditions. Here we use a computational model to investigate an alternative possible function of stochastic phenotype switching - as a way to adapt more quickly even in a static environment. We show that when a genetic mutation causes a population to become less fit, switching to an alternative phenotype with higher fitness (growth rate) may give the population enough time to develop compensatory mutations that increase the fitness again. The possibility of switching phenotypes can reduce the time to adaptation by orders of magnitude if the "fitness valley" caused by the deleterious mutation is deep enough. Our work has important implications for the emergence of antibiotic-resistant bacteria. In line with recent experimental findings we hypothesise that switching to a slower growing but less sensitive phenotype helps bacteria to develop resistance by exploring a larger set of beneficial mutations while avoiding deleterious ones

Tadrowski, Andrew C.

Evans, Martin R.

Waclaw, Bartlomiej

Edinburgh Research Explorer

https://www.pure.ed.ac.uk/ws/files/57219707/1601.04600v2.pdf

Phenotypic Switching Can Speed up Microbial Evolution

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