Mutability of demographic noise in microbial range expansions

Qinqin Yu, Matti Gralka, Marie-Cécilia Duvernoy, Megan Sousa, Arbel Harpak, Oskar Hallatschek*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Demographic noise, the change in the composition of a population due to random birth and death events, is an important driving force in evolution because it reduces the efficacy of natural selection. Demographic noise is typically thought to be set by the population size and the environment, but recent experiments with microbial range expansions have revealed substantial strain-level differences in demographic noise under the same growth conditions. Many genetic and phenotypic differences exist between strains; to what extent do single mutations change the strength of demographic noise? To investigate this question, we developed a high-throughput method for measuring demographic noise in colonies without the need for genetic manipulation. By applying this method to 191 randomly-selected single gene deletion strains from the E. coli Keio collection, we find that a typical single gene deletion mutation decreases demographic noise by 8% (maximal decrease: 81%). We find that the strength of demographic noise is an emergent trait at the population level that can be predicted by colony-level traits but not cell-level traits. The observed differences in demographic noise from single gene deletions can increase the establishment probability of beneficial mutations by almost an order of magnitude (compared to in the wild type). Our results show that single mutations can substantially alter adaptation through their effects on demographic noise and suggest that demographic noise can be an evolvable trait of a population.
Original languageEnglish
Pages (from-to)2643-2654
Number of pages12
JournalThe ISME Journal
Volume15
Issue number9
Early online date21 Mar 2021
DOIs
Publication statusPublished - Sept 2021
Externally publishedYes

Funding

FundersFunder number
National Science Foundation1106400, 1555330
Simons Foundation633313, 327934
National Institute of General Medical SciencesR01GM115851

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