Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs

Alaksh Choudhury (), Benoit Gachet, Zoya Dixit, Roland Faure, Ryan T. Gill and Olivier Tenaillon ()
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Alaksh Choudhury: Université de Paris Cité, INSERM, IAME, UMR 1137
Benoit Gachet: Université de Paris Cité, INSERM, IAME, UMR 1137
Zoya Dixit: Université de Paris Cité, INSERM, IAME, UMR 1137
Roland Faure: Université de Paris Cité, INSERM, IAME, UMR 1137
Ryan T. Gill: University of Colorado-Boulder
Olivier Tenaillon: Université de Paris Cité, INSERM, IAME, UMR 1137

Nature Communications, 2023, vol. 14, issue 1, 1-16

Abstract: Abstract RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.

Date: 2023
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DOI: 10.1038/s41467-023-41882-7

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