Mistranslation can promote the exploration of alternative evolutionary trajectories in enzyme evolution
Journal article, 2021

Darwinian evolution preferentially follows mutational pathways whose individual steps increase fitness. Alternative pathways with mutational steps that do not increase fitness are less accessible. Here, we show that mistranslation, the erroneous incorporation of amino acids into nascent proteins, can increase the accessibility of such alternative pathways and, ultimately, of high fitness genotypes. We subject populations of the beta-lactamase TEM-1 to directed evolution in Escherichia coli under both low- and high-mistranslation rates, selecting for high activity on the antibiotic cefotaxime. Under low mistranslation rates, different evolving TEM-1 populations ascend the same high cefotaxime-resistance peak, which requires three canonical DNA mutations. In contrast, under high mistranslation rates they ascend three different high cefotaxime-resistance genotypes, which leads to higher genotypic diversity among populations. We experimentally reconstruct the adaptive DNA mutations and the potential evolutionary paths to these high cefotaxime-resistance genotypes. This reconstruction shows that some of the DNA mutations do not change fitness under low mistranslation, but cause a significant increase in fitness under high-mistranslation, which helps increase the accessibility of different high cefotaxime-resistance genotypes. In addition, these mutations form a network of pairwise epistatic interactions that leads to mutually exclusive evolutionary trajectories towards different high cefotaxime-resistance genotypes. Our observations demonstrate that protein mistranslation and the phenotypic mutations it causes can alter the evolutionary exploration of fitness landscapes and reduce the predictability of evolution.

mistranslation

phenotypic mutations

epistasis

genetic diversification

molecular evolution

Author

Jia Zheng

Swiss Institute of Bioinformatics

University of Zürich

Sinisa Bratulic

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Heidi E.L. Lischer

University of Bern

Swiss Institute of Bioinformatics

University of Zürich

Andreas Wagner

University of Zürich

Santa Fe Institute

Swiss Institute of Bioinformatics

Journal of Evolutionary Biology

1010-061X (ISSN) 1420-9101 (eISSN)

Vol. 34 8 1302-1315

Subject Categories

Evolutionary Biology

Other Basic Medicine

Microbiology

DOI

10.1111/jeb.13892

PubMed

34145657

More information

Latest update

4/5/2022 5