Mistranslation can promote the exploration of alternative evolutionary trajectories in enzyme evolution

Zheng, Jia; Bratulic, Sinisa; Lischer, Heidi E. L.; Wagner, Andreas (2021). Mistranslation can promote the exploration of alternative evolutionary trajectories in enzyme evolution. Journal of evolutionary biology, 34(8), pp. 1302-1315. Wiley 10.1111/jeb.13892

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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.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Biology > Bioinformatics and Computational Biology > Bioinformatics
08 Faculty of Science > Department of Biology > Bioinformatics and Computational Biology > Computational Biology
08 Faculty of Science > Department of Biology > Bioinformatics and Computational Biology

UniBE Contributor:

Tschanz-Lischer, Heidi Erika Lisa

Subjects:

500 Science > 570 Life sciences; biology

ISSN:

1420-9101

Publisher:

Wiley

Language:

English

Submitter:

Jolanda Paganoni Zurbrügg

Date Deposited:

11 May 2023 14:43

Last Modified:

11 May 2023 14:53

Publisher DOI:

10.1111/jeb.13892

PubMed ID:

34145657

BORIS DOI:

10.48350/182467

URI:

https://boris.unibe.ch/id/eprint/182467

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