Experimental Evolution of Escherichia coli Harboring an Ancient Translation Protein

Abstract

The ability to design synthetic genes and engineer biological systems at the genome scale opens new means by which to characterize phenotypic states and the responses of biological systems to perturbations. One emerging method involves inserting artificial genes into bacterial genomes and examining how the genome and its new genes adapt to each other. Here we report the development and implementation of a modified approach to this method, in which phylogenetically inferred genes are inserted into a microbial genome, and laboratory evolution is then used to examine the adaptive potential of the resulting hybrid genome. Specifically, we engineered an approximately 700-million-year-old inferred ancestral variant of tufB, an essential gene encoding elongation factor Tu, and inserted it in a modern Escherichia coli genome in place of the native tufB gene. While the ancient homolog was not lethal to the cell, it did cause a twofold decrease in organismal fitness, mainly due to reduced protein dosage. We subsequently evolved replicate hybrid bacterial populations for 2000 generations in the laboratory and examined the adaptive response via fitness assays, whole genome sequencing, proteomics, and biochemical assays. Hybrid lineages exhibit a general adaptive strategy in which the fitness cost of the ancient gene was ameliorated in part by upregulation of protein production. Our results suggest that an ancient–modern recombinant method may pave the way for the synthesis of organisms that exhibit ancient phenotypes, and that laboratory evolution of these organisms may prove useful in elucidating insights into historical adaptive processes.

DOI: 10.1007/s00239-017-9781-0

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Cite this paper

@inproceedings{Kaar2017ExperimentalEO, title={Experimental Evolution of Escherichia coli Harboring an Ancient Translation Protein}, author={Bet{\"{u}l Kaçar and Xueliang Ge and Suparna Sanyal and Eric A. Gaucher}, booktitle={Journal of Molecular Evolution}, year={2017} }