
Systematic bacterialization of yeast genes identifies a near-universally swappable pathway
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Abstract
Eukaryotes and prokaryotes last shared a common ancestor ~2 billion years ago, and while many present-day genes in these lineages predate this divergence, the extent to which these genes still perform their ancestral functions is largely unknown. To test principles governing retention of ancient function, we asked if prokaryotic genes could replace their essential eukaryotic orthologs. We systematically replaced essential genes in yeast by their 1:1 orthologs from Escherichia coli. After accounting for mitochondrial localization and alternative start codons, 31 out of 51 bacterial genes tested (61%) could complement a lethal growth defect and replace their yeast orthologs with minimal effects on growth rate. Replaceability was determined on a pathway-by-pathway basis; codon usage, abundance, and sequence similarity contributed predictive power. The heme biosynthesis pathway was particularly amenable to inter-kingdom exchange, with each yeast enzyme replaceable by its bacterial, human, or plant ortholog, suggesting it as a near-universally swappable pathway.
Article and author information
Author details
Funding
National Institutes of Health
- Edward Michael Marcotte
Cancer Prevention and Research Institute of Texas
- Edward Michael Marcotte
Welch Foundation (F1515)
- Edward Michael Marcotte
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Naama Barkai, Weizmann Institute of Science, Israel
Publication history
- Received: January 12, 2017
- Accepted: June 26, 2017
- Accepted Manuscript published: June 29, 2017 (version 1)
- Accepted Manuscript updated: June 30, 2017 (version 2)
- Version of Record published: July 31, 2017 (version 3)
- Version of Record updated: August 4, 2017 (version 4)
- Version of Record updated: April 6, 2018 (version 5)
Copyright
© 2017, Kachroo et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Computational and Systems Biology
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- Computational and Systems Biology
- Microbiology and Infectious Disease