Author
Listed:
- Morgan N. Price
(Lawrence Berkeley National Laboratory)
- Kelly M. Wetmore
(Lawrence Berkeley National Laboratory)
- R. Jordan Waters
(Lawrence Berkeley National Laboratory)
- Mark Callaghan
(Lawrence Berkeley National Laboratory)
- Jayashree Ray
(Lawrence Berkeley National Laboratory)
- Hualan Liu
(Lawrence Berkeley National Laboratory)
- Jennifer V. Kuehl
(Lawrence Berkeley National Laboratory)
- Ryan A. Melnyk
(Lawrence Berkeley National Laboratory)
- Jacob S. Lamson
(Lawrence Berkeley National Laboratory)
- Yumi Suh
(Lawrence Berkeley National Laboratory)
- Hans K. Carlson
(Lawrence Berkeley National Laboratory)
- Zuelma Esquivel
(Lawrence Berkeley National Laboratory)
- Harini Sadeeshkumar
(Lawrence Berkeley National Laboratory)
- Romy Chakraborty
(Lawrence Berkeley National Laboratory)
- Grant M. Zane
(University of Missouri)
- Benjamin E. Rubin
(University of California)
- Judy D. Wall
(University of Missouri)
- Axel Visel
(Lawrence Berkeley National Laboratory
University of California)
- James Bristow
(Lawrence Berkeley National Laboratory)
- Matthew J. Blow
(Lawrence Berkeley National Laboratory)
- Adam P. Arkin
(Lawrence Berkeley National Laboratory
University of California)
- Adam M. Deutschbauer
(Lawrence Berkeley National Laboratory
University of California)
Abstract
One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because they are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.
Suggested Citation
Morgan N. Price & Kelly M. Wetmore & R. Jordan Waters & Mark Callaghan & Jayashree Ray & Hualan Liu & Jennifer V. Kuehl & Ryan A. Melnyk & Jacob S. Lamson & Yumi Suh & Hans K. Carlson & Zuelma Esquive, 2018.
"Mutant phenotypes for thousands of bacterial genes of unknown function,"
Nature, Nature, vol. 557(7706), pages 503-509, May.
Handle:
RePEc:nat:nature:v:557:y:2018:i:7706:d:10.1038_s41586-018-0124-0
DOI: 10.1038/s41586-018-0124-0
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Citations
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Cited by:
- Daniel P. G. H. Wong & Benjamin H. Good, 2024.
"Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking,"
Nature Communications, Nature, vol. 15(1), pages 1-14, December.
- Joao A. Ascensao & Kelly M. Wetmore & Benjamin H. Good & Adam P. Arkin & Oskar Hallatschek, 2023.
"Quantifying the local adaptive landscape of a nascent bacterial community,"
Nature Communications, Nature, vol. 14(1), pages 1-19, December.
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