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Nat Microbiol. 2019 Feb;4(2):328-338. doi: 10.1038/s41564-018-0309-1. Epub 2018 Dec 3.

Genome-wide discovery of epistatic loci affecting antibiotic resistance in Neisseria gonorrhoeae using evolutionary couplings.

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Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
Department of Cell Biology, Harvard Medical School, Boston, MA, USA.
cBio Center, Dana-Farber Cancer Institute, Boston, MA, USA.
Department of Biological Sciences, Old Dominion University, Norfolk, VA, USA.
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA.
Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
Broad Institute of Harvard and MIT, Cambridge, MA, USA.


Genome analysis should allow the discovery of interdependent loci that together cause antibiotic resistance. In practice, however, the vast number of possible epistatic interactions erodes statistical power. Here, we extend an approach that has been successfully used to identify epistatic residues in proteins to infer genomic loci that are strongly coupled. This approach reduces the number of tests required for an epistatic genome-wide association study of antibiotic resistance and increases the likelihood of identifying causal epistasis. We discovered 38 loci and 240 epistatic pairs that influence the minimum inhibitory concentrations of 5 different antibiotics in 1,102 isolates of Neisseria gonorrhoeae that were confirmed in a second dataset of 495 isolates. Many known resistance-affecting loci were recovered; however, the majority of associations occurred in unreported genes, such as murE. About half of the discovered epistasis involved at least one locus previously associated with antibiotic resistance, including interactions between gyrA and parC. Still, many combinations involved unreported loci and genes. While most variation in minimum inhibitory concentrations could be explained by identified loci, epistasis substantially increased explained phenotypic variance. Our work provides a systematic identification of epistasis affecting antibiotic resistance in N. gonorrhoeae and a generalizable approach for epistatic genome-wide association studies.

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