Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis

Title: Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
Author(s): Skwark, MJ
Croucher, NJ
Puranen, S
Chewapreecha, C
Pesonen, M
Xu, YY
Turner, P
Harris, SR
Beres, SB
Musser, JM
Parkhill, J
Bentley, SD
Aurell, E
Corander, J
Item Type: Journal Article
Abstract: Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein-protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work.
Publication Date: 16-Feb-2017
Date of Acceptance: 24-Nov-2016
URI: http://hdl.handle.net/10044/1/55487
DOI: https://dx.doi.org/10.1371/journal.pgen.1006508
ISSN: 1553-7390
Publisher: Public Library of Science (PLoS)
Journal / Book Title: PLoS Genetics
Volume: 13
Issue: 2
Copyright Statement: © 2017 Skwark et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Sponsor/Funder: Medical Research Council (MRC)
Funder's Grant Number: MR/K010174/1B
Keywords: Science & Technology
Life Sciences & Biomedicine
Genetics & Heredity
DIRECT-COUPLING ANALYSIS
STREPTOCOCCUS-PNEUMONIAE
PENICILLIN RESISTANCE
STATISTICAL-METHODS
CONTACT PREDICTION
RESIDUE CONTACTS
EVOLUTION
PROTEINS
ASSOCIATION
COEVOLUTION
Aminoacyltransferases
Anti-Bacterial Agents
Bacterial Proteins
Epistasis, Genetic
Gene Regulatory Networks
Genetics, Population
Genome, Bacterial
Genomics
Genotype
Humans
Microbial Sensitivity Tests
Penicillin-Binding Proteins
Peptidyl Transferases
Selection, Genetic
Streptococcus pneumoniae
Streptococcus pyogenes
beta-Lactam Resistance
beta-Lactams
Humans
Streptococcus pneumoniae
Streptococcus pyogenes
beta-Lactams
Penicillin-Binding Proteins
Aminoacyltransferases
Peptidyl Transferases
Bacterial Proteins
Anti-Bacterial Agents
Microbial Sensitivity Tests
Genetics, Population
Genomics
beta-Lactam Resistance
Epistasis, Genetic
Genotype
Genome, Bacterial
Gene Regulatory Networks
Selection, Genetic
Science & Technology
Life Sciences & Biomedicine
Genetics & Heredity
DIRECT-COUPLING ANALYSIS
STREPTOCOCCUS-PNEUMONIAE
PENICILLIN RESISTANCE
STATISTICAL-METHODS
CONTACT PREDICTION
RESIDUE CONTACTS
EVOLUTION
PROTEINS
ASSOCIATION
COEVOLUTION
0604 Genetics
Developmental Biology
Publication Status: Published
Article Number: ARTN e1006508
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care



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