Dataset Information

Detecting patterns of accessory genome coevolution in Staphylococcus aureus using data from thousands of genomes.

ABSTRACT: Bacterial genomes exhibit widespread horizontal gene transfer, resulting in highly variable genome content that complicates the inference of genetic interactions. In this study, we develop a method for detecting coevolving genes from large datasets of bacterial genomes based on pairwise comparisons of closely related individuals, analogous to a pedigree study in eukaryotic populations. We apply our method to pairs of genes from the Staphylococcus aureus accessory genome of over 75,000 annotated gene families using a database of over 40,000 whole genomes. We find many pairs of genes that appear to be gained or lost in a coordinated manner, as well as pairs where the gain of one gene is associated with the loss of the other. These pairs form networks of rapidly coevolving genes, primarily consisting of genes involved in virulence, mechanisms of horizontal gene transfer, and antibiotic resistance, particularly the SCCmec complex. While we focus on gene gain and loss, our method can also detect genes that tend to acquire substitutions in tandem, or genotype-phenotype or phenotype-phenotype coevolution. Finally, we present the R package DeCoTUR that allows for the computation of our method.

SUBMITTER: Mehta RS

PROVIDER: S-EPMC10251594 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Detecting patterns of accessory genome coevolution in Staphylococcus aureus using data from thousands of genomes.

Mehta Rohan S RS Petit Robert A RA Read Timothy D TD Weissman Daniel B DB

BMC bioinformatics 20230609 1

Bacterial genomes exhibit widespread horizontal gene transfer, resulting in highly variable genome content that complicates the inference of genetic interactions. In this study, we develop a method for detecting coevolving genes from large datasets of bacterial genomes based on pairwise comparisons of closely related individuals, analogous to a pedigree study in eukaryotic populations. We apply our method to pairs of genes from the Staphylococcus aureus accessory genome of over 75,000 annotated ...[more]

PMID: 37296404

Similar Datasets

Project description:Approximatively 75% of the genome of S. aureus (“core” genome) are highly conserved between strains, whereas the remaining 25% (“accessory” genome) are composed of variable regions that are mostly composed of mobile genetic elements (MGE), containing virulence and resistance genes. We have developed a composite DNA-microarray (StaphVar Array) which selectively targets 403 genes located on the accessory or core variable genome. Target genes encode antimicrobial resistance factors (35 %), virulence factors (28 %) and adhesins (31%). This microarray was validated with reference strains and used to characterize the genomic DNA of 13 community-acquired methicillin resistant S. aureus (CA-MRSA) strains representative of all the Multilocus Sequence Types (STs) described to date in Belgium. Analysis of gene content of 8 reference strains by the StaphVar Array matched 96 to 99% of the theoretical results. Analysis of CA-MRSA strains showed that 54.4 % of the genes tested were strain-dependent. Strains presented specific exotoxin, enterotoxin, cytolysin and adhesin gene profile by multi-locus sequence typing (MLST) lineage. One exception to these “lineage-specific” gene profile was the variable presence of the Arginin Catabolic Mobile Element (ACME, characteristic of the USA300 clone) within ST8 strains. In conclusion, this novel StaphVar array enables characterization of more than 400 variable resistance and virulence determinants in S. aureus strains. CA-MRSA strains from Belgium displayed extensive diversity in virulence and resistance profile. The presence of the USA 300 clone in our country was confirmed. Although mainly located on MGE, association of virulence genes were highly conserved within strains of the same MLST lineage. CGH microarray was performed on 13 epidemiologically distinct clinical isolates of methicillin resistant S. aureus. S. aureus labeled genomic DNA were hybridized to StaphVar arrays containing 1326 60mer oligonucleotide probes (Eurogentec, Belgium).

Project description:In principle, whole-genome sequencing (WGS) can predict phenotypic resistance directly from a genotype, replacing laboratory-based tests. However, the contribution of different bioinformatics methods to genotype-phenotype discrepancies has not been systematically explored to date. We compared three WGS-based bioinformatics methods (Genefinder [read based], Mykrobe [de Bruijn graph based], and Typewriter [BLAST based]) for predicting the presence/absence of 83 different resistance determinants and virulence genes and overall antimicrobial susceptibility in 1,379 Staphylococcus aureus isolates previously characterized by standard laboratory methods (disc diffusion, broth and/or agar dilution, and PCR). In total, 99.5% (113,830/114,457) of individual resistance-determinant/virulence gene predictions were identical between all three methods, with only 627 (0.5%) discordant predictions, demonstrating high overall agreement (Fleiss' kappa = 0.98, P < 0.0001). Discrepancies when identified were in only one of the three methods for all genes except the cassette recombinase, ccrC(b). The genotypic antimicrobial susceptibility prediction matched the laboratory phenotype in 98.3% (14,224/14,464) of cases (2,720 [18.8%] resistant, 11,504 [79.5%] susceptible). There was greater disagreement between the laboratory phenotypes and the combined genotypic predictions (97 [0.7%] phenotypically susceptible, but all bioinformatic methods reported resistance; 89 [0.6%] phenotypically resistant, but all bioinformatics methods reported susceptible) than within the three bioinformatics methods (54 [0.4%] cases, 16 phenotypically resistant, 38 phenotypically susceptible). However, in 36/54 (67%) cases, the consensus genotype matched the laboratory phenotype. In this study, the choice between these three specific bioinformatic methods to identify resistance determinants or other genes in S. aureus did not prove critical, with all demonstrating high concordance with each other and phenotypic/molecular methods. However, each has some limitations; therefore, consensus methods provide some assurance.

Project description:BackgroundStaphylococcus aureus (S. aureus) with accessory gene regulator (agr) dysfunction occurs in health care settings. This study evaluated the prevalence and the molecular and drug resistance characteristics of S. aureus with dysfunctional agr in a pediatric population in Beijing, China.ResultsA total of 269 nonduplicate S. aureus clinical isolates were isolated from Beijing Children's Hospital, including 211 methicillin-resistant S. aureus (MRSA) from September 2010-2017 and 58 methicillin-sensitive S. aureus (MSSA) from February 2016-2017. Only 8 MRSA and 2 MSSA isolates were identified as agr dysfunction, and the overall prevalence rate was 3.7%. For MRSA isolates, ST59-SCCmec IV and ST239-SCCmec III were the most common clones, and the prevalence rate of agr dysfunction in ST239-SCCmec III isolates (17.39%) was significantly higher than in ST59-SCCmec IV (1.69%) and other genotype strains (P = 0.006). Among the agr dysfunctional isolates, only one MRSA ST59 isolate and one MSSA ST22 isolate harbored pvl. No significant difference was detected between agr dysfunction and agr functional isolates regarding the biofilm formation ability (P = 0.4972); however, 9/10 agr dysfunctional isolates could effectuate strong biofilm formation and multidrug resistance. Among MRSA, the non-susceptibility rates to ciprofloxacin, gentamicin, and trimethoprim-sulfamethoxazole were significantly higher in agr dysfunctional isolates than in isolates with functional agr (P < 0.05). Two isolates belonging to ST239 had no mutations in agr locus, but a synonymous mutation was found in agrA in another ST239 isolate. The inactivating mutations were detected in other seven agr dysfunctional isolates. The variants were characterized by non-synonymous changes (n = 5) and frameshift mutations (insertions, n = 2), which mainly occurred in agrC and agrA.ConclusionsThe results showed that agr dysfunctional S. aureus was not common in Chinese children, and ST59-SCCmec IV was associated with lower prevalence of agr dysfunction as compared to ST239-SCCmec III isolates. The agr dysfunctional isolates were healthcare-associated, multidrug resistant and form strong biofilm, which suggested that agr dysfunction might offer potential advantages for S. aureus to survive in a medical environment.

Dataset Information

Detecting patterns of accessory genome coevolution in Staphylococcus aureus using data from thousands of genomes.

Publications

Detecting patterns of accessory genome coevolution in Staphylococcus aureus using data from thousands of genomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets