Dataset Information

Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology.

ABSTRACT: Staphylococcus aureusis a major bacterial pathogen causing a variety of diseases ranging from wound infections to severe bacteremia or intoxications. Besides host factors, the course and severity of disease is also widely dependent on the genotype of the bacterium. Whole-genome sequencing (WGS), followed by bioinformatic sequence analysis, is currently the most extensive genotyping method available. To identify clinically relevant staphylococcal virulence and resistance genes in WGS data, we developed anin silicotyping scheme for the software SeqSphere(+)(Ridom GmbH, Münster, Germany). The implemented target genes (n= 182) correspond to those queried by the IdentibacS. aureusGenotyping DNA microarray (Alere Technologies, Jena, Germany). Thein silicoscheme was evaluated by comparing the typing results of microarray and of WGS for 154 humanS. aureusisolates. A total of 96.8% (n= 27,119) of all typing results were equally identified with microarray and WGS (40.6% present and 56.2% absent). Discrepancies (3.2% in total) were caused by WGS errors (1.7%), microarray hybridization failures (1.3%), wrong prediction of ambiguous microarray results (0.1%), or unknown causes (0.1%). Superior to the microarray, WGS enabled the distinction of allelic variants, which may be essential for the prediction of bacterial virulence and resistance phenotypes. Multilocus sequence typing clonal complexes and staphylococcal cassette chromosomemecelement types inferred from microarray hybridization patterns were equally determined by WGS. In conclusion, WGS may substitute array-based methods due to its universal methodology, open and expandable nature, and rapid parallel analysis capacity for different characteristics in once-generated sequences.

SUBMITTER: Strauß L

PROVIDER: S-EPMC4809937 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology.

Strauß Lena L Ruffing Ulla U Abdulla Salim S Alabi Abraham A Akulenko Ruslan R Garrine Marcelino M Germann Anja A Grobusch Martin Peter MP Helms Volkhard V Herrmann Mathias M Kazimoto Theckla T Kern Winfried W Mandomando Inácio I Peters Georg G Schaumburg Frieder F von Müller Lutz L Mellmann Alexander A

Journal of clinical microbiology 20160127 4

Staphylococcus aureusis a major bacterial pathogen causing a variety of diseases ranging from wound infections to severe bacteremia or intoxications. Besides host factors, the course and severity of disease is also widely dependent on the genotype of the bacterium. Whole-genome sequencing (WGS), followed by bioinformatic sequence analysis, is currently the most extensive genotyping method available. To identify clinically relevant staphylococcal virulence and resistance genes in WGS data, we dev ...[more]

PMID: 26818676

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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:While Staphylococcus aureus is associated with significant morbidity and mortality in equids (horses, donkeys, and mules), few studies have performed whole-genome sequencing to fully categorize large collections of equine isolates. Such sequencing allows for a comprehensive analysis of the genetic lineage and relationships of isolates, as well as the virulence genes present in each, which can be important for understanding the epidemiology of strains and their range of infections. Seventy-two clinical Staphylococcus aureus isolates from equids were collected at the Texas A&M University Veterinary Medical Teaching Hospital between 2007 and 2017. Whole-genome sequencing was performed to characterize the isolates according to sequence typing, biofilm association, antimicrobial resistance, and toxin gene carriage. Of the 72 isolates, 19% were methicillin resistant, of which the majority belonged to clonal complex 8. Eighteen distinct sequence types (STs) were represented, with the most common being ST1, ST133, ST8, and ST97. Most isolates had weak or negative overall biofilm production. Toxin and antimicrobial resistance gene carriage was varied; of note, this study revealed that a large proportion of North American equine isolates carry the leucocidin PQ toxin (66% of isolates). One isolate (17-021) carried genes imparting lincosamide and high-level mupirocin resistance, a combination not previously reported in equine-derived S. aureus isolates. IMPORTANCE This is one of the first studies to perform whole-genome sequencing (WGS) of a large collection of Staphylococcus aureus isolates, both methicillin resistant and susceptible, collected from horses. A large proportion of the isolates carry leucocidin PQ (LukPQ), making this one of the first reports of such carriage in the United States. The presence of lincosamide and high-level mupirocin resistance in a methicillin-susceptible S. aureus (MSSA) isolate highlights the importance of MSSA as a reservoir of important antimicrobial resistance genes. As microbial resistance genes on mobile genetic elements can pass between S. aureus strains and livestock-associated strains can be transferred to humans, these findings have important public health implications.

Project description:BackgroundThe emergence of resistance to anti-tuberculosis drugs is a serious and growing threat to public health. Next-generation sequencing is rapidly gaining traction as a diagnostic tool for investigating drug resistance in Mycobacterium tuberculosis to aid treatment decisions. However, there are few little data regarding the precision of such sequencing for assigning resistance profiles.MethodsWe investigated two sequencing platforms (Illumina MiSeq, Ion Torrent PGM™) and two rapid analytic pipelines (TBProfiler, Mykrobe predictor) using a well characterised reference strain (H37Rv) and clinical isolates from patients with tuberculosis resistant to up to 13 drugs. Results were compared to phenotypic drug susceptibility testing. To assess analytical robustness individual DNA samples were subjected to repeated sequencing.ResultsThe MiSeq and Ion PGM systems accurately predicted drug-resistance profiles and there was high reproducibility between biological and technical sample replicates. Estimated variant error rates were low (MiSeq 1 per 77 kbp, Ion PGM 1 per 41 kbp) and genomic coverage high (MiSeq 51-fold, Ion PGM 53-fold). MiSeq provided superior coverage in GC-rich regions, which translated into incremental detection of putative genotypic drug-specific resistance, including for resistance to para-aminosalicylic acid and pyrazinamide. The TBProfiler bioinformatics pipeline was concordant with reported phenotypic susceptibility for all drugs tested except pyrazinamide and para-aminosalicylic acid, with an overall concordance of 95.3%. When using the Mykrobe predictor concordance with phenotypic testing was 73.6%.ConclusionsWe have demonstrated high comparative reproducibility of two sequencing platforms, and high predictive ability of the TBProfiler mutation library and analytical pipeline, when profiling resistance to first- and second-line anti-tuberculosis drugs. However, platform-specific variability in coverage of some genome regions may have implications for predicting resistance to specific drugs. These findings may have implications for future clinical practice and thus deserve further scrutiny, set within larger studies and using updated mutation libraries.

Dataset Information

Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology.

Publications

Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology.

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