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Detecting Staphylococcus aureus virulence and resistance genes: A comparison of whole-genome sequencing and DNA microarray technology

: Strauß, L.; Ruffing, U.; Abdulla, S.; Alabi, A.; Akulenko, R.; Garrine, M.; Germann, A.; Grobusch, M.P.; Helms, V.; Herrmann, M.; Kazimoto, T.; Kern, W.; Mandomando, I.; Peters, G.; Schaumburg, F.; Müller, L. von; Mellmann, A.


Journal of clinical microbiology : JCM 54 (2016), Nr.4, S.1008-1016
ISSN: 0095-1137
ISSN: 1098-660X
Deutsche Forschungsgemeinschaft DFG
Me 3205/4-1
Fraunhofer IBMT ()

Staphylococcus aureus is 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 an in silico typing scheme for the software SeqSphere(+) (Ridom GmbH, Munster, Germany). The implemented target genes (n = 182) correspond to those queried by the Identibac S. aureus Genotyping DNA microarray (Alere Technologies, Jena, Germany). The in silico scheme was evaluated by comparing the typing results of microarray and of WGS for 154 human S. aureus isolates. 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 chromosome mec element 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.