Bioinformatics study of expression from genomes of epidemiologically related MRSA CC398 isolates from human and wild...

One of the most important livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) genetic lineages is the clonal complex (CC) 398, which can cause typical S. aureus-associated infections in people. In this work, whole-genome sequencing, RNA-sequencing, and gel-based comparative proteomics were applied to study the genetic characteristics of three MRSA CC398 isolates recovered from humans (strains C5621 and C9017), and from an animal (strain OR418). Of the three strains, C9017 presented the broadest resistance genotype, including resistance to fluroquinolone, clindamycin, tiamulin, macrolide and aminoglycoside antimicrobial classes. The scn, sak, and chp genes of the immune evasion cluster system were solely detected in OR418. Pangenome analysis showed a total of 288 strain-specific genes, most of which are hypothetical or phage-related proteins. OR418 had the most pronounced genetic differences. RNAIII (δ-hemolysin) gene was clearly the most expressed gene in OR418 and C5621, but it was not detected in C9017. Significant differences in the proteome profiles were found between strains. For example, the immunoglobulin-binding protein Sbi was more abundant in OR418. Considering that Sbi is a multifunctional immune evasion factor in S. aureus, the results point to OR418 strain having high zoonotic potential. Overall, multiomics biomarker signatures can assume an important role to advance precision medicine in the years to come. SIGNIFICANCE: MRSA is one of the most representative drug-resistant pathogens and its dissemination is increasing due to MRSA capability of establishing new reservoirs. LA-MRSA is considered an emerging problem worldwide and CC398 is one of the most important genetic lineages. In this study, three MRSA CC398 isolates recovered from humans and from a wild animal were analyzed through whole-genome sequencing, RNA-sequencing, and gel-based comparative proteomics in order to gather systems-wide omics data and better understand the genetic characteristics of this lineage to identify distinctive markers and genomic features of relevance to public health.