Whole-genome sequencing analysis of molecular epidemiology and silent transmissions causing meticillin-resistant Staphylococcus aureus bloodstream infections in a university hospital.

T Sato, T Yamaguchi, K Aoki,C Kajiwara, S Kimura,T Maeda, S Yoshizawa, M Sasaki,H Murakami,J Hisatsune, M Sugai, Y Ishii, K Tateda,Y Urita

The Journal of hospital infection(2023)

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摘要
BACKGROUND:The emergence of novel genomic-type clones, such as community-associated meticillin-resistant Staphylococcus aureus (MRSA) and livestock-associated MRSA, and their invasion into hospitals have become major concerns worldwide; however, little information is available regarding the prevalence of MRSA in Japan. Whole-genome sequencing (WGS) has been conducted to analyse various pathogens worldwide. Therefore, it is important to establish a genome database of clinical MRSA isolates available in Japan. AIM:A molecular epidemiological analysis of MRSA strains isolated from bloodstream-infected patients in a Japanese university hospital was conducted using WGS and single-nucleotide polymorphism (SNP) analysis. Additionally, through a review of patients' clinical characteristics, the effectiveness of SNP analysis as a tool for detecting silent nosocomial transmission that may be missed by other methods was evaluated in diverse settings and various time points of detection. METHODS:Polymerase-chain-reaction-based staphylococcal cassette chromosome mec (SCCmec) typing was performed using 135 isolates obtained between 2014 and 2018, and WGS was performed using 88 isolates obtained between 2015 and 2017. FINDINGS:SCCmec type II strains, prevalent in 2014, became rare in 2018, whereas the prevalence of SCCmec type IV strains increased from 18.75% to 83.87% of the population, and became the dominant clones. Clonal complex (CC) 5 CC8 and CC1 were detected between 2015 and 2017, with CC1 being dominant. In 88 cases, SNP analyses revealed nosocomial transmissions among 20 patients which involved highly homologous strains. CONCLUSIONS:Routine monitoring of MRSA by whole-genome analysis is effective not only for gaining knowledge regarding molecular epidemiology, but also for detecting silent nosocomial transmission.
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