Jin Ho 장진호Jhang, Kwangjin Ahn, Dokyun Kim, Seok Hoon Jeong, Hyun Soo Kim, Young Ree Kim, Young Ah Kim, Kyeong Seob Shin, Jeong Hwan Shin, Jeong Su Park, Kyoung Un Park, Yong Jun Kwon, S C Kim, Jong Hee Shin, Soon Young Ahn, SungYoung Lee, Songmee Bae, Jung Sik Yoo, Young Uh
Background/Objectives: The Korean Global Antimicrobial Resistance Surveillance System monitors bloodstream Staphylococcus aureus infections by combining antimicrobial susceptibility testing (AST) with conventional polymerase chain reaction (PCR). Considering the clinical significance of methicillin-resistant S. aureus (MRSA), we performed an in-depth analysis of isolates showing genotypic–phenotypic discrepancies. Methods: Isolates were collected from designated collection centers in the Republic of Korea between 2017 and 2024. The 30 μg cefoxitin disk diffusion method was used to define the phenotypes. PCR targeting mecA and the staphylococcal cassette chromosome mec (SCCmec) was used to identify genotypes through gel electrophoresis. Long-read whole-genome sequencing (WGS) was performed using the Revio system (Pacific Biosciences) for isolates exhibiting discrepancies between phenotypes and genotypes. Results: In total, 5808 isolates were screened, and seven cases of genotypic–phenotypic discrepancies were identified, including one infant and six elderly patients with chromosomal SCCmec type IV. Although WGS confirmed intact PCR primer-binding sites, structural alterations were observed: three isolates had normal-length mecA and mecR1, two had partial deletions in mecA, and two featured either mecA or mecR1 split into two proteins. Notably, although the six isolates with intact mecR1 genes matched the nucleotide length of SCCmec type IV, their sequences exhibited high homology with SCCmec type II. Conclusions: Despite the presence of mecA, the non-standard configuration of regulatory genes within the SCCmec elements suppressed actual resistance expression. Because conventional PCR focusing on partial gene segments could overlook such phenotypic traits, the meticulous observation and implementation of WGS are crucial for the accurate characterization of genotypic–phenotypic discrepancies.