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Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres
Published on: October 23, 2011
A novel multiplex PCR for the accurate identification of four clinically relevant Cutibacterium species
Koyo Yoshihara1, Shoji Seyama1, Yuji Hirai2
1Department of Clinical Microbiology, School of Pharmacy, Tokyo University of Pharmacy and Life Sciences, 1432-1 Horinouchi, Hachioji, Tokyo, 192-0392, Japan.
Abstract:
Cutibacterium is a genus of skin commensals involved in acne inflammation, occasionally causing healthcare-associated infections. Previously established multiplex PCR assays have been unable to detect Cutibacterium modestum. However, due to the reported occurrence of infections caused by this species, a comprehensive identification method that includes C. modestum is warranted. The objective of this study was to develop a novel multiplex PCR method that can rapidly distinguish between four Cutibacterium species, thereby facilitating the appropriate management of conditions such as acne and prosthesis-associated infections. We analyzed the species-specific regions of the recA gene and designed a new primer set to produce PCR amplicons that could be clearly distinguished from one another based on size differences of at least 150 bp among the four species. Assay performance was evaluated using 203 Cutibacterium isolates obtained from sterile site specimens from hospitalized patients, and assay sensitivity and specificity were also assessed. The newly developed multiplex PCR method could differentiate all four Cutibacterium species. We assessed the performance of this method using clinical isolates identified by 16S rRNA analysis. Consequently, all C. modestum strains that had been misidentified by the previous primer set were correctly identified, demonstrating 100% sensitivity and specificity. The multiplex PCR method developed in this study can accurately distinguish between four Cutibacterium species, including strains previously misclassified by conventional assays. This approach is expected to help clinicians select appropriate antimicrobial agents by enabling the early identification of pathogens causing acne and healthcare-associated infections.
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