Kuncheng Song

  • Designation: Laboratory Corporation of America Holdings (Labcorp)
  • Country: USA
  • Title: An In Silico Analysis of PCR-Based Monkeypox Virus Detection Assays: A Case Study for Ongoing Clinical Surveillance


Kuncheng Song is a senior bioinformatics scientist at the Center of Excellence for Bioinformatics, Data Science and AI, Laboratory Corporation of America Holdings (Labcorp), USA


The 2022 global Mpox outbreak swiftly introduced unforeseen diversity in the monkeypox virus (MPXV) population, resulting in numerous Clade IIb sublineages. This propagation of new MPXV mutations warrants the thorough re-investigation of previously recommended or validated primers designed to target MPXV genomes. This study explored 18 PCR primer sets and examined their binding specificity against 5210 MPXV genomes representing all the established MPXV lineages. Our results indicated that only five primer sets resulted in almost all perfect matches against the targeted MPXV lineages, and the remaining primer sets all contained 1–2 mismatches against almost all the MPXV lineages. We investigated the mismatched primer-genome pairs and discovered that some primers overlapped with poorly sequenced and assembled regions of the MPXV genomes, consistent across multiple lineages. However, we identified 173 99% genome-wide conserved regions across all 5210 MPXV genomes, representing 30 lineages/clades with at least 80% lineage-specific consensus for future primer development and primer binding evaluation. This exercise is crucial to ensure that the current detection schemes are robust and serve as a framework for primer evaluation in clinical testing development for other infectious diseases


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