Genomics Inform.  2023 Mar;21(1):e13. 10.5808/gi.22076.

Effective microbial molecular diagnosis of periodontitis-related pathogen Porphyromonas gingivalis from salivary samples using rgpA gene

Affiliations
  • 1Department of Bioconvergence Engineering, Dankook University, Yongin 16890, Korea
  • 2Department of Biological Sciences, Dankook University, Cheonan 31116, Korea
  • 3Department of Oral Microbiology and Immunology, College of Dentistry, Dankook University, Cheonan 31116, Korea
  • 4Department of Anesthesiology and Pain Management, Dankook University Hospital, Cheonan 31116, Korea
  • 5Animal Genomics and Bioresource Research Unit (AGB Research Unit), Faculty of Science, Kasetsart University, Bangkok 10900, Thailand
  • 6Center for Bio Medical Engineering Core Facility, Dankook University, Cheonan 31116, Korea
  • 7Department of Microbiology, College of Science & Technology, Dankook University, Cheonan 31116, Korea
  • 8HuNbiome Co., Ltd, R&D Center, Seoul 08503, Korea

Abstract

Importance of accurate molecular diagnosis and quantification of particular disease-related pathogenic microorganisms is highlighted as an introductory step to prevent and care for diseases. In this study, we designed a primer/probe set for quantitative real-time polymerase chain reaction (qRT-PCR) targeting rgpA gene, known as the specific virulence factor of periodontitis-related pathogenic bacteria ‘Porphyromonas gingivalis’, and evaluated its diagnostic efficiency by detecting and quantifying relative bacterial load of P. gingivalis within saliva samples collected from clinical subjects. As a result of qRT-PCR, we confirmed that relative bacterial load of P. gingivalis was detected and quantified within all samples of positive control and periodontitis groups. On the contrary, negative results were confirmed in both negative control and healthy groups. Additionally, as a result of comparison with next-generation sequencing (NGS)–based 16S metagenome profiling data, we confirmed relative bacterial load of P. gingivalis, which was not identified on bacterial classification table created through 16S microbiome analysis, in qRT-PCR results. It showed that an approach to quantifying specific microorganisms by applying qRT-PCR method could solve microbial misclassification issues at species level of an NGS-based 16S microbiome study. In this respect, we suggest that P. gingivalis–specific primer/probe set introduced in present study has efficient applicability in various oral healthcare industries, including periodontitis-related microbial molecular diagnosis field.

Keyword

molecular diagnosis; quantitative real-time PCR; gene
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