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Identification of Antibiotic Resistance Genes in Orofacial Abscesses Using a Metagenomics-based Approach: A Pilot Study

  • Yeeun Lee (Department of Dentistry, Seoul National University School of Dentistry) ;
  • Joo-Young Park (Department of Oral and Maxillofacial Surgery, Seoul National University School of Dentistry, Seoul National University Dental Hospital) ;
  • Youngnim Choi (Department of Immunology and Molecular Microbiology, School of Dentistry and Dental Research Institute, Seoul National University)
  • Received : 2023.01.30
  • Accepted : 2023.02.27
  • Published : 2023.06.30

Abstract

Purpose: Culture-based methods for microbiological diagnosis and antibiotic susceptibility tests have limitations in the management of orofacial infections. We aimed to profile pus microbiota and identify antibiotic resistance genes (ARGs) using a culture-independent approach. Materials and Methods: Genomic DNA samples extracted from the pus specimens of two patients with orofacial abscesses were subjected to shotgun sequencing on the NovaSeq system. Taxonomic profiling and prediction of ARGs were performed directly from the metagenomic raw reads. Result: Taxonomic profiling revealed obligate anaerobic polymicrobial communities associated with infections of odontogenic origins: the microbial community of Patient 1 consisted of one predominant species (Prevotella oris 74.6%) with 27 minor species, while the sample from Patient 2 contained 3 abundant species (Porphyromonas endodontalis 33.0%; P. oris 31.6%; and Prevotella koreensis 13.4%) with five minor species. A total of 150 and 136 putative ARGs were predicted in the metagenome of each pus sample. The coverage of most predicted ARGs was less than 10%, and only the CfxA2 gene identified in Patient 1 was covered 100%. ARG analysis of the seven assembled genome/metagenome datasets of P. oris revealed that strain C735 carried the CfxA2 gene. Conclusion: A metagenomics-based approach is useful to profile predominantly anaerobic polymicrobial communities but needs further verification for reliable ARG detection.

Keywords

Acknowledgement

This study was supported by the National Research Foundation of Korea (Daejeon, Korea) through the grants (2018R1A5A2024418 and 2020R1A2C2007038).

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