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Comparative analysis of skin microbiome across 10 sites in Koreans for forensic applications: a pilot study

  • Hye Seon Cho
  • , Ji woo Lee
  • , Ha Eun Cha
  • , Jooree Seo
  • , Si Keun Lim
  • Sungkyunkwan University

Research output: Contribution to journalArticlepeer-review

Abstract

Various microorganisms have a symbiotic relationship with human skin cells, influenced by intrinsic and extrinsic factors. The composition of the human microbiome varies based on the skin site. To investigate the microbial characteristics of different skin sites in Koreans, microbiome samples were collected from the scalp, forehead, cheek, retroauricular crease, cervical vertebrae, axilla, palm, lateral finger, femur, and plantar skin. The concentrations of human and bacterial DNA were quantified, and QIIME2 and MicrobiomeAnalyst platforms were used for microbial analysis. Forehead and cheek microbiome compositions were similar, with higher proportions of Streptococcus than that at other sites. Palm and lateral finger microbiome compositions were also similar, with higher proportions of Haemophilus than that at other sites. Lawsonella was specifically observed on the scalp, while Mycoplasma was found on cervical vertebrae. Staphylococcus, observed on all sites, was particularly predominant on axilla. The microbial composition of plantar was distinct, with no prevalent genus compared to that at other sites. Further research analyzing skin microbiomes from forensic evidence could help identify the origin of skin samples, aiding in crime scene reconstruction. Comparing our findings from Korean participants with international studies, it suggests that expanding research to include diverse populations could reveal regional and national differences in skin microbiomes, providing valuable insights for forensic science.

Original languageEnglish
Article number102706
JournalLegal Medicine
Volume78
DOIs
StatePublished - Oct 2025

Keywords

  • Korean skin microbiome
  • Microbial community analysis
  • Next-generation sequencing
  • Spatial variance

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