Frontiers in Microbiology (Oct 2022)

Identifying individual-specific microbial DNA fingerprints from skin microbiomes

  • Yiluan Zheng,
  • Yiluan Zheng,
  • Jianlu Shi,
  • Jianlu Shi,
  • Qi Chen,
  • Chao Deng,
  • Fan Yang,
  • Ying Wang,
  • Ying Wang,
  • Ying Wang

DOI
https://doi.org/10.3389/fmicb.2022.960043
Journal volume & issue
Vol. 13

Abstract

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Skin is an important ecosystem that links the human body and the external environment. Previous studies have shown that the skin microbial community could remain stable, even after long-term exposure to the external environment. In this study, we explore two questions: Do there exist strains or genetic variants in skin microorganisms that are individual-specific, temporally stable, and body site-independent? And if so, whether such microorganismal genetic variants could be used as markers, called “fingerprints” in our study, to identify donors? We proposed a framework to capture individual-specific DNA microbial fingerprints from skin metagenomic sequencing data. The fingerprints are identified on the frequency of 31-mers free from reference genomes and sequence alignments. The 616 metagenomic samples from 17 skin sites at 3-time points from 12 healthy individuals from Integrative Human Microbiome Project were adopted. Ultimately, one contig for each individual is assembled as a fingerprint. And results showed that 89.78% of the skin samples despite body sites could identify their donors correctly. It is observed that 10 out of 12 individual-specific fingerprints could be aligned to Cutibacterium acnes. Our study proves that the identified fingerprints are temporally stable, body site-independent, and individual-specific, and can identify their donors with enough accuracy. The source code of the genetic identification framework is freely available at https://github.com/Ying-Lab/skin_fingerprint.

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