Identifying individual-specific microbial DNA fingerprints from skin microbiomes - Zheng, Yiluan; Shi, Jianlu; Chen, Qi; Deng, Chao; Yang, Fan; Wang, Ying (Frontiers in Microbiology, 2022)
Skin is a critical ecosystem between human body and external environment. Previous studies have shown that skin microbial community could remain stable, even after long-term exposure to external environment. In this study, we explore two questions: Does 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 of body sites could identify their donors correctly. It is observed that 10 out of 12 individual-specific fingerprints could be aligned to Propionibacterium acnes. Our study prove that the identified fingerprints are temporally stable, body site-independent, and individual-specific and are able to 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 .