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Identifying individual-specific microbial DNA fingerprints from skin microbiomes

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 gene...

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Autores principales: Zheng, Yiluan, Shi, Jianlu, Chen, Qi, Deng, Chao, Yang, Fan, Wang, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583911/
https://www.ncbi.nlm.nih.gov/pubmed/36274714
http://dx.doi.org/10.3389/fmicb.2022.960043
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author Zheng, Yiluan
Shi, Jianlu
Chen, Qi
Deng, Chao
Yang, Fan
Wang, Ying
author_facet Zheng, Yiluan
Shi, Jianlu
Chen, Qi
Deng, Chao
Yang, Fan
Wang, Ying
author_sort Zheng, Yiluan
collection PubMed
description 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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spelling pubmed-95839112022-10-21 Identifying individual-specific microbial DNA fingerprints from skin microbiomes Zheng, Yiluan Shi, Jianlu Chen, Qi Deng, Chao Yang, Fan Wang, Ying Front Microbiol Microbiology 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. Frontiers Media S.A. 2022-10-06 /pmc/articles/PMC9583911/ /pubmed/36274714 http://dx.doi.org/10.3389/fmicb.2022.960043 Text en Copyright © 2022 Zheng, Shi, Chen, Deng, Yang and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Zheng, Yiluan
Shi, Jianlu
Chen, Qi
Deng, Chao
Yang, Fan
Wang, Ying
Identifying individual-specific microbial DNA fingerprints from skin microbiomes
title Identifying individual-specific microbial DNA fingerprints from skin microbiomes
title_full Identifying individual-specific microbial DNA fingerprints from skin microbiomes
title_fullStr Identifying individual-specific microbial DNA fingerprints from skin microbiomes
title_full_unstemmed Identifying individual-specific microbial DNA fingerprints from skin microbiomes
title_short Identifying individual-specific microbial DNA fingerprints from skin microbiomes
title_sort identifying individual-specific microbial dna fingerprints from skin microbiomes
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583911/
https://www.ncbi.nlm.nih.gov/pubmed/36274714
http://dx.doi.org/10.3389/fmicb.2022.960043
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