Zheng Yiluan, Shi Jianlu, Chen Qi, Deng Chao, Yang Fan, Wang Ying
Department of Automation, Xiamen University, Xiamen, China.
National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China.
Front Microbiol. 2022 Oct 6;13:960043. doi: 10.3389/fmicb.2022.960043. eCollection 2022.
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 . 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.
皮肤是连接人体与外部环境的重要生态系统。先前的研究表明,即使长期暴露于外部环境,皮肤微生物群落仍可保持稳定。在本研究中,我们探讨两个问题:皮肤微生物中是否存在个体特异性、时间稳定且与身体部位无关的菌株或基因变体?如果存在,这些微生物基因变体是否可以用作标记物(在我们的研究中称为“指纹”)来识别捐赠者?我们提出了一个框架,用于从皮肤宏基因组测序数据中捕获个体特异性的DNA微生物指纹。这些指纹是根据不含参考基因组和序列比对的31聚体的频率来识别的。我们采用了来自综合人类微生物组计划的12名健康个体在3个时间点从17个皮肤部位采集的616个宏基因组样本。最终,为每个个体组装一个重叠群作为指纹。结果表明,89.78%的皮肤样本(无论身体部位如何)都能正确识别其捐赠者。观察到12个个体特异性指纹中有10个可以与……比对。我们的研究证明,所识别的指纹在时间上是稳定的,与身体部位无关,且具有个体特异性,并且能够以足够的准确性识别其捐赠者。遗传识别框架的源代码可在https://github.com/Ying-Lab/skin_fingerprint上免费获取。