Identifying individual-specific microbial DNA fingerprints from skin microbiomes

Area of Science:

• Microbiology
• Genomics
• Bioinformatics

Background:

• The skin harbors a complex microbial ecosystem interacting with the external environment.
• Previous research indicates the skin microbiome's temporal stability.
• The potential for individual-specific, body-site-independent microbial markers remains largely unexplored.

Purpose of the Study:

• To investigate the existence of individual-specific, temporally stable, and body-site-independent microbial genetic variants on human skin.
• To develop a framework for capturing these microbial genetic variants as 'fingerprints' for individual identification.
• To assess the accuracy of these microbial fingerprints in identifying donors.

Main Methods:

• Developed a computational framework utilizing 31-mer frequencies from metagenomic sequencing data, independent of reference genomes.
• Analyzed 616 skin metagenomic samples from 17 body sites across 3 time points from 12 healthy individuals.
• Assembled individual-specific microbial contigs as DNA microbial fingerprints.

Main Results:

• Successfully identified individual-specific DNA microbial fingerprints from skin metagenomic data.
• Achieved 89.78% accuracy in correctly identifying donors across different body sites and time points.
• Found that 10 out of 12 individual-specific fingerprints could be attributed to Cutibacterium acnes.

Conclusions:

• Demonstrated that DNA microbial fingerprints are temporally stable, body-site-independent, and individual-specific.
• Validated the potential of these fingerprints for accurate donor identification.
• The developed framework and source code are publicly available for further research.