Abstract
The highly personalized human skin microbiome may serve as a viable marker in personal identification. Amplicon sequencing resolution using 16S rRNA cannot identify bacterial communities sufficiently to discriminate between individuals. Thus, novel higher-resolution genetic markers are required for forensic purposes. The clustered regularly interspaced short palindromic repeats (CRISPRs) are prokaryotic genetic elements that can provide a history of infections encountered by the bacteria. The sequencing of CRISPR spacers may provide phylogenetic information with higher resolution than other markers. However, using spacer sequencing for discrimination of personal skin microbiome is difficult due to limited information on CRISPRs in human skin microbiomes. It remains unclear whether personal microbiome discrimination can be achieved using spacer diversity or which CRISPRs will be forensically relevant. We identified common CRISPRs in the human skin microbiome via metagenomic reconstruction and used amplicon sequencing for deep sequencing of spacers. We successfully reconstructed 24 putative CRISPR arrays using metagenomic data sets. A total of 1,223,462 reads from three CRISPR arrays revealed that spacers in the skin microbiome were highly personalized, and conserved repeats were commonly shared between individuals. These individual specificities observed using CRISPR typing were confirmed by comparing the CRISPR diversity to microbiome diversity assessed using 16S rRNA amplicon sequencing. CRISPR typing achieved 95.2% accuracy in personal classification, whereas 16S rRNA sequencing only achieved 52.6%. These results suggest that sequencing CRISPRs in the skin microbiome may be a more powerful approach for personal identification and ecological studies compared to conventional 16S rRNA sequencing.IMPORTANCE Microbial community diversity analysis can be utilized to characterize the personal microbiome that varies between individuals. CRISPR sequences, which reflect virome structure, in the human skin environment may be highly personalized similar to the structures of individual viromes. In this study, we identified 24 putative CRISPR arrays using a shotgun metagenome data set of the human skin microbiome. The findings of this study expand our understanding of the nature of CRISPRs by identifying novel CRISPR candidates. We developed a method to efficiently determine the diversity of three CRISPR arrays. Our analysis revealed that the CRISPR spacer diversity in the human skin microbiome is highly personalized compared with the microbiome diversity assessed by 16S rRNA sequencing, providing a new perspective on the study of the skin microbiome.