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Objective To explore the possibility of using human skin and oral microorganisms to estimate the geographic origin of an individual through the sequencing analysis of bacterial 16S rRNA gene. Methods Microbial DNA was extracted from the palm and oral microorganisms of the Han population in Shanghai and Chifeng, Inner Mongolia, and the composition and diversity of the microbiota were analyzed by full-length 16S rRNA gene sequencing. Then, differential species were screened and a geographic location prediction model was constructed. Results The compositions of palm and oral microorganisms between Shanghai and Chifeng samples were both different. The abundance and uniformity of palm side skin microorganisms were higher in Chifeng samples than in Shanghai samples, while there was no significant difference in oral microorganisms. Permutational multivariate analysis of variance （PERMANOVA） confirmed that the β-diversity between the samples from the two places were statistically significant, and the coefficients of determination （R2） for skin and oral samples were 0.129 and 0.102, respectively. Through principal co-ordinates analysis （PCoA）, the samples from the two places could be preliminarily distinguished. The predictive model had the accuracies of 0.90 and 0.83 for the geographic origin using the skin and oral samples, respectively. Conclusion There are differences in the compositions of palm and oral microbiota between Han populations in Shanghai and Chifeng. The prediction model constructed by the random forest algorithm can trace the unknown individuals from the above two places.

Objective To explore the possibility of using human skin and oral microorganisms to estimate the geographic origin of an individual through the sequencing analysis of bacterial 16S rRNA gene. Methods Microbial DNA was extracted from the palm and oral microorganisms of the Han population in Shanghai and Chifeng, Inner Mongolia, and the composition and diversity of the microbiota were analyzed by full-length 16S rRNA gene sequencing. Then, differential species were screened and a geographic location prediction model was constructed. Results The compositions of palm and oral microorganisms between Shanghai and Chifeng samples were both different. The abundance and uniformity of palm side skin microorganisms were higher in Chifeng samples than in Shanghai samples, while there was no significant difference in oral microorganisms. Permutational multivariate analysis of variance (PERMANOVA) confirmed that the β -diversity between the samples from the two places were statistically significant, and the coefficients of determination R2 for skin and oral samples were 0.129 and 0.102, respectively. Through principal co-ordinates analysis (PCoA), the samples from the two places could be preliminarily distinguished. The predictive model had the accuracies of 0.90 and 0.83 for the geographic origin using the skin and oral samples, respectively. Conclusion There are differences in the compositions of palm and oral microbiota between Han populations in Shanghai and Chifeng. The prediction model constructed by the random forest algorithm can trace the unknown individuals from the above two places. [ABSTRACT FROM AUTHOR]

Objectives: To explore the possibility of using human skin and oral microorganisms to estimate the geographic origin of an individual through the sequencing analysis of bacterial 16S rRNA gene., Methods: Microbial DNA was extracted from the palm and oral microorganisms of the Han population in Shanghai and Chifeng, Inner Mongolia, and the composition and diversity of the microbiota were analyzed by full-length 16S rRNA gene sequencing. Then, differential species were screened and a geographic location prediction model was constructed., Results: The compositions of palm and oral microorganisms between Shanghai and Chifeng samples were both different. The abundance and uniformity of palm side skin microorganisms were higher in Chifeng samples than in Shanghai samples, while there was no significant difference in oral microorganisms. Permutational multivariate analysis of variance (PERMANOVA) confirmed that th e β - diversity between the samples from the two places were statistically significant, and the coefficients of determination ( R 2 ) for skin and oral samples were 0.129 and 0.102, respectively. Through principal co-ordinates analysis (PCoA), the samples from the two places could be preliminarily distinguished. The predictive model had the accuracies of 0.90 and 0.83 for the geographic origin using the skin and oral samples, respectively., Conclusions: There are differences in the compositions of palm and oral microbiota between Han populations in Shanghai and Chifeng. The prediction model constructed by the random forest algorithm can trace the unknown individuals from the above two places.