Background: Human skin harbors complex transient and resident microbial communities that show intra- & inter-individual variation due to various environmental and host-associated factors such as skin site, diet, age, gender, genetics, or the type and use of cosmetics. This variation remains largely uncharacterized in the Indian population; hence, the present study aims to characterize the variation in skin microbiota among individuals of Indian origin and quantify associations with age, diet, and geography.
Methods: Axillary sweat samples from genetically unrelated individuals (N = 58) residing in the three geographical locations of Maharashtra, India, were collected using a sterile cotton swab. Bacterial DNA was extracted using a standard protocol and checked for quality. Variable regions (V3-V4) of the 16S rRNA gene were sequenced using the Illumina platform. We used standard methods from microbiota bioinformatics, including alpha and beta diversity, community typing, and differential abundance, to quantify the association of skin microbiota with age, diet, and geographical location.
Results: Our study indicated the prevalence of phyla- Firmicutes, Proteobacteria, and Actinobacteria, consistent with previous reports on skin microbiota composition of the world population level. The alpha diversity (Shannon index) was significantly associated with the age group (Kruskal-Wallis test, p = 0.02), but not with geography (p = 0.62) or diet (p = 0.74). The overall skin microbiota community composition was significantly associated with geographical location based on Community State Types (CST) analysis and PERMANOVA (R2 = 0.07, p = 0.01). Differential abundance analysis at the genus level indicated a distinctively high abundance of Staphylococcus and Corynebacterium among individuals of the Pune district. Pseudomonas and Anaerococcus were abundant in individuals from Ahmednagar whereas, Paenibacillus, Geobacillus, Virgibacillus, Jeotgalicoccus, Pullulanibacillus, Delsulfosporomusa, Citinovibrio, and Calditerricola were abundant in individuals from Nashik district.
Conclusion: Our work provides one of the first characterizations of skin microbiota variation in different sub-populations in India. The analysis quantifies the level of individuality, as contrasted to the other factors of age, geography, and diet, thus helping to evaluate the applicability of skin microbiota profiles as a potential biomarker to stratify individuals.
Keywords: Aging; Diet; Diversity; Geographical variation; Indian Population; Skin microbiota.
©2022 Potbhare et al.