A Tri-Source Microbiome Dataset from Human Sleep Environments: Saliva, Pillow Dust, and Bedroom Air.

Despite the established importance of the human microbiome in health, the integrated microbial exposures occurring within the sleep environment remain poorly understood. Sleep represents a critical period of prolonged exposure to indoor microbial reservoirs, yet no study has simultaneously examined the connectivity between environmental sources and the human oral microbiome. We present a novel, tri-source microbiome dataset characterizing microbial communities from co-located saliva, pillow dust, and bedroom air collected from healthy participants in real-world sleep environments. Samples were collected under standardized protocols and analyzed using 16S rRNA gene amplicon sequencing (V3-V4 region). Rigorous quality control and bioinformatic processing were applied to generate high-resolution amplicon sequence variants. Alpha diversity analysis revealed that pillow dust serves as the most diverse and stable microbial reservoir, exhibiting significantly higher species richness and phylogenetic diversity than saliva or air (p < 0.05). Beta diversity analysis showed distinct clustering by sample type, with indoor air and pillow dust exhibiting closer microbial similarity to each other than to saliva. Notably, significant genus-level correlations were identified between air and pillow dust (e.g., Brevitalea, Gardnerella) and between pillow dust and saliva (e.g., Actinomyces, Bifidobacterium), suggesting potential microbial exchange through gravitational settling and physical contact. This tri-source dataset provides a unique resource for investigating host-environment microbial interactions during rest. Our findings highlight the sleep environment as a significant exposome factor that may influence oral microbiome dynamics, offering new avenues for research into respiratory health, built environment science, and human exposome studies.