Background

Americans spend the vast majority of their lives in built environments. Even traditionally outdoor pursuits, such as exercising, are often now performed indoors. Bacteria that colonize these indoor ecosystems are primarily derived from the human microbiome. The modes of human interaction with indoor surfaces and the physical conditions associated with each surface type determine the steady-state ecology of the microbial community.

Results

Bacterial assemblages associated with different surfaces in three athletic facilities, including floors, mats, benches, free weights, and elliptical handles, were sampled every other hour (8 am to 6 pm) for 2 days. Surface and equipment type had a stronger influence on bacterial community composition than the facility in which they were housed. Surfaces that were primarily in contact with human skin exhibited highly dynamic bacterial community composition and non-random co-occurrence patterns, suggesting that different host microbiomes-shaped by selective forces-were being deposited on these surfaces through time. However, bacterial assemblages found on the floors and mats changed less over time, and species co-occurrence patterns appeared random, suggesting more neutral community assembly.

Conclusions

These longitudinal patterns highlight the dramatic turnover of microbial communities on surfaces in regular contact with human skin. By uncovering these longitudinal patterns, this study promotes a better understanding of microbe-human interactions within the built environment.

Understanding microbial partnerships with the medicinally and economically important crop Cannabis has the potential to affect agricultural practice by improving plant fitness and production yield. Furthermore, Cannabis presents an interesting model to explore plant-microbiome interactions as it produces numerous secondary metabolic compounds. Here we present the first description of the endorhiza-, rhizosphere-, and bulk soil-associated microbiome of five distinct Cannabis cultivars. Bacterial communities of the endorhiza showed significant cultivar-specificity. When controlling cultivar and soil type the microbial community structure was significantly different between plant cultivars, soil types, and between the endorhiza, rhizosphere and soil. The influence of soil type, plant cultivar and sample type differentiation on the microbial community structure provides support for a previously published two-tier selection model, whereby community composition across sample types is determined mainly by soil type, while community structure within endorhiza samples is determined mainly by host cultivar.

Standardized studies examining environmental microbial exposure in populations at risk for asthma are necessary to improve our understanding of the role this factor plays in disease development. Here we describe studies aimed at developing guidelines for high-resolution culture-independent microbiome profiling, using a phylogenetic microarray (PhyloChip), of house dust samples in a cohort collected as part of the NIH-funded Inner City Asthma Consortium (ICAC). We demonstrate that though extracted DNA concentrations varied across dust samples, the majority produced sufficient 16S rRNA to be profiled by the array. Comparison of array and 454-pyrosequencing performed in parallel on a subset of samples, illustrated that increasingly deeper sequencing efforts validated greater numbers of array-detected taxa. Community composition agreement across samples exhibited a hierarchy in concordance, with the highest level of agreement in replicate array profiles followed by samples collected from adjacent 1×1 m(2) sites in the same room, adjacent sites with different sized sampling quadrants (1×1 and 2×2 m(2)), different sites within homes (living and bedroom) to lowest in living room samples collected from different homes. The guidelines for sample collection and processing in this pilot study extend beyond PhyloChip based studies of house-associated microbiota, and bear relevance for other microbiome profiling approaches such as next-generation sequencing.