Urban greenness influences airborne bacterial community composition.

Urban green space provides health benefits for city dwellers, and new evidence suggests that microorganisms associated with soil and vegetation could play a role. While airborne microorganisms are ubiquitous in urban areas, the influence of nearby vegetation on airborne microbial communities remains poorly understood. We examined airborne microbial communities in parks and parking lots in Eugene, Oregon, using high-throughput sequencing of the bacterial 16S rRNA gene on the Illumina MiSeq platform to identify bacterial taxa, and GIS to measure vegetation cover in buffer zones of different diameters. Our goal was to explore variation among highly vegetated (parks) versus non-vegetated (parking lots) urban environments. A secondary objective was to evaluate passive versus active collection methods for outdoor airborne microbial sampling. Airborne bacterial communities from five parks were different from those of five parking lots (p=0.023), although alpha diversity was similar. Direct gradient analysis showed that the proportion of vegetated area within a 50m radius of the sampling station explained 15% of the variation in bacterial community composition. A number of key taxa, including several Acidobacteriaceae were substantially more abundant in parks, while parking lots had higher relative abundance of Acetobacteraceae. Parks had greater beta diversity than parking lots, i.e. individual parks were characterized by unique bacterial signatures, whereas parking lot communities tended to be similar to each other. Although parks and parking lots were selected to form pairs of nearby sites, spatial proximity did not appear to affect compositional similarity. Our results also showed that passive and active collection methods gave comparable results, indicating the "settling dish" method is effective for outdoor airborne sampling. This work sets a foundation for understanding how urban vegetation may impact microbial communities, with potential implications for designing neighborhoods and open space systems that foster better human health.

Humans differ in their personal microbial cloud.

Dispersal of microbes between humans and the built environment can occur through direct contact with surfaces or through airborne release; the latter mechanism remains poorly understood. Humans emit upwards of 10(6) biological particles per hour, and have long been known to transmit pathogens to other individuals and to indoor surfaces. However it has not previously been demonstrated that humans emit a detectible microbial cloud into surrounding indoor air, nor whether such clouds are sufficiently differentiated to allow the identification of individual occupants. We used high-throughput sequencing of 16S rRNA genes to characterize the airborne bacterial contribution of a single person sitting in a sanitized custom experimental climate chamber. We compared that to air sampled in an adjacent, identical, unoccupied chamber, as well as to supply and exhaust air sources. Additionally, we assessed microbial communities in settled particles surrounding each occupant, to investigate the potential long-term fate of airborne microbial emissions. Most occupants could be clearly detected by their airborne bacterial emissions, as well as their contribution to settled particles, within 1.5-4 h. Bacterial clouds from the occupants were statistically distinct, allowing the identification of some individual occupants. Our results confirm that an occupied space is microbially distinct from an unoccupied one, and demonstrate for the first time that individuals release their own personalized microbial cloud.

Mobile phones carry the personal microbiome of their owners.

Most people on the planet own mobile phones, and these devices are increasingly being utilized to gather data relevant to our personal health, behavior, and environment. During an educational workshop, we investigated the utility of mobile phones to gather data about the personal microbiome - the collection of microorganisms associated with the personal effects of an individual. We characterized microbial communities on smartphone touchscreens to determine whether there was significant overlap with the skin microbiome sampled directly from their owners. We found that about 22% of the bacterial taxa on participants' fingers were also present on their own phones, as compared to 17% they shared on average with other people's phones. When considered as a group, bacterial communities on men's phones were significantly different from those on their fingers, while women's were not. Yet when considered on an individual level, men and women both shared significantly more of their bacterial communities with their own phones than with anyone else's. In fact, 82% of the OTUs were shared between a person's index and phone when considering the dominant taxa (OTUs with more than 0.1% of the sequences in an individual's dataset). Our results suggest that mobile phones hold untapped potential as personal microbiome sensors.

Bacterial community composition of divergent soil habitats in a polar desert.

Edaphic factors such as pH, organic matter, and salinity are often the most significant drivers of diversity patterns in soil bacterial communities. Desert ecosystems in particular are model locations for examining such relationships as food web complexity is low and the soil environment is biogeochemically heterogeneous. Here, we present the findings from a 16S rRNA gene sequencing approach used to observe the differences in diversity and community composition among three divergent soil habitats of the McMurdo Dry Valleys, Antarctica. Results show that alpha diversity is significantly lowered in high pH soils, which contain higher proportions of the phyla Acidobacteria and Actinobacteria, while mesic soils with higher soil organic carbon (and ammonium) content contain high proportions of Nitrospira, a nitrite-oxidizing bacteria. Taxonomic community resolution also had a significant impact on our conclusions, as pH was the primary predictor of phylum-level diversity, while moisture was the most significant predictor of diversity at the genus level. Predictive power also increased with increasing taxonomic resolution, suggesting a potential increase in niche-based drivers of bacterial community composition at such levels.

Bacterial communities on classroom surfaces vary with human contact.

BACKGROUND: Humans can spend the majority of their time indoors, but little is known about the interactions between the human and built-environment microbiomes or the forces that drive microbial community assembly in the built environment. We sampled 16S rRNA genes from four different surface types throughout a university classroom to determine whether bacterial assemblages on each surface were best predicted by routine human interactions or by proximity to other surfaces within the classroom. We then analyzed our data with publicly-available datasets representing potential source environments. RESULTS: Bacterial assemblages from the four surface types, as well as individual taxa, were indicative of different source pools related to the type of human contact each surface routinely encounters. Spatial proximity to other surfaces in the classroom did not predict community composition. CONCLUSIONS: Our results indicate that human-associated microbial communities can be transferred to indoor surfaces following contact, and that such transmission is possible even when contact is indirect, but that proximity to other surfaces in the classroom does not influence community composition.

Factors Controlling Soil Microbial Biomass and Bacterial Diversity and Community Composition in a Cold Desert Ecosystem: Role of Geographic Scale.

Understanding controls over the distribution of soil bacteria is a fundamental step toward describing soil ecosystems, understanding their functional capabilities, and predicting their responses to environmental change. This study investigated the controls on the biomass, species richness, and community structure and composition of soil bacterial communities in the McMurdo Dry Valleys, Antarctica, at local and regional scales. The goals of the study were to describe the relationships between abiotic characteristics and soil bacteria in this unique, microbially dominated environment, and to test the scale dependence of these relationships in a low complexity ecosystem. Samples were collected from dry mineral soils associated with snow patches, which are a significant source of water in this desert environment, at six sites located in the major basins of the Taylor and Wright Valleys. Samples were analyzed for a suite of characteristics including soil moisture, pH, electrical conductivity, soil organic matter, major nutrients and ions, microbial biomass, 16 S rRNA gene richness, and bacterial community structure and composition. Snow patches created local biogeochemical gradients while inter-basin comparisons encompassed landscape scale gradients enabling comparisons of microbial controls at two distinct spatial scales. At the organic carbon rich, mesic, low elevation sites Acidobacteria and Actinobacteria were prevalent, while Firmicutes and Proteobacteria were dominant at the high elevation, low moisture and biomass sites. Microbial parameters were significantly related with soil water content and edaphic characteristics including soil pH, organic matter, and sulfate. However, the magnitude and even the direction of these relationships varied across basins and the application of mixed effects models revealed evidence of significant contextual effects at local and regional scales. The results highlight the importance of the geographic scale of sampling when determining the controls on soil microbial community characteristics.