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Abstract While often obvious for macroscopic organisms, determining whether a microbe is dead or alive is fraught with complications. Fields such as microbial ecology, environmental health, and medical microbiology each determine how best to assess which members of the microbial community are alive, according to their respective scientific and/or regulatory needs. Many of these fields have gone from studying communities on a bulk level to the fine-scale resolution of microbial populations within consortia. For example, advances in nucleic acid sequencing technologies and downstream bioinformatic analyses have allowed for high-resolution insight into microbial community composition and metabolic potential, yet we know very little about whether such community DNA sequences represent viable microorganisms. In this review, we describe a number of techniques, from microscopy- to molecular-based, that have been used to test for viability (live/dead determination) and/or activity in various contexts, including newer techniques that are compatible with or complementary to downstream nucleic acid sequencing. We describe the compatibility of these viability assessments with high-throughput quantification techniques, including flow cytometry and quantitative PCR (qPCR). Although bacterial viability-linked community characterizations are now feasible in many environments and thus are the focus of this critical review, further methods development is needed for complex environmental samples and to more fully capture the diversity of microbes (e.g., eukaryotic microbes and viruses) and metabolic states (e.g., spores) of microbes in natural environments.

Abstract Background Microbial communities associated with indoor dust abound in the built environment. The transmission of sunlight through windows is a key building design consideration, but the effects of light exposure on dust communities remain unclear. We report results of an experiment and computational models designed to assess the effects of light exposure and wavelengths on the structure of the dust microbiome. Specifically, we placed household dust in replicate model “rooms” with windows that transmitted visible, ultraviolet, or no light and measured taxonomic compositions, absolute abundances, and viabilities of the resulting bacterial communities. Results Light exposure per se led to lower abundances of viable bacteria and communities that were compositionally distinct from dark rooms, suggesting preferential inactivation of some microbes over others under daylighting conditions. Differences between communities experiencing visible and ultraviolet light wavelengths were relatively minor, manifesting primarily in abundances of dead human-derived taxa. Daylighting was associated with the loss of a few numerically dominant groups of related microorganisms and apparent increases in the abundances of some rare groups, suggesting that a small number of microorganisms may have exhibited modest population growth under lighting conditions. Although biological processes like population growth on dust could have generated these patterns, we also present an alternate statistical explanation using sampling models from ecology; simulations indicate that artefactual, apparent increases in the abundances of very rare taxa may be a null expectation following the selective inactivation of dominant microorganisms in a community. Conclusions Our experimental and simulation-based results indicate that dust contains living bacterial taxa that can be inactivated following changes in local abiotic conditions and suggest that the bactericidal potential of ordinary window-filtered sunlight may be similar to ultraviolet wavelengths across dosages that are relevant to real buildings.

Greater exposure to environmental microorganisms has been hypothesized to reduce the likelihood of developing autoimmune disorders, and vegetation is known to be a source of diverse microbiota to the air. However, the spatiotemporal dynamics of airborne microbial communities in urban environments with varying amounts and types of vegetation are poorly understood. In this study we used high-throughput sequencing of the bacterial 16S rRNA gene to assess whether fine-scale variation in urban vegetation influences the diversity, composition, or structure of airborne bacterial communities over time. We used passive settling dishes to collect airborne bacteria from 36 sites representing three urban land cover types (forest, grassland, paved) over a 3-month period in Eugene-Springfield, Oregon, USA. We used remote sensing data (aerial 4-band orthoimagery and LiDAR) and geographic information systems (GIS) to assess detailed site characteristics (e.g., total vegetation cover and structural diversity) for each site. Our initial analysis indicated that site was the most important factor explaining variation in bacterial community structure (R2 = 0.32, p < 0.001), followed by sampling date (R2 = 0.24, p < 0.001), while land cover type was a significant but weak predictor (R2 = 0.06, p < 0.001) and other vegetation metrics were even less predictive. However, when samples were analyzed separately by date, the explanatory power of land cover type increased substantially; six of nine dates showed significant effects (p < 0.05) with R2 ranging from 0.16–0.31, indicating that land cover type had a marked influence on bacterial community structure that was obscured by the effects of site and sampling date. Despite the importance of site as a predictor of bacterial community structure, Mantel tests for spatial correlation were insignificant for most sampling dates, suggesting that localized site characteristics were driving this relationship. We use our results to propose a space-time conceptual model of the interactions between site-scale environmental features (e.g., vegetation characteristics) and regional-scale temporal processes and events (e.g., agricultural harvesting) to understand and perhaps manage intraurban airborne bacterial communities.