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It has been known for centuries that microorganisms are ubiquitous in the atmosphere, where they are capable of long-distance dispersal. Likewise, it is well-established that these airborne bacteria and fungi can have myriad effects on human health, as well as the health of plants and livestock. However, we have a limited understanding of how these airborne communities vary across different geographic regions or the factors that structure the geographic patterns of near-surface microbes across large spatial scales. We collected dust samples from the external surfaces of ∼1,200 households located across the United States to understand the continental-scale distributions of bacteria and fungi in the near-surface atmosphere. The microbial communities were highly variable in composition across the United States, but the geographic patterns could be explained by climatic and soil variables, with coastal regions of the United States sharing similar airborne microbial communities. Although people living in more urbanized areas were not found to be exposed to distinct outdoor air microbial communities compared with those living in more rural areas, our results do suggest that urbanization leads to homogenization of the airborne microbiota, with more urban communities exhibiting less continental-scale geographic variability than more rural areas. These results provide our first insight into the continental-scale distributions of airborne microbes, which is information that could be used to identify likely associations between microbial exposures in outdoor air and incidences of disease in crops, livestock, and humans.

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The Atacama Desert, the oldest and driest desert on Earth, displays significant rains only once per decade. To investigate how microbial communities take advantage of these sporadic wet events, we carried out a geomicrobiological study a few days after a heavy rain event in 2015. Different physicochemical and microbial community analyses were conducted on samples collected from playas and an alluvial fan from surface, 10, 20, 50, and 80 cm depth. Gravimetric moisture content peaks were measured in 10 and 20 cm depth samples (from 1.65 to 4.1% w/w maximum values) while, in general, main anions such as chloride, nitrate, and sulfate concentrations increased with depth, with maximum values of 13–1,125; 168–10,109; and 9,904–30,952 ppm, respectively. Small organic anions such as formate and acetate had maximum concentrations from 2.61 to 3.44 ppm and 6.73 to 28.75 ppm, respectively. Microbial diversity inferred from DNA analysis showed Actinobacteria and Alphaproteobacteria as the most abundant and widespread bacterial taxa among the samples, followed by Chloroflexi and Firmicutes at specific sites. Archaea were mainly dominated by Nitrososphaerales, Methanobacteria, with the detection of other groups such as Halobacteria. Metaproteomics showed a high and even distribution of proteins involved in primary metabolic processes such as energy production and biosynthetic pathways, and a limited but remarkable presence of proteins related to resistance to environmental stressors such as radiation, oxidation, or desiccation. The results indicated that extra humidity in the system allows the microbial community to repair, and prepare for the upcoming hyperarid period. Additionally, it supplies biomarkers to the medium whose preservation potential could be high under strong desiccation conditions and relevant for planetary exploration. [ABSTRACT FROM AUTHOR]

Although microbial communities are ubiquitous in nature, relatively little is known about the structural and functional roles of their constituent organisms’ underlying interactions. A common approach to study such questions begins with extracting a network of statistically significant pairwise co-occurrences from a matrix of observed operational taxonomic unit (OTU) abundances across sites. The structure of this network is assumed to encode information about ecological interactions and processes, resistance to perturbation, and the identity of keystone species. However, common methods for identifying these pairwise interactions can contaminate the network with spurious patterns that obscure true ecological signals. Here, we describe this problem in detail and develop a solution that incorporates null models to distinguish ecological signals from statistical noise. We apply these methods to the initial OTU abundance matrix and to the extracted network. We demonstrate this approach by applying it to a large soil microbiome data set and show that many previously reported patterns for these data are statistical artifacts. In contrast, we find the frequency of three-way interactions among microbial OTUs to be highly statistically significant. These results demonstrate the importance of using appropriate null models when studying observational microbiome data, and suggest that extracting and characterizing three-way interactions among OTUs is a promising direction for unraveling the structure and function of microbial ecosystems. [ABSTRACT FROM AUTHOR]

The complexities of the relationships between plant and soil microbial communities remain unresolved. We determined the associations between plant aboveground and belowground (root) distributions and the communities of soil fungi and bacteria found across a diverse tropical forest plot. Soil microbial community composition was correlated with the taxonomic and phylogenetic structure of the aboveground plant assemblages even after controlling for differences in soil characteristics, but these relationships were stronger for fungi than for bacteria. In contrast to expectations, the species composition of roots in our soil core samples was a poor predictor of microbial community composition perhaps due to the patchy, ephemeral, and highly overlapping nature of fine root distributions. Our ability to predict soil microbial composition was not improved by incorporating information on plant functional traits suggesting that the most commonly measured plant traits are not particularly useful for predicting the plot-level variability in belowground microbial communities. [ABSTRACT FROM AUTHOR]

Many investigations across natural and artificial plant diversity gradients have reported that both soil physicochemical factors and plant community composition affect soil microbial communities. To test the effect of plant diversity loss on soil bacterial communities, we conducted a five-year plant functional group removal experiment in a steppe ecosystem in Inner Mongolia (China). We found that the number and composition type of plant functional groups had no effect on bacterial diversity and community composition, or on the relative abundance of major taxa. In contrast, bacterial community patterns were significantly structured by soil water content differences among plots. Our results support researches that suggest that water availability is the key factor structuring soil bacterial communities in this semi-arid ecosystem. [ABSTRACT FROM AUTHOR]

There is an increasing interest to combine phylogenetic data with distributional and ecological records to assess how natural communities arrange under an evolutionary perspective. In the microbial world, there is also a need to go beyond the problematic species definition to deeply explore ecological patterns using genetic data. We explored links between evolution/phylogeny and community ecology using bacterial 16 S r RNA gene information from a high-altitude lakes district data set. We described phylogenetic community composition, spatial distribution, and β-diversity and biogeographical patterns applying evolutionary relatedness without relying on any particular operational taxonomic unit definition. High-altitude lakes districts usually contain a large mosaic of highly diverse small water bodies and conform a fine biogeographical model of spatially close but environmentally heterogeneous ecosystems. We sampled 18 lakes in the Pyrenees with a selection criteria focused on capturing the maximum environmental variation within the smallest geographical area. The results showed highly diverse communities nonrandomly distributed with phylogenetic β-diversity patterns mainly shaped by the environment and not by the spatial distance. Community similarity based on both bacterial taxonomic composition and phylogenetic β-diversity shared similar patterns and was primarily structured by similar environmental drivers. We observed a positive relationship between lake area and phylogenetic diversity with a slope consistent with highly dispersive planktonic organisms. The phylogenetic approach incorporated patterns of common ancestry into bacterial community analysis and emerged as a very convenient analytical tool for direct inter- and intrabiome biodiversity comparisons and sorting out microbial habitats with potential application in conservation studies. [ABSTRACT FROM AUTHOR]

Identifying the traits that determine spatial distributions can be challenging when studying organisms, like bacteria, for which phenotypic information is limited or non-existent. However, genomic data provide another means to infer traits and determine the ecological attributes that account for differences in distributions. We determined the spatial distributions of ~124 000 soil bacterial taxa across a 3.41 km2 area to determine whether we could use phylogeny and/or genomic traits to explain differences in habitat breadth. We found that occupancy was strongly correlated with environmental range; taxa that were more ubiquitous were found across a broader range of soil conditions. Across the ~500 taxa for which genomic information was available, genomic traits were more useful than phylogeny alone in explaining the variation in habitat breadth; bacteria with larger genomes and more metabolic versatility were more likely to have larger environmental and geographical distributions. Just as trait-based approaches have proven to be so useful for understanding the distributions of animals and plants, we demonstrate that we can use genomic information to infer microbial traits that are difficult to measure directly and build trait-based predictions of the biogeographical patterns exhibited by microbes. [ABSTRACT FROM AUTHOR]

There has been a recent explosion of research within the field of microbial ecology that has been fueled, in part, by methodological improvements that make it feasible to characterize microbial communities to an extent that was inconceivable only a few years ago. Furthermore, there is increasing recognition within the field of ecology that microorganisms play a critical role in the health of organisms and ecosystems. Despite these developments, an important gap still persists between the theoretical framework of macroecology and microbial ecology. We highlight two idiosyncrasies of microorganisms that are fundamental to understanding macroecological patterns and their mechanistic drivers. First, high dispersal rates provide novel opportunities to test the relative importance of niche, stochastic, and historical processes in structuring biological communities. Second, high speciation rates potentially lead to the convergence of ecological and evolutionary time scales. After reviewing these unique aspects, we discuss strategies for improving the conceptual integration of microbes into macroecology. As examples, we discuss the use of phylogenetic ecology as an integrative approach to explore patterns across the tree of life. Then we demonstrate how two general theories of biodiversity (i.e., the recently developed theory of stochastic geometry and the neutral theory) can be adapted to microorganisms. We demonstrate how conceptual models that integrate evolutionary and ecological mechanisms can contribute to the unification of microbial ecology and macroecology. [ABSTRACT FROM AUTHOR]

Exploring large environmental datasets generated by high-throughput DNA sequencing technologies requires new analytical approaches to move beyond the basic inventory descriptions of the composition and diversity of natural microbial communities. In order to investigate potential interactions between microbial taxa, network analysis of significant taxon co-occurrence patterns may help to decipher the structure of complex microbial communities across spatial or temporal gradients. Here, we calculated associations between microbial taxa and applied network analysis approaches to a 16S rRNA gene barcoded pyrosequencing dataset containing >160 000 bacterial and archaeal sequences from 151 soil samples from a broad range of ecosystem types. We described the topology of the resulting network and defined operational taxonomic unit categories based on abundance and occupancy (that is, habitat generalists and habitat specialists). Co-occurrence patterns were readily revealed, including general non-random association, common life history strategies at broad taxonomic levels and unexpected relationships between community members. Overall, we demonstrated the potential of exploring inter-taxa correlations to gain a more integrated understanding of microbial community structure and the ecological rules guiding community assembly. [ABSTRACT FROM AUTHOR]

We spend the majority of our lives indoors; yet, we currently lack a comprehensive understanding of how the microbial communities found in homes vary across broad geographical regions and what factors are most important in shaping the types of microorganisms found inside homes. Here, we investigated the fungal and bacterial communities found in settled dust collected from inside and outside approximately 1200 homes located across the continental US, homes that represent a broad range of home designs and span many climatic zones. Indoor and outdoor dust samples harboured distinct microbial communities, but these differences were larger for bacteria than for fungi with most indoor fungi originating outside the home. Indoor fungal communities and the distribution of potential allergens varied predictably across climate and geographical regions; where you live determines what fungi live with you inside your home. By contrast, bacterial communities in indoor dust were more strongly influenced by the number and types of occupants living in the homes. In particular, the female : male ratio and whether a house had pets had a significant influence on the types of bacteria found inside our homes highlighting that who you live with determines what bacteria are found inside your home. [ABSTRACT FROM AUTHOR]