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Abstract The species area relationship is a classic ecological law describing the relationship between habitat increase and the number of species. Species area relationships are resoundingly positive across macrobes such as plants and animals, and emerge through non-exclusive stochastic and deterministic processes including changes in immigration and extinction, drift, and environmental heterogeneity. Due to unique attributes of the microbial lifestyle, they may not abide by similar rules as macrobes, especially when it comes to spatial scaling. We predict that host-associated microbiomes will exhibit shallower species area relationships than free-living microbiomes due to strong host filtering, and that the species area relationships of bacteria will be shallower than fungi due primarily to differences in dispersal ability. We test these predictions in a relatively simple field system where bromeliad phytotelmata comprise aquatic ecosystems that support invertebrates and environmental substrates such as detritus. Larger phytotelmata generate larger habitat islands for microbiomes allowing us to explicitly examine their species area relationships. We find that the species area relationships of free-living and host-associated microbiomes differ, as do those of microbiome members. By assessing the relationship between environmental conditions and richness, and measuring diversity across scales, we posit that these observed differences in species area relationships are owed to differences in realized niches and dispersal abilities among microbes. These findings highlight that the classic laws of biological spatial scaling do not necessarily accurately represent microbiomes, and that the influence of area on diversity appears to be more important for some microbiomes and microbes than others. 

Abstract Food webs govern interactions among organisms and drive energy fluxes within ecosystems. With an increasing appreciation for the role of symbiotic microbes in host metabolism and development, it is imperative to understand the extent to which microbes conform to, and potentially influence, canonical food web efficiencies and structures. Here, we investigate whether bacteria and their taxa and functional genes are compositionally nested within a simple model food web hierarchy, and the extent to which this is predicted by the trophic position of the host. Using shotgun and amplicon sequencing of discrete food web compartments within replicate tank bromeliads, we find that both taxonomy and function are compositionally nested and largely mirror the pyramid-shaped distribution of food webs. Further, nearly the entirety of bacterial taxa and functional genes associated with hosts are contained within host-independent environmental samples. Community composition of bacterial taxa did not significantly correlate with that of functional genes, indicating a high likelihood of functional redundancy. Whereas bacterial taxa were shaped by both location and trophic position of their host, functional genes were not spatially structured. Our work illustrates the advantages of applying food web ecology to predict patterns of overlapping microbiome composition among unrelated hosts and distinct habitats. Because bacterial symbionts are critical components of host metabolic potential, this result raises important questions about whether bacterial consortia are shaped by the same energetic constraints as hosts, and whether they play an active role in food web efficiency. 

Abstract The potential promise of the microbiome to ameliorate a wide range of societal and ecological challenges, from disease prevention and treatment to the restoration of entire ecosystems, hinges not only on microbiome engineering but also on the stability of beneficial microbiomes. Yet the properties of microbiome stability remain elusive and challenging to discern due to the complexity of interactions and often intractable diversity within these communities of bacteria, archaea, fungi, and other microeukaryotes. Networks are powerful tools for the study of complex microbiomes, with the potential to elucidate structural patterns of stable communities and generate testable hypotheses for experimental validation. However, the implementation of these analyses introduces a cascade of dichotomies and decision trees due to the lack of consensus on best practices. Here, we provide a road map for network-based microbiome studies with an emphasis on discerning properties of stability. We identify important considerations for data preparation, network construction, and interpretation of network properties. We also highlight remaining limitations and outstanding needs for this field. This review also serves to clarify the varying schools of thought on the application of network theory for microbiome studies and to identify practices that enhance the reproducibility and validity of future work. 

Abstract Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m³of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition. 

Abstract Fungi are among the most diverse and ecologically important kingdoms in life. However, the distributional ranges of fungi remain largely unknown as do the ecological mechanisms that shape their distributions^1,2. To provide an integrated view of the spatial and seasonal dynamics of fungi, we implemented a globally distributed standardized aerial sampling of fungal spores³. The vast majority of operational taxonomic units were detected within only one climatic zone, and the spatiotemporal patterns of species richness and community composition were mostly explained by annual mean air temperature. Tropical regions hosted the highest fungal diversity except for lichenized, ericoid mycorrhizal and ectomycorrhizal fungi, which reached their peak diversity in temperate regions. The sensitivity in climatic responses was associated with phylogenetic relatedness, suggesting that large-scale distributions of some fungal groups are partially constrained by their ancestral niche. There was a strong phylogenetic signal in seasonal sensitivity, suggesting that some groups of fungi have retained their ancestral trait of sporulating for only a short period. Overall, our results show that the hyperdiverse kingdom of fungi follows globally highly predictable spatial and temporal dynamics, with seasonality in both species richness and community composition increasing with latitude. Our study reports patterns resembling those described for other major groups of organisms, thus making a major contribution to the long-standing debate on whether organisms with a microbial lifestyle follow the global biodiversity paradigms known for macroorganisms^4,5. 

Abstract Metazoans rely on interactions with microorganisms through multiple life stages. For example, developmental trajectories of mosquitoes can vary depending on the microorganisms available during their aquatic larval phase. However, the role that the local environment plays in shaping such host-microbe dynamics and the consequences for the host organism remain inadequately understood. Here, we examine the influence of abiotic factors, locally available bacteria, and their interactions on the development and associated microbiota of the mosquito Aedes albopictus. Our findings reveal that leaf detritus infused into the larval habitat water, sourced from native Hawaiian tree ‘ōhi‘a lehua Metrosideros polymorpha, invasive strawberry guava Psidium cattleianum, or a pure water control, displayed a more substantial influence than either temperature variations or simulated microbial dispersal regimes on bacterial community composition in adult mosquitoes. However, specific bacteria exhibited divergent patterns within mosquitoes across detrital infusions that did not align with their abundance in the larval habitat. Specifically, we observed a higher relative abundance of a Chryseobacterium sp. strain in mosquitoes from the strawberry guava infusion than the pure water control, whereas the opposite trend was observed for a Pseudomonas sp. strain. In a follow-up experiment, we manipulated the presence of these two bacterial strains and found larval developmental success was enhanced by including the Chryseobacterium sp. strain in the strawberry guava infusion and the Pseudomonas sp. strain in the pure water control. Collectively, these data suggest that interactions between abiotic factors and microbes of the larval environment can help shape mosquito populations' success. 

Abstract The dominant benthic primary producers in coral reef ecosystems are complex holobionts with diverse microbiomes and metabolomes. In this study, we characterize the tissue metabolomes and microbiomes of corals, macroalgae, and crustose coralline algae via an intensive, replicated synoptic survey of a single coral reef system (Waimea Bay, Oʻahu, Hawaii) and use these results to define associations between microbial taxa and metabolites specific to different hosts. Our results quantify and constrain the degree of host specificity of tissue metabolomes and microbiomes at both phylum and genus level. Both microbiome and metabolomes were distinct between calcifiers (corals and CCA) and erect macroalgae. Moreover, our multi-omics investigations highlight common lipid-based immune response pathways across host organisms. In addition, we observed strong covariation among several specific microbial taxa and metabolite classes, suggesting new metabolic roles of symbiosis to further explore. 

Microbes are found in nearly every habitat and organism on the planet, where they are critical to host health, fitness, and metabolism. In most organisms, few microbes are inherited at birth; instead, acquiring microbiomes generally involves complicated interactions between the environment, hosts, and symbionts. Despite the criticality of microbiome acquisition, we know little about where hosts’ microbes reside when not in or on hosts of interest. Because microbes span a continuum ranging from generalists associating with multiple hosts and habitats to specialists with narrower host ranges, identifying potential sources of microbial diversity that can contribute to the microbiomes of unrelated hosts is a gap in our understanding of microbiome assembly. Microbial dispersal attenuates with distance, so identifying sources and sinks requires data from microbiomes that are contemporary and near enough for potential microbial transmission. Here, we characterize microbiomes across adjacent terrestrial and aquatic hosts and habitats throughout an entire watershed, showing that the most species-poor microbiomes are partial subsets of the most species-rich and that microbiomes of plants and animals are nested within those of their environments. Furthermore, we show that the host and habitat range of a microbe within a single ecosystem predicts its global distribution, a relationship with implications for global microbial assembly processes. Thus, the tendency for microbes to occupy multiple habitats and unrelated hosts enables persistent microbiomes, even when host populations are disjunct. Our whole-watershed census demonstrates how a nested distribution of microbes, following the trophic hierarchies of hosts, can shape microbial acquisition. 

Advances in metagenomic sequencing have provided an unprecedented view of the microbial world, but untangling the web of microbe interdependencies and the complex relationship between microbiome and host is a major challenge in biology. New statistical methods are needed to analyze metagenomic data and infer these relationships. Focusing on amplicon sequencing data, we present methods for leveraging phylogenetic information in deep neural network models and for transfer learning from large data repositories. This approach is demonstrated in experiments using data from the Earth Microbiome Project (EMP) and a dataset of 1500 samples from Waimea Valley on the island of Oahu, Hawaii.