Ecological landscape explains aquifers microbial structure.

Aquifers have significant social, economic, and ecological importance. They supply 30 % of the freshwater for human consumption worldwide, including agricultural and industrial use. Despite aquifers' importance, the relationships between aquifer categories and their inhabiting microbial communities are still unknown. Characterizing variations within microbial communities' function and taxonomy structure at different aquifers could give a panoramic view of patterns that may enable the detection and prediction of environmental impact caused by multiple sources. Using publicly available shotgun metagenomic datasets, we examined whether soil properties, land use, and climate variables would have a more significant influence on the taxonomy and functional structure of the microbial communities than the ecological landscapes of the aquifer (i.e., Karst, Porous, Saline, Geyser, and Porous Contaminated). We found that these categories are stronger predictors of microbial communities' structure than geographical localization. In addition, our results show that microbial richness and dominance patterns are the opposite of those found in multicellular life, where extreme habitats harbour richer functional and taxonomic microbial communities. We found that low-abundant and recently described candidate taxa, such as the chemolithoautotrophic genus Candidatus Altiarcheum and the Candidate phylum Parcubacteria, are the main contributors to aquifer microbial communities' dissimilarities. Genes related to gram-negative bacteria proteins, cell wall structures, and phage activity were the primary contributors to aquifer microbial communities' dissimilarities among the aquifers' ecological landscapes. The results reported in the present study highlight the utility of using ecological landscapes for investigating aquifer microbial communities. In addition, we suggest that functions played by recently described and low abundant bacterial groups need further investigation once they might affect water quality, geochemical cycles, and the effects of anthropogenic disturbances such as pollution and climatic events on aquifers.

Integrating Computational Methods to Investigate the Macroecology of Microbiomes.

Studies in microbiology have long been mostly restricted to small spatial scales. However, recent technological advances, such as new sequencing methodologies, have ushered an era of large-scale sequencing of environmental DNA data from multiple biomes worldwide. These global datasets can now be used to explore long standing questions of microbial ecology. New methodological approaches and concepts are being developed to study such large-scale patterns in microbial communities, resulting in new perspectives that represent a significant advances for both microbiology and macroecology. Here, we identify and review important conceptual, computational, and methodological challenges and opportunities in microbial macroecology. Specifically, we discuss the challenges of handling and analyzing large amounts of microbiome data to understand taxa distribution and co-occurrence patterns. We also discuss approaches for modeling microbial communities based on environmental data, including information on biological interactions to make full use of available Big Data. Finally, we summarize the methods presented in a general approach aimed to aid microbiologists in addressing fundamental questions in microbial macroecology, including classical propositions (such as "everything is everywhere, but the environment selects") as well as applied ecological problems, such as those posed by human induced global environmental changes.