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Microbial Data Synthesis and Meta-analysis for the Biodiversity Exploratories

Subject Area Microbial Ecology and Applied Microbiology
Term from 2014 to 2020
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 252263987
 
Final Report Year 2022

Final Report Abstract

MicroSYSteM was designed as a separate synthesis and meta-analysis project within the Biodiversity Exploratories to focus on soil microbial diversity. For most soil bacteria, the actual habitat adaptations have largely remained unresolved due to the fact that only about 18,000 of the estimated up to 10^9 bacterial species have been described to date. To determine niche spaces of a large number of 4154 different types of Acidobacteria as a model group, we used the occurrence patterns of bacterial sequence types along gradients of 41 environmental variables and employed a niche modeling approach that yielded values for optimum activity for each variable. Although the evolution of habitat adaptation was mainly cladogenic, it was disrupted by recurrent events of convergent evolution that resulted in frequent habitat switching within individual clades of Acidobacteria. Our findings indicate that the high diversity of soil acidobacterial communities is largely sustained by differential habitat adaptation even at the level of closely related species. One of the largest knowledge gaps to date is the lack of understanding of the link between microbial community composition and ecosystem processes. It is unclear how changes in the relative composition of microbial communities can be predicted to affect soil processes. Since only a fraction of soil bacteria is active and thus contributes to ecosystem process, we utilized the ratio of the 16S rRNA gene transcripts to 16S rRNA genes (the rRNA/rDNA ratio) as an indicator of cellular ribosome content which in turn reflects potential activity. It was necessary to develop a novel statistical procedure to distinguish reliable values from those that were false positive due stochastic sequencing noise. Approximately 1% of the bacterial richness at sequence variant level was classified to be active. Statistical modeling of response variables that describe key ecosystem functions like respiration or biomass degradation, revealed that the counts of active taxa had the strongest explanatory power for soil respiration and enzymatic activities related to the carbon cycle (glucosidase, xylosidase and chitinase), whereas community composition (richness of rDNA sequences) had only low predictive power. Interactions between microorganisms in densely populated habitats such as soils likely represent important drivers of microbial community structure and function. Improved network analysis was used to construct networks for 206,849 bacterial and 19,791 fungal sequence variants in all 300 Experimental Plots of the Exploratories and to identify potential interactions between microorganisms and the specific microbial keystone sequence variants in different types of soils. Notably, the keystone sequence variants often correlated with active sequence variants (as identified by their high rRNA/rDNA ratio), thereby providing independent evidence for a key role of these sequence variants in the interaction network because of their specific activity. Since co-occurrence may only reflect similar responses towards environmental pressures rather than direct interaction, however, we also developed a novel framework for the analysis of interactions as a function of differences in environmental conditions. This framework is based on a generalized Lotka-Volterra approach and can accomodate large datasets from the Exploratories.

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