No abstract

Microorganisms in wastewater treatment plants (WWTPs) are essential for water purification to protect public and environmental health. However, their diversity and the factors that control it are poorly understood. Using a systematic global-sampling effort, we analyzed the 16S rRNA gene sequences from ~1,200 activated sludge samples taken from 269 WWTPs in 23 countries on 6 continents. Our analyses revealed that the global activated sludge bacterial communities contain ~1 billion bacterial phylotypes with a Poisson lognormal diversity distribution. Despite this high diversity, activated sludge has a small global core bacterial community (n = 28 OTUs) that is strongly linked to activated sludge performance. Meta-analyses with global datasets associate the activated sludge microbiomes most closely to freshwater populations. In contrast to macroorganism diversity, activated sludge bacterial communities show no latitudinal gradient. Furthermore, their spatial turnover is scale-dependent and appears to be largely driven by stochastic processes (dispersal, drift), although deterministic factors (temperature, organic input) also are important. Our findings enhance mechanistic understanding of the global diversity and biogeography of activated sludge bacterial communities within a theoretical ecology framework and have important implications for microbial ecology and wastewater treatment processes.

Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.

Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore the potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C-cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations, whereas ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by Canonical correspondence analysis, Mantel tests and the similarity tests that soil pH, temperature, NH 4 þ -N and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. On the basis of these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N-cycling genes and consequently microbe-mediated soil N dynamics.

Microbes play key roles in various biogeochemical processes, including carbon (C) and nitrogen (N) cycling. However, changes of microbial community at the functional gene level by livestock grazing, which is a global land-use activity, remain unclear. Here we use a functional gene array, GeoChip 4.0, to examine the effects of free livestock grazing on the microbial community at an experimental site of Tibet, a region known to be very sensitive to anthropogenic perturbation and global warming. Our results showed that grazing changed microbial community functional structure, in addition to aboveground vegetation and soil geochemical properties. Further statistical tests showed that microbial community functional structures were closely correlated with environmental variables, and variations in microbial community functional structures were mainly controlled by aboveground vegetation, soil C/N ratio, and NH 4 + -N. In-depth examination of N cycling genes showed that abundances of N mineralization and nitrification genes were increased at grazed sites, but denitrification and N-reduction genes were decreased, suggesting that functional potentials of relevant bioprocesses were changed. Meanwhile, abundances of genes involved in methane cycling, C fixation, and degradation were decreased, which might be caused by vegetation removal and hence decrease in litter accumulation at grazed sites. In contrast, abundances of virulence, stress, and antibiotics resistance genes were increased because of the presence of livestock. In conclusion, these results indicated that soil microbial community functional structure was very sensitive to the impact of livestock grazing and revealed microbial functional potentials in regulating soil N and C cycling, supporting the necessity to include microbial components in evaluating the consequence of land-use and/or climate changes.

Background The newly defined superphylum Patescibacteria such as Parcubacteria (OD1) and Microgenomates (OP11) has been found to be prevalent in groundwater, sediment, lake, and other aquifer environments. Recently increasing attention has been paid to this diverse superphylum including > 20 candidate phyla (a large part of the candidate phylum radiation, CPR) because it refreshed our view of the tree of life. However, adaptive traits contributing to its prevalence are still not well known. Results Here, we investigated the genomic features and metabolic pathways of Patescibacteria in groundwater through genome-resolved metagenomics analysis of > 600 Gbp sequence data. We observed that, while the members of Patescibacteria have reduced genomes (~ 1 Mbp) exclusively, functions essential to growth and reproduction such as genetic information processing were retained. Surprisingly, they have sharply reduced redundant and nonessential functions, including specific metabolic activities and stress response systems. The Patescibacteria have ultra-small cells and simplified membrane structures, including flagellar assembly, transporters, and two-component systems. Despite the lack of CRISPR viral defense, the bacteria may evade predation through deletion of common membrane phage receptors and other alternative strategies, which may explain the low representation of prophage proteins in their genomes and lack of CRISPR. By establishing the linkages between bacterial features and the groundwater environmental conditions, our results provide important insights into the functions and evolution of this CPR group. Conclusions We found that Patescibacteria has streamlined many functions while acquiring advantages such as avoiding phage invasion, to adapt to the groundwater environment. The unique features of small genome size, ultra-small cell size, and lacking CRISPR of this large lineage are bringing new understandings on life of Bacteria. Our results provide important insights into the mechanisms for adaptation of the superphylum in the groundwater environments, and demonstrate a case where less is more, and small is mighty.

Soil microbial respiration is an important source of uncertainty in projecting future climate and carbon (C) cycle feedbacks. However, its feedbacks to climate warming and underlying microbial mechanisms are still poorly understood. Here we show that the temperature sensitivity of soil microbial respiration (Q10) in a temperate grassland ecosystem persistently decreases by 12.0 ± 3.7% across 7 years of warming. Also, the shifts of microbial communities play critical roles in regulating thermal adaptation of soil respiration. Incorporating microbial functional gene abundance data into a microbially-enabled ecosystem model significantly improves the modeling performance of soil microbial respiration by 5–19%, and reduces model parametric uncertainty by 55–71%. In addition, modeling analyses show that the microbial thermal adaptation can lead to considerably less heterotrophic respiration (11.6 ± 7.5%), and hence less soil C loss. If such microbially mediated dampening effects occur generally across different spatial and temporal scales, the potential positive feedback of soil microbial respiration in response to climate warming may be less than previously predicted.

It is of great interest to elucidate underlying mechanisms to maintain stability of anaerobic digestion, an important process in waste treatment. By operating triplicate anaerobic digesters continuously for two years, we found that microbial community composition shifted over time despite stable process performance. Using an association network analysis to evaluate microbial interactions, we detected a clear successional pattern, which exhibited increasing modularity but decreasing connectivity among microbial populations. Phylogenetic diversity was the most important factor associated with network topology, showing positive correlations with modularity but negative correlations with network complexity, suggesting induced niche differentiation over time. Positive, but not negative, correlation strength was significantly related (p < 0.05) to phylogeny. Furthermore, among populations exhibiting consistent positive correlations across networks, close phylogenetic linkages were evident (e.g. Clostridiales organisms). Clostridiales organisms were also identified as keystone populations in the networks (i.e., they had large effects on other species), suggestive of an important role in maintaining process stability. We conclude that microbial interaction dynamics of anaerobic digesters evolves over time during stable process performance.