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Large water diversion projects are important constructions for reallocation of human-essential water resources. Deciphering microbiota dynamics and assembly mechanisms underlying canal water ecosystem services especially during long-distance diversion is the prerequisite for water quality monitoring, biohazard warning and sustainable management. Using a 1432-km canal of the South-to-North Water Diversion Projects as a model system, we answer three central questions: how bacterial and micro-eukaryotic communities spatio-temporally develop, how much ecological stochasticity contributes to microbiota assembly, and which immigrating populations better survive and navigate across the canal. We applied quantitative ribosomal RNA gene sequence analyses to investigate canal water microbial communities sampled over a year, as well as null model- and neutral model-based approaches to disentangle the microbiota assembly processes. Our results showed clear microbiota dynamics in community composition driven by seasonality more than geographic location, and seasonally dependent influence of environmental parameters. Overall, bacterial community was largely shaped by deterministic processes, whereas stochasticity dominated micro-eukaryotic community assembly. We defined a local growth factor (LGF) and demonstrated its innovative use to quantitatively infer microbial proliferation, unraveling taxonomically dependent population response to local environmental selection across canal sections. Using LGF as a quantitative indicator of immigrating capacities, we also found that most micro-eukaryotic populations (82%) from the source lake water sustained growth in the canal and better acclimated to the hydrodynamical water environment than bacteria (67%). Taxa inferred to largely propagate include Limnohabitans sp. and Cryptophyceae, potentially contributing to water auto-purification. Combined, our work poses first and unique insights into the microbiota assembly patterns and dynamics in the world's largest water diversion canal, providing important ecological knowledge for long-term sustainable water quality maintenance in such a giant engineered system.
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... Therefore, the protection of water quality and aquatic ecosystem health in the Danjiangkou Reservoir is extremely important, which is an important part of the ecological management of major rivers in China . Previous studies on the Danjiangkou Reservoir mainly focused on the evaluation of water quality, the structural characteristics of phytoplankton and zooplankton communities , but rarely on organic carbon. ...
Dynamic changes in total organic carbon (TOC) concentration in lakes and reservoirs affect the functions of aquatic ecosystems and are a key component of water quality management, especially in drinking water sources. The Danjiangkou Reservoir is the water source area of the Middle Route Project of the South-to-North Water Diversion in China. Its water quality is of critical importance to the safety of water diversion. TOC concentration and other environmental factors at 19 sampling sites in the Danjiangkou Reservoir were investigated quarterly during 2020–2021 to explore the differences at the spatio-temporal scales. A generalized additive model (GAM) was used to analyze the environmental factors correlated with the observed spatio-temporal variations of TOC concentration. The results showed that the comprehensive trophic level index (TLI) of the Danjiangkou Reservoir was under the state of intermediate nutrition, and the water quality was overall good. In terms of temporal patterns, TOC concentration was higher in both spring and summer and lower in other seasons. Spatially, TOC concentrations were found in descending order from the site of outlet, Han reservoir, entrance of reservoir, and Dan reservoir. The single-factor GAM model showed that TOC correlated with different environmental factors across spatio-temporal scales. Water temperature (WT), permanganate index (CODMn), and ammonia nitrogen (NH4+-N) were significantly correlated with TOC in autumn, but only total nitrogen (TN) and transparency (SD) were significant in winter. Spatially, WT, chemical oxygen demand (COD), NH4+-N, TN, and conductivity (Cond) correlated with TOC in the Dan reservoir, but WT, COD, NH4+-N, total phosphorus (TP), and chlorophyll a (Chl.a) were significant in the Han reservoir. The multi-factor GAM model indicated that the environmental factors correlated with TOC concentration were mainly WT, TN, Cond, CODMn, and TP, among which WT and Cond showed a significant linear relationship with TOC concentration (edf = 1, p < 0.05), while TN, CODMn, and TP had a significant nonlinear relationship with TOC concentration (edf > 1, p < 0.05). Comprehensive trophic level index (TLI) and TOC concentration revealed a highly significant correlation (R2 = 0.414, p < 0.001). Therefore, the GAM model could well explain the environmental factors associated with the spatio-temporal dynamics of TOC concentration, providing a reference for the evaluation of water quality and research on the carbon cycle in similar inland reservoirs.
As the water source for the Middle Route Project of the South-to-North Water Diversion Project (MR-SNWD) of China, the Danjiangkou Reservoir (DJR) is in the process of ecosystem reassembly, but the composition, function, and assembly mechanisms of bacterioplankton communities are not yet clear. In this study, the composition, distribution characteristics and influencing factors of bacterioplankton communities were analyzed by high-throughput sequencing (HTS); PICRUSt2 was used to predict community function; a molecular ecological network was used to analyze bacterioplankton interactions; and the assembly process of bacterioplankton communities was estimated with a neutral model. The results indicated that the communities, function and interaction of bacterioplankton in the DJR had significant annual and seasonal variations and that the seasonal differences were greater than that the annual differences. Excessive nitrogen (N) and phosphorus (P) nutrients in the DJR are the most important factors affecting water quality in the reservoir, N and P nutrients are the main factors affecting bacterial communities. Season is the most important factor affecting bacterioplankton N and P cycle functions. Ecological network analysis indicated that the average clustering coefficient and average connectivity of the spring samples were lower than those of the autumn samples, while the number of modules for the spring samples was higher than that for the autumn samples. The neutral model explained 66.3%, 63.0%, 63.0%, and 70.9% of the bacterioplankton community variations in samples in the spring of 2018, the autumn of 2018, the spring of 2019, and the autumn of 2019, respectively. Stochastic processes dominate bacterioplankton community assembly in the DJR. This study revealed the composition, function, interaction, and assembly of bacterioplankton communities in the DJR, providing a reference for the protection of water quality and the ecological functions of DJR bacterioplankton.
Immigration has been recently recognized as an important ecological process that affects the microbial community structure in diverse ecosystems. However, the fate of microbial immigrants in the new environment and their involvement in the local biochemical network remain unclear. In this study, we performed meta-omics-supervised characterization of immigrants' activities in anaerobic sludge digesters. Metagenomic analyses revealed that immigrants from the feed sludge accounted for the majority of populations capable of anaerobic respiration in a digester. Electron acceptors that were predicted to be respired, including nitrate, nitrite, sulfate, and elemental sulfur, were added to digester sludge in batch tests. Consumption of up to 91% of the added electron acceptors was observed within the experiment period. 16S rRNA sequencing detected populations that were stimulated by the electron acceptors, largely overlapping with respiration-capable immigrants identified by metagenomic analysis. Metatranscriptomic analysis of the batch tests provided additional evidence for upregulated expression of respiration genes and concomitant suppressed expression of methanogenesis. Anaerobic respiration activity was further evaluated in full-scale digesters in nine wastewater treatment plants. Although nitrate and sulfate respiration were ubiquitous, the expression level of respiration genes was generally 2-3 orders of magnitude lower than the expression of methanogenesis in most digesters, suggesting marginal ecological roles by immigrants in full-scale digester ecosystems.
The genomic scale metabolic networks of the microorganisms can be constructed based on their genome sequences, functional annotations, and biochemical reactions, reflecting almost all of the metabolic functions. Mathematical simulations of metabolic fluxes could make these functions be visualized, thereby providing guidance for rational engineering design and experimental operations. This review summarized recently developed flux simulation algorithms of microbial systems. For the single microbial systems, the optimal planning algorithm has low complexity because there is no interaction between microorganisms, and it can quickly simulate the stable metabolic states through the pseudo-steady hypothesis. Besides, the experimental conditions of single microbial systems are easier to reach or close to the optimal states of simulation, compared with polymicrobial systems. The polymicrobial culture systems could outcompete the single microbial systems as they could relieve metabolic pressure through metabolic division, resource exchange, and complex substrate co-utilization. Besides, they provide varieties of intracellular production environments, which render them the potential to achieve efficient bioproduct synthesis. However, due to the quasi-steady hypothesis that restricts the simulation of the dynamic processes of microbial interactions and the algorithm complexity, there are few researches on simulation algorithms of polymicrobial metabolic fluxes. Therefore, this review also analyzed and combed the microbial interactions based on the commonly used hypothesis of maximizing growth rates, and studied the strategies of coupling interactions with optimal planning simulations to metabolism. Finally, this review provided new insights for the genomic scale metabolic flux simulations of polymicrobial systems.
The occurrence of antibiotics in groundwater has significant spatial variability, owing to the complexity of pollutant properties, pollution sources and groundwater recharge and discharge conditions. This study aimed to identify the relationship between antibiotic occurrence and hydrochemistry in groundwater. Thus, we undertook this study in a characteristic alluvial-diluvial aquifer where groundwater receives unidirectional recharge from surface water. In total, 47 samples were collected from the Hutuo River before and after an artificial replenishment project. We screened up to four classes of antibiotics and detected 28 types. The statistical analysis of antibiotic concentrations, indicated that there were two pollution areas. Next, we discussed the results pertaining to the occurrence and source of antibiotics by comparing them with hydrochemical data. In the study area, a positive correlation has been found between inorganic compounds, as SO4²⁻ and Cl⁻, and the most mobile antibiotics given that both share the same source. This shows that a previous sound geochemical study may provide evidence of the extend of antibiotic occurrence, as in the Hutuo River aquifer. The relationship between antibiotics and hydrochemistry in groundwater is determined by recharge sources (rainwater and surface water contaminated with antibiotics). Antibiotics from wastewater treatment plants enter groundwater indirectly through surface water with high SO4²⁻ in lightly polluted areas, while in heavily polluted areas, there are high concentrations of inorganic components in garbage leachate and wastewater leakage that carry antibiotics directly into groundwater. In summarized, the relationship between antibiotics and hydrochemistry observed in this study shows that a previous sound geochemical study may provide evidence of the extend of antibiotic occurrence.
Periphytic algae exist widely in different waters. However, little is known about periphytic algae in long-distance water diversion channels across watersheds. We investigated the periphytic algae and the environmental factors at twenty sampling sites in the middle route of the South-to-North Water Diversion Project (MRP). The dominant species were Desmodesmus intermedius (Hegewald), Calothrix thermalis (Bornet & Flahault), Calothrix parietina (Bornet & Flahault) and Leptolyngbya benthonica (Anagnostidis) (dominance > 0.02) as measured in a whole year. Habitat heterogeneity in the MRP led to lower spatial heterogeneity and higher temporal heterogeneity of the periphytic algal community. Stochastic processes are the major process in periphytic community assembly. In deterministic processes, homogeneous selection had the major role in structuring the periphytic community, whereas the role of heterogeneous selection was less significant. In stochastic processes, dispersal limitations had the major role in structuring the periphytic community, whereas the role of homogenizing dispersal and drift were less significant. The variation in total nitrogen and total phosphorus promoted more stochastic processes (−1.96 < βNTI < 1.96). The variations in water temperature and water velocity promoted more heterogeneous selection (βNTI > 1.96). In integrating all of this empirical evidence, we explore the role of environmental factors in the action of ecological processes shaping thecommunity assembly of the periphytic algal community.
The bacteria in the water column and surface sediments are inherently intertwined and inseparable in aquatic ecosystems, yet little is known about the integrated spatiotemporal dynamics and driving mechanisms of both planktonic and sedimentary bacterial communities in reservoirs. By investigating the planktonic and sedimentary bacteria during four seasons from 88 samples of 11 representative sites across the Danjiangkou reservoir, we depicted an integrated biogeographic pattern of bacterial communities in the water source of the world's largest water diversion project. Our study revealed both planktonic (mantel r = 0.502, P = 0.001) and sedimentary (mantel r = 0.131, P = 0.009) bacterial communities were significantly correlated with environmental heterogeneity, but a weak disparity along spatial heterogeneity, and the significant seasonal dynamics of planktonic (mantel r = 0.499, P = 0.001) rather than sedimentary bacteria. Particularly, rare biosphere played a main role in determining the community succession in the reservoir. It not only exhibited a more striking environmental separation than abundant taxa but also was an essential part in mediating spatiotemporal shifts of planktonic bacteria and maintaining the stability of bacterial community. These rare bacteria were respectively mediated by stochastic (62.68%) and selective (79.60%) processes in water and sediments despite abundant taxa being largely determined by stochastic processes (86.88%−93.96%). Overall, our study not only fills a gap in understanding the bacterial community dynamics and underlying drivers in source water reservoirs, but also highlights the particular importance of rare bacteria in mediating biogeochemical cycles in world's large reservoir ecosystems.
Mainstream anaerobic ammonium oxidation (anammox) represents one of the most promising energy-efficient mechanisms of fixed nitrogen elimination from wastewaters. However, little is known about the exact processes and drivers of microbial community assembly within the complex microbial biofilms that support anammox in engineered ecosystems. Here, we followed anammox biofilm development on fresh carriers in an established 8m³ mainstream anammox reactor that is exposed to seasonal temperature changes (∼25-12°C) and varying NH4⁺ concentrations (5-25 mg/L). We use fluorescence in situ hybridization and 16S rRNA gene sequencing to show that three distinct stages of biofilm development emerge naturally from microbial community composition and biofilm structure. Neutral modelling and network analysis are employed to elucidate the relative importance of stochastic versus deterministic processes and synergistic and antagonistic interactions in the biofilms during their development. We find that the different phases are characterized by a dynamic succession and an interplay of both stochastic and deterministic processes. The observed growth stages (Colonization, Succession and Maturation) appear to be the prerequisite for the anticipated growth of anammox bacteria and for reaching a biofilm community structure that supports the desired metabolic and functional capacities observed for biofilm carriers already present in the system (∼100gNH4-N m³ d⁻¹). We discuss the relevance of this improved understanding of anammox-community ecology and biofilm development in the context of its practical application in the start-up, configuration, and optimization of anammox biofilm reactors.
The hadal zone, mostly comprising of deep trenches and constituting of the deepest part of the world’s oceans, represents the least explored habitat but one of the last frontiers on our planet. The present scientific understanding of the hadal environment is still relatively rudimentary, particularly in comparison with that of shallower marine environments. In the last 30 years, continuous efforts have been launched in deepening our knowledge regarding the ecology of the hadal trench. However, the geological and environmental processes that potentially affect the sedimentary, geochemical and biological processes in hadal trenches have received less attention. Here, we review recent advances in the geology, biology, and environment of hadal trenches and offer a perspective of the hadal science involved therein. For the first time, we release high-definition images taken by a new full-ocean-depth manned submersible Fendouzhe that reveal novel species with an unexpectedly high density, outcrops of mantle and basaltic rocks, and anthropogenic pollutants at the deepest point of the world’s ocean. We advocate that the hydration of the hadal lithosphere is a driving force that influences a variety of sedimentary, geochemical, and biological processes in the hadal trench. Hadal lithosphere might host the Earth’s deepest subsurface microbial ecosystem. Future research, combined with technological advances and international cooperation, should focus on establishing the intrinsic linkage of the geology, biology, and environment of the hadal trenches.
Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems.
With the application and development of high-throughput sequencing technology in life and health sciences, massive multi-omics data brings the problem of efficient management and utilization. Database development and biocuration are the prerequisites for the reuse of these big data. Here, relying on China National GeneBank (CNGB), we present CNGB Sequence Archive (CNSA) for archiving omics data, including raw sequencing data and its further analyzed results which are organized into six objects, namely Project, Sample, Experiment, Run, Assembly and Variation at present. Moreover, CNSA has created a correlation model of living samples, sample information and analytical data on some projects. Both living samples and analytical data are directly correlated with the sample information. From either one, information or data of the other two can be obtained, so that all data can be traced throughout the life cycle from the living sample to the sample information to the analytical data. Complying with the data standards commonly used in the life sciences, CNSA is committed to building a comprehensive and curated data repository for storing, managing and sharing of omics data. We will continue to improve the data standards and provide free access to open-data resources for worldwide scientific communities to support academic research and the bio-industry.
Database URL: https://db.cngb.org/cnsa/.
A fundamental goal in microbiome studies is determining which microbes affect host physiology. Standard methods for determining changes in microbial taxa measure relative, rather than absolute abundances. Moreover, studies often analyze only stool, despite microbial diversity differing substantially among gastrointestinal (GI) locations. Here, we develop a quantitative framework to measure absolute abundances of individual bacterial taxa by combining the precision of digital PCR with the high-throughput nature of 16S rRNA gene amplicon sequencing. In a murine ketogenic-diet study, we compare microbial loads in lumenal and mucosal samples along the GI tract. Quantitative measurements of absolute (but not relative) abundances reveal decreases in total microbial loads on the ketogenic diet and enable us to determine the differential effects of diet on each taxon in stool and small-intestine mucosa samples. This rigorous quantitative microbial analysis framework, appropriate for diverse GI locations enables mapping microbial biogeography of the mammalian GI tract and more accurate analyses of changes in microbial taxa in microbiome studies. Changes in microbial taxa are commonly derived from estimations of relative abundance, which inherently limits the depth of the analysis. Here, the authors present an absolute quantification method based on digital PCR anchoring and 16S rRNA gene sequencing and show how a ketogenic diet affects individual taxon’s absolute abundance in stool and small-intestine mucosa samples in mice
Studies of marine benthic archaeal communities are updating our view of their taxonomic composition and metabolic versatility. However, large knowledge gaps remain with regard to community assembly processes and inter taxa associations. Here, using 16S rRNA gene amplicon sequencing and qPCR, we investigated the spatiotemporal dynamics, assembly processes, and co-occurrence relationships of the archaeal community in 58 surface sediment samples collected in both summer and winter from across ~1500 km of the eastern Chinese marginal seas. Clear patterns in spatiotemporal dynamics in the archaeal community structure were observed, with a more pronounced spatial rather than seasonal variation. Accompanying the geographic variation was a significant distance-decay pattern with varying contributions from different archaeal clades, determined by their relative abundance. In both seasons, dispersal limitation was the most important process, explaining ~40% of the community variation, followed by homogeneous selection and ecological drift, that made an approximately equal contribution (~30%). This meant that stochasticity rather than determinism had a greater impact on the archaeal community assembly. Furthermore, we observed seasonality in archaeal co-occurrence patterns: closer inter-taxa connections in winter than in summer, and unmatched geographic patterns between community composition and co-occurrence relationship. These results demonstrate that the benthic archaeal community was assembled under a seasonal-consistent mechanism but the co-occurrence relationships changed over the seasons, indicating complex archaeal dynamic patterns in coastal sediments of the eastern Chinese marginal seas.
Immigration is a process that can influence the assembly of microbial communities in natural and engineered environments. However, it remains challenging to quantitatively evaluate the contribution of this process to the microbial diversity and function in the receiving ecosystems. Currently used methods, i.e., counting shared microbial species, microbial source tracking, and neutral community model, rely on abundance profile to reveal the extent of overlapping between the upstream and downstream communities. Thus, they cannot suggest the quantitative contribution of immigrants to the downstream community function because activities of individual immigrants are not considered after entering the receiving environment. This limitation can be overcome by using an approach that couples a mass balance model with high-throughput DNA sequencing, i.e., ecogenomics-based mass balance. It calculates the net growth rate of individual microbial immigrants and partitions the entire community into active populations that contribute to the community function and inactive ones that carry minimal function. Linking activities of immigrants to their abundance further provides quantification of the contribution from an upstream environment to the downstream community. Considering only active populations can improve the accuracy of identifying key environmental parameters dictating process performance using methods such as machine learning.
The deep mechanisms (deterministic and/or stochastic processes) underlying community assembly are a central challenge in microbial ecology. However, the relative importance of these processes in shaping riverine microeukaryotic biogeography is still poorly understood. Here, we compared the spatiotemporal and biogeographical patterns of microeukaryotic community using high-throughput sequencing of 18S rRNA gene and multivariate statistical analyses from a subtropical river during wet and dry seasons.
Our results provide the first description of biogeographical patterns of microeukaryotic communities in the Tingjiang River, the largest river in the west of Fujian province, southeastern China. The results showed that microeukaryotes from both wet and dry seasons exhibited contrasting community compositions, which might be owing to planktonic microeukaryotes having seasonal succession patterns. Further, all components of the microeukaryotic communities (including total, dominant, always rare, and conditionally rare taxa) exhibited a significant distance-decay pattern in both seasons, and these communities had a stronger distance-decay relationship during the dry season, especially for the conditionally rare taxa. Although several variables had a significant influence on the microeukaryotic communities, the environmental and spatial factors showed minor roles in shaping the communities. Importantly, these microeukaryotic communities were strongly driven by stochastic processes, with 89.9%, 88.5%, and 89.6% of the community variation explained by neutral community model during wet, dry, and both seasons, respectively. The neutral community model also explained a large fraction of the community variation across different taxonomic groups and levels. Additionally, the microeukaryotic taxa, which were above and below the neutral prediction, were ecologically and taxonomically distinct groups, which might be interactively structured by deterministic and stochastic processes.
This study demonstrated that stochastic processes are sufficient in shaping substantial variation in river microeukaryotic metacommunity across different hydrographic regimes, thereby providing a better understanding of spatiotemporal patterns, processes, and mechanisms of microeukaryotic community in waters.
As a toxic element, excessive amounts of fluoride in environment can be harmful because of its antimicrobial activity, however little is known about the relationship between fluoride and the bacterial community in groundwater systems. Here, we use samples from a typical fluorosis area to test the hypothesis that fluoride concentration is a fundamental structuring factor for bacterial communities in groundwater. Thirteen groundwater samples were collected; high-throughput 16S rRNA gene sequencing and statistical analysis were conducted to compare the bacterial community composition in individual wells. The results showed that Proteobacteria, with most relative abundance in groundwater, decreased along the groundwater fluoride concentration. Additionally, relative abundances of 12 families were also statistically correlated with fluoride concentration. The bacterial community was significantly explained by TOC (P = 0.045) and fluoride concentration (P = 0.007) of groundwater. This suggests that fluoride and TOC likely plays an important role in shaping the microbial community structure in these groundwater systems. Our research suggest that fluoride concentration should be taken into consideration in future when evaluating microbial response to environmental conditions in groundwater system, especially for fluoride rich groundwater.
In this article, a data matrix of 20 indicators (6960 observations) was obtained from 29 water quality monitoring stations of the Middle Route (MR) of the South-to-North Water Diversion Project of China (SNWDPC). Multivariate statistical techniques including analysis of variance (ANOVA), correlation analysis (CA), and principal component analysis (PCA) were applied to understand and identify the interrelationships between the different indicators and the most contributive sources of anthropogenic and natural impacts on water quality. The water quality index (WQI) was used to assess the classification and variation of water quality. The distributions of the indicators revealed that six heavy-metal indicators including arsenic (As), mercury (Hg), cadmium (Cd), chromium (Cr), selenium (Se), and lead (Pb) were within the Class I standard, while the As, Pb, and Cd displayed spatial variation. Moreover, some physicochemical indicators such as dissolved oxygen, 5-day biochemical oxygen demand (as BOD5), and total phosphorus (TP) had spatio-temporal variability. The correlation analysis result demonstrated that As, Hg, Cd, Cr, Se, Pb, copper (Cu), and zinc (Zn) had high correlation coefficients. The PCA result extracted three principal components (PC) accounting for 82.67% of the total variance, while the first PC was indicative of the mixed sources of anthropogenic and natural contributions, the second and the third PCs were mainly controlled by human activities and natural sources, respectively. The calculation results of the WQI showed an excellent water quality of the MR of the SNWDPC where the values of the stations ranged from 10.49 to 17.93, while Hg was the key indicator to determine the WQI > 20 of six stations, which indicated that the Hg can be the main potential threat to water quality and human health in this project. The result suggests that special attention should be paid to the monitoring of Hg, and the investigation and supervision within the areas of high-density human activities in this project should be taken to control the impacts of urban and industrial production and risk sources on water quality.
Recent work has highlighted the importance of confounder control in microbiome association studies1,2. For instance, multiple pathologies previously linked to gut ecosystem dysbiosis display concomitant changes in stool consistency3–6, a major covariate of microbiome variation2,7. In those cases, observed microbiota alterations could largely reflect variation in faecal water content. Moreover, stool moisture variation has been linked to fluctuations in faecal microbial load, inducing artefacts in relative abundance profile analyses8,9. Hence, the identification of associations between the gut microbiota and specific disease manifestations in pathologies with complex aetiologies requires a deconfounded, quantitative assessment of microbiome variation. Here, we revisit a disease association microbiome data set comprising 106 patients with primary sclerosing cholangitis (PSC) and/or inflammatory bowel disease¹⁰. Assessing quantitative taxon abundances⁹, we study microbiome alterations beyond symptomatic stool moisture variation. We observe an increased prevalence of a low cell count Bacteroides 2 enterotype across the pathologies studied, with microbial loads correlating inversely with intestinal and systemic inflammation markers. Quantitative analyses allow us to differentiate between taxa associated with either intestinal inflammation severity (Fusobacterium) or cholangitis/biliary obstruction (Enterococcus) among previously suggested PSC marker genera. We identify and validate a near-exclusion pattern between the inflammation-associated Fusobacterium and Veillonella genera, with Fusobacterium detection being restricted to Crohn’s disease and patients with PSC–Crohn’s disease. Overall, through absolute quantification and confounder control, we single out clear-cut microbiome markers associated with pathophysiological manifestations and disease diagnosis.
Microorganisms in wastewater treatment plants (WWTPs) are essential for water purification to protect public and environmental health. However, the diversity of microorganisms and the factors that control it are poorly understood. Using a systematic global-sampling effort, we analysed the 16S ribosomal RNA 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 operational taxonomic units) 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 and drift), although deterministic factors (temperature and organic input) are also important. Our findings enhance our 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.
Ubiquitous in natural and engineered ecosystems, microbial immigration is one of the mechanisms shaping community assemblage. However, quantifying immigration impact remains challenging especially at individual population level. The activities of immigrants in the receiving community are often inadequately considered, leading to potential bias in identifying the relationship between community composition and environmental parameters.
This study quantified microbial immigration from an upstream full-scale anaerobic reactor to downstream activated sludge reactors. A mass balance was applied to 16S rRNA gene amplicon sequencing data to calculate the net growth rates of individual populations in the activated sludge reactors. Among the 1178 observed operational taxonomic units (OTUs), 582 had a positive growth rate, including all the populations with abundance > 0.1%. These active populations collectively accounted for 99% of the total sequences in activated sludge. The remaining 596 OTUs with a growth rate ≤ 0 were classified as inactive populations. All the abundant populations in the upstream anaerobic reactor were inactive in the activated sludge process, indicating a negligible immigration impact. We used a supervised learning regressor to predict environmental parameters based on community composition and compared the prediction accuracy based on either the entire community or the active populations. Temperature was the most predictable parameter, and the prediction accuracy was improved when only active populations were used to train the regressor.
Calculating growth rate of individual microbial populations in the downstream system provides an effective approach to determine microbial activity and quantify immigration impact. For the studied biological process, a marginal immigration impact was observed, likely due to the significant differences in the growth environments between the upstream and downstream processes. Excluding inactive populations as a result of immigration further enhanced the prediction of key environmental parameters affecting process performance.
Electronic supplementary material
The online version of this article (10.1186/s40168-019-0682-x) contains supplementary material, which is available to authorized users.
Planktonic fungi are important components of aquatic ecosystems, and analyses of their community composition and function have far-reaching significance for the ecological management and maintenance of reservoir environments. However, few studies have investigated the composition, distribution, and function of planktonic fungi in reservoir ecosystems and their relationship with water quality. Here, the composition of the planktonic fungal community in the surface water layer of the Danjiangkou Reservoir is investigated using Illumina MiSeq sequencing. According to the results, the reservoir community is primarily composed of 7 phyla, including Ascomycota, Rozellomycota, Basidiomycota, Chytridiomycota, and Zygomycota, comprising 294 genera, demonstrating the rich diversity of this community. Redundancy analysis (RDA) of the planktonic fungal community and environmental factors showed dissolved oxygen (DO), chemical oxygen demand (COD), total nitrogen (TN), chlorophyll a (Chl a), and permanganate (CODMn) to be important factors influencing the distribution of planktonic fungi. Spearman correlation analysis of the planktonic fungal community composition and diversity indices with physical and chemical water quality parameters showed that the impacts of TN, COD and DO were the most significant. The results of this study on the planktonic fungal community in the Danjiangkou Reservoir area using high-throughput sequencing revealed that the community is sensitive to water quality parameters. This result provides a reference for studying the composition and distribution of the planktonic fungal community in Danjiangkou Reservoir and its role in the biogeochemical cycle.
Microbial communities (microbiota) influence human and animal disease and immunity, geochemical nutrient cycling and plant productivity. Specific groups, including bacteria, archaea, eukaryotes or fungi, are amplified by PCR to assess the relative abundance of sub-groups (e.g. genera). However, neither the absolute abundance of sub-groups is revealed, nor can different amplicon families (i.e. OTUs derived from a specific pair of PCR primers such as bacterial 16S, eukaryotic 18S or fungi ITS) be compared. This prevents determination of the absolute abundance of a particular group and domain-level shifts in microbiota abundance can remain undetected.
We have developed absolute quantitation of amplicon families using synthetic chimeric DNA spikes. Synthetic spikes were added directly to environmental samples, co-isolated and PCR-amplified, allowing calculation of the absolute abundance of amplicon families (e.g. prokaryotic 16S, eukaryotic 18S and fungal ITS per unit mass of sample).
Spikes can be adapted to any amplicon-specific group including rhizobia from soils, Firmicutes and Bifidobacteria from human gut or Enterobacteriaceae from food samples. Crucially, using highly complex soil samples, we show that the absolute abundance of specific groups can remain steady or increase, even when their relative abundance decreases. Thus, without absolute quantitation, the underlying pathology, physiology and ecology of microbial groups may be masked by their relative abundance.
Danjiangkou Reservoir is water source of Middle Route Project of the South-to-North Water Diversion (SNWD) Project, research on the dynamic changes in the water storage within the Danjiangkou Reservoir constitutes an important guide for reservoir water volume management practices. A practical method for estimating the water storage and its dynamics was proposed in this study based on inundated areas from Moderate Resolution Imaging Spectroradiometer (MODIS) observations between 2000 and 2016. The results show that the mean Danjiangkou Reservoir water storage was 10.548 billion m3 year-1. Significant seasonal changes (ρ < 0.01 in t-test) were observed with annual minima (~9.610 billion m3) occurring between February to July and annual maxima (~11.514 billion m3) occurring from August to the following January. Based on the monthly changes in the probability of the water supply, the guaranteed rate of water supply in the second half year (July-December) was higher than that during the first half year (January-June). The water supply in May was greatly deficient. In addition, the full guaranteed rate of the water supply over the past 17 years only accounted for 17.6%. Therefore, reservoir management practices should reduce the water released prior to May and reserve enough water according to the demands of water receiving areas to improve the efficiency of water resource utilization.
Whether or not communities of microbial eukaryotes are structured in the same way as bacteria is a general and poorly explored question in ecology. Here, we investigated this question in a set of planktonic lake microbiotas in Eastern Antarctica that represent a natural community ecology experiment. Most of the analysed lakes emerged from the sea during the last 6,000 years, giving rise to waterbodies that originally contained marine microbiotas and that subsequently evolved into habitats ranging from freshwater to hypersaline. We show that habitat diversification has promoted selection driven by the salinity gradient in bacterial communities (explaining ~72% of taxa turnover), while microeukaryotic counterparts were predominantly structured by ecological drift (~72% of the turnover). Nevertheless, we also detected a number of microeukaryotes with specific responses to salinity, indicating that albeit minor, selection has had a role in the structuring of specific members of their communities. In sum, we conclude that microeukaryotes and bacteria inhabiting the same communities can be structured predominantly by different processes. This should be considered in future studies aiming to understand the mechanisms that shape microbial assemblages.
Surface sediments are the inner source of contaminations in aquatic systems and usually maintain aerobic conditions. As the key participators of nitrification process, little is known about the activities and contributions of ammonia-oxidizing archaea (AOA) and bacteria (AOB) in the surface sediments. In this study, we determined the net and potential nitrification rates and used 1-octyne as an AOB specific inhibitor to detect the contributions of AOA and AOB to nitrification in surface sediments of Danjiangkou reservoir, which is the water source area of the middle route of South-to-North Water Diversion Project in China. Quantitative PCR and Illumina high-throughput sequencing were used to evaluate the abundance and diversity of the amoA gene. The net and potential nitrification rates ranged from 0.42 to 1.93 and 2.06 to 8.79 mg N kg−1 dry sediments d−1, respectively. AOB dominated in both net and potential nitrification, whose contribution accounted for 52.7–78.6% and 59.9–88.1%, respectively. The cell-specific ammonia oxidation rate calculation also revealed the cell-specific rates of AOB were higher than that of AOA. The Spearman’s rank correlation analysis suggested that ammonia accumulation led to the AOB predominant role in net nitrification activity, and AOB abundance played the key role in potential nitrification activity. Furthermore, phylogenetic analysis suggested AOB were predominantly characterized by the Nitrosospira cluster, while AOA by the Nitrososphaera and Nitrososphaera sister clusters. This study will help us to better understand the contributions and characteristics of AOA and AOB in aquatic sediments and provide improved strategies for nitrogen control in large reservoirs.
Understanding how population-level dynamics contribute to ecosystem-level processes is a primary focus of ecological research and has led to important breakthroughs in the ecology of macroscopic organisms. However, the inability to measure population-specific rates, such as growth, for microbial taxa within natural assemblages has limited ecologists’ understanding of how microbial populations interact to regulate ecosystem processes. Here, we use isotope incorporation within DNA molecules to model taxon-specific population growth in the presence of 18O-labeled water. By applying this model to phylogenetic marker sequencing data collected from stable-isotope probing studies, we estimate rates of growth, mortality, and turnover for individual microbial populations within soil assemblages. When summed across the entire bacterial community, our taxon-specific estimates are within the range of other whole-assemblage measurements of bacterial turnover. Because it can be applied to environmental samples, the approach we present is broadly applicable to measuring population growth, mortality, and associated biogeochemical process rates of microbial taxa for a wide range of ecosystems and can help reveal how individual microbial populations drive biogeochemical fluxes.
Bacterial communities are essential to the biogeochemical cycle in riverine ecosystems. However, little is presently known about the integrated biogeography of planktonic and sedimentary bacterial communities in large rivers. ResultsThis study provides the first spatiotemporal pattern of bacterial communities in the Yangtze River, the largest river in Asia with a catchment area of 1,800,000 km2. We find that sedimentary bacteria made larger contributions than planktonic bacteria to the bacterial diversity of the Yangzte River ecosystem with the sediment subgroup providing 98.8% of 38,906 operational taxonomic units (OTUs) observed in 280 samples of synchronous flowing water and sediment at 50 national monitoring stations covering a 4300 km reach. OTUs within the same phylum displayed uniform seasonal variations, and many phyla demonstrated autumn preference throughout the length of the river. Seasonal differences in bacterial communities were statistically significant in water, whereas bacterial communities in both water and sediment were geographically clustered according to five types of landforms: mountain, foothill, basin, foothill-mountain, and plain. Interestingly, the presence of two huge dams resulted in a drastic fall of bacterial taxa in sediment immediately downstream due to severe riverbed scouring. The integrity of the biogeography is satisfactorily interpreted by the combination of neutral and species sorting perspectives in meta-community theory for bacterial communities in flowing water and sediment. Conclusions
Our study fills a gap in understanding of bacterial communities in one of the world’s largest river and highlights the importance of both planktonic and sedimentary communities to the integrity of bacterial biogeographic patterns in a river subject to varying natural and anthropogenic impacts.
We examined the relationship between viruses and co-occurring bacterial communities across spatiotemporal scale in two contrasting freshwater lakes, namely meromictic Lake Pavin and dimictic Lake Aydat (Central France). Next-generation sequencing of 16S rRNA genes suggested distinct patterns in bacterioplankton community composition (BCC) between the lakes over depths and seasons. BCC were generally dominated by members of Actinobacteria, Proteobacteria, and Bacteroidetes covering about 95% of all sequences. Oxygen depletion at the bottom waters in Aydat and existence of permanent anoxia in the monimolimnion of Pavin resulted in the occurrence and dominance of lesser known members of lake communities such as Methylotenera, Methylobacter, Gallionella, Sulfurimonas, and Syntrophus in Pavin and Methylotenera and Sulfuritalea in Aydat. Differences in BCC appeared strongly related to dissolved oxygen concentration, temperature, viral infection, and virus-to-bacteria ratio. UniFrac analysis indicated a clear distinction in BCC when the percentage of viral infected bacterial cells and virus-to-bacteria ratio exceeded a threshold level of 10% and 5, respectively, suggesting a link between viruses and their potential bacterial host communities. Our study revealed that in both the lakes, the prevailing environmental factors across time and space structured and influenced the adaptation of bacterial communities to specific ecological niches.
Although the health of rivers is threatened by multiple anthropogenic stressors with increasing frequency, it remains an open question how riverine microbial communities respond to emerging micropollutants. Here, by using 16S rDNA amplicon sequencing of 60 water samples collected during different hydrological seasons, we investigated the spatio-temporal variation and the co-occurrence patterns of microbial communities in the anthropogenically impacted Jiulong River in China. The results indicated that the riverine microbial co-occurrence network had a non-random, modular structure, which was mainly shaped by the taxonomic relatedness of co-occurring species. Fecal indicator bacteria may survive for prolonged periods of time in river water, but they formed an independent module which had fewer interactions with typical freshwater bacteria. Multivariate analysis demonstrated that nutrients and micropollutants (i.e. pharmaceuticals and personal care products, PPCPs) exerted combined effects in shaping α- and β-diversity of riverine microbial communities. Remarkably, we showed that a hitherto unrecognized disruptive effect of PPCPs on the abundance variations of central species and module communities was stronger than the influence of physico-chemical factors, suggesting the key role played by micropollutants for the microbial co-occurrence relationships in lotic ecosystems. Overall, our findings provide novel insights into community assembly in aquatic environments experiencing anthropogenic stresses.
Particle-associated bacteria (PAB) and free-living bacteria (FLB) from aquatic environments during phytoplankton blooms differ in their physical distance from algae. Both the interactions within PAB and FLB community fractions and their relationship with the surrounding environmental properties are largely unknown. Here, by using high-throughput sequencing and network-based analyses, we compared the community and network characteristics of PAB and FLB from a plateau lake during a Microcystis aeruginosa bloom. Results showed that PAB and FLB differed significantly in diversity, structure and microbial connecting network. PAB communities were characterized by highly similar bacterial community structure in different sites, tighter network connections, important topological roles for the bloom-causing M. aeruginosa and Alphaproteobacteria, especially for the potentially nitrogen-fixing (Pleomorphomonas) and algicidal bacteria (Brevundimonas sp.). FLB communities were sensitive to the detected environmental factors and were characterized by significantly higher bacterial diversity, less connectivity, larger network size and marginal role of M. aeruginosa. In both networks, covariation among bacterial taxa was extensive (>88% positive connections), and bacteria potentially affiliated with biogeochemical cycling of nitrogen (i.e., denitrification, nitrogen-fixation and nitrite-oxidization) were important in occupying module hubs, such as Meganema, Pleomorphomonas, and Nitrospira. These findings highlight the importance of considering microbial network interactions for the understanding of blooms.
Next-generation 16S ribosomal RNA gene sequencing is widely used to determine the relative composition of the mammalian gut microbiomes. However, in the absence of a reference, this does not reveal alterations in absolute abundance of specific operational taxonomic units if microbial loads vary across specimens.
Here we suggest the spiking of exogenous bacteria into crude specimens to quantify ratios of absolute bacterial abundances. We use the 16S rDNA read counts of the spike-in bacteria to adjust the read counts of endogenous bacteria for changes in total microbial loads. Using a series of dilutions of pooled faecal samples from mice containing defined amounts of the spike-in bacteria Salinibacter ruber, Rhizobium radiobacter and Alicyclobacillus acidiphilus, we demonstrate that spike-in-based calibration to microbial loads allows accurate estimation of ratios of absolute endogenous bacteria abundances. Applied to stool specimens of patients undergoing allogeneic stem cell transplantation, we were able to determine changes in both relative and absolute abundances of various phyla, especially the genus Enterococcus, in response to antibiotic treatment and radio-chemotherapeutic conditioning.
Exogenous spike-in bacteria in gut microbiome studies enable estimation of ratios of absolute OTU abundances, providing novel insights into the structure and the dynamics of intestinal microbiomes.
Electronic supplementary material
The online version of this article (doi:10.1186/s40168-016-0175-0) contains supplementary material, which is available to authorized users.
Acinetobacter spp are ubiquitous gram negative and non fermenting coccobacilli that have the ability to occupy several ecological niches including environment, animals and human. Among the different species, Acinetobacter baumannii has evolved as global pathogen causing wide range of infection. Since the implementation of molecular techniques, the habitat and the role of non baumannii Acinetobacter in human infection have been elucidated. In addition, several new species have been described. In the present review, we summarize the recent data about the natural reservoir of non-baumannii Acinetobacter including the novel species that have been described for the first time from environmental sources and reported during the last years.
The annually recurrent spring phytoplankton blooms in freshwater lakes initiate pronounced successions of planktonic ciliate species. Although there is considerable knowledge on the taxonomic diversity of these ciliates, their species-specific interactions with other microorganisms are still not well understood. Here we present the succession patterns of 20 morphotypes of ciliates during spring in Lake Zurich, Switzerland, and we relate their abundances to phytoplankton genera, flagellates, heterotrophic bacteria, and abiotic parameters. Interspecific relationships were analyzed by contemporaneous correlations and time-lagged co-occurrence and visualized as association networks. The contemporaneous network pointed to the pivotal role of distinct ciliate species (e.g., Balanion planctonicum, Rimostrombidium humile) as primary consumers of cryptomonads, revealed a clear overclustering of mixotrophic/omnivorous species, and highlighted the role of Halteria/Pelagohalteria as important bacterivores. By contrast, time-lagged statistical approaches (like local similarity analyses, LSA) proved to be inadequate for the evaluation of high-frequency sampling data. LSA led to a conspicuous inflation of significant associations, making it difficult to establish ecologically plausible interactions between ciliates and other microorganisms. Nevertheless, if adequate statistical procedures are selected, association networks can be powerful tools to formulate testable hypotheses about the autecology of only recently described ciliate species.
Despite their importance to host health and development, the communities of microorganisms associated with humans and other animals are characterized by a large degree of unexplained variation across individual hosts. The processes that drive such inter-individual variation are not well understood. To address this, we surveyed the microbial communities associated with the intestine of the zebrafish, Danio rerio, over developmental time. We compared our observations of community composition and distribution across hosts with that predicted by a neutral assembly model, which assumes that community assembly is driven solely by chance and dispersal. We found that as hosts develop from larvae to adults, the fit of the model to observed microbial distributions decreases, suggesting that the relative importance of non-neutral processes, such as microbe-microbe interactions, active dispersal, or selection by the host, increases as hosts mature. We also observed that taxa which depart in their distributions from the neutral prediction form ecologically distinct sub-groups, which are phylogenetically clustered with respect to the full metacommunity. These results demonstrate that neutral processes are sufficient to generate substantial variation in microbiota composition across individual hosts, and suggest that potentially unique or important taxa may be identified by their divergence from neutral distributions.The ISME Journal advance online publication, 21 August 2015; doi:10.1038/ismej.2015.142.
Predicted increases in runoff of terrestrial dissolved organic matter (DOM) and sea surface temperatures implicate substantial changes in energy fluxes of coastal marine ecosystems. Despite marine bacteria being critical drivers of marine carbon cycling, knowledge of compositional responses within bacterioplankton communities to such disturbances is strongly limited. Using 16S rRNA gene pyrosequencing, we examined bacterioplankton population dynamics in Baltic Sea mesocosms with treatments combining terrestrial DOM enrichment and increased temperature. Among the 200 most abundant taxa, 62 % either increased or decreased in relative abundance under changed environmental conditions. For example, SAR11 and SAR86 populations proliferated in combined increased terrestrial DOM/temperature mesocosms, while the hgcI and CL500-29 clades (Actinobacteria) decreased in the same mesocosms. Bacteroidetes increased in both control mesocosms and in the combined increased terrestrial DOM/temperature mesocosms. These results indicate considerable and differential responses among distinct bacterial populations to combined climate change effects, emphasizing the potential of such effects to induce shifts in ecosystem function and carbon cycling in the future Baltic Sea.
It is known that fluoride-resistant microorganisms are different from fluoride-sensitive ones in growth, adherence and metabolic activity. It was hypothesized that these phenotypic differences were due to stable genotypic changes in the fluoride-resistant strains. However, until now, no studies have reported these genotypic changes. The aim of this study is to identify such changes in a fluoride-resistant Streptococcus mutans strain (C180-2FR) using whole-genome shotgun (WGS) sequencing and to examine the potential function of the identified mutations by comparing gene expression between the fluoride-sensitive (C180-2) and C180-2FR strains. We performed 50 bp paired-end Illumina shotgun sequencing for both strains. Through extensive bioinformatic analysis, we were able to identify 8 single nucleotide polymorphisms (SNPs) in the genome of C180-2FR, which were further confirmed by Sanger sequencing. Expression of the genes containing or in proximity to the SNPs in C180-2 and C180-2FR was then quantified by real-time PCR. A gene cluster containing genes coding for fluoride antiporters was up-regulated 10-fold in C180-2FR when compared to that in C180-2, independent of growth phase. Two SNPs are located in this gene cluster, one in its promoter region and the other in its protein-coding region. In addition, one gene, which codes for a putative glycerol uptake facilitator protein, was found to be down-regulated by 60% in C180-2FR at an early growth phase. The promoter region of this gene contained a SNP. No difference in expression was found for the other SNP-containing genes. In summary, using WGS sequencing, we were able to uncover genetic changes in the genome of a fluoride-resistant strain. These findings can provide new insights into the mechanism of microbial fluoride resistance.
Understanding environmental and biological influences on the dynamics of microbial communities has received great attention in microbial ecology. Here, utilizing large time-series 16S rRNA gene data, we show that in activated sludge of an environmentally important municipal wastewater treatment plant, 5-year temporal dynamics of bacterial community shows no significant seasonal succession, but is consistent with deterministic assemblage by taxonomic relatedness. Biological interactions are dominant drivers in determining the bacterial community assembly, whereas environmental conditions (mainly sludge retention time and inorganic nitrogen) partially explain phylogenetic and quantitative variances and indirectly influence bacterial assembly. We demonstrate a correlation-based statistical method to integrate bacterial association networks with their taxonomic affiliations to predict community-wide co-occurrence and co-exclusion patterns. The results show that although taxonomically closely related bacteria tend to positively co-occur (for example, out of a cooperative relationship), negative co-excluding correlations are deterministically observed between taxonomically less related species, probably implicating roles of competition in determining bacterial assembly. Overall, disclosures of the positive and negative species-species relations will improve our understanding of ecological niches occupied by unknown species and help to predict their biological functions in ecosystems.
Members of the acI lineage of Actinobacteria are the most abundant microorganisms in most freshwater lakes; however, our understanding of the keys to their success and their role in carbon and nutrient cycling in freshwater systems has been hampered by the lack of pure cultures and genomes. We obtained draft genome assemblies from 11 single cells representing three acI tribes (acI-A1, acI-A7, acI-B1) from four temperate lakes in the United States and Europe. Comparative analysis of acI SAGs and other available freshwater bacterial genomes showed that acI has more gene content directed toward carbohydrate acquisition as compared to Polynucleobacter and LD12 Alphaproteobacteria, which seem to specialize more on carboxylic acids. The acI genomes contain actinorhodopsin as well as some genes involved in anaplerotic carbon fixation indicating the capacity to supplement their known heterotrophic lifestyle. Genome-level differences between the acI-A and acI-B clades suggest specialization at the clade level for carbon substrate acquisition. Overall, the acI genomes appear to be highly streamlined versions of Actinobacteria that include some genes allowing it to take advantage of sunlight and N-rich organic compounds such as polyamines, di- and oligopeptides, branched-chain amino acids and cyanophycin. This work significantly expands the known metabolic potential of the cosmopolitan freshwater acI lineage and its ecological and genetic traits
China National GeneBank DataBase (CNGBdb) is a data platform aiming to systematically archiving and sharing of multi-omics data in life science. As the service portal of Bio-informatics Data Center of the core structure, namely, "Three Banks and Two Platforms" of China National GeneBank (CNGB), CNGBdb has the advantages of rich sample resources, data resources, cooperation projects, powerful data computation and analysis capabilities. With the advent of high throughput sequencing technologies, research in life science has entered the big data era, which is in the need of closer international cooperation and data sharing. With the development of China's economy and the increase of investment in life science research, we need to establish a national public platform for data archiving and sharing in life science to promote the systematic management, application and industrial utilization. Currently, CNGBdb can provide genomic data archiving, information search engines, data management and data analysis services. The data schema of CNGBdb has covered projects, samples, experiments, runs, assemblies, variations and sequences. Until May 22, 2020, CNGBdb has archived 2176 research projects and more than 2221 TB sequencing data submitted by researchers globally. In the future, CNGBdb will continue to be dedicated to promoting data sharing in life science research and improving the service capability. CNGBdb website is: https://db.cngb.org/.
Testate amoebae are widely distributed in natural ecosystems and play an important role in the material cycle and energy flow. However, community assembly of testate amoebae is not well understood, especially with regard to the relative importance of the stochastic and deterministic processes over time. In this study, we used Illumina high-throughput sequencing to explore the community assembly of testate amoebae from surface waters in two reservoirs of subtropical China over a seven-year period. Majority of testate amoebae belonged to the rare taxa because their relative abundances were typically lower than 0.01% of the total eukaryotic plankton community. The testate amoeba community dynamics exhibited a stronger interannual than seasonal variation in both reservoirs. Further, species richness, rather than species turnover, accounted for the majority of community variation. Environmental variables explained less than 20% of the variation in community composition of testate amoebae, and the community assembly appeared to be strongly driven by stochastic processes. Based on the Sloan neutral community model, it was found that neutral processes explained more than 65% of community variation. More importantly, the Stegen null model analysis showed that the stochastic processes (e.g., ecological drift) explained a significantly higher percentage of community assembly than deterministic processes over seven years, although deterministic processes were more influential in certain years. Our results provide new perspectives for understanding the ecological patterns, processes and mechanisms of testate amoeba communities in freshwater ecosystems at temporal scale, and have important implications for monitoring plankton diversity and protecting drinking-water resources.
Geographic patterns of bacteria and microeukaryotes have attracted increasing attention. However, mechanisms underlying geographic patterns in the community composition of both microbial groups are still poorly resolved. In particular, knowledge of whether bacterial communities and microeukaryotic communities are subject to the same or different assembly mechanisms is still limited. In this study, we investigated the biogeographic patterns of bacterial and microeukaryotic communities of 23 lakes on the Tibetan Plateau and quantified the relative influence of assembly mechanisms in shaping both microbial communities. Results showed that water salinity was the major driving force in controlling the community structures of bacteria and microeukaryotes. Although bacterial and microeukaryotic communities exhibited similar distance-decay patterns, the bacterial communities were mainly governed by environmental filtering (niche-related process), whereas microeukaryotic communities were strongly driven by dispersal limitation (neutral-related process). Furthermore, we found that bacteria exhibited wider niche breadths and higher dispersal ability, but lower community stabilities than microeukaryotes. The similar distribution patterns but contrasting assembly mechanisms effecting bacteria and microeukaryotes resulted from the differences in dispersal ability and community stability. Our results highlight the importance of considering organism types in studies of the assembly mechanisms that shape microbial communities in microbial ecology.
We examined the relationship between viruses and co-occurring bacterial communities across spatiotemporal scale in two
contrasting freshwater lakes, namely meromictic Lake Pavin and dimictic Lake Aydat (Central France). Next-generation sequencing
of 16S rRNA genes suggested distinct patterns in bacterioplankton community composition (BCC) between the lakes
over depths and seasons. BCC were generally dominated by members of Actinobacteria, Proteobacteria, and Bacteroidetes
covering about 95% of all sequences. Oxygen depletion at the bottom waters in Aydat and existence of permanent anoxia in
the monimolimnion of Pavin resulted in the occurrence and dominance of lesser known members of lake communities such as
Methylotenera, Methylobacter, Gallionella, Sulfurimonas, and Syntrophus in Pavin and Methylotenera and Sulfuritalea in Aydat.
Differences in BCC appeared strongly related to dissolved oxygen concentration, temperature, viral infection, and virus-tobacteria
ratio. UniFrac analysis indicated a clear distinction in BCC when the percentage of viral infected bacterial cells and
virus-to-bacteria ratio exceeded a threshold level of 10%and 5, respectively, suggesting a link between viruses and their potential
bacterial host communities. Our study revealed that in both the lakes, the prevailing environmental factors across time and space
structured and influenced the adaptation of bacterial communities to specific ecological niches.
Keywords Bacterial community composition and diversity . Illumina sequencing . Viral lysis . Physicochemical gradients .
Temperate lakes . Microbial ecology
Hydrodynamics drives both stochastic and deterministic community assembly in aquatic habitats, by translocating microbes across geographic barriers and generating changes in selective pressures. Thus, heterogeneity of hydrogeological settings and episodic surface inputs from recharge areas might play important roles in shaping and maintaining groundwater microbial communities. Here we took advantage of the Hainich Critical Zone Exploratory to disentangle mechanisms of groundwater microbiome differentiation via a three-year observation in a setting of mixed carbonate-siliciclastic alternations along a hillslope transect. Variation partitioning of all data elucidated significant roles of hydrochemistry (35.0%) and spatial distance (18.6%) but not of time in shaping groundwater microbiomes. Groundwater was dominated by rare species (99.6% of OTUs), accounting for 25.9% of total reads, whereas only 26 OTUs were identified as core species. The proximity to the recharge area gave prominence to high microbial diversity coinciding with high surface inputs. In downstream direction, the abundance of rare OTUs decreased whereas core OTUs abundance increased up to 47% suggesting increasing selection stress with a higher competition cost for colonization. In general, environmental selection was the key mechanism driving the spatial differentiation of groundwater microbiomes, with N-compounds and dissolved oxygen as the major determinants, but it was more prominent in the upper aquifer with low flow velocity. Across the lower aquifer with higher flow velocity, stochastic processes appeared to be additionally important for community assembly. Overall, this study highlights the impact of surface and subsurface conditions, as well as flow regime and related habitat accessibility, on groundwater microbiomes assembly.
Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. Here we propose a general mathematical framework to quantify ecological stochasticity under different situations in which deterministic factors drive the communities more similar or dissimilar than null expectation. An index, normalized stochasticity ratio ( NST ), was developed with 50% as the boundary point between more deterministic (<50%) and more stochastic (>50%) assembly. NST was tested with simulated communities by considering abiotic filtering, competition, environmental noise, and spatial scales. All tested approaches showed limited performance at large spatial scales or under very high environmental noise. However, in all of the other simulated scenarios, NST showed high accuracy (0.90 to 1.00) and precision (0.91 to 0.99), with averages of 0.37 higher accuracy (0.1 to 0.7) and 0.33 higher precision (0.0 to 1.8) than previous approaches. NST was also applied to estimate stochasticity in the succession of a groundwater microbial community in response to organic carbon (vegetable oil) injection. Our results showed that community assembly was shifted from more deterministic ( NST = 21%) to more stochastic ( NST = 70%) right after organic carbon input. As the vegetable oil was consumed, the community gradually returned to be more deterministic ( NST = 27%). In addition, our results demonstrated that null model algorithms and community similarity metrics had strong effects on quantifying ecological stochasticity.
Now is an opportune time to foster collaborations across sectors and geographical boundaries to enable development of best practices for drinking water (DW) microbiome research, focusing on accuracy and reproducibility of meta-omic techniques (while learning from past microbiome projects). A large-scale coordinated effort that builds on this foundation will enable the urgently needed comprehensive spatiotemporal understanding and control of DW microbiomes by engineering interventions to protect public health. This opinion paper highlights the need to initiate and conduct a large-scale coordinated DW microbiome project by addressing key knowledge gaps and recommends a roadmap for this effort.
Eutrophication or excessive nutrient richness is an impairment of many freshwater ecosystems and a prominent cause of harmful algal blooms. It is generally accepted that nitrogen and phosphorus nutrients are the primary causative factor, however, for systems subject to large anthropogenic perturbation, this may no longer be true, and the role of micronutrients is often overlooked. Here we report a study on Lake Tai (Taihu), a large, spatially diverse and hypereutrophic lake in China. We performed small-scale mesocosm nutrient limitation bioassays using boron, iron, cobalt, copper, molybdenum, nitrogen and phosphorus on phytoplankton communities sampled from different locations in Taihu to test the relative effects of micronutrients on in situ algal assemblages. In addition to commonly-used methods of chemical and biological analysis (including algal phytoplankton counting), we used flow cytometry coupled with data-driven analysis to monitor changes to algal assemblages. We found statistically significant effects of limitation or co-limitation for boron, cobalt, copper and iron. For copper at one location chlorophyll-a was over four times higher for amendment with copper, nitrogen and phosphorous than for the latter two alone. Since copper is often proposed as amendment for the environmental management of harmful algal blooms, this result is significant. We have three primary conclusions: first, the strong effects for Cu that we report here are mutually consistent across chlorophyll-a results, count data, and results determined from a data-driven approach to flow cytometry. Given that we cannot rule out a role for a Fe-Cu homeostatic link in causing these effects, future research into MNs and how they interact with N, P, and other MNs should be pursued to explore new interventions for effective management of HABs. Second, in view of the stimulatory effect that Cu exhibited, management of HABs with Cu as an algal biocide may not always be advisable. Third, our approach to flow cytometry offers data confirming our results from chemical and biological analysis, however also holds promise for future development as a high-throughput tool for use in understanding changes in algal assemblages. The results from this study concur with a small and emerging body of literature suggesting that the potential role of micronutrients in eutrophication requires further consideration in environmental management.
Wastewater treatment plants (WWTPs) are implicated as hotspots for the dissemination of antibacterial resistance into the environment. However, the in situ processes governing removal, persistence, and evolution of resistance genes during wastewater treatment remain poorly understood. Here, we used quantitative metagenomic and metatranscriptomic approaches to achieve a broad-spectrum view of the flow and expression of genes related to antibacterial resistance to over 20 classes of antibiotics, 65 biocides, and 22 metals. All compartments of 12 WWTPs share persistent resistance genes with detectable transcriptional activities that were comparatively higher in the secondary effluent, where mobility genes also show higher relative abundance and expression ratios. The richness and abundance of resistance genes vary greatly across metagenomes from different treatment compartments, and their relative and absolute abundances correlate with bacterial community composition and biomass concentration. No strong drivers of resistome composition could be identified among the chemical stressors analyzed, although the sub-inhibitory concentration (hundreds of ng/L) of macrolide antibiotics in wastewater correlates with macrolide and vancomycin resistance genes. Contig-based analysis shows considerable co-localization between resistance and mobility genes and implies a history of substantial horizontal resistance transfer involving human bacterial pathogens. Based on these findings, we propose future inclusion of mobility incidence (M%) and host pathogenicity of antibiotic resistance genes in their quantitative health risk ranking models with an ultimate goal to assess the biological significance of wastewater resistomes with regard to disease control in humans or domestic livestock.
In this study, the spatial and seasonal bacterioplankton community dynamics were investigated in the main channel of the Middle Route of the South-to-North Water Diversion Project (MRP) using Illumina HiSeq sequencing. Water samples were collected in spring and summer from south to north at eight water quality monitoring stations, respectively. The results showed that seasonal changes had a more pronounced effect on the bacterioplankton community compositions (BCCs) than spatial variation. The diversity analysis results indicated that samples of summer have more operational taxonomic units (OTUs), higher richness and diversity than those in spring. The main phyla, Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria and Chloroflexi, displayed significant differences (P < 0.05) between spring and summer in the main channel. The Redundancy analysis (RDA) targeting all samples indicated that specific conductivity (SPC), dissolved oxygen (DO), pH and temperature (T) might be key factors in driving BCCs, while trophic status showed no significant correlation (P > 0.05). The present study provides important insights into the potential ecological roles of specific taxa in the new artificial ecosystem and it offers reference for studies on ecosystem succession of other giant interbasin water diversion project in the world.
We investigated changes in quality and quantity of extracellular and biomass-derived organic matter (OM) from three axenic algae (genera Rhodomonas, Chlamydomonas, Coelastrum) during growth of Limnohabitans parvus, Limnohabitans planktonicus and Polynucleobacter acidiphobus representing important clusters of freshwater planktonic Betaproteobacteria. Total extracellular and biomass-derived OM concentrations from each alga were approximately 20 and 1 mg l−1, respectively, from which up to 9% could be identified as free carbohydrates, polyamines, or free and combined amino acids. Carbohydrates represented 54–61% of identified compounds of the extracellular OM from each alga. In biomass-derived OM of Rhodomonas and Chlamydomonas 71–77% were amino acids and polyamines, while in that of Coelastrum 85% were carbohydrates. All bacteria grew on alga-derived OM of Coelastrum, whereas only Limnohabitans strains grew on OM from Rhodomonas and Chlamydomonas. Bacteria consumed 24–76% and 38–82% of all identified extracellular and biomass-derived OM compounds, respectively, and their consumption was proportional to the concentration of each OM compound in the different treatments. The bacterial biomass yield was higher than the total identifiable OM consumption indicating that bacteria also utilized other unidentified alga-derived OM compounds. Bacteria, however, also produced specific OM compounds suggesting enzymatic polymer degradation or de novo exudation. This article is protected by copyright. All rights reserved.
Understanding the influences of biotic and abiotic factors on microbial community structure and methanogenesis are important for its engineering and ecological significance. In this study, four biogas digesters were supplied with the same inoculum and feeding sludge, but operated at different sludge retention time (7 to 16 days) and organic loading rates for 90 days to determine the relative influence of biotic and environmental factors on the microbial community assembly and methanogenic performance. Despite different operational parameters, all digester communities were dominated by Bacteroidales, Clostridiales and Thermotogales, and followed the same trend of population dynamics over time. Network and multivariate analyses suggest that deterministic factors, including microbial competition (involving Bacteroidales spp.), niche differentiation (e.g., within Clostridiales spp.), and periodic microbial immigration (from feed sludge), are the key drivers of microbial community assembly and dynamics. A yet-to-be-cultured phylotype of Bacteroidales (GenBank ID: GU389558.1) is implicated as a strong competitor for carbohydrates. Moreover, biogas-producing rate and methane content were significantly related with the abundances of functional populations rather than any operational or physicochemical parameter, revealing microbiological mediation of methanogenesis. Combined, this study enriches our understandings of biological and environmental drivers of microbial community assembly and performance in anaerobic digesters.
Understanding the trend of chemical composition of precipitation is of great importance for air pollution control strategies in Northern China. A comprehensive study on the long-term chemical compositions of precipitation was carried out from 2003 to 2014 at the Shangdianzi (SDZ) regional background station in northern China. All samples were analyzed for pH, electrical conductivity and major ions (F⁻, Cl⁻, NO3⁻, SO42 −, NH4⁺, Mg2 +, Ca2 +, K⁺ and Na⁺). The average pH during this period was 4.53 ± 0.35, which is considerably lower than those reported in other background stations in China (Linan, Waliguan and Longfengshan). NH4⁺, SO42 −, Ca2 + and NO3⁻ were the dominant ions in precipitation, with concentrations (volume-weighted mean) of 212.99 μeq L− 1, 200.20 μeq L− 1, 116.88 μeq L− 1 and 98.56 μeq L− 1, respectively. The ion concentrations at SDZ were much higher than those of other background stations and megacities in China. A significantly increasing trend was observed for NO3⁻ (7.26% year− 1), and a decreasing trend was observed for SO42 −/NO3⁻, suggesting that the precipitation of SDZ evolved from a sulfuric acid type to a mixed type dominated by both sulfuric and nitric acid. The source identification indicated that SO42 −, NO3⁻, NH4⁺ and F⁻ were dominated by secondary sources, Mg2 +, Ca2 + and Na⁺ mostly originated from natural sources, and K⁺ and Cl⁻ probably associated with anthropogenic sources. Long-range transport of air masses could influence the acidity, electrical conductivity and ion concentrations of precipitation at SDZ. The higher acidity and ion concentrations mainly occurred in the southerly and westerly trajectory pathways and partially in northwest pathways. Anthropogenic pollutants and crustal sources along these pathways were significant contributors to the chemical composition of precipitation in SDZ.
We present the open-source software package DADA2 for modeling and correcting Illumina-sequenced amplicon errors (https://github.com/benjjneb/dada2). DADA2 infers sample sequences exactly and resolves differences of as little as 1 nucleotide. In several mock communities, DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
Streams and rivers form dense networks, shape the Earth's surface and, in their sediments, provide an immensely large surface area for microbial growth. Biofilms dominate microbial life in streams and rivers, drive crucial ecosystem processes and contribute substantially to global biogeochemical fluxes. In turn, water flow and related deliveries of nutrients and organic matter to biofilms constitute major constraints on microbial life. In this Review, we describe the ecology and biogeochemistry of stream biofilms and highlight the influence of physical and ecological processes on their structure and function. Recent advances in the study of biofilm ecology may pave the way towards a mechanistic understanding of the effects of climate and environmental change on stream biofilms and the biogeochemistry of stream ecosystems.
Acinetobacter occupies an important position in nature because of its ubiquitous presence in diverse environments such as soils, fresh water, oceans, sediments, and contaminated sites. Versatile metabolic characteristics allow species of this genus to catabolize a wide range of natural compounds, implying active participation in the nutrient cycle in the ecosystem. On the other hand, multi-drug-resistant Acinetobacter baumannii causing nosocomial infections with high mortality has been raising serious concerns in medicine. Due to the ecological and clinical importance of the genus, Acinetobacter was proposed as a model microorganism for environmental microbiological studies, pathogenicity tests, and industrial production of chemicals. For these reasons, Acinetobacter has attracted significant attention in scientific and biotechnological fields, but only limited research areas such as natural transformation and aromatic compound degradation have been intensively investigated, while important physiological characteristics including quorum sensing, motility, and stress response have been neglected. The aim of this review is to summarize the recent achievements in Acinetobacter research with a special focus on strain DR1 and to compare the similarities and differences between species or other genera. Research areas that require more attention in future research are also suggested.