Annual periodicity in planktonic bacterial and archaeal community composition of eutrophic Lake Taihu

Spatiotemporal patterns and co-occurrence patterns of dissimilatory nitrate reduction to ammonium community in sediments of the Lancang River cascade reservoirs

Dissimilatory nitrate reduction to ammonium (DNRA) is an important nitrate reduction pathway in freshwater sediments. Many studies have focused on the DNRA process in various natural habitats. However, the joint operation of cascade reservoirs will affect the physical and chemical properties of sediments, which may change the DNRA process and bacterial community pattern in the surface sediments of cascade reservoirs. Our study was the first to investigate the spatiotemporal distribution patterns of potential DNRA rate, nrfA gene abundances, and DNRA bacterial community diversity in surface sediments of the Lancang River cascade reservoirs. The results of slurry incubation experiments combined with the 15N isotope tracer experiment ascertained that the potential rates of DNRA were 0.01-0.15 nmol-N cm-3 h-1, and qPCR results indicated that the abundance range of nrfA was 1.08 × 105-2.51 × 106 copies g-1 dry weight. High throughput sequencing of the nrfA gene revealed that the relative abundance of Anaeromyxobacter (4.52% on average), Polyangium (4.09%), Archangium (1.86%), Geobacter (1.34%), and Lacunisphaera (1.32%) were high. Pearson and RDA correlation analysis exhibited that nrfA gene abundance was positively correlated with altitude, pH, OC, and sand concentration. Anaeromyxobacter was positively correlated with reservoir age and DNRA potential rate. The deterministic environmental selection process plays a crucial role in the formation of the DNRA bacterial community. Network analysis displayed that the dominant DNRA genus was the key population of the DNRA microbial community in the sediments of Lancang River cascade reservoirs. This study reveals that the variation of DNRA bacterial activity and community structure is largely driven by the construction of cascade reservoirs, and provides a new idea for further understanding the characteristics of the DNRA community in the cascade reservoir ecosystem.

Stringent Response of Cyanobacteria and Other Bacterioplankton during Different Stages of a Harmful Cyanobacterial Bloom

We conducted a field study to investigate the role of stringent response in cyanobacteria and coexisting bacterioplankton during nutrient-deprived periods at various stages of bloom in a freshwater lake (Utah Lake) for the first time. Using metagenomics and metatranscriptomics analyses, we examined the cyanobacterial ecology and expression of important functional genes related to stringent response, N and P metabolism, and regulation. Our findings mark a significant advancement in understanding the mechanisms by which toxic cyanobacteria survive and proliferate during nitrogen (N) and phosphorus (P) limitations. We successfully identified and analyzed the metagenome-assembled genomes (MAGs) of the dominant bloom-forming cyanobacteria, namely, Dolichospermum circinale, Aphanizomenon flos-aquae UKL13-PB, Planktothrix agardhii, and Microcystis aeruginosa. By mapping RNA-seq data to the coding sequences of the MAGs, we observed that these four prevalent cyanobacteria species activated multiple functions to adapt to the depletion of inorganic nutrients. During and after the blooms, the four dominant cyanobacteria species expressed high levels of transcripts related to toxin production, such as microcystins (mcy), anatoxins (ana), and cylindrospermopsins (cyr). Additionally, genes associated with polyphosphate (poly-P) storage and the stringent response alarmone (p)ppGpp synthesis/hydrolysis, including ppk, relA, and spoT, were highly activated in both cyanobacteria and bacterioplankton. Under N deficiency, the main N pathways shifted from denitrification and dissimilatory nitrate reduction in bacterioplankton toward N2-fixing and assimilatory nitrate reduction in certain cyanobacteria with a corresponding shift in the community composition. P deprivation triggered a stringent response mediated by spoT-dependent (p)ppGpp accumulation and activation of the Pho regulon in both cyanobacteria and bacterioplankton, facilitating inorganic and organic P uptake. The dominant cyanobacterial MAGs exhibited the presence of multiple alkaline phosphatase (APase) transcripts (e.g., phoA in Dolichospermum, phoX in Planktothrix, and Microcystis), suggesting their ability to synthesize and release APase enzymes to convert ambient organic P into bioavailable forms. Conversely, transcripts associated with bacterioplankton-dominated pathways like denitrification were low and did not align with the occurrence of intense cyanoHABs. The strong correlations observed among N, P, stringent response metabolisms and the succession of blooms caused by dominant cyanobacterial species provide evidence that the stringent response, induced by nutrient limitation, may activate unique N and P functions in toxin-producing cyanobacteria, thereby sustaining cyanoHABs.

Shifts in composition and function of bacterial communities reveal the effect of small barriers on nitrous oxide and methane accumulation in fragmented rivers

Rivers are often blocked by barriers to form different habitats, but it is not clear whether this change will affect the accumulation of N₂O and CH₄ in rivers. Here, low barriers (less than 2 m, LB) increased N₂O concentration by 1.13 times and CH₄ decreased by 0.118 times, while high barriers (higher than 2 m, less than 5 m high, HB) increased N₂O concentration by 1.19 times and CH₄ by 2.76 times. Co-occurrence network analysis indicated LB and HB can promote the enrichment of Cyanobium and Chloroflexi, further limiting complete denitrification and increasing N₂O accumulation. The LB promotes methanotrophs (Methylocystis, Methylophilus, and Methylotenera) to compete with denitrifiers (Pseudomonas) in water, and reduce CH₄ accumulation. While the HB can promote the methanotrophs to compete with nitrifiers (Nitrosospira) in sediment, thus reducing the consumption of CH₄. LB and HB reduce river velocity, increase water depth, and reduce dissolved oxygen (DO), leading to enrichment of nirS-type denitrifiers and the increase of N₂O concentration in water. Moreover, the HB reduces DO concentration and pmoA gene abundance in water, which can increase the accumulation of CH₄. In light of the changes in the microbial community and variation in N₂O and CH₄ accumulation, the impact of fragmented rivers on global greenhouse gas emissions merits further study.

Temporal heterogeneity of bacterial communities and their responses to Raphidiopsis raciborskii blooms

To elucidate the interspecies connectivity between cyanobacteria and other bacteria (noncyanobacteria), microbial diversity and composition were investigated through high-throughput sequencing (HTS) in a drinking water reservoir in Chongqing city, Southwest China, during Raphidiopsis raciborskii blooms. Significant temporal changes were observed in microbial community composition during the sampling period, primarily reflected by variations in relative bacterial abundance. The modularity analysis of the network demonstrated that the bacterial community forms co-occurrence/exclusion patterns in response to variations in environmental factors. Moreover, five modules involved in the dynamic phases of the R. raciborskii bloom were categorized into the Pre-Bloom, Bloom, Post-Bloom, and Non-Bloom Groups. The reservoir was eutrophic (i.e., the average concentrations of total nitrogen (TN) and total phosphorus (TP) were 2.32 and 0.07 mg L^-1, respectively) during the investigation; however, Pearson's correlation coefficient showed that R. raciborskii was not significantly correlated with nitrogen and phosphorus. However, other environmental factors, such as water temperature, pH, and the permanganate index, were positively correlated with R. raciborskii. Importantly, Proteobacteria (α-, γ-Proteobacteria), Acidobacteria, Chloroflexi, and Firmicutes were preferentially associated with increased R. raciborskii blooms. These results suggested that the transition of R. raciborskii bloom-related microbial modules and their keystone species could be crucial in the development and collapse of R. raciborskii blooms and could provide a fundamental basis for understanding the linkage between the structure and function of the microbial community during bloom dynamics.

Time after time: Detecting annual patterns in stream bacterial biofilm communities

To quantify the major environmental drivers of stream bacterial population dynamics, we modelled temporal differences in stream bacterial communities to quantify community shifts, including those relating to cyclical seasonal variation and more sporadic bloom events. We applied Illumina MiSeq 16S rRNA bacterial gene sequencing of 892 stream biofilm samples, collected monthly for 36‐months from six streams. The streams were located a maximum of 118 km apart and drained three different catchment types (forest, urban and rural land uses). We identified repeatable seasonal patterns among bacterial taxa, allowing their separation into three ecological groupings, those following linear, bloom/trough and repeated, seasonal trends. Various physicochemical parameters (light, water and air temperature, pH, dissolved oxygen, nutrients) were linked to temporal community changes. Our models indicate that bloom events and seasonal episodes modify biofilm bacterial populations, suggesting that distinct microbial taxa thrive during these events including non‐cyanobacterial community members. These models could aid in determining how temporal environmental changes affect community assembly and guide the selection of appropriate statistical models to capture future community responses to environmental change.

Groundwater bacterial communities evolve over time in response to recharge

Time series analyses are a crucial tool for uncovering the patterns and processes shaping microbial communities and their functions, especially in aquatic ecosystems. Subsurface aquatic environments are perceived to be more stable than surface oceans and lakes, due to the lack of sunlight, the absence of photosysnthetically-driven primary production, low temperature variations, and oligotrophic conditions. However, periodic groundwater recharge should affect the structure and succession of groundwater microbiomes. To disentangle the long-term temporal changes in bacterial communities of shallow fractured bedrock groundwater, and identify the drivers of the observed patterns, we analysed bacterial 16S rRNA gene sequencing data for samples collected monthly from three groundwater wells over a six-year period (n = 230) along a hillslope recharge area. We showed that the bacterial communities in the groundwater of limestone-mudstone alternations were not stable over time and exhibited non-linear dissimilarity patterns which corresponded to periods of groundwater recharge. Further, we observed an increase in dissimilarity over time (generalized additive model P < 0.001) indicating that the successive recharge events result in communities that are increasingly more dissimilar to the initial reference time point. The sampling period was able to explain up to 29.5% of the variability in bacterial community composition and the impact of recharge events on the groundwater microbiome was linked to the strength of the recharge and local environmental selection. Many groundwater bacteria originated from the recharge-related sources (mean = 66.5%, SD = 15.1%) and specific bacterial taxa were identified as being either enriched or repressed during recharge events. Overall, similar to surface aquatic environments, the microbiomes in shallow fractured-rock groundwater vary through time, though we revealed groundwater recharges as unique driving factors for these patterns. The high temporal resolution employed here highlights the dynamics of bacterial communities in groundwater, which is an essential resource for the provision of clean drinking water; understanding the biological complexities of these systems is therefore crucial.

Diverse and active archaea communities occur in non-disinfected drinking water systems-Less activity revealed in disinfected and hot water systems

The knowledge about the members of active archaea communities in DWDS is limited. The current understanding is based on high-throughput 16S ribosomal RNA gene (DNA-based) amplicon sequencing that reveals the diversity of active, dormant, and dead members of the prokaryote (bacteria, archaea) communities. The sequencing primers optimized for bacteria community analysis may underestimate the share of the archaea community. This study characterized archaea communities at five full-scale drinking water distribution systems (DWDS), representing a variety of drinking water production units (A-E); A&B use artificially recharged non-disinfected groundwater (ARG), the other DWDS's supplied water disinfected by using ultraviolet (UV) light and chlorine compounds, C&D were surface waterworks and E was a ground waterworks. For the first time for archaea community analyses, this study employed the archaea-specific high-throughput sequencing primers for 16S ribosomal RNA (rRNA) as a target (reverse-transcribed cDNA; an RNA-based approach) in addition to the previously used 16S rRNA gene target (rDNA; a DNA-based approach) to reveal the active fraction of the archaea present in DWDS. The archaea community structure in varying environmental conditions in the water and biofilm of the five DWDSs were investigated by taking into consideration the system properties (cold or hot water system) and water age (distance from the treatment plants) in samples from each season of one year. The RNA-based archaea amplicon reads were obtained mostly from cold water samples from DWDSs (A-B) distributing water without disinfection where the DNA-based and RNA-based analysis created separate clusters in a weighted beta-diversity analysis. The season and location in DWDS A further affected the diversity of these archaea communities as was seen by different clusters in beta-diversity plots. The recovery of archaea reads was not adequate for analysis in any of the disinfected samples in DWDSs C-E or non-disinfected hot water in DWDSs A-B when utilizing RNA-based template. The metabolically active archaea community of DWDSs thus seemed to be effectively controlled by disinfection of water and in the hot water systems by the temperature. All biofilms regardless of DWDS showed lower species richness values (mainly Nitrososphaeria class) than non-disinfected water from DWDSs A-B where several archaea classes occurred (e.g. Woesearchaeia, Nitrososphaeria, Micrarchaeia, Methanomicrobia, Iairchaeia, Bathyarchaeia) indicating only part of the archaea members were able to survive in biofilms. Thus, Archaea has been shown as a significant part of normal DWDS biota, and their role especially in non-disinfected DWDS may be more important than previously considered.

Effect of different types of anthropogenic pollution on the bacterial community of urban rivers

The health of urban rivers is threatened by multiple anthropogenic stressors. Bacterial communities in rivers can quickly respond to different types of polluted environments, making them useful for water quality assessments and predictive insights. However, research on river bacterial communities has largely ignored interactions between these communities. Here, 16S rRNA amplicon sequencing analysis is used to comprehensively analyze the bacterial communities in the water and sediments in different types of anthropogenically impacted urban river. The results show that distinct differences occur in the bacterial communities in the river sediment and water with different pollution types. The changes in the bacterial communities in sediments were more pronounced than those in the water. A modular analysis further showed that the microbial co-occurrence network under different types of pollution had a nonrandom modular structure, and this structure was mainly driven by classification correlation and bacterial function. Genes identified for nitrogen cycling in all the river water and sediment samples included major functional genes for nitrogen fixation, assimilatory nitrogen reduction, nitrification, denitrification, and ammonification. Carbon degradation genes were mainly observed in the carbon cycle. Taken together, the above findings provide further insights into microbial communities in urban river ecosystems under anthropogenic contamination. PRACTITIONER POINTS: The physical and chemical indicators of the four types of pollution drive bacterial community structure. Bacterial community has C, N, P metabolic genes indicating its ecological effect. River bacteria were connected more frequently in the same or similar type of pollution in the co-occurrence network. Microbe-environment correlations and microbe-microbe interactions were combined to determine crucial indicators.

Spatial-temporal dynamics and influencing factors of archaeal communities in the sediments of Lancang River cascade reservoirs (LRCR), China

The spatial and temporal distribution of the archaeal community and its driving factors in the sediments of large-scale regulated rivers, especially in rivers with cascade hydropower development rivers, remain poorly understood. Quantitative PCR (qPCR) and Illumina MiSeq sequencing of the 16S rRNA archaeal gene were used to comprehensively investigate the spatiotemporal diversity and structure of archaeal community in the sediments of the Lancang River cascade reservoirs (LRCR). The archaeal abundance ranged from 5.11×104 to 1.03×106 16S rRNA gene copies per gram dry sediment and presented no temporal variation. The richness, diversity, and community structure of the archaeal community illustrated a drastic spatial change. Thaumarchaeota and Euryyarchaeota were the dominant archaeal phyla in the sediments of the cascade rivers, and Bathyarchaeota was also an advantage in the sediments. PICRUSt metabolic inference analysis revealed a growing number of genes associated with xenobiotic metabolism and carbon and nitrogen metabolism in downstream reservoirs, indicating that anthropogenic pollution discharges might act as the dominant selective force to alter the archaeal communities. Nitrate and C/N ratio were found to play important roles in the formation of the archaeal community composition. In addition, the sediment archaeal community structure was also closely related to the age of the cascade reservoir and hydraulic retention time (HRT). This finding indicates that the engineering factors of the reservoir might be the greatest contributor to the archaeal community structure in the LRCR.

The Lifestyle-Dependent Microbial Interactions Vary Between Upstream and Downstream of the Three Gorges Dam

Dams represent the most significant anthropogenic disturbance to global rivers. Previous studies have shown that free-living and particle-attached microbes exhibited differentially in river and reservoir ecosystems. However, little is known about the dam’s effect on their co-occurrence patterns. Here, a random matrix theory (RMT)-based network approach was used to construct microbial ecological networks for free-living and particle-attached communities in the immediate vicinity of the Three Gorges Dam (TGD), based on a high-throughput sequencing of 16S rRNA gene. Microbial distribution pattern showed that differences caused by lifestyle (free-living vs. particle-attached) were greater than those caused by geographic position (upstream vs. downstream of the TGD). Network analysis revealed higher connectivity and a lower number of modules in the overall downstream networks. Furthermore, considering the lifestyle, the network structures and properties for free-living and particle-attached microbes were different between upstream and downstream of the dam. Specifically, free-living communities located upstream of the dam exhibited a more complex co-occurrence pattern than the particle-attached communities, whereas the opposite was true for those located downstream of the dam. This variation indicated a strong impact of the dam on microbial interactions for microbes with similar lifestyle in the vicinity of the dam. We identified 112 persistent operational taxonomic unit (OTU)-level species that stably coexisted regardless of lifestyle and geographic positions. These persistent species occupied 21.33–25.57% of the total nodes in each network, and together with their first neighbors, they contributed more than 50% of the nodes and edges belonging to each network. Furthermore, we found that taxonomic affiliations for central nodes (with high degree) varied in these persistent species sub-networks. Collectively, our findings expand the current understanding of the dam’s effect on species interaction variation patterns for free-living and particle-attached communities in the vicinity of the dam, which are more complex than traditional alpha and beta microbial diversity.

Water Quality Prediction in the Luan River Based on 1-DRCNN and BiGRU Hybrid Neural Network Model

The current global water environment has been seriously damaged. The prediction of water quality parameters can provide effective reference materials for future water conditions and water quality improvement. In order to further improve the accuracy of water quality prediction and the stability and generalization ability of the model, we propose a new comprehensive deep learning water quality prediction algorithm. Firstly, the water quality data are cleaned and pretreated by isolation forest, the Lagrange interpolation method, sliding window average, and principal component analysis (PCA). Then, one-dimensional residual convolutional neural networks (1-DRCNN) and bi-directional gated recurrent units (BiGRU) are used to extract the potential local features among water quality parameters and integrate information before and after time series. Finally, a full connection layer is used to obtain the final prediction results of total nitrogen (TN), total phosphorus (TP), and potassium permanganate index (COD-Mn). Our prediction experiment was carried out according to the actual water quality data of Daheiting Reservoir, Luanxian Bridge, and Jianggezhuang at the three control sections of the Luan River in Tangshan City, Hebei Province, from 5 July 2018 to 26 March 2019. The minimum mean absolute percentage error (MAPE) of this method was 2.4866, and the coefficient of determination (R2) was able to reach 0.9431. The experimental results showed that the model proposed in this paper has higher prediction accuracy and generalization than the existing LSTM, GRU, and BiGRU models.

Microbial diversity accumulates in a downstream direction in the Three Gorges Reservoir

Organic and inorganic materials migrate downstream and have important roles in regulating environmental health in the river networks. However, it remains unclear whether and how a mixture of materials (i.e., microbial species) from various upstream habitats contribute to microbial community coalescence upstream of a dam. Here we track the spatial variation in microbial abundance and diversity in the Three Gorges Reservoir based on quantitative PCR and 16S rRNA gene high-throughput sequencing data. We further quantitatively assess the relative contributions of microbial species from mainstem, its tributaries, and the surrounding riverbank soils to the area immediately upstream of the Three Gorges Dam (TGD). We found an increase of microbial diversity and the convergent microbial distribution pattern in areas immediately upstream of TGD, suggesting this area become a new confluence for microbial diversity immigrating from upstream. Indeed, the number of shared species increased from upstream to TGD but unique species decreased, indicating immigration of various sources of microbial species overwhelms local environmental conditions in structuring microbial community close to TGD. By quantifying the sources of microbial species close to TGD, we found little contribution from soils as compared to tributaries, especially for sites closer to TGD, suggesting tributary microbes have greater influence on microbial diversity and environmental health in the Three Gorges Reservoir. Collectively, our results suggest that tracking microbial geographic origin and evaluating accumulating effects of microbial diversity shed light on the ecological processes in microbial communities and provide information for regulating aquatic ecological health.

Streamlined and Abundant Bacterioplankton Thrive in Functional Cohorts

This study examines evolutionary and ecological relationships of three of the most ubiquitous and abundant freshwater bacterial genera: “Ca. Planktophila” (acI-A), “Ca. Nanopelagicus” (acI-B), and “Ca. Fonsibacter” (LD12). Due to high abundance, these genera might have a significant influence on nutrient cycling in freshwaters worldwide, and this study adds a layer of understanding to how seemingly competing clades of bacteria can coexist by having different cooperation strategies. Our synthesis ties together network and ecological theory with empirical evidence and lays out a framework for how the functioning of populations within complex microbial communities can be studied.

While fastidious microbes can be abundant and ubiquitous in their natural communities, many fail to grow axenically in laboratories due to auxotrophies or other dependencies. To overcome auxotrophies, these microbes rely on their surrounding cohort. A cohort may consist of kin (ecotypes) or more distantly related organisms (community) with the cooperation being reciprocal or nonreciprocal and expensive (Black Queen hypothesis) or costless (by-product). These metabolic partnerships (whether at single species population or community level) enable dominance by and coexistence of these lineages in nature. Here we examine the relevance of these cooperation models to explain the abundance and ubiquity of the dominant fastidious bacterioplankton of a dimictic mesotrophic freshwater lake. Using both culture-dependent (dilution mixed cultures) and culture-independent (small subunit [SSU] rRNA gene time series and environmental metagenomics) methods, we independently identified the primary cohorts of actinobacterial genera “Candidatus Planktophila” (acI-A) and “Candidatus Nanopelagicus” (acI-B) and the proteobacterial genus “Candidatus Fonsibacter” (LD12). While “Ca. Planktophila” and “Ca. Fonsibacter” had no correlation in their natural habitat, they have the potential to be complementary in laboratory settings. We also investigated the bifunctional catalase-peroxidase enzyme KatG (a common good which “Ca. Planktophila” is dependent upon) and its most likely providers in the lake. Further, we found that while ecotype and community cooperation combined may explain “Ca. Planktophila” population abundance, the success of “Ca. Nanopelagicus” and “Ca. Fonsibacter” is better explained as a community by-product. Ecotype differentiation of “Ca. Fonsibacter” as a means of escaping predation was supported but not for overcoming auxotrophies.

IMPORTANCE This study examines evolutionary and ecological relationships of three of the most ubiquitous and abundant freshwater bacterial genera: “Ca. Planktophila” (acI-A), “Ca. Nanopelagicus” (acI-B), and “Ca. Fonsibacter” (LD12). Due to high abundance, these genera might have a significant influence on nutrient cycling in freshwaters worldwide, and this study adds a layer of understanding to how seemingly competing clades of bacteria can coexist by having different cooperation strategies. Our synthesis ties together network and ecological theory with empirical evidence and lays out a framework for how the functioning of populations within complex microbial communities can be studied.

The balance between deterministic and stochastic processes in structuring lake bacterioplankton community over time

One major goal in microbial ecology is to establish the importance of deterministic and stochastic processes for community assembly. This is relevant to explain and predict how diversity changes at different temporal scales. However, understanding of the relative quantitative contribution of these processes and particularly of how they may change over time is limited. Here, we assessed the importance of deterministic and stochastic processes based on the analysis of the bacterial microbiome in one alpine oligotrophic and in one subalpine mesotrophic lake, which were sampled over two consecutive years at different time scales. We found that in both lakes, homogeneous selection (i.e., a deterministic process) was the main assembly process at the annual scale and explained 66.7% of the bacterial community turnover, despite differences in diversity and temporal variability patterns between ecosystems. However, in the alpine lake, homogenizing dispersal (i.e., a stochastic process) was the most important assembly process at the short‐term (daily and weekly) sampling scale and explained 55% of the community turnover. Alpha diversity differed between lakes, and seasonal stability of the bacterial community was more evident in the oligotrophic lake than in the mesotrophic one. Our results demonstrate how important forces that govern temporal changes in bacterial communities act at different time scales. Overall, our study validates on a quantitative basis, the importance and dominance of deterministic processes in structuring bacterial communities in freshwater environments over long time scales.

Prokaryotic and eukaryotic microbiomes associated with blooms of the ichthyotoxic dinoflagellate Cochlodinium (Margalefidinium) polykrikoides in New York, USA, estuaries

While harmful algal blooms caused by the ichthyotoxic dinoflagellate, Cochlodinium (Margalefidinium) polykrikoides, are allelopathic and may have unique associations with bacteria, a comprehensive assessment of the planktonic communities associated with these blooms has been lacking. Here, we used high-throughput amplicon sequencing to assess size fractionated (0.2 and 5 μm) bacterial (16S) and phytoplankton assemblages (18S) associated with blooms of C. polykrikoides during recurrent blooms in NY, USA. Over a three-year period, samples were collected inside (‘patch’) and outside (‘non-patch’) dense accumulations of C. polykrikoides to assess the microbiome associated with these blooms. Eukaryotic plankton communities of blooms had significantly lower diversity than non-bloom samples, and non-bloom samples hosted 30 eukaryotic operational taxonomic units (OTUs) not found within blooms, suggesting they may have been allelopathically excluded from blooms. Differential abundance analyses revealed that C. polykrikoides blooms were significantly enriched in dinoflagellates (p<0.001) and the experimental enrichment of C. polykrikoides led to a significant increase in the relative abundance of eight genera of dinoflagellates but a significant decline in other eukaryotic plankton. Amoebophrya co-dominated both within- and near- C. polykrikoides blooms and was more abundant in bloom patches. The core bacterial microbiome of the >0.2μm fraction of blooms was dominated by an uncultured bacterium from the SAR11 clade, while the >5μm size fraction was co-dominated by an uncultured bacterium from Rhodobacteraceae and Coraliomargarita. Two bacterial lineages within the >0.2μm fraction, as well as the Gammaproteobacterium, Halioglobus, from the >5μm fraction were unique to the microbiome of blooms, while there were 154 bacterial OTUs only found in non-bloom waters. Collectively, these findings reveal the unique composition and potential function of eukaryotic and prokaryotic communities associated with C. polykrikoides blooms.

Evolution in action: habitat transition from sediment to the pelagial leads to genome streamlining in Methylophilaceae

The most abundant aquatic microbes are small in cell and genome size. Genome-streamlining theory predicts gene loss caused by evolutionary selection driven by environmental factors, favouring superior competitors for limiting resources. However, evolutionary histories of such abundant, genome-streamlined microbes remain largely unknown. Here we reconstruct the series of steps in the evolution of some of the most abundant genome-streamlined microbes in freshwaters ("Ca. Methylopumilus") and oceans (marine lineage OM43). A broad genomic spectrum is visible in the family Methylophilaceae (Betaproteobacteria), from sediment microbes with medium-sized genomes (2-3 Mbp genome size), an occasionally blooming pelagic intermediate (1.7 Mbp), and the most reduced pelagic forms (1.3 Mbp). We show that a habitat transition from freshwater sediment to the relatively oligotrophic pelagial was accompanied by progressive gene loss and adaptive gains. Gene loss has mainly affected functions not necessarily required or advantageous in the pelagial or is encoded by redundant pathways. Likewise, we identified genes providing adaptations to oligotrophic conditions that have been transmitted horizontally from pelagic freshwater microbes. Remarkably, the secondary transition from the pelagial of lakes to the oceans required only slight modifications, i.e., adaptations to higher salinity, gained via horizontal gene transfer from indigenous microbes. Our study provides first genomic evidence of genome reduction taking place during habitat transitions. In this regard, the family Methylophilaceae is an exceptional model for tracing the evolutionary history of genome streamlining as such a collection of evolutionarily related microbes from different habitats is rare in the microbial world.

The Seasonal Dynamics and the Influence of Human Activities on Campus Outdoor Microbial Communities

Large-scale campus resembles a small “semi-open community,” harboring disturbances from the exchanges of people and vehicles, wherein stressors such as temperature and population density differ among the ground surfaces of functional partitions. Therefore, it represents a special ecological niche for the study on microbial ecology in the process of urbanization. In this study, we investigated outdoor microbial communities in four campuses in Wuhan, China. We obtained 284 samples from 55 sampling sites over six seasons, as well as their matching climatic and environmental records. The structure of campus outdoor microbial communities which influenced by multiple climatic factors featured seasonality. The dispersal influence of human activities on microbial communities also contributed to this seasonal pattern non-negligibly. However, despite the microbial composition alteration in response to multiple stressors, the overall predicted function of campus outdoor microbial communities remained stable across campuses. The spatial–temporal dynamic patterns on campus outdoor microbial communities and its predicted functions have bridged the gap between microbial and macro-level ecosystems, and provided hints toward a better understanding of the effects of climatic factors and human activities on campus micro-environments.

Seasonal succession and spatial distribution of bacterial community structure in a eutrophic freshwater Lake, Lake Taihu

In aquatic ecosystems, both phytoplankton and bacteria play pivotal roles. Based on 16S rRNA gene sequencing, considerable research focused on phytoplankton colony attached and free-living bacteria has revealed the close relationship between them, and indicated that the entire bacterial community mediates crucial biogeochemical processes in aquatic ecosystems. However, our understanding of their distribution patterns and response to environmental factors remains poor. Besides, picocyanobacteria, which were omitted from attached bacteria analysis, were reported to be important in cyanobacterial blooms. To explore the spatiotemporal variation of the entire bacterial community with their driving environmental factors and detect the relationships among them, we collected 61 water samples spanning one year and the entire Lake Taihu regions for surveying the entire bacterial community. Our results indicated: 1) seasonal variation of the bacterial community composition was stronger than spatial variation due to the clearly seasonal variation of Microcystis, Synechococcus (pico-cyanobacteria) and other bacteria (Actinomycetales, Pirellulaceae and Sphingobacteriaceae); 2) the spatial distribution of the bacterial community showed that different phyla were dominant in different regions; 3) the bacterial co-occurrence networks varied seasonally and were dominated by Microcystis, ACK-M1, Chthoniobacteraceae, Synechococcus, Pirellulaceae and Pelagibacteraceae; 4) phytoplankton density, chlorophyll a, water temperature and total nitrogen were the major factors that drove the spatiotemporal variation of bacterial community composition. This study revealed the seasonal succession and spatial distribution of the entire bacterial community in Lake Taihu, providing new insights into the relationship between water bloom-forming cyanobacterial species and other bacteria, and their response to environmental factors in eutrophic freshwater ecosystem.

Culturing the ubiquitous freshwater actinobacterial acI lineage by supplying a biochemical 'helper' catalase

The actinobacterial acI lineage is among the most successful and ubiquitous freshwater bacterioplankton found on all continents, often representing more than half of all microbial cells in the lacustrine environment and constituting multiple ecotypes. However, stably growing pure cultures of the acI lineage have not been established despite various cultivation efforts based on ecological and genomic studies on the lineage, which is in contrast to the ocean from which abundant microorganisms such as Prochlorococcus, Pelagibacter, and Nitrosopumilus have been isolated. Here, we report the first two pure cultures of the acI lineage successfully maintained by supplementing the growth media with catalase. Catalase was critical for stabilizing the growth of acI strains irrespective of the genomic presence of the catalase-peroxidase (katG) gene. The two strains, representing two novel species, displayed differential phenotypes and distinct preferences for reduced sulfurs and carbohydrates, some of which were difficult to predict based on genomic information. Our results suggest that culture of previously uncultured freshwater bacteria can be facilitated by a simple catalase-supplement method and indicate that genome-based metabolic prediction can be complemented by physiological analyses.

Agricultural Risk Factors Influence Microbial Ecology in Honghu Lake

Agricultural activities, including stock-farming, planting industry, and fish aquaculture, can affect the physicochemical and biological characters of freshwater lakes. However, the effects of pollution producing by agricultural activities on microbial ecosystem of lakes remain unclear. Hence, in this work, we selected Honghu Lake as a typical lake that is influenced by agriculture activities. We collected water and sediment samples from 18 sites, which span a wide range of areas from impacted and less-impacted areas. We performed a geospatial analysis on the composition of microbial communities associated with physicochemical properties and antibiotic pollution of samples. The co-occurrence networks of water and sediment were also built and analyzed. Our results showed that the microbial communities of impacted and less-impacted samples of water were largely driven by the concentrations of TN, TP, NO₃⁻-N, and NO₂⁻-N, while those of sediment were affected by the concentrations of Sed-OM and Sed-TN. Antibiotics have also played important roles in shaping these microbial communities: the concentrations of oxytetracycline and tetracycline clearly reflected the variance in taxonomic diversity and predicted functional diversity between impacted and less-impacted sites in water and sediment samples, respectively. Furthermore, for samples from both water and sediment, large differences of network topology structures between impacted and less-impacted were also observed. Our results provide compelling evidence that the microbial community can be used as a sentinel of eutrophication and antibiotics pollution risk associated with agricultural activity; and that proper monitoring of this environment is vital to maintain a sustainable environment in Honghu Lake.

Microbial Community Dynamics During Lake Ice Freezing

Many freshwater environments experience dramatic seasonal changes with some systems remaining ice-covered for most of the winter. Freshwater systems are also highly sensitive to environmental change. However, little is known about changes in microbial abundance and community composition during lake ice formation and times of persistent ice cover. The goal of this study is to characterize temporal dynamics of microbial communities during ice formation and persistent ice cover. Samples were collected in triplicate, five days per week from surface water in the Keweenaw Waterway between November and April. Environmental conditions along with microbial abundance and microbial community composition was determined. Distinct community composition was found between ice-free and ice-covered time periods with significantly different community composition between months. The microbial community underwent dramatic shifts in microbial abundance and diversity during the transitions into and out of ice cover. The richness of the microbial community increased during times of ice cover. Relatives of microbes involved in nitrogen cycling bloomed during times of ice cover as sequences related to known nitrifying taxa were significantly enriched during ice cover. These results help to elucidate how microbial abundance and diversity change over drastic seasonal transitions and how ice cover may affect microbial abundance and diversity.

Statistical determination of crucial taxa indicative of pollution gradients in sediments of Lake Taihu, China

In order to accurately monitor the changes in a freshwater ecosystem in response to anthropogenic stressors, microbe-environment correlations and microbe-microbe interactions were combined to determine crucial indicator taxa in contaminated sediments. The diversity, composition, and co-occurrence pattern of bacterial communities in 23 sediment samples collected from Lake Taihu were explored using 16S rRNA amplicon sequencing analysis. Fisher's exact test showed that the cluster analyses of samples could show a direct correlation between the relative abundance of bacterial communities and the physicochemical properties of the sediment (P < 0.0001), suggesting that bacterial communities can be used to monitor contamination gradients in freshwater sediments. According to the microbe-environment correlation, 24 orders and 60 families were initially identified via indicator species analysis as indicator taxa of different pollution levels. The co-occurrence network further showed that topological features of bacterial communities were clearly different at different pollution levels, although the diversity and composition of bacterial communities displayed similarities between minimally and moderately polluted sites. Indicator taxa were then screened for keystone species, which co-occurrence relationships showed the high degree and low betweenness centrality values (i.e. degree >5, betweenness centrality <1000) of the network. Nine orders and 13 families were finally extracted as crucial indicator taxa of the different pollution levels in eutrophic Lake Taihu. Obtaining crucial indicator taxa from environmental sequences allows to trace increasing levels of pollution in aquatic ecosystems and provides a novel mean to monitor watersheds sensitive to anthropic influences.

How bacterioplankton community can go with cascade damming in the highly regulated Lancang-Mekong River Basin

Rivers make vital contributions to the transport of water, sediment and nutrients from terrestrial to marine ecosystems. However, many large rivers worldwide are suffering from dam regulation. Increasing attention has been paid to bacterioplankton communities since they are highly responsive to river alterations and may influence biogeochemical processes. Here, a comprehensive study was conducted in the highly regulated Lancang-Mekong River Basin to address the question of how bacterioplankton communities respond to cascade damming. The results showed that dam constructions increased nutrient concentrations and threatened water quality in cascade reservoirs. Bacterioplankton cell abundance was reduced by damming, and α-diversity was inhibited in cascade reservoirs. Fortunately, however, river ecosystems were resilient after the remarkable disturbance caused by damming. Moreover, bacterioplankton community composition was significantly altered by cascade dams, including a shift in the dominant phylum from r-strategists to k-strategists. Meanwhile, according to GeoChip analysis, the functional composition of bacterioplankton was less affected than taxonomic composition. In addition, geographic and environmental features both followed a distance-decay relationship with community and functional composition, but the local environment condition was the dominant driver in the Lancang River. Therefore, the impoundments of cascade dams had significant impacts on bacterioplankton communities and more attention should be paid to the potential ecological consequences of river regulation.

Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis

Bovine mastitis continues to be a complex disease associated with significant economic loss in dairy industries worldwide. The incidence rate of subclinical mastitis (IRSCM) can show substantial variation among different farms; however, the milk microbiota, which have a direct influence on bovine mammary gland health, have never been associated with the IRSCM. Here, we aimed to use high-throughput DNA sequencing to describe the milk microbiota from two dairy farms with different IRSCMs and to identify the predominant mastitis pathogens along with commensal or potential beneficial bacteria. Our study showed that Klebsiella, Escherichia-Shigella, and Streptococcus were the mastitis-causing pathogens in farm A (with a lower IRSCM), while Streptococcus and Corynebacterium were the mastitis-causing pathogens in farm B (with a higher IRSCM). The relative abundance of all pathogens in farm B (22.12%) was higher than that in farm A (9.82%). However, the genus Bacillus was more prevalent in farm A. These results may be helpful for explaining the lower IRSCM in farm A. Additionally, the gut-associated genera Prevotella, Ruminococcus, Bacteroides, Rikenella, and Alistipes were prevalent in all milk samples, suggesting gut bacteria can be one of the predominant microbial contamination in milk. Moreover, Listeria monocytogenes (a foodborne pathogen) was found to be prevalent in farm A, even though it had a lower IRSCM. Overall, our study showed complex diversity between the milk microbiota in dairy farms with different IRSCMs. This suggests that variation in IRSCMs may not only be determined by the heterogeneity and prevalence of mastitis-causing pathogens but also be associated with potential beneficial bacteria. In the future, milk microbiota should be considered in bovine mammary gland health management. This would be helpful for both the establishment of a targeted mastitis control system and the control of the safety and quality of dairy products.

Variations of Bacterial Community Composition and Functions in an Estuary Reservoir during Spring and Summer Alternation

In this study, we focused on the dynamics of bacterial community composition in a large reservoir in the Yangtze estuary during spring and summer seasons, especially the variations of functional mechanisms of microbial community during the seasonal alternation between spring and summer. Both 16S rRNA gene sequencing and shotgun metagenomic sequencing technology were used for these purposes. The results indicated that obvious variations of bacterial community structures were found at different sites. Particle-associated bacterial taxa exhibited higher abundance at the inlet site, which was closer to the Yangtze River with a high level of turbidity. In other sites, Synechococcus, as the most dominant cyanobacterial species, revealed high abundance driven by increased temperature. Moreover, some heterotrophic bacterial taxa revealed high abundance following the increased Synechococcus in summer, which indicated potential correlations about carbon source utilization between these microorganisms. In addition, the shotgun metagenomic data indicated during the period of seasonal alternation between spring and summer, the carbohydrate transport and metabolism, energy production and conversion, translation/ribosomal biogenesis, and cell wall/membrane/envelope biogenesis were significantly enhanced at the exit site. However, the course of cell cycle control/division was more active at the internal site.

Four Major South Korea's Rivers Using Deep Learning Models

Harmful algal blooms are an annual phenomenon that cause environmental damage, economic losses, and disease outbreaks. A fundamental solution to this problem is still lacking, thus, the best option for counteracting the effects of algal blooms is to improve advance warnings (predictions). However, existing physical prediction models have difficulties setting a clear coefficient indicating the relationship between each factor when predicting algal blooms, and many variable data sources are required for the analysis. These limitations are accompanied by high time and economic costs. Meanwhile, artificial intelligence and deep learning methods have become increasingly common in scientific research; attempts to apply the long short-term memory (LSTM) model to environmental research problems are increasing because the LSTM model exhibits good performance for time-series data prediction. However, few studies have applied deep learning models or LSTM to algal bloom prediction, especially in South Korea, where algal blooms occur annually. Therefore, we employed the LSTM model for algal bloom prediction in four major rivers of South Korea. We conducted short-term (one week) predictions by employing regression analysis and deep learning techniques on a newly constructed water quality and quantity dataset drawn from 16 dammed pools on the rivers. Three deep learning models (multilayer perceptron, MLP; recurrent neural network, RNN; and long short-term memory, LSTM) were used to predict chlorophyll-a, a recognized proxy for algal activity. The results were compared to those from OLS (ordinary least square) regression analysis and actual data based on the root mean square error (RSME). The LSTM model showed the highest prediction rate for harmful algal blooms and all deep learning models out-performed the OLS regression analysis. Our results reveal the potential for predicting algal blooms using LSTM and deep learning.

Synchrony of Eukaryotic and Prokaryotic Planktonic Communities in Three Seasonally Sampled Austrian Lakes

Freshwater systems are characterized by an enormous diversity of eukaryotic protists and prokaryotic taxa. The community structures in different lakes are thereby influenced by factors such as habitat size, lake chemistry, biotic interactions, and seasonality. In our study, we used high throughput 454 sequencing to study the diversity and temporal changes of prokaryotic and eukaryotic planktonic communities in three Austrian lakes during the ice-free season. In the following year, one lake was sampled again with a reduced set of sampling dates to observe reoccurring patterns. Cluster analyses (based on SSU V9 (eukaryotic) and V4 (prokaryotic) OTU composition) grouped samples according to their origin followed by separation into seasonal clusters, indicating that each lake has a unique signature based on OTU composition. These results suggest a strong habitat-specificity of microbial communities and in particular of community patterns at the OTU level. A comparison of the prokaryotic and eukaryotic datasets via co-inertia analysis (CIA) showed a consistent clustering of prokaryotic and eukaryotic samples, probably reacting to the same environmental forces (e.g., pH, conductivity). In addition, the shifts in eukaryotic and bacterioplanktonic communities generally occurred at the same time and on the same scale. Regression analyses revealed a linear relationship between an increase in Bray-Curtis dissimilarities and elapsed time. Our study shows a pronounced coupling between bacteria and eukaryotes in seasonal samplings of the three analyzed lakes. However, our temporal resolution (biweekly sampling) and data on abiotic factors were insufficient to determine if this was caused by direct biotic interactions or by reacting to the same seasonally changing environmental forces.

Establishment and convergence of photosynthetic microbial biomats in shallow unit process open-water wetlands

The widespread adoption of engineered wetlands designed for water treatment is hindered by uncertainties in system reliability, resilience and management associated with coupled biological and physical processes. To better understand how shallow unit process open-water wetlands self-colonize and evolve, we analyzed the composition of the microbial community in benthic biomats from system establishment through approximately 3 years of operation. Our analysis was conducted across three parallel demonstration-scale (7500 m²) cells located within the Prado Constructed Wetlands in Southern California. They received water from the Santa Ana River (5.9 ± 0.2 mg/L NO₃-N), a water body where the flow is dominated by municipal wastewater effluent from May to November. Phylogenetic inquiry and microscopy confirmed that diatoms and an associated aerobic bacterial community facilitated early colonization. After approximately nine months of operation, coinciding with late summer, an anaerobic community emerged with the capability for nitrate attenuation. Varying the hydraulic residence time (HRT) from 1 to 4 days the subsequent year resulted in modest ecological changes across the three parallel cells that were most evident in the outlet regions of the cells. The community that established at this time was comparatively stable for the remaining years of operation and converged with one that had previously formed approximately 550 km (350 miles) away in a pilot-scale (400 m²) wetland in Northern California. That system received denitrified (20.7 ± 0.7 mg/L NO₃-N), secondary treated municipal wastewater for 5 years of operation. Establishment of a core microbiome between the two systems revealed a strong overlap of both aerobic and anaerobic taxa with approximately 50% of the analyzed bacterial sequences shared between the two sites. Additionally the same species of diatom, Stauirsa construens var. venter, was prolific in both systems as the putative dominant primary producer. Our results indicate that despite differences in scale, geographic location and source waters, the shallow open-water wetland design can select for a rapid convergence of microbial structure and functionality associated with the self-colonizing benthic biomat. This resulting biomat matures over the first growing season with operational parameters such as HRT further exerting a modest selective bias on community succession.

Evaluation of different 16S rRNA gene V regions for exploring bacterial diversity in a eutrophic freshwater lake

Massive partial sequencing of 16S rRNA genes has become the predominant tool used for studying microbial ecology. However, determining which hypervariable regions and primer sets should be used for screening microbial communities requires extensive investigation if controversial results are to be avoided. Here, the performances of different variable regions of the 16S rRNA gene on bacterial diversity studies were evaluated in silico with respect to the SILVA non-redundant reference database (SILVA SSU Ref 123NR), and subsequently verified using samples from Lake Taihu in China, a eutrophic lake. We found that the bacterial community composition results were strongly impacted by the different V regions. The results show that V1-V2 and V1-V3 regions were the most reliable regions in the full-length 16S rRNA sequences, while most V3 to V6 regions (including V3, V4, V3-V4, V5, V4-V5, V6, V3-V6, V4-V6, and V5-V6) were more closely aligned with the SILVA SSU Ref 123NR database. Overall, V4 was the most prominent V region for achieving good domain specificity, higher coverage and a broader spectrum in the Bacteria domain, as confirmed by the validation experiments. S-D-Bact-0564-a-S-15/S-D-Bact-0785-b-A-18 is, therefore, a promising primer set for surveying bacterial diversity in eutrophic lakes.

Close Link Between Harmful Cyanobacterial Dominance and Associated Bacterioplankton in a Tropical Eutrophic Reservoir

Cyanobacteria tend to become the dominant phytoplankton component in eutrophic freshwater environments during warmer seasons. However, general observations of cyanobacterial adaptive advantages in these circumstances are insufficient to explain the prevalence of one species over another in a bloom period, which may be related to particular strategies and interactions with other components of the plankton community. In this study, we present an integrative view of a mixed cyanobacterial bloom occurring during a warm, rainy period in a tropical hydropower reservoir. We used high-throughput sequencing to follow temporal shifts in the dominance of cyanobacterial genera and shifts in the associated heterotrophic bacteria community. The bloom occurred during late spring-summer and included two distinct periods. The first period corresponded to Microcystis aeruginosa complex (MAC) dominance with a contribution from Dolichospermum circinale; this pattern coincided with high water retention time and low transparency. The second period corresponded to Cylindrospermopsis raciborskii and Synechococcus spp. dominance, and the reservoir presented lower water retention time and higher water transparency. The major bacterial phyla were primarily Cyanobacteria and Proteobacteria, followed by Actinobacteria, Bacteroidetes, Verrucomicrobia, and Planctomycetes. Temporal shifts in the dominance of cyanobacterial genera were not only associated with physical features of the water but also with shifts in the associated heterotrophic bacteria. The MAC bloom was associated with a high abundance of Bacteroidetes, particularly Cytophagales. In the second bloom period, Planctomycetes increased in relative abundance, five Planctomycetes OTUs were positively correlated with Synechococcus or C. raciborskii OTUs. Our results suggest specific interactions of the main cyanobacterial genera with certain groups of the heterotrophic bacterial community. Thus, considering biotic interactions may lead to a better understanding of the shifts in cyanobacterial dominance.

The sensitivity and stability of bacterioplankton community structure to wind-wave turbulence in a large, shallow, eutrophic lake

Lakes are strongly influenced by wind-driven wave turbulence. The direct physical effects of turbulence on bacterioplankton community structure however, have not yet been addressed and remains poorly understood. To examine the stability of bacterioplankton communities under turbulent conditions, we simulated conditions in the field to evaluate the responses of the bacterioplankton community to physical forcing in Lake Taihu, using high-throughput sequencing and flow cytometry. A total of 4,520,231 high quality sequence reads and 74,842 OTUs were obtained in all samples with α-proteobacteria, γ-proteobacteria and Actinobacteria being the most dominant taxa. The diversity and structure of bacterioplankton communities varied during the experiment, but were highly similar based on the same time of sampling, suggesting that bacterioplankton communities are insensitive to wind wave turbulence in the lake. This stability could be associated with the traits associated with bacteria. In particular, turbulence favored the growth of bacterioplankton, which enhanced biogeochemical cycling of nutrients in the lake. This study provides a better understanding of bacterioplankton communities in lake ecosystems exposed to natural mixing/disturbances.

Shift in bacterioplankton diversity and structure: Influence of anthropogenic disturbances along the Yarlung Tsangpo River on the Tibetan Plateau, China

River systems have critical roles in the natural water environment and the transportation of nutrients. Anthropogenic activities, including wastewater discharge and river damming, raise adverse impacts on ecosystem and continuum of rivers. An increasing amount of attention has been paid to riverine bacterioplankton as they make vital contributions to biogeochemical nutrient cycle. A comprehensive study was conducted on the bacterioplankton community along the Yarlung Tsangpo River, which is the longest plateau river in China and is suffering from various anthropogenic impacts. The results indicated that nutrient variations corresponded to anthropogenic activities, and silica, nitrogen and phosphorus were retained by the dam. River damming influenced the biomass and diversity of the bacterioplankton, but significant alterations in the community structure were not observed between upstream and downstream of the dam. Moreover, the spatial distribution of the bacterioplankton community changed gradually along the river, and the dominant bacterioplankton in the upstream, midstream and downstream portions of the river were Firmicutes, Bacteroidetes and Proteobacteria, respectively. Soluble reactive phosphorus, elevation, ammonium nitrogen, velocity and turbidity were the main environmental factors that shape the bacterioplankton community. Our study offers the first insights into the variation of a bacterioplankton community of a large river in plateau region.

Temporal patterns of phyto- and bacterioplankton and their relationships with environmental factors in Lake Taihu, China

Phytoplankton and bacterioplankton are integral components of aquatic food webs and play essential roles in the structure and function of freshwater ecosystems. However, little is known about how phyto- and bacterioplankton may respond synchronously to changing environmental conditions. Thus, we analyzed simultaneously the composition and structure of phyto- and bacterioplankton on a monthly basis over 12 months in cyanobacteria-dominated areas of Lake Taihu and compared their responses to changes in environmental factors. Metric multi-dimensional scaling (mMDS) revealed that the temporal variations of phyto- and bacterioplankton were significant. Time lag analysis (TLA) indicated that the temporal pattern of phytoplankton tended to exhibit convergent dynamics while bacterioplankton showed highly stable or stochastic variation. A significant directional change was found for bacterioplankton at the genus level and the slopes (rate of change) and regression R² (low stochasticity or stability) were greater if Cyanobacteria were included, suggesting a higher level of instability in the bacterial community at lower taxonomy level. Consequently, phytoplankton responded more rapidly to the change in environmental conditions than bacterioplankton when analyzed at the phylum level, while bacterioplankton were more sensitive at the finer taxonomic resolution in Lake Taihu. Redundancy analysis (RDA) results showed that environmental variables collectively explained 51.0% variance of phytoplankton and 46.7% variance of bacterioplankton, suggesting that environmental conditions have a significant influence on the temporal variations of phyto- and bacterioplankton. Furthermore, variance partitioning indicated that the bacterial community structure was largely explained by water temperature and nitrogen, suggesting that these factors were the primary drivers shaping bacterioplankton.

Response of bacterial communities to cyanobacterial harmful algal blooms in Lake Taihu, China

Cyanobacterial harmful algal blooms are prevalent around the world, influencing aquatic organisms and altering the physico-chemical properties in freshwater systems. However, the response of bacterial communities to toxic cyanobacterial blooms and associated microcystins (MC) remain poorly understood even though global concentrations of MC have increased dramatically in the past few decades. To address this issue, the dynamics of bacterial community composition (BCC) in the water column and how BCC is influenced by both harmful cyanobacterial blooms and environmental factors were investigated on a monthly basis from August 2013 to July 2014 in Lake Taihu, China. Non-metric multidimensional scaling (NMDS) revealed that seasonal variation in BCC was significant, and that the succession of BCC greatly depends on changes in environmental conditions. Redundancy analysis (RDA) results showed that the overall variation of BCC was explained mainly by dissolved oxygen (DO), nitrate nitrogen (NO₃^--N), and Microcystis. The alpha biodiversity of the bacterial community was different among months with the highest diversity in February and the lowest diversity in October. Furthermore, significant negative relationships were found between alpha biodiversity indices and Microcystis abundance as well as with intracellular MC concentrations, indicating that Microcystis and associated MC may influence the bacterial community structure by reducing its biodiversity. This study shows that potential associations exist between toxic cyanobacterial blooms and bacterial communities but more investigations are needed to obtain a mechanistic understanding of their complex relationships.

Identification of unique microbiomes associated with harmful algal blooms caused by Alexandrium fundyense and Dinophysis acuminata

Biotic interactions dominate plankton communities, yet the microbial consortia associated with harmful algal blooms (HABs) have not been well-described. Here, high-throughput amplicon sequencing of ribosomal genes was used to quantify the dynamics of bacterial (16S) and phytoplankton assemblages (18S) associated with blooms and cultures of two harmful algae, Alexandrium fundyense and Dinophysis acuminata. Experiments were performed to assess changes in natural bacterial and phytoplankton communities in response to the filtrate from cultures of these two harmful algae. Analysis of prokaryotic sequences from ecosystems, experiments, and cultures revealed statistically unique bacterial associations with each HAB. The dinoflagellate, Alexandrium, was strongly associated with multiple genera of Flavobacteria including Owenweeksia spp., Maribacter spp., and individuals within the NS5 marine group. While Flavobacteria also dominated Dinophysis-associated communities, the relative abundance of Alteromonadales bacteria strongly co-varied with Dinophysis abundances during blooms and Ulvibacter spp. (Flavobacteriales) and Arenicella spp. (Gammaproteobacteria) were associated with cells in culture. Eukaryotic sequencing facilitated the discovery of the endosymbiotic, parasitic dinoflagellate, Amoebophrya spp., that had not been regionally described but represented up to 17% of sequences during Alexandrium blooms. The presence of Alexandrium in field samples and in experiments significantly altered the relative abundances of bacterial and phytoplankton by both suppressing and promoting different taxa, while this effect was weaker in Dinophysis. Experiments specifically revealed a negative feedback loop during blooms whereby Alexandrium filtrate promoted the abundance of the parasite, Amoebophrya spp. Collectively, this study demonstrates that HABs formed by Alexandrium and Dinophysis harbor unique prokaryotic and eukaryotic microbiomes that are likely to, in turn, influence the dynamics of these HABs.

Sediment bacterial communities in a eutrophic lake influenced by multiple inflow-rivers

Sediment bacterial communities are sensitive to environmental fluctuations, particularly external input sources. Studying the relationships between bacterial community distribution and the estuarine environment is critical for understanding the river-lake confluence ecosystem and the effect of inflow-rivers on lakes. In the present study, bacterial communities from the sediments of 14 estuaries and four pelagic sites of the Taihu Lake were investigated via high-throughput sequencing. The results demonstrated that Delta-, Beta-, and Gamma-proteobacteria, Acidobacteria, Nitrospira, Bacilli, Anaerolineae, and Actinobacteria were the major classes in sediment bacterial communities of the Taihu Lake. In general, the inflow-rivers of different pollution types have distinctly different influences on sediment bacterial communities of the lake. The bacterial community composition and physicochemical properties of pelagic sites were closer to those of the estuaries of western region which was polluted by serious industrial and agricultural pollution. The bacterial community diversity of estuaries was lower than those of pelagic sites. Spearman correlation analysis indicated that α-diversity of the bacterial community was significantly correlated with C/N, total nitrogen, and total carbon in estuarine sediments. Redundancy analysis revealed that the variance in bacterial community composition was also significantly associated with C/N (24.9%) followed by total phosphorus (15.8%), nitrite (7.2%), and nitrate (7.7%) among different estuaries. This study provides a reference to understand the influence of inflow-rivers on the lake ecosystem, which offered a basic guidance for maintaining the ecological system and protecting the water environment of lacustrine basin.

Characterising and predicting cyanobacterial blooms in an 8-year amplicon sequencing time course

Cyanobacterial blooms occur in lakes worldwide, producing toxins that pose a serious public health threat. Eutrophication caused by human activities and warmer temperatures both contribute to blooms, but it is still difficult to predict precisely when and where blooms will occur. One reason that prediction is so difficult is that blooms can be caused by different species or genera of cyanobacteria, which may interact with other bacteria and respond to a variety of environmental cues. Here we used a deep 16S amplicon sequencing approach to profile the bacterial community in eutrophic Lake Champlain over time, to characterise the composition and repeatability of cyanobacterial blooms, and to determine the potential for blooms to be predicted based on time course sequence data. Our analysis, based on 135 samples between 2006 and 2013, spans multiple bloom events. We found that bloom events significantly alter the bacterial community without reducing overall diversity, suggesting that a distinct microbial community-including non-cyanobacteria-prospers during the bloom. We also observed that the community changes cyclically over the course of a year, with a repeatable pattern from year to year. This suggests that, in principle, bloom events are predictable. We used probabilistic assemblages of OTUs to characterise the bloom-associated community, and to classify samples into bloom or non-bloom categories, achieving up to 92% classification accuracy (86% after excluding cyanobacterial sequences). Finally, using symbolic regression, we were able to predict the start date of a bloom with 78-92% accuracy (depending on the data used for model training), and found that sequence data was a better predictor than environmental variables.

Microbial profiles of a drinking water resource based on different 16S rRNA V regions during a heavy cyanobacterial bloom in Lake Taihu, China

Understanding of the bacterial community structure in drinking water resources helps to enhance the security of municipal water supplies. In this study, bacterial communities were surveyed in water and sediment during a heavy cyanobacterial bloom in a drinking water resource of Lake Taihu, China. A total of 325,317 high-quality sequences were obtained from different 16S ribosomal RNA (rRNA) regions (V3, V4, and V6) using the Miseq sequencing platform. A notable difference was shown between the water and sediment samples, as predominated by Cyanobacteria, Proteobacteria, and Actinobacteria in the water and Proteobacteria, Chloroflexi, and Verrucomicrobia in the sediment, respectively. The LD12 family dominated the water surface and was tightly associated with related indicators of cyanobacterial propagation, indicating involvement in the massive proliferation of cyanobacterial blooms. Alternatively, the genus Nitrospira dominated the sediment samples, which indicates that nitrite oxidation was very active in the sediment. Although pathogenic bacteria were not detected in a large amount, some genera such as Mycobacterium, Acinetobacter, and Legionella were still identified but in very low abundance. In addition, the effects of different V regions on bacterial diversity survey were evaluated. Overall, V4 and V3 were proven to be more promising V regions for bacterial diversity survey in water and sediment samples during heavy water blooms in Lake Taihu, respectively. As longer, cheaper, and faster DNA sequencing technologies become more accessible, we expect that bacterial community structures based on 16S rRNA amplicons as an indicator could be used alongside with physical and chemical indicators, to conduct comprehensive assessments for drinking water resource management.

Ecogenomics of Zooplankton Community Reveals Ecological Threshold of Ammonia Nitrogen

Communities of zooplankton can be adversely affected by contamination resulting from human activities. Yet understanding the influence of water quality on zooplankton under field-conditions is hindered by traditional labor-intensive approaches that are prone to incomplete or uncertain taxonomic determinations. Here, for the first time, an eco-genomic approach, based on genetic diversity in the mitochondrial cytochrome c oxidase I (COI) region of DNA of zooplankton was used to develop a site-specific, water quality criterion (WQC) for ammonia (NH₃). Ammonia has been recognized as a primary stressor in the catchment of the large, eutrophic Tai Lake, China. Nutrients, especially NH₃ and nitrite (NO₃^-) had more significant effects on structure of the zooplankton community than did other environmental factors. Abundances of rotifers increased along a gradient of increasing concentrations of total ammonia nitrogen (TAN), while abundances of copepods and cladocera decreased. A novel, rapid, species sensitivity distribution (SSD) approach based on operational taxonomic units (OTUs) was established to develop a WQC for NH₃. The WQC based on OTUs was consistent with the WQC based on the traditional morphology taxonomy approach. This genetics-based SSD approach could be a useful tool for monitoring for status and trends in species composition and deriving ecological criteria and an efficient biomonitoring tool to protect local aquatic ecosystems in virtually any aquatic ecosystem.

Spatial distribution of planktonic bacterial and archaeal communities in the upper section of the tidal reach in Yangtze River

Bacterioplankton and archaeaplankton communities play key roles in the biogeochemical processes of water, and they may be affected by many factors. In this study, we used high-throughput 16S rRNA gene sequencing to profile planktonic bacterial and archaeal community compositions in the upper section of the tidal reach in Yangtze River. We found that the predominant bacterial phyla in this river section were Proteobacteria, Firmicutes, and Actinobacteria, whereas the predominant archaeal classes were Halobacteria, Methanomicrobia, and unclassified Euryarchaeota. Additionally, the bacterial and archaeal community compositions, richnesses, functional profiles, and ordinations were affected by the spatial heterogeneity related to the concentration changes of sulphate or nitrate. Notably, the bacterial community was more sensitive than the archaeal community to changes in the spatial characteristics of this river section. These findings provide important insights into the distributions of bacterial and archaeal communities in natural water habitats.

Spatiotemporal variation of bacterial and archaeal communities in sediments of a drinking reservoir, Beijing, China

Bacterial and archaeal assemblages are one of the most important contributors to the recycling of nutrients and the decomposition of organic matter in aquatic sediments. However, their spatiotemporal variation and its driving factors remain unclear, especially for drinking reservoirs, which are strongly affected by human consumption. Using quantitative PCR and Illumina MiSeq sequencing, we investigated the bacterial and archaeal communities in the sediments of a drinking reservoir, the Miyun Reservoir, one of the most important drinking sources for Beijing City. The abundance of bacteria and archaea presented no spatiotemporal variation. With respect to community diversity, visible spatial and temporal differences were observed in archaea, whereas the bacterial community showed minor variation. The bacterial communities in the reservoir sediment mainly included Proteobacteria, Bacteroidetes, Nitrospirae, Acidobacteria, and Verrucomicrobia. The bacterial community structure showed obvious spatial variation. The composition of the bacterial operational taxonomic units (OTUs) and main phyla were dam-specific; the composition of samples in front of the dam were significantly different from the composition of the other samples. The archaeal communities were mainly represented by Woesearchaeota and Euryarchaeota. Distinctly spatial and seasonal variation was observed in the archaeal community structure. The sediment NH₄⁺-N, pH, and water depth were identified as the key driving factors of changes in the composition of the bacterial and archaeal communities. Water depth might have the greatest influence on the microbial community structure. The dam-specific community structure may be related to the greater water depth in front of the dam. This finding indicates that water depth might be the greatest contributor to the microbial community structure in the Miyun Reservoir.

Comparison and Interpretation of Taxonomical Structure of Bacterial Communities in Two Types of Lakes on Yun-Gui plateau of China

Bacterial communities from freshwater lakes are shaped by various factors such as nutrients, pH value, temperature, etc. Their compositions and relative abundances would undergo changes to adapt the changing environments, and in turn could affect the environments of freshwater lakes. Analyses of the freshwater lake’s bacterial communities under different environments would be of pivotal importance to monitor the condition of waterbody. In this study, we have collected freshwater samples from two lakes on Yun-Gui plateau of China, Lake Dianchi and Lake Haixihai, and analyzed the bacterial community structures from these samples based on 16S rRNA sequencing. Results have shown that: Firstly, the bacterial community of these samples have very different taxonomical structures, not only between two lakes but also among the intra-groups for samples collected from Dianchi. Secondly, the differences between samples from two lakes are highly associated with the chemical-geographical properties of the two lakes. Thirdly, for samples of Dianchi and Haixihai, analytical results of physicochemical, taxonomical structure and relative abundance of community revealed that extreme physicochemical factors caused by human activities have strongly affected the bacterial ecosystem in Dianchi. These results have clearly indicated the importance of combining biological profiling and chemical-geographical properties for monitoring Chinese plateau freshwater bacterial ecosystem, which could provide clues for Chinese freshwater ecosystem remediation on plateau.

Temporal and Spatial Dynamics of Archaeal Communities in Two Freshwater Lakes at Different Trophic Status

In either eutrophic Dianchi Lake or mesotrophic Erhai Lake, the abundance, diversity, and structure of archaeaplankton communities in spring were different from those in summer. In summer, archaeaplankton abundance generally decreased in Dianchi Lake but increased in Erhai Lake, while archaeaplankton diversity increased in both lakes. These two lakes had distinct archaeaplankton community structure. Archaeaplankton abundance was influenced by organic content, while trophic status determined archaeaplankton diversity and structure. Moreover, in summer, lake sediment archaeal abundance considerably decreased. Sediment archaeal abundance showed a remarkable spatial change in spring but only a slight one in summer. The evident spatial change of sediment archaeal diversity occurred in both seasons. In Dianchi Lake, sediment archaeal community structure in summer was remarkably different from that in spring. Compared to Erhai Lake, Dianchi Lake had relatively high sediment archaeal abundance but low diversity. These two lakes differed remarkably in sediment archaeal community structure. Trophic status determined sediment archaeal abundance, diversity and structure. Archaeal diversity in sediment was much higher than that in water. Water and sediment habitats differed greatly in archaeal community structure. Euryarchaeota predominated in water column, but showed much lower proportion in sediment. Bathyarchaeota was an important component of sediment archaeal community.