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Elucidation of the linkages between the bacterial community composition and chromophoric dissolved organic matter (CDOM) in lake ecosystems is critical for the understanding of the inland water carbon cycling. Despite substantial research into the relationship between the bacteria community and the bulk DOM pool, knowledge of the specific relationship between the optical dynamics of DOM and the bacterioplankton community in lake ecosystems is still poor. We investigated the linkages between the optical dynamics of DOM and bacteria composition in shallow eutrophic Lake Taihu, China. Redundancy Analysis (RDA) indicated that besides water temperature and phytoplankton biomass, also CDOM was an important factor determining the composition of the bacterial community. Generalized Additive Models (GAM) showed that terrestrial humic-like C1 and tyrosine-like C4 were the key factors explaining the abundance of the main bacterial clades. C1 was closely correlated with Verrucomicrobia, Actinobacteria, Alphaproteobacteria, Betaproteobacteria and Planctomycetes, and C4 was closely related to the latter two and to Bacteroidetes. At family level, the dominant families - Pelagibacteraceae (Alphaproteobacteria) and Gemmataceae (Planctomycetes) - were related to both allochthonous and autochthonous CDOM fluorophores but responded differently to the various CDOM components. Tryptophan-like C2 was significantly and positively correlated with Gemmataceae and Ellin6075 (Acidobacteria). Additionally, we found that the biomasses of Cyanophyta, terrestrial humic-like C1, tryptophan-like C4 and C5 were significantly related to the richness of heterotrophic bacterioplankton. Our results provide new insight into the relationship between bacteria and DOM optical dynamics although the mechanisms leading to these relationships need further experimental investigations., (Copyright © 2019 Elsevier B.V. All rights reserved.)

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., (Published by Elsevier B.V.)

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., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Molecular mechanism of interaction between the bloom-forming cyanobacterial species and attached microbios within cyanobacterial aggregates has not been elucidated yet and understanding of which would help to unravel the cyanobacteria bloom-forming mechanism. In this study, we profiled the metabolically active community by high-throughput metatranscriptome sequencing from cyanobacterial aggregates during cyanobacterial bloom period in Lake Taihu, China. A total of 308 million sequences were obtained using the HiSeq 2500 sequencing platform, which provided a great sequence coverage to carry out the in-depth taxonomic classification, functional classification, and metabolic pathway analysis of the cyanobacterial aggregates. The results show that bacteria dominated in cyanobacterial aggregates, accounting for more than 96.66% of total sequences. Microcystis was the most abundant genus, accounted for 26.80% of total assigned sequences at the genus level in cyanobacterial aggregates community; however, Proteobacteria (46.20%) was found to be as the most abundant active bacterial populations at the phylum level. More importantly, nitrogen, phosphonate, and phosphinate metabolism which associated with eutrophication were found in this study. Especially, the enzymes and organisms relating to denitrification and anammox of nitrogen metabolism, which reduced nitrogen concentration by reducing nitrate to nitrogen to inhibit the eutrophication, were first discovered in Lake Taihu during cyanobacterial bloom period. The present study provides a snapshot of metatranscriptome for cyanobacterial aggregates in Lake Taihu and demonstrates that cyanobacterial aggregates could play a key role in the nitrogen cycle in eutrophic water.

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.

Bacterioplankton plays a key role in nutrient cycling and is closely related to water eutrophication and algal bloom. We used high-throughput 16S rRNA gene sequencing to profile archaeal and bacterial community compositions in the surface water of Lake Taihu. It is one of the largest lakes in China and has suffered from recurring cyanobacterial bloom. A total of 81 water samples were collected from 9 different sites in 9 different months of 2012. We found that temporal variation of the microbial community was significantly greater than spatial variation (adonis, n = 9999, P < 1e-4). The composition of bacterial community in December was similar to that in January, and so was the archaeal community, suggesting potential annual periodicity. Unsupervised K-means clustering was used to identify the synchrony of abundance variations between different taxa. We found that the cluster consisting mostly of ACK-M1, C111 (members of acIV), Pelagibacteraceae (alfV-A) and Synechococcaceae showed relatively higher abundance in autumn. On the contrary, the cluster of Comamonadaceae and Methylophilaceae (members of lineage betI and betIV) had higher abundance in spring. The co-occurrence relationships between taxa were greatly altered during the cyanobacterial bloom according to our further network module analysis.

Cyanobacterial blooms represent a significant environmental problem, threatening aquatic ecosystems worldwide. Caused by the eutrophication of water bodies and global climate change, these blooms have altered freshwater ecosystems worldwide during recent decades. Although cyanobacterial blooms are typically caused by blue-green cyanobacteria, which derive their color from the phycocyanin pigment, other pigmented cyanobacterial blooms have been frequently observed in water bodies. These blooms pose a serious environmental threat to inland waters, endangering global public health and aquatic ecosystems. Therefore, comprehending the mechanism of color variation in cyanobacterial blooms is crucial for revealing the outbreak mechanism and implementing effective prevention and control measures. This study developed a human–machine interactive workflow for extracting cyanobacterial blooms and recognizing their colors based on the Forel-Ule index and Sentinel-2 MultiSpectral Instrument data. Using this workflow, the authors conducted spatiotemporal analysis and statistical analysis of bloom color for cyanobacterial blooms in four typical eutrophic lakes from 2019 to 2022. The findings indicated a declining trend in cyanobacterial blooms across the four studied lakes over the years, among which Hulun Lake experienced an annual increase in cyanobacterial blooms and emerged as the lake with the most severe outbreak of such blooms in 2022. The yellowing status of cyanobacterial blooms varied among the four lakes, with Taihu Lake and Dianchi Lake exhibiting a relatively high proportion of green-yellow and yellow cyanobacterial blooms, followed by Chaohu Lake, whereas Hulun Lake had the lowest occurrence. The workflow developed in this study was implemented in Google Earth Engine and provided an automated, integrated, and rapid monitoring solution for the long-term monitoring and color recognition of cyanobacterial blooms. [ABSTRACT FROM AUTHOR]

• Analyzed the taxonomic and functional dynamics of microbial community to algal blooms. • Constructed 161 high-quality metagenome-assembled genomes by binning analysis. • Cyanobacterial strains showed diverse energy pathways, transporters and prokaryotic defense systems. • Nitrogen and phosphorus influence the microbial structure by affecting co-pathways. Freshwater lakes are threatened by harmful cyanobacterial blooms, whose basic unit is Cyanobacterial Aggregate (CA). CA-attached bacteria play a significant role through different blooming stages with substantial variation of their taxonomic structure. However, little is known about their functional variations and functional links with cyanobacteria due to the lack of reference genomes. In this longitudinal study, we collected 16 CA samples from Lake Taihu, one of China's largest freshwater lakes, from April 2015 to February 2016, and sequenced their V4 region of 16S rRNA genes, full metagenomes (MG), and metatranscriptomes (MT). The analysis of these data revealed the dynamics of microbial taxonomic and functional structure in CAs, influenced by both external environmental factors and internal metabolism. 55 OTUs, 456 genes, and 37 transcripts showed significantly differential abundance across the early, middle, and late blooming stages (ANOVA test, P < 0.05). Total nitrogen and total phosphorus were proved to be the most important environmental drivers of microbial taxonomic and functional variations in CAs (Mantel's r > 0.25, P < 0.05). We constructed 161 high-quality metagenome-assembled genomes (MAGs), out of which 22 were cyanobacterial strains with diverse energy pathways, transporters and prokaryotic defense systems. Based on these MAGs, we constructed a cyanobacteria-bacteria co-nitrogen-pathway and a cyanobacteria-bacteria co-phosphorus-pathway, by which we demonstrated how nitrogen and phosphorus influence the dynamics of the microbial structure to a certain extent by affecting these co-pathways. Overall, these results characterized the taxonomic, functional, and transcriptional variations of microbes in CAs through different blooming stages. Genome assembly and metabolic analysis of cyanobacteria and their attached bacteria suggested that the material exchange and signal transduction do, indeed, exist among them. Our understanding of the underlying molecular pathways for cyanobacterial blooms could lead to the control of blooms by interventional strategies to disrupt critical microbes' expression. [Display omitted] [ABSTRACT FROM AUTHOR]

l 2-nFlu was the most predominant NPAH. l ΣNPAHs showed the highest concentration in dry season. l The main source of NPAHs was the direct emission via combustion. l Seven sampling sites in the surface water had health risk. Nitrated polycyclic aromatic hydrocarbons (NPAHs) have toxic potentials that are higher than those of their corresponding parent polycyclic aromatic hydrocarbons (PAHs) and thus have received increasing attention in recent years. In this study, the occurrence, distribution, source, and human health risk assessment of 15 NPAHs and 16 PAHs were investigated in the surface water from 20 sampling sites of Lake Taihu during the dry, normal, and flood seasons of 2018. The ΣPAH concentrations ranged from 255 to 7298 ng/L and the ΣNPAH concentrations ranged from not-detected (ND) to 212 ng/L. Among the target analytes, 2-nitrofluorene (2-nFlu) was the predominant NPAH, with a detection frequency ranging from 85% to 90% and a maximum concentration of 56.2 ng/L. The three-ringed and four-ringed NPAHs and PAHs comprised the majority of the detected compounds. In terms of seasonal variation, the highest levels of the ΣNPAHs and ΣPAHs were in the dry season and flood season, respectively. Diagnostic ratio analysis indicated that the prime source of NPAHs was direct combustion, whereas in the case of PAHs the contribution was predominantly from a mixed pattern including pollution from unburned petroleum and petroleum combustion. The human health risk of NPAHs and PAHs was evaluated using a lifetime carcinogenic risk assessment model. The carcinogenic risk level of the targets ranged from 2.09 × 10−7 to 5.75 × 10−5 and some surface water samples posed a potential health risk. Image, graphical abstract [ABSTRACT FROM AUTHOR]