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

Science of the Total Environment 669 (2019) 29–40

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Seasonal succession and spatial distribution of bacterial community structure in a eutrophic freshwater Lake, Lake Taihu Congmin Zhu a,h, Junyi Zhang b,c, Muhammad Zohaib Nawaz d,e,f, Shahid Mahboob g, Khalid A. Al-Ghanim g, Iqrar Ahmad Khan e, Zuhong Lu b,⁎, Ting Chen h,i,⁎⁎ a MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, Beijing; National Research Center for Information Science and Technnology, Department of Automation, Tsinghua University, Beijing 100084, China b State Key Lab for Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China c Wuxi Environmental Monitoring Centre, Wuxi 214121, China d Department of Computer Science, University of Agriculture, Faisalabad 38040, Pakistan e Center for Advanced Studies in Agriculture and Food Security, University of Agriculture, Faisalabad 38040, Pakistan f Wuxi Metagene Science & Technology Co., Ltd, Wuxi, People's Republic of China g Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia h Institute for Artificial Intelligence, State Key Lab of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China i Tsinghua-Fuzhou Institute of Digital Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Analyzed the seasonal and spatial dynamics of the entire bacterial community composition involved in cyanobacterial blooms • Found strong seasonal but weak spatial succession in bacterial community composition due to the cyanobacterial variation • Explored the relationships among Microcystis, Synechococcus (picocyanobacteria) and their related bacteria • Determined the main factors that drove the spatiotemporal variation of bacterial community composition

a r t i c l e

i n f o

Article history: Received 24 October 2018 Received in revised form 4 March 2019 Accepted 6 March 2019 Available online 08 March 2019 Editor: Henner Hollert Keywords: Cyanobacterial blooms Bacterial community

a b s t r a c t 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

⁎ Corresponding author. ⁎⁎ Corresponding author at: Institute for Artificial Intelligence, State Key Lab of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. E-mail addresses: [email protected] (Z. Lu), [email protected] (T. Chen).

https://doi.org/10.1016/j.scitotenv.2019.03.087 0048-9697/Published by Elsevier B.V.

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C. Zhu et al. / Science of the Total Environment 669 (2019) 29–40

16S rRNA gene Seasonal succession Spatial distribution Driving factors

stronger than spatial variation due to the clearly seasonal variation of Microcystis, Synechococcus (picocyanobacteria) 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.

1. Introduction

costs and reducing the supply of potable water. The serious consequences of CyanoHAB in Lake Taihu have resulted in increased demands for further studies to supply effective measures for treatment and prevention. Exploring how bacterial communities respond to environmental changes, their spatial distribution across the lake and the driving factors in different seasons will provide biological insights potentially allowing control of blooms by interventional strategies to disrupt their whole response. Therefore, by collecting samples of the fraction larger than 0.22 μm spanning an entire year and the entire Lake Taihu, we examined the seasonal and spatial dynamics of the bacterial community in Lake Taihu, explored the seasonal dynamics of relationship networks with the dominant (pico-) cyanobacterial genus and their related bacteria, and detected the major driving factors of bacterial community structure.

Microorganisms play an important role in energy conversion and information transmission (Okafor, 2011; Pernthaler, 2013) in aquatic ecosystems, and are sensitive to fluctuations in the external environment. Bacteria respond to environmental changes by altering the composition of the planktonic colony, which can to an extent, reflect the state of the water environment through regulating water quality control (Hahn, 2006). Previous studies have extensively reported that cyanobacterial blooms are caused by the imbalance of nutrients, including nitrogen and phosphorus (Paerl et al., 2011; Xu et al., 2010). Recently, 16S rRNA gene sequencing has emerged as a molecular marker for species demarcation of prokaryotes and many studies have focused on the microbial community structure involved in cyanobacterial blooms. Numerous studies have focused on free-living bacteria (Li et al., 2015; Niu et al., 2011) and planktonic colony attached bacteria (Cai et al., 2014; Tang et al., 2015), and have given us important insights into the bacterial community structure involved in cyanobacterial blooms. In previously published literature, the fraction smaller than 3 μm (LaMontagne and Holden, 2003; Ortega-Retuerta et al., 2013; Vani et al., 2014) or between 0.22–3 μm (Crespo et al., 2013) was considered free-living bacteria, while the fraction larger than 3 μm (Crespo et al., 2013; LaMontagne and Holden, 2003; Ortega-Retuerta et al., 2013) or between 3–50 μm (Vani et al., 2014) was considered as colony attached bacteria. These studies have shown that while there are significant phylogenetic differences between free-living bacteria and attached bacteria, there exists a close relationship and rapid exchange between them (Tang et al., 2015). When the environment changes, free-living bacteria and attached bacteria are believed to produce their responses and affect each other, resulting in an overall joint response. We are interested in how they respond as a whole to environmental changes. Additionally, in previous work, picocyanobacteria (cells b2 μm) (Haverkamp et al., 2009), which were reported to play an important role in eutrophic lakes (Dittrich et al., 2004; Vörös et al., 1998), were often filtered out when we collected the fraction larger than 3 μm. The role of picocyanobacteria in microbial communities needs to be further analyzed. Therefore, in this study we intend to analyze the entire bacterial community including picocyanobacteria involved in cyanobacterial blooms and its response to environmental factors. This will not only shed light on bacterial diversity and the environmental factors driving whole community variation, but also report the succession of dominant cyanobacterial genera and detect their relationships with picocyanobacteria (cells b2 μm) and other free-living bacteria. Several studies have been carried out on the fraction larger than 0.22 μm to evaluated the entire bacterial community in eutrophic lakes (Berry et al., 2017; Tang et al., 2015) and reservoirs (Liu et al., 2015a). Lake Taihu is the third largest freshwater lake in China irrigating millions of hectares of grains and cotton in a lush agricultural region and supplying drinking water for N2 million people (Lucie, 2007; Qin et al., 2007). However, since the beginning of the twentieth century, Cyanobacterial Harmful Algal Blooms (CyanoHABs) have been a frequent occurrence in Lake Taihu, resulting in the production of harmful toxins and causing hypoxia in the water, thereby dramatically increasing water treatment

2. Material and methods 2.1. Sample collection and site geochemistry To cover the entire lake, 61 samples were collected from January 2013 to December 2013 from six sampling stations including Da Pukou (DP), Mei Lianghu (ML), Ping Taishan (PT), Sha Zhunan (SZ), Xu Hu (XH) and Xiao Meikou (XM) (Fig. S1A and Table S1). To collect samples, water was collected at a depth of 0.5 m with a 2 L Schindler sampler and filtered through 0.22 μm (Berry et al., 2017; Liu et al., 2015a) mixed fiber microporous membranes (Shanghai Xinya). The fraction N0.22 μm was used to extract DNA and corresponding water samples are used for physical and chemical analysis. Water temperature (WT), dissolved oxygen (DO) and pH were measured using YSI6600-V2 (USA). The physical and chemical indicators of water environment, including total phosphorus (TP) (standard method: GB/T11893–1989), total nitrogen (TN) (HJ 636–2012), ammonia nitrogen (NH4+-N) (HJ 535–2009), potassium permanganate index (CODMn) (GB/T11892–1989), chemical oxygen demand (CODCr) (GB/T11914–1989) and biochemical oxygen demand (BOD5) (HJ 505–2009), were measured in accordance with the corresponding standard methods. Density analyses of suspension (SS), chlorophyll a (Chla) and phytoplankton (PD) were determined using the Water and Wastewater Monitoring Analysis Method (V. 4). 2.2. DNA extraction and sequencing Samples were treated with Guaranteed Reagent levels of anhydrous ethanol at 20 °C, and DNA was extracted using MO BIO's Power Clean ® DNA Clean-Up kit according to the manufacturer's instructions. Next, the DNA was used as the template for amplifying the V4 region of 16S rRNA gene. PCR primer pairs previously validated in the literature (Zhang et al., 2017a; Zhang et al., 2017b) used in this study were as follows: forward (F) 5′- AYTGGGYDTAAAGNG -3′ and reverse (R) 5′TACNVGGGTATCTAATCC -3′. Based on the Ion torrent PGM platform (318 chips), single-end sequencing was performed on V4 region (250 bp) of the 16S rRNA gene to assess the taxonomic composition using the Illumina MiSeq sequencing platform. The sequences were deposited into the National Center for Biotechnology Information (NCBI)

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(Coordinators, 2016) database with the Sequence Read Archive (SRA) accession number of SRP173897.

b0.62) (Deng, 2012; Jizhong et al., 2010; Olesen et al., 2007; Shi et al., 2016).

2.3. 16S rRNA gene sequences data processing

3. Results

The raw 16S rRNA gene sequence data were analyzed using Quantitative Insights into Microbial Ecology (QIIME v1.9.1) (Caporaso et al., 2010). In brief, sequences were demultiplexed based on a unique barcode assigned to each sample. Sequences with quality scores lower than 20 or length shorter than 200 bp were filtered out. Qualified sequences were then clustered into species-level OTUs (Operational Taxonomic Units) using an open-reference OTU picking protocol at a 97% similarity cutoff in QIIME with UCLUST (Edgar, 2010). The GreenGenes database (version 13_5) (Desantis et al., 2006) was used as the reference to identify their taxonomic origins. Chimera reads and the corresponding OTUs were removed by ChimeraSlayer (Haas et al., 2011) and QIIME scripts. Raw abundance of OTUs in each sample were estimated by counting the reads number of each OTU, and then diversity analyses were conducted. The smallest read count in our samples (~25 K sequences) was used to re-sample the original OTU table for normalizing the sequencing depth.

3.1. Temporal-Spatial variations of environmental variables

2.4. Microbial diversity and statistical analysis After we obtained OTU tables with equal sequencing depth and phylogenetic trees, microbial richness (Margalef), evenness (Pielou), and diversity (Shannon-Wiener) were estimated using the R statistical calculation software package vegan (O'Hara et al., 2011). To test statistical significance of difference in community composition across different sampling seasons or stations, the vegdist, anosim, adonis and cor.test functions in R software (v. 3.4.1) were used for calculation. The threshold was set as Bonferroni corrected p-value b 0.05. For β-diversity, OTU table-based Bray-Curtis metric and phylogenetic-based Unifrac metric were employed to measure the pairwise community distance between samples. Principal coordinate analysis (PCoA) was used to visualize the Bray-Curtis distance matrix of 61 samples with ade4 and ggplot2 packages in R software. The hierarchical clustering method UPGMA (Unweighted Pair Group Method with Arithmetic Mean) was applied to group samples based on the unweighted unifrac metric and FigTree v1.4.0 was used to visualize the resulting clustering tree. Also in R software, hclust for cluster analysis was used for data analysis, as well as the heatmap package. In addition, canonical correspondence analysis (CCA) and redundancy analysis (RDA) were performed with vegan package in R. 2.5. Network construction and analysis Co-occurrence networks were constructed for each season based on OTU relative abundance using Molecular Ecological Network Analyses (MENA) (Deng et al., 2012; Jizhong et al., 2010; Jizhong et al., 2011), which calculated the Pearson correlation coefficients (PCC) for each pair of OTUs, and then used a permutation test to compute the statistical significance of the PCC values. The similarity thresholds were determined for microbial communities based on the random matrix theory approach. If two OTUs have a correlation larger than the similarity threshold, this correlation is significant (P b 0.01). Edges were set between pairs of OTUs for which the PCC was significant. Then, the network was visualized with Cytoscape (Assenov et al., 2007). We then characterized network modularity for each network constructed for each season with the greedy modularity optimization method (Deng et al., 2012; Shi et al., 2016). We used modularity bigger than 0.4 as the threshold to detect modules. To identify the topological roles in the network of each node, its within-module connectivity (Zi) and among-module connectivity (Pi) were used to classify the node into four categories: module hubs (Zi N 2.5), network hubs (Zi N 2.5 and Pi N 0.62), connectors (Pi N 0.62) and peripherals (Zi b 2.5 and Pi

In total, ten environmental factors were measured (Table S2). Referring to the Chinese environmental quality standards for surface water (GB3838–2002), Total Nitrogen (TN) was used as the water quality index. The annual TN peak was in March (3.63 mg/L), and the second highest value was 3.06 mg/L in June. Generally, TN trends toward higher values in the first half of the year and lower values in the second half of the year (Fig. 1A). The variation in NH4+-N was roughly similar to that of TN. The annual mean of the total phosphorus (TP) was 0.08 mg/L and the monthly level was variable, ranging from 0.04 to 0.12 mg/L. The annual means of the physical and chemical parameters of water quality for six stations in Lake Taihu are shown in Table S3. The water quality at station DP was the poorest of the six stations with a mean TN of 3.04 mg/L, and Total Phosphorous (TP) as high as 0.13 mg/L. The water quality at Station XH was the best with TN and TP values of 1.55 mg/L and 0.03 mg/L, respectively, both lower than the means of the entire lake. We divided 61 samples into four seasons (Winter-Spring-SummerAutumn) based on the meteorological conditions of the Lake Taihu region, in particular the lake water temperature. Spring falls between April and June with a mean temperature of 19.3 °C. Summer lasts from July to October with a mean temperature of 27.9 °C. Autumn runs from November through to December with a mean temperature of 13.5 °C. Winter includes the months of January through to March with a mean temperature of 6.9 °C. Both phytoplankton density and chlorophyll a showed significant differences across the four seasons by ANOVA test with the highest phytoplankton density occurring in summer (October) and the highest chlorophyll a occurring in autumn (November) (Fig. 1A). Surprisingly, the whole lake average density peaks of phytoplankton and chlorophyll a did not appear in summer (July–October), but rather in December (9.4°C) when they were as high as 1.86 × 108 cell/L and 83 mg/m3, respectively (Table S4). The annual mean of phytoplankton was 4.56 × 107 cell/L, and varied between 0.37 and 923 × 107 cell/L. The annual mean value of chlorophyll a was 27.4 mg/m3 with variation of 4–154 mg/m3. In terms of the trend, the peak phytoplankton density in 2013 did not appear in the summer during cyanobacterial bloom formation; instead, it appeared in the months with lower water temperature (November–December). This phenomenon may be related to meteorological conditions such as typhoons in July–August 2013. Additionally, the regions which experience cyanobacterial blooms have recently spread from bays to the center of the lake, and the timing of cyanobacterial blooms has expanded from summer to winter (Ma et al., 2016; Zhang et al., 2018). 3.2. Seasonal succession of bacterial composition Bacteria in Lake Taihu showed obvious seasonal succession. At the OTU level, adonis was used to test the four quarters and gave a result of R2 = 0.38, p b 0.01, which indicated that a significant difference existed across the four groups. Bacterial richness, evenness and diversity were shown in Table S5. ANOVA test showed significantly different richness, evenness and diversity across four seasons (Fig. 1B) of which bacterial diversity was highest during spring and lowest during autumn. Based on Bray-Curtis similarity, PCoA results clearly showed that the 61 samples could be divided into three groups (I-III) (Fig. S1B). Group I included all samples from winter and some samples from spring. Group II consisted of the remaining spring samples, all summer samples, and three autumn samples. Group III only contained autumn samples. According to UPGMA clustering analysis of the top 60 abundant OTUs, 61 samples were divided into five significantly different groups (Adonis,

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C. Zhu et al. / Science of the Total Environment 669 (2019) 29–40

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Fig. 1. Variations in environmental factors and comparison of bacterial diversity. (A) The variations of average phytoplankton density, chlorophyll a, temperature and total nitrogen for each sampling station along sampling time. (B) Seasonal comparison of the richness (Margalef), evenness (Pielou), and diversity (Shannon-Wiener). (C) Spatial comparison of the richness, evenness and diversity.

R2 = 0.71, N = 17,686, p = 0.00) (Fig. 2). According to clustering analysis, six of the 11 samples in Cluster 1 were collected in spring and the other five from summer. Nine of the 17 samples in Cluster 2 were collected in summer and three from autumn. All nine samples in Cluster 5 were from autumn. Eighteen of the 24 samples in Cluster 4 and Cluster 5 were from winter and the remaining six samples were from spring. These results showed the obvious seasonal succession of bacterial community structure. During the survey period, Cyanobacteria (26.5%), Proteobacteria (23.3%), Verrucomicrobia (13.4%) and Actinobacteria (11.9%) were the dominant phyla and peaked in December (74.7%), January (40.6%), October (19.4%), April (19.5%), respectively (Fig. S1C). Different phyla dominated different seasons with different relative abundance (Fig. 3). ANOSIM analysis of the top 15 phyla containing the largest number of OTUs was conducted to determine obvious and significant differences between adjacent seasons and across the four seasons (Table S6). Between summer and autumn, among the top 15 abundant phyla, only

TM7 showed no significant difference. Similarly, neither Nitrospirae nor OP3 showed significant differences between winter and spring. It is worth noting that, among the remaining phyla, significant differences were all observed either between adjacent seasons or across the four seasons. These results suggested that the bacterial community in Lake Taihu has obvious seasonal succession at the phylum level. Furthermore, the succession at the genus level between adjacent seasons was identified through the ANOSIM analysis (Fig. 3). Among the dominant 20 genera, 17 genera were found to differ significantly across the four seasons (p-value b 0.05). Cyanobacteria represented the most abundant phylum, with three predominant genera Microcystis (13.7%), Synechococcus (2.9%) and Dolichospermum (0.3%). As the first dominant genus, Microcystis showed significant differences between all adjacent seasons except from winter to spring. It is worth noting that Synechococcus (pico- cyanobacterial genus) appeared mainly in spring and summer. Additionally, except from summer to autumn Synechococcus showed significant difference between all other adjacent seasons.

C. Zhu et al. / Science of the Total Environment 669 (2019) 29–40

Cluster 2

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Cluster 4

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Microcystis Candidatus_Xiphinematobacter Acidimicrobiales Actinobacteria Row Actinomycetales Phycisphaerales Z-Score TM7 Planctomycetes  Synechococcaceae Synechococcus Synechococcus Holophagaceae  Pelagibacteraceae Alphaproteobacteria Gemmatimonadetes Acidobacteria  Sinobacteraceae Pedosphaerales Planctomyces Pedosphaerales  Chlorobi:OPB56 Pirellulaceae Ellin6075 Haptophyceae -2 Isosphaeraceae Stramenopiles Flavobacterium Verrucomicrobiaceae -4 Methylotenera Polynucleobacter Comamonadaceae Burkholderiales -6 Janthinobacterium Methylophilaceae Betaproteobacteria Proteobacteria Luteolibacter Gemmataceae Bacteroidetes Xanthomonadaceae Xanthomonadaceae Chitinophagaceae Chitinophagaceae Sphingobacteriales Fluviicola Cyclobacteriacear ACK−M1 Sediminibacterium Cerasicoccaceae Cryptophyta Opitutus R4−41B Chthoniobacteraceae Cytophagaceae Prosthecobacter Methylophilaceae Saprospiraceae Methylacidiphilae Bacteria Gammaproteobacteria

67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67

Summer

Spring

Autumn

Winter

Fig. 2. UPGMA and heatmap of bacterial samples based on the abundance of the top 60 OTUs.

3.3. Spatial variations of bacterial composition To examine whether significant spatial variation appeared across different sampling stations, we performed an ANOVA test on richness, evenness and diversity. We found that there was no significant difference in bacterial diversity among sampling stations (Fig. 1C). This was verified by Adnois test on OTU composition showing that variation across different sampling stations (R2 = 0.04, p = 0.61, permutation n = 9999) was less significant than that across different seasons (R2 = 0.38, p b 0.01, permutation n = 9999). Additionally, from the PCoA plot (Fig. S1B) samples collected from same stations were less similar to each other, suggesting that spatial variations were smaller. However, the spatial distribution of bacterial α-diversity with richness, evenness, and diversity revealed a certain regularity (Fig. 4A). XH has the highest bacterial diversity and ML has the lowest bacterial diversity. The spatial distributions of the top 10 dominant phyla across the four seasons were shown in Fig. 4B. Different phyla dominated different stations. During spring, Actinobacteria and Bacteroidetes were dominant in the northern lake region (ML). Gemmatimonadetes and Chlorobi were abundant in the eastern lake region (XH), and Cyanobacteria in the center of the lake (PT). The maximum dominance of Planctomycetes and Proteobacteria appeared in the southern lake region (XM) and the western lake region (DP), respectively. In summer, the maximum dominance of Cyanobacteria appeared in the northern lake region (ML), Actinobacteria in the

eastern lake region (XH), Proteobacteria and Verrucomicrobia in the center of lake (PT), Bacteroidetes and Gemmatimonadetes in the southern lake region (XM), and, Planctomycetes, Chloroflexi, and Chlorobi in the western lake region (DP). In autumn, Planctomycetes predominantly appeared in SZ. Enrichment of Proteobacteria, Actinobacteria, Bacteroidetes, Acidobacteria, Chloroflexi, and Chlorobi was found in the eastern lake region (XH). Abundance peaks of Gemmatimonadetes, Cyanobacteria and Verrucomicrobia respectively appeared in the center of lake (PT), the southern lake region (XM) and the western lake region (DP). In winter, Cyanobacteria and Bacteroidetes were dominant in the northern lake region (ML). Abundance peaks of Verrucomicrobia and Actinobacteria appeared in SZ, Chloroflexi, Gemmatimonadetes, and Chlorobi in the eastern lake region (XH), Planctomycetes in the lake heart region (PT), Acidobacteria in the southern lake region (XM), and, Proteobacteria in the western lake region (DP). 3.4. Seasonal succession of bacterial co-occurrence patterns To explore the succession of OTU associations across four seasons, co-occurrence networks were constructed for each season (Fig. 5) and the node roles in those networks were identified based on the topological characteristics (Fig. S2). Using the random matrix theory, the thresholds were determined to be 0.85 for all microbial communities (Table S7). The node connectivity of all the networks showed scale-

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C. Zhu et al. / Science of the Total Environment 669 (2019) 29–40

Candidatus_Xiphinematobacter ** Synechococcus ** Flavobacterium * Methylotenera ** Fluviicola ** Opitutus ** Polynucleobacter * Planctomyces ** Top three phyla: Prosthecobacter ** Proteobacteria (23.5%) Janthinobacterium ** Cyanobacteria (16.2%) Actinobacteria (14.3%)

Top three phyla: Proteobacteria (34.1%) Verrucomicrobia (14.9%) Actinobacteria (14.4%) 15%

31%

15%

Winter Microcystis ** Candidatus_Xiphinematobacter Methylotenera ** Synechococcus * Opitutus ** Polynucleobacter ** Prosthecobacter ** Janthinobacterium ** Luteolibacter ** Planctomyces

19%

20%

Spring

22%

11%

**

6%

*

Microcystis Candidatus_Xiphinematobacter Synechococcus Flavobacterium Opitutus Fluviicola Planctomyces Methylotenera Prosthecobacter Sediminibacterium Others

Microcystis ** Synechococcus ** Planctomyces ** Opitutus ** Fluviicola *

Opitutus 3.3%** 16% Fluviicola 3.2%** Planctomyces 3.1%** Prosthecobacter 2.4%** Synechococcus 9.9%** Candidatus_Xiphinematobacter 16.2%** Sediminibacterium 2.5%* Flavobacterium 4.3%* Methylotenera 2.6%** 14% Microcystis 33.7%**

Sediminibacterium * Prosthecobacter * Polynucleobacter * Methylotenera * Rhodobacter ** 39%

9%

Autumn

Summer 16%

76%

17% Top three phyla: Cyanobacteria (60.7%) Proteobacteria (12.5%) Verrucomicrobia (8.7%)

Microcystis ** Planctomyces ** Opitutus * Fluviicola * Prosthecobacter * Flavobacterium ** Janthinobacterium * Gemmatimonas ** Dolichospermum * Rubrivivax **

Top three phyla: Cyanobacteria (26.4%) Proteobacteria (18.4%) Planctomycetes (15.2%)

Fig. 3. Dominant genera with significant differences in seasonal succession in Lake Taihu. Ring charts characterize the composition of seasonal average profiling of dominant genera. The description in the center is the annual average profiling of dominant genera. Red arrows indicate a significant increase between adjacent seasons and blue arrows indicate a significant decrease. * 0.01 b p ≤ 0.05, ** p ≤ 0.01. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

free characteristics, as indicated by R2 of the power law distribution of node degree ranging from 0.80 to 0.91, and were significantly different from random networks generated using identical numbers of nodes and links based on the average clustering coefficient and average geodesic distance, indicating that the network structures were unlikely due to chance. (Tables S7). Overall, taxa tended to co-occur (positive correlations, red lines) rather than co-exclude (negative correlations, blue lines); positive correlations accounted for 92–100% of the potential interactions observed during all four seasons (Fig. 5). Microbial communities formed larger networks with more nodes in spring and summer than in autumn and winter (Table S7). It is important to note that although the autumn network had the fewest nodes, it had the second largest number of edges surpassed only by the summer network. To assess possible topological roles of taxa in the networks, we classified nodes into four categories: peripherals, connectors, module hubs and network hubs (Fig. S2, see methods for definitions). Module hubs

were detected in all networks except autumn. The five module hubs identified originated from Verrucomicrobia, Proteobacteria, Actinobacteria and two Planctomycetes (Fig. 5 and Fig. S2). Connectors were also detected in summer and winter but not in spring and autumn. Five out of seven connectors in these rhizosphere networks were Actinobacteria, Gemmatimonadetes, Planctomycetes and the other two were from Bacteroidetes (Fig. 5 and Fig. S2). No network hubs were detected in any of the networks, as no single node had Pi N 0.62 and Zi N 2.5 (Fig. S2). To identify the taxonomic composition for each network, we visualized the phylogeny for major modules with at least 20 nodes and labeled the dominant families in each module (Fig. 5). During spring, Microcystis, Betaproteobacteria, and Cerasicoccaceae were predominant in module 8. In addition, Synechococcus and Pirellulaceae with high abundance appeared in module 3. Modules 1 and 3 were highly correlated and mainly composed of Synechococcus and Pirellulaceae. Modules 2, 4, 5, and 6 were relatively diverse, the main components of which

C. Zhu et al. / Science of the Total Environment 669 (2019) 29–40

B

A

Spring

Summer

Autumn

35

Winter

High:0.25 Low: 0.10

High:600 Low:400

Cyanobacteria

Proteobacteria

Verrucomicrobia

Margalef

High:1.0 Low:0.5

Actinobacteria

Planctomycetes

Bacteroidetes

Pielou

High: 7.0

Acidobacteria

Low: 5.0

Chloroflexi

Gemmatimonadetes

Shannon-Wiener Chlorobi

Fig. 4. Spatial variations of bacterial composition. (A) Spatial changes of bacterial α-diversity in Lake Taihu. (B) Spatial changes of dominant phyla of bacteria in Lake Taihu across four seasons.

were ACK-M1, Chitinophagaceae, Sphingobacteriaceae, Pelagibacteraceae, and Actinomycetales. During summer, Microcystis, Candidatus_Xiphine matobacter and Pirellulaceae formed module 3. It is noteworthy that modules 1, 2, 4 and 5 were highly correlated and that the main species were Gemmataceae, Chitinophagaceae, Candidatus_Xiphinematobacter, ACK-M1, Pirellulaceae, Phycisphaerales, Synechococcaceae, CL500–15,

Actinomycetales, and Pelagibacteraceae. In autumn, only five highly correlated modules appeared. Microcystis, Cerasicoccaceae, and Burkholderiales appeared in module 1, while ACK-M1 appeared in module 2, along with Actinomycetales and Betaproteobacteria. During winter, Microcystis, Actinomycetales, and Xanthomonadaceae appeared in module 9. Modules 1, 2, 3 were highly correlated, the main species of

36

C. Zhu et al. / Science of the Total Environment 669 (2019) 29–40

c__Actinobacteria c__Actinobacteria c__Betaproteobacteria c__Betaproteobacteria c__Betaproteobacteria c__Betaproteobacteria c__Actinobacteria

c__Alphaproteobacteria c__Sphingobacteriia c__[Pedosphaerae] c__Alphaproteobacteria

c__Planctomycetia

c__Oscillatoriophycideae

c__Actinobacteria c__Actinobacteria c__Betaproteobacteria c__Betaproteobacteria c__Betaproteobacteria c__Betaproteobacteria

c__Opitutae

c__Alphaproteobacteria

c__Oscillatoriophycideae

c__Actinobacteria

c__[Saprospirae]

c__Betaproteobacteria

c__Planctomycetia

c__[Leptospirae]

c__Gemmatimonadetes

c__Gemmatimonadetes

c__Alphaproteobacteria c__Sphingobacteriia c__[Pedosphaerae] c__Alphaproteobacteria

c__Planctomycetia

c__Oscillatoriophycideae

c__Opitutae

c__Planctomycetia

c__Betaproteobacteria

c__[Leptospirae]

c__Gemmatimonadetes

c__[Pedosphaerae]

c__Actinobacteria

c__[Saprospirae]

c__Planctomycetia

c__Gammaproteobacteria

c__Synechococcophycideae c__Sphingobacteriia c__Opitutae

c__Betaproteobacteria

c__Alphaproteobacteria

c__Planctomycetia

c__Actinobacteria c__Betaproteobacteria

c__Actinobacteria

c__Chloroplast

c__[Spartobacteria]

c__Alphaproteobacteria

c__Betaproteobacteria

c__[Spartobacteria] c__Chloroplast

c__Planctomycetia

c__[Saprospirae]

c__[Saprospirae]

c__Actinobacteria

c__Gammaproteobacteria

c__Actinobacteria

c__Acidimicrobiia

0

c__Actinobacteria

0

c__[Saprospirae]

c__Betaproteobacteria

c__Acidimicrobiia

c__Actinobacteria

0 c__Betaproteobacteria

0

c__Actinobacteria

c__Actinobacteria c__Actinobacteria

c__Flavobacteriia

c__Betaproteobacteria

c__[Methylacidiphilae] c__Alphaproteobacteria

c__Alphaproteobacteria c__Actinobacteria

c__Actinobacteria

c__Flavobacteriia

c__Betaproteobacteria

c__Actinobacteria

c__Gammaproteobacteria c__Planctomycetia

c__Oscillatoriophycideae

c__Actinobacteria

c__Planctomycetia

c__Alphaproteobacteria

c__Planctomycetia

c__Oscillatoriophycideae

c__[Spartobacteria]

c__Alphaproteobacteria

c__[Spartobacteria]

c__Planctomycetia

0

c__[Saprospirae] c__Synechococcophycideae c__Alphaproteobacteria

c__OM190

c__Planctomycetia

c__Planctomycetia

c__[Saprospirae] c__Synechococcophycideae c__Alphaproteobacteria

c__Alphaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Acidimicrobiia c__Gammaproteobacteria

c__Gammaproteobacteria

c__OM190

c__Planctomycetia

c__Alphaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Gammaproteobacteria c__[Spartobacteria]

c__Actinobacteria c__Oscillatoriophycideae

c__[Methylacidiphilae]

c__Alphaproteobacteria

c__OPB56

c__Actinobacteria

c__Planctomycetia

0

c__Betaproteobacteria

c__Acidimicrobiia

0

0

c__Alphaproteobacteria

0

c__[Saprospirae]

c__Synechococcophycideae

0 c__Betaproteobacteria

c__Actinobacteria

c__Synechococcophycideae

c__Actinobacteria c__Actinobacteria

0

c__[Saprospirae]

c__[Saprospirae]

c__Actinobacteria

0

c__Synechococcophycideae

c__Betaproteobacteria c__Synechococcophycideae

c__OPB56

c__Gammaproteobacteria

c__Alphaproteobacteria

c__[Spartobacteria] c__Actinobacteria

c__Gammaproteobacteria

c__Actinobacteria c__Acidimicrobiia

0

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Planctomycetia

c__Chloroplast

c__[Spartobacteria] c__Chloroplast

0

c__Actinobacteria

c__Cytophagia c__Synechococcophycideae

c__Betaproteobacteria c__Alphaproteobacteria c__Oscillatoriophycideae

c__Actinobacteria

c__[Spartobacteria]

c__[Spartobacteria]

c__Acidimicrobiia

c__Actinobacteria

c__Gammaproteobacteria

c__[Spartobacteria]

c__[Spartobacteria]

c__Actinobacteria

c__Betaproteobacteria

c__Phycisphaerae

c__Oscillatoriophycideae

c__[Spartobacteria]

c__Betaproteobacteria

c__Phycisphaerae

c__Betaproteobacteria c__OPB56

c__Betaproteobacteria

c__Betaproteobacteria

0

c__Ellin6529

c__OPB56

c__Betaproteobacteria

c__Actinobacteria

0

c__Ellin6529

c__Actinobacteria c__Alphaproteobacteria c__[Saprospirae]

c__Alphaproteobacteria

c__[Spartobacteria]

c__[Saprospirae]

c__[Spartobacteria]

c__Planctomycetia c__Anaerolineae

c__Planctomycetia

c__Gammaproteobacteria

c__Anaerolineae

c__Gammaproteobacteria

c__[Spartobacteria] c__Oscillatoriophycideae

c__[Spartobacteria]

c__Actinobacteria

c__Deinococci

c__Oscillatoriophycideae

c__Alphaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Deinococci

c__Planctomycetia

c__Oscillatoriophycideae

c__Actinobacteria c__Actinobacteria c__Actinobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

c__Alphaproteobacteria c__Chloroplast

0

c__Actinobacteria

c__Planctomycetia

c__Oscillatoriophycideae

c__Actinobacteria c__Actinobacteria c__Actinobacteria

c__Alphaproteobacteria

0

c__Oscillatoriophycideae

c__Alphaproteobacteria c__Chloroplast

0

c__Alphaproteobacteria

0

c__Oscillatoriophycideae

c__Alphaproteobacteria

c__Alphaproteobacteria

c__Planctomycetia

c__Planctomycetia

c__Synechococcophycideae

c__[Pedosphaerae] c__Oscillatoriophycideae

c__Synechococcophycideae

c__[Pedosphaerae] c__Oscillatoriophycideae

c__Actinobacteria c__Alphaproteobacteria c__Actinobacteria c__Actinobacteria c__Sphingobacteriia c__[Saprospirae] c__Actinobacteria c__Alphaproteobacteria c__Verrucomicrobiae c__Betaproteobacteria

c__Actinobacteria c__Alphaproteobacteria c__Actinobacteria c__Actinobacteria c__Sphingobacteriia c__[Saprospirae] c__Actinobacteria c__Alphaproteobacteria c__Verrucomicrobiae

c__Planctomycetia

c__Actinobacteria

c__Betaproteobacteria

c__Sphingobacteriia

c__Planctomycetia

c__Actinobacteria

c__Sphingobacteriia c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria c__Planctomycetia

c__Gammaproteobacteria

Spring

module1 module2 module3 module4 module5 module6 module7 module8 module9 module10

c__Betaproteobacteria

c__Gammaproteobacteria c__Cytophagia

c__Sphingobacteriia c__Opitutae

c__Actinobacteria

c__Gemmatimonadetes

c__OM190

c__Betaproteobacteria c__Planctomycetia

c__Synechococcophycideae

c__Planctomycetia

c__Oscillatoriophycideae

c__Opitutae

c__Planctomycetia c__Acidimicrobiia

c__OM190

c__[Saprospirae]

c__Opitutae

c__Alphaproteobacteria c__[Saprospirae]

c__Betaproteobacteria

c__Planctomycetia

c__Acidimicrobiia c__Betaproteobacteria

c__[Pedosphaerae]

c__Synechococcophycideae

c__Betaproteobacteria

c__Planctomycetia

c__Actinobacteria

c__Actinobacteria

c__Planctomycetia

c__Alphaproteobacteria

c__Actinobacteria c__Planctomycetia

c__Gammaproteobacteria

c__[Saprospirae]

c__TK17

c__Alphaproteobacteria

c__Chloroplast

c__[Saprospirae]

c__TK17

c__Chloroplast

c__Alphaproteobacteria c__[Spartobacteria] c__Betaproteobacteria

0

c__Betaproteobacteria

c__[Spartobacteria] c__Alphaproteobacteria c__[Spartobacteria] c__Oscillatoriophycideae c__Alphaproteobacteria c__Actinobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__[Spartobacteria]

0 c__Betaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Alphaproteobacteria

c__iii1-8

c__[Spartobacteria] c__Betaproteobacteria

c__Alphaproteobacteria

c__Planctomycetia

c__Betaproteobacteria

c__Alphaproteobacteria

c__Flavobacteriia

c__Planctomycetia

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria c__Betaproteobacteria

c__Alphaproteobacteria

c__Planctomycetia

c__Oscillatoriophycideae

c__Betaproteobacteria c__Actinobacteria

c__Betaproteobacteria c__Flavobacteriia c__[Spartobacteria]

c__Actinobacteria

c__Betaproteobacteria

c__[Spartobacteria]

c__Planctomycetia

c__Actinobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

c__Alphaproteobacteria

c__Alphaproteobacteria

c__Actinobacteria c__Betaproteobacteria

c__Alphaproteobacteria c__[Spartobacteria] c__Oscillatoriophycideae c__Alphaproteobacteria c__Actinobacteria

c__Oscillatoriophycideae

c__iii1-8

c__Planctomycetia

c__Planctomycetia

c__Actinobacteria

c__Betaproteobacteria c__Betaproteobacteria c__Opitutae

c__Acidimicrobiia

c__Alphaproteobacteria c__Cytophagia

c__Opitutae

c__PBS-25

c__[Saprospirae] c__Betaproteobacteria

c__Betaproteobacteria c__Betaproteobacteria

0

c__[Saprospirae]

c__Acidimicrobiia

0

c__[Saprospirae]

c__PBS-25

c__[Saprospirae]

c__Oscillatoriophycideae

c__Alphaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Cytophagia

c__Actinobacteria

c__Oscillatoriophycideae

c__Actinobacteria

c__Actinobacteria c__Oscillatoriophycideae c__Acidimicrobiia

c__Actinobacteria

c__Oscillatoriophycideae

c__Actinobacteria

c__Acidimicrobiia c__Planctomycetia

c__[Spartobacteria]

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria c__Planctomycetia

c__[Spartobacteria]

c__Actinobacteria

8-Microcystis Betaproteobacteria Cerasicoccaceae

4-Pelagibacteraceae 6-Actinomycetales

c__Actinobacteria

c__Actinobacteria c__Planctomycetia

c__[Spartobacteria]

c__[Pedosphaerae]

c__Planctomycetia

c__Actinobacteria

c__Flavobacteriia

c__[Spartobacteria]

c__[Pedosphaerae]

c__Actinobacteria

c__Flavobacteriia c__Actinobacteria

c__Acidimicrobiia

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Planctomycetia

c__Actinobacteria

c__Betaproteobacteria

c__Betaproteobacteria

0

c__Acidimicrobiia

c__Oscillatoriophycideae

c__Acidimicrobiia

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Planctomycetia

c__Betaproteobacteria

c__Alphaproteobacteria

c__[Pedosphaerae]

c__Betaproteobacteria

c__Betaproteobacteria

c__[Chloracidobacteria]

c__Betaproteobacteria

c__Betaproteobacteria

c__Alphaproteobacteria

c__Actinobacteria

c__Planctomycetia

c__Actinobacteria

c__Opitutae

2-ACK-M1 Chitinophagaceae Sphingobacteriaceae

c__[Saprospirae]

c__Planctomycetia

c__Actinobacteria c__[Saprospirae] c__Opitutae

c__Actinobacteria

c__Betaproteobacteria

c__iii1-8

c__[Pedosphaerae]

c__Actinobacteria

c__[Methylacidiphilae]

c__Alphaproteobacteria c__Actinobacteria 0 c__Chloroplast c__Alphaproteobacteria c__Alphaproteobacteria c__Acidimicrobiia

0 c__Actinobacteria

c__[Saprospirae]

5-ACK-M1

c__Alphaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Alphaproteobacteria c__Actinobacteria 0 c__Chloroplast c__Alphaproteobacteria c__Alphaproteobacteria c__Acidimicrobiia

0

c__Oscillatoriophycideae

c__Actinobacteria

c__Actinobacteria

c__iii1-8

c__[Pedosphaerae]

c__Actinobacteria

c__Planctomycetia

c__Nitrospira

c__Alphaproteobacteria

c__Acidimicrobiia c__Opitutae

c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Alphaproteobacteria

c__Phycisphaerae

c__Actinobacteria c__Alphaproteobacteria c__Sphingobacteriia c__Planctomycetia c__Sphingobacteriia

c__Opitutae

c__[Saprospirae]

c__Actinobacteria

c__[Methylacidiphilae]

1-Pirellulaceae Bacteria

c__Verrucomicrobiae

c__Betaproteobacteria

c__PBS-25

c__Betaproteobacteria c__Betaproteobacteria

c__Gammaproteobacteria

c__Opitutae

c__Actinobacteria

c__Acidimicrobiia

c__Betaproteobacteria

c__[Saprospirae]

c__[Saprospirae]

c__Alphaproteobacteria

c__[Saprospirae]

c__Planctomycetia

c__Betaproteobacteria

c__Alphaproteobacteria c__Betaproteobacteria 0

c__Opitutae c__Actinobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Deltaproteobacteria c__Synechococcophycideae

c__Alphaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Opitutae

c__Actinobacteria

0

c__Planctomycetia c__Oscillatoriophycideae

c__Nitrospira

c__Alphaproteobacteria

c__Actinobacteria c__Alphaproteobacteria c__Sphingobacteriia c__Planctomycetia c__Sphingobacteriia c__Opitutae

c__Flavobacteriia

c__Betaproteobacteria c__[Spartobacteria]

c__Phycisphaerae

0

c__Planctomycetia c__Actinobacteria

c__Planctomycetia

c__Alphaproteobacteria c__Betaproteobacteria

c__Betaproteobacteria c__Betaproteobacteria

c__Gammaproteobacteria

c__Actinobacteria

c__Chloroplast

c__Actinobacteria c__[Methylacidiphilae]

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Alphaproteobacteria c__[Saprospirae]

c__[Saprospirae]

c__Alphaproteobacteria

c__Opitutae

c__Acidimicrobiia

c__[Spartobacteria]

0 c__Actinobacteria

c__Actinobacteria

c__Deltaproteobacteria c__Synechococcophycideae

c__Betaproteobacteria 0

c__Chloroplast

c__Actinobacteria

0

c__Betaproteobacteria

c__Acidobacteria-6 c__PBS-25

c__Flavobacteriia

c__Betaproteobacteria 0

c__Planctomycetia

c__Betaproteobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

0

c__Betaproteobacteria

0

c__Planctomycetia c__Actinobacteria

c__[Methylacidiphilae] c__[Spartobacteria]

c__Betaproteobacteria

c__[Chloracidobacteria]

c__Betaproteobacteria

c__Actinobacteria

c__Chloroplast

c__Actinobacteria

c__[Pedosphaerae]

c__Betaproteobacteria

c__Acidimicrobiia

c__Alphaproteobacteria

c__Opitutae

c__Acidimicrobiia

c__Planctomycetia

c__Betaproteobacteria

c__Actinobacteria c__Alphaproteobacteria

0

c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Verrucomicrobiae

c__Acidimicrobiia

c__Betaproteobacteria

c__[Spartobacteria]

0

c__Alphaproteobacteria

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Alphaproteobacteria

c__Chloroplast

c__Actinobacteria c__Actinobacteria

0

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Actinobacteria

c__Acidobacteria-6

c__Planctomycetia

c__Betaproteobacteria

0

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Planctomycetia

c__Alphaproteobacteria

c__Acidimicrobiia

c__Oscillatoriophycideae

c__[Saprospirae] 0

c__[Saprospirae]

0

c__[Spartobacteria]

c__Actinobacteria

c__[Saprospirae]

c__Actinobacteria

c__Betaproteobacteria

c__[Spartobacteria]

c__Actinobacteria

c__Actinobacteria

c__Anaerolineae

c__Betaproteobacteria

c__Actinobacteria

c__Anaerolineae

c__Actinobacteria c__[Spartobacteria]

c__Actinobacteria

c__[Spartobacteria]

c__Chloroplast

c__Actinobacteria c__[Saprospirae]

c__Actinobacteria

c__Sphingobacteriia

c__Chloroplast c__[Saprospirae]

c__Phycisphaerae

c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Opitutae

c__Sphingobacteriia

c__Opitutae

c__Actinobacteria

c__Phycisphaerae

c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__[Spartobacteria]

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria c__Betaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria c__Actinobacteria

c__Opitutae 0

0

c__Actinobacteria

c__[Methylacidiphilae]

c__[Methylacidiphilae] c__Planctomycetia

c__Alphaproteobacteria

c__Planctomycetia

c__Actinobacteria

c__Alphaproteobacteria

c__Actinobacteria

c__Actinobacteria c__Betaproteobacteria

c__Actinobacteria

0

c__Actinobacteria

c__Betaproteobacteria

c__[Saprospirae]

c__Betaproteobacteria

c__Betaproteobacteria

c__[Saprospirae]

c__Gemmatimonadetes

c__Nitrospira c__Actinobacteria

c__Gemmatimonadetes

c__[Spartobacteria]

c__Nitrospira

c__Actinobacteria

c__Actinobacteria c__Oscillatoriophycideae

c__Oscillatoriophycideae

0

c__[Spartobacteria]

c__Planctomycetia

c__[Spartobacteria]

c__Actinobacteria c__Oscillatoriophycideae

c__[Saprospirae]

c__Oscillatoriophycideae

c__Oscillatoriophycideae

3-Synechococcus Pirellulaceae

c__Opitutae

c__Actinobacteria

c__Actinobacteria

c__Flavobacteriia

c__Alphaproteobacteria

0

c__Actinobacteria

0

c__Actinobacteria

c__Flavobacteriia

c__[Saprospirae]

c__Alphaproteobacteria

c__Actinobacteria

0

c__Actinobacteria

c__[Spartobacteria]

c__Betaproteobacteria

c__[Saprospirae]

c__Phycisphaerae

c__[Spartobacteria]

c__Betaproteobacteria c__Synechococcophycideae

7-Deinococcaceae Deinococcus

c__Synechococcophycideae

c__Betaproteobacteria

c__Betaproteobacteria c__[Spartobacteria]

c__[Spartobacteria]

c__AT-s54

c__AT-s54

c__[Spartobacteria]

9-Chthoniobacteraceae Candidatus_Xiphinematobacter

c__[Spartobacteria]

c__Opitutae

c__Opitutae c__Betaproteobacteria

c__Planctomycetia

c__Betaproteobacteria

c__[Spartobacteria]

c__Planctomycetia

c__[Spartobacteria]

c__Betaproteobacteria

c__Betaproteobacteria c__Actinobacteria

c__Opitutae

c__Actinobacteria

c__Gammaproteobacteria

c__Opitutae

c__Gammaproteobacteria c__Betaproteobacteria

c__[Spartobacteria]

c__Betaproteobacteria

c__Acidobacteria-6

c__Planctomycetia

c__[Spartobacteria]

c__Actinobacteria

c__Acidobacteria-6

c__Sphingobacteriia

c__Planctomycetia

c__Sphingobacteriia

c__Verrucomicrobiae

c__Verrucomicrobiae c__Gammaproteobacteria

c__Verrucomicrobiae

c__Gammaproteobacteria

c__Cytophagia

c__Verrucomicrobiae

c__Cytophagia 0

c__Actinobacteria

c__[Saprospirae]

c__Actinobacteria

c__Planctomycetia

c__Gammaproteobacteria

0

0

c__Planctomycetia

c__Actinobacteria

c__[Saprospirae]

c__Actinobacteria

c__Planctomycetia

c__Gammaproteobacteria

c__Planctomycetia

c__Alphaproteobacteria

c__Alphaproteobacteria c__Deltaproteobacteria

c__Alphaproteobacteria

c__Deltaproteobacteria

c__Actinobacteria

c__Gammaproteobacteria

c__Acidimicrobiia

c__Betaproteobacteria

c__Synechococcophycideae c__Planctomycetia

c__Opitutae c__[Chloracidobacteria]

c__Betaproteobacteria

c__Planctomycetia

c__Gammaproteobacteria

c__Betaproteobacteria

c__Planctomycetia

c__Opitutae

c__[Spartobacteria]

c__Betaproteobacteria

c__Acidimicrobiia

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Acidimicrobiia

c__Oscillatoriophycideae

c__Synechococcophycideae

c__Planctomycetia

c__[Saprospirae]

c__Phycisphaerae

c__Betaproteobacteria

c__Opitutae

c__[Saprospirae]

c__[Chloracidobacteria]

c__Betaproteobacteria

c__Acidimicrobiia

c__Betaproteobacteria

c__Synechococcophycideae

c__Opitutae

c__[Saprospirae]

c__Actinobacteria

c__Alphaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__[Spartobacteria]

c__Betaproteobacteria

c__Acidimicrobiia

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Acidimicrobiia

c__Oscillatoriophycideae

c__Synechococcophycideae

c__Planctomycetia

10Rhizobiales

28 modules, 458 nodes, 1691 links (100% positive) c__OPB56 c__[Spartobacteria] c__[Spartobacteria] c__Gammaproteobacteria c__[Saprospirae] c__Actinobacteria c__[Saprospirae] c__Gammaproteobacteria c__Actinobacteria c__[Spartobacteria]

c__Planctomycetia

c__OPB56 c__[Spartobacteria] c__[Spartobacteria] c__Gammaproteobacteria c__[Saprospirae] c__Actinobacteria c__[Saprospirae] c__Gammaproteobacteria c__Actinobacteria c__[Spartobacteria]

c__Planctomycetia c__Phycisphaerae c__[Saprospirae] c__Phycisphaerae c__Betaproteobacteria c__Planctomycetia c__Actinobacteria

c__Planctomycetia

c__Planctomycetia

c__Planctomycetia

c__Planctomycetia

c__Phycisphaerae

c__Planctomycetia

c__Ellin6529

c__Flavobacteriia

c__Planctomycetia

c__Phycisphaerae

c__Planctomycetia

module1 6-Cerasicoccaceae module2 Betaproteobacteria module3 module4 module5 module6 module7 module8 module9 module10 5-ACK-M1 Actinomycetales Pelagibacteraceae

c__Phycisphaerae

c__Planctomycetia

c__Phycisphaerae

c__Phycisphaerae

c__Nitrospira 0

c__Nitrospira

c__Planctomycetia

c__Planctomycetia

c__Actinobacteria

c__Phycisphaerae

c__[Spartobacteria]

c__Phycisphaerae

c__[Spartobacteria]

c__Actinobacteria

0

c__[Spartobacteria]

0 c__Planctomycetia

c__[Spartobacteria]

c__Actinobacteria

c__[Spartobacteria]

c__Actinobacteria

c__[Spartobacteria]

c__Verrucomicrobiae

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__AT-s54

c__Actinobacteria

c__[Spartobacteria]

c__[Spartobacteria]

c__Verrucomicrobiae

c__Acidimicrobiia c__[Spartobacteria]

c__Actinobacteria

c__[Spartobacteria] c__AT-s54

c__Actinobacteria

c__Actinobacteria

0

c__Actinobacteria

c__[Spartobacteria]

0

c__Betaproteobacteria

c__[Pedosphaerae]

c__[Spartobacteria] c__Betaproteobacteria

c__Opitutae

c__Opitutae

c__[Pedosphaerae] c__Nitrospira

c__[Pedosphaerae]

c__Actinobacteria

c__Acidobacteria-6

c__Planctomycetia

c__Nitrospira c__Actinobacteria

c__Planctomycetia

c__Acidobacteria-6

0 c__Gemmatimonadetes

0 c__Gemmatimonadetes

c__Betaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

Acidobacteria

c__[Methylacidiphilae]

c__Actinobacteria

c__Planctomycetia

c__[Methylacidiphilae]

c__Betaproteobacteria

c__Acidimicrobiia

c__Planctomycetia c__Betaproteobacteria

c__Acidimicrobiia

c__[Saprospirae] c__Planctomycetia

0

c__Planctomycetia

0

c__Actinobacteria c__Phycisphaerae

c__PBS-25

c__Actinobacteria c__Phycisphaerae

c__PBS-25 c__[Saprospirae]

c__Betaproteobacteria

c__iii1-8

c__Betaproteobacteria

c__[Spartobacteria]

c__iii1-8

c__Planctomycetia

c__[Spartobacteria]

c__Planctomycetia

c__Planctomycetia

c__Cytophagia

c__Phycisphaerae

c__Planctomycetia

c__Gammaproteobacteria c__Betaproteobacteria

c__Gammaproteobacteria

c__Planctomycetia

c__Acidobacteria-6

c__Betaproteobacteria

c__Planctomycetia

c__Acidobacteria-6

c__Anaerolineae c__Gammaproteobacteria

c__Actinobacteria

c__iii1-8

c__Gammaproteobacteria

c__Actinobacteria

c__Alphaproteobacteria 0 c__Betaproteobacteria c__[Pedosphaerae] c__iii1-8 c__Alphaproteobacteria c__OM190 c__Planctomycetia c__Acidobacteria-6 c__Planctomycetia c__Flavobacteriia c__Planctomycetia

c__Alphaproteobacteria 0 c__Betaproteobacteria c__[Pedosphaerae] c__iii1-8 c__Alphaproteobacteria c__OM190 c__Planctomycetia c__Acidobacteria-6 c__Planctomycetia c__Flavobacteriia c__Planctomycetia

c__[Spartobacteria]

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria c__Anaerolineae c__iii1-8

c__Cytophagia

c__Phycisphaerae

c__Planctomycetia

c__Planctomycetia

Summer

c__Flavobacteriia

c__Planctomycetia

c__Betaproteobacteria 0

c__Betaproteobacteria

c__Planctomycetia

c__[Saprospirae]

c__Phycisphaerae

c__[Spartobacteria] 0

c__[Spartobacteria] 0

Unassign

c__Planctomycetia c__Phycisphaerae c__[Saprospirae] c__Phycisphaerae c__Betaproteobacteria c__Planctomycetia c__Actinobacteria

c__Planctomycetia

c__Planctomycetia

c__[Saprospirae] c__[Methylacidiphilae]

c__Ellin6529 c__[Methylacidiphilae]

0 0 c__Planctomycetia c__Planctomycetia

c__Acidimicrobiia

c__[Pedosphaerae]

c__OPB56

c__[Spartobacteria]

c__Actinobacteria

c__OPB56

c__Actinobacteria

c__Actinobacteria

c__Gemmatimonadetes

c__Gemmatimonadetes c__Actinobacteria

c__Actinobacteria

c__Cytophagia

c__Cytophagia c__OPB56

c__OPB56

c__Actinobacteria

c__Actinobacteria c__SC3

c__SC3

c__Planctomycetia

c__Planctomycetia

c__Actinobacteria

Actinobacteria

c__Planctomycetia c__Synechococcophycideae c__Synechococcophycideae

c__Actinobacteria

c__Planctomycetia

c__Actinobacteria

c__Synechococcophycideae c__Synechococcophycideae c__Actinobacteria

c__Actinobacteria

c__Deltaproteobacteria

c__Gemmatimonadetes

c__Gammaproteobacteria

c__Synechococcophycideae

c__Actinobacteria

c__[Pedosphaerae]

c__Actinobacteria

c__Deltaproteobacteria

c__Gemmatimonadetes

c__Synechococcophycideae

c__Actinobacteria

c__OM190

c__Actinobacteria

c__Actinobacteria

c__OM190

c__Synechococcophycideae

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Synechococcophycideae

c__Planctomycetia

c__Actinobacteria c__Alphaproteobacteria c__Actinobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria

c__Actinobacteria

c__Gammaproteobacteria

c__Synechococcophycideae

c__[Spartobacteria]

c__[Pedosphaerae]

c__Actinobacteria

c__Planctomycetia

c__Actinobacteria c__Alphaproteobacteria c__Actinobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria

c__Actinobacteria

c__Actinobacteria c__Actinobacteria

c__Synechococcophycideae

c__Actinobacteria

c__Flavobacteriia

c__Gammaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Betaproteobacteria c__Actinobacteria c__Gammaproteobacteria c__Betaproteobacteria

c__Synechococcophycideae

c__[Spartobacteria]

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria c__Actinobacteria

c__Synechococcophycideae

c__Actinobacteria

c__Flavobacteriia

c__Gammaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Betaproteobacteria c__Actinobacteria c__Gammaproteobacteria c__Betaproteobacteria

c__OM190

c__OM190

c__Synechococcophycideae

c__Actinobacteria

c__Synechococcophycideae c__Actinobacteria

c__Actinobacteria

c__Ellin6529 c__Synechococcophycideae

c__Actinobacteria

c__Ellin6529

c__Actinobacteria

c__Synechococcophycideae c__Actinobacteria

c__Synechococcophycideae

c__[Methylacidiphilae]

c__Synechococcophycideae

c__[Methylacidiphilae]

c__Actinobacteria

c__Actinobacteria c__Synechococcophycideae

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Synechococcophycideae c__Actinobacteria

c__Synechococcophycideae

c__Actinobacteria

c__Synechococcophycideae

c__Actinobacteria

c__Actinobacteria

c__[Saprospirae]

c__Synechococcophycideae

c__Actinobacteria

c__[Saprospirae]

c__Actinobacteria c__[Saprospirae]

c__Synechococcophycideae

c__Actinobacteria

c__Actinobacteria

c__[Saprospirae] c__Actinobacteria

c__Acidimicrobiia

c__Gammaproteobacteria

c__Thermoleophilia

c__Planctomycetia

c__Acidimicrobiia

c__Gammaproteobacteria

c__Thermoleophilia

c__Planctomycetia

c__Synechococcophycideae c__Planctomycetia c__OM190

c__Actinobacteria c__Gemmatimonadetes

c__Synechococcophycideae c__Planctomycetia c__OM190

c__Actinobacteria

c__Betaproteobacteria

c__Acidimicrobiia

c__Gemmatimonadetes c__Betaproteobacteria

c__Acidimicrobiia

c__Actinobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__[Pedosphaerae]

c__Alphaproteobacteria

c__Alphaproteobacteria

c__Flavobacteriia c__Oscillatoriophycideae c__Oscillatoriophycideae c__[Spartobacteria] c__Oscillatoriophycideae c__[Spartobacteria] c__Oscillatoriophycideae c__Alphaproteobacteria c__Oscillatoriophycideae c__Alphaproteobacteria

c__Oscillatoriophycideae

c__Flavobacteriia c__Oscillatoriophycideae c__Oscillatoriophycideae c__[Spartobacteria] c__Oscillatoriophycideae c__[Spartobacteria] c__Oscillatoriophycideae c__Alphaproteobacteria c__Oscillatoriophycideae c__Alphaproteobacteria

c__[Pedosphaerae]

c__Oscillatoriophycideae c__Alphaproteobacteria

c__[Spartobacteria]

c__Oscillatoriophycideae

c__Actinobacteria

c__Oscillatoriophycideae c__[Spartobacteria]

c__[Spartobacteria]

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Actinobacteria

Bacteroidetes

c__Betaproteobacteria

c__Actinobacteria

c__[Pedosphaerae]

c__Alphaproteobacteria

c__Flavobacteriia

c__Betaproteobacteria

c__Alphaproteobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Flavobacteriia

c__[Pedosphaerae]

c__Actinobacteria

c__Oscillatoriophycideae

c__Planctomycetia

c__Actinobacteria

c__Oscillatoriophycideae

c__[Spartobacteria] c__Oscillatoriophycideae

c__Oscillatoriophycideae c__Actinobacteria

c__Synechococcophycideae

c__Planctomycetia

c__Actinobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Oscillatoriophycideae c__Synechococcophycideae

c__Actinobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Acidimicrobiia

c__Oscillatoriophycideae

c__Oscillatoriophycideae c__Actinobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Acidimicrobiia

c__Actinobacteria

0 c__Acidimicrobiia

c__Actinobacteria

c__Oscillatoriophycideae c__Planctomycetia c__Planctomycetia

c__Betaproteobacteria c__Opitutae

c__Planctomycetia c__Betaproteobacteria c__Opitutae

c__Planctomycetia c__Betaproteobacteria

c__Betaproteobacteria

c__Opitutae

c__Planctomycetia

c__Planctomycetia

c__Betaproteobacteria

c__Betaproteobacteria c__Betaproteobacteria

c__Opitutae

c__Oscillatoriophycideae

c__Planctomycetia c__Betaproteobacteria

c__Betaproteobacteria

c__Gemmatimonadetes

c__Opitutae

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Planctomycetia 0

c__Alphaproteobacteria

0

c__Alphaproteobacteria c__Opitutae c__Actinobacteria c__Verrucomicrobiae 0 c__Alphaproteobacteria c__Betaproteobacteria

c__Oscillatoriophycideae c__Planctomycetia 0

0

c__Alphaproteobacteria c__Opitutae c__Actinobacteria c__Verrucomicrobiae 0 c__Alphaproteobacteria c__Betaproteobacteria c__Betaproteobacteria

c__Betaproteobacteria

c__Planctomycetia c__Oscillatoriophycideae

c__Opitutae

c__Planctomycetia 0

c__Planctomycetia

0

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Gammaproteobacteria

c__Alphaproteobacteria 0

c__Actinobacteria

c__Actinobacteria

c__Planctomycetia c__Betaproteobacteria

c__Opitutae

c__Oscillatoriophycideae

c__Gammaproteobacteria

c__Gammaproteobacteria

c__Actinobacteria

c__Gammaproteobacteria

c__Planctomycetia

c__Alphaproteobacteria 0

c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__Betaproteobacteria c__Chloroplast

c__Opitutae c__Gammaproteobacteria c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria c__Planctomycetia c__Planctomycetia c__[Spartobacteria] c__Planctomycetia c__[Spartobacteria] c__Planctomycetia c__Planctomycetia c__Planctomycetia

c__Acidimicrobiia

c__[Spartobacteria]

c__Betaproteobacteria c__Planctomycetia c__Planctomycetia c__[Spartobacteria] c__Planctomycetia c__[Spartobacteria] c__Planctomycetia c__Planctomycetia c__Planctomycetia

c__[Pedosphaerae]

c__[Spartobacteria]

c__[Spartobacteria]

c__[Pedosphaerae]

c__Betaproteobacteria

c__Alphaproteobacteria

c__Acidimicrobiia

c__[Spartobacteria]

c__Alphaproteobacteria c__Opitutae

c__Planctomycetia c__Alphaproteobacteria

c__Chloroplast

c__Betaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Gammaproteobacteria

c__Betaproteobacteria

c__Alphaproteobacteria c__Opitutae

Chloroflexi

c__Betaproteobacteria

c__Betaproteobacteria c__Opitutae

c__Alphaproteobacteria

0

c__Betaproteobacteria c__Alphaproteobacteria

c__Opitutae

c__Actinobacteria

0

c__Alphaproteobacteria

c__Planctomycetia

c__Actinobacteria

c__Alphaproteobacteria

c__Planctomycetia

c__Alphaproteobacteria c__Actinobacteria

c__Opitutae

c__Alphaproteobacteria

c__Planctomycetia

c__Actinobacteria

c__Actinobacteria c__Actinobacteria

c__Cytophagia

c__[Spartobacteria]

c__Synechococcophycideae

c__Planctomycetia

c__Synechococcophycideae

c__Betaproteobacteria c__Actinobacteria

c__Planctomycetia

c__Opitutae

c__Synechococcophycideae

c__Betaproteobacteria

c__Betaproteobacteria c__[Saprospirae]

c__Actinobacteria c__Opitutae

c__Alphaproteobacteria

c__Synechococcophycideae

c__Betaproteobacteria c__Alphaproteobacteria

c__[Saprospirae]

c__Alphaproteobacteria

c__Alphaproteobacteria c__Planctomycetia

c__Cytophagia

c__Alphaproteobacteria

c__Opitutae

c__[Spartobacteria] c__Planctomycetia

c__Planctomycetia

c__Betaproteobacteria

c__Chloroplast

c__Verrucomicrobiae

c__Betaproteobacteria

c__Opitutae c__Alphaproteobacteria

c__Gammaproteobacteria

c__Opitutae

c__Alphaproteobacteria

c__Alphaproteobacteria

c__Alphaproteobacteria c__Chloroplast

c__Actinobacteria c__Betaproteobacteria c__Opitutae c__Alphaproteobacteria c__Betaproteobacteria c__[Saprospirae] c__Alphaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Gammaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Verrucomicrobiae

c__Chloroplast

c__Alphaproteobacteria

c__Acidobacteria-6

c__Alphaproteobacteria c__Chloroplast

c__Actinobacteria c__Betaproteobacteria c__Opitutae c__Alphaproteobacteria c__Betaproteobacteria c__[Saprospirae] c__Alphaproteobacteria

c__Acidobacteria-6

c__Acidobacteria-6

c__Planctomycetia

c__[Spartobacteria]

c__Acidobacteria-6

c__Planctomycetia

c__[Spartobacteria]

Cyanobacteria

c__Acidimicrobiia c__[Saprospirae]

c__Betaproteobacteria

c__Acidimicrobiia c__[Saprospirae]

c__Betaproteobacteria c__Acidimicrobiia

c__Acidimicrobiia

c__[Saprospirae]

c__Alphaproteobacteria

c__[Saprospirae]

c__Acidimicrobiia

c__[Saprospirae]

c__Alphaproteobacteria

c__[Saprospirae]

3-Microcystaceae Microcystis Pirellulaceae Chthoniobacteraceae Candidatus_Xiphinematobacter

7-Synechococcaceae Synechococcus Stramenopiles ACK-M1

c__[Saprospirae] c__OPB56

c__Acidimicrobiia

2-ACK-M1 Pirellulaceae Phycisphaerales

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Opitutae

0 0

c__Planctomycetia

4- Synechococcaceae Synechococcus Synechococcaceae CL500-15

c__Alphaproteobacteria

c__Gemmatimonadetes

c__Opitutae

c__Planctomycetia

1-Gemmataceae Chitinophagaceae Chthoniobacteraceae Candidatus_Xiphinematobacter

c__Oscillatoriophycideae

c__Oscillatoriophycideae c__Betaproteobacteria

Chlorobi

c__Oscillatoriophycideae c__Oscillatoriophycideae

c__Actinobacteria

c__Alphaproteobacteria c__Betaproteobacteria c__Actinobacteria c__[Spartobacteria] c__Alphaproteobacteria c__[Chloracidobacteria] c__Alphaproteobacteria c__Alphaproteobacteria c__[Saprospirae]

c__Planctomycetia

c__Alphaproteobacteria c__Betaproteobacteria c__Actinobacteria c__[Spartobacteria] c__Alphaproteobacteria c__[Chloracidobacteria] c__Alphaproteobacteria c__Alphaproteobacteria c__[Saprospirae]

c__Oscillatoriophycideae

c__Planctomycetia

c__Actinobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Actinobacteria

0

c__Alphaproteobacteria

c__Oscillatoriophycideae

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__Planctomycetia c__Planctomycetia

0

c__Alphaproteobacteria

c__Actinobacteria

c__[Saprospirae]

c__Oscillatoriophycideae c__Planctomycetia

c__Actinobacteria

c__Alphaproteobacteria

c__Acidimicrobiia

c__Actinobacteria

c__Oscillatoriophycideae

c__Actinobacteria

c__[Saprospirae]

c__Oscillatoriophycideae c__Oscillatoriophycideae

c__Alphaproteobacteria

c__Oscillatoriophycideae c__Oscillatoriophycideae

c__Alphaproteobacteria

0

c__Oscillatoriophycideae c__Oscillatoriophycideae

c__Actinobacteria

8-Comamonadaceae Sphingomonadaceae Opitutaceae

c__Betaproteobacteria

c__[Saprospirae] c__OPB56

c__Betaproteobacteria

c__[Saprospirae]

c__Flavobacteriia

c__Acidimicrobiia

c__[Saprospirae]

c__Flavobacteriia

c__Acidimicrobiia

c__Alphaproteobacteria

c__Alphaproteobacteria

0

c__Betaproteobacteria

c__Betaproteobacteria

c__Opitutae

0

c__[Saprospirae]

c__Planctomycetia

c__Sphingobacteriia

c__Sphingobacteriia

c__[Spartobacteria]

0

c__Betaproteobacteria

c__Betaproteobacteria

c__Opitutae

0

c__[Saprospirae]

c__Planctomycetia

c__Sphingobacteriia

c__Sphingobacteriia

c__[Spartobacteria]

c__[Spartobacteria]

c__[Spartobacteria]

Gemmatimonadetes

20 modules, 414 nodes, 2447 links (100% positive)

NC10

module1 module2 module3 module4 module5

Nitrospirae c__Actinobacteria c__Planctomycetia c__Actinobacteria c__Planctomycetia c__Planctomycetia

c__Actinobacteria c__Planctomycetia c__Actinobacteria c__Planctomycetia

c__Flavobacteriia c__Flavobacteriia

c__Planctomycetia

c__Planctomycetia

c__Flavobacteriia c__Flavobacteriia

c__Sphingobacteriia c__Planctomycetia

c__Planctomycetia

c__Sphingobacteriia c__Actinobacteria

c__Planctomycetia

c__[Spartobacteria] c__Actinobacteria c__Sphingobacteriia

c__[Spartobacteria]

c__Actinobacteria

OP3

c__Sphingobacteriia c__Chloroplast

c__Actinobacteria

c__[Spartobacteria] c__Chloroplast c__Betaproteobacteria

c__[Spartobacteria]

c__[Pedosphaerae] c__Betaproteobacteria c__Sphingobacteriia

c__[Pedosphaerae]

c__[Chloracidobacteria]

c__Sphingobacteriia

c__Planctomycetia c__[Chloracidobacteria]

c__Planctomycetia c__Planctomycetia

c__Planctomycetia

c__Planctomycetia c__Holophagae c__Sphingobacteriia c__Planctomycetia

c__Planctomycetia

Autumn

c__Planctomycetia

10-Sphingobacteriales Oxalobacteraceae Polynucleobacter Chitinophagaceae

9-Pirellulaceae Saprospiraceae

c__Planctomycetia c__Holophagae c__Sphingobacteriia c__Planctomycetia

5-Ellin6067 Acetobacteraceae

Planctomycetes c__[Leptospirae] c__Synechococcophycideae c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Betaproteobacteria c__Actinobacteria c__Betaproteobacteria c__Actinobacteria c__Actinobacteria c__Betaproteobacteria c__Betaproteobacteria c__Betaproteobacteria

c__Oscillatoriophycideae c__Oscillatoriophycideae c__Acidimicrobiia c__Betaproteobacteria 0 c__Betaproteobacteria c__Betaproteobacteria c__[Pedosphaerae] c__Oscillatoriophycideae c__[Saprospirae] c__Opitutae

c__Betaproteobacteria

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Acidimicrobiia

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Holophagae

c__Actinobacteria

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Actinobacteria

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

0

c__Acidimicrobiia

c__Holophagae

c__Acidimicrobiia

0

c__Betaproteobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Actinobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Actinobacteria c__Alphaproteobacteria c__Sphingobacteriia c__Actinobacteria c__Actinobacteria c__Alphaproteobacteria c__Actinobacteria c__Actinobacteria c__Betaproteobacteria c__Actinobacteria

c__Oscillatoriophycideae c__Oscillatoriophycideae c__Oscillatoriophycideae c__Cytophagia c__Alphaproteobacteria c__Oscillatoriophycideae c__Oscillatoriophycideae c__Oscillatoriophycideae c__Oscillatoriophycideae c__Oscillatoriophycideae

c__Actinobacteria c__Alphaproteobacteria c__Alphaproteobacteria c__Actinobacteria c__Alphaproteobacteria c__Sphingobacteriia c__Actinobacteria c__Actinobacteria c__Alphaproteobacteria c__Actinobacteria c__Actinobacteria c__Betaproteobacteria c__Actinobacteria

Spirochaetes

c__Alphaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Actinobacteria

c__Oscillatoriophycideae c__Oscillatoriophycideae c__Cytophagia c__Oscillatoriophycideae c__Oscillatoriophycideae c__Alphaproteobacteria c__Oscillatoriophycideae c__Oscillatoriophycideae c__Oscillatoriophycideae c__Oscillatoriophycideae

c__Betaproteobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Alphaproteobacteria

c__Actinobacteria c__Actinobacteria

c__Actinobacteria

c__Actinobacteria c__Alphaproteobacteria c__Oscillatoriophycideae

c__Oscillatoriophycideae

2-ACK-M1 Actinomycetales Betaproteobacteria

ACK-M1

c__Holophagae

c__Actinobacteria

c__Oscillatoriophycideae

c__OPB56 c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__OPB56 c__Oscillatoriophycideae

3-Chthoniobacteraceae Candidatus_Xiphinematobacter Synechococcus Saprospiraceae

c__Gemmatimonadetes

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Alphaproteobacteria

c__Actinobacteria

c__[Spartobacteria]

c__Oscillatoriophycideae

c__Holophagae c__Alphaproteobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Gemmatimonadetes

c__Actinobacteria

c__Alphaproteobacteria

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Actinobacteria c__Betaproteobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

0

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Betaproteobacteria

c__Acidimicrobiia

c__Betaproteobacteria

0

c__[Spartobacteria]

c__Oscillatoriophycideae

c__Acidimicrobiia

0 c__Alphaproteobacteria

c__Oscillatoriophycideae

Proteobacteria

c__Actinobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Actinobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__Oscillatoriophycideae

c__Actinobacteria

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Oscillatoriophycideae

c__Betaproteobacteria

c__[Saprospirae]

c__Oscillatoriophycideae c__Oscillatoriophycideae

c__Acidimicrobiia

0

c__Acidimicrobiia

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria c__[Saprospirae] c__Alphaproteobacteria

c__Actinobacteria

c__Actinobacteria c__Actinobacteria c__Actinobacteria c__SC3

c__Actinobacteria c__Actinobacteria

c__SC3

c__Actinobacteria c__Oscillatoriophycideae

c__Actinobacteria

c__Betaproteobacteria

0 c__Opitutae c__Synechococcophycideae

c__Oscillatoriophycideae c__Actinobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Opitutae

c__Opitutae c__Betaproteobacteria

c__Actinobacteria c__Actinobacteria

c__Synechococcophycideae

c__Oscillatoriophycideae

c__[Leptospirae] c__Synechococcophycideae c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Betaproteobacteria c__Actinobacteria c__Betaproteobacteria c__Actinobacteria c__Actinobacteria c__Betaproteobacteria c__Betaproteobacteria c__Betaproteobacteria c__Betaproteobacteria c__Betaproteobacteria

c__Alphaproteobacteria

c__Opitutae

c__Acidimicrobiia

c__Betaproteobacteria

0 c__Opitutae

c__Opitutae c__Oscillatoriophycideae

c__Opitutae

c__Actinobacteria

c__Betaproteobacteria

c__Opitutae

c__Opitutae

c__Actinobacteria

c__Betaproteobacteria

c__Alphaproteobacteria

c__Opitutae c__Opitutae c__Opitutae

c__Oscillatoriophycideae c__Oscillatoriophycideae c__Acidimicrobiia 0 c__Betaproteobacteria c__Betaproteobacteria c__Betaproteobacteria c__[Pedosphaerae] c__Oscillatoriophycideae c__[Saprospirae] c__Opitutae

c__[Spartobacteria] c__[Spartobacteria] c__[Spartobacteria] c__Planctomycetia

c__[Spartobacteria] c__[Spartobacteria] c__[Spartobacteria]

c__[Spartobacteria]

c__Planctomycetia

TM7

c__[Spartobacteria] c__[Spartobacteria] c__SC3

c__[Spartobacteria] c__[Spartobacteria]

c__SC3

c__[Saprospirae]

4-Pirellulaceae Sphingobacteriales

c__[Spartobacteria] c__[Spartobacteria]

c__[Saprospirae]

c__[Spartobacteria]

c__[Spartobacteria] c__[Spartobacteria]

c__[Spartobacteria]

c__[Spartobacteria] c__[Spartobacteria] c__Actinobacteria

c__[Spartobacteria]

c__[Saprospirae] c__Actinobacteria c__Actinobacteria c__[Saprospirae]

c__Betaproteobacteria c__Actinobacteria c__Synechococcophycideae c__Synechococcophycideae

c__Actinobacteria c__Betaproteobacteria c__Actinobacteria c__Synechococcophycideae c__Synechococcophycideae

c__Betaproteobacteria

c__Betaproteobacteria

Thermi

5 modules, 180 nodes, 1841 links (92.56% positive)

c__Actinobacteria c__Actinobacteria c__Acidimicrobiia c__Actinobacteria

c__Alphaproteobacteria c__Betaproteobacteria

c__Alphaproteobacteria

c__Acidimicrobiia

c__Alphaproteobacteria

c__Betaproteobacteria

c__Acidimicrobiia

c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Alphaproteobacteria

c__Planctomycetia

c__Alphaproteobacteria

c__Actinobacteria

c__Synechococcophycideae c__[Spartobacteria]

c__Acidimicrobiia

c__Betaproteobacteria

c__Synechococcophycideae c__Actinobacteria

c__[Spartobacteria]

0 c__[Chloracidobacteria] c__Deltaproteobacteria c__Deltaproteobacteria

c__[Spartobacteria]

c__[Spartobacteria]

c__[Spartobacteria]

c__[Spartobacteria]

c__Opitutae c__[Methylacidiphilae]

c__[Spartobacteria]

c__Betaproteobacteria

c__Planctomycetia c__Sphingobacteriia

c__[Pedosphaerae] c__Planctomycetia

c__[Saprospirae]

c__[Spartobacteria]

c__OM190

c__[Pedosphaerae]

c__[Spartobacteria]

c__Sphingobacteriia

c__Opitutae

c__Actinobacteria

c__Gammaproteobacteria c__OM190

c__Opitutae

c__Actinobacteria

c__[Saprospirae]

c__Actinobacteria

c__[Spartobacteria]

c__Nitrospira c__[Spartobacteria] c__Nitrospira 0c__Planctomycetia c__Actinobacteria

c__[Spartobacteria]

c__Nitrospira c__[Spartobacteria] c__Nitrospira 0c__Planctomycetia

c__Sphingobacteriia

c__Gammaproteobacteria

c__Actinobacteria c__Planctomycetia c__Sphingobacteriia

c__Sphingobacteriia

c__Opitutae

c__[Pedosphaerae] c__Actinobacteria

c__Sphingobacteriia

c__Opitutae

c__Opitutae

c__[Pedosphaerae]

c__Planctomycetia c__Actinobacteria c__Opitutae

c__Actinobacteria

c__Opitutae

c__Opitutae

c__Actinobacteria

c__Actinobacteria

c__Opitutae

c__Opitutae c__Planctomycetia

c__Opitutae

c__Opitutae

c__Planctomycetia

c__Actinobacteria c__Planctomycetia c__Opitutae

c__Opitutae

c__Planctomycetia c__Gammaproteobacteria c__Planctomycetia

c__Opitutae

c__Sphingobacteriia c__Opitutae

c__Planctomycetia c__Planctomycetia

c__Opitutae

c__Planctomycetia c__Gammaproteobacteria c__Planctomycetia

c__Sphingobacteriia

c__Actinobacteria c__Alphaproteobacteria

c__Opitutae

c__[Saprospirae]

c__Actinobacteria

c__[Saprospirae]

c__[Saprospirae]

c__Actinobacteria c__Alphaproteobacteria c__[Saprospirae]

c__Actinobacteria

c__[Saprospirae]

c__Actinobacteria

c__[Saprospirae]

c__Opitutae

c__Betaproteobacteria c__[Saprospirae]

c__[Saprospirae]

c__Actinobacteria

c__[Saprospirae]

c__Opitutae

c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__[Saprospirae]

c__Betaproteobacteria

c__[Saprospirae]

c__Opitutae

c__[Saprospirae]

c__[Saprospirae]

c__Actinobacteria c__[Saprospirae]

c__Betaproteobacteria

c__[Saprospirae]

c__Actinobacteria c__Actinobacteria c__[Saprospirae]

c__Betaproteobacteria

c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Planctomycetia

c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__[Saprospirae]

0

c__Alphaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Actinobacteria c__Alphaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Betaproteobacteria

0

0

0

c__Betaproteobacteria

c__Actinobacteria

c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Actinobacteria c__Planctomycetia c__Actinobacteria c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Oscillatoriophycideae

c__Actinobacteria

c__Actinobacteria c__[Saprospirae]

c__Betaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__[Saprospirae]

0

c__Chloroplast

c__Betaproteobacteria

c__Betaproteobacteria

0

0

c__Actinobacteria

c__Actinobacteria

c__iii1-8

c__Actinobacteria

c__Chloroplast

c__Oscillatoriophycideae

0

c__Chloroplast

0

c__Betaproteobacteria 0

c__iii1-8

c__Alphaproteobacteria c__Oscillatoriophycideae

0

c__Betaproteobacteria

c__Oscillatoriophycideae

c__Chloroplast

c__Alphaproteobacteria

c__Alphaproteobacteria 0

c__Actinobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

c__[Spartobacteria]

c__Chloroplast

c__Betaproteobacteria

c__[Spartobacteria]

c__Betaproteobacteria

c__Betaproteobacteria c__Betaproteobacteria

c__Alphaproteobacteria c__Betaproteobacteria

c__Chloroplast c__Actinobacteria

c__Betaproteobacteria c__Betaproteobacteria

c__Alphaproteobacteria c__Betaproteobacteria

c__Actinobacteria

c__Alphaproteobacteria

0

c__Alphaproteobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Chloroplast

c__Betaproteobacteria c__Actinobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__Actinobacteria

c__Acidimicrobiia

c__[Spartobacteria]

c__Betaproteobacteria c__Actinobacteria

0

c__Alphaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Acidimicrobiia

c__Actinobacteria

c__Alphaproteobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Alphaproteobacteria

c__[Spartobacteria] c__Betaproteobacteria

c__Betaproteobacteria

c__Alphaproteobacteria c__Planctomycetia c__Betaproteobacteria c__Betaproteobacteria c__Alphaproteobacteria c__Actinobacteria c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Alphaproteobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__[Spartobacteria]

c__Alphaproteobacteria

c__[Saprospirae]

c__Actinobacteria c__[Saprospirae] c__[Saprospirae]

c__[Saprospirae]

c__Actinobacteria c__[Saprospirae] c__[Saprospirae]

c__Betaproteobacteria c__Actinobacteria

5-ACK-M1 Betaproteobacteria Chitinophagaceae Sediminibacterium

c__Oscillatoriophycideae

c__Alphaproteobacteria

c__Betaproteobacteria

c__Chloroplast

c__Oscillatoriophycideae c__Actinobacteria

c__Actinobacteria

c__Oscillatoriophycideae

0

c__Actinobacteria

c__Actinobacteria c__Alphaproteobacteria

c__Actinobacteria c__Alphaproteobacteria c__Actinobacteria c__Actinobacteria

c__Betaproteobacteria

c__Alphaproteobacteria

c__Planctomycetia

c__Chloroplast

0

8-Comamonadaceae

c__Planctomycetia

c__Chloroplast c__Oscillatoriophycideae

c__[Saprospirae]

c__Chloroplast

1-Stramenopiles Chthoniobacteraceae Candidatus_Xiphinematobacter Saprospiraceae

c__Opitutae

c__[Saprospirae] c__Actinobacteria

c__Betaproteobacteria

3-ACK-M1 Pelagibacteraceae Actinomycetales

c__Acidimicrobiia

c__Betaproteobacteria c__[Saprospirae]

c__Acidimicrobiia

c__Chloroplast

2-ACK-M1 Synechococcaceae

c__Planctomycetia

c__Alphaproteobacteria

c__[Spartobacteria]

c__[Spartobacteria] c__Alphaproteobacteria

Winter

Pirellulaceae

c__[Spartobacteria]

c__[Spartobacteria]

c__Acidobacteria-6

c__Actinobacteria c__[Methylacidiphilae]

c__Planctomycetia

0

c__Alphaproteobacteria

c__Planctomycetia c__Synechococcophycideae c__Actinobacteria

c__Alphaproteobacteria

c__[Spartobacteria]

c__Acidobacteria-6

c__Planctomycetia

c__Planctomycetia

c__Betaproteobacteria

c__Betaproteobacteria

c__Actinobacteria c__Betaproteobacteria

c__[Spartobacteria]

c__Opitutae

c__[Saprospirae]

c__Actinobacteria

c__Acidimicrobiia c__Actinobacteria

c__[Spartobacteria] c__Actinobacteria

c__Acidimicrobiia

c__Actinobacteria

c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Betaproteobacteria

c__[Spartobacteria]

c__Betaproteobacteria

c__[Pedosphaerae]

c__[Saprospirae] c__Actinobacteria

c__[Pedosphaerae]

c__[Saprospirae]

c__Actinobacteria

c__Betaproteobacteria

c__Synechococcophycideae c__[Spartobacteria]

c__Actinobacteria

c__Betaproteobacteria

c__[Saprospirae]

c__Actinobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

c__Actinobacteria

c__Alphaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__[Chloracidobacteria] c__Deltaproteobacteria

c__Actinobacteria c__Synechococcophycideae

c__[Spartobacteria]

c__Betaproteobacteria c__Actinobacteria

c__[Spartobacteria]

c__Betaproteobacteria c__Alphaproteobacteria

c__Deltaproteobacteria

c__[Saprospirae]

c__Alphaproteobacteria

c__Acidimicrobiia c__[Saprospirae]

c__Alphaproteobacteria c__Synechococcophycideae

c__Betaproteobacteria

7-Pirellulaceae Rhodobacteraceae Rhodobacter

c__Actinobacteria

c__Betaproteobacteria

c__[Methylacidiphilae] c__Planctomycetia

c__Actinobacteria

c__Betaproteobacteria

c__[Methylacidiphilae]

c__Betaproteobacteria 0 c__Alphaproteobacteria c__Betaproteobacteria

0 c__Betaproteobacteria

c__Actinobacteria c__Acidimicrobiia c__Betaproteobacteria 0 c__Alphaproteobacteria c__Betaproteobacteria

0 c__Betaproteobacteria c__Alphaproteobacteria

c__Actinobacteria

c__Acidimicrobiia

c__Actinobacteria c__Actinobacteria

c__Betaproteobacteria

c__Actinobacteria c__Actinobacteria

c__Actinobacteria c__Actinobacteria c__Acidimicrobiia c__Actinobacteria

c__Alphaproteobacteria c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

1-Microcystaceae Microcystis Cerasicoccaceae Burkholderiales

Verrucomicrobia

c__Alphaproteobacteria

c__Alphaproteobacteria

c__Betaproteobacteria 0

c__[Spartobacteria] c__Acidimicrobiia

c__Betaproteobacteria

c__Betaproteobacteria

c__Alphaproteobacteria c__Planctomycetia c__Betaproteobacteria c__Betaproteobacteria c__Alphaproteobacteria c__Actinobacteria c__Betaproteobacteria

c__[Spartobacteria]

c__Betaproteobacteria 0 c__Acidimicrobiia

4-Sphingobacteriales Cerasicoccaceae

6-Chitinophagaceae

c__[Spartobacteria] c__[Pedosphaerae]

c__[Pedosphaerae]

c__Gammaproteobacteria c__[Spartobacteria]

c__Planctomycetia

c__Betaproteobacteria

c__Gammaproteobacteria c__[Spartobacteria]

c__Gammaproteobacteria

c__Gammaproteobacteria

c__Planctomycetia

c__[Spartobacteria]

c__Betaproteobacteria

c__Planctomycetia

c__Gammaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Opitutae

c__Gammaproteobacteria

c__Opitutae

c__[Spartobacteria]

c__[Spartobacteria]

c__Planctomycetia

c__Planctomycetia

c__Betaproteobacteria

c__Betaproteobacteria

c__Betaproteobacteria

c__Opitutae

c__Opitutae

c__Betaproteobacteria

c__Gammaproteobacteria

c__[Spartobacteria]

c__Planctomycetia

c__Betaproteobacteria

c__Gammaproteobacteria

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

c__Actinobacteria

0

c__Betaproteobacteria

c__Betaproteobacteria

c__Verrucomicrobiae

c__Verrucomicrobiae

c__Actinobacteria

c__Actinobacteria

c__Gemmatimonadetes

c__Actinobacteria

c__Actinobacteria

0

c__Betaproteobacteria

c__Betaproteobacteria

c__Verrucomicrobiae

c__Verrucomicrobiae

c__Gammaproteobacteria

27 modules, 266 nodes, 926 links (99.89% positive)

c__Actinobacteria

c__Actinobacteria

c__Gemmatimonadetes

c__Gammaproteobacteria

9-Microcystis Actinomycetales Xanthomonadaceae Microcystaceae

10-Chthoniobacteraceae Comamonadaceae Gemmataceae

Fig. 5. Co-occurrence network and modular analysis of four seasons. Node colors indicate different major phyla; pie charts represent the composition of modules with N20 nodes. A red link indicates positive covariation between two individual nodes, whereas a blue link indicates negative covariation. Nodes in the middle of modules are module hubs, and nodes in black boxes are connectors. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

which were Stramenopiles, Saprospiraceae, C111, Synechococcaceae, Candidatus_Xiphinematobacter, Pelagibacteraceae, ACK-M1, and Actinomycetales. In general, the bacterial networks of Lake Taihu were successional based on Microcystis, ACK-M1, Chthoniobacteraceae, Synechococcus, Pirellulaceae and Pelagibacteraceae. 3.5. Relationship between water bacteria and environmental factors To explore the relationship between water bacterial diversity and environmental factors, the top 10 dominant microbial phyla and eight environmental factors (WT, DO, SS, TN，NH4+-N, BOD5, Chla and PD) which were significantly correlated with bacterial diversity (p b 0.05) based on Pearson correlation coefficients were selected for redundancy analysis (RDA). The Monte Carlo permutation test was used to assess

the RDA reliability, revealing that all eight environmental factors were significantly correlated with the total sequencing axis (p = 0.00). Eight environmental factors explained for 49.5% of the species distribution with adjusted R2. WT, SS and TN were positively correlated with RDA1, while Chla, PD and RDA1 were negatively correlated with RDA1 (Fig. S3). To further explore the driving factors underlying bacterial community structure in different seasons, the top 10 dominant families were selected for RDA analysis (Fig. 6). In spring, WT positively correlated with RDA1 (R = 0.99，p = 0.00), while TN (R = 0.99，p = 0.03), DO (R = 0.99，p = 0.01), and BOD5 (R = 0.91，p = 0.01) were negatively correlated with RDA1 (Fig. 6A). In summer, WT and RDA1 were positively correlated (R = 0.45, p = 0.00) (Fig. 6B). Pelagibacteraceae had a close relationship with Pirellulaceae. In autumn, a negative correlation

C. Zhu et al. / Science of the Total Environment 669 (2019) 29–40

Fig. 6. RDA biplots for four seasons based on OTU data and environmental variables. (A) spring; (B) summer; (C) autumn; (D) winter.

37

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was observed between WT and RDA1 (R = −0.68, p = 0.01). SS (R = 0.79, p = 0.03) and TN (R = 0.28, p = 0.00) positively correlated with RDA1 (Fig. 6C). In addition, the points were relatively scattered, indicating that the difference between samples was large. In winter, WT (R = 0.27，p = 0.00), TN (R = 0.97，p = 0.00), NH4+-N (R = 0.98， p = 0.00), BOD5 (R = 0.69，p = 0.00) and RDA1 were positively correlated. DO (R = −0.66, p = 0.04) and SS (R = −0.79, p = 0.05) were negatively correlated with RDA1 (Fig. 6D). In addition, in the winter both the points and bacteria were relatively scattered, indicating that the differences between the samples were large and that the bacterial families were relatively independent. In terms of the annual data, PD, Chla, and WT were the main factors driving the succession of bacterial communities, consistent with the results at the phylum level. However, the RDA results from the four seasons showed that the major factors involved in structuring the bacterial community in spring, summer and autumn were WT, and in winter were TN and NH4+-N. Therefore, different factors shaped the bacterial communities in different seasons with phytoplankton (PD and Chla), temperature (WT) and nitrogen (TN and NH4+-N) as the main driving factors. 4. Discussion 4.1. Seasonal succession of bacterial community in Lake Taihu The major phyla of bacteria in Lake Taihu are Cyanobacteria, Proteobacteria and Verrucomicrobia. The alternate succession of dominant cyanobacterial genera (generally Microcystis and Dolichospermum) led to cyanobacterial blooms appearing year round. In recent years, global warming (O'Neil et al., 2012; Paerl and Paul, 2012) and extreme weather (Yang et al., 2016; Zhu et al., 2014) have altered conditions, and the cyanobacteria in Lake Taihu have continued to multiply greatly (Ma et al., 2016), even during autumn and winter. In particular, the rise in temperature of Lake Taihu was implicated as an important environmental factor (Liu et al., 2011) affecting the rapid development of Microcystis. Microcystis has been widely reported as the dominant cyanobacterial genus in Lake Taihu (Chen et al., 2003; Ma et al., 2016; Tan et al., 2009). In addition, Proteobacteria is a common and dominant phylum in bodies of water, especially Betaproteobacteria which is dominant in freshwater ecosystems (Newton et al., 2011). In this study, Alphaproteobacteria (32.9%), Betaproteobacteria (44.3%), Gammaproteobacteria (13.0%) and Deltaproteobacteria (4.6%) were observed as predominant Proteobacteria classes. While the main families were Pelagibacteraceae (5.4%) and Comamonadaceae (4.2%). A large number of studies have found that Pelagibacteraceae have a large biomass in fresh water and river areas, and that the mass reproduction of Pelagibacteraceae in winter and spring is likely due to reduced water temperature and light (Meziti et al., 2015; Ortmann and Santos, 2016). A significant negative correlation exists between Proteobacteria and Cyanobacteria (R = −0.736, p = 0.00), suggesting a competitive relationship between Proteobacteria and Cyanobacteria in Lake Taihu. In the succession of the four seasons, Microcystis, Candidatus_ Xiphinematobacter and Synechococcus were the three significant genera with the highest relative abundance. In the present study, it is worth noting that the peak relative abundance of Microcystis appeared in the autumn instead of summer with relative abundance in four seasons 19.6% (spring), 39.1% (summer), 75.6% (autumn) and 15.0% (winter). Synechococcus was another dominant genus, and previous reports have suggested that it is an important genus of pico-Cyanobacteria in Lake Taihu with cell size b2 μm (Newton et al., 2011). In a previous study of Lake Taihu phytoplankton, Synechococcus was found throughout the year, especially as a dominant group from April to September (Li et al., 2015). Furthermore, real-time PCR results indicated that Synechococcus was more abundant than Microcystis during the period of July–September in Lake Taihu (Ye et al., 2011). Synechococcus is not only abundant during the cyanobacterial bloom, but also in some low

eutrophication horizontal lakes (Cai et al., 2012). The succession between Synechococcus and Microcystis has been previously reported; however, the mechanism of their interaction in the aquatic ecosystem requires further investigation. Moreover, our results showed that Candidatus_Xiphinematobacter was abundant in all four seasons. This genus is believed to be an endosymbiotic bacteria of entomopathogenic nematodes which are affiliated with Xiphinema (Schlesner et al., 2006). Its specific ecological function in cyanobacterial blooms remains unclear. Network analysis revealed that bacteria in Lake Taihu took Microcystis, ACK-M1, Chthoniobacteraceae, Synechococcus, Pirellulaceae, Pelagibacteraceae, Comamonadaceae, C111, Actinomycetales and Sphingobacteriaceae as the main lines for succession. It is noteworthy that, because of the differences in annotation databases, the same groups may have different taxonomic names after annotation in different databases. We used GreenGenes database as the reference database. Some OTUs annotated in GreenGenes databases as the genera of Plagibacteraceae, ACK-M1, Chthoniobacteraceae, C111, and Rickettsiales were annotated in SILVA databases as the genera of LD12, hgcI_clade (Sporichthyaceae), LD29, Acidimicrobiaceae, and SAR11_clade. During cyanobacterial blooms, the proportion of LD12 and hgcI_clade were relatively high (Zhang et al., 2017b), and it is likely that some OTUs annotated to Pelagibacteraceae and LD12, ACK-M1 and Sporichthyaceae represent the same group. ACK-M1 is the most important line of succession after Microcystis in the entire year, and its relative abundance in winter and spring was the highest of all genera, consistent with previous study (Klawonn et al., 2015). Additionally, a comparison study of the free-living bacteria and phytoplankton colony attached bacteria in Lake Taihu indicated that ACK-M1 was significantly more abundant in free-living bacteria than in phytoplankton colony attached bacteria (Tian et al., 2009). Although ACK-M1 is widely reported as an opportunistic group in other bodies of water (Gabriel et al., 2003; Okuda et al., 2014), its ecological functions remain largely elusive. 4.2. Spatial variations of bacteria in Lake Taihu Our analysis showed that the community composition had a weaker correlation in spatial distribution than temporal succession of bacteria, with no significant difference across different sampling stations. This likely because Lake Taihu is a large shallow lake that is influenced by storms, rainfall, water diversion and navigation, and this strong hydrodynamic action resulted in the homogenization of water. However, several regularities were detected. Station XH had the highest bacterial diversity as well as the best water quality. Station XH is located at the eastern point of Lake Taihu with a relatively prosperous water grass community and few outbreaks of cyanobacteria, so the water quality is well maintained. Station ML showed the lowest bacterial diversity along with the worst water quality. Station ML is located toward the northern area of the lake with relatively high nutrient availability year round (Wu et al., 2019). Consequently, cyanobacterial blooms in ML tend to be severe, especially in summer and autumn. Although XM had a relatively high water quality, it had the second worst bacterial diversity, which indicates that high water quality is not necessarily equal to high species diversity and worse bacterial diversity may be a sign of water quality deterioration. 4.3. Driving factor of bacterial diversity in Lake Taihu The Lake Taihu ecosystem contains diverse bacterial species, which not only serve as an important component of the food chain, but also act to regulate the water environment. Thus, it is important to identify the drivers of bacterial diversity and community structure in these waters. Generally, the factors affecting bacterial diversity within lakes are internal environmental factors, including morphological characteristics (size and depth of the lake) (Kormas et al., 2011; Shen et al., 2011), physical and chemical characteristics (temperature, pH, salinity, and

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mineral nutrients) (Dziallas and Grossart, 2011; Liu et al., 2015b; Wu et al., 2010), the concentration and type of organic matter (DOM) (Grossart et al., 2006), composition of the food web (Adrian et al., 2001; Stockner and Porter, 1988; Van der Gucht et al., 2005), and, interactions between species (giardia feeding effects and the bacteriostasis of viruses) (Coulliette et al., 2010; Daly et al., 2007). In addition, some external factors, such as climatic conditions and human intervention (e.g., multiplication and discharge, ecological dredging, water diversion drainage and another water environment comprehensive treatments) (He et al., 2013; Lian et al., 2018; Paerl and Paul, 2012) may also contribute to bacterial diversity. We found that water temperature, chlorophyll a and phytoplankton were the main factors driving the succession of bacterial communities in Lake Taihu. Water temperature has been confirmed in many studies to be a main factor influencing the structure of the bacterial community within a body of water, (Crump and Hobbie, 2005; Kan et al., 2007). Each kind of bacteria in the water requires an optimum temperature. For example, the optimum temperature for Microcystis ranges from 25 to 32 °C (Bouchard and Purdie, 2011) and the optimum temperature for Aphanizomenon ranges from 23 to 29 °C (Tsujimura et al., 2010). Thus, water temperature can affect the structure of the bacterial community directly. In addition, water temperature can indirectly affect bacterial community structure and composition by regulating chemical and biochemical processes, plankton, fish and other groups, such as higher aquatic plants (Niu et al., 2011). Different lakes possess different driving factors, but even for similar lakes the driving factors of bacterial community structure tend to be different in different seasons. Phytoplankton were shown to be the most important driving factor of bacterial community structure, consistent with previous studies (Niu et al., 2011; Wu et al., 2007). Earlier research has shown that the biomass of Cyanobacteria and Bacillariophyta, and water temperature are the most important factors affecting free-living bacteria and phytoplankton community succession (Niu et al., 2011). This conclusion is consistent with our study, with the main difference being that previous research focused on phytoplankton, while the present study focused on all bacteria in the water. The bacteria in this study included the dominant species of phytoplankton, Microcystis, with an average annual relative abundance of 70.7%. After filtering out the sequences belonging to Microcystis and Dolichospermum and performing RDA analysis, the results did not change and water temperature, chlorophyll a and phytoplankton remained the main factors driving the succession of bacterial communities. In recent years, an increasing number of studies have shown that extreme temperature, wind flow, rainfall, typhoons and other extreme weather have a great impact on the outbreak of cyanobacterial blooms in Lake Taihu (Yang et al., 2017; Yang et al., 2016; Zhu et al., 2014). In addition, water diversion and drainage (Hu et al., 2008; Li et al., 2011), ecological dredging discharge (Hu et al., 2017), and other comprehensive treatment measures also have a certain impact on water quality and have affected bacterial community structure. These factors likely contribute to the increase in cyanobacterial blooms in Lake Taihu and thus should be considered in future studies examining the driving factors of bacterial community structure. 5. Conclusions By collecting 61 water samples from Lake Taihu spanning an entire year and the entire lake, we revealed the succession of dominant cyanobacterial genera with the driving environmental factors and detected their relationships with picocyanobacteria and other free-living bacteria. First, we found Cyanobacteria, Proteobacteria, Verrucomicrobia, Actinobacteria, and Planctomycetes were the dominant bacterial groups across all four seasons in Lake Taihu. The community structure significantly differed among the four seasons, revealing an obvious seasonal succession pattern of bacteria in the lake. Second, the bacterial networks were found to be successional

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based on Microcystis, ACK-M1, Chthoniobacteraceae, Synechococcus, Pirellulaceae and Pelagibacteraceae. Besides, the relationships among cyanobacterial genera, pico-cyanobacterial genera and their related bacteria were also reported. Finally, integration with environmental measures revealed that phytoplankton, temperature, and nitrogen were the main factors driving bacterial community succession with different factors shaping the bacterial communities in different seasons. This study provides new insights into the bacterial succession patterns and regularities of bacterial community structure in a large eutrophic freshwater lake. Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2019.03.087.

Conflict of interest Authors declare that there is no conflict of interest.

Acknowledgements This work is supported by the National Natural Science Foundation of China (grant number: 61305066, 61561146396, 61322308, 61872218, 31600096, 61673241), Tsinghua-Fuzhou Institute research program and the Collaborative Projects with Siemens. The authors (SM and KAAG) would like to express their sincere appreciation to the Deanship of Scientific Research at King Saud University for its funding through the Research Group Project No. RG-1435-012. References Adrian, R., Wickham, S.A., Butler, N.M., 2001. Trophic interactions between zooplankton and the microbial community in contrasting food webs: the epilimnion and deep chlorophyll maximum of a mesotrophic lake. Aquat. Microb. Ecol. 24, 83–97. Assenov, Y., Ramírez, F., Schelhorn, S.-E., Lengauer, T., Albrecht, M., 2007. Computing topological parameters of biological networks. Bioinformatics 24, 282–284. Berry, M.A., Davis, T.W., Cory, R.M., Duhaime, M.B., Johengen, T.H., Kling, G.W., et al., 2017. Cyanobacterial harmful algal blooms are a biological disturbance to Western Lake Erie bacterial communities. Environ. Microbiol. 19, 1149–1162. Bouchard, J.N., Purdie, D.A., 2011. Effect of elevated temperature, darkness, and hydrogen peroxide treatment on oxidative stress and cell death in the bloom-forming toxic cyanobacterium microcystis aeruginosa. J. Phycol. 47, 1316–1325. Cai, Y., Kong, F., Shi, L., Yu, Y., 2012. Spatial heterogeneity of cyanobacterial communities and genetic variation of microcystis populations within large, shallow eutrophic lakes (Lake Taihu and Lake Chaohu, China). J. Environ. Sci. (China) 24, 1832–1842. Cai, H., Jiang, H., Krumholz, L.R., Yang, Z., 2014. Bacterial community composition of sizefractioned aggregates within the phycosphere of cyanobacterial blooms in a eutrophic freshwater lake. PLoS One 9, e102879. Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., et al., 2010. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336. Chen, Y., Qin, B., Teubner, K., Dokulil, M.T., 2003. Long-term dynamics of phytoplankton assemblages: microcystis-domination in Lake Taihu, a large shallow lake in China. J. Plankton Res. 25, 445–453. Coordinators, N.R., 2016. Database resources of the national center for biotechnology information. Nucleic Acids Res. 44, D7–D19. Coulliette, A.D., Peterson, L.A., Mosberg, J.A.W., Rose, J.B., 2010. Evaluation of a new disinfection approach: efficacy of chlorine and bromine halogenated contact disinfection for reduction of viruses and microcystin toxin. Am. J. Trop. Med. Hyg. 82, 279–288. Crespo, B.G., Pommier, T., Fernández-Gómez, B., Pedrós-Alió, C., 2013. Taxonomic composition of the particle-attached and free-living bacterial assemblages in the Northwest Mediterranean Sea analyzed by pyrosequencing of the 16S rRNA. Microbiologyopen 2, 541–552. Crump, B.C., Hobbie, J.E., 2005. Synchrony and seasonality in bacterioplankton communities of two temperate rivers. Limnol. Oceangr. 50 (50), 1718–1729. Daly, Robert I., Ho, Lionel, Brookes†, Justin D., 2007. Effect of chlorination on Microcystis aeruginosa cell integrity and subsequent microcystin release and degradation. Environ. Sci. Technol. 41, 4447–4453. Deng, Y., 2012. Molecular ecological network analyses. BMC Bioinforma. 13 (1) (2012-0530). (13: 113). Deng, Y., Jiang, Y., Yang, Y., He, Z., Luo, F., Zhou, J., 2012. Molecular ecological network analyses. BMC Bioinforma. 13, 113. Desantis, T.Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E.L., Keller, K., et al., 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072. Dittrich, M., Kurz, P., Wehrli, B., 2004. The role of autotrophic Picocyanobacteria in calcite precipitation in an oligotrophic Lake. Geomicrobiol J. 21, 45–53.

40

C. Zhu et al. / Science of the Total Environment 669 (2019) 29–40

Dziallas, C., Grossart, H.P., 2011. Temperature and biotic factors influence bacterial communities associated with the cyanobacterium Microcystis sp. Environ. Microbiol. 13, 1632–1641. Edgar, R.C., 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461. Gabriel, Z., Hannen, E.J., Van, Agterveld K.V., Katleen, V.D.G., Lindstr?M ES, Jeroen VW, et al., 2003. Rapid screening for freshwater bacterial groups by using reverse line blot hybridization. Appl. Environ. Microbiol. 69, 5875–5883. Grossart, H.P., Czub, G., Simon, M., 2006. Algae-bacteria interactions and their effects on aggregation and organic matter flux in the sea. Environ. Microbiol. 8, 1074–1084. Haas, B.J., Gevers, D., Earl, A.M., Feldgarden, M., Ward, D.V., Giannoukos, G., et al., 2011. Chimeric 16S rRNA sequence formation and detection in sanger and 454pyrosequenced PCR amplicons. Genome Res. 21, 494–504. Hahn, M.W., 2006. The microbial diversity of inland waters. Curr. Opin. Biotechnol. 17, 256–261. Haverkamp, T.H., Schouten, D., Doeleman, M., Wollenzien, U., Huisman, J., Stal, L.J., 2009. Colorful microdiversity of Synechococcus strains (picocyanobacteria) isolated from the Baltic Sea. ISME J. 3, 397. He, W., Shang, J., Lu, X., Fan, C., 2013. Effects of sludge dredging on the prevention and control of algae-caused black bloom in Taihu Lake, China. J. Environ. Sci. 25, 430–440. Hu, W., Zhai, S., Zhu, Z., 2008. Impacts of the Yangtze River water transfer on the restoration of Lake Taihu. Ecol. Eng. 34, 30–49. Hu, X., Wu, S., Min, Z., Weng, S., Guo, L., 2017. Study on the Changes of Nitrogen and Phosphorus Release with Time from Sediment in Taihu Lake after Ecological Dredging. Earth & Environmental Science, Iop Conference Series, p. 012058. Jizhong, Z., Ye, D., Feng, L., Zhili, H., Qichao, T., Xiaoyang, Z., 2010. Functional molecular ecological networks. Mbio 1, 1592–1601. Jizhong, Z., Ye, D., Feng, L., Zhili, H., Yunfeng, Y., 2011. Phylogenetic molecular ecological network of soil microbial communities in response to elevated CO2. mBio 2 (e00122–11). Kan, J., Suzuki, M.T., Wang, K., Evans, S.E., Chen, F., 2007. High temporal but low spatial heterogeneity of bacterioplankton in the Chesapeake Bay. Appl. Environ. Microbiol. 73, 6776–6789. Klawonn, I., Bonaglia, S., Brüchert, V., Ploug, H., 2015. Aerobic and anaerobic nitrogen transformation processes in N2-fixing cyanobacterial aggregates. ISME J. 9, 1456–1466. Kormas, K.A., Gkelis, S., Vardaka, E., Moustaka-Gouni, M., 2011. Morphological and molecular analysis of bloom-forming cyanobacteria in two eutrophic, shallow Mediterranean lakes. Limnologica 41, 167–173. LaMontagne, M.G., Holden, P.A., 2003. Comparison of free-living and particle-associated bacterial communities in a coastal lagoon. Microb. Ecol. 46, 228–237. Li, Y., Acharya, K., Yu, Z., 2011. Modeling impacts of Yangtze River water transfer on water ages in Lake Taihu, China. Ecol. Eng. 37, 325–334. Li, J., Zhang, J., Liu, L., Fan, Y., Li, L., Yang, Y., et al., 2015. Annual periodicity in planktonic bacterial and archaeal community composition of eutrophic Lake Taihu. Sci. Rep. 5, 15488. Lian, H., Lei, Q., Zhang, X., Yen, H., Wang, H., Zhai, L., et al., 2018. Effects of anthropogenic activities on long-term changes of nitrogen budget in a plain river network region: a case study in the Taihu Basin. Sci. Total Environ. 1212–1220. Liu, X., Lu, X., Chen, Y., 2011. The effects of temperature and nutrient ratios on Microcystis blooms in Lake Taihu, China: an 11-year investigation. Harmful Algae 10, 337–343. Liu, L., Jun, Y., Hong, L., Zheng, Y., 2015a. Synchronous dynamics and correlations between bacteria and phytoplankton in a subtropical drinking water reservoir. FEMS Microbiol. Ecol. 90, 126–138. Liu, L., Yang, J., Zheng, Y., Wilkinson, D.M., 2015b. The biogeography of abundant and rare bacterioplankton in the lakes and reservoirs of China. ISME J. 9, 2068. Lucie, G., 2007. Ecology. Doing battle with the green monster of Taihu Lake. Science 317, 1166. Ma, J., Qin, B., Paerl, H.W., Brookes, J.D., Hall, N.S., Shi, K., et al., 2016. The persistence of cyanobacterial (Microcystis spp.) blooms throughout winter in Lake Taihu, China. Limnol. Oceanogr. 61, 711–722. Meziti, A., Kormas, K.A., Moustaka-Gouni, M., Karayanni, H., 2015. Spatially uniform but temporally variable bacterioplankton in a semi-enclosed coastal area. Syst. Appl. Microbiol. 38, 358. Newton, R.J., Jones, S.E., Alexander, E., Mcmahon, K.D., Stefan, B., 2011. A guide to the natural history of freshwater lake bacteria. Microbiol Mol Biol Rev 75, 14–49. Niu, Y., Shen, H., Chen, J., Xie, P., Yang, X., Tao, M., et al., 2011. Phytoplankton community succession shaping bacterioplankton community composition in Lake Taihu, China. Water Res. 45, 4169–4182. O'Hara, R.B., Legendre, P., Stevens, M.H., Blanchet, F.G., Kindt, R., Solymos, P., et al., 2011. Vegan: community ecology package. Version 2.0-2. J. Stat. Softw. 48, 1–21. Okafor, N., 2011. Ecology of Microorganisms in Freshwater: Springer Netherlands. Okuda, N., Watanabe, K., Fukumori, K., Nakano, S.I., Nakazawa, T., 2014. Biodiversity Researches on Microbial Loop in Aquatic Systems. Olesen, J.M., Jordi, B., Dupont, Y.L., Pedro, J., 2007. The modularity of pollination networks. Proc. Natl. Acad. Sci. U. S. A. 104, 19891–19896. O'Neil, J.M., Davis, T.W., Burford, M.A., Gobler, C.J., 2012. The rise of harmful cyanobacteria blooms: the potential roles of eutrophication and climate change. Harmful Algae 14, 313–334. Ortega-Retuerta, E., Joux, F., Jeffrey, W.H., Ghiglione, J.F., 2013. Spatial variability of particle-attached and free-living bacterial diversity in surface waters from the Mackenzie River to the Beaufort Sea (Canadian Arctic). Biogeosciences 10, 2747–2759.

Ortmann, A.C., Santos, T.T.L., 2016. Spatial and temporal patterns in the Pelagibacteraceae across an estuarine gradient. FEMS Microbiol. Ecol. 92. Paerl, H.W., Paul, V.J., 2012. Climate change: links to global expansion of harmful cyanobacteria. Water Res. 46, 1349–1363. Paerl, H.W., Xu, H., McCarthy, M.J., Zhu, G., Qin, B., Li, Y., et al., 2011. Controlling harmful cyanobacterial blooms in a hyper-eutrophic Lake (lake Taihu, China): the need for a dual nutrient (N & P) management strategy. Water Res. 45, 1973–1983. Pernthaler, J., 2013. Freshwater microbial communities. In: Rosenberg, E., DeLong, E., Lory, S., Stackebrandt, E., Thompson, F. (Eds.), The Prokaryotes. Springer, Berlin Heidelberg, pp. 97–112. Qin, B., Xu, P., Wu, Q., Luo, L., Zhang, Y., 2007. Environmental issues of Lake Taihu, China. Hydrobiologia 581, 3–14. Schlesner, H., Jenkins, C., Staley, J.T., 2006. The Phylum Verrucomicrobia: A Phylogenetically Heterogeneous Bacterial Group: Springer New York. Shen, H., Niu, Y., Xie, P., Tao, M., Yang, X.I., 2011. Morphological and physiological changes in Microcystis aeruginosa as a result of interactions with heterotrophic bacteria. Freshw. Biol. 56, 1065–1080. Shi, S., Nuccio, E.E., Shi, Z.J., He, Z., Zhou, J., Firestone, M.K., 2016. The interconnected rhizosphere: high network complexity dominates rhizosphere assemblages. Ecol. Lett. 19, 926–936. Stockner, J., Porter, K., 1988. Microbial food webs in freshwater planktonic ecosystems. In: Carpenter, S. (Ed.), Complex Interactions in Lake Communities. Springer, New York, pp. 69–83. Tan, X., Kong, F., Zeng, Q., Cao, H., Qian, S., Zhang, M., 2009. Seasonal variation of Microcystis in Lake Taihu and its relationships with environmental factors. J. Environ. Sci. 21, 892–899. Tang, X., Li, L., Shao, K., Wang, B., Cai, X., Zhang, L., et al., 2015. Pyrosequencing analysis of free-living and attached bacterial communities in Meiliang Bay, Lake Taihu, a large eutrophic shallow lake in China. Can. J. Microbiol. 61, 22–31. Tian, C., Tan, J., Wu, X., Ye, W., Liu, X., Li, D., et al., 2009. Spatiotemporal transition of bacterioplankton diversity in a large shallow hypertrophic freshwater lake, as determined by denaturing gradient gel electrophoresis. J. Plankton Res. 31, 885–897. Tsujimura, S., Ishikawa, K., Tsukada, H., 2010. Effect of temperature on growth of the cyanobacterium Aphanizomenon flos-aquae. Lake Biwa and Lake Yogo. Phycol. Res. 49, 275–280. Van der Gucht, K., Vandekerckhove, T., Vloemans, N., Cousin, S., Muylaert, K., Sabbe, K., et al., 2005. Characterization of bacterial communities in four freshwater lakes differing in nutrient load and food web structure. FEMS Microbiol. Ecol. 53, 205–220. Vani, M., Philippe, A., Nicolas, T., Connie, L., 2014. Phylogenetic differences in attached and free-living bacterial communities in a temperate coastal lagoon during summer, revealed via high-throughput 16S rRNA gene sequencing. Appl. Environ. Microbiol. 80, 2071–2083. Vörös, L., Callieri, C., Balogh, K.V., Bertoni, R., 1998. Freshwater picocyanobacteria along a trophic gradient and light quality range. Hydrobiologia 369-370, 117–125. Wu, Q.L., Zwart, G., Wu, J., Kamst-van Agterveld, M.P., Liu, S., Hahn, M.W., 2007. Submersed macrophytes play a key role in structuring bacterioplankton community composition in the large, shallow, subtropical Taihu Lake, China. Environ. Microbiol. 9, 2765–2774. Wu, W., Li, G., Li, D., Liu, Y., 2010. Temperature may be the dominating factor on the alternant succession of Aphanizomenon flos-aquae and Microcystis aeruginosa in Dianchi Lake. Fresenius Environ. Bull. 20, 846–853. Wu, T., Qin, B., Brookes, J.D., Yan, W., Ji, X., Feng, J., 2019. Spatial distribution of sediment nitrogen and phosphorus in Lake Taihu from a hydrodynamics-induced transport perspective. Sci. Total Environ. 650, 1554–1565. Xu, H., Paerl, H.W., Qin, B., Zhu, G., Gaoa, G., 2010. Nitrogen and phosphorus inputs control phytoplankton growth in eutrophic Lake Taihu, China. Limnol. Oceanogr. 55, 420–432. Yang, Z., Zhang, M., Shi, X., Kong, F., Ma, R., Yu, Y., 2016. Nutrient reduction magnifies the impact of extreme weather on cyanobacterial bloom formation in large shallow Lake Taihu (China). Water Res. 103, 302–310. Yang, J.R., Lv, H., Isabwe, A., Liu, L., Yu, X., Chen, H., et al., 2017. Disturbance-induced phytoplankton regime shifts and recovery of cyanobacteria dominance in two subtropical reservoirs. Water Res. 120, 52–63. Ye, W., Tan, J., Liu, X., Lin, S., Pan, J., Li, D., et al., 2011. Temporal variability of cyanobacterial populations in the water and sediment samples of Lake Taihu as determined by DGGE and real-time PCR. Harmful Algae 10, 472–479. Zhang, J., Ding, X., Guan, R., Zhu, C., Xu, C., Zhu, B., et al., 2017a. Evaluation of different 16S rRNA gene V regions for exploring bacterial diversity in a eutrophic freshwater lake. Sci. Total Environ. 618. Zhang, J., Zhu, C., Guan, R., Xiong, Z., Zhang, W., Shi, J., et al., 2017b. Microbial profiles of a drinking water resource based on different 16S rRNA V regions during a heavy cyanobacterial bloom in Lake Taihu, China. Environ. Sci. Pollut. Res. 24, 12796–12808. Zhang, M., Shi, X., Yang, Z., Yu, Y., Shi, L., Qin, B., 2018. Long-term dynamics and drivers of phytoplankton biomass in eutrophic Lake Taihu. Sci. Total Environ. 876–8865. Zhu, M., Paerl, H.W., Zhu, G., Wu, T., Li, W., Shi, K., et al., 2014. The role of tropical cyclones in stimulating cyanobacterial (Microcystis spp.) blooms in hypertrophic Lake Taihu, China. Harmful Algae 39, 310–321.