LI Xiang-yang,LI Yuan,YANG Zi-lin,LI Dan,ZENG Si-yu,HE Miao

(1.School of Life and Health Science,Kaili University,Kaili 556011,Guizhou,China；2. School of Environment, Tsinghua University, Beijing 100084, China；3.Department of Environmental Science and Engineering,Fudan University,Shanghai 200433,China；4. China Three Gorges Corporation, Beijing 100038, China)

Abstract:To investigate and compare the distribution,diversity and dynamics of bacterioplankton communities in Lake Taihu and Lake Yangcheng in Jiangsu Province,China,the bacterial community composition was analyzed from 85 samples using 454-pyrosequencing of 16S rRNA genes.The samples were taken weekly within an intensive time period from June to October 2012.A total of 142 354 clean reads were generated that were assigned to 4 589 operational taxonomic units(OTUs),with Proteobacteria(mainly γ-Proteobacteria)and Bacteroidetes being the dominant taxa in both lakes.In addition,19.55%of OTUs,accounting for 95.01%of the total reads,were shared by bacterial communities in the two lakes,which indicated a high degree of overlap between them.The communities in Lake Yangcheng had a higher α-diversity than those in Lake Taihu,which may be mainly attributed to the rare taxa found in both lakes.Interestingly,the results showed that the bacterioplankton composition profile dramatically fluctuated over time.This may be explained by the low capability of the communities to resist external disturbances in extremely shallow lakes.Our study provides information for better understanding of the spatiotemporal dynamics in bacterial communities and differences in their compositions between two related lakes.

Key words:bacterial community；16S rRNA gene；454-pyrosequencing；Lake Taihu；Lake Yangcheng

Bacterial communities are key components in aquatic ecosystems,and play a crucial role in biogeochemical cycles and profoundly impact water quality[1].The composition and diversity of bacterioplankton are closely related to spatial,temporal and environmental factors in water systems,such as ecological habitats,seasonality,and nutrient concentrations[2～6].For example,elevation showed strong influence on bacterioplankton community composition,and the dissimilarity of bacterioplankton community increased with increasing differences in elevation[4]；bacterioplankton community dissimilarity strongly adheres to geographic distance decay relationship in 42 lakes and reservoirs across China[6].

Lake Taihu is the third largest freshwater lake in China,covering an area of 2 338 km2with a mean depth of 1.9 meters[7].Lake Yangcheng,part of the Taihu basin,has a similar depth and is about one-nineteenth the size of Lake Taihu.Two lakes are in close proximity and are the key freshwater resources for residents in the surrounding areas.In recent decades,both lakes have undergone increasingly serious eutrophication as a result of human activities[8～9].In recent years,with high-throughput sequencing of the 16S rRNA gene,many studies have been performed to investigate the diversity and composition of bacterioplankton,as well as its relationship to environmental factors[10～11].Several studies revealed that seasonal succession caused significant differences in bacterial communities,and temporal variation of the microbial community was significantly greater than spatial variation in Lake Taihu[10～13].However,to date,sampling in an intensive time period to investigate the composition and dynamics of bacterioplankton communities in Lake Taihu has rarely been documented.

Studies of the bacterioplankton community in Lake Yangcheng are scarce,except for that Bai et al.[14]investigated in 2013 the bacterial community structure,especially the Cyanobacteria composition,and compared the community similarity between Lakes Taihu and Yangcheng at temporal scale.However,the understanding of bacterial community responding to environmental factors in this lake remains poor.More importantly,the two adjacent lakes share similar geographic and climatic conditions,so they can be ideally used to explore the determinants leading to the divergence of the bacterial profiles between these two lakes.

Therefore,by collecting water samples weekly from June to October 2012 at each of three sites in the two lakes,we characterized and compared the diversity and composition of their bacterioplankton communities,explored the spatiotemporal dynamics of bacterial composition profiles,and determined the linkages within the bacterial communities in response to changing environmental parameters.

1 Materials and methods

1.1 Sampling sites

Water samples were collected from total six sites in Lake Taihu and Lake Yangcheng,Jiangsu,China.The sampling sites are shown in Fig.1.Sampling site T1(Jinsu port)is a water source area of Suzhou City,which is less affected by pollution than the other two sampling sites,T2(beacon No.4)and T3(Xintang port).The latter two sites are located in areas subjected to industrial wastewater dis-charge(Fig.1A).Lake Yangcheng is divided into three parts,and water samples were collected from the Y1(western),Y2(middle)and Y3(eastern)parts of the lake(Fig.1B).

1.2 Sampling and environmental factors

Triplicate water samples were collected weekly 0.5 m below the surface from six sites from June to October 2012.Some samples were not collected due to bad weather.A total of 85 samples were obtained from the two lakes for processing and analysis.For each sample,water temperature(Tem),pH,dissolved oxygen(DO),chlorophyll-a(Chl-a)and algal density were simultaneously measured in situ using a Multi-Parameter Water Quality Sonde(6600V2-00,YSI Inc.,America).Total nitrogen(TN),total phosphorus(TP),ammonium nitrogen(NH4+-N),nitrate nitrogen(NO3-N)and chemical oxygen demand(COD)were determined using the standard methods[15].The eutrophication evaluation was performed with the trophic level index(TLI)method[16].

1.3 DNA extraction,amplification,and 454-pyrosequencing

The samples were transported to the laboratory on ice for DNA extraction immediately.A 100 mL volume of water from each sample was centrifuged using a high-speed freezing centrifuge at 12 000 r/min for 15 min at 4°C.The supernatant was discarded and the precipitate was resuspended with ddH2O.DNA was extracted using Universal Genomic DNA Extraction Kit Ver.3.0(DV811A,TaKaRa Bio Inc.,China)according to the manufacturer’s instructions.DNA was extracted from the triplicate samples of each site and was mixed together.The primer pair 338F(5′-ACTCCTACGGGAGGCAGCAG-3′)and 533R(5′-TTACCGCGGCTGCTGGCAC-3′)was used to amplify the V3 region of the 16S rRNA gene[17].The PCR products were purified and sequenced on the 454 GS FLX Titanium(SinoGenoMax Co.,Ltd.,Beijing,China).The raw pyrosequencing data generated in the present study were submitted to the National Center for Biotechnology Information(NCBI)Sequence Read Archive(SRA)under accession number SRP092336.

1.4 Sequence processing and bacterial popula原tion analyses

Pyrosequencing reads were analyzed with MOTHUR following the standard operating procedure(SOP)suggested by Schloss et al.[18].After removing the primer sequences and barcodes,low-quality reads were trimmed,including reads with an ambiguous base,less than 200 bp,or with homopolymers longer than 8 bp.Chimeras were removed through the“chimera.uchime”method,using the preclustered sequences as their own reference.Reads affiliated with chloroplasts or mitochondria were excluded from the subsequent analysis.Finally,clean reads were aligned and clustered into OTUs with a threshold value of 97%sequence similarity.

1.5 Bacterial diversity and statistical analyses

Fig.1 Sampling locations in Lake Taihu(A)and Lake Yangcheng(B)

To avoid biases generated by differences in sequencing depth,samples were normalized to the same depth,based on the sample that had the lowest number of sequences prior to downstream bioinformatics analysis.The α-diversity indices(Shan-non,Simpson and Chao1)were calculated using the“summary.single”command implemented in MOTHUR,and displayed as a boxplot for both two lakes.The β-diversity measure was used to analyze bacterial community differences between samples and sites.The microbial community structures in different samples were compared using UniFrac[19]based on the phylogenetic relationship of representative reads from different samples.Weighted UniFrac distance calculations and the corresponding significant test were performed between pairs of samples using the Fast UniFrac pipeline[20].

Statistical analysis of metagenomic profiles(STAMP)was employed to test for significant differences in bacterial community abundances between Lake Taihu and Lake Yangcheng[21].Statistical significance of differences between samples(q value)was assessed using the two-sided Fisher’s exact test with Storey’s false discovery rate method of multiple test correction within STAMP.The confidence intervals were determined using the Newcombe-Wilson method.Features with a q value of less than 0.05 were deemed significant.

1.6 Relationships between bacterial communi原ties and environment

The vegan 2.3-0 package implemented in R(http://www.r-project.org/)was used to explore the relationship between changes in community structure and measured environment variables.The detrended correspondence analysis(DCA)values of the gradient length along the longest axis of Lake Taihu and Lake Yangcheng were 3.18 and 3.66,respectively.Therefore,redundancy analysis(RDA)was chosen for ordination analysis.As some environment variables were missing for some samples,only 59 samples(29 for Lake Taihu,30 for Lake Yangcheng)were included in RDA analysis.Environmental factors were log-transformed and standardized as explanatory variables.The significance of the environmental factors was tested with 999 Monte Carlo permutations,and only factors that were found to be significant(P＜0.05)were included in the subset of forward selected variables.

2 Results

2.1 Sequencing data and diversity analysis

Pyrosequencing yielded a total of 336 341 raw reads from the 85 samples collected from the two lakes.After removing low quality reads,142 354 clean reads remained from the 85 samples(71 027 reads in 42 Lake Taihu samples and 71 327 reads in 43 Lake Yangcheng samples).These clean reads were aligned and clustered into 4 589 unique OTUs(2 368 in Lake Taihu and 3 118 in Lake Yangcheng)at 97%sequence similarity.The numbers of OTUs varied from 1 031 to 3 489 in all samples.

The α-diversity indices(Shannon,Simpson and Chao1)were calculated using a subset of 1 031 reads per sample,selected randomly based on the sample with the smallest sequencing effort.The sequencing effort was sufficient to capture the relative complete diversity of these communities,which were confirmed by the high Good’s coverage index,ranging from 88.1%to 96.5%in each sample(Table S1).Differences in the indices between the two lakes are present in Fig.2 with the P values of paired sample t-test shown on the top of each boxplot.Overall,the community diversity in Lake Yangcheng was higher than that in Lake Taihu.While the former had a greater Shannon index and a smaller Simpson index than the latter(Figs.2A and 2B,P＜0.01 for Shannon index,P＜0.02 for Simpson index).On average,the Chao1 index of Lake Yangcheng showed～1.36 times the community richness index in Lake Taihu(Fig.2C,P＜0.001).

Among the 4 589 OTUs,19.55%were shared by the two lakes,while 32.05%and 48.40%were unique to samples from Lake Taihu and Lake Yangcheng,respectively(Fig.3A).When the abundance of each OTU was accounted for,95.01%of the total reads occurred in both lakes,1.86%were exclusive to the Lake Taihu,and 3.13%to the Lake Yangcheng(Fig.3B).

2.2 Bacterial community composition

Fig.2 Boxplot of diversity indices in Lake Taihu and Lake Yangcheng

Fig.3 Comparison of bacterial community structure between Lake Taihu and Lake Yangcheng

The 4 589 OTUs were assigned into 23 known phyla covering 193 genera based on MOTHUR-modified RDP taxonomy.At the phylum level,Lakes Taihu and Yangcheng shared all of the top ten major phyla(assayed as average relative abundance)(Fig.4A).The dominant phyla included Proteobacteria(65.26%),Bacteroidetes(13.52%),Actinobacteria(1.28%),Firmicutes(1.30%)and Cyanobacteria(0.98%)for Lake Taihu,and Proteobacteria(57.92%),Bacteroidetes(18.43%),Cyanobacteria(2.33%),Actinobacteria(2.00%),Verrucomicrobia(1.18%)for Lake Yangcheng(Fig.4A).In both lakes,γ-Proteobacteria(37.95%in Lake Taihu vs.31.16%in Lake Yangcheng),followed by β-Proteobacteria(19.20%vs.20.15%)and α-Proteobacteria(4.61%vs.3.17%),was the dominant subdivisions of Proteobacteria.The top five major phyla occupied 82.34%and 81.86%of the total bacterial composition in Lakes Taihu and Yangcheng,respectively.In more detail,bacterial composition of each sample at the phylum level is shown in Figs.4B and 4C.Overall,both lake bacterial communities displayed a similar composition.However,the relative abundances of all the phyla,except for Firmicutes and Gemmatimonadetes,were significantly distinct(P＜0.05)between the two lakes based on STAMP analysis(Fig.5A).

Fig.4 Relative abundances of bacteria within the community at the phylum level in Lake Taihu and Lake Yangcheng

At the genus level,the most abundant genera(average relative abundance＞0.1%)made up 55.29%and 50.98%of the total bacterial composition in Lakes Taihu and Yangcheng,respectively(the details are listed in Table S2).Genera with average relative abundance＞1% included Escherichia_Shigella(23.24%in Lake Taihu vs.18.26%in Lake Yangcheng),Serratia(10.98%vs.8.19%),Limnohabitans(7.72%vs.5.52%),Flavobacterium(3.96%vs.6.83%),Algoriphagus(1.46%vs.0.87%),Polynucleobacter(1.34%vs.2.83%),Rhodobacter(1.33%vs.1.19%),and GpⅡa(0.49%vs.1.42%)(Table S2).Accordingly,the two lakes had similar profiles of bacterial community composition.Two genera of Enterobacteriaceae,containing Escherichia and Serratia,represented the dominant bacterial groups across all samples.Among seven top abundant genera,Polynucleobacter and GpⅡa showed statistically marked differences(P＜0.05)between two lakes based on STAMP analysis(Fig.5B).

2.3 Temporal variations of bacterial composi原tion within each lake

Fig.5 Comparison of bacterial composition profiles for Lake Taihu(red)and Lake Yangcheng(green)at the phylum(A)and the genus(B)levels using STAMP analysis

Samples obtained from three different sites in each lake at the same time point were chosen to compare their bacterioplankton composition temporally.Clearly,bacterial abundances varied at the phylum level over time among samples at each site of Lake Taihu(Fig.4B)and Lake Yangcheng(Fig.4C).For example,among 11 samples from the T1 site,the abundances of Bacteroidetes(bright blue)fluctuated widely,ranging from 3.71%to 23.15%,with a medium value of 6.20%.In addition,the weighted UniFrac distance analysis showed significant changes in the distance values between all pairs of samples collected from these two lakes(P＜0.05；Fig.6).

2.4 Spatial variation of bacterial community and its responses to the environmental parame原ters

Fig.6 Heatmap showing the weighted UniFrac distances between a pair of samples from six sampling sites in Lake Taihu(T1～3)(A)and Lake Yangcheng(Y1～3)(B)

RDA was performed to determine the relationship between environmental factors and bacterial community.In Lake Taihu,the first two axes showed 14.84%and 12.29%of the total variance for bacterioplankton OTUs composition(Fig.7A).Sampling site T1(Jinsu port)is a water source area of Suzhou City,which is less affected by pollution than the other two sampling sites.All samples collected from T1 clustered together and could be distinctly discriminated from the samples collected from T2 and T3 by RDA ordination(Fig.7A).Based on the Monte Carlo permutation tests in redundancy analysis,seven environment variables including NO3-N(P=0.001),TN(P=0.005),TP(P=0.001),Tem(P=0.035),pH(P=0.001),Chl-a(P=0.001),and algal density(P=0.004)showed significant influences on bacterial communities(P＜0.05)；other three environment variables(NH4+-N,COD,and DO)had P values greater than 0.05.In Lake Yangcheng,the first two axes explained 14.85%of the cumulative variance in the species-environment correlation with 9.7%in Axis 1 and 5.15%in Axis 2.Y3 had a smallest trophic level index(TLI)among three sites(Fig.S1).There was a separation between groups from Y3 and the Y1 and Y2 sites(Fig.7B).In contract to Lake Taihu,only three environmental factors(TP,P=0.025；Tem,P=0.002；algal density,P=0.016))in Lake Yangcheng were found to significantly contribute to the planktonic bacterial assemblage environment relationship(Fig.7B).

3 Discussion

One of the main objectives of the present study was to determine whether bacterial communities in Lakes Taihu and Yangcheng differed in diversity and composition.Our results revealed a higher αdiversity of bacterial communities in Lake Yangcheng compared to Lake Taihu using Shannon,Simpson and Chao1 indices(Fig.2).This result matches those from the previous investigation that Lake Yangcheng had larger bacteria diversity than Lake Taihu at phylum level[14].Previous studies showed that biodiversity was negatively correlated with a lake area,as bacterial communities in small lakes with large catchment area are easily and frequently influenced by the unpredictable input of bacteria from their surrounding catchments or sediments[4,22～23].Thus,a higher biodiversity in Lake Yangcheng was probably due to the smaller lake area than that of Lake Taihu.Additionally,Li et al.[4]reported in 2017 that the rare taxa govern the overall bacterial community diversity pattern.There were 1 471 and 2 221 OTUs unique to Lake Taihu and Lake Yangcheng,respec tively(Fig.3A).Hence,the greater number of specific OTUs identified in Lake Yangcheng compared with that in Lake Taihu,was potentially an important reason resulting in significant difference of bacterial community diversity between the two lakes.

Fig.7 RDA ordination analysis of the distribution of bacterial community related to the significant environment variables(P＜0.05)in Lake Taihu(A)and Lake Yangcheng(B)

An interesting finding in this study,however,was that 19.55%of the OTUs,occupying 95.01%of the total reads,were shared between bacterial com munities of the two lakes(Fig.3).We speculated that high degree of overlap between these two lakes was probably shaped by their similar geography and climate,as they are close to each other in distance and both originate from the Taihu basin[6].It has been reported that geographic distance showed a stronger correlation with the similarities of the bacterial community in Lake Taihu[24].In contrast to our findings,distinct or significant differences were observed in bacterioplankton community composition among closely situated lakes,e.g.three high-elevation tropical lakes located within the Lauca basin[25],two sub-alpine lakes in Taiwan[26],and two saline meromictic lakes(lakes Shunet and Shira)[27].

The overlap of OTUs between two lakes was attributed to the top shared dominant phyla(Fig.4A).In accordance with our results,numerous studies showed that five phyla(Proteobacteria,Actinobacteria,Bacteroidetes,Cyanobacteria and Verrucomicrobia)were the most abundant bacterial taxa in common lineages of freshwater lake bacteria[1,7,14,28～29].Although all five subdivisions of Proteobacteria were identified in two lakes,γ-Proteobacteria was the dominant subphylum,followed by β-Proteobacteria and α-Proteobacteria.This was inconsistent in some ways with the findings from previous studies that β-Proteobacteria was considered to be the dominant subphylum of the Proteobacteria[1,7,10,30].However,Huang et al.[31]reported in 2019 that γ-Proteobacteria followed by β-Proteobacteria was the most abundant class in the lake,lake wetland and estuary sediment samples.Therefore,we speculated that bacterial component exchange between sediments and water column may lead to this result.

At temporal scale,our results reveal a remarkable weekly fluctuation of bacterial communities at each site with sampling in an intensive time period.This phenomenon could be interpreted as that the bacterial community diversity in extremely shallow lake was instable,and was susceptible to climate and other factors,such as storms,rainfall,winds,and water diversion[10,13,32].Unlike in a deep reservoir or an ocean where water stratification is benefit for maintaining the stability of microbial community[33～34],wind-induced sediment resuspension represents a major characteristic in shallow turbid lake systems[30,35].Sediment resuspension can push bacteria to be released from sediments and incorporated into water column[31].For instance,the diversity and structure of bacterioplankton communities significantly varied in a wind wave turbulence experiment[30].In addition,two lakes probably suffer from frequent storms in summer due to the East Asian monsoon[32].

At spatial scale,RDA ordination analysis showed a distinct separation of taxonomic composition between the T1 site and the other two sampling sites(T2 and T3)in Lake Taihu.Previous studies reported that trophic status displayed significant correlation with community composition,and had indirect effects by altering the composition of bacterioplankton[3,36～37].It has been reported that the discharge of domestic and industrial wastewater led to an increased level of the nutrient loading[38].The seven environmental factors(NO3-N,TN,TP,Tem,pH,Chl-a,and algal density)influencing bacterial community compositions in Lake Taihu are related to trophic status except the time-related factor Tem.The T1 sample points are distributed at the lower left corner of Fig.7A.This is consistent with the fact that T1 is a crucial drinking water source and has milder eutrophication than the T2 and T3 sites,both of which are located in areas subjected to industrial wastewater discharge according to trophic level index(TLI)evaluation(Fig.S1).Similarly,the three factors affecting bacterial community changes in Lake Yangcheng were also related to trophic status(TP and algal density)and seasonality(Tem).Bacterial community in the site Y3 was distinct from those in the other two sampling sites(Y1 and Y2)in Lake Yangcheng,possibly due to the lower TP in the former site(Table S3).Thereby,the significant differences in spatial distribution of community composition in two lakes can be explained mostly by eutrophication degree and are highly related to the spatiotemporal changes of environmental factors.

Our RDA analysis showed seven environment factors(NO3-N,TN,TP,Tem,pH,Chl-a,and algal density)in Lake Taihu and Lake Yangcheng were significantly correlated with bacterial communities.These results are partly consistent with those findings in recent studies,which showed that there are strong linkages between bacterial community composition and water temperature,pH,NO3-N,and Chl-a in Lake Taihu[12,30,38].It is increasingly apparent that the composition and diversity of bacterioplankton are closely related to the surrounding environmental factors.Nutrientbioavailability(e.g.,NO3-N and phosphorus)and water properties(e.g.,temperature and pH)play critical roles in driving the activities and large-scale distribution of freshwater bacterial communities because they are playing a crucial role in the growth and development of bacteria[39～41].For example,phosphorus concentration was found to be one of the most important factors influencing change of bacterioplankton communities[39].Previous studies revealed that temperature has a significant effect on the dynamics and composition of plankton communities in rivers[40].As the range of optimal growth temperature for each phenotype is different,water temperature changes can result in variation in microbial community composition.In addition,it is well known that Chl-a can be used as a measure of algal biomass,which is a biological disturbance to lake bacterial communities.Various investigations have reported that Chl-a is significantly related to bacterial community composition[40,42].

In conclusion,we monitored the spatiotemporal dynamics of bacterial communities in the two lakes by sampling weekly within an intensive time period and through 454-pyrosequencing of 16S rRNA genes.In bacterial compositions,Lakes Taihu and Yangcheng shared the most abundant taxa and had no significant differences.However,Lake Yangcheng harbored significantly higher α diversity than Lake Taihu.A higher percentage of unique reads in Lake Yangcheng compared with that in Lake Taihu implied that the differences in bacterial diversity were mainly caused by the presence of rare taxa.Importantly,we observed remarkable fluctuation in the bacterial communities over time in both lakes.This suggested the low capability of the communities to resist external disturbances in extremely shallow lakes.In addition,the linkages within the bacterial communities in response to changing environmental parameters were documented for both lakes.

Supplement data

The following materials are available in the online version of this article.

Table S1 454-sequencing parameter statistics of clean reads

Table S2 Genera with an average relative abundance＞0.1%

Table S3 Summary of environment variables

Fig.S1 Trophic level index for six sites in the two lakes