Journal of Oceanology and Limnology   2020, Vol. 38 issue(3): 745-758     PDF       
http://dx.doi.org/10.1007/s00343-019-9096-7
Institute of Oceanology, Chinese Academy of Sciences
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Article Information

ZHANG Lei, LI Li, LIU Mengna, HU Yao, JIANG Jiahu
Temporal and spatial variations of bacterial community compositions in two estuaries of Chaohu Lake
Journal of Oceanology and Limnology, 38(3): 745-758
http://dx.doi.org/10.1007/s00343-019-9096-7

Article History

Received Apr. 19, 2019
accepted in principle Aug. 5, 2019
accepted for publication Sep. 6, 2019
Temporal and spatial variations of bacterial community compositions in two estuaries of Chaohu Lake
ZHANG Lei1,2, LI Li2, LIU Mengna2, HU Yao2, JIANG Jiahu1     
1 State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008;
2 School of Civil Engineering and Architecture, Chuzhou University, Chuzhou 239000, China
Abstract: The distinctive estuary hydrodynamics and nutrient input make the estuary ecosystem play a key role in lake ecosystems. The Nanfei River and Zhaohe River are two main inlets of Chaohu Lake, Anhui, East China. We selected estuaries of the two rivers as representative areas to study temporal and spatial changes of bacterial communities. In August (summer) and November (autumn) 2016 and February (winter) and May (spring) 2017, 16 water and sediment samples were collected from the estuaries. Physicochemical characteristics indicate significant differences in the nutritional status and eutrophication index of the estuaries due mainly to organic input. Examination of the number of operational taxonomic units, the diversity index, the community composition, and redundancy analysis revealed the following. First, the existence of varying degrees of seasonal differences in the distribution of almost all bacteria. In addition, the species diversity in the sediment samples was higher than that in the water samples, and the dominant species differed also among these samples. Second, a large number of unknown genera were detected, especially in the sediment samples, such as unclassified Xanthomonadales incertae sedis, unclassified Anaerolineaceae, and unclassified Alcaligenaceae. Last, TP, TN, and TOC were the main influential factors that affected the bacterial community structure.
Keywords: estuary    water and sediment    bacterial diversity    bacterial community structure    
1 INTRODUCTION

Pollutants in estuarine waters originate mainly from local river inputs due to human activities. When a river enters a lake, the hydrodynamic effect weakens, and pollutants in the lake may combine with particles through adsorption and sedimentation (Eggleton and Thomas, 2004), causing difference in nutrient distribution between sediment and water of the lake. As an important component of an ecosystem, lakes are rich in microbial resources, of which heterotrophic prokaryotes play a crucial role in the degradation and redistribution of chemical pollutants (Fernández-Luqueño et al., 2011; Liu et al., 2011). Studies on the effects of human activities and environmental conditions on bacterial community structures and organic mineralization have been carried out in lake ecosystems, including eutrophic shallow lakes (Tang et al., 2015), large inland saltwater lakes (Zhang et al., 2016), oligotrophic open oceans (Fuhrman et al., 1993), and cold spring sediments (Mills et al., 2004). These studies helped to uncover the link between bacterial community structure and lake nutrient status and to improve the understanding of bacterial diversity in different environments (Cao et al., 2014).

Chaohu Lake (117°17′–117°52′E, 31°25′–31°43′N) is one of the five largest freshwater lakes of China, total surface area 780 km2 and average depth 2.7 m (Deng et al., 2007). Chaohu Lake plays many roles in water supply, floods control, ecological balance, and economic development (Meng and Ma, 2015). However, as a shallow lake, the lake is very susceptible to human activities. In recent decades, with the quick economic development of surrounding cities and towns, wastewaters from industry and household polluted the lake via rivers, introducing a large volume of organic matter. In general, the increasing pollution load promoted the accumulation of authigenic organic matter and exacerbated the pollution status of lakes (Zan et al., 2012). Indeed, Chaohu Lake now became one of the five most polluted lakes in China. To alleviate the eutrophication of the lake, the local government launched the "Water Diversion Project" in 2012, in which Changjiang (Yangtze) River water is introduced into Chaohu Lake through Zhaohe River to shorten water cycle of the lake and alleviate eutrophication.

At present, most of the research projects on Chaohu Lake focus on heavy metals (Kong et al., 2015), nutrient changes (Liu et al., 2012), eutrophication (Huang et al., 2013), and control strategies (Shang and Shang, 2005). The bacterial community structure of the lake remains poorly understood. A previous study has shown that the bacterial community status is closely related to water quality and that changes in bacterial structure respond well to water pollution load (Zhang et al., 2015). Therefore, understanding the structural characteristics of bacterial communities is the key to study the pollution of Chaohu Lake. Although relationship between bacterial community structure and environmental factors in eutrophic shallow lakes has been widely investigated, studies on the effects of nutrients on the sediment flora structure under continuous seasonal changes are scarce. In this study, we chose Nanfei River and Zhaohe River estuaries as test sites, the water and sediment were sampled in spring, summer, autumn, and winter and analyzed. With rapid development in molecular biology, high-throughput sequencing technology has been widely used in environmental microbiology research (Huber et al., 2007). Compared with traditional monoclonal technology, DGGE (denaturing gradient gel electrophoresis), RFLP (restriction endonuclease fragment length polymorphism), and other approaches, highthroughput sequencing technology has obvious flux advantages and very high resolution, facilitating more comprehensive analysis with more details of the bacterial community structure of a sample.

In this study, 16S rRNA gene sequencing was performed, and the bacterial community structures were analyzed for the sediments of Nanfei River estuary and Zhaohe River estuary. Relationship between metabolic function of bacteria and environmental factors was clarified to reveal the complexity of the lake ecology. The driving force behind the composition of water and sediment bacterial communities was determined for improving water quality and the ecological environment of the lake.

2 MATERIAL AND METHOD 2.1 Sampling sites and sample collection

The Nanfei River is located in the northwest corner of Chaohu Lake, by which many cities and counties situated with dense populations. Thus, the river estuary is the most polluted area of Chaohu Lake. The middle estuary area was selected for the study site (Site N) (Fig. 1). The other site is located in the middle part of the Zhaohe River estuary (Site Z). As an artificial river, Zhaohe River intakes water from Changjiang River as a link between Changjiang River and Chaohu Lake. Four sets (seasonal) of water (NW8, NW11, NW2, and NW5) and sediment (NS8, NS11, NS2, and NS5) were sampled from Nanfei River estuary and four sets of water (ZW8, ZW11, ZW2, and ZW5) and sediment (ZS8, ZS11, ZS2, and ZS5) samples from Zhaohe River estuary. One water sample and one sediment sample were collected at a time in each site. The corresponding sampling times were August (summer) and November (autumn) 2016, and February (winter) and May (spring) 2017. For each site, surface sediment samples (< 5 cm deep) were collected using a 1/16 m2 Petersen grab sampler. Sediments of three separate grabs were homogenized as a composite sample, and three replicate sediments from each site were obtained. An aliquot of each composite sample was stored in a 15-mL sterile centrifuge tube at -80℃ until freeze-drying and subsequent DNA extraction. Water was sampled approximately 50 cm below the surface using a vertical sampler and repeated three times; the samples were collected in plastic bottles pre-washed with deionized water.

Fig.1 Map of the sampling sites in Chaohu Lake, China
2.2 Physicochemical analysis

At each site, pH, water temperature (Temp) and dissolved oxygen (DO) were measured on-site using a multi-parameter water quality analyzer (YSI 6600V2, USA). Chemical analyses, comprising total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC), were performed using standardized methods (Ruban et al., 2001) in triplication with a standard deviation lower than 5%.

2.3 DNA extraction and PCR amplification

Bacterial genomic DNA of the 16 samples was extracted using the Fast DNA Spin Kit for Soil kit (MP Biomedicals, Fountain Pkwy. Solon, OH, USA). The concentration and purity of the genomic DNA were measured with an ultraviolet spectrophotometer (RS232G), and the integrity of the DNA sample was assessed by 0.8% agarose gel electrophoresis at a voltage of 120 V and an electrophoresis time of approximately 20 min. The extracted DNA stock wa s diluted to 20 ng/μL and used as a PCR template for sequencing of the highly variable V4 region of the bacterial 16S rRNA gene of approximately 400 bp in length. A universal primer for the V4 region was used (515F GTGCCAGCMGCCGCGGTAA/907R CCGTCAATTCMTTTRAGTTT) (Lane, 1991; Caporaso et al., 2011). The program was as follows: re-denaturation at 94℃ for 5 min, denaturation at 50℃; annealing at 94℃ for 30 s, 50℃ for 30 s, and 72℃ for 1 min for 27 cycles; 72℃ for 5 min; hold at 4℃. The product was purified using AXYGEN's gel recovery kit. The PCR amplification product was subjected to fluorescence quantification according to the preliminary quantitative results of electrophoresis with a Quant-iT PicoGreen dsDNA Assay Kit (Life Technologies cat, P11496) and a microplate reader (BioTek, FLx800). Based on the results, each sample was then mixed according to the amount of sequencing required and sent to Shanghai Personal Biotechnology Co., Ltd. for Illumina MiSeq high-throughput sequencing.

2.4 Statistical analysis

The alpha-diversity indices (Chao 1 index, Shannon index, Simpson index) of the 16 samples were calculated by software Mothur. Composition analysis was conducted at phylum and class levels. In order to assess the difference of bacterial community composition among samples of different locations (Nanfei River estuary and Zhaohe River estuary) and sample types (water and sediment), analysis of similarities (ANOSIM) was performed based on Bray-Curtis dissimilarity with 9999 permutations using R package "vegan". The NMDS was conducted in R with the vegan package. Bacteria of the dominant phylum and class in each sample were evaluated. To examine relationships between bacterial community structure and environmental parameters, redundancy analysis (RDA) was performed using CANOCO 4.5 software (Ter Braak and Smilauer, 2002).

3 RESULT 3.1 Physicochemical characteristics of samples

Major geographical and physiochemical characteristics of the lake sediments are summarized in Supplementary Table S1. Across the sampling sites, all water samples presented a slightly to moderately alkaline pH (7.68–8.49, average 8.14), and the temperature of the water in summer and winter was approximately 32℃ and 3℃, respectively. The DO content in the water of the Nanfei River estuary and Zhaohe River estuary was highest in winter, at 11.95 mg/L and 11.40 mg/L, respectively. The TN and TP contents in each group showed seasonal changes. The range of TN in the water and sediment samples was 0.79–2.02 mg/L and 1.29– 2.15 g/kg, respectively, and that of TP was 0.06–0.27 mg/L and 0.17–1.56 g/kg, respectively. The TOC content in the sediments ranged 8.62–12.41 g/kg for the Nanfei River estuary and 1.49–3.94 g/kg for the Zhaohe River estuary, respectively; the TOC content in the two estuaries was significantly different (P < 0.05).

3.2 Biodiversity analysis

A total of 298 512 high-quality sequences were available from the 16 samples for subsequent analysis, with random sampling of the sequence for each. Rarefaction curves were constructed using the number of sequences and the number of OTUs between the different samples (Fig. 2). At 97% similarity level, the rarefaction curves of most samples reached saturation. A few samples were not completely saturated but approached the saturation state, indicating that most of the information from the samples was obtained and reflected the structural composition of the bacterial community in the sediment. Diversity indexes (Chao 1 and Shannon) for the sediment samples were significantly higher than those for the water samples (P < 0.05) (Table 1). Among them, ZS2 had the most diverse bacterial population (Shannon=10.61; Chao 1=5 135.74), and there was no significant difference between the two sampling points. The seasonal variation trend for the Chao 1 index was the same among the water samples, and the sediment sample Chao 1 index results exhibited similar seasonal trends. In addition, ANOSIM indicated that abundant bacterial community composition significantly (P < 0.05) differed among the sediments samples in Zhaohe estuary (Supplementary Table S2).

Fig.2 Rarefaction curves of OTUs clustered at 97% sequence identity across 16 samples from the Nanfei River and Zhaohe River estuaries
Table 1 Diversity of bacterial 16S rRNA gene libraries of 16 samples in Chaohu Lake
3.3 Analysis of dominant bacterium in the water and sediment of Chaohu Lake

Figure 3 shows the distribution of dominant bacteria in the samples at phylum level. Proteobacteria (34.02±9.86)%, Actinobacteria (12.86±9.48)%, Cyanobacteria (12.07±20.10)%, Bacteroidetes (9.85±6.29)%, Chloroflexi (4.94±2.98)%, Planctomycetes (4.52±2.57)%, Acidobacteria (3.54±5.07)%, Nitrospirae (3.15±2.99)%, Verrucomicrobia (1.31±1.17)%, and Gemmatimonadetes (1.17±0.98)% were common dominant bacteria in water and sediment samples. Chlorobi (1.81±1.78)%, Firmicutes (0.15±0.20)%, and Microgenomates (0.05±0.12)% were dominant bacteria in water samples only, whereas Euryarchaeota (3.33±1.73)%, Ignavibacteriae (3.20±0.33)%, Latescibacteria (2.51±0.99)%, Nitrospinae (1.25±1.45)%, and Omnitrophica (0.79±1.08)% were dominant in sediment samples only.

Fig.3 Relative abundances of the top 10 phyla or sub-phyla in each sample (a total of 21 phyla or classes for all 16 samples) from the Nanfei River and Zhaohe River estuaries

The bacterial community composition of the water and sediment samples showed similarity at phylum level but significant differences at genus level (Figs. 4 & 5). For example, in the water samples, unclassified Family I (23.32±22.59)% was the most abundant bacterium, followed by hgcI clade (13.88±5.84)%, unclassified LD12 freshwater group (6.12±6.74)%, CL500-29 marine group (3.51±2.54)%, unclassified Comamonadaceae (2.94±3.72)%, unclassified Chloroplast (2.90±6.34)% and Flavobacterium (2.56±4.34)%. Among sediment samples, unclassified Xanthomonadales incertae sedis (7.35±4.12)% was the most abundant bacterium, followed by unclassified Anaerolineaceae (4.61±1.38)%, unclassified Nitrospiraceae (3.92±0.96)%, unclassified 43F-1404R (3.57±2.19)%, unclassified Subgroup_22 (3.34±0.91)%, Subgroup 6 (2.97±2.02)%, and unclassified SC-I-84 (2.85±1.73)%. Overall, the bacterial community of sediment samples displayed higher diversity and uniformity compared to the water samples.

Fig.4 Relative abundances of the top 20 genera in water samples (a total of 48 genera or unclassified genus) from the Nanfei River and Zhaohe River estuaries
Fig.5 Relative abundances of the top 20 genera in sedimentary samples (a total of 38 genera or unclassified genus) from the Nanfei River and Zhaohe River estuaries
3.4 Factors influencing the bacterial communities

Bacterial abundance, community succession, and functional activity respond quickly to changes in nutrient salts, hydrology, and other environmental factors in lakes (Paerl et al., 2003; Shade et al., 2011). RDA analysis was used to determine the effects of environmental factors on bacterial community structure, and the physicochemical parameters that significantly affect the bacterial community were selected using the forward selection method in CANOCO 4.5 (Ter Braak and Smilauer, 2002). Figure 6 illustrates the relationship between bacterium and environmental factors in the water. Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, Bacteroidetes, Chloroflexi, Acidobacteria, and Actinobacteria were correlated positively with TN and T and negatively with TP and DO; Cyanobacteria and Microgenomates showed the opposite trends. Alphaproteobacteria correlated positively with TP and TN and negatively with DO. Relationship between bacterium and environmental factors in sediments is presented in Fig. 7. As shown, the relative abundances of Betaproteobacteria, Alphaproteobacteria, Deltaproteobacteria, Actinobacteria, Cyanobacteria, Latescibacteria, and Verrucomicrobia were correlated negatively with TP, TN, and TOC, but Acidobacteria, Gammaproteobacteria, Euryarchaeota and Omnitrophica were correlated positively with TP, TN, and TOC. These results suggest that environmental factors have different positive or negative implications for the distributions of these bacteria.

Fig.6 Water analysis (RDA) of bacterial communities and correlation between relative abundances of major bacterium and main water parameters
Fig.7 Sediment analysis (RDA) of bacterial communities and correlation between relative abundances of major bacterium and main sediment parameters
4 DISCUSSION

Nanfei River and Zhaohe River estuaries are representative areas for studying the bacterial community structure of the water and sediment in Chaohu Lake. Our data show temporal and spatial differences between physical and chemical indicators for the water and sediment samples (Supplementary Table S1), which results from the combination of hydrodynamic disturbance, molecular diffusion, and bioturbation. Phosphorus (Sun et al., 2010) and other contaminants (Yu et al., 2014) are converted to inorganic substances by mineralization and degradation via the activities of microorganisms and are released into the lake by pore water under certain conditions. Overall, the nitrogen and phosphorus contents in the water at the sampling sites increased. The TP, TN, and TOC contents in the sediments of Nanfei River estuary were significantly higher than those of Zhaohe River estuary. Among them, the seasonal variation of TP content in Nanfei River estuary was 0.97–1.56 g/kg, and the seasonal variation in Zhaohe River estuary was 0.17–0.41 g/kg. The TP content displayed a significant decreasing trend from west to east in Chaohu Lake sediment (Ding et al., 2014) along with the development of agricultural and phosphorus deposits around the lake area. Continuous mining may be the main reason for the high TP in the western region of the lake (Zan et al., 2011).

Species diversity is a prerequisite for maintaining the normal function of ecosystems. The richness and diversity of bacterial communities play an important role in nutrient salt cycling, organic matter degradation, heavy metal transformation, and greenhouse gas emissions in lake ecosystems (Ansola et al., 2014). NMDS (Supplementary Fig.S1) show that most of the water samples and sediment samples have similar bacterial community composition in the same season at the same sampling point. For example, NS5 and NW5, ZS8 and ZW8, ZS5 and ZW5 have similar bacterial community composition. Similar temperature conditions may be the main reason for the similar composition of bacterial communities in water and sediments, and the interaction of water and sediments creates similar nutrient conditions for bacterial communities. Previous studies have also shown that nutrients (Xing and Kong, 2007) and temperature (Deng et al., 2007) have an important influence on the composition of bacterial communities. In this study, the Chao 1 index and Shannon index values of the sediment samples were higher than those of the water samples, likely because there are much higher levels of nutrients in sediments than in water, providing a suitable breeding environment for the growth and reproduction of bacteria and promoting the growth of a variety of bacteria, which in turn leads to a more complex bacterial community structure (Bai et al., 2012). In addition, because the sampling points were located in estuaries, there is a certain fluidity to the water flow. Removing a large number of planktonic bacteria during the process of water body renewal may reduce the diversity of the bacterial community of the water sample.

Changes in bacterial community composition are one of the most sensitive indicators reflecting lake eutrophication; thus, understanding the composition of bacterial communities facilitates a better understanding of the metabolic processes of aquatic ecosystems (Dillon et al., 2009). In this study, the temporal distribution of most bacterial communities in sediment samples varied widely (P < 0.05). Among 16 samples, Proteobacteria was the most advantageous bacteria in all samples. Most Proteobacteria have a strong ability to decompose different materials and can be widely used to metabolize various types of organic matter (Xue et al., 2018), thus playing a vital role in the nutrient cycle of lakes. As depicted in Fig. 3, seasonal variation in the relative abundance of Betaproteobacteria (13.61±4.21)% was minimal, and this phylum was dominant in both water and sediment samples. However, the advantage of this bacterium in the sediment samples was more evident than in the water samples, indicating that Betaproteobacteria can adapt well in different environments and resist temperature fluctuations (Newton et al., 2011). Betaproteobacteria serve as decomposers of complex organisms to produce nutrients such as ammonia and methane (Dang et al., 2010), which is consistent with the positive correlation between Betaproteobacteria and TN in RDA. As the Nanfei River estuary has a high TN content, a sufficient amount of nutrients may be the main reason for the dominance of this phylum in the estuary (Kielak et al., 2016). In this study, a large number of Alcaligenaceae (2.45±1.15)% belonging to Betaproteobacteria were found in sediments, species that are widely distributed in various habitats, from animals and humans to soil, sewage and sludge (Dam et al., 2009). The metabolic patterns of Alcaligenaceae are also diverse (Ghosh et al., 2005), and studies have shown that this family carries a large complement of plasmids (Riccio et al., 2001) that contain genes involved in biodegradation conferring Alcaligenaceae with functional features related to biodegradation and biogeochemistry (Wyndham et al., 1988).

Gammaproteobacteria (8.12±5.59)% and Deltaproteobacteria (6.24±5.97)% were also dominant among Proteobacteria, with higher relative abundance in sediment samples than in water samples. Gammaproteobacteria can participate in the decomposition of various organic carbons and organic phosphorus (Čanković et al., 2017). Unclassified Xanthomonadales incertae sedis, a member of Gammaproteobacteria with the ability to degrade aromatics (Xiao and Ni, 2013), also showed high relative abundance in this study. Overall, analysis of this taxon will help to mitigate the pollution of Chaohu Lake and maintain ecological balance. The study of the bacteria contributes to the removal of pollution and the maintenance of the ecological balance in Chaohu Lake. Deltaproteobacteria includes basic aerobic slime bacteria and some obligate anaerobic species, which degrade organic matter in the sediment via the oxidation and reduction of sulfur compounds (Čanković et al., 2017). In this study, unclassified Anaeromyxobacter (0.37±0.41)% was one of the important members of Deltaproteobacteria, which was only found in Nanfei River estuary. Subclass Anaeromyxobacter can utilize a variety of electron acceptors, including heavy metals complexed as nitrates, ferric iron, and manganese oxide (Thomas et al., 2009). Due to the dependence of Anaeromyxobacter on heavy metals and nitrates, observing the distribution of these species can help to elucidate the distribution and migration of pollutants in Chaohu Lake. In addition, Geothermobacter, an iron-reducing bacterium, was enriched (0.71±0.59)% in the sediment of Nanfei River estuary. Under anaerobic conditions, Geothermobacter can utilize acetic acid, formic acid, and succinic acid. As an electron donor, Fe3+ acts as a terminal electron acceptor, reducing various toxic heavy metals, degrading and consuming organic and inorganic contaminants and eventually reducing Fe3+ to Fe2+ (Lovley et al., 2011). The relative abundance of Geothermobacter in Nanfei River estuary was much higher than that in Zhaohe River estuary, indicating that sediments in Nanfei River estuary may contain higher concentrations of heavy metals and organic acids.

Alphaproteobacteria is a major group in highsalinity environments, but the relative abundance of Alphaproteobacteria (10.96±7.61)% in our water samples was high. RDA showed that Alphaproteobacteria correlated positively with TN and TP in water, which is consistent with the degradation of complex aromatic compounds and the anaerobic oxidation of ammonium and nitrite (Kaluzhnaya et al., 2011). The anthropogenic emissions of organic pollutants around the river are the main factors that promote the enrichment of Alphaproteobacteria in the Nanfei River estuary. In this study, the LD12 freshwater clade was the most abundant bacterium of Alphaproteobacteria. It has been reported that LD12 is the main genus in marine and freshwater systems (Henson et al., 2018), and the presence of this taxon in a freshwater system (Logares et al., 2010; Eiler et al., 2014) indicates changes in its ecological development. It has successfully adapted and migrated from the saltwater environment to the freshwater environment.

Bacteroidetes generally have the ability to settle and decompose hydrocarbons (Kasai et al., 2001) and are widely found in eutrophic lake waters (Tang et al., 2015) and sediments (Newton and McMahon, 2011). In our study, RDA showed that Bacteroidetes correlated positively with TOC, which is consistent with the functional characteristics of these bacteria. Studies have also shown that a large number of Bacteroidetes are often present in oil-contaminated environments, which may be due to their ability to secrete polysaccharide mucus, facilitating movement on smooth surfaces (Gao et al., 2014). Compared with the water samples in Zhaohe River in the lake area, the relative abundance of Bacteroidetes in Nanfei River estuary was higher (Fig. 3), indicating that there may be a more severe condition of hydrocarbon pollution in Nanfei River estuary. Many branches of the Bacteroidetes family were identified, among which the relative abundance of Flavobacterium at NW2 (6.17%) and NW5 (12.01%) was significantly higher than at other sites. Studies have shown that Flavobacterium is a common aerobic denitrifying bacterium with heterotrophic nitrification and the ability to metabolize refractory organics under conditions of sufficient dissolved oxygen (Zhou et al., 2007). Proper temperature, adequate dissolved oxygen and abundant nutrients may be the main reason for the predominance of Flavobacterium at NW2 and NW5. In addition, a large number of Bacteroidetes members with a relative abundance of less than 2% were found in the sediment, such as unclassified Bacteroidetes_vadinHA17 (0.35±0.50)%, unclassified Lentimicrobiaceae (1.82±0.66)%, unclassified Cytophagaceae (1.45±1.28)% and unclassified Saprospiraceae (0.38±0.59)%.

Currently, few Chloroflexi lineages been cultured and identified, and the specific functions of Chloroflexi within the context of ecosystems remain unknown. Nonetheless, studies have shown that the bacterium of this genus are widely distributed (Edmonds-Wilson et al., 2015), with a variety of metabolic types, including anaerobic phototrophs, anoxygenic phototrophs, obligate anaerobic heterotrophs, and anaerobic halorespirers. Chloroflexi can even exhibit a prey-specific growth response (Yamada and Sekiguchi, 2009). Hug et al. (2013) noted that the presence of Chloroflexi is often associated with uranium-contaminated aquifers. Therefore, the detection of a higher abundance of Chloroflexi in water samples indicates that there may be some uranium pollution in Nanfei River and Zhaohe River estuaries. RDA indicated that the abundance of Chloroflexi correlated negatively with TP (Fig. 6), which is consistent with the findings of Song et al.(2012). In our study, unclassified Anaerolineaceae was the most dominant member of Chloroflexi in sediments, with a relative abundance ranging 3.27%– 7.02%. Other studies on relative abundance have shown that Anaerolineaceae functions in the degradation of long-chain n-alkane species (N5-Z0) and cellular amino acid materials (Lv et al., 2014; Liang et al., 2016), accelerating the degradation of organic carbon compounds and cells in sediments and helping to restore and purify the ecosystem of Chaohu Lake.

The phylum Actinobacteria comprises a wide variety of members found in freshwater environments (Parveen et al., 2011). Haukka et al. (2006) reported that Actinobacteria prefer to live in a noneutrophic environment. Accordingly, Actinomycetes were not detected in the sediments of the Nanfei River estuary, but the higher relative abundance in other samples confirms that the eutrophication of the Nanfei River estuary is serious. Our data showed hgeI clade and CL500-29 marine group to be representative of Actinobacteria. CL500-29 marine group has a strong capacity for absorbing carbohydrates and nitrogenrich compounds and well tolerates low-DO environments (Lindh et al., 2015); hgeI clade has similar characteristics (Ghylin et al., 2014). Among them, the relative abundance of CL500-29 marine group in Nanfei River estuary and Zhaohe River estuary was highest in summer, which may be caused by the synergy of low DO, high T and TN and some unknown driving factors.

Cyanobacteria (23.86±23.40)% species are mainly distributed in water samples; they are more common in eutrophic alkaline waters with higher nitrogen and phosphorus contents and can be used as an indicator of the eutrophication of water bodies (Chen et al., 2013). Monitoring Cyanobacteria can provide a theoretical basis for the control of algal blooms in Chaohu Lake and create conditions for the restoration of the water ecosystem of this lake (Zhao et al., 2002). In RDA, TP and DO showed a positive correlation with Cyanobacteria; thus, increases in TP and DO concentrations in a certain range have a positive regulatory effect on the relative abundance of Cyanobacteria. Cyanobacterial blooms usually occur in summer and rarely occur under 15℃ (Whitton and Potts, 2007). Surprisingly, the relative abundance of Cyanobacteria in Zhaohe River estuary was over 57% in both autumn and winter, which indicates that in addition to temperature factors, other environmental factors in Chaohu Lake play a major role in regulating the distribution of this phylum. Among Cyanobacteria phylum, unclassified Family I and Microcystis (2.55±3.07)% were the most dominant at the two test points. The latter comprises a group of non-nitrogenfixing bacteria that degrade organic compounds such as nitrogen and phosphorus (Nalewajko and Murphy, 2001). In this study, the relative abundance of Microcystis varied seasonally, indicating that temperature is an important factor affecting the distribution of these bacteria (Robarts and Zohary, 1987). Spatially, the relative abundance of Microcystis in Nanfei River estuary was higher than that in Zhaohe River estuary, which may be due to the higher contents of nitrogen and phosphorus compounds in the former, which provides sufficient nutrition for the growth and reproduction of Microcystis.

Acidobacteria, Euryarchaeota, and Ignavibacteriae also decompose organic carbon (Mehta and Baross, 2006; Podosokorskaya et al., 2013), and Omnitrophica (tentatively classified as OP3) and Latescibacteria (tentatively classified as WS3) are magnetotactic bacteria capable of synthesizing magnetite (Fe3O4) from cells or pyrite (Fe3S4) crystal particles (Lin and Pan, 2015). In addition, Nitrospirae and Planctomycetes (Schneider et al., 2013) can to some extent decompose nitrogen-containing compounds in sediments. The fact that the organic matter content in sediments is much higher than that in water shall be the main reason why these bacteria are concentrated in sediments.

5 CONCLUSION

Chaohu Lake is a large shallow, eutrophic freshwater lake in China. Due to historical reasons and human activities, Chaohu Lake water pollution has become increasingly serious. In this study, 16S rRNA high-throughput sequencing technology was used to investigate the bacterial community structure of water and sediments in Nanfei River estuary and Zhaohe River estuary, providing a theoretical basis for the treatment of eutrophic water in Chaohu Lake. In this study, the physical and chemical indicators of TN, TOC, TP, and other parameters were significantly higher in Nanfei River estuary than in Zhaohe River estuary. Moreover, the discharge of sewage around Nanfei River and the mining of phosphate rock have increased the pollution of the lake area. The water of Changjiang River was introduced into Chaohu Lake via Zhaohe River. Compared with Nanfei River estuary, the water source of Zhaohe River estuary is cleaner. Our data show that Betaproteobacteria is a unique bacterial community with stable distribution in every sample. Overall, the observed changes in the water and sediment bacterial community have spatial specificity and seasonal characteristics. The bacterial community structure of Nanfei River estuary and Zhaohe River estuary differed greatly at the genus level, and the nutritional status may be a key force driving the lake and sediment bacterial communities. In addition, a large number of unidentifiable genera were found in the study, indicating that the bacterial community in Chaohu Lake sediments is very diverse.

6 DATA AVAILABILITY STATEMENT

All sequence data were deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive with accession No. SRP217654.

7 ACKNOWLEDGMENT

Anonymous reviewers are acknowledged for their constructive comments and helpful suggestions.

8 CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest.

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