Introduction

The environment of the lake–river ecotone is influenced by human activities, natural disaster, biogeochemical cycles and interaction between Lake and Rivers. Launched by IGBP/IHDP/WCRP (World Climate Research Programme)/DIVERSITAS (Integrating biodiversity science for human well-being), the global water system project (GWSP) has paid attention to the ecological environment problems in lake–river ecotone. Compared with the adjacent river ecological system or lake ecosystems, the boundary ecosystems may have a unique blend of characteristics and ecological communities (Patrick 2014), it is a more important water purification zone and buffer zone of pollution, for its abundant species diversity, high primary productivity and secondary production, leading to a special place for the energy and material flow, the transitional zone have special characteristics that must be taken into account for conservation of biodiversity (Valdovinos et al. 2012). The microorganisms play an extremely important role in the energy conversion, material recycling, nutrients and element speciation transformation, accumulation and migration. So far, some micro-ecological in the River and Lake ecotone is still unknown because of the limits of the traditional technology. Due to the rapid development of molecular biology technology which is based on the system of 16S rRNA gene (Pace et al. 1986; Winter et al. 2007), it is feasible to analyze microbial community comprehensively in different habitats (Venter et al. 2004; Lai et al. 2006; Agogue et al. 2005). Compared with the ordinary sequencing, the next-generation sequencing technology has the advantage of high flux, short test period, and is low-cost and repeatable (Mardis 2008; Ansorge 2009) and has been widely used in all kinds of environments, such as soil (Woo et al. 2014; Hansel et al. 2008), ocean (Nakajima et al. 2014), hot spring (Egas et al. 2014), lakes and rivers (Pascault et al. 2014; Liu et al. 2011), it promotes the study of uncultured microorganisms and trace amount bacteria in the environment, opening up a new research upsurge for the study of environmental microbial diversity. This study aimed to identify the microbial diversity in different lake–river ecotone, and to explore the evolution and adaptation of the microbial population to changing environmental conditions. This is the first report of the variation of microbial communities in pristine habitats of lake–river ecotone from China. Based on the analysis of the characteristics of the microbial distribution, this work is helpful to enhance understanding between microbes’ population and environmental variations, and provide scientific basis for water environment protection and water ecological security.

Materials and methods

Study area

Poyang Lake is China’s largest freshwater Lake, located at 28º 22′ N to 29º 45′ N, 115º 47′ E to 116º 45′ E, on the southern bank of the middle and lower reaches of the Yangtze River in the northern Jiangxi Province. Poyang Lake swallows a large quantity of water coming from five tributaries, including Xiushui River, Ganjiang River, Fu River, Xinjiang River and Raohe River. Due to the unique hydrological regime and special geographical conditions, the water level of Poyang Lake is controlled by both its tributaries and the Yangtze River and has a great seasonal variation (Wang et al. 2015a, b), producing wetlands over 3000 km2. Poyang Lake wetland is famous for its abundant biodiversity and has been registered in the UN as one of the world’s important wetlands since 1992. Previous studies observed the microbial diversity in traditional Lakes and Rivers, found a significant difference in microbial diversity from northern to southern Poyang Lake (Wu et al. 2012), and more, examined the differences in microbial diversity at different seasons and locations across the Three Gorges Dam of the Yangtze River (Wang et al. 2012a, b), other studies compared the levels of bacterial diversity in freshwater, Intertidal wetland, and marine sediments (Wang et al. 2012a, b), it could provide the basis and reference for microbial diversity in lake–river ecotone. This study takes the lake–river ecotone of Poyang Lake as a case, sets the sampling sites in Poyang Lake and Raohe River ecotone (hxl3 and hxl1), Yao Lake and the Ganjiang River ecotone (hu1 and he2) (Fig. 1), the former is mainly affected by the agricultural activities (Zhang et al. 2015), the latter is connected with Poyang Lake but relatively independent and located at the edge of the city, mainly affected by domestic waste. Sampling sites are located in the Poyang Lake wetland, its surrounding Rivers merge in the Poyang Lake, which is multi-resources lacustrine sediment.

Fig. 1
figure 1

Water sampling sites in lake–river ecotone (hxl3 Poyang Lake, hxl1 Raohe River, hu1 Yao Lake, he2 Ganjiang River, three sampling points are set up for each)

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Sample analysis

Bacterial genomic DNA was extracted from the water samples of Yao Lake, Ganjiang River, Raohe River and Poyang Lake, respectively. The molecular weight of genomic DNA extracted from these water samples was approximately 23 kb (Zhang et al. 2012), which was in agreement with the expected value (Huang et al. 2013).

The TN concentrations were determined using an alkaline potassium persulfate digestion-UV spectrophotometric method at 275 and 220 nm with 1-cm light path cuvette (Yang et al. 2015). Determination of total phosphorus was done using ammonium molybdate spectrophotometric method (GB 11893-89).

Next-generation sequencing

The DNA was sequenced through the Illumina platform (Miseq) for paired-end sequencing (Mao et al. 2013), and the low-quality reads were removed under the machine data. The statistical data are shown in Table 1.

Table 1 Sample sequencing data statistics
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In order to obtain high-quality tags, the splicing tags sequence was processed. After processing all the samples, a total of 1142790 high-quality tags were obtained, and the average sample was 285697 ± 41785. At the 0.97 level of clustering similarity for species classification of operational taxonomic units (OTU), a total of 8657 OTU were obtained for the 4 samples. The Singletons OTU (i.e., abundance was 1 OTU) number was 3155, and the non-Singletons OTU number was 5502. Singletons OTU may be caused by sequencing errors, which was ignored and not included in the later analysis. Statistical results of sample OTU are in Table 2.

Table 2 Sample OTU statistics
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Results and discussion

Analysis of OTU Venn diagram

The Venn diagram, a visual display of overlap between OTU samples, was used to display a plurality of samples and their unique OTU number, which was obtained in 0.97 of the similarity of each sample, by the OTU, which represents species, we can find out the core of microorganisms in different environments (Fig. 2).

Fig. 2
figure 2

Venn diagram (different color graphics represent different groups among a plurality of color graphics overlapping part number represents the number of OTU between multiple groups have similarity)

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Different color graphics represent different samples or different groups. The overlapping part of different color graphics represents the common OTU number between two samples or two groups. Similarly, among a plurality of color graphics overlapping part number represents the number of OTU between multiple samples or groups have similarity. From the OTU Venn chart analysis, the OTU number of 205 is shared by Ganjiang River, Yao Lake, Raohe River and Poyang Lake samplers. The common OTU number of Ganjiang River and Yao Lake is 640, and the common OTU number from Poyang Lake and Raohe River is 339. The number of unique OTU from Ganjiang River is 601, making up 10.92 % of the total OUT, the number of unique OTU from Yao Lake is 782, making up 14.21 percent of the total OUT, the number of unique OTU from Raohe River is 433, making up 7.87 % of the total OUT, and the number of unique OTU from Poyang Lake is 2477, making up 45.01 percent of the total OUT. Out of all of these water samples, Poyang Lake had the largest number of unique microbial population, followed by Yao Lake and Ganjiang River orderly, and Raohe River had the least.

Comparison of the sequences similarity, we took more than 97 % cloned sequence similarity to the same operational taxonomic unit (OTU), the microbial diversity index were analyzed with MOTHUR in microbial communities from the four samples.

Diversity indices analyses

Alpha diversity including Observed species index, Chao index, Shannon index and Simpson index, etc., we calculated Alpha diversity value by mothur (v1.31.2) software, and made the corresponding dilution curve by R (v2.15.3) software.

Observed species index and Chao index reflect the species richness in a sample, representing the number of species in a community, not the abundance of each species in the community. Dilution curves can reflect the adequacy of sample sequencing. If the curve tends to be flattening, the sequencing depth has been basically covered by all species in sample. Figure 3a, b shows that the number of sequencing had covered all species in sampling sites.

Fig. 3
figure 3

The richness/diversity estimators from samples (hxl3 Poyang Lake, hxl: Raohe River, hu1 Yao Lake, he2 Ganjiang River)

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Greater Shannon value represents higher community diversity, while greater Simpson index value represents lower community diversity (Fig. 3c, d). When species richness is the same, community with greater species evenness has more diversity. Results showed that the microbial community diversity was abundant in Poyang Lake, followed successively by the Ganjiang River, the Yao Lake, and the Raohe River.

The microbial diversity and community composition are varying with the surrounding environment. The microbial communities were compared by phylogenetic information, and obvious evolutionary differences exist between Poyang Lake water samples and the other samples. Due to the effect of Yangtze River and five Rivers (Ganjiang River, Fu River, Xinjiang River, Raohe River, Xiushui River), microbial resources in Poyang Lake is rich and diverse.

Microbial variation with the environment

The dominant population in samplers is defined as that account for more than 5 % (Huang et al. 2012) of the total number of similar microbial sequencing (Table 3).

Table 3 Abundance of microorganisms in each sampling point (Tags number)
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Quantitative and qualitative analysis shows that, the most abundant microbial populations is Proteobacteria, followed by Bacteroidetes, then Actinobacteria, Acidobacteria, Verrucomicrobia, Firmicutes, Planctomycetes, etc. From the Table 3, Planctomycetes in Yao Lake and the Ganjiang River ecotone are more abundant compared to Raohe River ecotone, some bacteria from Planctomycetes could use nitrite under hypoxia (NO2 −) oxidation of ammonium ion (NH4 +) generated nitrogen to obtain energy, It has the vital significance to the global nitrogen cycle, and also important in wastewater treatment (Meckenstock et al. 2002). A number of 2974 Crenarchaeota was detected from Poyang Lake, and a little Crenarchaeota in Raohe River. America scholars (Könneke et al. 2005) successfully isolated a strain of Crenarchaeota Nitrosopumilus maritimus from the sea for the first time in 2005, which contained ammonia oxidation that had Archaea ammonia monooxygenase (amoA) genes. It can oxidize ammonia nitrogen to obtain the energy assimilation of inorganic carbon growth. Nitrospira were relatively rich in Poyang Lake, it has an effect on nitrification and nitrite oxidation (Wang et al. 2014), and mainly distributed in the environment that is affected by human activities. The Chlamydiae was found in Ganjiang River water flowing through the Nanchang City, which is a kind of special bacteria that can only survive in the cytoplasm, and mainly includes two kinds of bacteria, Chlamydia trachomatis and Chlamydia psittaci. C. trachomatis usually only infects humans, while Chlamydia psittaci can infect many kinds of animal and birds, and lead to respiratory diseases, abortion, and arthritis. Archaea in Yao Lake were rare, and Fusobacteria was most abundant in the Ganjiang River water. Studies (Kostic et al. 2013; Rubinstein et al. 2013) have found out that Fusobacterium is unusually active in colon cancer cells, and seems to coexist with tumor malignant degree. On the whole, microbial components in different geographic space were both related and varied with different environments.

Due to the changes of the surrounding environment (Wang et al. 2015a, b; Xiang et al. 2015), the microbial diversity and community composition also show constantly collaborative response. Raohe River was mainly affected by the agricultural activities and copper/phosphorite mines, etc., which could cause the high-concentration value of TP that occurred in the river mouth area of Poyang Lake (Table 4), and the PAO (such as Pseudomonas, Acinetobacter) were richer than Ganjiang River. Yao Lake and Ganjiang River were mainly affected by the city residents living pollution, as a result of population increase, the amount of TN discharged into the Ganjiang River and Yao Lake have increased in recent years (Yang et al. 2015), which caused a richness of nitrifying bacteria (Table 4). Affected by domestic sewage and industrial activities of the city, Chlamydiae and Fusobacteria in Ganjiang River are more abundant compared to other samples. Poyang Lake is the confluence of these flowing, by both the Yangtze River and five River, Poyang Lake has more frequent substance and energy exchange, more hydrostatic and stream habitat interaction, so that Poyang Lake has rich microbial resources. Poyang Lake is an enormous gene pool, including a large number of DNA sequences of ammonia oxidizing bacteria and ammonia oxidizing archaea. Research data show that it is possible to isolate functional microbes from Poyang Lake, which play an important role in nitrogen cycle of the earth.

Table 4 TN, TP and some responsive microorganisms
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