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Article

Structural Diversity of Bacterial Communities and Its Relation to Environmental Factors in the Surface Sediments from Main Stream of Qingshui River

by
Zengfeng Zhao
1,
Ruizhi Zhao
1,
Xiaocong Qiu
2,*,
Yongpeng Wan
1 and
Lin Lee
1
1
School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan 750021, China
2
School of Life Science, Ningxia University, Yinchuan 750021, China
*
Author to whom correspondence should be addressed.
Water 2022, 14(21), 3356; https://doi.org/10.3390/w14213356
Submission received: 1 September 2022 / Revised: 15 October 2022 / Accepted: 20 October 2022 / Published: 22 October 2022
(This article belongs to the Section Biodiversity and Functionality of Aquatic Ecosystems)
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Abstract

:
This paper aims to preliminarily understand the structure and diversity of the bacterial community in the sediments of the Qingshui River, and analyze the differences of dominant bacteria in different river reaches, and identify the influence degree of environmental factors. In this study, surface sediments of the main stream of the Qingshui River were selected to analyze both bacterial community composition and a diversity index using the high-throughput sequencing analysis of bacterial 16S rDNA, further exploring their relationships with environmental factors. Results showed that 16,855 OTUs in the surface sediments belonged to 66 phyla, 164 classes, 274 orders, 317 families, and 501 genera of bacteria, while carbon/nitrogen-fixing bacteria were dominant at the class and genus level. There was a significant (p < 0.05) spatial difference between bacterial species composition and the diversity index in surface sediments. Proteobacteria was the most abundant phylum in the sediments of the main stream of the Qingshui River, with an average abundance of 48.15%, followed by Bacteroidetes (21.74%) and Firmicutes (5.71%). The abundance of Alphaproteobacteria in Proteobacteria was the highest (15.38%) and followed by Flavobacteriia in Bacteroidetes (11.57%). The most dominant bacteria genera were different at different areas. The most dominant genera were Phyllobacterium in Kaicheng, Qiying, Liwang, Tongxin and Changshantou, with relative abundances of 4.27%, 4.67%, 5.88%, 4.15% and 6.22%, respectively. Flavobacterium was the most dominant genus in both Dongjiao and Sanying, with a relative abundance of 5.03% and 5.84%, respectively. Rhodobacter was the most dominant genus in Hexi, with a relative abundance of 8.29%. Gillisia was the most dominant genus in Quanyanshan, with a relative abundance of 5.51%. Pearson correlation analysis further indicated that NH4+, pH, and Cr were the main factors affecting the bacterial community structure and diversity in surface sediments. Therefore, our findings suggest that both nutrient elements (i.e., N) and toxic heavy metalloids affect the abundance and diversity of bacteria in surface sediments from the main stream of the Qingshui River. Areas of the river sampled in this study provide the biggest microbial sampling coverage to date. The results provide a preliminary understanding of bacterial communities in sediments of different reaches of the Qingshui River, and provide a reference for further research on the application of functional bacteria in pollution control of the Qingshui River.

1. Introduction

Sediments, an important part of river ecosystems, are the “sinks” of land-based pollutants in the river basin, and also the “source” and “sinks” of river water pollution [1,2,3]. River microbes (including bacteria, fungi and archaea) play an important role in nutrient transformation and cycles in river sediments, formation and decomposition of organic matter, and circulation and energy flow in rivers, as well as various other ecological processes [4,5]. River micro-organisms are rich in species, diverse in function and sensitive to environmental changes [6,7]. They are important indicator organisms of environmental changes, and play an important role in river water environment self-purification and water ecology self-repair [6,7]. The community structure and succession process of river microorganisms affect the migration and transformation of pollutants in rivers [8], reflecting the extent to which the river ecosystem is subject to external disturbances. Therefore, river microbial information can be used to assess the health of river ecosystems, analyze the causes of degradation, and trace the sources of pollution [9,10].
Bacteria are one of the most abundant and widely distributed microbial domains in rivers, and play a major role in the processes of biogeochemical cycles in river ecosystems [11,12]. At present, research on river bacteria mainly focuses on both spatial distribution and influencing factors of bacteria in water body and sediments. These findings generally suggest that the Proteobacteria and Firmicutes are the dominant phyla in the water body and sediments, while the time, flow and environmental factors are all important factors affecting the structure and diversity of bacterial communities [13,14,15]. For example, Proteobacteria and Firmicutes are the dominant bacterial phyla in the water and sediments of the Ibrahim River in coastal Lebanon, and the bacterial communities are greatly affected by time and hydrological factors [13]. Proteobacteria is the most dominant phylum in the Niyang River sediments, and total nitrogen (TN), total phosphorus (TP), dissolved oxygen (DO), chromium (Cr), strontium (Sr), barium (Ba) and manganese (Mn) are the main factors affecting the microbial community structure in sediments, while time is not the most important factor [14]. The most dominant bacterial phylum in the water body and sediments of the Yellow River was Proteobacteria; here, pH, DO, and dissolved organic carbon (DOC) were the main factors controlling bacterial communities in water bodies in the Yellow River, while pH, nitrate, and moisture content were the main factors affecting the bacterial community of surface sediments; these authors also suggest that suspended granular sediment in the Yellow River has had important effects on bacterial diversity and community structure [15].
The Qingshui River, known as the mother river of the Guyuan people, is located in the southern part of Ningxia. The Qingshui River Basin has a fragile ecological environment and is the area with the most backward economic development and the largest number of poor people in Ningxia [16]. Its water quality status has an important impact on the economic development of the river basin and the quality of the water environment of the Yellow River in the Ningxia section [17]. The water quality of the Qingshui River is basically class V water in the environmental quality standards for surface water (GB 3838-2002) issued by the Ministry of Ecology and Environment, PRC, and the main controlling factors of pollution are TN, biochemical oxygen demand (BOD), chemical oxygen demand (COD), and fluoride (F−) generated by rock weathering [18,19]. In addition, the concentration of Cr in the water exceeds the surface class III water standard (GB 3838-2002), and the Hg content in the sediments exceeds the background value of Ningxia soil [20,21]. The population structure and diversity of phytoplankton and riparian plants in the Qingshui River have also been studied [22,23]. However, there have been few studies on bacteria in the Qingshui River. The Qingshui River Basin has various climate types. The southern part belongs to a warm temperate semi-humid zone, the middle part belongs to a middle temperate semi-arid zone, and the northern part belongs to a middle temperate arid zone [16]. Existing research has focused on the Guyuan section in the south of the Qingshui River and the confluence of the Yellow River in the north [24,25]. The overall understanding of bacteria in the Qingshui River is still lacking. As such, an understanding of the bacterial ecology of different areas within the Qinghshui River is still lacking. This systematic understanding will be helpful in determining the main pollution factors affecting the bacteria in this area and the pollutants degrading bacteria, so as to control the total amount of pollution factors into the river or colonize functional bacteria through manual intervention, and realize the ecological management of the Qingshui River. This will provide a new idea for improving the water quality of the Qingshui River.
Here, we collected the samples from nine areas in the main stream of the Qingshui River, and the bacterial diversity and community composition were analyzed based on the results of 16S rDNA high-throughput sequencing technology. This paper has aimed to have a preliminary understanding of the bacterial community structure and diversity in the sediments of the Qingshui River (headwaters—estuaries), to analyze the differences of bacterial communities in different river reaches, and to evaluate the relationship between the bacterial community composition and the typical environmental factors, so as to provide a reference for further study of pollution control modes in the Qingshui River.

2. Materials and Methods

2.1. Study Area

The Qingshui River originates from Heicigou in Kaicheng Township at the foot of Liupan Mountain, flowing northward through Yuanzhou District to Quanyanshan in Zhongning County, and then joining into the Yellow River (105°00′–107°07′ E and 35°36′–37°37′ N) [20]. It is characterized by 1,448,100 ha of basin area and 320 km of the main stream length. Its source elevation is 2480 m; its estuary elevation is 1192 m; its watercourse average ratio is 1.49‰. Since the Qingshui River Basin is located in the arid northwest inland area to benefit the poorest area of Ningxia, it is of great significance to study the water environment status in its basin for regional ecological protection and economic development.

2.2. Sample Collection and Pretreatment

As shown in Figure 1, nine sampling points were set up in the main stream of the Qingshui River, based on its hydrological laws and tributary distribution, and their name and coordinates are S1 (Kaicheng 106°15′30.96′′ N, 35°51′23.76′′ E), S2 (Dongjiao 106°17′49.92′′ N, 36°3′13.68′′ E), S3 (Sanying 106°9′59.76′′ N, 36°16′24.24′′ E), S4 (Qiying 106°9′59.76′′ N, 36°16′24.24′′ E), S5 (Liwang 106°6′42.84′′ N, 36°39′47.52′′ E), S6 (Tongxin 105°53′47.40′′ N, 36°57′57.60′′ E), S7 (He xi 105°49′27.84′′ N, 37°6′45′′ E), S8 (Changshantou 105°37′4.8′′ N, 37°24′47.16′′ E), and S9 (Quanyanshan 105°32′41.64′′ N, 37°29′4.56 E). In April 2020 (dry season), a grapple sludge collector was used to collect their surface sediments (0–20 cm). These sediment samples were divided into two parts. One was air-dried for the analysis of physico-chemical indicators (air-dried at room temperature), and another part was cryopreserved at −20 °C for high-throughput sequencing of the bacterial 16S rDNA.

2.3. Analysis of Physical-Chemical Properties and Heavy Metals in Sediments

The determination of sediment pH was with a potential method (HJ 962-2018). TN was determined with a modified Kjeldahl method (HJ 717-2014). Potassium chloride solution extraction-spectrophotometry (HJ 634-2012) was used to determine the concentrations of ammonium nitrogen (NH4+), nitrate nitrogen (NO3−), and nitrite nitrogen (NO2−). Total phosphorus (TP) and available phosphorus (AP) were measured by alkali fusion molybdenum antimony anti-spectrophotometry (HJ 632-2011) and sodium bicarbonate leaching molybdenum antimony anti-spectrophotometry (HJ 704-2014), respectively. The concentrations of arsenic (As), Cr, Hg, and plumbum (Pb) were determined by inductively coupled plasma mass spectrometry (ICP-MS), as described with the previous method [21].

2.4. 16S rDNA High-Throughput Sequencing

Sediment samples from the Qingshui River were sequenced by China’s Beijing Biomarker Biotechnology Co., Ltd. The total bacterial DNA in the sediment was extracted with the FastDNA® Spin Kit for soil DNA (Mpbio, Irvine, CA USA), and the concentration, purity and integrity of the extracted DNA were evaluated with NanoDrop (ThermoFisher, Waltham, MA, USA) and 1% agarose gel electrophoresis [26]. Detection, the OD (260/280) value was between 1.8 and 2.0, and the DNA sample concentration was greater than 50ng.L−1 for PCR amplification. Amplification of the target V3–V4 region of 16S rRNA (target fragment: about 459 bp), PCR amplification primer sequences were: V3F (5′-CCTACGGGNGGCWGCAG-3′) and V4R (5′-GGACTACHVGGGTWTCTAAT-3′), PCR reaction of the system was: 30 μL system, including 100 ng template DNA, 15 μL 2 × EasyTaq® PCRSuperMix, 10 μmol·L−1 × 2 forward/reverse primers and 5 μL ddH2O, 3 parallel samples for each sample; PCR amplification was completed with Veriti96 PCR instrument (ABI, Los Angeles, CA, USA), and the amplification conditions were: pre-denaturation at 95 °C for 2 min; PCR cycles were 30 times, followed by denaturation at 95 °C for 20 s, annealing at 51 °C for 30 s, and extension at 72 °C for 60 s; the final extension was at 72 °C for 5 min. The PCR products were purified with a QIAquick PCR Purification Kit (QIAGEN, Hilden, Germany) for subsequent sequencing. The TruSeq® DNA Sample Preparation library preparation kit plus adapters and corresponding barcodes were used to construct a library for the 16S rRNA gene sequencing. The constructed sequencing library was used for sequencing experiments using the Illumina HiSeq 2500 sequencing platform. The sequencing protocol was 2 × 250 bp sequencing at both ends, and the Mothur software platform was used for raw data quality filtering, noise reduction, dechimera removal, and non-uniformity removal [14,27]. Quality control operations included bacterial sequencing. The clean reads of unified sequencing depth were submitted to the QIIME 1.9.1 platform for annotation of microbial species taxonomic information based on operational taxonomic units (OTUs), and the similarity parameter was set to 0.97. Annotation of species’ taxonomic information from the phylum level to the genus level was performed by comparing with the Greengenes database “http://greengenes.secondgenome.com (accessed on 5 June, 2020)” using the algorithm of the RDP Classifier.

2.5. Data Processing and Statistical Analysis

SPSS25 software was used for descriptive statistics and correlation analysis of physico-chemical factors, heavy metals and microbial community diversity. Before the correlation analysis, the Kolmogorov–Smirnov normal distribution test was used to determine whether each environment variable conformed to the normal distribution. The results showed that most environment variables were normally distributed (p > 0.05), so the Pearson correlation analysis was selected. The bacterial abundance bar chart, spatial distribution of environmental factors, and Pearson correlation coefficient chart were plotted using Origin2021.
The indexes of ACE, Chao1, and Observed Species were used to characterize species abundance, while their higher value indicated the higher microbial community. The Shannon index, one of the microbial diversity indexes, being combined with the Simpson Diversity Index, are generally used to reflect the Alpha Diversity Index. The larger the Shannon value presented, the higher the community diversity. The larger the Simpson exponential value indicated, the lower the community diversity.

3. Results

3.1. Physico-Chemical Properties and Heavy Metal Content

The physico-chemical properties and heavy metal content in surface sediments is shown in Figure 2. Heavy metals and environmental parameters content are pH (8.75 ± 0.106), TN (336 ± 174mg·kg−1), NH4+ (39.1 ± 16.3mg·kg−1), NO3− (5.77 ± 4.24mg·kg−1), NO2− (0.472 ± 0.503 mg·kg−1), TP (417 ± 120 mg·kg−1), AP (47.6 ± 29.6 mg·kg−1), As (11.9 ± 0.909 mg·kg−1), Cr (56.2 ± 14.0 mg·kg−1), Hg (0.375 ± 0.756 mg·kg−1), and Pb (17.5 ± 1.87 mg·kg−1). TN and TP were the most abundant physico-chemical factors, and As and Cr were the most abundant heavy metals. The contents of TN, TP, AP, NO3−, and Pb were all the highest in the surface sediments of S2. The spatial variation of pH was not large, and the water was weakly alkaline. The As content was the highest at the S6 point, and the Hg content was generally lower in all sample points, but with a higher level at the S1, S2 and S3 points; The content of NO2− was the lowest at S2, S6, and S8, but the highest at S7.

3.2. Structural Characteristics of Bacteria in Surface Sediments

The relative abundance of bacteria at the phylum level in surface sediments is shown in Figure 3a. A total of 66 bacterial phyla were detected, mainly including the Proteobacteria (39.72–55.80%), Bacteroidetes (8.59–28.42%), Acidobacteria (0.21–13.79%), Firmicutes (1.38–10.71%), Planctomycetes (0.85–10.96%), Chloroflexi (0.34–8.34%), Cyanobacteria (0.43–8.15%), Actinobacteria (0.88–5.95%), Verrucomicrobia (0.26–2.16%), Gemmatimonadetes (0.21–1.24%), and TM6 (0.04–1.32%). At the phylum level, the dominant phylum in surface sediments (the average abundance with greater than 5%) was the Proteobacteria (48.15%), Bacteroidetes (21.74%), and Firmicutes (5.71%); Proteobacteria and Bacteroidetes were the common dominant phyla (relative abundance greater than 5%) among the nine sample points. The relative abundance of bacteria at the class level in the sediments is shown in Figure 3b. A total of 164 bacterial classes were detected, of which the dominant bacteria (average abundance greater than 5%) were Alphaproteobacteria (15.38%), Betaproteobacteria (15.16%), Flavobacteriia (11.57%), Gammaproteobacteria (9.75%), Deltaproteobacteria (7.46%). Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria were the dominant groups with a common dominance in the nine sample point sites (relative abundance greater than 5%). The relative abundance of bacteria at the genus level in the sediments is shown in Figure 3c. A total of 501 genera of bacteria were detected, and the sediment dominant bacteria (average abundance greater than 1%) were Rhodobacter (3.44%), Phyllobacterium (3.02%), Flavobacterium (2.64%), Hydrogenophaga (1.04%), and Planctomyces (1.04%). The most dominant bacteria genera were different among the sampling points, the proportion of Phyllobacterium species at S1, S4, S5, S6 and S8 (which was the highest), were 4.27%, 4.67%, 5.88%, 4.15%, and 6.22%, respectively. The S2 and S3 points had the highest proportions of the Flavobacterium species, which were 5.03% and 5.84%, respectively. At the S7 point, the Rhodobacter accounted for the highest proportion with 8.29%, while at the S9 point, Gillisia accounted for the highest proportion with 5.51%.

3.3. Analysis of Bacterial Community Diversity in Sediment

The analytical results of the bacterial community diversity in the sediment were shown in Table 1. This study obtained a total of 298,867 sequences, and then detected a total of 16,855 OTUs. The number of OTUs in the sample point varied from 1198 to 3693. In community ecology, sample α-diversity could reflect its abundance and diversity of the microbial community. All indexes of ACE, Chao1, and Observed Species in the surface sediments were the largest in the S2 point, but the smallest in the S6 point. It showed that the bacterial community richness in the sediments was the highest at the S2 point, but the lowest bacterial community richness at the S6 point. The Shannon index was the smallest at the S6 point but the largest at S1; the Simpson index was the largest at the S6 point but the smallest at the S1 point. It showed that the species diversity and uniformity were the worst at the S6 point, but the best at the S1 point.

3.4. Effects of Environmental Factors on Microbial Community Structure and Diversity

The Pearson correlation analysis between environmental factors and the α-diversity index of bacterial community in sediments is shown in Figure 4. The diversity of bacteria and the characteristics of community structure were very sensitive to be altered with an environment of aquatic ecosystems. This indicated that it was of practical significance to study the effects of environmental factors on the differences in bacterial communities. In this study, heavy metals (As, Cr, Pb and Hg) and physico-chemical properties (pH, TN, NH4+, NO3−, NO2−, TP and AP) in sediments were selected as environmental factors. The relationship between N sources (TN and NO3−) and indexes of ACE, Chao1, and Observed Species was significantly (p < 0.01) positively correlated, TP was significantly (p < 0.01) positively correlated with ACE and Chao1 and positively correlated (p < 0.05) with the Observed Species index. There was a positive relationship (p < 0.05) between AP and indexes of ACE, Chao1, Observed Species, and Shannon, while there was a negative relationship between Cr and these indexes.
As shown in Figure 5, NH4+ and pH are positively correlated (p < 0.05) with Firmicutes, Cr was significantly positively correlated (p < 0.01) with Cyanobacteria, and positively correlated (p < 0.05) with Verrucomicrobia. NH4+, pH, and Cr had a greater influence on the bacterial communities in the sediments, compared to others. Here, NH4+, NO2−, NO3−, and pH were positively correlated with Proteobacteria, but negatively with the Gemmatimonadetes, Actinobacteria, Planctomycetes, and Verrucomicrobia at a phylum level. Cr was positively correlated with Bacteroidetes, but negatively with the Acidobacteria. Pb was positively correlated with the Planctomycetes and Chloroflexi, and negatively correlated with Bacteroidetes and Cyanobacteria.

4. Discussion

4.1. Composition and Function of Dominant Bacteria in Sediments

Species diversity is a prerequisite for maintaining the ecosystem’s function [28]. The dominant bacteria in the main stream of the Qingshui River were the Proteobacteria, Bacteroidetes, and Firmicutes, which accounted for 75.60% of the total sequences, showing the richness of its community composition. This also is positively corresponding to the most common dominant bacterial phylum in other surface waters and sediments, as illustrated in the Yellow River Delta wetlands [29], Yellow River [30], Dianchi Lake [31], Dongting Lake [32], as well as the ocean [33,34]. However, there was a small difference, as most of these sediment bacteria belong to the Proteobacteria, Chloroflexi, Actinobacteria, and Firmicutes. A previous study has reported that both Proteobacteria and Firmicutes were typical of freshwater phyla [35]. The Proteobacteria is the most dominant phylum of all point sediment samples, being consistent with the previous results from the river, lake and marine sediments [30,31,32,33,34,36,37]. A study has demonstrated that Proteobacteria (44.2%) is the most dominant bacterial phylum in the Guyuan section of the upper reaches of the Qingshui River (S1 and S2 in this study are located in the Guyuan section), followed by Verrucomicrobia (14.4%) [24]. The most dominant bacterial phylum at the confluence of the Qingshui River and the Yellow River (S9 in this study is located in the confluence of the Qingshui River and the Yellow River) is Cyanobacteria [25]. Neither Verrucomicrobia nor Cyanobacteria were found to be in high relative abundance in this study. This may be influenced by factors such as sampling time. Indeed, it has been shown that the Proteobacteria plays an important role in the substance N cycle [38]. Bacteroidetes contain a variety of pathogenic bacteria, commonly found in humans and animals [39]. Since it is generally derived from animal or human feces, Bacteroidetes shows a higher abundance in sediments of the aquatic environment. Therefore, it is speculated that the sampling points in this study may have been affected by land-based sources of emissions or other human activities. Bacteroidetes had the lowest abundance at the S1 point at the source of the Qingshui River, but it showed an increasing trend with the flow direction of the river. This may be attributed the fact that the source was less affected by untreated domestic water discharges. Firmicutes can be involved in the degradation and transformation of a variety of substances and elements [40]. The changes in the abundance of different classes of Proteobacteria in sediments are also an important indicator in the study of microbial community structure [41]. The Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria in sediments were the dominant bacteria in all sampling points, suggesting that they occupy a relatively important position in the ecological ecosystem. Alphaproteobacteria is a typical dominant group of freshwater bacterial communities, including nitrogen-fixing bacteria that coexists with plants and plays an important role in promoting ammonia oxidation and nitrogen fixation [42]. In particular, Betaproteobacteria exists much more likely in contaminated environments, and can be used as an ecological indicator for monitoring and evaluating environmental quality. Betaproteobacteria was more abundant in the sediments of the main stream of the Qingshui River, whereas it was the highest at the S2 point This is due to the fact that the S2 point, being located in Yuanzhou District, Guyuan City, was greatly affected by the precipitation induced by the discharge of surrounding industrial and domestic wastewater. A previous study has reported that Gammaproteobacteria plays a key role in the denitrification of salty wastewater [43], and also the oxidation of sediments’ anaerobic ammonia. However, Gammaproteobacteria also contains a large number of pathogenic bacteria such as Salmonella, Legionella and Vibrio. These findings suggest that the presence of Gammaproteobacteria in the bacterial community, which indicates that the sediments of the main stream of the Qingshui River had higher carbon and nitrogen contents and more frequent carbon and nitrogen cycles, while their presence also poses a great risk to human health. The abundance of Flavobacteriia and Deltaproteobacteria in eight sample points was more than 5%. Since it also contains some bacteria that feed on other bacteria, Deltaproteobacteria affects the cycle of nitrogen, phosphorus, sulfur, and carbon in the sediments [44]. Yet, Flavobacteriia only play a key role in the decomposition of organic matter [45]. Rhodobacter is a phototrophic bacterium, it is a curial denitrifying bacterium in activated sludge, as it can oxidize and decompose organic matter in water [46]. Eutrophication therefore promotes its growth. In addition, an increase in the abundance of Rhodobacter could also be observed in the environments polluted by farming [47,48]. Phyllobacterium is a facultative anaerobic bacterium, has a nitrogen fixation function, which has good application prospects as a new microbial resource of the biological treatment of nitrogen-containing heterocyclic compounds. Flavobacterium is a bacterial species under Bacteroidia that is considered to degrade organic compounds [49]. In addition, Flavobacterium also contains some conditional pathogenic bacteria. According to the distribution of water quality in the Qingshui River, it can be speculated that the increase in content of artificially imported organic matter has promoted the increase in Flavobacterium, which is a potential public health safety risk. Planctomyces had a high abundance in soils in high-saline areas [50], as it is related to the alkaline nature of the soil in the Qingshui River Basin. Hydrogenophaga are facultative autotrophic bacteria, using the energy of organic oxidation as energy, inorganic matter as hydrogen donors, and organic matter as the basic carbon source of microbial types.

4.2. Correlation between the Structure and Diversity of Bacterial Community and Environmental Factors in Qingshui River Sediments

The richness and diversity of bacterial communities are important indicators of the stability of aquatic ecosystems [51], as it is closely related to the nutrient content. Thus, they can be used as potential biological indicators [52]. N and P are important nutrients for bacterial survival and reproduction. Indeed, in a nutrient-deficient environment, their growths are largely dependent on N and P levels. In addition, due to changes in the living conditions, such as nutrients, bacteria can promote the proliferation of certain taxon-bacteria, significantly increasing their biomass. However, the deterioration of the ecological-environmental conditions induced by excessive nutrients partly inhibits the diversity of the bacteria [53]. As highlighted in Figure 4, the increased content of N and P in the Qingshui River sediments have promoted the abundance of bacteria; AP was positively correlated with the Shannon index, suggesting that increased AP content benefits to increase species diversity of bacteria. Ding et al. [54] have reported that bacterial community diversity in water sediments decreased with increasing nutrient levels. This is consistent with the relevant analysis results in this study, which was that the abundance of bacteria in nine sample points generally increased with the increase in N and P content, while the diversity of bacteria showed a tendency to rise first and then decrease with the increase in N and P content. Cr was inversely correlated with the index ACE, Chao1, and Observed Species, but other heavy metals had little correlation with the α-diversity index. This suggests that Cr has a strong inhibitory effect on the abundance of bacteria. For example, the S6 point had the highest content of Cr and the lowest richness and diversity of the bacterial community, highlighting that Cr may be an important factor influencing the richness and diversity of bacterial communities at the S6 point. Zhao et al. [55] also argue that high enrichment of heavy metals reduces the diversity of the bacterial communities.
The positive relationship between environmental factors and the bacteria indicates that they have a promoting effect on the growth of the bacteria, or have a strong tolerance to bacteria, while negative correlation suggests the inhibition of bacterial growth or poor tolerance of the bacteria. The Pearson correlation analysis showed that the N nutrients (i.e., NH4+, NO3− and NO2−) in the sediments of the Qingshui River had a greater impact on the microbial community, and Cr had a greater impact on microbial communities than other metals. For example, at the S1 point, NH4+ content was the lowest, promoting the growth of the Acidobacteria, Actinobacteria, Planctomycetes, and Chloroflexi; the lower Cr content promoted the growth of Acidobacteria. At both the S2, S3 points, the high content of NH4+ promotes the growth of Proteobacteria and Firmicutes. Proteobacteria plays an important role in the substance N cycle [38]. In this study, Proteobacteria was positively correlated with NH4+ and NO3−, indicating that Proteobacteria promoted the transformation of N to NH4+ and NO3−. Previous studies have demonstrated that high concentrations of heavy metals can reduce the diversity of bacterial communities [53]. In contrast, this study found that Cyanobacteria, Bacteroidetes, and Verrucomicrobia at the phylum level showed a strong tolerance to Cr, while Planctomycetes and Chloroflexi at the phylum level showed a strong tolerance to Pb.
There is currently no agreement to explain the relationship between the key drivers and the microbial diversity [24]. There is still much work to be performed to clarify the impact of environmental factors on bacterial communities in the Qingshui River. We should pay attention to a wider range of environmental factors and screen the most important environmental factors from the survey results of different water periods in the Qingshui River.

5. Conclusions

Based on the main stream of the Qing-Shui River, this study has indicated that sediment bacteria at the phylum level mainly included Proteobacteria (39.72–55.80%), Bacteroidetes (8.59–28.42%), Acidobacteria (0.21–13.79%), Firmicutes (1.38–10.71%), and Planctomycetes (0.85–10.96%). At the level of class and genus, carbon/nitrogen-circulating bacteria were dominant, while the abundance of Alphaproteobacteria of Proteobacteria and Rhodobacter of Alphaproteobacteria were the highest. The bacterial richness index was the highest at the S2 point, and the bacterial diversity index was the largest at the S1 point. NO2−, NH4+, and NO3− promoted the growth of both Proteobacteria and Firmicutes at the phylum level, but they had an inhibitory effect on most bacterial growth; pH inhibited the growth of Firmicutes at the phylum level. At the phylum level, Cyanobacteria, and Verrucomicrobia showed a strong tolerance to Cr, but Planctomycetes and Chloroflexi showed a strong tolerance to Pb. The study of Qingshui river sediment bacteria communities and driving factors have a preliminary understanding, but each environment variable to a clear influence of the bacterial community structure has not been determined, in the future work should continue to pay attention to the relationship between the bacterial community and environmental factors in the Qingshui River at different water periods, and identify the most important environmental factors, thus putting forward the Qingshui River ecological management mode.

Author Contributions

Conceptualization, Z.Z. and X.Q.; methodology, Z.Z.; software, Z.Z.; validation, Z.Z., R.Z. and L.L.; formal analysis, Z.Z., R.Z. and Lee, L.; investigation, Z.Z.; resources, X.Q.; data curation, Z.Z. and R.Z.; writing—original draft preparation, Z.Z.; writing—review and editing, X.Q.; visualization, Y.W.; supervision, X.Q.; project administration, Z.Z.; funding acquisition, X.Q. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the Ningxia University first-class discipline (water conservancy engineering) construction subsidy project under award number NXYLXK2021A03.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data are not publicly available due to privacy.

Acknowledgments

This material is based on work supported by the Ningxia University first-class discipline (water conservancy engineering) construction subsidy project under award number NXYLXK2021A03.

Conflicts of Interest

The authors declare that there were no conflicts of interest or any potential financial or other interests that could be perceived to influence the outcomes of this research.

References

  1. Jiang, Y.; Ma, X.; Wang, B.; Jiang, B.; Wang, W.; Wang, Y.; Zhang, C. Effects of environmental factors on phosphorus adsorption capacity and release risk in lake sediments. Plant Soil Environ. 2022, 68, 186–194. [Google Scholar] [CrossRef]
  2. Zeng, J.; Han, G.L.; Zhang, S.T.; Zhang, Q. Suspended Sediments Quality Assessment in a Coastal River: Identification of Potentially Toxic Elements. Int. J. Environ. Res. Public Health 2022, 19, 4293. [Google Scholar] [CrossRef] [PubMed]
  3. Zeng, J.; Han, G.L.; Zhang, S.T.; Liang, B.; Qu, R.; Liu, M.; Liu, J.K. Potentially toxic elements in cascade dams-influenced river originated from Tibetan Plateau. Environ. Res. 2022, 208, 112716. [Google Scholar] [CrossRef] [PubMed]
  4. Zhang, W.; Zhu, M.; Li, Y.; Wang, C.; Qian, B.; Niu, L.; Wang, P.; Gu, J.; Yang, N. How fluvial inputs directly and indirectly affect the ecological status of different lake regions: A bio-assessment framework. J. Hydrol. 2020, 582, 124502. [Google Scholar] [CrossRef]
  5. Prosser, J.I. Ecosystem processes and interactions in a morass of diversity. FEMS Microbiol. Ecol. 2012, 81, 507–519. [Google Scholar] [CrossRef] [Green Version]
  6. Kevin, P.; Feris, P.W.R.M.; James, E.; Gannon, A.W.E.H. Determining Rates of Change and Evaluating Group-Level Resiliency Differences in Hyporheic Microbial Communities in Response to Fluvial Heavy-Metal Deposition. Appl. Environ. Microb. 2004, 70, 4756–4765. [Google Scholar] [CrossRef]
  7. Zhang, S.; Li, K.; Hu, J.; Wang, F.; Chen, D.; Zhang, Z.; Li, T.; Li, L.; Tao, J.; Liu, D.; et al. Distinct assembly mechanisms of microbial sub-communities with different rarity along the Nu River. J. Soil Sediment 2022, 22, 1530–1545. [Google Scholar] [CrossRef]
  8. Takaki, Y.; Hattori, K.; Yamashita, Y. Factors Controlling the Spatial Distribution of Dissolved Organic Matter with Changes in the C/N Ratio From the Upper to Lower Reaches of the Ishikari River, Japan. Front. Earth Sci. 2022, 10, 305. [Google Scholar] [CrossRef]
  9. Wiesner-Friedman, C.; Beattie, R.E.; Stewart, J.R.; Hristova, K.R.; Serre, M.L. Characterizing Differences in Sources of and Contributions to Fecal Contamination of Sediment and Surface Water with the Microbial FIT Framework. Environ. Sci. Technol. 2022, 56, 4231–4240. [Google Scholar] [CrossRef]
  10. Yang, C.; Zeng, Z.; Wang, Y.Y.; He, G.Y.; Hu, Y.S.; Gao, D.D.; Dai, Y.H.; Li, Q.Y.; Zhang, H. Ecological risk assessment and identification of the distinct microbial groups in heavy metal-polluted river sediments. Environ. Geochem. Health 2022. [Google Scholar] [CrossRef]
  11. Tian, W.; Zhang, H.Y.; Guo, Y.H.; Wang, Z.Y.; Huang, T.S. Temporal and Spatial Patterns of Sediment Microbial Communities and Driving Environment Variables in a Shallow Temperate Mountain River. Microorganisms 2022, 10, 816. [Google Scholar] [CrossRef]
  12. Wang, P.; Chen, B.; Yuan, R.Q.; Li, C.Q.; Li, Y. Characteristics of aquatic bacterial community and the influencing factors in an urban river. Sci. Total Environ. 2016, 569, 382–389. [Google Scholar] [CrossRef] [PubMed]
  13. El Najjar, P.; Pfaffl, M.; Ouaini, N.; Abdel Nour, A.; El Azzi, D. Water and sediment microbiota diversity in response to temporal variation at the outlet of the Ibrahim River (Lebanon). Environ. Monit. Assess. 2020, 192, 201. [Google Scholar] [CrossRef] [PubMed]
  14. Liu, X.D.; Huang, Y.; Wang, Y.H.; Wang, B.B.; Wu, B.; Lu, G.H. Structural Characteristics of Microbial Communities in the Sediments of the Niyang River in Tibet. Environ. Sci. 2020, 41, 3249–3256. [Google Scholar] [CrossRef]
  15. Xia, N.; Xia, X.H.; Liu, T.; Hu, L.J.; Zhu, B.T.; Zhang, X.T.; Dong, J.W. Characteristics of bacterial community in the water and surface sediment of the Yellow River, China, the largest turbid river in the world. J. Soil Sediment 2014, 14, 1894–1904. [Google Scholar] [CrossRef]
  16. Kai, X.L. Study on Environmental Behavior and Health Risk of Heavy Metals and Organochlorine Pesticides in Qingshui River; Ningxia University: Ningxia, China, 2021. [Google Scholar]
  17. Kai, X.L.; Zhang, W.J.; Qiu, X.C.; Chu, J.D.; Zhang, Y.Z. Health risk evaluation of children caused by water pollutants in Qingshui River. Environ. Chem. 2018, 37, 2809–2819. [Google Scholar] [CrossRef]
  18. Wu, Y.L.; Lee, S.L.; Qiu, X.C.; Yang, Y.Y.; Lei, X.B. Analysis and Assessment of Water Quality in Qingshui River Basin. Admin. Techol. Environ. Monit. 2021, 33, 40–45. [Google Scholar] [CrossRef]
  19. Wang, S.Q.; Zhao, Z.F.; Qiu, X.C.; Ouyang, H.; Wu, Y.L. Spatial-temporal Characteristics of Water Environmental Quality in Mainstream of Qingshui River. Southwest China J. Agric. Sci. 2021, 3, 386–391. [Google Scholar] [CrossRef]
  20. Zhao, Z.F.; Shi, W.; Qiu, X.C.; OuYang, H.; Wang, S.Q.; Sun, X.Y.; Lee, S.L. Distribution Characteristics and Health Risk Assessment of Five Heavy Metals in the Water of Qingshui River Basin. Admin. Techol. Environ. Monit. 2021, 33, 35–40. [Google Scholar] [CrossRef]
  21. Lee, S.L.; Zhao, Z.F.; Qiu, X.C.; Guo, Q.; Wu, Y.L. Distribution Characteristics and Risk Assessment of Heavy Metals in Qingshui River Basin of Ningxia. Journal of Irrigation and Drainage. J. Irrig. Drain 2020, 39, 128–137. [Google Scholar] [CrossRef]
  22. Duan, J.R.; Shi, W.; Qiu, X.C.; Wang, X.Y. Plant Community Structure and Diversity in the Riparian Zone of the Qingshui River Basin. J. Anhui Agric. Sci. 2020, 48, 73–76. [Google Scholar] [CrossRef]
  23. Shi, W.; Duan, J.R.; Qiu, X.C.; Wang, X.Y. Study on community structure and diversity of zooplankton in Qingshui river. Hubei Agric. Sci. 2021, 60, 100–104. [Google Scholar] [CrossRef]
  24. Cao, X.F.; Wang, Y.J.; Xu, Y.; Duan, G.Q.; Huang, M.S.; Peng, J.F. Adaptive Variations of Sediment Microbial Communities and Indication of Fecal-Associated Bacteria to Nutrients in a Regulated Urban River. Water-Sui 2020, 12, 1344. [Google Scholar] [CrossRef]
  25. Zhao, M.M.; Wang, S.M.; Chen, Y.P.; Wu, J.H.; Xue, L.G.; Fan, T.T. Pollution status of the Yellow River tributaries in middle and lower reaches. Sci. Total Environ. 2020, 722, 137861. [Google Scholar] [CrossRef]
  26. Yang, H.; Zhang, G.Z.; Yang, X.N.; Wu, F.P.; Zhao, W. 16S rRNA high-throughput sequencing was used to study the microbial community structure and diversity in rainwater harvesting cellar water. Environ. Sci. 2017, 04, 1704–1716. [Google Scholar] [CrossRef]
  27. Guo, X.C.; Miao, Y.; Wu, B.; Ye, L.; Yu, H.Y.; Liu, S.; Zhang, X.X. Correlation between microbial community structure and biofouling as determined by analysis of microbial community dynamics. Bioresour. Technol. 2015, 197, 99–105. [Google Scholar] [CrossRef]
  28. Ansola, G.; Arroyo, P.; Saenz De Miera, L.E. Characterisation of the soil bacterial community structure and composition of natural and constructed wetlands. Sci. Total Environ. 2014, 473, 63–71. [Google Scholar] [CrossRef]
  29. Yu, Y.; Wang, H.; Liu, J.; Wang, Q.; Shen, T.; Guo, W.; Wang, R. Shifts in microbial community function and structure along the successional gradient of coastal wetlands in Yellow River Estuary. Eur. J. Soil Biol. 2012, 49, 12–21. [Google Scholar] [CrossRef]
  30. Xia, N.; Xia, X.; Zhu, B.; Zheng, S.; Zhuang, J. Bacterial diversity and community structure in the sediment of the middle and lower reaches of the Yellow River, the largest turbid river in the world. Aquat. Microb. Ecol. 2013, 71, 43–55. [Google Scholar] [CrossRef] [Green Version]
  31. Dai, Y.; Yang, Y.; Wu, Z.; Feng, Q.; Xie, S.; Liu, Y. Spatiotemporal variation of planktonic and sediment bacterial assemblages in two plateau freshwater lakes at different trophic status. Appl. Microbiol. Biot. 2016, 100, 4161–4175. [Google Scholar] [CrossRef]
  32. Huang, W.; Jiang, X. Profiling of Sediment Microbial Community in Dongting Lake before and after Impoundment of the Three Gorges Dam. Int. J. Environ. Res. Public Health 2016, 13, 617. [Google Scholar] [CrossRef] [PubMed]
  33. Acosta-Gonzalez, A.; Marques, S. Bacterial diversity in oil-polluted marine coastal sediments. Curr. Opin. Biotech. 2016, 38, 24–32. [Google Scholar] [CrossRef] [PubMed]
  34. Mahmoudi, N.; Robeson, M.S.I.; Castro, H.F.; Fortney, J.L.; Techtmann, S.M.; Joyner, D.C.; Paradis, C.J.; Pfiffner, S.M.; Hazen, T.C. Microbial community composition and diversity in Caspian Sea sediments. FEMS Microbiol. Ecol. 2015, 91, 1–11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Zhang, Q.; Wu, Z.; Zhao, J.; Wang, G.; Hao, J.; Wang, S.; Lin, Y.; Guan, H.; Zhang, J.; Jian, S.; et al. Composition and Functional Characteristics and Influencing Factors of Bacterioplankton Community in the Huangshui River, China. Microorganisms 2021, 9, 2260. [Google Scholar] [CrossRef] [PubMed]
  36. Wan, Y.; Ruan, X.; Zhang, Y.; Li, R. Illumina sequencing-based analysis of sediment bacteria community in different trophic status freshwater lakes. Microbiologyopen 2017, 6, e00450. [Google Scholar] [CrossRef]
  37. Sáenz de Miera, L.; Gutierrez-Gonzalez, J.J.; Arroyo, P.; Falagan, J.; Ansola, G. Prokaryotic community diversity in the sediments of saline lagoons and its resistance to seasonal disturbances by water level cycles. J. Soil Sediment 2021, 21, 3169–3184. [Google Scholar] [CrossRef]
  38. Hou, L.; Zhou, Q.; Wu, Q.; Gu, Q.; Sun, M.; Zhang, J. Spatiotemporal changes in bacterial community and microbial activity in a full-scale drinking water treatment plant. Sci. Total Environ. 2018, 625, 449–459. [Google Scholar] [CrossRef]
  39. He, W.; Xiong, Y.; Ge, J.; Chen, Y.; Chen, X.; Zhong, X.; Ou, Z.; Gao, Y.; Cheng, M.; Mo, Y.; et al. Composition of gut and oropharynx bacterial communities in Rattus norvegicus and Suncus murinus in China. BMC Vet. Res. 2020, 16, 413. [Google Scholar] [CrossRef]
  40. Goffredi, S.K.; Orphan, V.J. Bacterial community shifts in taxa and diversity in response to localized organic loading in the deep sea. Environ. Microbiol. 2010, 12, 344–363. [Google Scholar] [CrossRef]
  41. Jeong, C.Y.; Ham, J.H. Comparative analysis of the microbial community in the sediments of two constructed wetlands differentially influenced by the concentrated poultry feeding operations. J. Soil Sediment 2016, 17, 557–566. [Google Scholar] [CrossRef]
  42. Zhu, L.; Zhou, H.; Xie, X.; Li, X.; Zhang, D.; Jia, L.; Wei, Q.; Zhao, Y.; Wei, Z.; Ma, Y. Effects of floodgates operation on nitrogen transformation in a lake based on structural equation modeling analysis. Sci. Total Environ. 2018, 631–632, 1311–1320. [Google Scholar] [CrossRef] [PubMed]
  43. Miao, Y.; Liao, R.; Zhang, X.; Liu, B.; Li, Y.; Wu, B.; Li, A. Metagenomic insights into salinity effect on diversity and abundance of denitrifying bacteria and genes in an expanded granular sludge bed reactor treating high-nitrate wastewater. Chem. Eng. J. 2015, 277, 116–123. [Google Scholar] [CrossRef]
  44. Zhang, J.; Yang, Y.; Zhao, L.; Li, Y.; Xie, S.; Liu, Y. Distribution of sediment bacterial and archaeal communities in plateau freshwater lakes. Appl. Microbiol. Biot. 2015, 99, 3291–3302. [Google Scholar] [CrossRef] [PubMed]
  45. Vu, C.H.T.; Chun, S.; Seo, S.; Cui, Y.; Ahn, C.; Oh, H. Bacterial community enhances flocculation efficiency of Ettlia sp. by altering extracellular polymeric substances profile. Bioresour. Technol. 2019, 281, 56–65. [Google Scholar] [CrossRef] [PubMed]
  46. Nabil, B.; André, P.; Nadia, A.; Claude-Olivier, S.; Hocine, G.; Nabil, M. Enhancement of the denitrification performance of an activated sludge using an electromagnetic field in batch mode. Chemosphere 2021, 262, 128827. [Google Scholar] [CrossRef]
  47. Dong, P.; Guo, H.; Wang, Y.; Wang, R.; Chen, H.; Zhao, Y.; Wang, K.; Zhang, D. Gastrointestinal microbiota imbalance is triggered by the enrichment of Vibrio in subadult Litopenaeus vannamei with acute hepatopancreatic necrosis disease. Aquaculture 2021, 533, 736199. [Google Scholar] [CrossRef]
  48. Liu, S.; Ren, H.; Shen, L.; Lou, L.; Tan, G.; Zheng, P.; Hu, B. pH levels drive bacterial community structure in sediments of the Qiantang River as determined by 454 pyrosequencing. Front. Microbiol. 2015, 6, 285. [Google Scholar] [CrossRef]
  49. Drury, B.; Rosi-Marshall, E.; Kelly, J.J. Wastewater Treatment Effluent Reduces the Abundance and Diversity of Benthic Bacterial Communities in Urban and Suburban Rivers. Appl. Environ. Microb. 2013, 79, 1897–1905. [Google Scholar] [CrossRef] [Green Version]
  50. Wang, H.Q.; Wang, R.F.; Zhong, W.; Ma, Q.L.; Zong, K.J.; Zhao, C.C.; Wang, Q. Advance in Structural Characteristics and Influence Factors of Functional Microbial Communities in the Soils of the Wetlands in the Yellow River Delta. Wetl. Sci. 2022, 20, 111–118. [Google Scholar] [CrossRef]
  51. Reed, H.E.; Martiny, J.B.H. Microbial composition affects the functioning of estuarine sediments. ISME J. 2013, 7, 868–879. [Google Scholar] [CrossRef]
  52. Ghosh Roy, S.; Wimpee, C.F.; McGuire, S.A.; Ehlinger, T.J. Responses of Bacterial Taxonomical Diversity Indicators to Pollutant Loadings in Experimental Wetland Microcosms. Water-Sui 2022, 14, 251. [Google Scholar] [CrossRef]
  53. Zhu, L.; Sun, L.Y.; Chu, R.H.; Qian, J. On the characteristic of sediments microbial community structure of urban polluted river. Adv. Water Sci. 2013, 24, 132–137. [Google Scholar] [CrossRef]
  54. Yu, Y.; Wang, Y.Y.; Fang, D.X.; Ren, J.; Wang, Y. Bacterial diversity in surface sediments of Baiyangdian lake and its influencing factors. Chin. J. Environ. Eng. 2021, 15, 1121–1130. [Google Scholar] [CrossRef]
  55. Zhao, J.; Zhao, X.; Chao, L.; Zhang, W.; You, T.; Zhang, J. Diversity change of microbial communities responding to zinc and arsenic pollution in a river of northeastern China. J. Zhejiang Univ.-Sci. B 2014, 15, 670–680. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Sampling points of nine sediments in the main stream of Qingshui River.
Figure 1. Sampling points of nine sediments in the main stream of Qingshui River.
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Figure 2. Scatter plot of physical-chemical properties and heavy metals in surface sediments. (Note: pH has no dimension).
Figure 2. Scatter plot of physical-chemical properties and heavy metals in surface sediments. (Note: pH has no dimension).
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Figure 3. Distribution of bacterial community structure in sediments. (Note: (a) relative abundance at the bacterial phylum level in sediments; (b) relative abundance at the bacterial class level in sediments (c) relative abundance at the bacterial genus level in sediments).
Figure 3. Distribution of bacterial community structure in sediments. (Note: (a) relative abundance at the bacterial phylum level in sediments; (b) relative abundance at the bacterial class level in sediments (c) relative abundance at the bacterial genus level in sediments).
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Figure 4. Pearson correlation analysis between environmental factors and α-diversity index of bacterial community in sediments. (Note: * indicates significant correlation at 0.05 level and ** indicates significant correlation at 0.01 level.).
Figure 4. Pearson correlation analysis between environmental factors and α-diversity index of bacterial community in sediments. (Note: * indicates significant correlation at 0.05 level and ** indicates significant correlation at 0.01 level.).
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Figure 5. Pearson correlation analysis between environmental factors and dominant phylum of bacterial community in sediments. (Note: * indicates significant correlation at 0.05 level and ** indicates significant correlation at 0.01 level. Aci: Acidobacteria; Act: Actinobacteria; Bac: Bacteroidetes; Chl: Chloroflexi; Cya: Cyanobacteria; Fir: Firmicutes; Gem: Gemmatimonadetes; Pla: Planctomycetes; Pro: Proteobacteria; Ver: Verrucomicrobia.).
Figure 5. Pearson correlation analysis between environmental factors and dominant phylum of bacterial community in sediments. (Note: * indicates significant correlation at 0.05 level and ** indicates significant correlation at 0.01 level. Aci: Acidobacteria; Act: Actinobacteria; Bac: Bacteroidetes; Chl: Chloroflexi; Cya: Cyanobacteria; Fir: Firmicutes; Gem: Gemmatimonadetes; Pla: Planctomycetes; Pro: Proteobacteria; Ver: Verrucomicrobia.).
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Table
Table 1. The α-diversity index levels of bacterial community.
Table 1. The α-diversity index levels of bacterial community.
SampleACEChao1Observed SpeciesShannonSimpson
S12196.952359.7018559.2300.007
S26313.386072.7636938.8770.010
S32669.742694.0221098.0970.010
S41677.401756.5912818.5830.007
S51612.061720.4212717.7430.023
S61582.641678.8511987.5770.027
S72521.762508.3318187.7730.013
S81675.041775.6413407.9500.017
S92880.122995.8522909.0300.010
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Zhao, Z.; Zhao, R.; Qiu, X.; Wan, Y.; Lee, L. Structural Diversity of Bacterial Communities and Its Relation to Environmental Factors in the Surface Sediments from Main Stream of Qingshui River. Water 2022, 14, 3356. https://doi.org/10.3390/w14213356

AMA Style

Zhao Z, Zhao R, Qiu X, Wan Y, Lee L. Structural Diversity of Bacterial Communities and Its Relation to Environmental Factors in the Surface Sediments from Main Stream of Qingshui River. Water. 2022; 14(21):3356. https://doi.org/10.3390/w14213356

Chicago/Turabian Style

Zhao, Zengfeng, Ruizhi Zhao, Xiaocong Qiu, Yongpeng Wan, and Lin Lee. 2022. "Structural Diversity of Bacterial Communities and Its Relation to Environmental Factors in the Surface Sediments from Main Stream of Qingshui River" Water 14, no. 21: 3356. https://doi.org/10.3390/w14213356

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