Method for evaluating river pollution and application thereof

Abstract

The invention provides a method for evaluating river pollution and application thereof, and belongs to the technical field of river pollution treatment. The invention discloses the relationship between the microbial community composition change and the environmental factor in the river water body of the drainage basin. According to the invention, bacterial communities and virus communities in a river are significantly related to environmental factors (r is greater than 0.8, and p is less than 0.05), which indicates that the environmental factors are the main reason influencing the difference and abundance change of the bacterial communities and virus communities in the river, and environmental pollution control measures should be taken to establish a perfect pollution control system. According to the method, a scientific basis is provided for the management of a river ecosystem and the protection of biological diversity, the influence of the environmental factors on the point location can be known by detecting the microbial community structure of the river in the river, a reference is provided for reasonably utilizing scarce fresh water resources, and a safety guarantee is provided for preventing and controlling the water environment pollution risk and ensuring the water quality safety.

Description

Technical Field

[0001] The invention belongs to the technical field of river pollution control, and in particular relates to a method for evaluating river pollution and an application thereof. Background Art

[0002] Rivers are an important source of freshwater resources, and microorganisms are an important component of river systems. Microbial population characteristics can be used as biological indicators to indicate the diversity and health of ecosystems, which is crucial to solving water environmental problems. Under the influence of human activities, microbial communities in river basins may change, but the laws of change and the mechanisms of influence still need further study. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a method for evaluating river pollution, determine the factors in the river that have a response relationship with bacterial and viral communities and their response relationship, and then determine the key areas of river pollution, so as to carry out targeted governance.

[0005] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions:

[0006] A method for evaluating river pollution comprises the following steps: collecting water samples from multiple points in a river, obtaining environmental factor data, bacterial community data and viral community data of the water samples; performing correlation analysis on the environmental factor data with the bacterial community data and the viral community data, respectively, to obtain environmental factor data significantly correlated with the bacterial community and viral community composition, respectively; performing collinear network analysis on the bacterial community data and the viral community data, to obtain dominant bacterial phyla significantly correlated with the viral community; by analyzing the species composition of the bacterial community and the viral community at the detection point, it can be known what environmental factors affect the point, and the river pollution can be evaluated.

[0007] Preferably, the environmental factor data include water temperature, pH, dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, total nitrogen concentration, nitrite concentration, nitrate concentration and soluble organic carbon concentration.

[0008] Preferably, bacterial community data and viral community data with a correlation coefficient with the environmental factor data greater than 0.6 and a p-value less than 0.05 are retained for co-occurrence network analysis.

[0009] Preferably, DNA is extracted from the water sample and subjected to high-throughput sequencing analysis and metagenomic sequencing analysis.

[0010] Preferably, ASV clustering analysis is performed on the data from high-throughput sequencing analysis to obtain bacterial community data.

[0011] Preferably, the similarity level adopted in the ASV cluster analysis is above 97%.

[0012] Preferably, Votus cluster analysis is performed on the data from the metagenomic sequencing analysis to obtain viral community data.

[0013] Preferably, the similarity level adopted by the Votus cluster analysis is above 97%.

[0014] Preferably, the number of collection points for the water samples is ≥10.

[0015] The invention also provides application of the method in river pollution control.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] The present invention provides a method for evaluating river pollution. The present invention uses environmental factor data in a river basin to perform correlation analysis with bacterial community data and viral community data, respectively, to construct a correlation heat map between bacterial community and environmental factors, viral community and environmental factors, and to find the response relationship between bacterial community and viral community and environmental factors (physical and chemical parameters) in the river basin. The present invention finds that the bacterial community and viral community in the river basin are significantly correlated with environmental factors (r>0.8, p<0.05), indicating that environmental factors are the main reasons affecting the structural differences and abundance changes of bacterial and viral communities in the river basin. Corresponding environmental pollution prevention and control measures should be taken. By detecting environmental factors, the changes in bacterial and viral communities can be quickly understood, and a complete microbial detection and early warning system can be established, so that environmental pollution problems caused by microorganisms can be discovered in time. By analyzing the species composition of bacterial and viral communities at the detection point, it can be known what environmental factors affect the point, and environmental pollution can be treated in time. The present invention provides a scientific basis for the management of river basin ecosystems and the protection of biodiversity, and provides a reference for the rational use of scarce freshwater resources. At the same time, community biological indicators have the potential to assess the ecological status of urban rivers, thereby protecting river water resources and ensuring the safety of river water quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a map of the abundance of species composition of viral communities in the basin rivers during winter;

[0019] Figure 2 Heat map showing the correlation between viral communities and environmental factors in the basin rivers in winter;

[0020] Figure 3 This is a map of species composition abundance of bacterial communities in the basin rivers during winter;

[0021] Figure 4 Heat map showing the correlation between bacterial communities and environmental factors in the river basin in winter;

[0022] Figure 5 This is the collinear network diagram of the viral community and bacterial community in the river basin in winter;

[0023] Figure 6 This is a map of species composition and abundance of viral communities in the basin rivers in summer;

[0024] Figure 7 Heat map showing the correlation between viral communities and environmental factors in the basin rivers in summer;

[0025] Figure 8 This is a map of species composition and abundance of bacterial communities in the river basin in summer;

[0026] Fig. 9 Heat map showing the correlation between bacterial communities and environmental factors in the river basin in summer;

[0027] Fig.10 This is a collinear network diagram of viral and bacterial communities in the basin rivers in summer. DETAILED DESCRIPTION

[0028] The present invention provides a method for evaluating river pollution, comprising the following steps: collecting water samples from multiple points in a river, obtaining environmental factor data, bacterial community data, and viral community data of the water samples; performing correlation analysis on the environmental factor data with the bacterial community data and the viral community data, respectively, to obtain environmental factor data significantly correlated with the bacterial community and viral community composition, respectively; performing collinear network analysis on the bacterial community data and the viral community data, to obtain dominant bacterial phyla significantly correlated with the viral community; by analyzing the species composition of the bacterial community and the viral community at the detection point, it can be known what environmental factors affect the point, and the river pollution can be evaluated. The number of water sample collection points is ≥10.

[0029] In the present invention, the environmental factor data include water temperature, pH, dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, total nitrogen concentration, nitrite concentration, nitrate concentration and soluble organic carbon concentration; the bacterial community data include bacterial community composition and abundance; the viral community data include viral community composition and abundance.

[0030] In the present invention, the environmental factor data may be detected by conventional methods in the art.

[0031] In the present invention, after the water sample is collected, DNA in the sample is extracted, and high-throughput sequencing analysis and metagenomic sequencing analysis are performed.

[0032] In the present invention, ASV cluster analysis is performed on the data of high-throughput sequencing analysis to obtain bacterial community data, and the similarity level adopted in the ASV cluster analysis is above 97%.

[0033] The present invention preferably uses a 0.22 μm filter membrane to filter the water sample and extract the DNA collected in the filter membrane; preferably uses the Illumina MiSeq sequencing platform and adopts a paired double-end 250bp strategy for sequencing; as an implementable method, a forward primer 515F (SEQ ID NO.1) and a reverse primer 806R (SEQ ID NO.2) are used to synthesize a long primer with a sample label and a sequencing-specific primer on the basis of the above-mentioned universal primers to amplify the 16S rRNA gene V4 region; after obtaining the original sequencing data of the amplified product using the above-mentioned long primer pair, the present invention preferably performs the following processing: using fastq software to perform quality control on the original sequencing data, the quality control is filtering and processing to remove low-quality sequences, adapter sequences and other contaminants, and then using FLASH software for splicing; using the Qiime2 process to perform denoising on the sequence after quality control splicing based on default parameters, the denoising process includes error correction, removal of chimeras, filtering of low-quality and low-frequency sequences, and merging of overlapping sequences; flattening according to the minimum sample sequence, and then referring to Sliva 16S rRNA database (v 138), using Naive bayes in Qiime2 to perform species classification analysis on ASVs, and the bacterial community data obtained include bacterial community composition and abundance.

[0034] In the present invention, after the water sample is collected, DNA in the sample is extracted, and metagenomic sequencing is performed. The sequenced data is subjected to Votus cluster analysis to obtain viral community data, and the similarity level adopted by the Votus cluster analysis is above 97%.

[0035] The present invention preferably uses a 0.22 μm filter membrane to filter the water sample, extracts the DNA in the collected filter membrane, performs metagenomic sequencing to obtain raw sequencing data, and then preferably performs the following processing: using fastq software to perform quality control on the raw data, the quality control is filtering and processing to remove low-quality sequences, adapter sequences and other contaminants, using bowtie2 to compare with the host genome sequence, remove host contamination, obtain optimized sequences, use software MEGAHIT to perform metagenomic assembly, and filter contig sequences shorter than 300 bp. CD-HIT software is used to cluster virus operational classification units to obtain the virus community data including the community composition and abundance of viruses.

[0036] The present invention performs correlation analysis on the environmental factor data with the viral community data and the bacterial community data, respectively, and preferably selects the top 200 ASVs (Amplicon Sequence Variants) with the highest relative abundance and the viral sequence for correlation analysis, and constructs a correlation heat map of bacterial community and environmental factors, and viral community and environmental factors; the environmental factors with stars in the heat map and the bacterial community are environmental factors significantly correlated with the composition of the bacterial community, and the environmental factors with stars in the heat map and the viral community are environmental factors significantly correlated with the composition of the viral community. Preferably, in the present invention, the drawing of the heat map uses Spearman analysis to screen and retain the bacterial community data and the viral community data with a correlation coefficient of >0.6 and a p value of <0.05 with the environmental factor data, and more preferably, the drawing of the heat map uses Spearman analysis to screen and retain the bacterial community data and the viral community data with a correlation coefficient of >0.8 and a p value of <0.05 with the environmental factor data.

[0037] The above-retained bacterial community data and viral community data are subjected to co-occurrence network analysis, wherein the nodes and number reflect the complexity of the connection between the bacterial community (ASVs) and the viral community (votus), the nodes represent the bacterial community and the viral community at the phylum level, and the connection is the edge connecting two nodes, which can not only represent the positive or reverse effect of the interaction relationship between species, but also show the importance of the correlation relationship; the tool for co-occurrence network analysis preferably includes the Hmisc software package in R language. Co-occurrence network analysis (Co-occurrence Network) uses abundance correlation to construct a network model to find the connection between different microorganisms, and displays the internal structure of the microbial community through a network diagram or a connection model, thereby showing the co-occurrence pattern between species, so as to simplify the complex microecological network and extract useful information. Different color circles represent different species, and the larger the diameter, the higher the species abundance. The pink line connection refers to the positive correlation between species, the green line indicates the negative correlation, and the thickness of the line reflects the size of the spearman coefficient between the two species. The thicker the line, the higher the correlation between species, and vice versa.

[0038] The present invention also provides an application of the above method in river pollution control. The present invention has found that environmental factors are the main reason affecting the differences and abundance changes of bacterial and viral communities in rivers. By detecting environmental factors, the changes in bacterial and viral communities can be quickly understood, and a complete microbial detection and early warning system can be established. By analyzing the species composition of bacterial and viral communities at the detection points, it can be known what kind of environmental factors affect the point, so that environmental pollution can be controlled in a timely manner.

[0039] In the specific embodiments of the present application, the high-throughput sequencing is performed by Beijing Biomaike Biotechnology Co., Ltd.; the metagene sequencing is performed by Beijing Biomaike Biotechnology Co., Ltd.

[0040] The technical solutions provided by the present invention are described in detail below in conjunction with the embodiments, but they should not be construed as limiting the protection scope of the present invention.

[0041] Example 1

[0042] Water samples were collected from 14 points in the river. A portable multi-parameter water quality meter was used to measure the water temperature (T) and pH on site. A dissolved oxygen meter was used to measure the dissolved oxygen concentration (DO). After the water samples were brought back to the laboratory, basic water quality indicators were immediately tested. Ammonia nitrogen (NH4 + -N), total phosphorus (TP), total nitrogen (TN), nitrite (NO2 - -N) and nitrate (NO3 - -N); TOC analyzer was used to measure soluble organic carbon (TOC).

[0043] The water samples from each sampling point were filtered through a 0.22 μm acetate filter membrane, and about 500 mL to 1 L of water was filtered from each water sample. The filter membrane was collected and stored in a refrigerator at -80 °C for future use. The DNA in the collected filter membrane was extracted using a DNA extraction kit, and the paired double-end 250 bp strategy was used for sequencing using the Illumina MiSeq sequencing platform: the target fragment was the V4 variable region of the bacterial 16S rRNA gene (about 253 bp), the universal forward primer was 515F (5'-GTGCCAGCMGCCGCGGTAA-3', SEQ ID NO.1), and the universal reverse primer was 806R (5'-GGACTACHVGGGTWTCTAAT-3', SEQ ID NO.2). Long primers with sample tags and sequencing-specific primers were synthesized based on the universal primers, and the target fragments were amplified from the DNA extracted above. The amplified products were recovered and purified using agarose gel, and then subjected to high-throughput sequencing after purification. The raw data obtained by sequencing were subjected to Reads quality control, splicing, filtering and ASV clustering to obtain bacterial community data, including bacterial community composition and abundance. The top 200 ASVs with the highest relative abundance were selected for correlation analysis, and the bacterial community data with a correlation coefficient of >0.8 and a p-value <0.05 with the environmental factor data were retained.

[0044] The water samples from each sampling point were filtered through a 0.22 μm acetate filter membrane. Each water sample was filtered for about 500 mL to 1 L of water. The filter membrane was collected and stored in a refrigerator at -80 °C for future use. The Illumina MiSeq sequencing platform was used, and the paired double-end 250 bp strategy was used for sequencing. The raw data was quality controlled using fastp software, and the bowtie2 was used to align with the host genome sequence to remove host contamination and obtain the optimized sequence. The software MEGAHIT was used for metagenomic assembly, and contig sequences shorter than 300 bp were filtered. CD-HIT software was used to cluster virus operational taxonomic units to obtain virus community data, including virus community composition and abundance. The top 200 virus sequences with the highest relative abundance were selected for correlation analysis, and virus community data with correlation coefficients > 0.8 and p values ​​< 0.05 with the environmental factor data were retained.

[0045] The retained bacterial community data and viral community data were subjected to co-occurrence network analysis using the Hmisc software package in R language to construct a co-occurrence network between the viral community and the bacterial community, and to obtain the dominant bacterial phyla significantly correlated with the viral community. By analyzing the species composition of the bacterial community and the viral community at the detection point, it is possible to determine what environmental factors affect the point and evaluate the river pollution.

[0046] Example 2

[0047] The method in Example 1 was used to evaluate river pollution in August 2023 and January 2024.

[0048] 1. Study area and sample collection

[0049] The Songhua River Basin is located in the northern part of Northeast China, with a basin area of ​​557,200 square kilometers and an annual runoff of 76.2 billion cubic meters. The basin is located in the northern temperate monsoon climate zone, with four distinct seasons, warm and rainy summers, cold and dry winters, and a large temperature difference throughout the year. The average temperature for many years is between 3 and 5°C. The highest temperature is in July, with a daily average of 20 to 25°C, and the highest temperature has reached more than 40°C. The annual precipitation is 800 to 1,000 mm; the annual average flow is 81.9 cubic meters per second. The Songhua River in Jilin Province is located at 41°44′~45°24′N, 124°26′~128°50′E, and is the southern source of the Songhua River. The total length of the river is 795 km, and the basin area is 78,180 km2. Ten national / provincially controlled sections (Renjiadian W1, Lijiatun W3, Lanqi Bridge W4, Jiuzhan W6, Shaokou W7, Xiaobaiqi W8, Songhuajiang Village W9, Zhenjiangkou W11, Ningjiang W13, and Songlin Village W14) of the Songhua River mainstream in Jilin Province were collected. W5 and W12 are the outlets of Jilin Wastewater Treatment Plant and Songyuan Wastewater Treatment Plant, respectively, and W2 and W10 are Huifa River and Yinma River, two important tributaries of the Songhua River Basin in Jilin Province. At each location, water samples were collected from 0.1 m below the water surface, and 3 parallel water samples were collected at each sampling point. At each location, a total volume of 12 L of surface water was collected into a fully rinsed sterile container. After collection, the samples were immediately transported to the laboratory, stored in the dark at 4 ° C, and tested within 1 to 3 days. The longitude and latitude information of each sampling point is shown in Table 1.

[0050] Table 1 Latitude and longitude information of each sampling point

[0051]

[0052]

[0053] 2.1 In August 2023 (summer), the test results of the physical and chemical properties of river water at each sampling point are shown in Table 2.

[0054] Table 2 Physical and chemical parameters of river water at each sampling point

[0055]

[0056] 2.2 In January 2024 (in winter, data from points W10 and W14 were not collected due to problems such as thick ice on the water surface), the test results of the physical and chemical properties of river water at each sampling point are shown in Table 2.

[0057] Table 2 Physical and chemical parameters of river water at each sampling point

[0058]

[0059] 3.1 Apply metagenomic sequencing to water samples to obtain viral community data, such as Figure 1 and Figure 6As shown in the figure, at the family level, Myoviridae, Siphoviridae and Podoviridae are dominant. These viruses are also common water virus families. The average abundance of viruses is from high to low: Myoviridae, Siphoviridae, Podoviridae. Among them, the algal DNA virus family (Phycodnaviridae), which uses eukaryotic algae as natural hosts, has a relatively stable relative abundance in the basin, and the relative abundance is slightly higher in the upstream, which is due to the high water temperature in the upstream basin, which is suitable for the survival of algae. At the same time, a type of giant virus of the Mimiviridae family was also detected in the samples, which can infect a variety of phytoplankton and protozoa, and its relative abundance is higher in downstream samples. From the perspective of different geographical locations, there are differences in the relative abundance of dominant virus species at the family level in the upstream and downstream of the basin. The relative abundance of Myoviridae and Algal DNA Viridae is relatively close in the upstream, the relative abundance of Longiviridae and unclassified viruses is higher in the middle and lower reaches than in the upstream, and the Brachyviridae is enriched in the upstream. Overall, most viruses are bacteriophages that infect bacteria. Generally speaking, the main stream has a fast flow rate, while the tributaries are in a relatively slow flow state, which is easy for microorganisms to gather and proliferate. However, due to the diversity of tributaries flowing into the main stream, the probability of rare microorganisms appearing in the main stream water increases.

[0060] The Sperman rank correlation test was used to test the correlation between species at the specific family level and environmental factors, such as Figure 2 and 7 As shown in the figure, the relative abundance of virus communities in winter and summer is positively correlated with environmental factors. This is due to the frequent microbial activities and vigorous metabolism in summer, while pollutants accumulate in winter, leading to the complexity and interrelationship of virus communities. In winter, river freezing has a certain impact on the lack of viral diversity, resulting in an increase in pollutants, which has caused a significant change in the correlation between environmental factors and viral communities. Among them, Myoviridae and Brachyviridae are significantly positively correlated with TOC, T, DO and ammonia nitrogen. Temperature changes lead to changes in viral abundance, indicating that river freezing has a significant impact on the correlation of viral species, and there are obvious seasonal changes.

[0061] 3.2 High-throughput sequencing of water samples using 16S rRNA gene sequencing technology was performed to obtain bacterial community data, such as Figure 3 and Figure 8As shown in the figure, the first dominant phylum in both winter and summer is Proteobacteria, because Proteobacteria contains a large number of phototrophic, chemoautotrophic and chemoheterotrophic bacteria, which can utilize pollutants such as nitrogen and phosphorus in rivers and have strong adaptability in various water environments. Secondly, the sum of Actinobacteria, Proteobacteria, Cyanobacteria and Bacteroidetes accounted for more than 53% in each sample, but the distribution of these phyla was different. In summer, with the increase of temperature, the dominant role of Bacteroidetes decreased, and the relative abundance of Cyanobacteria and Firmicutes increased significantly, because the thermophilic characteristics of cyanobacteria caused them to multiply in large numbers in summer.

[0062] The Sperman rank correlation test was used to test the correlation between species at a specific phylum level and environmental factors, such as Figure 4 and Fig. 9 The results showed that the strongest correlations in summer and winter were related to nitrate nitrogen and dissolved oxygen. Most bacterial phyla are nitrogen-fixing microorganisms, which promote nitrogen cycle in water bodies. At the same time, dissolved oxygen levels also affect the activity of microorganisms. At the phylum level, the relative abundance of Nitrospira in summer was negatively correlated with temperature (r=-0.71, p<0.01) and positively correlated with dissolved oxygen (r=0.7, p<0.01). This is because the water temperature is high in summer, and microorganisms grow more vigorously in nutrient-rich environments, which leads to large differences in microbial communities in different environments. In water bodies, if nitrifying bacteria are lacking, the ammonia nitrogen / nitrate / nitrite cycle system will be interrupted, which will lead to damage to the aquatic environment. At the same time, dissolved oxygen will also directly affect the changes in ammonia nitrogen concentration in water bodies. In winter samples, Bacteroidetes and Actinobacteria are dominant phyla compared to summer, accounting for about 22.5% of the total bacterial community. It may be due to the enhanced nitrification capacity of the system in winter, and Bacteroidetes plays a vital role in the nitrification of organic matter. In winter, temperature is the most important environmental factor affecting the microbial community in water bodies, and Fusobacteriota and others are suitable for survival in low temperature environments. TP is positively correlated with most bacterial phyla, which is conducive to the growth of microorganisms and causes a large number of microorganisms to reproduce. This is because the water body does not flow in winter, and a large amount of available phosphorus is easily accumulated in the water body. The results show that environmental driving factors can explain the differences in bacterial communities better than spatial scale.

[0063] 3.3 The symbiotic pattern between bacterial and viral communities was constructed based on correlation (Spearman|r|>0.8) and significance (p value<0.05), where the nodes and number reflect the complexity of the connection between bacterial and viral communities. Figure 5 and Fig.10 shown.

[0064] Depend on Figure 5 and Fig.10 It can be seen that the winter virus and bacterial meta-network have stronger correlations in winter than in summer, indicating their dominant role in bacterial and viral communities. At the same time, it shows a decreasing trend. This is because the rainfall in summer is large, the water body flows, and the winter is frozen, which leads to stronger correlations in winter nodes and closer viral associations. In both winter and summer, the positive correlation between viruses and bacteria is as high as more than 98%. There are some potential connections between viruses and bacterial hosts, indicating that this virus group has a wider host range. In winter, the tail bacteriophage phylum is significantly positively correlated with the planktonic bacteria phylum. While Urovircota (tail bacteriophage phylum) and NCLDV (nucleocytoplasmic large DNA virus) increase, actinomycetes, Bacteroidetes and Proteobacteria are also increasing. It can be predicted that Proteobacteria, Bacteroidetes, Planktonic bacteria, and Actinomycetes are the main sources of viral hosts associated with a large number of viruses.

[0065] From the above results, it can be seen that nitrate nitrogen, nitrite nitrogen, ammonia nitrogen, total nitrogen and total phosphorus in the water body are significantly positively correlated with the composition of microbial communities in different seasons, indicating that these environmental factors are the main reasons affecting the differences in the composition of bacterial and viral communities in river basins. It can be seen that environmental factors can indicate the pollution levels of river basins in different seasons, and corresponding environmental pollution prevention and control measures should be taken.

[0066] The present invention can know what kind of environmental factors affect the point by detecting the bacterial and viral community structure of the water body, and can provide technical support for the pollution management and prevention of river ecosystems. Based on the correlation (Spearman|r|>0.8) and significance (p value<0.05) with environmental factors, the present invention retains the bacterial community and the viral community, constructs the symbiotic model between the bacterial community and the viral community, and finds that the bacterial community and the viral community in the river basin, especially the planktonic bacteria and the tail phage, can provide effective monitoring and management means for the governance of the river.

[0067] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for evaluating river pollution, characterized in that: The method comprises the following steps: collecting water samples from multiple points in a river, obtaining environmental factor data, bacterial community data and viral community data of the water samples; performing correlation analysis on the environmental factor data with the bacterial community data and the viral community data, respectively, to obtain environmental factor data significantly correlated with the bacterial community and viral community composition, respectively; performing collinear network analysis on the bacterial community data and the viral community data, to obtain dominant bacterial phyla significantly correlated with the viral community; by analyzing the species composition of the bacterial community and the viral community at the detection point, it can be known what environmental factors affect the point, and the river pollution can be evaluated.

2. The method according to claim 1, characterized in that: The environmental factor data include water temperature, pH, dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, total nitrogen concentration, nitrite concentration, nitrate concentration and dissolved organic carbon concentration.

3. The method according to claim 1, characterized in that The bacterial community data and viral community data with a correlation coefficient greater than 0.6 and a p value less than 0.05 with the environmental factor data were retained for co-occurrence network analysis.

4. The method according to claim 1, characterized in that The DNA of the water sample is extracted and subjected to high-throughput sequencing analysis and metagenomic sequencing analysis.

5. The method according to claim 4, characterized in that ASV clustering analysis was performed on the data from high-throughput sequencing analysis to obtain bacterial community data.

6. The method according to claim 5, characterized in that The similarity level adopted in the ASV cluster analysis was above 97%.

7. The method according to claim 4, characterized in that Votus cluster analysis was performed on the data from metagenomic sequencing analysis to obtain viral community data.

8. The method according to claim 4, characterized in that The similarity level adopted by the Votus cluster analysis was above 97%.

9. The method according to claim 1, characterized in that: The number of collection points for the water samples is ≥10.

10. Use of the method according to any one of claims 1 to 9 in river pollution control.

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