Surface water nitrate nitrogen microbial fingerprint tracing method

Abstract

The invention provides a surface water nitrate nitrogen microorganism fingerprint tracing method which comprises the following steps: collecting a surface water sample of a target drainage basin to obtain a water body sample; determining a nitrogen isotope ratio and an oxygen isotope ratio of the water body sample; sequencing the microbial barcode of the water body sample; based on the nitrogen isotope ratio and the oxygen isotope ratio, calculating contribution rates of different nitrogen pollution source groups by adopting a Bayesian isotope mixed model, and grouping the contribution rates of different nitrogen pollution sources; calculating different indicator species indexes of each group through an R language operation indicspecies program package so as to screen out indicator species, and constructing a nitrogen pollution source microbiological map according to the microbiological bar code; and obtaining microorganisms indicating nitrogen pollution sources in surface water according to the nitrogen pollution source microbial map. According to the invention, the traceability precision is improved, and the cost can be reduced.

Description

Technical Field

[0001] The invention relates to the technical field of nitrogen and oxygen isotope tracing, and in particular to a method for tracing the nitrate nitrogen microbial fingerprint of surface water. Background Art

[0002] Excessive nitrogen compounds entering the environment aquatic ecosystems can cause a rapid increase in nitrate nitrogen concentrations in surface waters within the basin, resulting in nitrate pollution of surface waters. It can lead to a rapid increase in toxic algae, known as algal blooms (or red tides), which deplete oxygen in the water and can cause dead zones that affect underwater life, making it a top priority to analyze the source of nitrogen pollution.

[0003] There are many sources of nitrogen in surface water, among which the most concerned is the tracing of nitrate pollution. Due to the overlap of nitrogen isotope ratios from different nitrate sources, people have begun to use nitrogen-oxygen dual isotope methods and end-member mixing models in recent years to more accurately determine the source of nitrate and study its biogeochemical process. With the development of science and technology and the proposal of precise pollution control, qualitative analysis of the source of nitrogen in water bodies can no longer meet the needs of environmental management. Scholars choose to use isotope technology combined with model quantitative technology to obtain the contribution rate of various pollution sources, commonly used are IsoSource, SIAR (stable isotope source analysis model), etc. However, it is suitable for large-scale basins, and the tracing accuracy is relatively small.

[0004] Pollution sources have unique biological barcode characteristics. Currently, SourceTracker microbial sources are widely used to analyze the sources of river pollutants and the contribution of surrounding factories, farmland, and aquaculture plants to river pollution. Microbial barcodes cannot be used to couple biological characteristics with nitrogen pollution sources, and microbial characteristics undergo biogeochemical processes after the pollution source water enters the surface water. Therefore, it is necessary to screen out surface water indicator microbial fingerprints that can indicate different nitrogen pollution sources, providing new methods and ideas for tracing the source of nitrate nitrogen pollution in surface water.

[0005] The existing nitrogen and oxygen isotope traceability technology is cumbersome and has low traceability accuracy. It is even unable to distinguish the source when facing small watersheds or plain river network areas; microbial fingerprint traceability can only indicate the relationship between the pollution source and the microorganisms between the monitored surface water samples, and is not associated with nitrogen pollution. Summary of the invention

[0006] In order to overcome the deficiencies of the prior art, the present invention aims to provide a method for tracing the microbial fingerprint of nitrate nitrogen in surface water.

[0007] To achieve the above object, the present invention provides the following solutions:

[0008] A method for tracing the microbial fingerprint of nitrate nitrogen in surface water, comprising:

[0009] Collect surface water samples from the target watershed to obtain water samples;

[0010] Determining the nitrogen isotope ratio and the oxygen isotope ratio of the water sample;

[0011] Sequencing the microbial barcode of the water sample;

[0012] Based on the nitrogen isotope ratio and the oxygen isotope ratio, the contribution rates of different nitrogen pollution source groups are calculated using a Bayesian isotope mixing model, and the contribution rates of different nitrogen pollution sources are grouped;

[0013] The indicespecies package of R language is used to calculate the different indicator species indexes of each group to screen out the indicator species, and a microbial map of nitrogen pollution sources is constructed according to the microbial barcodes;

[0014] Microorganisms indicating the source of nitrogen pollution in surface water are obtained according to the nitrogen pollution source microbial map.

[0015] Preferably, determining the nitrogen isotope ratio and the oxygen isotope ratio of the water sample comprises:

[0016] Take 20 mL of the water sample in a 40 mL headspace bottle, add 0.1 mL CdCl2 solution, then add 0.8 mL NH4Cl solution, and finally add 3 × 10 cm 4N clean zinc sheet, and shake on a shaker at 220 r / min for 15 min;

[0017] Remove the zinc sheet, seal the headspace bottle, and complete the NO2- reduction step;

[0018] Add 1 mL of a 1:1 mixture of NaN3 solution and CH3COOH to the headspace bottle after NO2- reduction, and shake vigorously to mix the sample and reagent. Then oscillate at 220 r / min for 30 min, and finally add 0.6 mL of NaOH solution as a terminator to end the azidation reaction;

[0019] The nitrogen isotope ratio and oxygen isotope ratio of N2O gas were tested online using Gas-Bench-stable isotope mass spectrometer.

[0020] Preferably, sequencing the microbial barcode of the water sample comprises:

[0021] The total genomic DNA from water samples was extracted using the CTAB / SDS method;

[0022] Different regions of 16S rRNA / 18SrRNA / ITS genes were amplified using specific primers and barcodes;

[0023] An equal volume of 1X loading buffer was mixed with the PCR product and electrophoresed on a 2% agarose gel for DNA detection;

[0024] use Ultra TM IIDNA library preparation kit to generate sequencing libraries;

[0025] Paired reads were assigned to water samples based on barcodes and barcode and primer sequences were truncated by cutting off the barcode and primer sequences;

[0026] Use fastp software to perform quality filtering on raw tags to obtain high-quality clean tags;

[0027] Use Vsearch to compare the clean tags with the reference database to detect chimeric sequences and remove them to obtain valid tags;

[0028] For the obtained valid labels, denoising was performed using the DADA2 or deblur module in the QIIME2 software;

[0029] QIIME2 software was used for species annotation and multiple sequence alignment;

[0030] Data Normalization

[0031] The absolute abundance of amplicon sequence variants was normalized using the sequence number as the standard, corresponding to the sample with the fewest sequences.

[0032] Preferably, based on the nitrogen isotope ratio and the oxygen isotope ratio, the contribution rates of different nitrogen pollution source groups are calculated using a Bayesian isotope mixing model, and the contribution rates of different nitrogen pollution sources are grouped, including:

[0033] Denote the delta of nitrate by δ 15 N-NO3- and δ 18 O-NO3- isotope, and calculated according to the following formula:

[0034] δ(‰)=(R 样品 / R 标准 -1)×1000;

[0035] Among them, R 样品 and R 标准 Respectively represent the N / N or O / O ratio of the sample / standard sample, i.e. δ1514181615N-NO3- and δ 18 O-NO3-; N isotope uses atmospheric nitrogen (N2) as the reference standard; O isotope uses Vienna standard average seawater;

[0036] The Bayesian isotope mixing model was run in R language to quantify the proportional contribution of potential NO3--N sources to surface water.

[0037] Divide into multiple groups according to the maximum proportional contribution.

[0038] Preferably, the formula of the Bayesian isotope mixing model is: Among them, X ij represents the value of isotope j of mixture i, where i = 1, 2, 3 ... N and j = 1, 2, 3 ... J; p k represents the contribution ratio of source k, calculated by the SIAR model; S jk represents the value of isotope j in source k, k = 1, 2, 3, ..., K, with an average value of μ jk ; Standard deviation is Normal distribution; C jk represents the fractionation factor of isotope j on source k, and its normal distribution is average value λ jk and standard deviation τ jk ; εjk represents the residual error, which is the variable that cannot be determined between individual mixtures, and has a mean of 0 and a standard deviation of σ j The normal distribution of .

[0039] Preferably, the indicspecies package has two value-added features, including obtaining confidence intervals for indicator values ​​by bootstrapping and sequentially selecting appropriate indicator species by trying all taxonomic group combinations.

[0040] Preferably, the target watershed includes rivers, lakes and seas.

[0041] Preferably, the multiple groups divided according to the maximum proportional contribution specifically include: a fertilizer source group, a soil nitrogen source group, and a domestic sewage and feces source group.

[0042] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0043] The present invention provides a surface water nitrate nitrogen microbial fingerprint tracing method, comprising: collecting surface water samples in a target watershed to obtain water samples; determining the nitrogen isotope ratio and oxygen isotope ratio of the water samples; sequencing the microbial barcodes of the water samples; based on the nitrogen isotope ratio and the oxygen isotope ratio, using a Bayesian isotope mixing model to calculate the contribution rates of different nitrogen pollution source groups, and grouping the contribution rates of different nitrogen pollution sources; calculating different indicator species indexes of each group by using the indicspecies program package in R language to screen out indicator species, and constructing a nitrogen pollution source microbial map according to the microbial barcode; obtaining microorganisms indicating the source of nitrogen pollution in surface water according to the nitrogen pollution source microbial map. The present invention can reduce costs while improving the accuracy of tracing. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0045] Figure 1 A flow chart of a method provided by an embodiment of the present invention;

[0046] Figure 2 A schematic diagram of indicator species of fertilizer pollution sources during the dry season provided by an embodiment of the present invention;

[0047] Figure 3 A schematic diagram of indicator species of fertilizer pollution sources during the flood season provided by an embodiment of the present invention;

[0048] Figure 4 Indicator species for domestic sewage and feces pollution sources during the dry season provided in an embodiment of the present invention;

[0049] Figure 5 Indicator species for domestic sewage and feces pollution sources during the flood season provided by the embodiment of the present invention;

[0050] Figure 6 The dry season soil nitrogen source indicator species provided by the embodiment of the present invention;

[0051] Figure 7 A schematic diagram of indicator species for soil nitrogen sources during the flood season provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] Figure 1 A flow chart of a method provided by an embodiment of the present invention, such as Figure 1 As shown, the present invention provides a method for tracing the microbial fingerprint of nitrate nitrogen in surface water, comprising:

[0055] Step 100: Collect surface water samples in the target watershed to obtain water samples;

[0056] Step 200: Determine the nitrogen isotope ratio and oxygen isotope ratio of the water sample;

[0057] Step 300: sequencing the microbial barcode of the water sample;

[0058] Step 400: Based on the nitrogen isotope ratio and the oxygen isotope ratio, using a Bayesian isotope mixing model to calculate the contribution rates of different nitrogen pollution source groups, and grouping the contribution rates of different nitrogen pollution sources;

[0059] Step 500: Calculate the different indicator species indexes of each group by using the indicspecies program package of R language to screen out the indicator species, and construct a microbial map of nitrogen pollution sources according to the microbial barcodes;

[0060] Step 600: Obtain microorganisms indicating the source of nitrogen pollution in surface water according to the nitrogen pollution source microbial map.

[0061] The technical route of this embodiment specifically includes the following steps:

[0062] Step 1: According to the industrial distribution and land use in the study area, surface water samples were collected, including 54 nitrogen and oxygen isotope samples and 156 microbial samples;

[0063] Step 2 is as follows:

[0064] (1) Determination of nitrogen and oxygen isotope values ​​of water samples:

[0065] Take 20mL in a 40mL headspace bottle, add 0.1mL CdCl2 solution (20g / L), then add 0.8mL NH4Cl solution (250g / L), and finally add 3×10cm 4N (or 3N) clean zinc sheet (wiped clean with alcohol), and shake on a shaker at 220r / min for 15min (full reaction). Take out the zinc sheet, seal the headspace bottle, and complete the NO2- reduction step. Add 1mL of a 1:1 mixture of NaN3 solution (2mol / L) and CH3COOH (20%) to the headspace bottle after NO2- reduction, and shake vigorously to mix the sample and reagent. Then shake at 220r / min for 30min (full reaction), and finally add 0.6mL of NaOH solution (6mol / L) as a terminator (the solution is alkaline, which is not conducive to the azidation reaction) to end the azidation reaction.

[0066] The nitrate is converted into N2O gas through the above chemical process reaction, and the nitrogen and oxygen isotope values ​​of N2O gas are tested online by Gas-Bench-stable isotope mass spectrometer. In the adoption mode, cold trap No. 1 is placed in liquid nitrogen, and the N2O in the sample is injected by the PAL automatic sampler, and then it is frozen and enriched in cold trap No. 1 after removing water and CO2 through the external chemical trap of magnesium perchlorate and caustic soda lime. The purge time is 350S (the purge time can be adjusted according to the concentration of N2O). 10s before the end of the purge, cold trap No. 2 is immersed in liquid nitrogen in advance, and then the eight-way valve is switched to the injection mode, and then the first cold trap leaves the liquid nitrogen tank. After the frozen and fixed N2O is released, it is transferred to cold trap No. 2 by the low-flow He gas flow (about 7cm3 / min) and frozen again. The freezing enrichment time is 95s. Afterwards, the No. 2 cold trap was extracted from the liquid nitrogen, the N2O in the capillary was vaporized, and sent into the chromatographic column by low-flow He gas for further separation and purification, and then brought into the IRMS by helium gas to determine the nitrogen isotope ratio.

[0067] Data processing

[0068] δ 15 N air The value is based on nitrogen in air as the reference standard, δ 15 N air The value is calculated using the following formula:

[0069]

[0070] In the formula, δ 15 N Air It is the difference in thousandths between the nitrogen stable isotope ratio of the sample and the stable nitrogen isotope ratio of the reference material air;

[0071] R( 15 N / 14 N sample ) is the nitrogen isotope abundance ratio in the sample

[0072] R( 15 N / 14 N air ) is the nitrogen isotope abundance ratio of nitrogen in the air.

[0073] δ 15 The analytical accuracy of N value is ±0.3‰.

[0074] δ 18 O SMOW The value is based on SMOW as the reference standard, δ 18 O SMOW The value is calculated using the following formula:

[0075]

[0076] In the formula, δ 18 O SMOW It is the thousandth difference of the oxygen stable isotope ratio of the sample relative to the stable oxygen isotope ratio of the average ocean water of the reference material standard;

[0077] R( 18 O / 16 O sample ) is the oxygen isotope abundance ratio in the sample

[0078] R( 18 O / 16 O SMOW ) is the oxygen isotope abundance ratio in standard average seawater.

[0079] δ 18 The analytical accuracy of O value is 0.3‰.

[0080] Data Quality:

[0081] Nitrogen isotopes in nitrate (δ 15 N)STD<0.3(5); oxygen isotope (δ 18 O)STD<0.3(5)

[0082] (2) Sequencing microbial barcodes of water samples:

[0083] 1) Extraction of genomic DNA

[0084] Extraction of genomic DNA The total genomic DNA in the sample was extracted using the CTAB / SDS method. The DNA content and purity were monitored by 1% agarose gel. Depending on the concentration, the DNA was diluted to 1 ng / μL and sterile water was added.

[0085] 2) Generation of Amplicon

[0086] Different regions of 16S rRNA / 18SrRNA / ITS genes (16S V4 / 16S V3 / 16S V3-V4 / 16SV4-V5, 18S V4 / 18S V9, ITS1 / ITS2, Arc V4) were amplified using specific primers (e.g. 16S V4: 515F-806R, 18S V4: 528F-706R, 18S V9: 1380F-1510R, etc.) and barcodes. All PCR films contained 15 μL of High-fidelity PCR master mix (New England Biolabs), 0.2 μM of each primer and 10 ng of target DNA. For each primer and 10 ng of target DNA, the cycling conditions included: first denaturation at 98°C for 1 min. The cycling conditions were: first denaturation at 98°C for 1 min, then 30 cycles at 98°C (10 s), 50°C (30 s), and 72°C (30 s), and finally extension at 72°C for 5 min. Finally extension at 72°C for 5 min.

[0087] 3) Quantification and identification of PCR results

[0088] An equal volume of 1X loading buffer (containing SYB green) was mixed with the PCR product and electrophoresed on a 2% agarose gel for DNA detection. The PCR product was then purified using the Qiagen Gel Extraction Kit (Qiagen, Germany).

[0089] 4) Library preparation and sequencing

[0090] Follow the manufacturer's recommendations. Ultra TM IIDNA library preparation kit (CatNo.E7645) was used to generate sequencing libraries. The quality of the libraries was assessed on a Qubit@2.0 fluorometer (Thermo Scientific) and an Agilent Bioanalyzer 2100 system. Finally, the libraries were sequenced on an Illumina NovaSeq platform, generating 250 bp paired-end reads.

[0091] 5) Data segmentation

[0092] Paired reads were assigned to samples based on their unique barcodes and truncated by cutting off the barcode and primer sequences. 1.2 Merging of paired reads FLASH (version 1.2.11, http: / / ccb.jhu.edu / software / FLASH / ) was used, which is a very fast and accurate analysis tool designed to merge paired reads when at least some of the paired reads overlap with other paired reads. FLASH (version 1.2.11) was used to merge when at least some of the reads overlapped with reads generated from the other end of the same DNA fragment. The spliced ​​sequences are called raw tags.

[0093] 6) Data Filtering

[0094] The raw tags were quality filtered using fastp (version 0.20.0) software to obtain high-quality clean tags.

[0095] 7) Removal of chimeras

[0096] The clean tags were compared with reference databases (Silva database for 16S / 18S https: / / www.arb-silva.de / , Unite database for ITS https: / / unite.ut.ee / ) using Vsearch (version 2.15.0) to detect chimeric sequences, which were then removed to obtain valid tags.

[0097] 8) ASVs denoising

[0098] For the valid tags obtained previously, denoising was performed using the DADA2 or deblur module in the QIIME2 software. The module was used for denoising (QIIME2-202006 version) to obtain the initial ASVs (Amplicon sequence variations) (default: DADA2), and then ASVs with an abundance of less than 5 were filtered out.

[0099] 9) Species annotation

[0100] Species annotation was performed using QIIME2 software. For 16S / 18S, the annotation database was the Silva database, while for ITS, the annotation database was the Unite database.

[0101] 10) Construction of phylogenetic relationships

[0102] In order to study the phylogenetic relationships of each ASV and the differences in dominant species among different samples (groups), multiple sequence alignment was performed using QIIME2 software.

[0103] 11) Data Normalization

[0104] The absolute abundance of ASVs was normalized using the sequence number as the standard, corresponding to the sample with the fewest sequences.

[0105] Step 3: Express δ of nitrate as δ 15 N-NO3- and δ 18 O-NO3- isotope, and calculated according to the following formula: δ(‰) = (R sample / R standard-1) × 1000 R sample and R standard represent the N / N or O / O ratio of sample / standard sample, i.e. δ1514181615N-NO3- and δ 18 O-NO3-; N isotopes are based on atmospheric nitrogen (N2) as the reference standard; O isotopes use Vienna Standard Mean Seawater (V-SMOW); By using the R language to calculate the Bayesian isotope mixing model (MixSIAR), the proportional contribution of potential NO 3--N sources to surface water can be quantified. The model is expressed as: 1. In the formula: X ij represents the δ value of isotope j in mixture i; P k represents the proportion of source k; S jk represents the δ value of the jth isotope from the kth source, which follows a normal distribution with a mean of 2 and a variance of 1; C jk represents the fractionation coefficient of the j isotope from the kth source, which follows a normal distribution with a mean of λ and a variance of τ; ε is the residual error, which represents the variance that cannot be quantified between other mixtures, and its mean and standard deviation are usually 0;

[0106] According to the maximum contribution rate, they were divided into fertilizer source group, soil nitrogen source group and domestic sewage and feces source group;

[0107] The indicespecies package in R can be used to calculate the indicator species index for each group. The indicspecies package has two features that are worth mentioning: obtaining the confidence interval of the indicator value through the bootstrap method (obtained by setting the nbootcans parameter in the strassoc() function) and selecting the appropriate indicator species by continuously trying all taxonomic group combinations (function multipatt())

[0108] Finally, the indicator species of nitrate nitrogen grouping were screened and the microbial atlas of nitrate nitrogen pollution sources was constructed. A total of 6 groups of microbial atlases of nitrogen sources in the dry season and the wet season were screened out, such as Figures 2 to 7shown.

[0109] The contribution rates of different sources of nitrogen pollution were calculated using the MixSIAR model. The results were grouped and the indicator microbial species of each group were calculated to obtain microorganisms that indicate the sources of nitrogen pollution in surface water.

[0110] The beneficial effects of the present invention are as follows:

[0111] The present invention makes up for the shortcomings of low precision and high cost of nitrogen and oxygen isotope traceability technology; it associates microbial traceability technology with nitrate nitrogen pollution, and efficiently uses microbial indicator species to indicate the source of nitrogen pollution, thereby improving the accuracy of nitrogen pollution traceability, enhancing traceability efficiency, and reducing work costs.

[0112] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0113] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for tracing the origin of nitrate nitrogen in surface water by microbial fingerprint, characterized in that: include: Collect surface water samples from the target watershed to obtain water samples; Determining the nitrogen isotope ratio and the oxygen isotope ratio of the water sample; Sequencing the microbial barcode of the water sample; Based on the nitrogen isotope ratio and the oxygen isotope ratio, the contribution rates of different nitrogen pollution source groups are calculated using a Bayesian isotope mixing model, and the contribution rates of different nitrogen pollution sources are grouped; The indicespecies package of R language is used to calculate the different indicator species indexes of each group to screen out the indicator species, and a microbial map of nitrogen pollution sources is constructed according to the microbial barcodes; Microorganisms indicating the source of nitrogen pollution in surface water are obtained according to the nitrogen pollution source microbial map.

2. The method for tracing the nitrate nitrogen microbial fingerprint of surface water according to claim 1, characterized in that: Determining the nitrogen isotope ratio and the oxygen isotope ratio of the water sample, including: Take 20 mL of the water sample in a 40 mL headspace bottle, add 0.1 mL CdCl2 solution, then add 0.8 mL NH4Cl solution, and finally add 3 × 10 cm 4N clean zinc sheet, and shake on a shaker at 220 r / min for 15 min; Remove the zinc sheet, seal the headspace bottle, and complete the NO2- reduction step; Add 1 mL of a 1:1 mixture of NaN3 solution and CH3COOH to the headspace bottle after NO2- reduction, and shake vigorously to mix the sample and reagent. Then oscillate at 220 r / min for 30 min, and finally add 0.6 mL of NaOH solution as a terminator to end the azidation reaction; The nitrogen isotope ratio and oxygen isotope ratio of N2O gas were tested online using Gas-Bench-stable isotope mass spectrometer.

3. The method for tracing the nitrate nitrogen microbial fingerprint of surface water according to claim 1, characterized in that: Sequencing the microbial barcode of the water sample, including: The total genomic DNA from water samples was extracted using the CTAB / SDS method; Different regions of 16S rRNA / 18SrRNA / ITS genes were amplified using specific primers and barcodes; An equal volume of 1X loading buffer was mixed with the PCR product and electrophoresed on a 2% agarose gel for DNA detection; use Ultra TM IIDNA library preparation kit to generate sequencing libraries; Paired reads were assigned to water samples based on barcodes and barcode and primer sequences were truncated by cutting off the barcode and primer sequences; Use fastp software to perform quality filtering on raw tags to obtain high-quality clean tags; Use Vsearch to compare the clean tags with the reference database to detect chimeric sequences and remove them to obtain valid tags; For the obtained valid labels, denoising was performed using the DADA2 or deblur module in the QIIME2 software; QIIME2 software was used for species annotation and multiple sequence alignment; Data Normalization The absolute abundance of amplicon sequence variants was normalized using the sequence number as the standard, corresponding to the sample with the fewest sequences.

4. The method for tracing the nitrate nitrogen microbial fingerprint of surface water according to claim 1, characterized in that: Based on the nitrogen isotope ratio and the oxygen isotope ratio, the contribution rates of different nitrogen pollution source groups are calculated using the Bayesian isotope mixing model, and the contribution rates of different nitrogen pollution sources are grouped, including: Denote the delta of nitrate by δ 15 N-NO3- and δ 18 O-NO3- isotope, and calculated according to the following formula: δ(‰)=(R 样品 / R 标准 -1)×1000; Among them, R 样品 and R 标准 Respectively represent the N / N or O / O ratio of the sample / standard sample, i.e. δ1514181615N-NO3- and δ 18 O-NO3-; N isotope uses atmospheric nitrogen (N2) as the reference standard; O isotope uses Vienna standard average seawater; The Bayesian isotope mixing model was run in R language to quantify the proportional contribution of potential NO3--N sources to surface water. Divide into multiple groups according to the maximum proportional contribution.

5. The method for tracing the nitrate nitrogen microbial fingerprint of surface water according to claim 4, characterized in that: The formula for the Bayesian isotope mixing model is: Among them, X ij represents the value of isotope j of mixture i, where i = 1, 2, 3 ... N and j = 1, 2, 3 ... J; p k represents the contribution ratio of source k, calculated by the SIAR model; S jk represents the value of isotope j in source k, k = 1, 2, 3, ..., K, with an average value of μ jk ; Standard deviation is Normal distribution; C jk represents the fractionation factor of isotope j on source k, and its normal distribution is average value λ jk and standard deviation τ jk ; εjk represents the residual error, which is the variable that cannot be determined between individual mixtures, and has a mean of 0 and a standard deviation of σ j The normal distribution of .

6. The method for tracing the nitrate nitrogen microbial fingerprint of surface water according to claim 1, characterized in that: The indicspecies package has two important features, including bootstrapping to obtain confidence intervals for indicator values ​​and sequential selection of appropriate indicator species by trying all possible combinations of taxonomic groups.

7. The method for tracing the nitrate nitrogen microbial fingerprint of surface water according to claim 1, characterized in that: The target watershed includes rivers, lakes and seas.

8. The method for tracing the nitrate nitrogen microbial fingerprint of surface water according to claim 4, characterized in that: The multiple groups divided according to the maximum proportional contribution include: fertilizer source group, soil nitrogen source group and domestic sewage and feces source group.

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