A method for tracing the microbial fingerprint of nitrate nitrogen in surface water

Abstract

This invention provides a method for tracing the source of nitrate nitrogen in surface water using microbial fingerprinting, comprising: collecting surface water samples from 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; calculating the contribution rate of different nitrogen pollution source groups based on the nitrogen and oxygen isotope ratios using a Bayesian isotope mixture model, and grouping the contribution rates of different nitrogen pollution sources; calculating different indicator species indices for each group using the R language indicespecies package to screen indicator species, and constructing a nitrogen pollution source microbial map based on the microbial barcodes; and obtaining the microorganisms indicating the sources of nitrogen pollution in surface water based on the nitrogen pollution source microbial map. This invention improves the accuracy of source tracing while reducing costs.

Description

Technical Field

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

[0002] Excessive nitrogen compounds entering the aquatic ecosystem can rapidly increase nitrate nitrogen concentrations in surface waters within a watershed, leading to nitrate pollution. This can cause a rapid increase in toxic algae, known as algal blooms (or red tides), which deplete oxygen in the water and can create dead zones affecting aquatic life. Therefore, conducting source apportionment analysis for nitrogen pollution is of paramount importance.

[0003] Nitrogen in surface water originates from many sources, with nitrate pollution being the most concerning. Due to overlapping nitrogen isotope ratios among different nitrate sources, researchers have recently begun using nitrogen-oxygen dual isotope methods and end-member mixing models to more accurately determine nitrate sources and study their biogeochemical processes. With technological advancements and the advocacy of precision pollution control, qualitative analysis of nitrogen sources in water bodies is no longer sufficient for environmental management needs. Scholars have opted to combine isotope techniques with quantitative modeling techniques to obtain the contribution rates of various pollution sources, commonly using IsoSource and SIAR (Stable Isotope Source Apportionment Model). However, these methods are suitable for large-scale watersheds, and their source tracing accuracy is relatively low.

[0004] Pollution sources possess unique bio-barcode characteristics. Currently, SourceTracker microbial source analysis is widely used to analyze the origins of river pollutants and the contributions of surrounding factories, farmland, and aquaculture farms to river pollution. However, microbial barcoding cannot couple biological characteristics with nitrogen pollution sources for analysis. Furthermore, microbial characteristics undergo biogeochemical processes after polluted water bodies enter surface water. Therefore, it is necessary to screen for surface water indicator microbial fingerprint profiles that can indicate different nitrogen pollution sources, providing new methods and approaches for tracing the sources of nitrate nitrogen pollution in surface water.

[0005] Existing nitrogen and oxygen isotope source tracing technologies are cumbersome to measure and have low accuracy, and they cannot even distinguish the source when dealing with small watersheds or plain river network areas; microbial fingerprinting can only indicate the relationship between the pollution source and the microorganisms in the monitored surface water sample, and is not related to nitrogen pollution. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, the purpose of this invention is to provide a method for tracing the microbial fingerprint of nitrate nitrogen in surface water.

[0007] To achieve the above objectives, the present invention provides the following solution:

[0008] A method for tracing the source of nitrate nitrogen in surface water using microbial fingerprinting includes:

[0009] Surface water samples were collected from the target watershed to obtain water samples;

[0010] The nitrogen isotope ratio and oxygen isotope ratio of the water sample were determined.

[0011] Sequencing the microbial barcodes of the water samples;

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

[0013] The indexes of different indicator species in each group were calculated using the indicspecies package in R language to screen out indicator species, and a microbial map of nitrogen pollution sources was constructed based on the microbial barcodes.

[0014] Based on the aforementioned microbial map of nitrogen pollution sources, microorganisms indicating the sources of nitrogen pollution in surface water were obtained.

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

[0016] Take 20 mL of the water sample into a 40 mL headspace vial, add 0.1 mL of CdCl2 solution, then add 0.8 mL of NH4Cl solution, and finally add 3 × 10 cm 4N clean zinc sheets. 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 vial after NO2- reduction, and shake vigorously to mix the sample and reagents. Then shake at 220 r / min for 30 min, and finally add 0.6 mL of NaOH solution as a terminator to end the azide reaction;

[0019] The nitrogen and oxygen isotope ratios of N2O gas were measured online using a Gas-Bench-Stable Isotope Mass Spectrometer.

[0020] Preferably, sequencing the microbial barcodes of the water sample includes:

[0021] Total genomic DNA was extracted from water samples using the CTAB / SDS method.

[0022] 16S rRNA / 18S rRNA / ITS genes from different regions were amplified using specific primers and barcodes;

[0023] Mix an equal volume of 1X loading buffer with the PCR product, perform electrophoresis on a 2% agarose gel, and then perform DNA detection.

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

[0025] The barcodes are used to assign paired readings to water samples, and the barcodes and primer sequences are truncated by cutting them apart.

[0026] Use FastP software to quality filter the raw labels to obtain high-quality clean labels;

[0027] Vsearch is used to compare clean labels with a reference database to detect chimeric sequences, remove chimeric sequences, and obtain valid labels.

[0028] For the obtained valid tags, noise reduction is performed using the DADA2 or deblur module in the QIIME2 software.

[0029] Species annotation and multiple sequence alignment were performed using the QIIME2 software.

[0030] Data normalization

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

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

[0033] Let δ represent the δ of nitrate. 15 N-NO3- and δ 18 O-NO3- isotopes, 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 These represent the N / N or O / O ratios of the sample / standard sample, respectively, i.e., δ1514181615N-NO3- and δ 18 O-NO3-; N isotopes use atmospheric nitrogen (N2) as a reference standard; O isotopes use the Vienna standard mean seawater;

[0036] The proportionate contribution of potential NO3-N sources to surface water was quantified by using a Bayesian isotope mixing model in R language.

[0037] They are divided into multiple groups based on the maximum proportional contribution.

[0038] Preferably, the formula for the Bayesian isotope mixing model is: Among them, X ij The value of isotope j in mixture i represents the value of isotope j, where i = 1, 2, 3…N and j = 1, 2, 3…J; p k S represents the contribution ratio of source k, calculated by the SIAR model; jk This represents the value of isotope j in source k, where k = 1, 2, 3, ..., K, and the average value is μ. jk The standard deviation is The normal distribution of C; jk The fractionation factor of isotope j at source k is represented by the normal distribution with average value λ. jk and standard deviation τ jk εjk represents the residual error, which is an undetermined variable among individual mixtures, and follows a mean of 0 and a standard deviation of σ. j It follows a normal distribution.

[0039] Preferably, the indicspecies package has two value-referenced features, including obtaining the confidence interval of the indicator value through bootstrapping and selecting the appropriate indicator species by iteratively trying all taxonomic 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: fertilizer source group, soil nitrogen source group, and domestic sewage and feces source group.

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

[0043] This invention provides a method for tracing the source of nitrate nitrogen in surface water using microbial fingerprinting, comprising: collecting surface water samples from 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; calculating the contribution rate of different nitrogen pollution source groups based on the nitrogen and oxygen isotope ratios using a Bayesian isotope mixture model, and grouping the contribution rates of different nitrogen pollution sources; calculating different indicator species indices for each group using the R language indicespecies package to screen indicator species, and constructing a nitrogen pollution source microbial map based on the microbial barcodes; and obtaining the microorganisms indicating the sources of nitrogen pollution in surface water based on the nitrogen pollution source microbial map. This invention improves the accuracy of source tracing while reducing costs. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 A flowchart of the method provided in an embodiment of the present invention;

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

[0047] Figure 3 A schematic diagram of indicator species for fertilizer pollution sources during the high-water season provided in an embodiment of the present invention;

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

[0049] Figure 5 Indicator species for domestic sewage and fecal pollution sources during the high-water season provided in this embodiment of the invention;

[0050] Figure 6 Indicator species for soil nitrogen sources during dry seasons provided in embodiments of the present invention;

[0051] Figure 7 A schematic diagram of soil nitrogen source indicator species during the wet season provided in an embodiment of the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] Figure 1 The method flowchart provided in the embodiments of the present invention is as follows: Figure 1 As shown, this invention provides a method for tracing the source of nitrate nitrogen in surface water using microbial fingerprinting, comprising:

[0055] Step 100: Collect surface water samples from 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 barcodes of the water sample;

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

[0059] Step 500: Calculate the index of different indicator species for each group using the indicspecies package in R language to screen out indicator species, and construct a microbial map of nitrogen pollution sources based on the microbial barcodes;

[0060] Step 600: Obtain microorganisms indicating the sources of nitrogen pollution in surface water based on the aforementioned microbial map of nitrogen pollution sources.

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

[0062] Step 1: Based on the industrial distribution and land use of the study area, surface water samples were collected from the watershed, including 54 nitrogen and oxygen isotope samples and 156 microbial samples.

[0063] Step 2 is as follows:

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

[0065] Take 20 mL of the solution and add it to a 40 mL headspace vial. Add 0.1 mL of CdCl2 solution (20 g / L), then add 0.8 mL of NH4Cl solution (250 g / L), and finally add a 3 × 10 cm 4N (or 3N) clean zinc sheet (wiped clean with alcohol). Shake on a shaker at 220 rpm for 15 min (to ensure complete reaction). Remove the zinc sheet, seal the headspace vial, and complete the NO2- reduction step. Add 1 mL of a 1:1 mixture of NaN3 solution (2 mol / L) and CH3COOH (20%) to the NO2--reduced headspace vial, and shake vigorously to mix the sample and reagents. Shake at 220 rpm for 30 min (to ensure complete reaction), and finally add 0.6 mL of NaOH solution (6 mol / L) as a terminator (the solution is alkaline, which is unfavorable for the azidation reaction) to end the azidation reaction.

[0066] The nitrates were converted into N2O gas through the aforementioned chemical reaction process. The nitrogen and oxygen isotope values ​​of the N2O gas were then measured using a Gas-Bench-Stable Isotope Mass Spectrometer. In the sampling mode, cold trap 1 was placed in liquid nitrogen. After N2O in the sample was injected by a PAL autosampler, it passed through an external chemical trap containing magnesium perchlorate and caustic soda lime to remove water and CO2 before entering cold trap 1 for freezing and enrichment. The purge time was 350 s (the purge time could be adjusted according to the N2O concentration). Ten s before the end of the purge, cold trap 2 was pre-immersed in liquid nitrogen. Subsequently, the eight-way valve was switched to the injection mode, and then the primary cold trap left the liquid nitrogen tank. The frozen and fixed N2O was released and transferred to cold trap 2 by a low-flow-rate He gas (approximately 7 cm3 / min) for refreezing. The freezing and enrichment time was 95 s. The liquid nitrogen was then removed from the No. 2 cold trap, and N2O was vaporized in the capillary. The N2O was then sent to the chromatographic column by a low-flow-rate He gas for further separation and purification. The nitrogen isotope ratio was then determined by an IRMS gas in helium.

[0067] Data processing

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

[0069]

[0070] In the formula, δ 15 N Air The difference in the stable nitrogen isotope ratio of the sample relative to the stable nitrogen isotope ratio of the reference material air is expressed as a fraction of a thousand.

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

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

[0073] δ 15 The analytical precision for 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 The oxygen stable isotope ratio of the sample is the difference in thousands of parts relative to the stable oxygen isotope ratio of the standard average ocean water of the reference material.

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

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

[0079] δ 18 The analytical precision for the O value is 0.3‰.

[0080] Data quality:

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

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

[0083] 1) Extraction of genomic DNA

[0084] Genomic DNA was extracted from the samples using the CTAB / SDS method. DNA content and purity were monitored using 1% agarose gel electrophoresis. Based on the desired concentration, the DNA was diluted to 1 ng / μL and sterile water was added.

[0085] 2) Generation of amplicon

[0086] Different regions of the 16S rRNA / 18S rRNA / ITS genes (16S V4 / 16S V3 / 16S V3-V4 / 16S V4-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 stock solution (New England Biolabs), 0.2 μM per primer and 10 ng of target DNA. Cycling conditions for each primer and 10 ng of target DNA included: initial denaturation at 98 °C for 1 minute, followed by 30 cycles at 98 °C (10 s), 50 °C (30 s), and 72 °C (30 s), and a final extension at 72 °C for 5 minutes.

[0087] 3) Quantification and identification of PCR results

[0088] Mix an equal volume of 1X loading buffer (containing SYB Green) with the PCR product, perform electrophoresis on a 2% agarose gel, and then perform DNA detection. The PCR product mixture was then purified using the Qiagen Gel Extraction Kit (Qiagen, Germany).

[0089] 4) Library preparation and sequencing

[0090] According to the manufacturer's recommendations, use Ultra TM The IIDNA library preparation kit (Cat No. E7645) was used to generate sequencing libraries. Library quality was assessed using a Qubit@2.0 fluorescence analyzer (Thermo Scientific) and an Agilent Bioanalyzer 2100 system. Finally, the libraries were sequenced on the Illumina NovaSeq platform, yielding 250 bp paired-end reads.

[0091] 5) Data partitioning

[0092] Paired reads are assigned to samples based on their unique barcodes, and the barcodes and primer sequences are truncated. 1.2 Merging Paired Reads: FLASH (version 1.2.11, http: / / ccb.jhu.edu / software / FLASH / ) is used, a very fast and accurate analysis tool designed to merge paired reads when at least some of them overlap with other paired reads. Merging is performed using FLASH (version 1.2.11) when at least a partial read overlaps with a read generated at the other end of the same DNA fragment. The spliced ​​sequence is called the original tag.

[0093] 6) Data Filtering

[0094] Use the FastP (version 0.20.0) software to perform quality filtering on the original labels to obtain high-quality clean labels.

[0095] 7) Remove chimeras

[0096] Vsearch (version 2.15.0) was used to compare clean labels with reference databases (Silva database for 16S / 18S https: / / www.arb-silva.de / , and Unie database for ITS https: / / unite.ut.ee / ) to detect chimeric sequences. Chimeric sequences were then removed to obtain valid labels.

[0097] 8) ASVs noise reduction

[0098] For the previously obtained valid labels, denoising is performed using the DADA2 or deblur module in the QIIME2 software. The module performs denoising (QIIME2-202006 version) to obtain the initial ASVs (Amplicon sequence variants) (default: DADA2), and then filters out ASVs with an abundance of less than 5.

[0099] 9) Species annotation

[0100] Species annotation was performed using the 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] To investigate the phylogenetic relationships of different ASVs 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: Use δ to represent the δ value of nitrate. 15 N-NO3- and δ 18 O-NO3- isotopes are calculated using the following formula: δ(‰)=(Rsample / Rstandard-1)×1000 Rsample and Rstandard represent the N / N or O / O ratio of the sample / standard sample, respectively, i.e., δ1514181615N-NO3- and δ 18 O-NO3-; N isotopes use atmospheric nitrogen (N2) as the reference standard; O isotopes use Vienna Standard Mean Seawater (V-SMOW); The proportional contribution of potential NO3--N sources to surface water can be quantified using the Bayesian isotope mixing model (MixSIAR) in R language. This model is expressed as: 1. Where: X ij P represents the δ value of isotope j in mixture i; k S represents the proportion of source k; jk Let represent the δ value of the j-th isotope from the k-th source, following a normal distribution with mean = variance; C jk denoted by , the fractionation coefficient of isotope j from the k-th source follows a normal distribution with mean λ and variance τ; ε is the residual error, representing the unquantifiable variance among the other mixtures, with mean and standard deviation typically both being 0.

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

[0107] The `indicspecies` package in R can be used to calculate the indices for different taxa. The `indicspecies` package has two key features: obtaining the confidence interval for the indicator value using a bootstrap method (by setting the `nbootcans` parameter in the `strassoc()` function) and selecting the appropriate indicator species by iteratively trying all taxa combinations (using the `multipatt()` function).

[0108] Finally, indicator species for nitrate nitrogen groups were screened, and a microbial map of nitrate nitrogen pollution sources was constructed. A total of six groups of nitrogen-source microorganisms with different characteristics during dry and wet seasons were identified, such as... Figures 2 to 7As shown.

[0109] The contribution rate of different nitrogen pollution sources was calculated using the MixSIAR model; based on the results, the groups were divided, and the indicator microbial species of each group were calculated to obtain the microorganisms that indicate the sources of nitrogen pollution in surface water.

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

[0111] This invention overcomes the shortcomings of low accuracy and high cost of nitrogen and oxygen isotope source tracing technology; by linking microbial source tracing technology with nitrate nitrogen pollution, it efficiently utilizes microbial indicator species to represent the source of nitrogen pollution, thereby improving the accuracy and efficiency of nitrogen pollution source tracing and reducing operating costs.

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

[0113] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for tracing the source of nitrate nitrogen in surface water using microbial fingerprinting, characterized in that, include: Surface water samples were collected from the target watershed to obtain water samples; The nitrogen isotope ratio and oxygen isotope ratio of the water sample were determined. Sequencing the microbial barcodes of the water samples; Based on the nitrogen isotope ratio and the oxygen isotope ratio, the contribution rate of different nitrogen pollution source groups is calculated using a Bayesian isotope mixing model, and the contribution rates of different nitrogen pollution sources are grouped. The indexes of different indicator species in each group were calculated using the indicspecies package in R language to screen out indicator species, and a microbial map of nitrogen pollution sources was constructed based on the microbial barcodes. Based on the aforementioned microbial map of nitrogen pollution sources, microorganisms indicating the sources of nitrogen pollution in surface water were obtained; Based on the nitrogen isotope ratios and oxygen isotope ratios, a Bayesian isotope mixing model was used to calculate the contribution rates of different nitrogen pollution source groups, and the contribution rates of different nitrogen pollution sources were grouped, including: Let δ represent the δ of nitrate. 15 N-NO3- and δ 18 O-NO3- isotopes, 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 These represent the sample / standard sample respectively. 15 N / 14 N or 18 O / 16 O ratio, i.e., δ 15 N-NO3- and δ 18 O-NO3-; N isotopes are referenced to atmospheric nitrogen; O isotopes are based on the Vienna standard mean seawater; The proportionate contribution of potential NO3-N sources to surface water was quantified by using a Bayesian isotope mixing model in R language. The groups are divided into multiple groups based on the maximum proportional contribution. Specifically, these groups include: fertilizer source group, soil nitrogen source group, and domestic sewage and excrement source group. The formula for the Bayesian isotope mixing model is: Among them, X ij The value of isotope j in mixture i represents the value of isotope j, where i = 1, 2, 3…N and j = 1, 2, 3…J; p k S represents the contribution ratio of source k, calculated by the SIAR model; jk This represents the value of isotope j in source k, where k = 1, 2, 3, ..., K, and the average value is μ. jk The standard deviation is The normal distribution of C; jk The fractionation factor of isotope j at source k is represented by the normal distribution with average value λ. jk and standard deviation τ jk ;ε ij Representing the residual error, it is an undetermined variable among individual mixtures, and follows a mean of 0 and a standard deviation of σ. j The normal distribution; The indicspecies package has two value-referred features: obtaining the confidence interval of the indicator value through bootstrapping and selecting the appropriate indicator species by iteratively trying all taxonomic combinations.

2. The method for tracing the source of nitrate nitrogen in surface water using microbial fingerprinting according to claim 1, characterized in that, The determination of the nitrogen isotope ratio and oxygen isotope ratio of the water sample includes: Take 20 mL of the water sample into a 40 mL headspace vial, add 0.1 mL of CdCl2 solution, then add 0.8 mL of NH4Cl solution, and finally add 3 × 10 cm 4N clean zinc sheets. 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 vial after NO2- reduction, shake vigorously to mix the sample and reagent, then shake at 220 r / min for 30 min, and finally add 0.6 mL of NaOH solution as a terminator to end the azide reaction. The nitrogen and oxygen isotope ratios of N2O gas were measured online using a Gas-Bench-Stable Isotope Mass Spectrometer.

3. The method for tracing the microbial fingerprint of nitrate nitrogen in surface water according to claim 1, characterized in that, Sequencing the microbial barcodes of the water samples includes: Total genomic DNA was extracted from water samples using the CTAB / SDS method. 16S rRNA / 18S rRNA / ITS genes from different regions were amplified using specific primers and barcodes; Mix an equal volume of 1X loading buffer with the PCR product, perform electrophoresis on a 2% agarose gel, and then perform DNA detection. use Ultra TM IIDNA library preparation kit generates sequencing libraries; The barcodes are used to assign paired readings to water samples, and the barcodes and primer sequences are truncated by cutting them apart. Use FastP software to quality filter the raw labels to obtain high-quality clean labels; Vsearch is used to compare clean labels with a reference database to detect chimeric sequences, and chimeric sequences are removed to obtain valid labels; For the obtained valid tags, noise reduction is performed using the DADA2 or deblur module in the QIIME2 software. Species annotation and multiple sequence alignment were performed using QIIME2 software. Data normalization; The absolute abundance of amplicon sequence variations was normalized using the sequence number as the standard, with the sequence number corresponding to the sample with the fewest variations.

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

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