Method for monitoring biodiversity of estuary environment based on eDNA

Abstract

The invention belongs to the technical field of estuary environment biodiversity monitoring, and particularly relates to a method for monitoring estuary environment biodiversity based on eDNA. According to the method, three core strategies of gradient partition point distribution, sediment-dominated collaborative sampling and multi-method parallel verification are creatively integrated, and a set of special eDNA monitoring method for the complex estuary environment is formed. The implementation result proves that the method can systematically, sensitively and non-invasively reveal the spatial pattern of the estuary biocenosis, and effectively solves the key technical problems that the traditional method is large in interference and low in efficiency, and the general eDNA technology is insufficient in pertinence to benthic organisms and poor in representativeness.

Description

Technical Field

[0001] This invention belongs to the field of estuarine environmental biodiversity monitoring technology, specifically relating to a method for monitoring estuarine environmental biodiversity based on eDNA. Background Technology

[0002] Environmental DNA (eDNA) refers to DNA left in the environment by organisms. It may originate from shed tissues, mucus, secretions, excrement, etc. It has little disturbance to biological communities and is highly sensitive to species detection, making it an effective tool for monitoring aquatic biodiversity.

[0003] Estuarine environments exhibit significant spatiotemporal dynamics. Unidirectional water flow and tidal action in estuaries transport environmental DNA from its source, expanding its diffusion range. Compared to most freshwater and marine environments, estuarine waters exhibit higher and more frequent turbidity, and suspended particles may contain compounds that inhibit PCR reactions. Current technologies for monitoring estuarine benthic biodiversity face a dual challenge. First, traditional morphological survey methods have inherent flaws: they are highly dependent on professional personnel, costly, time-consuming, and prone to interfering with biological communities during sampling, and instantaneous sampling easily misses low-abundance species, thus failing to comprehensively and dynamically reflect the true ecological situation. Second, directly applying conventional environmental DNA (eDNA) technology to estuarine benthic monitoring is ineffective. The large amount of particulate matter in turbid water environments easily clogs filter membranes, resulting in small water sample filtration volumes and difficulties in eDNA enrichment. This problem is particularly prominent in estuaries with high sediment content (such as the Yellow River estuary). Currently, there is a lack of standardized, integrated, and intelligent eDNA monitoring methods specifically designed for complex estuarine ecosystems. Summary of the Invention

[0004] To address the shortcomings of the existing technologies, the purpose of this invention is to provide a method for monitoring estuarine biodiversity based on eDNA.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: This invention provides a method for monitoring estuarine biodiversity based on eDNA, comprising the following steps: (1) Monitoring point layout: The main river channel area 4 to 30 kilometers upstream of the river estuary was selected as the core sampling range. Along the main river channel, the sampling points were evenly distributed at intervals of 5 to 5.5 kilometers. (2) Sample collection: Water and sediment samples were collected simultaneously at each sampling point within one tidal cycle. Water samples were collected using the net bag method, filter membrane method, and tea bag method, respectively. Samples obtained by different methods at each sampling site were stored independently. (3) Sequencing and analysis: The samples obtained by different methods in step (2) were pretreated, the eDNA of the samples was extracted, and the concentration and quality of the extracted genomic eDNA were tested; a gene library was constructed; sequencing was performed using the Illumina HiSeq high-throughput sequencing platform; finally, the bioinformatics analysis of the gene data was performed to obtain the species classification and diversity information of planktonic, benthic animals and fish communities in the estuarine environment.

[0006] In this invention, the main river channel area, ranging from 4 to 30 kilometers upstream of the river estuary, was selected as the core sampling range. This range covers the transition zone from the upstream section dominated by freshwater to the downstream transition zone where fresh and brackish water meet, thus fully capturing the environmental gradient changes from freshwater to brackish water mixing.

[0007] To address the specific environmental challenges of different estuaries, this invention leverages the complementary sampling mechanisms and timescales of the plankton net method, the tea bag method, and the membrane filtration method to construct a three-dimensional, high-resolution sampling system capable of both capturing instantaneous states and integrating periodic signals. The membrane filtration method precisely records the composition and concentration of biological DNA in the water body during the target tidal phase, reflecting the state of the biological community at that specific moment. Within the precise time window calculated based on the tide table for the target phase, large-volume water samples are collected and filtered on-site—a crucial step in obtaining core phase characteristic data. The plankton net method, synchronized with the membrane filtration method, provides biological verification and supplementation to the eDNA data collected by the membrane method. Horizontal or vertical trawling of the plankton net is performed simultaneously with the membrane filtration water sample collection within the same time window and at the same sampling point, ensuring that the captured organisms and eDNA signals originate from the same hydrological conditions. The tea bag method, through a preset soaking-recovery time, ensures that the adsorbed eDNA covers the entire tidal cycle or key phase segment. It can reflect the cumulative signal of biological DNA over a period of time, and is used to analyze the transport and accumulation effect of eDNA during the tide. Multiple tea bags are placed at the core point and collected at different time intervals to construct a complete tidal cycle eDNA time series covering high tide, high tide, low tide and low tide, revealing the dynamic change law, so as to capture the dynamic of eDNA transport with the tide.

[0008] In some implementations, step (2) of collecting sediment samples includes: collecting surface sediments of 0-5 cm from the riverbed using sterile centrifuge tubes and freezing them at -20°C on-site.

[0009] In some embodiments, step (2) of collecting water samples by netting includes: during the middle of high tide, the water sample is filtered on-site using a plankton net, and the filtered water sample is collected in a sterile self-sealing bag to obtain a concentrated plankton sample, which is then stored at -20°C.

[0010] In some implementations, concentrated plankton samples are filtered through a membrane to enrich DNA, and the membrane is stored at -80°C for DNA extraction.

[0011] In some embodiments, the pore size of the planktonic net is 60-65 μm, preferably 64 μm.

[0012] In some embodiments, step (2) of collecting water samples by the filter membrane method includes: during the middle of high tide, the water sample is filtered with a filter membrane to extract the eDNA in the water sample onto the filter membrane, and the filter membrane is collected and stored at -80°C.

[0013] In some embodiments, the pore size of the filter membrane is 0.4~0.5 μm.

[0014] In some embodiments, step (2) of collecting water samples by the tea bag method includes: placing the filter membrane in a tea bag and placing 3 to 4 magnetic balls in the tea bag to make the tea bag sink in the water, then fixing the tea bag, arranging multiple tea bags at the same sampling point to cover the complete tidal cycle, recovering the filter membrane at different time intervals, and storing it at -80°C.

[0015] In some implementations, in step (3), DNA is extracted from samples obtained by different methods and gene libraries are constructed independently.

[0016] In some embodiments, step (3) includes pretreatment of the sediment sample, which includes homogenization by a homogenizer followed by freeze drying, filtration of impurities by a mesh screen and mixing.

[0017] In some implementations, in step (3), the primer sequence for sequencing is selected from any one of 18S rDNA, chloroplast, 16S rDNA, CO1 and 12S rDNA chloroplast.

[0018] Among them, 18S rDNA and chloroplasts can be used to analyze phytoplankton and algae other than cyanobacteria; 16S rDNA can be used to analyze cyanobacteria; and CO1 and mitochondrial 12S rDNA chloroplasts can be used for further analysis of fish, benthic animals and zooplankton.

[0019] In some implementations, the primer sequences for sequencing are selected from 18S rDNA.

[0020] In some implementations, step (3) includes sequence quality control, library splitting, sequence clustering, filtering, and annotation.

[0021] In some implementations, UPARSE v7.1 software is used to perform OTU clustering on the quality control spliced ​​sequences and remove chimeras.

[0022] In some implementations, sequences annotated to chloroplasts and mitochondria are removed from all samples during sequence clustering.

[0023] Compared with the prior art, the technical solution of the present invention has the following beneficial effects: This invention establishes a standardized, integrated, and intelligent eDNA monitoring method for complex estuarine ecosystems. Regarding sampling point deployment, this invention abandons traditional uniform or random sampling methods and pioneers a composite sampling model combining "ecological gradient zoning" and "environmental stress coupling." First, the core sampling area is selected as the main channel region 4 to 30 kilometers upstream of the river estuary. This area covers the transition zone from the freshwater-dominated upstream section to the brackish water confluence downstream zone, comprehensively capturing the environmental gradient changes from freshwater to brackish water mixing. Furthermore, addressing the specific environmental problems of different estuaries, such as high suspended sediment in the Yellow River estuary, urban pollutant input into the estuary, and strong tidal disturbances, this invention, based on the above framework, sets up auxiliary sampling points in the corresponding key impact areas. For estuaries significantly affected by tides, this method also requires correlating the sampling time of at least one core sampling point within the brackish water mixing zone with a preset tidal phase (such as mid-high tide or late low tide). Utilizing the complementarity of the sampling mechanisms and time scales of the plankton net method, tea bag method, and membrane filter method, a three-dimensional, high-resolution sampling system is constructed that can both "capture instantaneous states" and "integrate periodic signals." This invention combines three methods (net method, tea bag method, and membrane method) for synchronous sampling during the tidal cycle at each sampling site to collect eDNA, enabling comprehensive and accurate detection of biodiversity in water bodies and overcoming the limitations of single methods. Experiments show that the technical solution of this invention is applicable to biodiversity monitoring in various water bodies such as rivers, lakes, and oceans, and has the advantages of comprehensive detection, high accuracy, and high efficiency. Attached Figure Description

[0024] Figure 1 This is a biological community distribution map in Example 1 of the present invention; Figure 2 This is a diagram showing the distribution of biological communities in Comparative Example 1 of this invention; Figure 3 This is a diagram showing the distribution of biological communities in Comparative Example 2 of this invention; Figure 4 This is a diagram showing the distribution of biological communities in Comparative Example 3 of this invention; Figure 5 This is a diagram showing the distribution of biological communities in Comparative Example 4 of this invention. Detailed Implementation

[0025] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0026] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0027] To enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention will be described in detail below with reference to specific embodiments.

[0028] The methods involved in the following embodiments are as follows: Net method: Samples were collected using a planktonic net with 64 μm mesh size. The biological community structure was relatively complex, with significant variations in the relative abundance of various organisms. Some organisms, such as Melosira and Skeletona, accounted for a high proportion in some samples, while other organisms, such as Cyclotella and Pseudo-nitzschia, also showed significant relative abundance in different samples.

[0029] Tea bag method: Environmental DNA is collected by adsorption using specially made tea bags; the biological community structure is relatively simple, with certain organisms such as Melosira and Skeletona dominating in multiple samples, while the relative abundance of other organisms is relatively low.

[0030] Membrane filtration: Environmental DNA is collected using membrane filtration. The biological community structure exhibits characteristics different from the previous two methods. In some samples, certain organisms, such as Melosira and Skeletona, have relatively high abundance, while the relative abundance of other organisms is relatively balanced.

[0031] Sampling points were set up in the Yellow River estuary and nearshore waters to collect water and sediment samples simultaneously. Environmental DNA macrobarcoding technology was used to monitor plankton, benthic animals, and fish communities. Water quality parameters were measured on-site using a YSI multi-parameter water quality analyzer, while other water quality indicators and heavy metal content were determined using standard laboratory analytical methods.

[0032] After collection, water samples were placed in 5 L sterile purified water bottles and stored at -20℃ on-site before being transported back to the laboratory for DNA filtration and enrichment. The filter membranes were stored at -80℃ for subsequent DNA extraction and amplification. Additionally, 20 L of water samples were filtered using a No. 25 plankton net, and the concentrated plankton sample was transferred to 50 mL sterile centrifuge tubes. After storage at -20℃, the samples were transported back to the laboratory for further DNA enrichment through filtration, and the filter membranes were stored at -80℃ for DNA extraction. For the passive adsorption method, a 0.45 μm filter membrane was used as the adsorbent. In each experimental group, one filter membrane was removed with tweezers and placed in a tea bag. Three to four magnetic weights were placed in the tea bag to ensure it sank in the water. The tea bag was then secured with a plumb line. The filter membranes were removed at 4 h, 24 h, and 48 h after enrichment. The filter membranes were stored at -80℃ for subsequent DNA extraction and amplification.

[0033] Sediment samples were collected using a mud sampler. The collected surface sediment (0–5 cm) was immediately placed in 50 mL sterile centrifuge tubes, frozen at -20°C on-site, and transported to the laboratory. A portion of the sediment samples was stored at -80°C for DNA extraction, while another portion was used for the determination of environmental factors and heavy metal content.

[0034] Example 1 A method for monitoring estuarine biodiversity based on eDNA, taking the Yellow River estuary and its nearshore waters as an example, specifically includes the following steps: (1) Monitoring point layout: The main river channel area from 4 km to 30 km upstream of the river estuary was selected as the core sampling range. Along the main river channel, the sampling points were evenly distributed at intervals of 5.2 km, for a total of 5 sampling points; (2) Sample Collection: Water and sediment samples were collected simultaneously at each sampling point for one tidal cycle. Environmental DNA macrobarcoding technology was used to monitor plankton, benthic animals, and fish communities. On-site water quality parameters were measured using a YSI multi-parameter water quality analyzer, while other water quality indicators and heavy metal content were determined using standard laboratory analytical methods. Simultaneous collection of water quality indicators and their corresponding physicochemical properties (heavy metal content, etc.) was conducted to analyze the impact of environmental factors on species community characteristics. Water samples were collected using three methods: netting, membrane filtration, and tea bag filtration. The membrane filtration method involved collecting samples in mid-high tide and placing them in 5 L sterile purified water bottles. These samples were stored at -20°C on-site and then transported back to the laboratory for DNA enrichment using a 0.45 μm filter membrane. The filter membrane was stored at -80°C for subsequent DNA extraction and amplification. The netting method involved filtering 20 L of water samples using a 25-gauge plankton net (64 μm pore size) during mid-high tide. The concentrated plankton sample was transferred to 50 mL sterile centrifuge tubes, stored at -20°C, and then transported back to the laboratory for further DNA enrichment through filtration. The filter membrane was then stored at -80°C for DNA extraction. The tea bag method involved using a 0.45 μm filter membrane… Using μm filter membranes as the adsorbent, multiple tea bags were placed at the same sampling site, covering the complete tidal cycle. For each experimental group, a filter membrane was removed with tweezers and placed into a tea bag. Three to four magnetic balls were placed inside the tea bag to ensure it sank in the water. The tea bag was then secured with a plumb line. The filter membranes were removed at 4 h, 24 h, and 48 h after enrichment and stored at -80℃ for subsequent DNA extraction and amplification. Sediment samples were collected from the surface (0–5 cm) according to HJ 494–2009. Gravel, sawdust, weeds, shells, and other large biological debris were removed and collected into sterile tubes (generally 50 mL). These samples were stored outdoors on dry ice or at -20℃, and in the laboratory at -20℃. Sediment collection at the same sampling point should cover as many microhabitats as possible. Samples obtained from different methods at each sampling site were stored independently.

[0035] (3) eDNA extraction Filter membrane samples (water samples / mixed zooplankton tissue samples): The filter membrane was broken up by agitation using grinding beads and lysis buffer.

[0036] Sediment samples: Homogenized by a homogenizer, freeze-dried, filtered to remove impurities and mixed.

[0037] DNA extraction was performed using an extraction kit to extract all biological DNA retained on the filter membrane. Genomic DNA extraction was performed according to the DNeasy® PowerSoil® ProKit (QIAGEN, US) instructions. The quality of the extracted genomic DNA was assessed using 1% agarose gel electrophoresis, and DNA concentration and purity were determined using a Nano Drop 2000 (Thermo Scientific, USA).

[0038] PCR was performed using TransGen AP221-02: TransStartFastpfuDNAPolymerase; PCR instrument: ABIGeneAmp®; 9700 model; all samples were processed according to the formal experimental conditions, with three replicates for each sample. The PCR products of the same sample were mixed and detected by 2% agarose gel electrophoresis. The PCR products were recovered by gel excision using the AxyPrepDNA Gel Recovery Kit (AXYGEN), and eluted with Tris_HCl; the concentration and quality of the extracted genomic eDNA were detected by 2% agarose gel electrophoresis.

[0039] (4) Sequencing and analysis Using 18S primers as an example, high-throughput analysis was performed on the obtained eDNA. The primer sequences are as follows: 18S rDNA-v9 upstream primer (5'-3') TCCCTGCCHTTTGTACACAC; 18S rDNA-v9 downstream primer (5'-3') CCTTCYGCAGGTTCACCTAC.

[0040] High-throughput sequencing: FastP (https: / / github.com / OpenGene / fastp, version 0.19.6) software was used for quality control of the raw paired-end sequencing sequences, and FLASH (http: / / www.cbcb.umd.edu / software / flash, version 1.2.11) software was used for assembly. UPARSE v7.1 software (http: / / drive5.com / uparse / ) was used to cluster the quality-controlled assembled sequences using Operational Taxonomic Units (OTUs) based on 97% similarity, and chimeras were removed. Chloroplast and mitochondrial sequences annotated in all samples were removed (removal is recommended if chloroplast and mitochondrial contamination is present). To minimize the impact of sequencing depth on subsequent Alpha and Beta diversity data analysis, the sequence count of all samples was flattened to 20,000 (sequence flattening is recommended). After flattening, the average sequence coverage (Good's coverage) for each sample still reached 99.09%. We used RDPclassifier (http: / / rdp.cme.msu.edu / , version 2.11) to perform OTU taxonomic annotation by comparing the Silva 16S rRNA gene database (v138) with a confidence threshold of 70%, and analyzed the community composition of each sample at different species classification levels.

[0041] Bioinformatics analysis: This analysis process includes five key steps: sequence quality control, library splitting, sequence clustering (OTU / ASV), filtering, and annotation. It aims to obtain high-quality species composition data from raw sequencing data.

[0042] Sequencing was performed using the Illumina HiSeq high-throughput sequencing platform; finally, bioinformatics analysis of the genetic data was conducted to obtain information on the species classification and diversity of planktonic, benthic, and fish communities in the estuarine environment.

[0043] Comparative Example 1 The experimental method was the same as in Example 1, except that the main river channel area of ​​the main stream of the river, from 4 km to 30 km, was selected as the core sampling range. Along the main river channel, the sampling points were evenly distributed at intervals of 5.2 km, for a total of 5 sampling sites. Water samples were collected using only the net bag method and the filter membrane method.

[0044] Comparative Example 2 The experimental method was the same as in Example 1, except that water samples were collected using only the membrane filtration method and the tea bag method.

[0045] Comparative Example 3 The experimental method was the same as in Example 1, except that water samples were collected using only the net bag method and the tea bag method.

[0046] Comparative Example 4 The experimental method was the same as in Example 1, except that water samples were collected using only the net bag method and the filter membrane method.

[0047] Example 1 and Comparative Example 1 4. The number of species detected in the monitored biological communities is shown in Table 1.

[0048] Table 1 Species Count

[0049] As can be seen from the table, Example 1 significantly increased the number of species detected, indicating that it can capture a wider range of biological groups and detect a more comprehensive species composition, making it suitable for comprehensive biodiversity studies.

[0050] Example 1 and Comparative Example 1 4. Pie chart of microbial communities at the species level, as shown below Figures 1 to 5 As shown in the figure, the pie chart of the biological community in Example 1 shows a richer and more balanced distribution of species. In addition to dominant phytoplankton such as *Cladosporium* and *Skeletonema*, it also includes small invertebrates such as copepods and ostracods, as well as eDNA signals from some fish. The proportion of low-abundance species (rare diatoms, small benthic organisms) is also relatively increased. The monitoring results include a large number of species that are difficult to identify, rare, or small, such as `aff._Protosuberites_sp._190513-06` and `Pseudobiotus_sp._SHR-2005`. The detection of these species provides an effective method for discovering and analyzing hidden biodiversity. The species distribution is balanced, and the proportion of key species is more reasonable, thus more realistically reflecting the natural composition and ecological structure of the estuarine biological community. In contrast, the pie charts of Examples 1-4 show a significantly higher proportion of dominant species and a significantly insufficient coverage of low-abundance species. For example, in Comparative Example 1, phytoplankton accounted for over 65% of the community, while the signal from small invertebrates and fish accounted for less than 8%, which may be related to the design of the sampling sites. Comparative Example 2, using the membrane filtration and tea bag methods, showed that highly adsorbent algae were dominant, and fish-related eDNA was almost undetectable. The community structures in Comparative Examples 3 and 4 also exhibited homogeneous characteristics, lacking the comprehensiveness of multi-group co-detection shown in Example 1. This clearly demonstrates that the combination of the three sampling methods can effectively compensate for the shortcomings of single or two methods, more realistically restoring the natural composition of biological communities in the estuarine environment and providing a more reliable visual basis for biodiversity assessment.

[0051] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of them. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for monitoring estuarine biodiversity based on eDNA, characterized in that, Includes the following steps: (1) Monitoring point layout: The main river channel area 4 to 30 kilometers upstream of the river estuary was selected as the core sampling range. Along the main river channel, the sampling points were evenly distributed at intervals of 5 to 5.5 kilometers. (2) Sample collection: Water and sediment samples were collected simultaneously at each sampling point within one tidal cycle. Water samples were collected using the net bag method, filter membrane method, and tea bag method, respectively. Samples obtained by different methods at each sampling site were stored independently. (3) eDNA extraction and sequencing: The samples obtained by different methods in step (2) were pretreated to extract eDNA from the samples and the concentration and quality of the extracted genomic eDNA were tested; a gene library was constructed; sequencing was performed using the Illumina HiSeq high-throughput sequencing platform; finally, bioinformatics analysis of the gene data was performed to obtain information on the species classification and diversity of planktonic, benthic and fish communities in the estuarine environment.

2. The method as described in claim 1, characterized in that, In step (2), the sediment samples are collected by taking 0-5 cm of surface sediment from the riverbed and collecting it in sterile centrifuge tubes, and freezing it at -20℃ on site.

3. The method as described in claim 1, characterized in that, In step (2), the water sample collection by the net bag method includes: during the middle of the high tide, the water sample is filtered on site using a plankton net, and the filtered water sample is collected in a sterile self-sealing bag to obtain a concentrated plankton sample, which is then stored at -80℃.

4. The method as described in claim 3, characterized in that, The pore size of the planktonic net is 60~65 μm.

5. The method as described in claim 1, characterized in that, In step (2), the water sample collection method by the filter membrane method includes: during the middle of the high tide, the water sample is filtered on site with a filter membrane, the eDNA in the water sample is extracted onto the filter membrane, and the filter membrane is collected and stored at -80℃.

6. The method as described in claim 5, characterized in that, The pore size of the filter membrane is 0.4~0.5 μm.

7. The method as described in claim 1, characterized in that, In step (2), the tea bag method for collecting water samples includes: placing the filter membrane in a tea bag and placing 3-4 magnetic balls in the tea bag to make the tea bag sink in the water, then fixing the tea bag, arranging multiple tea bags at the same sampling point to cover the complete tidal cycle, recovering the filter membrane at different time intervals, and storing it at -80℃; preferably, the different time intervals are 4 h, 24 h, and 48 h.

8. The method as described in claim 1, characterized in that, In step (3), DNA was extracted from samples obtained by different methods and gene libraries were constructed independently.

9. The method as described in claim 1, characterized in that, In step (3), the primer sequences for sequencing are selected from any one of 18S rDNA, chloroplast (RBCL), 16S rDNA, CO1 and 12S rDNA.

10. The method as described in claim 1, characterized in that, In step (3), the bioinformatics analysis includes sequence quality control, library splitting, sequence clustering, filtering, and annotation.

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