Method for identifying species and functions of eukaryotic algae in aquatic ecosystem

Abstract

The invention relates to the technical field of molecular biology, in particular to a method for identifying eukaryotic algae species and functions in an aquatic ecosystem. The method provided by the invention has the advantages of high throughput, high sensitivity and high accuracy, does not need pretreatment steps such as enrichment culture and the like, can synchronously realize species identification and functional characteristic analysis of eukaryotic algae through an in-situ detection technology on the basis of the specificity difference of genetic materials of eukaryotic algae, and has a wide application prospect. A full-chain technical system from molecular recognition to function analysis is constructed, and the method has important significance on optimization of water quality protection and algae risk management strategies.

Description

Technical Field

[0001] This invention relates to the field of molecular biology, and in particular to a method for identifying eukaryotic algae species and functions in aquatic ecosystems. Background Technology

[0002] Eukaryotic algae are a class of lower eukaryotic autotrophic organisms with photosynthetic capabilities and cellular structures exhibiting typical eukaryotic characteristics. Widely distributed in aquatic ecosystems such as oceans, lakes, and rivers, eukaryotic algae participate in key ecological processes including the biogeochemical cycles of elements such as carbon, silicon, nitrogen, and phosphorus, oxygen release, and nutrient transformation, maintaining the stability of aquatic ecosystem services and functions. As one of the most important primary producers in aquatic ecosystems, eukaryotic algae are a polyphyletic and paraphyletic group, mainly including phyla such as Cryptophyta, Dinophyta, Chrysophyta, Xanthophyta, Bacillus, Phaeophyta, Euglenophyta, Rhodophyta, Chlorophyta, and Charophyta. Eukaryotic algae inhabit water bodies and sediments in aquatic environments and are highly sensitive to environmental changes such as nutrient levels, light, temperature, and disturbance. Their excessive proliferation can trigger algal blooms and release algal toxins, leading to poisoning and death of aquatic organisms, thereby disrupting ecosystem balance and threatening human health regarding water use.

[0003] Species identification and functional analysis of eukaryotic algae are fundamental to the protection of aquatic ecosystem health. Systematically analyzing the species composition and functional characteristics of eukaryotic algae in water bodies and sediments will not only deepen our scientific understanding of the synergistic mechanisms of community structure and function of key producers in the aquatic environment, but also provide important basic data support and theoretical basis for water environment protection and pollution control.

[0004] To date, there is no unified procedure for identifying eukaryotic algae species and functions. Although traditional microscopic methods can identify algal species based on cell morphology, many algae exhibit only subtle differences, leading to significant discrepancies between different researchers' assessments. Algae at different life stages and developmental phases may exhibit atypical morphology or lack of characteristic features. Some algae require pure culture for identification based on their life history, which is extremely difficult, time-consuming, and has a low success rate. With the development of molecular biology and genomics, PCR amplification technology can rapidly identify eukaryotic algal species classification information based on specific primers. However, primer selection and optimization rely heavily on experience and only provide information on algal species composition. Furthermore, primers exhibit strong biases, making it difficult to identify low-abundance and unknown algae, failing to discover novel eukaryotic algae, and not reflecting the functional characteristics of algae.

[0005] Patent application CN113528503A discloses a method for immobilizing eukaryotic algal communities to study their structural diversity in freshwater. This method primarily focuses on the collection and immobilization of eukaryotic algal samples and is applicable to the study of eukaryotic algal species composition in various lakes. Patent CN106048058A discloses eukaryotic algae-specific primers (upstream primer: 5'-AAAGTTAGGTGAGCG-3', downstream primer: 5'-CAGTCAATCGGTATG-3'), which can obtain the diversity and species composition of eukaryotic algae in activated sludge from propylene oxide saponification wastewater. Patent application CN113142034A discloses a method for simultaneously identifying phytoplankton and benthic algae in aquatic ecosystems. Based on a self-constructed algal species annotation database, it uses PCR amplification technology to obtain species composition information for all eukaryotic and prokaryotic algae. However, while existing technologies can identify the species composition of eukaryotic algae, primers are biased and there are still significant limitations in terms of functional characteristics analysis and ecological risks. These limitations restrict a comprehensive understanding of the diversity and functional characteristics of eukaryotic algae in aquatic systems, ultimately affecting scientific decision-making in water environment management and the effective formulation of ecological restoration strategies.

[0006] Given the current limitations of eukaryotic algae species and function identification technologies, there is an urgent need to establish a standardized technical solution for rapid, accurate, and efficient species identification and function testing of eukaryotic algae in water bodies and / or sediments. Summary of the Invention

[0007] To address the aforementioned technical problems, this invention provides a method for identifying eukaryotic algae species and functions in aquatic ecosystems. The method offered by this invention boasts advantages of high throughput, high sensitivity, and high accuracy, eliminating the need for pretreatment steps such as enrichment culture. Based on the specific differences in the genetic material of eukaryotic algae, in-situ detection technology can simultaneously achieve species identification and functional characterization of eukaryotic algae, constructing a complete technological system from molecular recognition to functional analysis. This is of great significance for optimizing water quality protection and algal risk management strategies.

[0008] In a first aspect, the present invention provides a method for identifying eukaryotic algae species and functions in an aquatic ecosystem, the method comprising the following steps:

[0009] (1) Collect environmental samples from aquatic ecosystems;

[0010] (2) Extract and purify DNA from the environmental sample, and perform metagenomic sequencing on the high-quality DNA to obtain raw metagenomic sequencing data;

[0011] (3) The raw metagenomic sequencing data were subjected to quality control and short sequence splicing, targeted and non-targeted assembly of genome binning, and then quality assessment was performed to select high-quality eukaryotic assembled genomes.

[0012] (4) Species annotation is performed on the high-quality eukaryotic assembled genome, the eukaryotic algal genomes are verified and selected, and the genome abundance is calculated;

[0013] (5) Compare the gene set of the eukaryotic algae genome with the reference database to obtain information on the functional potential and ecological risk of the eukaryotic algae genome;

[0014] The standard for high-quality DNA is: DNA concentration greater than or equal to 10 μg / μL and total content greater than or equal to 2 μg.

[0015] The selection criteria for high-quality eukaryotic assembled genomes are: integrity greater than 20% and genome contamination less than 5%.

[0016] The method provided by this invention can simultaneously characterize the species composition and functional characteristics of eukaryotic algae in aquatic ecosystems and systematically quantify the ecological roles of eukaryotic algae in various aquatic environments. This is of great significance for optimizing water quality protection and algae risk management strategies.

[0017] As a preferred technical solution of the present invention, the environmental samples in step (1) include water samples and / or sediment samples.

[0018] As a preferred technical solution of the present invention, the method for collecting the water samples is as follows: collect at least two surface water samples from the aquatic ecosystem at a depth of 0.3-0.8m (e.g., 0.3m, 0.5m, 0.7m, 0.8m, etc.) and mix them thoroughly.

[0019] As a specific embodiment of the present invention, the method for collecting the water samples is as follows: collect 3 surface water samples at a depth of 0.5m from the aquatic ecosystem, each sample being 5L, mix them evenly, and place them in sterile bottles.

[0020] As a preferred technical solution of the present invention, the method for collecting the sediment samples is as follows: collect at least two bottom sediment samples from the aquatic ecosystem at a depth of 0-5cm (e.g., 0cm, 1cm, 2cm, 3cm, 4cm, 5cm, etc.) and mix them thoroughly.

[0021] As a preferred technical solution of the present invention, when studying eukaryotic algae in water and sediment simultaneously, and collecting water samples and sediment samples at the same time, the sediment samples are collected from the bottom sediment location corresponding to the water samples.

[0022] As a preferred embodiment of the present invention, the extraction and purification of DNA from the environmental sample includes: filtering a mixed surface water sample using a filter membrane, and then extracting DNA from the filter membrane containing the water sample by cryogenic grinding with liquid nitrogen.

[0023] The mixed surface water sample needs to be filtered within 24 hours and stored at 0-4℃ before filtration.

[0024] As a preferred embodiment of the present invention, the pore size of the filter membrane is 0.22 μm.

[0025] As a specific embodiment of the present invention, the extraction and purification of DNA from the environmental sample includes: filtering the mixed surface water sample using a filter membrane with a pore size of 0.22 μm; after filtration, the filter membrane containing the water sample is cryogenically ground with liquid nitrogen; and DNA extraction is performed using two filter membranes each time, following the instructions of the DNA extraction kit.

[0026] As a preferred embodiment of the present invention, the extraction and purification of DNA from the environmental sample includes: centrifuging the sediment sample to remove the supernatant, and then using 0.5-1g (e.g., 0.5g, 0.6g, 0.7g, 0.8g, 0.9g, 1g, etc.) of sediment sample for DNA extraction.

[0027] If the filtered membrane or sediment sample containing the water sample is not immediately used for DNA extraction, it should be frozen at -80°C until DNA extraction is performed.

[0028] As a preferred technical solution of the present invention, each environmental sample undergoes at least two independent DNA extraction operations, the extracted DNA from each environmental sample is mixed, the mixed DNA is quality evaluated, and the high-quality DNA is used for metagenomic sequencing.

[0029] In one specific embodiment of the present invention, the metagenomic sequencing is performed using the Illumina NovaSeq platform in paired-end 150bp mode.

[0030] As a preferred technical solution of the present invention, the quality control in step (3) is used to remove sequences containing uncertain bases, repetitive sequences or possible contamination, and finally obtain high-quality short sequences for subsequent research.

[0031] In one specific embodiment of the present invention, the quality control is performed using the Read QC module in the metaWRAP software.

[0032] As a preferred technical solution of the present invention, the short sequence splicing in step (3) is used to obtain the contiguous group of the metagenomics.

[0033] In one specific embodiment of the present invention, the short sequence splicing is performed using MEGAHIT software.

[0034] As a preferred embodiment of the present invention, the targeted and non-targeted assembly genome binning method in step (3) includes:

[0035] A. The targeted binning method for contigs includes: using multiple annotation software programs to annotate and classify contigs in metagenomics obtained from short sequence splicing, fusing and identifying eukaryotic contigs, screening eukaryotic sequences with contig lengths greater than 1 kb, and binning the screened eukaryotic sequences to obtain targeted eukaryotic assembled genomes; wherein, the annotation and classification of contigs in metagenomics obtained from short sequence splicing is performed using three software programs: EukRep, DeepMicroClass, and Whokaryote; the fusing and identifying eukaryotic contigs includes: merging the annotation and classification results of the three software programs, using the SeqKit tool to select eukaryotic sequences, and identifying eukaryotic contigs based on the eukaryotic sequence results; the binning of the screened eukaryotic sequences is performed using the MetaBAT2 tool;

[0036] B. The non-targeted binning method for contigs includes: binning all contigs with a sequence length greater than 1kb to obtain non-targeted assembled genomes; and selecting genomes with a eukaryotic sequence ratio greater than 0.8 in the non-targeted assembled genomes based on the eukaryotic contigs in the targeted binning. Among these, the binning of all contigs with a sequence length greater than 1kb is performed using the MetaBAT2 tool.

[0037] As a preferred technical solution of the present invention, the quality assessment method in step (3) is as follows: merging the results of targeted eukaryotic assembly genome and non-targeted eukaryotic assembly genome, performing genome quality assessment, and selecting high-quality genomes as the final eukaryotic assembly genome; wherein, the genome quality assessment is performed using BUSCO and EukCC tools.

[0038] As a preferred technical solution of the present invention, step (4) includes: performing gene prediction on the eukaryotic assembled genome identified in step (3), then performing species annotation on the eukaryotic assembled genome, selecting eukaryotic algal genomes from the annotation results, then establishing an index on the eukaryotic algal genomes and comparing it with the high-quality short sequences obtained in step (3), and finally calculating the abundance of eukaryotic algal genomes.

[0039] As a specific embodiment of the present invention, the MetaEuk tool is used to perform gene prediction on the eukaryotic assembled genome identified in step (3).

[0040] As a specific embodiment of the present invention, the EUKulele tool is used for species annotation of eukaryotic assembled genomes.

[0041] As a specific embodiment of the present invention, the Bowtie2 tool is used to index the eukaryotic algal genome.

[0042] As a specific embodiment of the present invention, the Coverm tool is used to calculate the abundance of eukaryotic algal genomes.

[0043] As a preferred technical solution of the present invention, step (5) includes: comparing the predicted genes of the eukaryotic algae genome identified in step (4) with the reference database to identify the functional characteristics of key metabolic genes and algal toxin synthesis genes of eukaryotic algae, thereby comprehensively evaluating the functional potential, ecological risks and ecological roles of eukaryotic algae.

[0044] The reference databases include KEGG (Kyoto Encyclopedia of Genes and Genomes): used for identifying metabolic pathways and functional modules; COG (Clusters of Orthologous Groups): used for annotating evolutionarily conserved functional units; and CAZy (Carbohydrate-Active enZymes): used for identifying carbohydrate-active enzymes, particularly for studying algal carbon source metabolism. Simultaneously, special attention should be paid to algal toxin synthesis genes in the KEGG database. Their presence in various eukaryotic algal genomes should be extracted and summarized to screen environmental algal genomes with potential algal toxin synthesis capabilities, thereby comprehensively assessing the functional potential, ecological risks, and ecological roles of eukaryotic algae.

[0045] The technical solution provided by the embodiments of the present invention has the following advantages compared with the prior art:

[0046] 1. Compared with traditional microscopic examination methods, the method provided by this invention does not require the enrichment, separation and cultivation of algae, and relies less on the professional skills of the operators.

[0047] 2. The present invention does not depend on the morphology and size of algal cells or the developmental stage of algae for the identification of eukaryotic algae. Both abundant and rare groups can be detected when the sequencing depth is deep enough, resulting in higher sensitivity.

[0048] 3. This invention can quickly and efficiently identify eukaryotic algae in a large number of environmental samples, and can identify novel eukaryotic algae species. The identification results are highly reproducible, highly standardized, and highly reliable.

[0049] 4. Compared with traditional molecular identification methods based on amplified sequencing of characteristic fragments, the metagenomic identification method of this invention can further explore species-specific functions in addition to species composition, and can provide more useful information for elucidating the environmental impact of eukaryotic algae. Attached Figure Description

[0050] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart of the method for identifying eukaryotic algae species and functions in an aquatic ecosystem, as shown in Example 1.

[0053] Figure 2 Example 1 shows the abundance distribution of eukaryotic algal genomes;

[0054] Figure 3 Example 1 shows the number of KEGG annotations of eukaryotic algal genomes and the presence of algal toxin-related genes;

[0055] Figure 4 This represents the number of COG annotations for the eukaryotic algal genome in Example 1;

[0056] Figure 5 This represents the number of CAZy annotations for the eukaryotic algal genome in Example 1. Detailed Implementation

[0057] To better understand the above-mentioned objectives, features, and advantages of the present invention, the solutions of the present invention will be further described below. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other.

[0058] Many specific details are set forth in the following description in order to provide a full understanding of the invention, but the invention may also be practiced in other ways different from those described herein; obviously, the embodiments in the specification are only some embodiments of the invention, and not all embodiments.

[0059] Example 1

[0060] This embodiment provides a method for identifying eukaryotic algae species and functions in an aquatic ecosystem. The flowchart of the method is shown below. Figure 1 As shown, the specific steps include the following:

[0061] S1. Environmental Sample Collection

[0062] Four monitoring points were selected in a lake for sampling. Three surface water samples were collected in parallel at a depth of 0.5 meters below the water surface using a water sampler. The water samples from each testing point were mixed evenly and placed in sterile bottles, and then quickly transported back to the laboratory at 0-4℃.

[0063] S2, DNA extraction and metagenomic sequencing

[0064] The mixed water sample was filtered through a 0.22 μm filter membrane within 24 hours. All filter membranes containing the water sample were stored in 50 mL sterile centrifuge tubes and kept at -80℃ for later use. The water samples collected from the four monitoring points were labeled as S1, S2, S3 and S4, respectively.

[0065] Filter membrane samples were ground and disrupted using liquid nitrogen, and then DNA was extracted using the FastDNA SPIN Kit for Soil (MPBiomedicals, USA). Two filter membranes were used each time, and DNA extraction was performed according to the kit instructions. Each environmental sample underwent three independent DNA extraction operations. The mixed DNA was used for concentration and quality assessment. DNA with a concentration greater than 10 μg / μL and a total amount greater than 2 μg was considered high-quality DNA. High-quality DNA was used for metagenomic sequencing on the Illumina NovaSeq platform in paired-end 150bp mode to obtain raw sequencing data.

[0066] S3, Metagenomic Data Processing and Eukaryotic Genome Acquisition

[0067] The Read QC module in the metaWRAP (v1.2.2) software package is used to perform quality control on the raw metagenomic sequencing data, removing short sequences containing a large number of uncertain bases, excessively high repetition ratios, potential contamination, and low overall quality scores, ultimately obtaining high-quality short sequences.

[0068] MEGAHIT (v1.2.9) was used to assemble the quality-controlled data. Based on the parameter -mem-flag2-min-contig-len 500, de novo assembly was performed using a distributed graph algorithm. Sequencing data from the four sites were assembled into 1,322,748 (S1), 1,444,288 (S2), 1,239,736 (S3), and 1,255,095 (S4) contigs, respectively.

[0069] Next, two methods were used for binning analysis of the eukaryotic genome:

[0070] A. Contiguous groups were annotated and classified using three software programs: EukRep (parameter: --min 1000), DeepMicroClass (parameter: -class Eukaryote), and Whokaryote. The results of the three programs were merged, and eukaryotic sequences were selected using SeqKit (v2.9.0). 352,319 (S1), 439,836 (S2), 356,335 (S3), and 312,549 (S4) eukaryotic contiguous groups were found at the four sites, respectively. Contiguous groups with sequence lengths greater than 1kb were screened, and binning was performed using the MetaBAT2 tool to obtain preliminary "targeted eukaryotic genome assembly" (281 sequences from the four sites).

[0071] B. To fully utilize all high-quality contigs and uncover potentially missed eukaryotic assembly results, MetaBAT2 binning was performed on all contigs with sequence lengths greater than 1 kb. The resulting preliminary untargeted assembled genomes were compared with the eukaryotic contigs identified by targeted binning, and the proportion of eukaryotic contigs in each untargeted assembled genome was calculated. Only assembled genomes with a eukaryotic contig proportion exceeding 80% were retained as "untargeted eukaryotic assembled genomes" (138 in total across four sites). The above "targeted eukaryotic assembled genomes" and "untargeted eukaryotic assembled genomes" were integrated to form a complete candidate eukaryotic assembled genome set (419 in total across four sites). To assess the integrity and purity of the eukaryotic genomes, BUSCO and EukCC were used for genome quality assessment. High-quality genomes (in this example, the criteria were: integrity greater than 20% and genome contamination less than 5%) were selected as the final eukaryotic assembled genomes (8 genomes in total across four sites) for subsequent gene annotation, functional prediction, and other analyses.

[0072] S4. Species annotation and abundance calculation of eukaryotic algal genomes

[0073] Gene prediction was performed on the identified eukaryotic assembled genomes using MetaEuk (parameters: -metaeuk-eval 0.001-min-ungapped-score 35-min-exon-aa 20-metaeuk-tcov 0.5-min-length 30). Subsequently, species annotation was performed on the genomes using EUKulele (v2.1.2). The quality of each candidate genome, gene prediction results, and species annotation results are shown in Table 1.

[0074] Table 1

[0075]

[0076] As can be seen, two of the eight genomes that met the quality criteria (MAG1 and MAG2) were classified as belonging to the phylum Chytridiomycota, a group of fungi that produce zoospores. The other six (MAG3-8) were all classified as belonging to the class Bacillariophyceae within the superphylum Heterokontophyta, a class of eukaryotic algae characterized by their diatom cells covered with silica (primarily silicon dioxide). Therefore, this invention successfully identified six eukaryotic diatom genomes that met the quality requirements, and these six eukaryotic algal genomes were screened for subsequent analysis.

[0077] Next, the genomes of the six identified eukaryotic algae were indexed and compared with high-quality short sequences to calculate the abundance of eukaryotic algal genomes. The results are as follows: Figure 2 The figure shows the relative abundance distribution of the six eukaryotic genomes in the four selected monitoring samples in Example 1. It can be seen that the distribution of different eukaryotic algae varies in different samples.

[0078] S5, Functional Potential and Ecological Risks of Eukaryotic Algae

[0079] Based on gene prediction results, eukaryotic genes from eukaryotic algal genomes were compared and annotated with the KEGG, COG, and CAZy databases. The results are as follows: Figure 3-5 As shown, where, Figure 3 Example 1 shows the number of KEGG annotations of eukaryotic algal genomes and the presence of algal toxin-related genes. Figure 4 This represents the COG annotation count of the eukaryotic algal genome in Example 1. Figure 5 This represents the CAZy annotation count of the eukaryotic algal genome in Example 1. It can be observed that the vast majority of eukaryotic genes failed to be annotated, indicating that a large amount of unknown / novel genetic information still exists in existing eukaryotic algae. These genes will provide important references for future research on eukaryotic algal biosynthesis. Simultaneously, based on the KEGG annotation results, genes related to algal toxin synthesis were screened (…). Figure 3 The study found that these eukaryotic algae all carried genes for algal toxin synthesis, suggesting potential health risks related to algal toxins. It is recommended that the management of this lake focus on the spatiotemporal distribution characteristics and population dynamics of these eukaryotic algae, and that a systematic monitoring network be established to provide a scientific basis for the precise prevention and control of algal blooms.

[0080] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0081] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for identifying eukaryotic algae species and functions in an aquatic ecosystem, characterized in that, The method includes the following steps: (1) Collect environmental samples from aquatic ecosystems; (2) Extract and purify DNA from the environmental sample, and perform metagenomic sequencing on the high-quality DNA to obtain raw metagenomic sequencing data; (3) The raw metagenomic sequencing data were subjected to quality control and short sequence splicing, targeted and non-targeted assembly of genome binning, and then quality assessment was performed to select high-quality eukaryotic assembled genomes. (4) Species annotation is performed on the high-quality eukaryotic assembled genome, the eukaryotic algal genomes are verified and selected, and the genome abundance is calculated; (5) Compare the gene set of the eukaryotic algae genome with the reference database to obtain information on the functional potential and ecological risk of the eukaryotic algae genome; The standard for high-quality DNA is: DNA concentration greater than or equal to 10 μg / μL and total content greater than or equal to 2 μg. The selection criteria for high-quality eukaryotic assembled genomes are: integrity greater than 20% and genome contamination less than 5%.

2. The method according to claim 1, characterized in that, The environmental samples mentioned in step (1) include water samples and / or sediment samples; Preferably, the water sample collection method is as follows: at least two surface water samples from a depth of 0.3-0.8m are collected from the aquatic ecosystem and mixed thoroughly; Preferably, the sediment sample collection method is as follows: at least two bottom sediment samples from a depth of 0-5 cm are collected from the aquatic ecosystem and mixed thoroughly; Preferably, when water samples and sediment samples are collected simultaneously, the sediment samples are collected from the bottom sediment location corresponding to the water samples.

3. The method according to claim 2, characterized in that, The extraction and purification of DNA from the environmental sample includes: filtering a mixed surface water sample using a filter membrane, and then using liquid nitrogen to freeze-mill the filter membrane containing the water sample before DNA extraction; preferably, the pore size of the filter membrane is 0.22 μm; And / or, the extraction and purification of DNA from the environmental sample includes: centrifuging the sediment sample to remove the supernatant, followed by DNA extraction using 0.5-1g of the sediment sample.

4. The method according to claim 3, characterized in that, Each environmental sample underwent at least two independent DNA extraction operations. The extracted DNA from each environmental sample was then mixed, and the quality of the mixed DNA was assessed. High-quality DNA was then used for metagenomic sequencing.

5. The method according to any one of claims 1-4, characterized in that, The quality control described in step (3) is used to remove sequences containing uncertain bases, repetitive sequences, or possible contamination, ultimately obtaining high-quality short sequences.

6. The method according to any one of claims 1-5, characterized in that, The short sequence splicing described in step (3) is used to obtain the contiguous groups of the metagenomics.

7. The method according to any one of claims 1-6, characterized in that, The targeted and non-targeted genome binning methods described in step (3) include: A. The targeted binning method for contigs includes: using multiple annotation software to annotate and classify the contigs of metagenomics obtained by short sequence splicing, fusing and identifying eukaryotic contigs, screening eukaryotic sequences with contig length greater than 1kb, and binning the screened eukaryotic sequences to obtain targeted eukaryotic assembled genomes. B. The non-targeted binning method for contigs includes: binning all contigs with a sequence length greater than 1kb to obtain non-targeted assembled genomes; and selecting genomes with a eukaryotic sequence ratio greater than 0.8 in the non-targeted assembled genomes based on the eukaryotic contigs in the targeted binning.

8. The method according to claim 7, characterized in that, The quality assessment method described in step (3) is as follows: merge the results of targeted eukaryotic assembly genomes and non-targeted eukaryotic assembly genomes, conduct genome quality assessment, and select high-quality genomes as the final eukaryotic assembly genomes.

9. The method according to any one of claims 1-8, characterized in that, Step (4) includes: performing gene prediction on the eukaryotic assembled genome identified in step (3), then performing species annotation on the eukaryotic assembled genome, selecting eukaryotic algal genomes from the annotation results, then indexing the eukaryotic algal genomes and comparing them with the high-quality short sequences obtained in step (3), and finally calculating the abundance of eukaryotic algal genomes.

10. The method according to claim 9, characterized in that, Step (5) includes: comparing the predicted genes of the eukaryotic algae genome identified in step (4) with the reference database to identify the functional characteristics of key metabolic genes and algal toxin synthesis genes of eukaryotic algae, thereby comprehensively assessing the functional potential and ecological risks of eukaryotic algae.

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