Accurate blue-green algae identification method based on environmental DNA (deoxyribonucleic acid) technology

Abstract

The invention belongs to the technical field of biology and environment, and provides an accurate blue-green algae identification method based on an environment DNA (Deoxyribose Nucleic Acid) technology, which comprises the following steps: S1, taking PCbetaF and PCalphaR454 as upstream and downstream primers of a CPC-IGS gene respectively; s2, then establishing a PCR reaction system, wherein the PCR reaction system comprises 5-20 [mu] L of Takara Premix Taq enzyme, 0.25 [mu] M of upstream and downstream primers and 10 ng of microbial DNA; s3, then executing a PCR (Polymerase Chain Reaction) program; according to the accurate blue-green algae identification method based on the environmental DNA technology, by optimizing primer design, PCR amplification conditions and a high-throughput sequencing strategy and combining a biological information analysis method, the accuracy and resolution of blue-green algae species identification are remarkably improved, and powerful technical support is provided for environmental monitoring, ecological protection and blue-green algae resource development and utilization.

Description

Technical Field

[0001] The invention belongs to the field of biology and environmental technology, and specifically is a method for accurately identifying cyanobacteria based on environmental DNA technology. Background Art

[0002] Cyanobacteria are the main primary producers in aquatic environments and are also important functional groups in aquatic ecosystems. Under conditions of eutrophication, cyanobacteria will proliferate on a large scale to form cyanobacterial blooms, which pose serious threats to the health of aquatic ecosystems. Traditional cyanobacteria identification is mainly based on morphological microscopic observations, but it has limitations such as difficulty in standardization and automation, high professional knowledge requirements, and high manpower and material costs. Environmental DNA (eDNA) technology is a technology that directly extracts DNA fragments from environmental samples and uses high-throughput sequencing methods to analyze biological communities. The rapid development and application of eDNA technology in the past 20 years has revolutionized our understanding of microbial diversity in the environment.

[0003] At present, 16S rRNA gene has been successfully applied to the analysis of cyanobacterial communities, but this method also has some disadvantages; first, 16S rRNA gene sequencing will obtain information on all bacteria, of which cyanobacteria only account for a small part. In order to obtain sufficient cyanobacterial sequences, a higher sequencing depth is required, which not only increases the cost but also leads to data waste; second, this method can only be used for higher taxonomic levels (species or genus level and above), and it is difficult to effectively distinguish the large number of intraspecific variations of cyanobacteria; CPC-IGS gene is the gene spacer between the phycocyanin genes CPCB and CPCA, and can perform phylogenetic analysis of cyanobacterial communities at the species or intraspecific strain classification level. Its high specificity makes it possible to use CPC-IGS sequencing to detect extremely diverse cyanobacterial communities in the environment.

[0004] To this end, those skilled in the art have proposed a method for accurately identifying cyanobacteria based on environmental DNA technology to solve the problems raised by the background technology. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method for accurately identifying cyanobacteria based on environmental DNA technology to solve the problems existing in the prior art.

[0006] A method for accurately identifying cyanobacteria based on environmental DNA technology, comprising the following steps:

[0007] The upstream and downstream primers of S1 and CPC-IGS genes were PCβF and PCαR454, respectively;

[0008] S2, PCR reaction system is 20 μL, including 5-20 μL Takara Premix Taq enzyme (Ex Taq version 2.0 plus dye), 0.25 μM upstream and downstream primers and 10 ng microbial DNA;

[0009] S3, then execute the PCR program, the PCR program includes: 94℃ pre-denaturation for 3min; then 30 cycles, each cycle includes 98℃ denaturation for 10s, 54℃ annealing for 30s, 68℃ extension for 1min; finally 68℃ extension for 10min, then three repeated PCRs are performed on each sample at the same time, the products are combined and gel recovered, and then the Illumina platform is used for double-end 250bp sequencing strategy for high-throughput sequencing, and high-throughput sequencing is performed on the PCR products;

[0010] S4 and CPC-IGS gene sequencing data were analyzed using the same data analysis method as conventional 16S rRNA gene sequencing; the original data were then quality controlled using VSEARCH v.2.14.1, and the chimera sequences were removed using the UNOISE3 algorithm in USEARCH v11 to generate zOTUs (zero-radius Operational TaxonomicUnit) representing species information; the representative sequences of zOTUs were then annotated using SINTAX software, and based on the existing CPC-IGS sequences in the NCBI database and manually verified, the sequences of pure cultured cyanobacteria strains were selected as the reference database for annotation, and the similarity threshold was set to 0.8;

[0011] The cyanobacterial communities obtained by S5 and CPC-IGS gene sequencing were superior to those obtained by 16S rRNA gene sequencing in terms of diversity, species-level identification accuracy, and variability.

[0012] Preferably, in step S1, the PCβF is 5′-GGCTGCTTGTTTACGCGACA-3′ and the PCαR454 is 5′-GCTTCGGTRAKKGGRGTTTTCAT-3′.

[0013] The environmental DNA-based precise identification method for cyanobacteria provided by the present invention significantly improves the accuracy and resolution of cyanobacteria identification by optimizing primer design, PCR amplification conditions and high-throughput sequencing strategy, and combines bioinformatics analysis methods, thus providing strong technical support for environmental monitoring, ecological protection and the development and utilization of cyanobacteria resources.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] 1. Improve sequencing efficiency and reduce costs: CPC-IGS sequencing is specifically targeted at cyanobacteria, avoiding the generation of a large number of non-cyanobacteria sequences, significantly improving sequencing efficiency and reducing sequencing costs;

[0016] 2. Improve identification accuracy: CPC-IGS gene has high specificity and can accurately identify cyanobacteria at the species or intraspecific strain level. Compared with 16S rRNA gene sequencing, it can provide more detailed and accurate species information and biodiversity;

[0017] 3. Enhanced variation capture capability: CPC-IGS sequencing can better capture the internal variation of cyanobacterial communities, avoiding the problem of low resolution of cyanobacterial classification based on 16S rRNA gene sequencing and underestimation of the degree of internal variation of cyanobacterial communities, providing more reliable data support for in-depth research on cyanobacterial communities. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a map of the amplified regions of 16S rRNA and CPC-IGS genes of the present invention;

[0019] Figure 2 It is the experimental and data analysis flow chart of the present invention;

[0020] Figure 3 It is a schematic diagram of the α diversity of the cyanobacterial community obtained by amplification of 16S rRNA and CPC-IGS genes of the present invention;

[0021] Figure 4 It is a schematic diagram of the composition of cyanobacteria community at the order, family, genus and species level of the present invention;

[0022] Figure 5 It is a schematic diagram of the β diversity of the cyanobacterial community of the present invention. DETAILED DESCRIPTION

[0023] The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0024] Embodiment: The present invention provides a method for accurately identifying cyanobacteria based on environmental DNA technology, comprising the following steps:

[0025] The upstream and downstream primers of S1 and CPC-IGS genes were PCβF (5′-GGCTGCTTGTTTACGCGACA-3′) and PCαR454 (5′-GCTTCGGTRAKKGGRGTTTTCAT-3′), respectively;

[0026] S2, then set up a PCR reaction system, the PCR reaction system includes 5-20 μL Takara Premix Taq enzyme (Ex Taq version 2.0 plus dye), 0.25 μM upstream and downstream primers and 10 ng microbial DNA;

[0027] S3, then execute the PCR program, the PCR program includes: 94℃ pre-denaturation for 3min; then 30 cycles, each cycle includes 98℃ denaturation for 10s, 54℃ annealing for 30s, 68℃ extension for 1min; finally 68℃ extension for 10min, then three repeated PCRs are performed on each sample at the same time, the products are combined and gel recovered, and then the Illumina platform is used for double-end 250bp sequencing strategy for high-throughput sequencing, and high-throughput sequencing is performed on the PCR products;

[0028] S4 and CPC-IGS gene sequencing data were analyzed using the same data analysis method as conventional 16S rRNA gene sequencing; the original data were then quality controlled using VSEARCH v.2.14.1, and the chimera sequences were removed using the UNOISE3 algorithm in USEARCH v11 to generate zOTUs representing species information; the representative sequences of zOTUs were then annotated using SINTAX software, and based on the existing CPC-IGS sequences in the NCBI database and manually verified, the sequences of pure cultured cyanobacteria strains were selected as the reference database for annotation, and the similarity threshold was set to 0.8;

[0029] The cyanobacterial communities obtained by S5 and CPC-IGS gene sequencing were superior to those obtained by 16S rRNA gene sequencing in terms of diversity, species-level identification accuracy, and variability.

[0030] The embodiments of the present invention are further described in detail below with reference to the accompanying drawings and application examples.

[0031] Application example: CPC-IGS sequencing was used to accurately detect cyanobacterial communities. Surface water samples were collected from 140 stations in 59 lakes and reservoirs in my country. After removing large particles or suspended matter through a 200-μm sieve, plankton was collected through a 0.22-μm filter membrane (47 mm in diameter, Millipore, Billerica, MA, USA). DNA was then extracted using a DNA extraction kit (FastDNA Spin Kit, MP Biomedicals, Solon, OH, USA), and CPC-IGS and 16S rRNA gene amplification were performed, such as Figure 1As shown; CPC-IGS was amplified using primers PCβF (5′-GGCTGCTTGTTTACGCGACA-3′) and PCαR454 (5′-GCTTCGGTRAKKGGRGTTTTCAT-3′), and 16S rRNA gene was amplified using primers 341F (5′-CCTAYGGGRBGCASCAG-3′) and 806R (5′-GGACTACNVGGGTWTCTAAT-3′); PCR reaction system was 20 μL, including 5-20 μL Takara Premix Taq enzyme (Ex Taq version 2.0 plus dye, Takara Bio, Kusatsu, Shiga, Japan), 0.25 μM upstream and downstream primers and 10 ng microbial DNA; the PCR program of CPC-IGS gene included 94°C pre-denaturation for 3 min; 30 cycles, including 98°C denaturation for 10 s, 54°C annealing for 30 s, 68°C extension for 1 min; and finally 68°C extension for 10 min; the PCR program of 16S rRNA gene included 95°C pre-denaturation for 5 min; 30 cycles, including 95°C denaturation for 30 s, 55°C annealing for 30 s, 72°C extension for 30 s; and finally 72°C extension for 5 min; three replicates of PCR were performed for each sample at the same time, and the products were combined and recovered by gel, followed by high-throughput sequencing using the Illumina platform with a double-end 250 bp sequencing strategy;

[0032] The CPC-IGS and 16S rRNA gene data were analyzed in the same way. The original data were quality controlled by VSEARCH v.2.14.1, and the chimera sequences were removed using the UNOISE3 algorithm in USEARCH v11 to generate zero-radius Operational Taxonomic Units (zOTUs), which can be approximated as species. The representative sequences of zOTUs were annotated with species using SINTAX software, and the similarity threshold was set to 0.8. The 16S rRNA gene sequencing results were analyzed using SILVA v138.1 reference database for annotation. After removing the annotated archaea, chloroplasts, mitochondria, eukaryotic sequences, and unknown sequences without species classification information, the number of sequences of all samples was normalized to 113007, including a total of 13731 zOTUs. Then, cyanobacteria sequences were extracted based on the annotation information, and finally cyanobacteria zOTUs were retained, totaling 678. CPC-IGS gene sequencing results were based on the existing CPC-IGS sequences in the NCBI database. After manual verification, the sequences of pure cultured cyanobacteria strains were selected as the reference database for annotation, and a total of 5111 zOTUs were obtained, and each sample was normalized to 77599 sequences. The overall process is as follows: Figure 2 shown.

[0033] We applied the 16S rRNA gene analysis strategy of zOTU to CPC-IGS gene analysis of cyanobacterial communities. For the commonly used 16S rRNA gene sequencing method, only about 4.94% of the sequences obtained by high-throughput sequencing belonged to cyanobacteria and were retained, and most of the sequences were discarded. The diversity of cyanobacterial communities (number of species, estimated number of species, and Shannon-Wiener index) obtained by 16S rRNA gene sequencing was significantly lower than that obtained by CPC-IGS gene sequencing, such as Figure 3 As shown, it is demonstrated that more and more detailed cyanobacterial taxonomic units can be obtained based on CPC-IGS gene sequencing.

[0034] like Figure 4 As shown in the figure, the main species populations and abundances of cyanobacteria at the order, family, genus and species levels obtained based on 16S rRNA and CPC-IGS gene sequencing showed great differences. Especially at the species level, the dominant species obtained by CPC-IGS sequencing were all species with clear annotation information, while many of the dominant species obtained by 16S rRNA gene sequencing were uncultured or unidentified species, indicating that CPC-IGS sequencing can better distinguish cyanobacteria at low taxonomic levels (species level) and obtain more detailed and accurate species information and biodiversity.

[0035] like Figure 5 As shown in the figure, the β diversity of the cyanobacterial community obtained by CPC-IGS sequencing was significantly higher than the result of 16S rRNA gene sequencing, indicating that the CPC-IGS sequencing method can better capture the internal variation of the cyanobacterial community, while 16S rRNA gene sequencing will underestimate the degree of variation within the cyanobacterial community.

[0036] As can be seen from the above, CPC-IGS sequencing of the present invention is specifically used to detect cyanobacteria, avoiding the generation of a large number of non-cyanobacterial sequences, significantly improving sequencing efficiency, and reducing sequencing costs; at the same time, CPC-IGS sequencing can better capture the internal variation of cyanobacterial communities, avoiding the problems of low resolution of cyanobacterial classification and underestimation of the internal variation of cyanobacterial communities based on 16S rRNA gene sequencing, providing more reliable data support for in-depth research on cyanobacterial communities, and CPC-IGS genes have a high degree of specificity, and can accurately identify cyanobacteria at the species or intraspecific strain level. Compared with 16S rRNA gene sequencing, it can provide more detailed and accurate species information and biodiversity.

[0037] The effects of the cyanobacteria accurate identification method based on environmental DNA technology in the embodiment are compared with the current existing technology (16S rRNA gene sequencing), as shown in the following table:

[0038]

[0039] It can be seen from the above table that the present invention (precise identification method of cyanobacteria based on environmental DNA technology) is superior to the current existing technology (16SrRNA gene sequencing) in terms of sequencing efficiency and cost, identification accuracy, variation capture ability, diversity assessment, and species information accuracy. The technology of the present invention is suitable for large-scale promotion and application.

[0040] The embodiments of the present invention are provided for the purpose of illustration and description. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present invention. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for accurate identification of cyanobacteria based on environmental DNA technology, characterized by: The following steps are involved: The upstream and downstream primers of S1 and CPC-IGS genes were PCβF and PCαR454, respectively; S2, then set up a PCR reaction system, including 5-20 μL Takara Premix Taq enzyme, 0.25 μM upstream and downstream primers and 10 ng microbial DNA; S3, then executing a PCR program, the PCR program comprising: 94°C pre-denaturation for 3 min; then 30 cycles, each cycle comprising 98°C denaturation for 10 s, 54°C annealing for 30 s, and 68°C extension for 1 min; finally 68°C extension for 10 min, then performing three replicate PCRs on each sample simultaneously, the products were combined and then recovered by gel, and then high-throughput sequencing was performed using an Illumina platform with a double-end 250 bp sequencing strategy; S4 and CPC-IGS gene sequencing data were analyzed using the same data analysis method as conventional 16S rRNA gene sequencing; the original data were then quality controlled using VSEARCH v.2.14.1, and the chimera sequences were removed using the UNOISE3 algorithm in USEARCH v11 to generate zOTUs representing species information; the representative sequences of zOTUs were then annotated using SINTAX software, and based on the existing CPC-IGS sequences in the NCBI database and manually verified, the sequences of pure cultured cyanobacteria strains were selected as the reference database for annotation, and the similarity threshold was set to 0.8; The cyanobacterial communities obtained by S5 and CPC-IGS gene sequencing were superior to those obtained by 16S rRNA gene sequencing in terms of diversity, species-level identification accuracy, and variability.

2. The method for accurately identifying cyanobacteria based on environmental DNA technology as claimed in claim 1, characterized in that: In step S1, the PCβF is 5′-GGCTGCTTGTTTACGCGACA-3′ and the PCαR454 is 5′-GCTTCGGTRAKKGGRGTTTTCAT-3′.

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