Lake and reservoir water source algal bloom risk early warning system based on 16S / 18SrRNA gene expression quantity threshold

Abstract

The invention belongs to the technical field of lake and reservoir water source risk prediction, and provides a lake and reservoir water source algae bloom risk early warning system based on a 16S / 18SrRNA gene expression quantity threshold, and the method comprises the following steps: S1, collecting a sample from a lake and reservoir water source surface layer water body; s2, using 7-gate water bloom algae specific primers for blue-green algae, green algae, diatom, euglena, dinoflagellate, chrysophyta and cryptoalga; s3, based on the qPCR standard curve, calculating the copy number of the 16SrRNA / 18SrRNA gene of the seven water bloom algae; s4, when the gene expression quantity of a certain algal bloom algae continuously reaches 106-7 copy number / mL for 7-12 days, determining that the algal bloom algae is in a window phase; according to the threshold value of the gene expression quantity of the water bloom algae 16SrRNA / 18SrRNA, the window period of water bloom algae cells can be accurately recognized, so that early warning of the algae bloom risk in the lake and reservoir water source is achieved, and early warning of algae bloom outbreak in the lake and reservoir water source is achieved one week or above in advance.

Description

Technical Field

[0001] The present invention belongs to the technical field of risk prediction of lake and reservoir water sources, and specifically is an early warning system for algal bloom risks in lake and reservoir water sources based on 16S / 18SrRNA gene expression thresholds. Background Art

[0002] The algae life cycle consists of a delay phase, an outbreak phase, a maintenance phase, and a decline phase. The delay phase is a critical window before an algal bloom occurs. During this phase, the metabolic activity of algal cells increases significantly, and the gene expression levels of 16SrRNA (prokaryotic algae) and 18SrRNA (eukaryotic algae) increase dramatically, directly reflecting the degree of cell division activity.

[0003] The current algal bloom monitoring technology in lake and reservoir water sources mainly relies on algal density or chlorophyll a concentration as a basis for judgment (for example, the WHO cyanobacteria level 2 risk warning line is 1×10 5 However, such methods can only assess risk after an algal bloom occurs and cannot provide early warning.

[0004] To this end, those skilled in the art have proposed an early warning system for algal bloom risk in lake and reservoir water sources based on the 16S / 18SrRNA gene expression threshold 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 an early warning system for algal bloom risks in lake and reservoir water sources based on the 16S / 18SrRNA gene expression threshold, so as to solve the problems that the existing technology can only perform risk rating after the algal bloom outbreak and cannot achieve early warning.

[0006] To achieve the above objectives, the present invention provides an early warning system for algal bloom risk in lake and reservoir water sources based on the threshold of 16SrRNA / 18SrRNA gene expression levels to accurately identify the cell window period, including the following steps:

[0007] Step 1: Select cyanobacteria, green algae, diatoms, euglena, dinoflagellates, chrysophytes, and cryptophytes as standard reference bloom algae of the seven common freshwater algae phyla, and extract DNA using a column-based bacterial total DNA extraction kit;

[0008] Step 2: Use the DNA extracted in the first step to perform PCR reaction to obtain the amplified product, clone the amplified product into the pMD18-T vector, and then transfer the plasmid into Escherichia coli DH5α, culture it to OD600 = 2.0, collect the cells by centrifugation, and extract the plasmid using a plasmid extraction kit. Use a UV / visible spectrophotometer to measure the plasmid concentration at an absorbance of 260 nm; dilute the plasmid DNA in a 10-fold gradient of 10 -1, 10 -2 , 10 -3 , 10 -4 , 10 -5 , 10 -6 , 10 -7 , 10 -8 As a template for qPCR reactions;

[0009] Step 3: Perform qPCR on the serial dilutions of the standard plasmid DNA samples from step 2 using universal primers for seven algae phyla. The qPCR reaction mixture (total volume 20 μL) included: 0.2 μL of primer-F, 0.2 μL of primer-F, 10 μL of SYBR Green pre-mix, 2 μL of DNA template, and 7.6 μL of sterile distilled water. The reaction was performed as follows: pre-denaturation at 94°C for 40 s, followed by 35 cycles of 94°C for 6 s and 56-59°C for 35 s. A standard curve was plotted comparing the standard plasmid DNA sample (gene copy number) with the Ct value of the bloom algae.

[0010] Step 4: Collect 300-500 mL of surface water from the water source of the lake or reservoir once daily. Use a 0.45 μm filter to obtain an enrichment of algal cells from the bloom. Use a column-based bacterial total RNA extraction kit to rapidly extract and purify RNA from the algal solution sample. Use TransScript One-Step gDNA to transcribe the RNA into cDNA.

[0011] Step 5: Using the cDNA as a template, perform a qPCR reaction using the same universal primers for the seven algae phyla as in Step 3. The qPCR reaction mixture (total volume 20 μL) includes: 0.2 μL of primer-F, 0.2 μL of primer-R, 10 μL of SYBR Green pre-mix, 2 μL of cDNA template, and 7.6 μL of sterile distilled water. The qPCR reaction conditions are the same as in Step 3. Based on the standard curve drawn in Step 3, calculate the copy numbers of 16S rRNA and 18S rRNA RNA of these seven algae blooms to obtain the gene expression levels of 16S rRNA and 18S rRNA in the algae blooms.

[0012] Step 6: When the gene expression level of 16SrRNA / 18SrRNA of a certain bloom algae among the seven representative bloom algae reaches 10 6-7 The copy number / mL is 3 to 7 days or more, which is determined to be the window period of the algal bloom cells, and an early warning is given that the lake water source area has the risk of algal bloom outbreak within 1-2 weeks.

[0013] Compared with the prior art, the present invention has the following beneficial effects:

[0014] 1. The threshold value of the 16SrRNA / 18SrRNA gene expression level of algal blooms used in the present invention can accurately identify the window period of algal bloom cells, thereby achieving early warning of algal bloom risks in lake and reservoir water sources, and warning of algal bloom outbreaks in lake and reservoir water sources 1-2 weeks in advance.

[0015] 2. The 16SrRNA / 18SrRNA gene of algae blooms used in the present invention as a monitoring indicator has higher analysis accuracy than the traditional algae monitoring image data.

[0016] 3. The present invention uses specially designed primers specific to seven phyla of algae blooms, which can effectively distinguish between seven phyla of algae blooms, namely cyanobacteria, green algae, diatoms, naked algae, dinoflagellates, golden algae and cryptophytes. Compared with the traditional algae monitoring image data, the present invention has stronger specificity.

[0017] 4. The algae bloom qPCR reaction system designed by the present invention has a cost as low as 2 yuan per reaction system, which is low in cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of the early warning system for algal bloom risk in lake and reservoir water sources based on 16S / 18SrRNA gene expression thresholds of the present invention;

[0019] Figure 2 This is a schematic diagram of the present invention's 16SrRNA gene expression threshold-based early warning of cyanobacteria bloom outbreak status;

[0020] Figure 3 This is a schematic diagram of the present invention's early warning of green algae bloom outbreaks based on 18SrRNA gene expression thresholds;

[0021] Figure 4 This is a schematic diagram of the early warning of the outbreak of Euglena blooms based on the 18SrRNA gene expression threshold of the present invention;

[0022] Figure 5 This is a schematic diagram of the diatom bloom outbreak status warning based on the 18SrRNA gene expression threshold of the present invention;

[0023] Figure 6 This is a schematic diagram of the early warning of dinoflagellate bloom outbreak based on the 18SrRNA gene expression threshold of the present invention;

[0024] Figure 7 This is a schematic diagram of the present invention's early warning of cryptoalgal bloom outbreaks based on 18SrRNA gene expression thresholds;

[0025] Figure 8 Schematic diagram of the early warning of golden algae bloom outbreak based on 18SrRNA gene expression threshold of the present invention;

[0026] Figure 9 This is a schematic diagram of the early warning of cyanobacteria bloom outbreak status based on the 16SrRNA gene expression threshold in actual water bodies of the present invention. DETAILED DESCRIPTION

[0027] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0028] The present invention provides a system for accurately identifying the cell window period of algal blooms based on the 16SrRNA / 18SrRNA gene expression threshold, thereby realizing early warning of algal bloom risks in lake and reservoir water sources. Figure 1 As shown; through laboratory simulation and combination with natural water bodies, lakes and reservoirs, surface water bodies were used to enrich algal bloom cells, and RT-qPCR reaction was used to measure the gene expression levels of 16SrRNA / 18SrRNA in algal blooms.

[0029] Among them, the amplification primers of 16SrRNA and 18SrRNA of water bloom algae of the present invention include:

[0030]

[0031] The technical solution of the present invention is further described in detail below through specific implementation methods.

[0032] Example 1

[0033] In this example, the cyanobacteria bloom was simulated in the laboratory, and the initial chlorophyll a concentration was 2 μg / L, and the 16SrRNA gene expression level reached 10 6 The cell window period is detected. After 7 consecutive days, the chlorophyll a concentration exceeds 10 μg / L, and the cyanobacteria bloom breaks out. Figure 2 shown.

[0034] Example 2

[0035] In this example, the green algae bloom was simulated in the laboratory, and the initial chlorophyll a concentration was 2 μg / L, and the 18SrRNA gene expression level reached 10 7 The cell window period is identified. After 7 consecutive days, the chlorophyll a concentration exceeds 10 μg / L, and the green algae bloom breaks out. Figure 3 shown.

[0036] Example 3

[0037] In this example, the bloom of Euglena was simulated in the laboratory, and the initial chlorophyll a concentration was 2 μg / L, and the 18SrRNA gene expression level reached 10 6The cell window period is identified. After 8 consecutive days, the chlorophyll a concentration exceeds 10 μg / L, and the algae bloom breaks out. Figure 4 shown.

[0038] Example 4

[0039] In this example, the diatom bloom was simulated in the laboratory, and the initial chlorophyll a concentration was 2 μg / L, and the 18SrRNA gene expression level reached 10 6 The cell window period is detected. After 10 consecutive days, the chlorophyll a concentration exceeds 10 μg / L, and the cyanobacteria bloom breaks out. Figure 5 shown.

[0040] Example 5

[0041] In this example, the dinoflagellate bloom was simulated in the laboratory, and the initial chlorophyll a concentration was 2 μg / L, and the 18SrRNA gene expression level reached 10 7 The cell window period is identified. After 10 consecutive days, the chlorophyll a concentration exceeds 10 μg / L, and the dinoflagellate bloom breaks out. Figure 6 shown.

[0042] Example 6

[0043] In this example, the cryptoalgae bloom was simulated in the laboratory, and the initial chlorophyll a concentration was 2 μg / L, and the 18SrRNA gene expression level reached 10 6 The cell window period is identified. After 12 consecutive days, the chlorophyll a concentration exceeds 10 μg / L, and the cryptoalgal bloom breaks out. Figure 7 shown.

[0044] Example 7

[0045] In this example, the golden algae bloom was simulated in the laboratory, and the initial chlorophyll a concentration was 2 μg / L, and the 18SrRNA gene expression level reached 10 6 The cell window period is detected. After 8 consecutive days, the chlorophyll a concentration exceeds 10 μg / L, and golden algae blooms occur. Figure 8 shown.

[0046] Example 8

[0047] In this embodiment, early warning monitoring of algae blooms was carried out in natural water bodies, lakes and reservoirs. The initial chlorophyll a concentration was about 3 μg / L, and the expression level of cyanobacteria 16SrRNA gene reached 10 6 The cell window period is 10 days after the chlorophyll a concentration in the water exceeds 10 μg / L, cyanobacteria become the dominant species, cyanobacteria blooms occur, and the density of other algae in the blooms is much lower than that of cyanobacteria. Figure 9 shown.

[0048] The thresholds used in this study, based on 16SrRNA / 18SrRNA gene expression levels in algal blooms, can accurately identify the window period for algal bloom cells, enabling early warning of algal bloom risks in lake and reservoir water sources, with a 1-2 week lead time for warning of algal bloom outbreaks. Compared to traditional algal monitoring image data, this method offers higher analysis accuracy, stronger specificity, and lower cost.

[0049] Comparative Example: The effects of the lake and reservoir water source algal bloom risk early warning system based on the 16S / 18SrRNA gene expression threshold of the embodiment and the current lake and reservoir water source algal bloom monitoring technology (comparative example) were compared to obtain the following table:

[0050]

[0051] As can be seen from the above table: Compared with the current technology that relies on algae density or chlorophyll a concentration for algal bloom monitoring, the lake and reservoir water source algal bloom risk early warning system based on 16S / 18SrRNA gene expression threshold has shown significant advantages: by monitoring gene expression, an indicator that directly reflects the degree of cell division activity, the system can achieve accurate early warning 1-2 weeks before the algal bloom outbreak, with greatly improved analytical accuracy and specificity. The cost of each qPCR reaction system is as low as 2 yuan, the operation is relatively standardized, not subject to the subjective influence and judgment of the operator, and the implementation difficulty is moderate; existing technologies mostly conduct risk assessment after the algal bloom outbreak, cell density determination is subject to the subjective influence of the operator, the analytical accuracy and specificity are low, the cost is high, and it is difficult to achieve early warning.

[0052] 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. An early warning system for algal bloom risk in lake and reservoir water sources based on 16S / 18SrRNA gene expression thresholds, characterized by: The following steps are involved: S1. Collect samples from surface water bodies at lake and reservoir water sources, enrich algal bloom cells through filter membranes, extract algal total RNA using a column-based bacterial total RNA extraction kit, and generate cDNA through reverse transcription reaction; S2. Using primers specific to seven phyla of bloom-forming algae, including cyanobacteria, green algae, diatoms, naked algae, dinoflagellates, golden algae, and cryptophytes, the cDNA in step (1) was subjected to real-time quantitative PCR (qPCR) reaction to measure the gene expression levels of 16SrRNA / 18SrRNA; S3. Calculate the 16SrRNA / 18SrRNA gene copy numbers of seven phyla of bloom-forming algae based on the qPCR standard curve; S4. When the gene expression level of a certain algae bloom reaches 10 for 3 to 7 consecutive days, 6-7 When the copy number is 0.1 / mL, the algae is determined to be in the window period, and a warning is issued that there is a risk of algal bloom outbreak in the lake and reservoir water source within 1-2 weeks.

2. The early warning system for algal bloom risk in lake and reservoir water sources based on 16S / 18S rRNA gene expression thresholds according to claim 1, characterized in that: The specific primers in step S2 include: Cyanobacteria: forward primer Cyan-F (SEQ ID NO: 1) and reverse primer Cyan-R (SEQ ID NO: 2); Green algae: forward primer Chl-F (SEQ ID NO: 3) and reverse primer Chl-R (SEQ ID NO: 4); Diatoms: forward primer Bac-F (SEQ ID NO: 5) and reverse primer Bac-R (SEQ ID NO: 6); Euglena: forward primer Eug-F (SEQ ID NO: 7) and reverse primer Eug-R (SEQ ID NO: 8); Dinoflagellate: forward primer Din-F (SEQ ID NO: 9) and reverse primer Din-R (SEQ ID NO: 10); Cryptomonas: forward primer Cry-F (SEQ ID NO: 11) and reverse primer Cry-R (SEQ ID NO: 12); Chrysophyte: forward primer Chr-F (SEQ ID NO: 13) and reverse primer Chr-R (SEQ ID NO: 14).

3. The early warning system for algal bloom risk in lake and reservoir water sources based on 16S / 18S rRNA gene expression thresholds according to claim 1, characterized in that: The qPCR reaction system is: The total volume is 20 μL, including 10 μL of SYBR Green premix, 0.2 μL of forward primer, 0.2 μL of reverse primer, 2 μL of template, and the balance is sterile distilled water; The reaction conditions were: pre-denaturation at 94°C for 40 seconds, followed by 35 cycles of denaturation at 94°C for 6 seconds and annealing / extension at 56-59°C for 35 seconds.

4. The early warning system for algal bloom risk in lake and reservoir water sources based on 16S / 18S rRNA gene expression thresholds according to claim 1, characterized in that: The warning threshold is dynamically adjusted according to the algae species: The window period threshold for cyanobacteria, diatoms, cryptophytes, golden algae, and euglena is a gene expression level ≥10 6 Copy number / mL; The window period threshold for green algae and dinoflagellates is gene expression level ≥10 7 Copy number / mL.

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