Multi-dimensional comprehensive evaluation method for microbial diversity of hot spring

Abstract

The invention discloses a multi-dimensional comprehensive evaluation method for microbial diversity of a hot spring, which comprises the following steps: collecting a water sample, a sediment and a biological membrane along the temperature gradient of the hot spring to form a sample, and carrying out pretreatment and in-situ fixation on the sample; carrying out metagenome, metatranscriptome and amplicon sequencing treatment on the sample; calculating three-dimensional indexes of a structural stability index SSI, a functional activeness score FAS and abundance of an environmental adaptability gene set through multi-omics integration analysis; and generating a biodiversity comprehensive evaluation report through a three-dimensional index based on the environmental adaptation index EAI. According to the method, three-dimensional quantitative analysis of structure-function-environment adaptability is realized. Through multi-omics stack analysis and environment factor coupling modeling, the problem of integrity deficiency of extreme environment biological resource evaluation is solved.

Description

Technical Field

[0001] This invention belongs to the field of environmental microbiology technology, and specifically relates to a multi-dimensional comprehensive evaluation method for the microbial diversity of hot springs. It is particularly suitable for analyzing the microbial community structure and functional activity of high-temperature, strongly acidic / alkaline hot spring ecosystems. Background Technology

[0002] Hot springs, characterized by high temperatures (>45℃), extreme pH levels (pH<3 or >9), and low nutrient levels, foster unique microbial resources, making them crucial settings for discovering new species, functional genes, and studying community stability. In hot spring ecosystems, microbial diversity is a vital indicator of biological richness and ecological health. A comprehensive evaluation of hot spring microbial diversity requires consideration from multiple dimensions, including species diversity, functional diversity, community structural stability, and environmental adaptability.

[0003] As a core area of ​​research on microorganisms in extreme environments, the assessment of microbial diversity in hot springs has made significant progress in recent years in terms of methodology, ecological understanding, and resource exploration. However, existing technologies for assessing microbial diversity in hot springs still have many shortcomings. For example, traditional culture methods are limited by the culturability of microorganisms and cannot comprehensively reflect the microbial diversity in hot springs; while molecular ecology-based methods can overcome the limitations of culture methods, they still face challenges in terms of operational complexity, cost, and the accuracy of data analysis. In addition, existing assessment systems often focus on a single dimension, such as species diversity or functional diversity, lacking a comprehensive assessment framework, making it difficult to comprehensively and accurately evaluate the microbial diversity and ecological significance of hot springs.

[0004] In the prior art, invention CN 114937472 A uses amplicon sequencing for microbial community diversity analysis, and invention CN 116504308 A uses metagenomic microbial diversity OTU clustering and species annotation analysis. However, current traditional methods are difficult to simultaneously analyze the correlation between community structure stability and metabolic function, relying only on a single genome (such as 16S rRNA sequencing), ignoring the functional gene information of uncultured microorganisms and the impact of environmental factors on microbial diversity. At the same time, there is a lack of quantitative evaluation of biological adaptation mechanisms driven by extreme environmental factors. Summary of the Invention

[0005] Purpose of the Invention: The purpose of this invention is to provide a multi-dimensional comprehensive evaluation method for the microbial diversity of hydrothermal vents. This invention provides a hydrothermal vent biodiversity evaluation method that integrates multiple omics and couples environmental factors, achieving quantitative analysis across three dimensions: structure, function, and environmental adaptability. Through multi-omics cascaded analysis and environmental factor coupling modeling, it solves the problem of incomplete evaluation of biological resources in extreme environments.

[0006] Technical solution: The present invention provides a multi-dimensional comprehensive evaluation method for the microbial diversity of hot springs, comprising the following steps: Step 1: Collect water samples, sediments, and biofilms along the temperature gradient of the hot spring, and pre-treat and fix the samples in situ. Step 2: Perform metagenomic, metagenomic, and amplicon sequencing on the samples; Step 3: Calculate the three-dimensional indicators of structural stability index (SSI), functional activity score (FAS), and environmental adaptability gene abundance through multi-omics integration analysis. Step 4: Generate a comprehensive biodiversity assessment report based on the Environmental Adaptability Index (EAI) using three-dimensional indicators.

[0007] Furthermore, step 1 specifically includes the following steps: Step 1.1, Stratified sampling: Collect water samples, sediments and biofilms along the temperature gradient of the hot spring, which includes high temperature zone → medium temperature zone → low temperature zone. Take 20-30 liters of water sample. Step 1.2, Pretreatment: When the water sample is turbid and contains insoluble impurities, it should first be filtered with a 2-5 micrometer filter membrane, and then filtered with a 0.22 micrometer filter membrane. The filter membranes should be stored in a refrigerator at -80℃. Step 1.3, In situ fixation: Add RNA protectant to the water sample and quick-freeze with dry ice for metatranscriptomics analysis.

[0008] Furthermore, in step 2, the metagenomics is used to detect microbial composition and functional genes; the metatranscriptome is used to detect actively expressed genes; the metagenomics and metatranscriptome are achieved using Illumina NovaSeq paired-end sequencing; the amplicon sequencing uses 16S / 18S amplicon to detect the structure of bacteria, archaea, and eukaryotic microorganisms, and is achieved using V4-V5 region high-throughput sequencing.

[0009] Furthermore, step 3 specifically includes the following steps: Step 3.1: Calculate the structural stability index (SSI). The formula is as follows: SSI = (Robustness × 0.6) + (Modularity Index × 0.4) Among them, robustness is the rate at which the remaining network connectivity is maintained after 30% of the network nodes are randomly removed, with a robustness threshold of ≥0.65; modularity index is the degree to which a co-occurring network is divided into independent functional modules, with a modularity index threshold of 0.3-0.8, and >0.5 indicating high stability; When SSI ≥ 0.75, it indicates that the community structure is highly stable; when 0.55 ≤ SSI < 0.75, it indicates moderate stability; when SSI < 0.55, it indicates low stability. Step 3.2: Calculate the functional activity score FAS, which is the ratio of metagenomic transcriptome / metagenomic expression levels. When FAS > 1.5, it indicates highly active genes; when 0.6 ≤ FAS ≤ 1.5, it indicates basic activity; when FAS < 0.6, it indicates silenced or repressed genes. Step 3.3: The environmental adaptation gene set consists of genes related to extreme environments, including heat shock protein genes hsp20 / hsp70, pH homeostasis genes kdpABC, and metal resistance genes arsB / czcA.

[0010] Furthermore, in step 4, the Environmental Adaptability Index (EAI) includes three thresholds: temperature survival threshold: 78-82℃; pH adaptability threshold: pH < 2.2 or > 9.5; and sulfide inhibition threshold: > 2.1 mM.

[0011] Furthermore, in step 4, the comprehensive biodiversity assessment report is generated using three-dimensional indicators as follows: Optimal stability zone: 45-65℃, ΔT≤10℃, EAI value of 1, indicating that the microbial community structure is intact and its function is active; T is temperature; Mild stress zone: 65-75℃, ΔT≤10℃, EAI value 0.92-1.00, formula 1 - 0.002×(T-65)², indicating increased heat shock protein expression; 75-77℃, ΔT≤10℃, EAI value 0.85-0.92, formula 0.92-0.035×(T-75), indicating archaea proportion >70%, community structure begins to reorganize; High fluctuation response region: For any temperature T, 10℃ < ΔT ≤ 15℃, the EAI value is 0.95, and the formula is EAI_base × 0.95, which means the SSI threshold is increased to 0.68; For any temperature T, ΔT > 15℃, the EAI value is 0.9, and the formula is EAI_base × 0.9, which means the SSI threshold is increased to 0.72. Critical survival zone: 77-79℃, EAI value 0.70-0.85, formula 0.85×e^(-0.3×(T-77)), indicating significant archaeal community dominance; 79-81℃, EAI value 0.40-0.70, formula 0.70×e^(-0.5×(T-79)), indicating only hyperthermophilic archaea survive, and functional gene expression is restricted; Ultra-high temperature collapse zone: 81-82℃, EAI value 0.10-0.40, formula 0.40×e^(-1.2×(T-81)), indicating that the community diversity index decreased by more than 50% and the proportion of genes with FAS>1.5 was less than 5%; >82℃, EAI value ≤0.10, formula max(0.01,0.10×e^(-2.0×(T-82))), indicating that the archaeal community collapsed and only hyperthermophilic spores remained; final comprehensive score = original three-dimensional score × EAI.

[0012] The present invention also discloses a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method of the present invention.

[0013] The present invention also discloses a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implements the steps of the method of the present invention.

[0014] The present invention also discloses a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the method of the present invention.

[0015] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: 1. This invention addresses the industry pain point of "incomparable results" in biodiversity assessment and establishes a new threshold system.

[0016] 2. By introducing the SSI index, which is calculated using modularity and robustness weighting, the accuracy and reliability of biodiversity assessment are improved, providing a scientific basis for ecological environmental protection and restoration.

[0017] 3. Research on environmental adaptation gene sets provides a deeper understanding of the adaptability and survival ability of microorganisms in different environments, which helps to promote the development of microbiology and related fields.

[0018] 4. By acquiring data through multiple omics types, the comprehensiveness and integration of the data were achieved, overcoming the one-sidedness and limitations of single-omics data, and providing a more accurate and comprehensive information foundation for biodiversity assessment. Attached Figure Description

[0019] Figure 1 This is a flowchart of the present invention.

[0020] Figure 2 This is the evaluation result for a certain hot spring. Detailed Implementation

[0021] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0022] like Figure 1 As shown, the present invention provides a multi-dimensional comprehensive evaluation method for the microbial diversity of hot springs, comprising the following steps: Step 1: Collect water samples, sediments, and biofilms along the temperature gradient of the hot spring, and pre-treat and fix the samples in situ. Step 2: Perform metagenomic, metagenomic, and amplicon sequencing on the samples; Step 3: Calculate the three-dimensional indicators of structural stability index (SSI), functional activity score (FAS), and environmental adaptability gene abundance through multi-omics integration analysis. Step 4: Generate a comprehensive biodiversity assessment report based on the Environmental Adaptability Index (EAI) using three-dimensional indicators.

[0023] 1. Sample collection, preprocessing and in situ fixation Stratified sampling: Water, sediment and biofilm samples were collected along the hot spring temperature gradient (high temperature zone → medium temperature zone → low temperature zone), with 20 liters of water sample taken.

[0024] Pretreatment: If the water sample is turbid and contains a lot of insoluble impurities, first filter it with a 2-5 micrometer filter membrane. This step is to filter out the solid particles contained in the water sample. Then filter it with a 0.22 micrometer filter membrane. The filter membrane needs to be stored in a refrigerator at -80℃.

[0025] In situ fixation: RNA protectant was immediately added and the sample was flash-frozen on dry ice for use in metatranscriptomics analysis.

[0026] 2. Acquisition of multi-omics data

[0027] 3. Bioinformatics Analysis Workflow Starting with standardized sample collection and simultaneous recording of environmental parameters, multi-omics data generation was then carried out. Amplicon sequencing, using ASV clustering and diversity analysis techniques, revealed the community structure of prokaryotes and eukaryotes, and analyzed its association with environmental factors through correlation modeling. Metagenomic sequencing explored the metabolic potential and species functional characteristics of microbial communities through sequence assembly, gene prediction, and functional annotation. Metatranscriptome sequencing identified actively transcribed functional genes and metabolic pathways through differential expression analysis, thereby reflecting the real-time physiological activity of the community. In the multi-omics data integration stage, Procrustes analysis was used to correlate community structure with functional profiles, comparing pathway expression differences between metagenomics (potential function) and metatranscriptome (actual activity), and combining environmental driver analysis to elucidate the regulatory effects of key environmental factors such as temperature and sulfur concentration on microbial adaptive strategies. Furthermore, high-quality metagenomic assembly was obtained through metagenomic binning technology, and co-occurrence networks were used to infer interactions between microorganisms. Finally, a multi-omics integration + environmental factor coupling approach was used to study hydrothermal vent biodiversity.

[0028] 4. Generation of key evaluation indicators (1) Structural Stability Index (SSI): Based on species co-occurrence network analysis (species co-occurrence network analysis is the core method for revealing species interactions and ecosystem stability within microbial communities. The standardized operating procedure for hot spring microbial research includes 7 key steps and parameter settings, such as the number of nodes, edge density, and modularization).

[0029] Calculation formula: SSI = (Robustness × 0.6) + (Modularity Index × 0.4); Robustness: The rate at which network connectivity is maintained after 30% of network nodes are randomly removed (threshold: ≥0.65). Modularity index: the degree to which a co-occurring network is divided into independent functional modules (threshold: 0.3-0.8, >0.5 indicates high stability); Evaluation criteria: SSI≥0.75: The community structure is highly stable (strong resistance to environmental disturbances); 0.55≤SSI<0.75: Moderately stable; SSI < 0.55: Low stability; The robustness parameter in the structural stability index (SSI) was obtained through topological resilience analysis of the microbial co-occurrence network.

[0030] (2) Functional Activity Score (FAS): The ratio of metatranscriptomics to metagenomics expression levels (i.e., functional activity score, FAS) is a key indicator for assessing gene functional activity in microbial communities. This ratio reflects the actual expression intensity of genes under specific environments by comparing the abundance of gene transcription levels (mRNA) and genomic levels (DNA) in the same environmental sample.

[0031] Activity grading criteria: FAS>1.5: Highly active genes (significant expression); 0.6 ≤ FAS ≤ 1.5: Basic activity; FAS < 0.6: Silencing or repressing genes; (3) Environmental adaptation gene set: abundance and diversity of genes related to extreme environments (heat shock proteins, pH homeostasis, heavy metal resistance), quantify the explanatory power (%) of each environmental factor on species composition, and identify dominant factors.

[0032] In the multi-omics integration and environmental factor coupling biodiversity assessment system for hydrothermal vents, environmental factors are not only the drivers of community structure but also the core calibration parameters for the assessment results. Their role is reflected in four main stages: data collection, threshold calculation, model construction, and result interpretation.

[0033] Based on the Structural Stability Index (SSI) and Functional Activity Score (FAS) evaluation, dynamic correction is performed (environmental factors determine the threshold of biological indicators).

[0034] The SSI threshold fluctuates with temperature: for hot springs with a daily temperature difference >15℃, the SSI threshold increases from 0.65 to 0.72 (requiring higher stability and disturbance resistance).

[0035] FAS activity grading correction: The FAS threshold of the acid tolerance gene kdpABC in acidic hot springs (pH<3) decreased to 1.2 (due to high basal expression levels).

[0036] Comprehensive evaluation weighted (Environmental Adaptability Index (EAI))

[0037] Final composite score = Original three-dimensional score × EAI (Environmental Adaptability Coefficient).

[0038] like Figure 2 As shown, communities with SSI>0.7 and thermostable genes>0.3% had a survival rate>90% after a sudden temperature drop of 10℃ (validating the stability threshold); genes with FAS>1.5 showed a 3.2-fold increase in activity in industrial enzyme expression experiments (validating the functional threshold).

Claims

1. A method for multidimensional comprehensive evaluation of hot spring microbial diversity, characterized in that, Comprising the following steps: Step 1, collecting water samples, sediments and biofilm samples along the hot spring temperature gradient, and pretreating and in-situ fixing the samples; Step 2, processing the samples for metagenome, metatranscriptome and amplicon sequencing; Step 3, calculating the three-dimensional indicators of structural stability index SSI, functional activity score FAS and environmental adaptability gene set abundance through multi-omics integration analysis; Step 4, generating a comprehensive evaluation report of biological diversity based on the environmental adaptation index EAI through three-dimensional indicators.

2. The method according to claim 1, wherein, Step 1 specifically comprises the following steps: Step 1.1, hierarchical sampling: collecting water samples, sediments and biofilm samples along the hot spring temperature gradient, wherein the hot spring temperature gradient includes high temperature zone→medium temperature zone→low temperature zone, and 20-30 liters of water samples are taken; Step 1.2, pretreatment: when the water sample is turbid, it contains insoluble impurities, so first filter with a 2-5 micron filter membrane, then filter with a 0.22 micron filter membrane, and store the filter membrane in a -80℃ freezer; Step 1.3, in-situ fixation: add RNA protectant to the water sample and freeze it with dry ice for metatranscriptome analysis.

3. The method according to claim 1, wherein, In step 2, the metagenome is used to detect microbial composition and functional genes; the metatranscriptome is used to detect actively expressed genes; metagenome and metatranscriptome are realized through Illumina NovaSeq double-end sequencing means; the amplicon sequencing is 16S / 18S amplicon, which is used to detect bacterial, archaeal and eukaryotic microbial structures, and is realized through V4-V5 region high-throughput sequencing means.

4. The method according to claim 1, wherein, Step 3 specifically comprises the following steps: Step 3.1, calculate the structural stability index SSI, the formula is as follows: SSI = (robustness x 0.6) + (modularity index x 0.4) Wherein, robustness is the retention rate of network connectivity after randomly removing 30% of network nodes, and the robustness threshold is ≥0.65; modularity index is the degree of being divided into independent functional modules in the co-occurrence network, and the modularity index threshold is 0.3-0.8, >0.5 for high stability; When SSI≥0.75, it indicates that the community structure is highly stable; when 0.55≤SSI<0.75, it indicates moderate stability; when SSI<0.55, it indicates low stability; Step 3.2, calculate the functional activity score FAS as the ratio of metatranscriptome / metagene expression; when FAS > 1.5, it indicates high activity genes; when 0.6≤ FAS ≤ 1.5: it indicates basic activity; when FAS < 0.6: it indicates silent or inhibited genes; Step 3.3, the environmental adaptability gene set is the extreme environment related gene, including heat shock protein gene hsp20 / hsp70, pH homeostasis gene kdpABC and metal resistance gene arsB / czcA.

5. The method according to claim 1, wherein, In step 4, the environmental adaptation index EAI includes three thresholds; temperature survival threshold: 78-82℃; pH adaptability threshold: pH <2.2 or >9.5; sulfide inhibition threshold: >2.1 mM.

6. The method according to claim 1, wherein, In step 4, the three-dimensional indicators are used to generate a comprehensive evaluation report of biological diversity, specifically: Optimal stable zone: 45-65℃, ΔT≤10℃, EAI value is 1, indicating that the microbial community structure is complete and the function is active; T is temperature; Mild pressure zone: 65-75℃, ΔT≤10℃, EAI value is 0.92-1.00, formula is 1-0.002×(T-65)², indicating that the expression of heat shock protein increases; 75-77℃, ΔT≤10℃, EAI value is 0.85-0.92, formula is 0.92-0.035×(T-75), indicating that the proportion of archaea is >70% and the community structure starts to recombine; High fluctuation response zone: any T, 10℃<ΔT≤15℃, EAI value is 0.95, formula is EAI_base×0.95, indicating that the SSI threshold is raised to 0.68; any T, ΔT>15℃, EAI value is 0.9, formula is EAI_base×0.9, indicating that the SSI threshold is raised to 0.72; Critical survival zone: 77-79℃, EAI value is 0.70-0.85, formula is 0.85×e^(-0.3×(T-77)), indicating that the archaea community is dominant; 79-81℃, EAI value is 0.40-0.70, formula is 0.70×e^(-0.5×(T-79)), indicating that only hyperthermophilic archaea survive and the function gene expression is limited; Ultra-high temperature collapse zone: 81-82℃, EAI value is 0.10-0.40, formula is 0.40×e^(-1.2×(T-81)), indicating that the community diversity index decreases by >50% and the proportion of genes with FAS>1.5 is <5%; >82℃, EAI value is ≤0.10, formula is max(0.01,0.10×e^(-2.0×(T-82))), indicating that the archaea community collapses and only hyperthermophilic bacterial spores remain; the final comprehensive score = original three-dimensional score × EAI.

7. A computer apparatus comprising a memory, a processor, and a computer program stored on the memory, wherein the computer program, when executed by the processor, causes the processor to perform the method of any one of claims 1 to 6. The processor executes the computer program to implement the steps of the method of claim 1.

8. A computer readable storage medium having stored thereon computer programs / instructions, characterized in that, The computer program / instructions are executed by the processor to implement the steps of the method of claim 1.

9. A computer program product comprising computer programs / instructions, characterized in that, The computer program / instructions are executed by the processor to implement the steps of the method of claim 1. The computer program / instructions are executed by the processor to implement the steps of the method of claim 1.

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