A quantitative analysis method for thermal adaptation of farmland soil microbial community
By using the STR-CTR double-layer quantitative calculation model and high-throughput sequencing technology, the problem of quantitative analysis of thermal adaptation of farmland soil microbial communities was solved, providing a reliable basis for farmland fertilization management and improving soil carbon sequestration and crop yield.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-08
- Publication Date
- 2026-06-30
AI Technical Summary
Existing technologies lack quantitative analysis methods for the thermal adaptation of farmland soil microbial communities, which cannot reflect the overall response characteristics. Furthermore, the analysis results cannot guide farmland fertilization management practices. The lack of standardized quantitative calculation models and data verification methods leads to poor reliability and repeatability of the results.
Using the STR-CTR two-layer quantitative calculation model, combined with different fertilization management measures and seasonal warming in farmland, and through high-throughput sequencing and randomization validation, we quantified the response characteristics of microbial communities to temperature and established a standardized quantitative analysis method.
It enables precise quantitative assessment of the thermal adaptation of microbial communities, with highly reliable results that can guide farmland fertilization management under the background of global warming, thereby improving soil carbon sequestration and crop yield.
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Figure CN122303405A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of soil microbial detection and ecological assessment technology, specifically to a quantitative analysis method for the thermal adaptation of farmland soil microbial communities. Background Technology
[0002] Against the backdrop of global climate change (warming), soil microorganisms, as core participants in the material cycle and energy flow of ecosystems, play a crucial role in regulating soil carbon cycling and nutrient transformation through their thermal adaptability, directly impacting the stability and productivity of farmland ecosystems. In research related to global warming and soil carbon feedback, there is an urgent need for precise quantitative assessment of the thermal adaptability of soil microbial communities. However, current technologies lack effective methods for quantitative analysis of microbial community-level thermal adaptability in farmland soils.
[0003] Currently, most existing technologies for studying soil microorganisms suffer from the following problems: 1. Most studies focus on qualitative analysis of community structure or only study the temperature response of a single microbial species, which cannot reflect the overall response characteristics of the entire microbial community to temperature changes. 2. Existing research does not take into account the actual scenarios of different fertilization management measures in farmland and seasonal warming, and its analysis results cannot directly guide farmland fertilization management practices; 3. Existing analytical methods lack standardized quantitative calculation models and data verification methods, resulting in poor reliability and repeatability of analytical results, making it difficult to meet the actual needs of farmland soil ecology research under the background of global warming.
[0004] Therefore, developing an analytical method suitable for farmland soil, capable of accurately quantifying the thermal adaptation of microbial communities, providing reliable results, and guiding actual production has become an urgent technical problem to be solved in this field. Summary of the Invention
[0005] To overcome the shortcomings of existing technologies, this invention proposes a quantitative analysis method for the thermal adaptation of farmland soil microbial communities. This method fills the technical gap in the quantitative assessment of the thermal adaptation of farmland soil microbial communities, accurately reflects the overall response characteristics of microbial communities to temperature, and the results have been verified by multiple randomizations, demonstrating high reliability. It can directly provide a scientific quantitative basis for the formulation of farmland fertilization management measures, high and stable crop yields, and improvement of soil carbon sequestration under global warming.
[0006] The present invention provides a quantitative analysis method for the thermal adaptation of farmland soil microbial communities, comprising the following steps: S1. Soil sample collection and pretreatment: Collect farmland soil samples from 0-15cm depth in different seasons, pass them through a 2mm sieve, and store them at -80℃. S2. Microbial DNA Extraction and High-Throughput Sequencing: Soil microbial DNA was extracted and its quality was tested. The DNA was diluted to 1 ng / μL and amplified by PCR using primers 341F and 806R for the V3-V4 region of bacterial 16S rRNA gene and primers ITS5-1737F and ITS2-2043R for the ITS1 region of fungi. The amplified products were detected, quantified, and library constructed, and then sequenced using the Illumina PE300 platform. S3. Sequencing data processing and species annotation: After quality control and splicing of the raw sequencing data, OTU clustering was performed according to the 97% similarity threshold and chimeras were removed. Species taxonomy annotation was performed on the representative OTU sequences with a reliability threshold of 0.7 to obtain the species taxonomy annotation results. S4. Calculation of Species-Specific Temperature Response Index (STR): Based on species annotation results, the Spearman correlation coefficient between the relative abundance of a single species and soil temperature is quantified to obtain the STR value. A positive STR value indicates that the species accumulates as the temperature increases, while a negative value indicates that the species decreases as the temperature increases. S5. Calculation of Community Temperature Response Index (CTR): Based on the STR values of all species in the community, combined with the relative abundance of species, according to the formula... Calculate the CTR value, where It is the STR value of species i. CTR represents the relative abundance of species i. A positive CTR value indicates that the community is mainly dominated by warm-loving species, a negative value indicates that the community is mainly dominated by cold-loving species, and zero indicates that the number of the two types of species is roughly equal. S6. Randomization Validation: All data are randomly divided into an 80% subset for STR calculation and a 20% subset for CTR calculation, and the randomization is repeated 999 times to verify the reliability of the quantitative analysis results. S7. Determination of thermal adaptation of farmland soil microbial communities: Determine the thermal adaptation characteristics of farmland soil microbial communities based on CTR values and randomization validation results.
[0007] Preferably, in S1, the different seasons are winter, spring, and summer, with a continuous temperature gradient change, specifically the soil from January to June.
[0008] Preferably, soil microbial DNA is extracted using the CTAB method or the SDS method, the DNA extraction quality is detected by 1% agarose gel electrophoresis, and the PCR amplification products are detected by 2% agarose gel electrophoresis.
[0009] Preferably, when mixing samples of equal mass based on PCR product concentration, the recovered products are detected and quantified using Biotec's Synergy HTX, and the purified PCR products are library constructed using Bioo Scientific's NEXTFLEX Rapid DNA-Seq Kit.
[0010] Preferably, Fastp software is used for raw data quality control, Flash software is used for sequence assembly, Uparse software is used for OTU clustering, and RDP classifier is used for species taxonomic annotation.
[0011] Preferably, the collected farmland soil includes soils with different fertilization management treatments, which include at least one of the following: natural restoration, no fertilization, inorganic fertilizer, inorganic fertilizer + full straw return to the field, and inorganic fertilizer + cow manure return to the field.
[0012] Preferably, when collecting soil samples from different fertilization and management treatments, the temperature of the top 5cm layer of soil is measured simultaneously to obtain the temperature data of the corresponding soil samples.
[0013] Preferably, when quantifying the Spearman correlation coefficient, the correlation analysis is performed with soil temperature in different seasons as the x-axis and the relative abundance of the corresponding species as the y-axis.
[0014] Preferably, when calculating the CTR value, all detectable microbial species in the species annotation results are included, including dominant and rare species.
[0015] Preferably, in S7, when determining the thermal adaptation characteristics of a microbial community, the number of OTUs that are significantly correlated with temperature is combined to comprehensively analyze the community's response to temperature changes.
[0016] Preferably, a quantitative analysis method for the thermal adaptation of farmland soil microbial communities also includes comparative analysis of the thermal adaptation characteristics of farmland soil microbial communities under different fertilization management treatments, providing a basis for the formulation of farmland fertilization management measures.
[0017] Preferably, when conducting comparative analysis, if the CTR value is positive, it is determined that the soil microbial community under the fertilization management treatment has a high thermal adaptability and the impact of global warming on its soil carbon pool is small; if the CTR value is negative, it is determined that the soil microbial community under the fertilization management treatment has a low thermal adaptability and the impact of global warming on its soil carbon pool is high.
[0018] The beneficial effects of this invention are as follows: 1. This invention establishes for the first time a quantitative analysis method (MCTA) for thermal adaptation of farmland soil microbial communities, filling the gap in the existing technology for quantitative assessment of thermal adaptation of farmland soil microbial communities. Compared with existing temperature response studies of single species or qualitative analysis of community structure, it can accurately reflect the overall response characteristics of the entire microbial community to temperature changes. 2. This invention designs a standardized STR-CTR two-layer quantitative calculation model. First, the temperature response of a single species is quantified by Spearman correlation coefficient, and then the overall community response is calculated by weighting the relative abundance of species. This realizes a progressive quantitative analysis from the species level to the community level. The calculation logic is scientific, and the results can accurately characterize the thermal adaptability of the microbial community. 3. This invention sets up 999 randomization verification steps, randomly dividing the data into subsets and repeating the calculation, effectively eliminating the influence of accidental factors on the analysis results. Compared with existing analysis methods without verification steps, the reliability and repeatability of the results are greatly improved. 4. This invention combines different fertilization management measures in farmland with the actual scenario of seasonal warming, collects continuous soil samples from winter to spring to summer and measures the temperature simultaneously. The analysis results can directly reflect the differences in thermal adaptation of farmland soil microbial communities under different fertilization management, and can provide a scientific basis for the formulation of farmland fertilization management measures under the background of global warming, and has extremely high practical application value. Attached Figure Description
[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.
[0020] Figure 1 Line graphs showing the variation of soil temperature in different months under all treatments provided by this invention; Figure 2 This invention provides an analysis diagram of the thermal adaptation characteristics of soil bacterial communities under different treatments. Figure 3 This invention provides an analysis diagram of the thermal adaptation characteristics of soil fungal communities under different treatments. Figure Labels
[0021] NR - Natural recovery; NF - No fertilizer; NPK - Inorganic fertilizer; WS - Inorganic fertilizer + full straw return to the field; CM - Inorganic fertilizer + cow manure return to the field. Detailed Implementation
[0022] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.
[0023] Example 1
[0024] This embodiment uses a long-term experimental field (starting in 1983 to the present) in Mengcheng County, Anhui Province as the research object to conduct a quantitative analysis of the thermal adaptation of farmland soil microbial communities under different fertilization management treatments. This embodiment is only used to explain the present invention and is not intended to limit the scope of protection of the present invention.
[0025] A quantitative analysis method for the thermal adaptation of farmland soil microbial communities, comprising the following steps: S1. Soil Sample Collection and Pretreatment Soil samples from the experimental field at depths of 0-15 cm were collected on January 26, February 23, March 12, April 14, May 21, and June 15, 2015. Five fertilization management treatments were set up: natural recovery (NR), no fertilization (NF), inorganic fertilizer (NPK), inorganic fertilizer + full straw return to the field (WS), and inorganic fertilizer + cow manure return to the field (CM). Each treatment was replicated three times. The soil temperature at the top 5 cm of soil in each treatment was measured simultaneously during collection. Soil samples were sieved through a 2 mm sieve and stored in a refrigerator at -80℃.
[0026]
[0027] The data in the table above show that, with the changes of winter, spring and summer, the soil temperature of all treatments increased significantly and the trend was consistent. Among them, the increase in soil temperature was relatively slow from January to April, while the temperature increased sharply from April to June.
[0028] S2, Microbial DNA Extraction and High-Throughput Sequencing Microbial DNA was extracted from each soil sample using the CTAB method. The quality of DNA extraction was assessed by 1% agarose gel electrophoresis. Qualified samples were diluted with sterile water to a final concentration. PCR amplification was performed using bacterial primers 341F / 806R and fungal primers ITS5-1737F / ITS2-2043R, respectively. PCR products were detected by 2% agarose gel electrophoresis. Based on the concentration of PCR products, samples were mixed in equal masses. The recovered products were detected and quantified using Biotek Synergy HTX. Libraries were constructed using the Bioo Scientific NEXTFLEX Rapid DNA-Seq Kit, and sequencing was performed using the Illumina PE300 platform.
[0029] S3. Sequencing Data Processing and Species Annotation The raw sequencing data were quality controlled using Fastp software, the sequences were assembled using Flash software, OTUs were clustered using Uparse software with 97% similarity and chimeras were removed, and species annotations were performed on the representative OTU sequences using RDP classifier with a reliability threshold of 0.7 to obtain the species taxonomic annotation results.
[0030]
[0031] The data in the table above show that: the planinomycetes are the exclusive indicator phylum for CM treatment, the cyanobacteria can be used as a strong indicator group for NPK treatment, and the actinomycetes are significantly higher than NR and NF under WS, CM and NPK treatments.
[0032]
[0033]
[0034] As shown in Tables 3 and 4, for all treatments, Ascomycota and Basidiomycota were the dominant fungal groups, accounting for >75% of the total. Different treatments (NR / NF / WS / CM / NPK) had a highly significant impact on the fungal community composition at the phylum level. Specifically, Basidiomycota had the highest relative abundance under the CM treatment, Ascomycota under the WS treatment, Zygomycota under the NF treatment, and Chytridiomycota under the NPK treatment.
[0035] S4, Calculation of Species-Specific Temperature Response Index (STR) Based on the species annotation results, the Spearman correlation coefficient between the relative abundance of each species and soil temperature was calculated to obtain the STR value of each species. Positive STR values indicate warm-loving species, while negative STR values indicate heat-averse species.
[0036] S5, Calculation of Community Temperature Response Index (CTR) Based on the STR values of all species in the community, combined with the relative abundance of species, according to the formula... Calculate the CTR values of bacterial and fungal communities under each treatment, where... It is the STR value of species i. CTR represents the relative abundance of species i. A positive CTR value indicates that the community is mainly dominated by warm-loving species, a negative value indicates that the community is mainly dominated by cold-loving species, and zero indicates that the number of the two types of species is roughly equal.
[0037] S6, Randomization Validation All data were randomly divided into an 80% subset for STR calculation and a 20% subset for CTR calculation, and the randomization was repeated 999 times to verify the reliability of the quantitative analysis results.
[0038] S7. Determination of thermal adaptation of farmland soil microbial communities Combining CTR values and randomization validation results, the thermal adaptation characteristics of microbial communities under each treatment were determined. The results showed that the bacterial and fungal communities in the WS and NF treatments had positive CTR values, indicating that the communities were dominated by warm-loving species and had high thermal adaptation capabilities. The CTR values in the NR, NPK, and CM treatments were negative, indicating that the communities were dominated by heat-averse species and had low thermal adaptation capabilities. At the same time, the WS and NPK treatments had the highest number of OTUs that were significantly correlated with temperature, at 1171 and 1296 respectively, indicating a higher degree of response to temperature changes.
[0039] Example 2 The impact assessment of farmland soil carbon pool under different fertilization management treatments is based on the quantitative analysis results of Example 1. The impact of global warming on farmland soil carbon pool under each fertilization management treatment is assessed as follows: Inorganic fertilizer + full straw return to the field (WS) and no fertilizer (NF) treatments: the microbial community CTR value is positive, the thermal adaptability is high, and the impact of global warming on the soil carbon pool is relatively small. It can be regarded as the preferred fertilization management mode to enhance soil carbon sequestration under the background of global warming. Natural Restoration (NR) and Inorganic Fertilizer + Cow Manure Return to Field (CM) Treatments: The microbial community CTR value was negative, indicating low thermal adaptability. Global warming had a significant impact on its soil carbon pool, requiring targeted optimization of management measures to enhance the thermal adaptability of the microbial community.
[0040] For the appendix Figure 1 Analysis showed that soil temperature increased significantly in all treatments with the changes of winter, spring and summer, with a consistent trend (R2=0.884, p=0.005). Among them, the increase in soil temperature was relatively slow from January to April, while the temperature increased sharply from April to June. For the appendix Figure 2 Analysis reveals that: the total comparison in the figure represents the thermal adaptation index; the maximum value comparison represents the maximum STR value of soil community-specific species under different treatments; the minimum value comparison represents the minimum STR value of soil community-specific species under different treatments; the median comparison represents the median STR value of soil community-specific species under different treatments; the mean comparison represents the mean STR value of soil community-specific species under different treatments; and the OTU number represents the number of species significantly correlated with temperature under different treatments.
[0041] For the appendix Figure 3 Analysis reveals that: the total comparison in the figure represents the thermal adaptation index; the maximum value comparison represents the maximum STR value of soil community-specific species under different treatments; the minimum value comparison represents the minimum STR value of soil community-specific species under different treatments; the median comparison represents the median STR value of soil community-specific species under different treatments; the mean comparison represents the mean STR value of soil community-specific species under different treatments; and the OTU number represents the number of species significantly correlated with temperature under different treatments.
[0042] Conclusion: Fertilization management alters the thermal adaptation of soil microbial communities. Specifically, farmland abandonment and long-term application of inorganic fertilizer + cow manure reduced the thermal adaptation of soil bacterial and fungal communities, with these communities dominated by heat-averse species. In contrast, the treatments of inorganic fertilizer + straw return and no fertilization increased the thermal adaptation of soil microbial communities, with these communities dominated by heat-loving species. This indicates that global warming has a greater impact on the soil carbon pool of farmland under abandonment and inorganic fertilizer + cow manure treatments, and a relatively smaller impact on inorganic fertilizer + straw return and no fertilization. This method provides a scientific theoretical basis for the formulation of fertilization management measures to enhance farmland soil carbon pools under global warming.
[0043] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.
Claims
1. A quantitative analysis method for the thermal adaptation of farmland soil microbial communities, characterized in that, The specific steps include: S1. Soil sample collection and pretreatment: Collect farmland soil samples from 0-15cm depth in different seasons, pass them through a 2mm sieve, and store them at -80℃. S2. Microbial DNA Extraction and High-Throughput Sequencing: Soil microbial DNA was extracted and its quality was tested. The DNA was diluted to 1 ng / μL and amplified by PCR using primers 341F and 806R for the V3-V4 region of bacterial 16S rRNA gene and primers ITS5-1737F and ITS2-2043R for the ITS1 region of fungi. The amplified products were detected, quantified, and library constructed, and then sequenced using the Illumina PE300 platform. S3. Sequencing data processing and species annotation: After quality control and splicing of the raw sequencing data, OTU clustering was performed according to the 97% similarity threshold and chimeras were removed. Species taxonomy annotation was performed on the representative OTU sequences with a reliability threshold of 0.7 to obtain the species taxonomy annotation results. S4. Calculation of Species-Specific Temperature Response Index (STR): Based on species annotation results, the Spearman correlation coefficient between the relative abundance of a single species and soil temperature is quantified to obtain the STR value. A positive STR value indicates that the species accumulates as the temperature increases, while a negative value indicates that the species decreases as the temperature increases. S5. Calculation of Community Temperature Response Index (CTR): Based on the STR values of all species in the community, combined with the relative abundance of species, according to the formula... Calculate the CTR value, where It is the STR value of species i. CTR represents the relative abundance of species i. A positive CTR value indicates that the community is mainly dominated by warm-loving species, a negative value indicates that the community is mainly dominated by cold-loving species, and zero indicates that the number of the two types of species is roughly equal. S6. Randomization Validation: All data are randomly divided into an 80% subset for STR calculation and a 20% subset for CTR calculation, and the randomization is repeated 999 times to verify the reliability of the quantitative analysis results. S7. Determination of thermal adaptation of farmland soil microbial communities: Determine the thermal adaptation characteristics of farmland soil microbial communities based on CTR values and randomization validation results.
2. The quantitative analysis method for thermal adaptation of farmland soil microbial communities according to claim 1, characterized in that: In S1, the different seasons are winter, spring, and summer, with a continuous temperature gradient, specifically the soil from January to June.
3. The quantitative analysis method for the thermal adaptation of farmland soil microbial communities according to claim 1, characterized in that: In S2, soil microbial DNA is extracted using the CTAB method or the SDS method, the DNA extraction quality is detected by 1% agarose gel electrophoresis, and the PCR amplification products are detected by 2% agarose gel electrophoresis.
4. The quantitative analysis method for the thermal adaptation of farmland soil microbial communities according to claim 1, characterized in that: In S2, when mixing samples of equal mass based on PCR product concentration, the Synergy HTX from Biotek is used to detect and quantify the recovered products, and the NEXTFLEX Rapid DNA-Seq Kit from Bioo Scientific is used to construct libraries from the purified PCR products.
5. The quantitative analysis method for the thermal adaptation of farmland soil microbial communities according to claim 1, characterized in that: In S3, Fastp software was used for raw data quality control, Flash software was used for sequence assembly, Uparse software was used for OTU clustering, and RDP classifier was used for species taxonomic annotation.
6. The quantitative analysis method for the thermal adaptation of farmland soil microbial communities according to claim 1, characterized in that: In S1, the collected farmland soil includes soils with different fertilization management treatments. The fertilization management treatments include at least one of the following: natural restoration, no fertilization, inorganic fertilizer, inorganic fertilizer + full straw return to the field, and inorganic fertilizer + cow manure return to the field.
7. The quantitative analysis method for the thermal adaptation of farmland soil microbial communities according to claim 1, characterized in that: When collecting soil samples from different fertilization and management treatments, the temperature of the top 5cm layer of soil was measured simultaneously to obtain the temperature data of the corresponding soil samples.
8. The quantitative analysis method for the thermal adaptation of farmland soil microbial communities according to claim 6, characterized in that: In S4, when quantifying the Spearman correlation coefficient, the soil temperature in different seasons was used as the x-axis and the relative abundance of the corresponding species was used as the y-axis for correlation analysis.
9. The quantitative analysis method for the thermal adaptation of farmland soil microbial communities according to claim 1, characterized in that: In S5, when calculating the CTR value, all detectable microbial species in the species annotation results are included, including dominant and rare species.
10. The quantitative analysis method for thermal adaptation of farmland soil microbial communities according to claim 1, characterized in that: In S7, when determining the thermal adaptation characteristics of microbial communities, the number of OTUs that are significantly correlated with temperature is combined to comprehensively analyze the community's response to temperature changes.
11. The quantitative analysis method for the thermal adaptation of farmland soil microbial communities according to claim 1, characterized in that, It also includes a comparative analysis of the thermal adaptation characteristics of farmland soil microbial communities under different fertilization management treatments, providing a basis for the formulation of farmland fertilization management measures.
12. The quantitative analysis method for thermal adaptation of farmland soil microbial communities according to claim 11, characterized in that: When conducting comparative analysis, if the CTR value is positive, it is determined that the soil microbial community under the fertilization management treatment has a high thermal adaptability and the impact of global warming on its soil carbon pool is small. If the CTR value is negative, it is determined that the soil microbial community under the fertilization management treatment has a low thermal adaptability and the impact of global warming on its soil carbon pool is high.