Microbial community analysis method based on statistical analysis

Abstract

The invention provides a microbial community analysis method based on statistical analysis, and belongs to the technical field of microbial community analysis. The microflora analysis method comprises the following steps: collecting a plurality of water samples, and carrying out pretreatment; sequencing the microflora of the water sample by adopting high-throughput sequencing to obtain a microflora sequencing result; preprocessing the microbial community sequencing result by adopting OTU clustering analysis and species annotation to obtain a data preprocessing result; and analyzing the data preprocessing result by adopting a statistical method. According to the method disclosed by the invention, various microorganisms in the water sample are sequenced by adopting high-throughput sequencing, the sequencing process is rapid, the result is accurate, and the microflora sequencing result is analyzed by combining various statistical analysis means such as difference analysis, similarity analysis and diversity analysis; and the structural composition and characteristics of the microbial community can be analyzed more comprehensively and accurately.

Description

Technical Field

[0001] The present invention relates to the technical field of microbial community analysis, and in particular to a microbial community analysis method based on statistical analysis. Background Art

[0002] The water ecosystem not only provides water for humans, but also provides rich animal and plant resources. However, the global population continues to rise and is accompanied by high-quality economic development, causing rivers to be polluted by domestic and industrial sewage, and even becoming more and more serious, which ultimately leads to frequent eutrophication of water bodies. Domestic and industrial sewage is rich in nitrogen and phosphorus, which is the culprit of eutrophication. In addition, due to the construction of water conservancy projects such as power stations and reservoirs in recent years, the flow rate of rivers has slowed down, the flow state of rivers has been changed, and the water quality has deteriorated.

[0003] With the closure of the sluice gates of the water conservancy hub, the local water ecological balance has been greatly affected. The reservoir has blocked the water from the river, causing the flow rate of the water at the lower end of the river to slow down, seriously affecting its self-purification capacity, and the water body has been continuously polluted, with eutrophication becoming increasingly serious.

[0004] Microorganisms, which have existed for more than two billion years, are the beginning of all life. Their existence has greatly affected the circulation of various substances on the earth. Microorganisms play a vital role in the entire ecological cycle. They can not only degrade organic matter, but also decompose substances such as cellulose, thereby promoting the recycling of resources. For example, by finding the key genes for the degradation of different pollutants and combining them with a certain strain, multiple pollutants can be degraded at the same time, greatly exerting their potential. Due to the diversity and wide distribution of microorganisms, they have been widely used in ecological restoration projects, such as water pollution control and soil remediation. Microorganisms play a very important role in these processes.

[0005] Surveys show that with the rapid population growth and further industrialization, the discharge of domestic and industrial sewage is increasing year by year, and substances such as nitrogen and phosphorus in water bodies are increasing in direct proportion to them, which in turn promotes the massive reproduction of microorganisms in the original river channels and a sharp increase in the number of microorganisms. For aquatic ecosystems, studying microorganisms, studying the circulation process of substances and elements in aquatic ecosystems, and their response to the surrounding environment can help us better understand the characteristics and functions of aquatic ecosystems. By analyzing the relationship and intensity of the microbial population structure and function in water bodies, it is helpful to reveal the relationship between the microbial population structure and function in water bodies, and to reveal the intrinsic connection between the microbial population structure and function in water bodies.

[0006] Therefore, it is particularly important for water management to have a deep understanding of the changes in river water quality, the causes of eutrophication and the methods of control.

[0007] In recent years, with the continuous improvement of the understanding of ecological restoration, microbial restoration has become one of the important means to restore the self-repair ability of nature. Through screening, targeted domestication and cultivation, most organic matter can be biodegraded without causing secondary pollution, and is suitable for lakes and rivers.

[0008] Human beings have been studying microorganisms for hundreds of years and have now become very mature, including microbial preservation technology, pure strain culture technology, aseptic technology and microscopy technology. Generally speaking, the separation culture method is quite mature, but there are still many defects. For example, the cultivation conditions of organisms with close symbiotic relationships and parasitic nutrition are very difficult. In addition, not only the sampling process, transportation and preservation of samples will affect the results, but also the culture time during the experiment will cause more or less errors in the results. Therefore, the traditional separation culture method is only suitable for studying a small number of species. It is also impossible to reflect information such as the diversity and function of water microorganisms, and it is impossible to discuss the correlation and degree of correlation of microbial communities in a given environment. Therefore, it is difficult to achieve the purpose of using bacterial communities to control water pollution.

[0009] Therefore, it is of great practical significance to provide a method for analyzing microbial communities based on statistical analysis under a given environment. Summary of the invention

[0010] The purpose of the present invention is to provide a microbial community analysis method based on statistical analysis, aiming to solve the technical problem that the prior art cannot perform detailed analysis of microbial communities in a given environment and it is difficult to control water pollution by using bacterial communities. The method of the present invention uses high-throughput sequencing to sequence a variety of microorganisms in water samples. The sequencing process is fast and the results are accurate. The microbial community sequencing results are analyzed by combining a variety of statistical analysis methods such as difference analysis, similarity analysis and diversity analysis, so that the structural composition and characteristics of the microbial community can be analyzed more comprehensively and accurately.

[0011] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions:

[0012] The present invention provides a method for analyzing microbial communities based on statistical analysis, comprising the following steps:

[0013] Collect multiple water samples and perform pretreatment;

[0014] Sequencing the microbial community of the water sample using high-throughput sequencing to obtain a microbial community sequencing result;

[0015] The OTU cluster analysis and species annotation are used to preprocess the microbial community sequencing results to obtain data preprocessing results;

[0016] The data preprocessing results were analyzed using statistical methods.

[0017] Furthermore, collecting multiple water samples means collecting multiple water samples from different locations in the same area.

[0018] Furthermore, the preprocessing includes establishing a sequencing library based on the multiple water samples.

[0019] Furthermore, the reaction conditions for the high-throughput sequencing are: initial denaturation at 98°C for 2 minutes, denaturation at 98°C for 15 seconds, denaturation at 55°C for 30 seconds, extension at 72°C for 30 seconds, and denaturation at 72°C for 5 minutes.

[0020] Furthermore, the statistical method includes diversity analysis, similarity analysis and difference analysis.

[0021] Furthermore, the diversity analysis reflects the diversity of microorganisms in the water environment of the water sample through the Alpha diversity index.

[0022] Furthermore, the similarity analysis adopts the non-weighted group average method in cluster analysis to analyze the similarity between the multiple water samples.

[0023] Furthermore, the difference analysis is to analyze the differences between the multiple water samples through the LEfse analysis method.

[0024] The present invention also provides the application of the microbial community analysis method based on statistical analysis described in the above technical solution in the analysis of microbial communities in water environments and the use of microorganisms to control water pollution.

[0025] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0026] (1) The present invention adopts high-throughput sequencing, which can generate a large amount of data in one sequencing, and the sequencing speed is fast, and the sequencing of a large number of samples can be completed in a short time. At the same time, the sequencing accuracy is high.

[0027] (2) The present invention uses cluster analysis and species annotation to classify the sequences obtained by high-throughput sequencing, which can better analyze the structure of the microbial community, collect data with similar characteristics, and classify them to facilitate the subsequent use of statistical analysis methods to analyze the structural composition and structural characteristics of the microbial community.

[0028] (3) The present invention performs similarity analysis, diversity analysis and difference analysis on the obtained sequencing results. The present invention identifies the biological states of different microbial flora, including genes, metabolism and classification, through difference analysis. Based on the results, the influence of the abundance of various microorganisms on the niche differentiation effect is studied, which facilitates people to explore the mutual influence relationship between various classifications of microbial communities in a given water environment; the present invention explores the correlation between different categories of microorganisms in the microbial community through similarity analysis, thereby laying a foundation for exploring the correlation between the microbial community and different water environment factors; the present invention analyzes the microbial community in a given water environment by combining a variety of analysis methods such as diversity analysis, difference analysis and similarity analysis, and the analysis results are more comprehensive and accurate. DETAILED DESCRIPTION

[0029] The present invention provides a method for analyzing microbial communities based on statistical analysis, comprising the following steps:

[0030] Collect multiple water samples and perform pretreatment;

[0031] Sequencing the microbial community of the water sample using high-throughput sequencing to obtain a microbial community sequencing result;

[0032] The OTU cluster analysis and species annotation are used to preprocess the microbial community sequencing results to obtain data preprocessing results;

[0033] The data preprocessing results were analyzed using statistical methods.

[0034] Collect multiple water samples and perform pretreatment;

[0035] In the present invention, collecting multiple water samples means collecting multiple water samples from different locations in the same area.

[0036] At the same time, water will be collected by using a water sampler, and the water samples collected by the water sampler will be stored in sterile polyethylene bottles, and the bottles will be marked with labels for point marking, and then microbial sequencing will be carried out; before formally collecting water samples, the present invention will first sample the inside and outside of the river water sampler at the sampling point five times to minimize analysis errors, and the sampling depth is controlled at 0.3 to 0.5 m below the surface of the river water body.

[0037] Sequencing the microbial community of the water sample using high-throughput sequencing to obtain a microbial community sequencing result;

[0038] After collecting water samples, the present invention uses a DNA extraction reagent box to extract all DNA from a 0.22 μm ultra-low temperature stored water filter membrane and sediment according to the specific operating procedures in the reagent box manual, establishes a sequencing library, and then uses Illumina MiSeq PE300 high-throughput sequencing technology to identify the obtained PCR results.

[0039] The present invention adopts high-throughput sequencing, which can realize the generation of a large amount of data in one sequencing, and the sequencing speed is fast, and the sequencing of a large number of samples can be completed in a short time. At the same time, the sequencing accuracy is high.

[0040] In the present invention, the preprocessing includes establishing a sequencing library based on the multiple water samples.

[0041] In the present invention, the reaction conditions for high-throughput sequencing are: initial denaturation at 98°C for 2 minutes, denaturation at 98°C for 15 seconds, denaturation at 55°C for 30 seconds, extension at 72°C for 30 seconds, and denaturation at 72°C for 5 minutes.

[0042] The OTU cluster analysis and species annotation are used to preprocess the microbial community sequencing results to obtain data preprocessing results;

[0043] The present invention performs OTU clustering and species annotation on the obtained sequencing results, which is convenient for subsequent analysis using statistical analysis methods.

[0044] The present invention uses cluster analysis and species annotation to classify the sequences obtained by high-throughput sequencing, which can better analyze the structure of the microbial community, collect data with similar characteristics, and classify them to facilitate the subsequent use of statistical analysis methods to analyze the structural composition and structural characteristics of the microbial community.

[0045] The data preprocessing results were analyzed using statistical methods.

[0046] In the present invention, the statistical methods include diversity analysis, similarity analysis and difference analysis.

[0047] In the present invention, the diversity analysis reflects the diversity of microorganisms in the water environment of the water sample through the Alpha diversity index.

[0048] The present invention adopts the Alpha diversity index to reflect the diversity of microorganisms in the water environment of the water sample. On this basis, the Coverage index is used to evaluate the coverage of the sequencing data. If multiple samplings are performed, the OTU level curve can also be used to compare the species richness and uniformity of the multiple samplings. Combined with the Alpha diversity index results, a more complete and comprehensive analysis of the diversity between multiple groups of samples can be performed. In addition, the pheatmap package is used to draw a cluster heat map to visualize the results.

[0049] In the present invention, the similarity analysis adopts the non-weighted group average method in cluster analysis to analyze the similarity between the multiple water samples.

[0050] The present invention uses the common non-weighted group average method in cluster analysis to analyze and compare the similarities between multiple samples sampled by the present invention. This method judges the effect of clustering by the length of each branch of the hierarchical tree. Since the differences between microbial communities at the phylum level are smaller when the samples are collected, it is easier to extract the similarities of dominant species between each sample. Preferably, after cluster analysis, the principal component analysis method can be used to study the similarities of microbial communities that do not provide samples among multiple sample companies.

[0051] In the present invention, the difference analysis is to analyze the differences among the multiple water samples by using the LEfse analysis method.

[0052] The present invention identifies the biological states of different microbial flora, including genes, metabolism and classification, through differential analysis, and based on the results, the influence of the abundance of various microorganisms on the niche differentiation effect is analyzed, so as to facilitate people to explore the mutual influence relationship between various classifications of microbial communities in a given water environment; the present invention explores the correlation between different categories of microorganisms in the microbial community through similarity analysis, thereby laying the foundation for exploring the correlation between the microbial community and different water environmental factors; the present invention analyzes the microbial community in a given water environment through a combination of diversity analysis, differential analysis and similarity analysis, and the analysis results are more comprehensive and accurate.

[0053] The present invention also provides the application of the microbial community analysis method based on statistical analysis described in the above technical solution in the analysis of microbial communities in water environments and the use of microorganisms to control water pollution.

[0054] The technical solutions provided by the present invention are described in detail below in conjunction with the embodiments, but they should not be construed as limiting the protection scope of the present invention.

[0055] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for analyzing microbial communities based on statistical analysis, characterized in that: The following steps are involved: Collect multiple water samples and perform pretreatment; Sequencing the microbial community of the water sample using high-throughput sequencing to obtain a microbial community sequencing result; The OTU cluster analysis and species annotation are used to preprocess the microbial community sequencing results to obtain data preprocessing results; The data preprocessing results were analyzed using statistical methods.

2. The microbial community analysis method based on statistical analysis according to claim 1, characterized in that: The collecting of multiple water samples means collecting multiple water samples from different locations within the same area.

3. The microbial community analysis method based on statistical analysis according to claim 1, characterized in that: The preprocessing includes establishing a sequencing library based on the multiple water samples.

4. The microbial community analysis method based on statistical analysis according to claim 1, characterized in that: The reaction conditions for the high-throughput sequencing are: initial denaturation at 98°C for 2 minutes, denaturation at 98°C for 15 seconds, denaturation at 55°C for 30 seconds, extension at 72°C for 30 seconds, and denaturation at 72°C for 5 minutes.

5. The microbial community analysis method based on statistical analysis according to claim 1, characterized in that: The statistical methods include diversity analysis, similarity analysis and difference analysis.

6. The microbial community analysis method based on statistical analysis according to claim 1, characterized in that: The diversity analysis reflects the diversity of microorganisms in the water environment of the water sample through the Alpha diversity index.

7. The method for analyzing microbial communities based on statistical analysis according to claim 1, characterized in that: The similarity analysis adopts the non-weighted group average method in cluster analysis to analyze the similarity between the multiple water samples.

8. The method for analyzing microbial communities based on statistical analysis according to claim 1, characterized in that: The difference analysis is to analyze the differences between the multiple water samples through the LEfse analysis method.

9. Application of the microbial community analysis method based on statistical analysis according to any one of claims 1 to 8 in the analysis of microbial communities in water environments and the use of microorganisms to control water pollution.