Metagenome analysis method suitable for microbiota in straw mushroom growth process

Abstract

The invention relates to a metagenome analysis method suitable for microbiota in a straw mushroom growth process, and relates to the technical field of microorganism application, and the metagenome analysis method comprises the following steps: extracting a microbial genome DNA sample in the straw mushroom growth process; detecting the quantity and the quality of the extracted DNA samples to obtain quantity and quality detection results of DNA; constructing a metagenome sequencing library with the insertion length of 400bp by using the extracted DNA samples, and sequencing to obtain original sequencing reads; the original sequencing reads are subjected to cutting treatment, and filtered reads are obtained; performing optimization processing on the filtered reads to obtain an optimization result; and performing gene data analysis on the optimization result, wherein the analysis content comprises gene prediction and gene abundance statistics. According to the method, the blank of microorganism detection in the straw mushroom growth process is filled up, and rich and comprehensive information analysis content is provided on the metagenome level.

Description

Technical Field

[0001] The present application relates to the field of microbial application technology, and in particular to a metagenomic analysis method suitable for microbial communities in the growth process of straw mushrooms. Background Art

[0002] In China, the cultivation history of straw mushroom is very long, with a history of about 1,500 years. With the rapid development of science and technology, edible mushroom varieties are commercially produced. As the demand for edible mushrooms increases year by year, the annual output of edible mushrooms is also growing steadily. The production of straw mushrooms is characterized by a circular economy, in which agricultural by-products such as straw are used to produce nutritious and protein-rich foods. Therefore, straw mushrooms can make an important contribution to the growing demand for protein. According to research by Le Vinh Thuc et al., straw mushrooms have a unique flavor, pleasant taste, high protein content, and low production cost, so it is a good protein food to alleviate food shortages. And straw mushrooms can provide stable production throughout the year, which is conducive to meeting global food challenges.

[0003] Metagenomic analysis of fungal culture matrix microorganisms provides new possibilities for the growth environment of various microorganisms. The structure and dynamics of bacterial and fungal communities, as well as the characteristics and contributions of various bacterial and fungal groups in the matrix that promote the growth of straw mushrooms during cultivation, were studied. In order to further increase the yield of straw mushrooms, how to detect the changes in microorganisms during the growth of straw mushrooms has become an urgent problem to be solved in the field of microbial application technology. Summary of the invention

[0004] In order to detect the changes in microorganisms during the growth of straw mushrooms, the present application provides a metagenomic analysis method suitable for the microbial community during the growth of straw mushrooms.

[0005] The present application provides a method for analyzing the metagenomics of microorganisms in the growth process of straw mushrooms using the following technical solution: A metagenomic analysis method for microbial communities during the growth of straw mushrooms, comprising the following steps: Step 1: Extracting microbial genomic DNA samples during the growth process of straw mushrooms; Step 2: Detecting the quantity and quality of the extracted DNA sample to obtain the DNA quantity and quality test results; Step 3: construct a metagenomic sequencing library with an insert length of 400 bp from the extracted DNA sample and perform sequencing to obtain raw sequencing reads; Step 4: trimming the original sequencing reads to obtain filtered reads; Step 5: Optimizing the filtered reads to obtain optimization results; Step 6: Perform gene data analysis on the optimization results, including gene prediction and gene abundance statistics.

[0006] By adopting the above technical solution, the present application solves the problem of genetic detection of microorganisms during the growth of straw mushrooms and realizes the monitoring of changes in microorganisms.

[0007] Optionally, the step 1 specifically includes the following steps: The microbial genomic DNA samples during the growth process of Volvariella volvacea were extracted using the OMEGA mago-bind soil DNA kit (M5635-02).

[0008] Optionally, the step 2 specifically includes the following steps: The extracted DNA samples were sent to the Qubit with WiFi TM DNA quantity and quality were determined by 4-fluorimetry and agarose gel electrophoresis.

[0009] Optionally, the step three specifically includes the following steps: The extracted microbial DNA was used to construct a metagenomic sequencing library with an insert length of 400 bp using the Illumina TruSeq Nano DNALT Library Preparation Kit, and each library was sequenced on the Illumina NovaSeq platform using the PE150 method of Personal Biotechnology Co, Ltd.

[0010] Optionally, the step 4 specifically includes the following steps: The original sequencing reads were subjected to Cutadapt to remove sequencing adapters from the sequencing reads, and then low-quality reads were trimmed using a sliding window algorithm in fastp to obtain trimmed reads.

[0011] Optionally, the optimization process specifically includes the following steps: The filtered reads were subjected to 5-mode classification and classified against an nr-derived database that includes proteins from archaea, bacteria, viruses, fungi, and microbial eukaryotes. Each sample was assembled using Megahit with the meta-large preset parameters, and then the generated contigs longer than 300 bp were summarized and clustered by mmseq2 in the "easy-linclust" mode. The contigs were aligned to the NCBI-nt database by mmseq2 in the "taxonomy" mode to obtain the lowest classification of non-redundant contigs, and the contigs assigned to Viridiplantae or Metazoa were excluded to obtain the optimized results.

[0012] Optionally, the gene prediction in step 6 specifically includes the following steps: MetaGeneMark was used to predict genes for the optimized results, and the cds of all samples were clustered using mmseqs2 in “easy-cluster” mode, with a protein sequence recognition threshold of 0.90 and a coverage of 90% for shorter contigs residues.

[0013] Optionally, the gene abundance statistics in step 6 specifically include the following steps: The optimized results were mapped to the predicted gene sequences in the non-localized mode of “-meta minScoreFraction = 0.55”, and CPM was used to normalize the abundance values ​​in the metagenome.

[0014] Optionally, the method for analyzing the metagenomics of the microbial community during the growth process of the straw mushroom provided in the present application further includes functional annotation of non-redundant genes, and the functional annotation of the non-redundant genes includes the following steps: Annotations were obtained in mmseq2 using the “search” mode of the KEGG protein database, and KO results were obtained using KOBAS.

[0015] Compared with the prior art, the present application provides a method for analyzing the metagenome of microorganisms in the growth process of straw mushrooms, filling the gap in the detection of microorganisms in the growth process of straw mushrooms. In addition, the analysis method provided by the present application provides rich and comprehensive information analysis content at the metagenome level. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is the composition analysis of the top 20 microbial species at the phylum level in Example 1 of the present application;

[0017] Figure 2 It is the composition analysis of the top 20 microbial species in Example 1 of the present application;

[0018] Figure 3 is a heat map of the relative abundance of the top 20 species at the species level in Example 1 of the present application;

[0019] Figure 4 This is the analysis of different species in Example 1 of the present application;

[0020] Figure 5 This is the LEfSe analysis result in Example 1 of the present application. DETAILED DESCRIPTION

[0021] The present application provides a metagenomic analysis method for microbial communities during the growth of straw mushrooms, comprising the following steps: Step 1: Extracting microbial genomic DNA samples during the growth process of straw mushrooms; Step 2: Detecting the quantity and quality of the extracted DNA sample to obtain the DNA quantity and quality test results; Step 3: construct a metagenomic sequencing library with an insert length of 400 bp from the extracted DNA sample and perform sequencing to obtain raw sequencing reads; Step 4: trimming the original sequencing reads to obtain filtered reads; Step 5, optimizing the filtered reads to obtain optimization results; Step 6: Perform gene data analysis on the optimization results, including gene prediction and gene abundance statistics.

[0022] In the present invention, as an implementation mode, the step 1 specifically includes the following steps: The microbial genomic DNA samples during the growth process of Volvariella volvacea were extracted using the OMEGA mago-bind soil DNA kit (M5635-02).

[0023] In the present invention, as an implementation mode, the step 2 specifically includes the following steps: The extracted DNA samples were sent to the Qubit with WiFi TM DNA quantity and quality were determined by 4-fluorimetry and agarose gel electrophoresis.

[0024] In the present invention, as an implementation mode, the step three specifically includes the following steps: The extracted microbial DNA was used to construct a metagenomic sequencing library with an insert length of 400 bp using the Illumina TruSeq Nano DNA LT Library Preparation Kit, and each library was sequenced on the Illumina NovaSeq platform using the PE150 method of Personal Biotechnology Co, Ltd.

[0025] In the present invention, as an implementation mode, the step 4 specifically includes the following steps: The original sequencing reads were subjected to Cutadapt to remove sequencing adapters from the sequencing reads, and then low-quality reads were trimmed using a sliding window algorithm in fastp to obtain trimmed reads.

[0026] In the present invention, as an embodiment, the optimization process specifically includes the following steps: performing 5-mode classification on the filtered reads and classifying the nr-derived database, which includes proteins from archaea, bacteria, viruses, fungi and microbial eukaryotes, assembling each sample using Megahit through the meta-large preset parameters, and then aggregating and clustering the generated contigs with a length of more than 300bp using mmseq2 in the "easy-linclust" mode, comparing the NCBI-nt database using mmseq2 in the "taxonomy" mode to obtain the lowest classification of non-redundant contigs, and excluding the contigs assigned to Viridiplantae or Metazoa to obtain the optimization results.

[0027] In the present invention, as an implementation mode, the gene prediction in step 6 specifically includes the following steps: MetaGeneMark was used to predict genes for the optimized results, and the cds of all samples were clustered using mmseqs2 in “easy-cluster” mode, with a protein sequence recognition threshold of 0.90 and a coverage of 90% for shorter contigs residues.

[0028] In the present invention, as an implementation mode, the gene abundance statistics in step 6 specifically includes the following steps: The optimized results were mapped to the predicted gene sequences in the non-localized mode of “-meta minScoreFraction = 0.55”, and CPM was used to normalize the abundance values ​​in the metagenome.

[0029] In the present invention, as an embodiment, the method for analyzing the metagenomics of the microbial community in the growth process of Volvariella volvacea provided in the present application further includes functional annotation of non-redundant genes, and the functional annotation of the non-redundant genes includes the following steps: Annotations were obtained in mmseq2 using the “search” mode of the KEGG protein database, and KO results were obtained using KOBAS.

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in combination with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structure of the drawings is only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0031] Preparation Example 1:

[0032] Cultivate straw mushrooms. The growing conditions of straw mushrooms are:

[0033] Phase 1: The formula contained in the matrix is: 5% lime, 10% bran, 85% waste cotton, and about 65% water content; Original matrix material: Available nitrogen content: 0.6g / kg, Available phosphorus: 0.2g / kg; Each layer (1 layer = 1 bed, length * width * height: 130cm * 150cm * 15cm) total dry weight (before adding water): 26-28kg; total wet weight (after adding water): 40-48kg; Dry weight of each layer: waste cotton: 26kg, bran: 2kg, lime: 750g; Production cycle: 19 days, before fermentation: 5 days, 3 days after fermentation; Add nitrogen and phosphorus fertilizers.

[0034] Phase 2: Step 1: On the waste cotton substrate, different proportions of urea (50%) and diammonium phosphate (50%) were used to add nitrogen fertilizer, unit: grams; nitrogen content is: 0; 25; 50; 75; 100; (fertilizer is urea); phosphorus fertilizer, unit: grams; phosphorus content is: 0; 10; 20; 30; 40; (fertilizer is diammonium phosphate); Step 2: Apply the two fertilizers equally and separately, and apply them once on the second day after sowing; The results show that the appropriate pH value of the culture medium is one of the important conditions for the growth of mycelium. Selecting the appropriate culture medium and increasing the appropriate nitrogen and phosphorus fertilizer ratio are the key technical measures to increase the yield of straw mushrooms. When the nitrogen fertilizer ratio is 2.5:1, that is, 50 grams of nitrogen fertilizer and 20 grams of phosphorus fertilizer, the maximum yield is 4-4.3 kg / bed.

[0035] Embodiment 1:

[0036] Example 1 of the present application discloses a metagenomic analysis method for a microbial community during the growth of straw mushrooms, comprising the following steps: The total microbial genomic DNA samples in the culture medium of Volvariella volvacea were extracted by OMEGA mago-bind soil DNA kit (M5635-02) (OMEGA Bio-Tek, Norcross, GA, USA); Quantity and quality of extracted DNA by Qubit with WiFi TM 4 Fluorometer measurement: Q33238 (Qubit TM Assay Tubes: Q32856; qbitTM 1X dsDNA HS detection kit: Q33231) (Invitrogen, USA) and agarose gel electrophoresis; The extracted microbial DNA was used to construct metagenomic sequencing libraries with an insert length of 400 bp using the Illumina TruSeq Nano DNA LT Library Preparation Kit, and each library was sequenced on the Illumina NovaSeq platform (Illumina, USA) using the PE150 method of Personal Biotechnology Co, Ltd (Shanghai, China); The raw sequencing reads were processed to obtain high-quality filtered reads for further analysis. First, sequencing adapters were removed from the sequencing reads by Cutadapt (v1.2.1). Second, low-quality reads were trimmed by a sliding window algorithm in fastp. Once high-quality filtered reads were obtained, metagenomic sequencing reads of each sample were subjected to 5-mode classification by Kaiju and classified against an nr-derived database that includes proteins from archaea, bacteria, viruses, fungi, and microbial eukaryotes. Each sample was assembled using Megahit (v1.1.2) with the meta-large preset parameters, and then the generated contigs longer than 300 bp were summarized and clustered by mmseq2 in the “easy-linclust” mode. The contigs were aligned to the NCBI-nt database by mmseq2 in the “taxonomy” mode to obtain the lowest classification of non-redundant contigs, and contigs assigned to Viridiplantae or Metazoa were excluded from subsequent analysis; MetaGeneMark was used for gene prediction, and the cds of all samples were clustered using mmseqs2 in “easy-cluster” mode, with a protein sequence recognition threshold of 0.90 and a shorter contig residue coverage of 90%; High-quality reads of each sample were mapped to the predicted gene sequences in the non-positioning mode of “-meta minScoreFraction = 0.55”, and CPM (copies per kilobase per million mapped reads) was used to normalize the abundance values ​​in the metagenome; The functions of non-redundant genes were obtained by annotation in mmseq2 using the “search” mode against the KEGG protein database, and the KO results were obtained using KOBAS.

[0037] Data Results

[0038] The metagenome and species level of the total microorganisms in the culture medium of the Volvariella volvacea in Example 1 of the present application were analyzed, specifically, the composition of the microbial community at 5 time points after nitrogen and phosphorus application was determined, and each group of samples was repeated 3 times. The metagenome analysis diagram is shown in FIG. Figure 1 As shown, the species level diagram is as follows Figure 2 shown.

[0039] Depend on Figure 1 From the relative abundance of the phyla, the dominant species at the phylum level were Proteobacteria, Firmicutes, Bacteroidota, Actinobacteria, and Plantomycetota. In the CK and N3P3 treatments, Firmicutes dominated in AD and N3P3S. Under the CK treatment, the number of Proteobacteria in the AD period first decreased and then increased, while the number of Proteobacteria in the N3P3 group first decreased and then increased. Figure 1 It can be seen that Proteobacteria and Firmicutes were the most abundant microorganisms, Bacteroidetes and Actinobacteria showed no obvious trend, while the abundance of Pontomyces and Microbacteria gradually decreased during the growth of Volvariella. In the N3P3 treatment, Proteobacteria were the most abundant species initially, but in N3P3S, Actinobacteria and Firmicutes became the dominant species, and their relative abundance gradually increased until the end of the Volvariella growth cycle. In the CK treatment, the relative abundance of Basidiomycetes gradually increased during the growth period, with the highest abundance in AN and AS.

[0040] After filtering and quality control, the total effective data volume for metagenomic sequencing was 98,971,2102 reads, with an average Q30 of 94% per sample. A total of 22 phyla and 526 genera (15,426 ASVs) were identified in different groups (AN / AD / AS / AC / N3P3N / N3P3D / N3P3S / N3P3C). More than 35% of the ASVs were at the species level of the microbiome.

[0041] Depend on Figure 2 It can be seen that at the species level, the species richness of N3P3 in the microbial community structure among the groups increased by 10 times compared with the CK group. In each group, the abundance of Proteobacteria gradually increased under N3P3 treatment, and the abundance of Micromonospora increased by 5% under N3P3 treatment compared with the CK treatment. Proteobacteria and Micromonospora have become the dominant flora of N3P3. Brevibacillus was the main flora in CK treatment, and Micromonospora spherical was the main flora in N3P3 treatment.

[0042] The relative abundance of the top 20 species at the species level in Example 1 was tested, and the test results were as follows: Figure 3 As shown. Figure 3 It can be seen that the abundance of Proteobacteria increased in the CK group but decreased in the N3P3 group during the four different stages of the microbial community composition in the culture medium of Volvariella volvacea. In the N3P3 group, the abundance of Bacillus was higher, while that in the CK group was lower. As the cultivation process progressed, their relative abundance continued to change, reaching the highest abundance at the end of the cultivation process.

[0043] Species analysis was performed on different species in the unfertilized samples (AC: stage 1, AD: stage 2, AN: stage 3, AS: stage 4) and fertilized samples (N3P3C: stage 1; N3P3D: stage 2; N3P3 N: stage 3; N3P 3S: stage 4). The results are shown in Figure 4 As shown. Figure 4 It can be seen that there are seven different microbial communities at the phylum level, including Actinobacteria, Bacteroidetes and Firmicutes, among which Firmicutes and Actinobacteria have the highest abundance in the AD and N3P3S groups. At the species level, there are 10 different microorganisms, mainly Micromonospora sphaeroides, Proteobacteria and Brevibacillus, among which Proteobacteria and Micromonospora sphaeroides have the highest abundance in the AD and N3P3D groups.

[0044] The embodiment was subjected to LEfSe analysis, and the analysis results are as follows: Figure 4 As shown, there were 80 different functional metabolic pathways at the L3 level, including pathways related to body systems, transport and catabolism, bacterial chemotaxis, and terpenoid and polyketide metabolism. The N3P3 group had 54 highly expressed metabolic pathways, mainly including amino acid metabolism, nitrogen metabolism, genetic information processing, and energy metabolism.

[0045] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for analyzing the metagenomics of microorganisms during the growth of straw mushrooms, characterized in that: The following steps are involved: Step 1: Extracting microbial genomic DNA samples during the growth process of straw mushrooms; Step 2: Detecting the quantity and quality of the extracted DNA sample to obtain the DNA quantity and quality test results; Step 3: construct a metagenomic sequencing library with an insert length of 400 bp from the extracted DNA sample and perform sequencing to obtain raw sequencing reads; Step 4: trimming the original sequencing reads to obtain filtered reads; Step 5: Optimizing the filtered reads to obtain optimization results; Step 6: Perform gene data analysis on the optimization results, including gene prediction and gene abundance statistics.

2. A method for analyzing the microbial community during the growth of straw mushrooms according to claim 1, characterized in that: The step 1 specifically includes the following steps: The microbial genomic DNA samples during the growth process of Volvariella volvacea were extracted using the OMEGA mago-bind soil DNA kit (M5635-02).

3. A method for analyzing the microbial community during the growth of straw mushrooms according to claim 1, characterized in that: The step 2 specifically includes the following steps: The extracted DNA samples were sent to the Qubit with WiFi TM DNA quantity and quality were determined by 4-fluorimetry and agarose gel electrophoresis.

4. The method for analyzing the microbial community during the growth of straw mushrooms according to claim 1, characterized in that: The step three specifically includes the following steps: The extracted DNA was used to construct a metagenomic sequencing library with an insert length of 400 bp using the Illumina TruSeq Nano DNA LT Library Preparation Kit, and each library was sequenced on the Illumina NovaSeq platform using the PE150 method of Personal Biotechnology Co., Ltd.

5. The method for analyzing the microbial community during the growth of straw mushrooms according to claim 1, characterized in that: The step 4 specifically includes the following steps: The original sequencing reads were subjected to Cutadapt to remove sequencing adapters from the sequencing reads, and then low-quality reads were trimmed using a sliding window algorithm in fastp to obtain trimmed reads.

6. A method for analyzing the microbial community during the growth of straw mushrooms according to claim 1, characterized in that: The optimization process specifically comprises the following steps: The filtered reads were subjected to 5-mode classification and classified against an nr-derived database that includes proteins from archaea, bacteria, viruses, fungi, and microbial eukaryotes. Each sample was assembled using Megahit with the meta-large preset parameters, and then the generated contigs longer than 300 bp were summarized and clustered by mmseq2 in the "easy-linclust" mode. The contigs were aligned to the NCBI-nt database by mmseq2 in the "taxonomy" mode to obtain the lowest classification of non-redundant contigs, and the contigs assigned to Viridiplantae or Metazoa were excluded to obtain the optimized results.

7. The method for analyzing the microbial community during the growth of straw mushrooms according to claim 1, characterized in that: The gene prediction in step 6 specifically includes the following steps: MetaGeneMark was used to predict genes for the optimization results. The cds of all samples were clustered using mmseqs2 in "easy-cluster" mode, with a protein sequence recognition threshold of 0.90 and a coverage of 90% for shorter contigs residues.

8. The method for analyzing the microbial population during the growth of straw mushrooms according to claim 1, characterized in that: The gene abundance statistics in step 6 specifically include the following steps: The optimized results were mapped to the predicted gene sequences in the non-localized mode of "-meta minScoreFraction = 0.55", and CPM was used to normalize the abundance values ​​in the metagenome.

9. The method for analyzing the microbial community during the growth of straw mushrooms according to claim 1, characterized in that: Also included is the functional annotation of non-redundant genes, wherein the functional annotation of the non-redundant genes comprises the following steps: The annotations were obtained in mmseq2 using the "search" mode of the KEGG protein database, and the KO results were obtained using KOBAS.

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