Screening method and system of cellulose degrading bacteria

Abstract

The embodiment of the invention provides a screening method and system for cellulose degrading bacteria. The method comprises the following steps: determining all genes of all microorganisms to be screened in a sample to be detected and first gene abundance data of all genes; based on the functional gene set, screening out a plurality of target genes from all the genes; determining second gene abundance data of the plurality of target genes according to the first gene abundance data; determining the cellulose degradation fraction of each microorganism to be screened according to the second gene abundance data; screening out cellulose degrading bacteria in all the microorganisms to be screened according to the cellulose degradation fraction of each microorganism to be screened. Meanwhile, a large number of microorganisms to be screened can be analyzed, and the screening efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of bioinformatics, and in particular to a method and system for screening cellulose-degrading bacteria. Background Art

[0002] In the aerobic fermentation process of organic solid wastes such as crop straw and sludge, microorganisms play a core role in fermentation. Screening out microorganisms that can efficiently degrade cellulose plays a key role in improving fermentation efficiency. At present, the methods for measuring and screening cellulose-degrading bacteria are mainly experimental methods, such as Congo red staining and reducing sugar method.

[0003] The Congo red staining method uses the property of Congo red dye to form a red complex with cellulose in the culture medium. When cellulose is decomposed by cellulase, the Congo red-cellulose complex cannot be formed, so a transparent circle will appear in the culture medium with the cellulose-decomposing bacteria as the center. The cellulose degradation ability of microorganisms can be screened and measured by observing whether a transparent circle is produced and the size of the transparent circle. However, this method is relatively complicated in operation, and usually requires a large amount of dilution process to clearly observe the formation of the hydrolysis circle, so it is not suitable for large-scale screening.

[0004] The principle of the reducing sugar method for determining cellulase activity is based on the hydrolysis of cellulose by cellulase. Cellulase breaks down cellulose into reducing sugars, such as glucose. The dinitrosalicylic acid colorimetric method is usually used in experiments to determine the content of reducing sugars. However, this method has high requirements for precise control of experimental conditions, including temperature, reaction time and other factors, making the experimental operation relatively complicated and not suitable for large-scale screening.

[0005] Both the Congo red staining method and the reducing sugar method have the problem of complicated operation and high requirements for precise control of experimental conditions, which makes large-scale screening impossible and leads to low screening efficiency. Summary of the invention

[0006] The embodiments of the present application provide a method and system for screening cellulose-degrading bacteria, which are used to achieve high-throughput screening and simultaneously analyze a large number of microorganisms to be screened, thereby improving the screening efficiency.

[0007] In a first aspect, the present invention provides a method for screening cellulose-degrading bacteria, comprising:

[0008] Determine all genes of all microorganisms to be screened in the sample to be detected and first gene abundance data of all genes, wherein the first gene abundance data includes the gene abundance value of each gene in all genes in each microorganism to be screened;

[0009] Based on the functional gene set, a plurality of target genes are screened out from all the genes, wherein the functional gene set includes a plurality of functional genes for indicating cellulose degradation function;

[0010] Determining second gene abundance data of the plurality of target genes according to the first gene abundance data, wherein the second gene abundance data includes a gene abundance value of each target gene in the plurality of target genes in each microorganism to be screened;

[0011] Determining the cellulose degradation score of each microorganism to be screened according to the second gene abundance data;

[0012] Cellulose-degrading bacteria among all the microorganisms to be screened are screened out according to the cellulose-degrading score of each microorganism to be screened.

[0013] In a possible embodiment, determining the cellulose degradation score of each microorganism to be screened based on the second gene abundance data includes: determining a first preset number of control genes and third gene abundance data for each target gene based on the second gene abundance data and the first gene abundance data, wherein the third gene abundance data includes the average gene abundance of the first preset number of control genes for each target gene in each microorganism to be screened; determining a gene attribute vector of all target genes, wherein the gene attribute vector is used to indicate the activation attribute or inhibition attribute of all target genes; and calculating the cellulose degradation score of each microorganism to be screened based on the gene attribute vector, the second gene abundance data and the third gene abundance data.

[0014] In a possible embodiment, determining a first preset number of control genes and third gene abundance data for each target gene based on the second gene abundance data and the first gene abundance data includes: summing the first gene abundance data to obtain the total gene abundance value of each gene in all the genes in each microorganism to be screened; sorting the total gene abundance value of each gene according to size to generate an abundance sequence; based on the abundance sequence, dividing all the genes into a second preset number of groups; determining the group to which all the target genes belong, and randomly selecting the first preset number of control genes from the group to which each target gene belongs to generate multiple groups of the first preset number of control genes; according to the first gene abundance data, obtaining the average gene abundance of each group of the first preset number of control genes in each microorganism to be screened to generate third gene abundance data.

[0015] In a possible embodiment, the cellulose degradation score of each microorganism to be screened is calculated based on the gene attribute vector, the second gene abundance data and the third gene abundance data, including: generating a first gene abundance matrix based on the second gene abundance data; generating a second gene abundance matrix based on the third gene abundance data; and calculating a degradation score matrix based on the gene attribute vector, the first gene abundance matrix and the second gene abundance matrix, wherein the degradation score matrix includes the cellulose degradation score of each microorganism to be screened.

[0016] In a possible embodiment, screening out cellulose-degrading bacteria from among all the microorganisms to be screened according to the cellulose degradation score of each microorganism to be screened includes: sorting each microorganism to be screened according to the cellulose degradation score of each microorganism to be screened to obtain a degradation score sequence; and screening out cellulose-degrading bacteria from among all the microorganisms to be screened according to the degradation score sequence.

[0017] In a possible embodiment, the determining of all genes of all microorganisms to be screened in the sample to be detected and the first gene abundance data of all the genes includes: performing metagenomic sequencing on the sample to be detected, and performing data preprocessing on the obtained sequencing data to obtain a transcript per million TPM value corresponding to each overlapping group of each microorganism to be screened in the sample to be detected; calculating the standard abundance value of each microorganism to be screened according to the TPM value corresponding to each overlapping group of each microorganism to be screened; and calculating the gene abundance value of each gene in all the genes in each microorganism to be screened according to the standard abundance value of each microorganism to be screened to generate the first gene abundance data.

[0018] In a possible embodiment, before determining all genes of all microorganisms to be screened and the first gene abundance data of all genes, the method further includes: obtaining pathway information related to cellulose degradation from a preset database; obtaining cellulases related to cellulose degradation and genes of the cellulases based on the pathway information; obtaining regulatory genes for regulating the cellulases from a preset database; and generating the functional gene set based on the genes of the cellulases and the regulatory genes.

[0019] In a possible embodiment, the regulatory genes include transcription activator genes and transcription repressor genes.

[0020] In a possible implementation, the formula for calculating the degradation score matrix is:

[0021]

[0022] Where D is the degradation score matrix; X is the first gene abundance matrix; B is the second gene abundance matrix; vector(G) is the gene attribute vector.

[0023] In one possible embodiment, the formula for calculating the standard abundance value of each microorganism to be screened is:

[0024]

[0025] In the formula, Bin k _abundance_value represents the standard abundance value of the microorganism k to be screened; T k,j represents the TPM value of the jth overlapping group in the microorganism k to be screened; L k,j represents the length of the jth overlapping group in the microorganism k to be screened;

[0026] The formula for calculating the gene abundance value of each gene in each microorganism to be screened is:

[0027]

[0028] Where, Gene_abundance k,i Indicates the gene abundance value of gene i of microorganism k to be screened; mapped_gene_read_length k,i Indicates the length of the sequencing data mapped to gene i; gene_length i Indicates the gene length of gene i; Bin k _abundance_value represents the standard abundance value of the microorganism k to be screened.

[0029] In a second aspect, the present application provides a screening system for cellulose-degrading bacteria, comprising:

[0030] A determination module, used to determine all genes of all microorganisms to be screened in the sample to be detected and first gene abundance data of all genes, wherein the first gene abundance data includes the gene abundance value of each gene in all the genes in each microorganism to be screened;

[0031] A screening module, used for screening a plurality of target genes from all the genes based on a functional gene set, wherein the functional gene set includes a plurality of functional genes for indicating a cellulose degradation function;

[0032] The determination module is further configured to determine second gene abundance data of the plurality of target genes based on the first gene abundance data, wherein the second gene abundance data includes a gene abundance value of each target gene in the plurality of target genes in each microorganism to be screened;

[0033] The determination module is further used to determine the cellulose degradation score of each microorganism to be screened according to the second gene abundance data;

[0034] The screening module is also used to screen out cellulose-degrading bacteria from all the microorganisms to be screened according to the cellulose degradation score of each microorganism to be screened.

[0035] The screening method and system for cellulose-degrading bacteria provided in the embodiment of the present application, by determining all genes of all microorganisms to be screened and the first gene abundance data of all genes; based on the functional gene set, multiple target genes are screened from all genes; according to the first gene abundance data, the second gene abundance data of multiple target genes are determined; according to the second gene abundance data, the cellulose degradation score of each microorganism to be screened is determined; according to the cellulose degradation score of each microorganism to be screened, the cellulose-degrading bacteria in all microorganisms to be screened are screened. The limitation of strict control of experimental conditions in experimental screening is overcome, the problem of inconsistent screening conditions is eliminated, the high repeatability of screening is ensured, high-throughput screening can be performed, and a large number of microorganisms to be screened can be analyzed at the same time, thereby improving the screening efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0037] Figure 1 A schematic diagram of the structure of a computer device provided in an embodiment of the present application;

[0038] Figure 2 A schematic diagram of a process for screening cellulose-degrading bacteria provided in one embodiment of the present application;

[0039] Figure 3 A schematic diagram of the experimental results of a cellulose Congo red staining experiment in a test example of the present application;

[0040] Figure 4 A schematic diagram of the structure of a screening system for cellulose-degrading bacteria provided in an embodiment of the present application.

[0041] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0042] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of systems and methods consistent with some aspects of the present application as detailed in the appended claims.

[0043] The method for screening cellulose-degrading bacteria provided in the present application determines the gene abundance of target genes related to cellulose degradation function in all microorganisms to be screened; further determines the cellulose degradation score of each microorganism to be screened based on the gene abundance of the target gene; and screens out cellulose-degrading bacteria by ranking the cellulose degradation scores of each microorganism to be screened, thereby solving the technical problems that the existing technology cannot carry out large-scale screening and has low screening efficiency.

[0044] Figure 1 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present application, which is used to perform the screening method for cellulose-degrading bacteria provided in an embodiment of the present application. Figure 1 As shown, the computer device provided in this embodiment includes: a receiving device 101, a processor 102 and a display device 103.

[0045] It is understandable that the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the object identification method. In other feasible implementations of the present application, the above architecture may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or arrange the components differently, which can be determined according to the actual application scenario and is not limited here. Figure 1 The components shown may be implemented in hardware, software, or a combination of software and hardware.

[0046] In a specific implementation process, the receiving device 101 may be an input / output interface or a communication interface, and may acquire the data to be screened.

[0047] The processor 102 may process the data to be screened to determine a screening result.

[0048] The display device 103 can be used to display the above-mentioned screening results and the like.

[0049] The display device may also be a touch display screen, which is used to receive user instructions while displaying the above-mentioned content to achieve interaction with the user.

[0050] It should be understood that the above-mentioned processor can be implemented by the processor reading instructions in the memory and executing the instructions, or it can be implemented by a chip circuit.

[0051] In addition, the network architecture and business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Ordinary technicians in this field can know that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0052] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0053] Figure 2 A schematic diagram of a method for screening cellulose-degrading bacteria provided in one embodiment of the present application is shown in FIG. Figure 2 As shown, the method includes:

[0054] S201: Determine all genes of all microorganisms to be screened in the sample to be detected and first gene abundance data of all genes, wherein the first gene abundance data includes the gene abundance value of each gene in all genes in each microorganism to be screened.

[0055] Specifically, S201 specifically includes S2011~S2013:

[0056] S2011: Perform metagenomic sequencing on the sample to be tested, and perform data preprocessing on the obtained sequencing data to obtain the transcripts per million (TPM) value corresponding to each overlapping group of each microorganism to be screened in the sample to be tested.

[0057] Specifically, the obtained sequencing data are subjected to data quality control, sequence assembly, binning, gene prediction and gene annotation to obtain the gene data of each microorganism to be screened in the sample to be detected, wherein the gene data includes overlapping groups; the sequencing data are mapped to each overlapping group of each microorganism to be screened to obtain the TPM value corresponding to each overlapping group.

[0058] Specifically, the obtained sequencing data is subjected to connector sequence detection and quality control, and connectors and low-quality sequences are removed to obtain the first processed data; the first processed data is assembled separately to obtain the second processed data; the second processed data is binned according to the nucleic acid composition information characteristics and microbial abundance information characteristics of different microorganisms to obtain the third processed data. The third processed data is subjected to gene prediction and gene annotation using the de novo prediction method to obtain the fourth processed data; the gene data of each microorganism to be screened is generated based on the first processed data, the second processed data, the third processed data and the fourth processed data.

[0059] The second processed data includes the overlapping groups of each microorganism to be screened; the third processed data includes the genome sequence of each microorganism to be screened; and the fourth processed data includes the gene sequence and the corresponding translated amino acid sequence of each microorganism to be screened.

[0060] S2012: Calculate the standard abundance value of each microorganism to be screened according to the TPM value corresponding to each overlapping group of each microorganism to be screened.

[0061] The formula for calculating the standard abundance value of each microorganism to be screened is:

[0062]

[0063] In the formula, Bin k _abundance_value represents the standard abundance value of the microorganism k to be screened; T k,j represents the TPM value of the jth overlapping group in the microorganism k to be screened; L k,j Represents the length of the jth overlapping group in the microorganism k to be screened.

[0064] S2013: Calculate the gene abundance value of each gene in all genes in each microorganism to be screened according to the standard abundance value of each microorganism to be screened to generate first gene abundance data.

[0065] The formula for calculating the gene abundance value of each gene in each microorganism to be screened is:

[0066]

[0067] Where, Gene_abundance k,i Indicates the gene abundance value of gene i of microorganism k to be screened; mapped_gene_read_length k,i Indicates the length of the sequencing data mapped to gene i; gene_length i Indicates the gene length of gene i, in base number; Bin k_abundance_value represents the standard abundance value of the microorganism k to be screened.

[0068] S202: Based on the functional gene set, a plurality of target genes are screened out from all genes, wherein the functional gene set includes a plurality of functional genes for indicating cellulose degradation function.

[0069] Specifically, according to the gene identifiers in the functional gene set, all genes are matched to obtain multiple target genes.

[0070] S203: Determine second gene abundance data of the plurality of target genes according to the first gene abundance data, wherein the second gene abundance data includes a gene abundance value of each target gene in the plurality of target genes in each microorganism to be screened.

[0071] Specifically, according to the plurality of target gene representations, matching is performed with the first gene abundance data to obtain the second gene abundance data.

[0072] S204: Determine the cellulose degradation score of each microorganism to be screened based on the second gene abundance data.

[0073] Specifically, the gene attribute of each target gene is determined; based on the second gene abundance data and each gene attribute, the sum of the gene abundance values ​​of each target gene in each microorganism to be screened is calculated to obtain the cellulose degradation score of each microorganism to be screened.

[0074] S205: Screening out cellulose-degrading bacteria from all the microorganisms to be screened according to the cellulose degradation score of each microorganism to be screened.

[0075] Specifically, S205 includes S2051~S2052:

[0076] S2051: Sort each microorganism to be screened according to its cellulose degradation score to obtain a degradation score sequence.

[0077] Specifically, each microorganism to be screened is sorted from large to small or from small to large according to the cellulose degradation score to obtain a degradation score sequence.

[0078] S2052: Screen out cellulose-degrading bacteria from all microorganisms to be screened based on the degradation score sequence.

[0079] Specifically, according to the degradation score sequence, microorganisms to be screened whose cellulose degradation scores are higher than a preset threshold or whose cellulose degradation scores rank within a preset range are selected as cellulose degrading bacteria.

[0080] The method for screening cellulose-degrading bacteria provided in the embodiment of the present application is to determine all genes of all microorganisms to be screened and the first gene abundance data of all genes; screen multiple target genes from all genes based on the functional gene set; determine the second gene abundance data of multiple target genes according to the first gene abundance data; determine the cellulose degradation score of each microorganism to be screened according to the second gene abundance data; and screen out cellulose-degrading bacteria from all microorganisms to be screened according to the cellulose degradation score of each microorganism to be screened. The limitation of strict control of experimental conditions in experimental screening is overcome, the problem of inconsistent screening conditions is eliminated, the high repeatability of screening is ensured, high-throughput screening can be performed, and a large number of microorganisms to be screened can be analyzed at the same time, thereby improving the screening efficiency.

[0081] In one embodiment of the present application, based on the above embodiment, step S204 also provides another implementation method, which is described in detail as follows:

[0082] S2041: Determine a first preset number of control genes and third gene abundance data for each target gene based on the second gene abundance data and the first gene abundance data, wherein the third gene abundance data includes the average gene abundance of the first preset number of control genes for each target gene in each microorganism to be screened.

[0083] The first preset number may be 100.

[0084] Specifically, S2041 includes Sa~Se:

[0085] Sa: Sum the first gene abundance data to obtain the total gene abundance value of each gene in all genes in each microorganism to be screened.

[0086] The first gene abundance data may be in the form of a table, wherein the column headings are the names of the microorganisms to be screened, the row headings are the gene names, and the data are the gene abundance values ​​of the genes in the corresponding microorganisms to be screened.

[0087] Specifically, the gene abundance data in the first gene abundance data are summed row by row to obtain the total gene abundance value of each gene in all genes in each microorganism to be screened.

[0088] Sb: Sort the total gene abundance value of each gene by size to generate an abundance sequence.

[0089] Sc: All genes are divided into a second preset number of groups based on abundance sequences.

[0090] The second preset number may be 50.

[0091] Specifically, an abundance ranking table is generated according to the abundance sequence; and all genes are divided into a second preset number of groups according to the abundance ranking table.

[0092] Among them, the column headings of the abundance ranking table include: gene name, gene abundance and ranking, etc.

[0093] Table 1 is an abundance ranking table provided in the embodiment of the present application, as shown in Table 1:

[0094] Table 1

[0095]

[0096] Sd: Determine the groups to which all target genes belong, and randomly select a first preset number of control genes from the group to which each target gene belongs, so as to generate multiple groups of the first preset number of control genes.

[0097] Specifically, a gene grouping table is generated based on the group information of all genes; the group to which each target gene belongs is obtained based on the gene grouping table; and a first preset number of control genes corresponding to each target gene are randomly selected in each group to generate multiple groups of the first preset number of control genes.

[0098] The column headings of the gene grouping table include gene name, gene group, and gene type.

[0099] Among them, gene types include functional genes and others.

[0100] Table 2 is a gene grouping table provided in the embodiment of the present application, as shown in Table 2:

[0101] Table 2

[0102]

[0103] Se: According to the first gene abundance data, obtain the average gene abundance of each group of the first preset number of control genes in each microorganism to be screened to generate the third gene abundance data.

[0104] Specifically, the first gene abundance data is matched according to the control gene name to obtain the gene abundance value of each control gene; based on the gene abundance value of each control gene, the average gene abundance of each group of the first preset number of control genes in each microorganism to be screened is calculated to generate the third gene abundance data.

[0105] S2042: Determine gene attribute vectors of all target genes, where the gene attribute vectors are used to indicate activation attributes or inhibition attributes of all target genes.

[0106] Among them, the gene attribute vector can be a row vector.

[0107] Exemplarily, the gene attribute vector may be [1 1 -1 ...], where +1 represents that the target gene has an activation attribute, and -1 represents that the target gene has an inhibition attribute.

[0108] S2043: Calculate the cellulose degradation score of each microorganism to be screened based on the gene attribute vector, the second gene abundance data and the third gene abundance data.

[0109] From the above description, it can be seen that the embodiment of the present application determines the first preset number of reference genes and the third gene abundance data of each target gene according to the second gene abundance data and the first gene abundance data; and calculates the cellulose degradation score of each microorganism to be screened according to the gene attribute vector, the second gene abundance data and the third gene abundance data. The reference gene is used to correct the cellulose degradation score, thereby improving the accuracy of the cellulose degradation score and thus improving the accuracy of screening cellulose degrading bacteria.

[0110] In one embodiment of the present application, based on the above embodiment, step S2043 also provides another implementation method, which is described in detail as follows:

[0111] Sf: Generate the first gene abundance matrix based on the second gene abundance data.

[0112] Wherein, each column of the first gene abundance matrix represents the gene abundance value of each target gene in a microorganism to be screened.

[0113] Sg: Generate the second gene abundance matrix based on the third gene abundance data.

[0114] Each column of the second gene abundance matrix represents the average gene abundance of a first preset number of control genes corresponding to each target gene in a microorganism to be screened.

[0115] Sh: A degradation score matrix is ​​calculated based on the gene attribute vector, the first gene abundance matrix and the second gene abundance matrix, wherein the degradation score matrix includes the cellulose degradation score of each microorganism to be screened.

[0116] Among them, the gene attribute vector can be a row vector.

[0117] Among them, the formula for calculating the degradation score matrix is:

[0118]

[0119] Where D is the degradation score matrix; X is the first gene abundance matrix; B is the second gene abundance matrix; vector(G) is the gene attribute vector.

[0120] From the above description, it can be seen that the embodiment of the present application simplifies the calculation process of the degradation score by calculating the degradation score matrix according to the gene attribute vector, the first gene abundance matrix and the second gene abundance matrix, and provides a basis for simultaneously analyzing a large number of microorganisms to be screened.

[0121] In one embodiment of the present application, based on the above embodiment, a process of obtaining a functional gene set is further included, which is described in detail as follows:

[0122] S206: Obtaining pathway information related to cellulose degradation from a preset database.

[0123] Among them, the pathway information is the metabolic pathway of cellulose degradation, including the gradual decomposition of cellulose into cellobiose under the combined action of β-glucosidase (EC3.2.1.21), exoglucanase (cellodextrinase, EC 3.2.1.74), endoglucanase (EC 3.2.1.4) and cellobiohydrolase (EC 3.2.1.91) acting on the non-reducing end, and finally converted into D-glucose under the action of β-glucosidase.

[0124] S207: Obtain cellulase and cellulase genes related to cellulose degradation according to pathway information.

[0125] Among them, cellulases include endoglucanases, exoglucanases (cellodextrinase), exoglucanases (cellobiohydrolases acting at the non-reducing end), exoglucanases (cellobiohydrolases acting at the reducing end) and β-glucosidases.

[0126] S208: Obtaining regulatory genes for regulating cellulase from a preset database.

[0127] Among them, regulatory genes include transcription activator genes and transcription repressor genes.

[0128] Among them, the transcription activator genes include transcription factor genes that enhance the expression of cellulase genes and genes that constitute the transcription activation complex.

[0129] Among them, the genes constituting the transcriptional activation complex include cellulase expression activators, cellulase regulators and transcriptional activation complex-regulated cellulase genes in fungi.

[0130] Among them, the transcriptional repressor genes include genes that inhibit the expression of cellulase genes.

[0131] Specifically, the regulation process of cellulase gene expression is obtained from a preset database; and the regulatory gene for regulating cellulase is retrieved from the regulation process of cellulase gene expression.

[0132] S209: Generate a functional gene set based on cellulase genes and regulatory genes.

[0133] Table 3 is a functional gene set provided in the examples of this application, as shown in Table 3:

[0134] Table 3

[0135]

[0136] From the above description, it can be seen that the embodiment of the present application obtains cellulases and cellulase genes related to cellulose degradation according to pathway information; obtains regulatory genes for regulating cellulases from a preset database; and generates a functional gene set according to cellulase genes and regulatory genes. The functional gene set not only covers genes encoding cellulases, but also includes regulatory genes that regulate the expression of cellulase genes, thereby improving the accuracy of cellulose-degrading bacteria screening.

[0137] In an experimental example of the present application, a method for screening cellulose-degrading bacteria is provided for application in aerobic fermentation samples of sludge, as detailed as follows:

[0138] The sludge aerobic fermentation samples selected in this experimental example were obtained as follows: 1.5 tons of sludge were collected from the sewage treatment facility and fully mixed with corn straw in a mass ratio of 5:1 (1.5 tons of sludge and 300 kg of corn straw). An aerobic composting experiment was carried out and the mixture of sludge and auxiliary materials was sampled during the high temperature stage.

[0139] In this experiment, the cellulose degradation score D value of microorganisms in the sludge aerobic fermentation sample was determined, and the microorganisms were sorted in descending order according to the D value, and the top 5% of microorganisms were determined to have strong cellulose degradation ability and can be used as candidate cellulose degradation bacteria. For microorganisms with a D value less than or equal to 0, it was determined that they did not have the ability to degrade cellulose.

[0140] Through the above method, this experimental example screened out microorganisms with cellulose degrading ability and microorganisms that cannot degrade cellulose in sludge aerobic fermentation. Table 4 lists the D value data of typical microorganisms, as shown in Table 4:

[0141] Table 4

[0142]

[0143] The microorganisms screened out in this experimental example that have the ability to degrade cellulose are Clostridium thermocellum, Bacillus licheniformis, a specific strain of Streptomyces, and Bacillus subtilis. At the same time, a microorganism that does not have the ability to degrade cellulose is also identified.

[0144] In a test example of the present application, a cellulose Congo red staining experiment was performed on the microorganisms screened out in the above experimental example. The experimental process includes: selecting morphologically distinguishable target bacterial colonies, transferring them to a shaking tube, shaking and culturing them at 60 degrees and 150rpm for 48 hours, and then diluting them 1000 times and applying them on a cellulose Congo red medium. These culture media are placed in a constant temperature incubator, cultured at 55 degrees for 48-60 hours, and observing whether a transparent hydrolysis zone is formed.

[0145] Figure 3 Schematic diagram of the experimental results of the cellulose Congo red staining experiment in a test example of this application. Figure 3 It can be seen that the microorganisms with cellulose degradation ability obtained in the above experimental examples are numbered 1, 2, 3, and 4, and they form obvious transparent hydrolysis circles on the cellulose Congo red culture medium. In contrast, the microorganism without cellulose degradation ability, numbered 5, did not form a hydrolysis circle on the same culture medium.

[0146] from Figure 3 It can be seen that the screening method for cellulose degrading bacteria provided in the examples of the present application has high accuracy and reliability.

[0147] Figure 4 A schematic diagram of the structure of the screening system for cellulose-degrading bacteria provided in the embodiments of the present application is shown in FIG. Figure 4 As shown, the cellulose degrading bacteria screening system 40 provided in this embodiment includes: a determination module 401 and a screening module 402 .

[0148] A determination module 401 is used to determine all genes of all microorganisms to be screened in the sample to be detected and first gene abundance data of all genes, wherein the first gene abundance data includes the gene abundance value of each gene in all the genes in each microorganism to be screened;

[0149] A screening module 402 is used to screen a plurality of target genes from all the genes based on a functional gene set, wherein the functional gene set includes a plurality of functional genes for indicating a cellulose degradation function;

[0150] The determination module 401 is further configured to determine second gene abundance data of the plurality of target genes according to the first gene abundance data, wherein the second gene abundance data includes a gene abundance value of each target gene in the plurality of target genes in each microorganism to be screened;

[0151] The determination module 401 is further used to determine the cellulose degradation score of each microorganism to be screened according to the second gene abundance data;

[0152] The screening module 402 is further used to screen out cellulose-degrading bacteria from all the microorganisms to be screened according to the cellulose-degrading score of each microorganism to be screened.

[0153] In a possible implementation, the determination module 401 is specifically used to: determine a first preset number of control genes and third gene abundance data for each target gene based on the second gene abundance data and the first gene abundance data, wherein the third gene abundance data includes the average gene abundance of the first preset number of control genes for each target gene in each microorganism to be screened; determine a gene attribute vector of all target genes, wherein the gene attribute vector is used to indicate the activation attribute or inhibition attribute of all target genes; and calculate the cellulose degradation score of each microorganism to be screened based on the gene attribute vector, the second gene abundance data and the third gene abundance data.

[0154] In a possible implementation, the determination module 401, when "determining a first preset number of control genes and third gene abundance data for each target gene according to the second gene abundance data and the first gene abundance data", is specifically used to: sum the first gene abundance data to obtain the total gene abundance value of each gene in all the genes in each microorganism to be screened; sort the total gene abundance value of each gene according to size to generate an abundance sequence; based on the abundance sequence, divide all the genes into a second preset number of groups; determine the group to which all the target genes belong, and randomly select the first preset number of control genes from the group to which each target gene belongs to generate multiple groups of the first preset number of control genes; according to the first gene abundance data, obtain the average gene abundance of each group of the first preset number of control genes in each microorganism to be screened to generate third gene abundance data.

[0155] In a possible implementation, the determination module 401, when "calculating the cellulose degradation score of each microorganism to be screened according to the gene attribute vector, the second gene abundance data and the third gene abundance data", is specifically used to: generate a first gene abundance matrix according to the second gene abundance data; generate a second gene abundance matrix according to the third gene abundance data; calculate a degradation score matrix according to the gene attribute vector, the first gene abundance matrix and the second gene abundance matrix, wherein the degradation score matrix includes the cellulose degradation score of each microorganism to be screened.

[0156] In a possible implementation, the screening module 402 is specifically used to: sort each of the microorganisms to be screened according to the cellulose degradation score of each microorganism to be screened to obtain a degradation score sequence; and screen out cellulose-degrading bacteria from all the microorganisms to be screened according to the degradation score sequence.

[0157] In a possible implementation, the determination module 401 is specifically used to: perform metagenomic sequencing on the sample to be tested, and perform data preprocessing on the obtained sequencing data to obtain a TPM value of transcripts per million corresponding to each overlapping group of each microorganism to be screened in the sample to be tested; calculate the standard abundance value of each microorganism to be screened according to the TPM value corresponding to each overlapping group of each microorganism to be screened; calculate the gene abundance value of each of all the genes in each microorganism to be screened according to the standard abundance value of each microorganism to be screened, so as to generate first gene abundance data.

[0158] In a possible design, the screening system 40 for cellulose degrading bacteria further includes:

[0159] A generation module is used to obtain pathway information related to cellulose degradation from a preset database; obtain cellulase related to cellulose degradation and the gene of the cellulase according to the pathway information; obtain the regulatory gene for regulating the cellulase from a preset database; and generate the functional gene set according to the gene of the cellulase and the regulatory gene.

[0160] In one possible design, the regulatory genes include transcription activator genes and transcription repressor genes.

[0161] In one possible design, the formula for calculating the degradation score matrix is:

[0162]

[0163] Where D is the degradation score matrix; X is the first gene abundance matrix; B is the second gene abundance matrix; vector(G) is the gene attribute vector.

[0164] In a possible design, the formula for calculating the standard abundance value of each microorganism to be screened is:

[0165]

[0166] In the formula, Bin k _abundance_value represents the standard abundance value of the microorganism k to be screened; T k,j represents the TPM value of the jth overlapping group in the microorganism k to be screened; L k,jrepresents the length of the jth overlapping group in the microorganism k to be screened;

[0167] The formula for calculating the gene abundance value of each gene in each microorganism to be screened is:

[0168]

[0169] Where, Gene_abundance k,i Indicates the gene abundance value of gene i of microorganism k to be screened; mapped_gene_read_length k,i Indicates the length of the sequencing data mapped to gene i; gene_length i Indicates the gene length of gene i; Bin k _abundance_value represents the standard abundance value of the microorganism k to be screened.

[0170] The screening system for cellulose-degrading bacteria provided in this embodiment can execute the method provided in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be described in detail here.

[0171] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0172] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0173] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0174] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0175] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0176] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0177] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0178] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0179] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0180] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application, are not limited to the precise structures described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for screening cellulose-degrading bacteria, characterized in that: include: Determine all genes of all microorganisms to be screened in the sample to be detected and first gene abundance data of all genes, wherein the first gene abundance data includes the gene abundance value of each gene in all genes in each microorganism to be screened; Based on the functional gene set, a plurality of target genes are screened out from all the genes, wherein the functional gene set includes a plurality of functional genes for indicating cellulose degradation function; Determining second gene abundance data of the plurality of target genes according to the first gene abundance data, wherein the second gene abundance data includes a gene abundance value of each target gene in the plurality of target genes in each microorganism to be screened; Determining the cellulose degradation score of each microorganism to be screened according to the second gene abundance data; Cellulose-degrading bacteria among all the microorganisms to be screened are screened out according to the cellulose-degrading score of each microorganism to be screened.

2. The method according to claim 1, characterized in that Determining the cellulose degradation score of each microorganism to be screened according to the second gene abundance data comprises: Determine a first preset number of control genes and third gene abundance data for each target gene according to the second gene abundance data and the first gene abundance data, wherein the third gene abundance data includes an average value of gene abundance of the first preset number of control genes for each target gene in each microorganism to be screened; Determining gene attribute vectors of all target genes, wherein the gene attribute vectors are used to indicate activation attributes or inhibition attributes of all target genes; The cellulose degradation score of each microorganism to be screened is calculated based on the gene attribute vector, the second gene abundance data and the third gene abundance data.

3. The method according to claim 2, characterized in that Determining a first preset number of control genes and third gene abundance data for each target gene according to the second gene abundance data and the first gene abundance data includes: The first gene abundance data are summed to obtain a total gene abundance value of each gene in all the genes in each microorganism to be screened; Sorting the total gene abundance value of each gene according to size to generate an abundance sequence; Based on the abundance sequence, dividing all the genes into a second preset number of groups; Determine the groups to which all the target genes belong, and randomly select the first preset number of control genes from the group to which each target gene belongs, so as to generate multiple groups of the first preset number of control genes; According to the first gene abundance data, the average gene abundance of each group of the first preset number of control genes in each of the microorganisms to be screened is obtained to generate third gene abundance data.

4. The method according to claim 2, characterized in that: The step of calculating the cellulose degradation score of each microorganism to be screened according to the gene attribute vector, the second gene abundance data and the third gene abundance data comprises: generating a first gene abundance matrix according to the second gene abundance data; generating a second gene abundance matrix according to the third gene abundance data; A degradation score matrix is ​​calculated based on the gene attribute vector, the first gene abundance matrix and the second gene abundance matrix, wherein the degradation score matrix includes the cellulose degradation score of each microorganism to be screened.

5. The method according to any one of claims 1 to 4, characterized in that: The step of screening out cellulose-degrading bacteria from all the microorganisms to be screened according to the cellulose degradation score of each microorganism to be screened comprises: Sorting each of the microorganisms to be screened according to the cellulose degradation score of each of the microorganisms to be screened to obtain a degradation score sequence; Cellulose-degrading bacteria among all the microorganisms to be screened are screened out according to the degradation score sequence.

6. The method according to any one of claims 1 to 4, characterized in that: The step of determining all genes of all microorganisms to be screened in the sample to be detected and the first gene abundance data of all genes includes: Performing metagenomic sequencing on the sample to be tested, and performing data preprocessing on the obtained sequencing data to obtain a transcript per million TPM value corresponding to each overlapping group of each microorganism to be screened in the sample to be tested; Calculating the standard abundance value of each microorganism to be screened according to the TPM value corresponding to each overlapping group of each microorganism to be screened; According to the standard abundance value of each microorganism to be screened, the gene abundance value of each gene in all the genes in each microorganism to be screened is calculated to generate first gene abundance data.

7. The method according to any one of claims 1 to 4, characterized in that: Before determining all genes of all microorganisms to be screened and the first gene abundance data of all genes, the method further includes: Obtaining pathway information related to cellulose degradation from a preset database; Acquire cellulase related to cellulose degradation and the gene of the cellulase according to the pathway information; Obtaining a regulatory gene for regulating the cellulase from a preset database; The functional gene set is generated according to the cellulase gene and the regulatory gene.

8. The method according to claim 7, characterized in that The regulatory genes include transcription activator genes and transcription repressor genes.

9. The method according to claim 4, characterized in that The formula for calculating the degradation score matrix is: Where D is the degradation score matrix; X is the first gene abundance matrix; B is the second gene abundance matrix; vector(G) is the gene attribute vector.

10. The method according to claim 6, characterized in that The formula for calculating the standard abundance value of each microorganism to be screened is: In the formula, Bin k _abundance_value represents the standard abundance value of the microorganism k to be screened; T k,j represents the TPM value of the jth overlapping group in the microorganism k to be screened; L k,j represents the length of the jth overlapping group in the microorganism k to be screened; The formula for calculating the gene abundance value of each gene in each microorganism to be screened is: In the formula, Gene_abundance k,i Indicates the gene abundance value of gene i of microorganism k to be screened; mapped_gene_read_length k,i Indicates the length of the sequencing data mapped to gene i; gene_length i Indicates the gene length of gene i; Bin k _abundance_value represents the standard abundance value of the microorganism k to be screened.

11. A screening system for cellulose-degrading bacteria, characterized in that: include: A determination module, used to determine all genes of all microorganisms to be screened in the sample to be detected and first gene abundance data of all genes, wherein the first gene abundance data includes the gene abundance value of each gene in all the genes in each microorganism to be screened; A screening module, used for screening a plurality of target genes from all the genes based on a functional gene set, wherein the functional gene set includes a plurality of functional genes for indicating a cellulose degradation function; The determination module is further configured to determine second gene abundance data of the plurality of target genes based on the first gene abundance data, wherein the second gene abundance data includes a gene abundance value of each target gene in the plurality of target genes in each microorganism to be screened; The determination module is further used to determine the cellulose degradation score of each microorganism to be screened according to the second gene abundance data; The screening module is also used to screen out cellulose-degrading bacteria from all the microorganisms to be screened according to the cellulose degradation score of each microorganism to be screened.

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