CN109166602B - Microbe macro-gene analysis system and method for aerobic composting of kitchen waste - Google Patents
Microbe macro-gene analysis system and method for aerobic composting of kitchen waste Download PDFInfo
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Abstract
The application relates to a kitchen waste aerobic composting microbial macro-gene analysis system and a method, belonging to the technical field of bioinformatics, wherein the system comprises: the method comprises the steps that a browser obtains a target biological label, a target primer sequence and target high-throughput sequencing data; the server splits the target high-throughput sequencing data according to the target biological label and the target primer sequence to obtain at least one group of biological sequences; analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results; adhering at least two analysis results through an adhesion procedure to obtain a biological classification report; performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result; sending the analysis result to a browser for display; can improve the analysis efficiency of the microbial macro gene and reduce the analysis difficulty.
Description
Technical Field
The invention relates to a system and a method for analyzing macro genes of microorganisms for aerobic composting of kitchen waste, belonging to the technical field of bioinformatics.
Background
Microbial metagenomics is a leading-edge technology system developed in recent years for exploring the microbial population structure and processes in complex environmental samples such as compost, soil, sediment and the like. The microbial metagenomics can simultaneously detect hundreds to thousands of samples in a single experiment, the generated data amount reaches 50-60 gigabytes (Gb), and the Gb contains thousands to hundreds of millions of gene sequences.
Microbial metagenomics enables the discovery of microbial dynamic processes in complex systems. However, due to the large amount of data, data analysis is difficult, and a variety of biological information analysis tools are often used. Currently, bioinformatic analysis tools include QIIME, Mothur, Ribosomal Database Project (RDP) naive bayesian classifier (RDP nasal bases classifier), R program, and the like.
The current biological information analysis tool needs to perform programming operation on a Linux system, and needs comprehensive knowledge in various aspects such as biological statistics, biological information, computer system maintenance and the like. And most biological information analysis tools are complex in installation process and often need to be programmed in the use process, so that the requirements on biological information and computer capability of data analysts are high. In addition, different data analysts have different recognitions on the metagenomic data of the microorganisms, and the data analysis process is easy to generate differences, which is not beneficial to the implementation of the standardized process and the subsequent tracking analysis.
Disclosure of Invention
The invention aims to provide a system and a method for analyzing macro genes of microorganisms in aerobic composting of kitchen waste. In order to achieve the purpose, the invention provides the following technical scheme:
in a first aspect, there is provided a system for micro-organism macro-genetic analysis of aerobic composting of kitchen waste, the system comprising: the system comprises a server and a browser in communication connection with the server;
the browser is used for acquiring a target biological label, a target primer sequence and target high-throughput sequencing data input by a user; sending the target bio-tag, the target primer sequence and the target high throughput sequencing data to the server;
the server is used for receiving the target biological label, the target primer sequence and the target high-throughput sequencing data; splitting the target high-flux sequencing data according to the target biological label and the target primer sequence to obtain at least one group of biological sequences; analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results; adhering the at least two analysis results by an adhesion language to obtain a biological classification report; performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result; sending the analysis result to the browser;
and the browser is used for displaying the analysis result.
Optionally, the server uses a galaxy development tool to integrate a data splitting tool based on a Needle Wunschman model using XML language, and the data splitting tool is used to perform the step of splitting the multigene mixed metagenomics sequencing data according to the target biological tag and the target primer sequence to obtain at least one group of biological sequences.
Optionally, the at least two bioinformatic analysis tools include: at least two open source software drivers from Usearch, Qiime, Mothur, BLASTN, and RDP naive Bayes classifiers.
Optionally, the sticky language comprises at least one of a utility report extraction language Perl and a Python language.
Optionally, the server is configured to: performing key microorganism species analysis on the bio-taxonomy report by multivariate mathematical analysis using the R language.
Optionally, the browser is configured to: the results of the analysis are displayed in graphical form.
Optionally, the analysis result comprises:
at least one of microbial composition, architecture of the microflora, and the mechanisms by which the microbes respond to different environmental processes in the compost sample.
In a second aspect, a macro-genetic analysis method for aerobic composting of kitchen waste is provided, which is used in a server, and comprises the following steps:
receiving a target biological label, a target primer sequence and target high-throughput sequencing data sent by a browser;
splitting the target high-flux sequencing data according to the target biological label and the target primer sequence to obtain at least one group of biological sequences;
analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results;
adhering the at least two analysis results by an adhesion language to obtain a biological classification report;
performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result;
and sending the analysis result to the browser.
In a third aspect, a macro-genetic analysis method for aerobic composting of kitchen waste is provided, which is used in a browser and comprises the following steps:
acquiring a target biological label, a target primer sequence and target high-throughput sequencing data input by a user;
sending the target biological label, the target primer sequence and the target high-throughput sequencing data to the server, wherein the target biological label and the target primer sequence are used for the server to split the target high-throughput sequencing data to obtain at least one group of biological sequences; analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results; adhering the at least two analysis results by an adhesion language to obtain a biological classification report; performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result;
and receiving and displaying the analysis result sent by the server.
The invention has the beneficial effects that: receiving a target biological label, a target primer sequence and target high-throughput sequencing data sent by a browser through a server, and splitting the target high-throughput sequencing data according to the target biological label and the target primer sequence to obtain at least one group of biological sequences; analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results; obtaining a biological classification report by at least two analysis results of adhesion language adhesion; performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result; sending the analysis result to a browser and displaying the analysis result by the browser; the problem that the efficiency of the analysis process of the microbial macro gene is low due to the fact that the installation process of the biological information analysis tool is complex and programming is often needed in the using process can be solved, and the analysis efficiency of the microbial macro gene can be improved.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings.
Drawings
Fig. 1 is a schematic structural diagram of a microbial macro-gene analysis system for aerobic composting of kitchen waste according to an embodiment of the present disclosure;
fig. 2 is a flowchart of a method for analyzing macro-genes of microbes in aerobic composting of kitchen waste according to an embodiment of the present disclosure.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
Fig. 1 is a schematic structural diagram of a microbial macro-gene analysis system for aerobic composting of kitchen waste according to an embodiment of the present application, as shown in fig. 1, the system at least includes: a server 110 and a browser 120.
The browser 120 is used for acquiring a target biological label, a target primer sequence and target high-throughput sequencing data input by a user; and sending the target biological label, the target primer sequence and the target high-throughput sequencing data to a server.
A server 110 for receiving a target bio-tag, a target primer sequence and target high throughput sequencing data; splitting the target high-throughput sequencing data according to the target biological label and the target primer sequence to obtain at least one group of biological sequences; analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results; obtaining a biological classification report by at least two analysis results of adhesion language adhesion; performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result; and sending the analysis result to the browser.
And a browser 120 for displaying the analysis result.
Optionally, the server 110 integrates a data splitting tool based on a Needle Wunschman model using extensible markup language XML language using a galaxy development tool, the data splitting tool being used for performing the step of splitting the multigene mixed metagenomics sequencing data according to the target biological tag and the target primer sequence to obtain at least one set of biological sequences.
Optionally, the at least two bioinformatic analysis tools include: at least two open source software drivers from Usearch, Qiime, Mothur, BLASTN, and RDP naive Bayes classifiers.
Optionally, the sticky language comprises at least one of a utility report extraction language Perl and a Python language.
Optionally, server 110 is used to perform key microorganism species analysis on the bioclassified reports by multivariate mathematical analysis using the R language.
Optionally, a browser 120 for displaying the analysis results in a graphical form.
Optionally, the analysis results comprise: at least one of microbial composition, architecture of the microflora, and the mechanisms by which the microbes respond to different environmental processes in the compost sample.
Fig. 2 is a flowchart of a method for analyzing macro-genes of microorganisms in aerobic composting of kitchen waste according to an embodiment of the present application, which is described in this embodiment by taking the method as an example applied to the system shown in fig. 1. The method at least comprises the following steps:
step 201, the browser obtains a target biological label, a target primer sequence and target high-throughput sequencing data input by a user.
Optionally, a biological tag (barcode) is used to uniquely identify the classification of the microorganism. The microorganism may be a microorganism for composting, such as: the examples of the bacteria, such as monads, streptomycetes and enterobacteriaceae, are not listed here.
The primer refers to a molecule which stimulates the synthesis of a macromolecule having a specific nucleotide sequence at the start of nucleotide polymerization and is covalently linked to the reactant. The primers are usually two oligonucleotide sequences synthesized artificially, one primer and one deoxyribonucleic acid (deoxyriboucleic acid) at one end of the target region
acid, DNA) template strand, and the other primer is complementary to the other DNA template strand at the other end of the target region, which functions as a point of initiation of nucleotide polymerization. The primer sequence refers to a sequence of a gene including a primer in the gene sequence.
High throughput sequencing data refers to data obtained by sequencing hundreds of thousands to millions of nucleic acid molecules at a time.
Optionally, the browser is provided with a data entry control through which the user enters the target bio-tag, the target primer sequence and the target high-throughput sequencing data.
In step 202, the browser sends the target bio-tag, the target primer sequence and the target high throughput sequencing data to the server.
Alternatively, the number of target biological tags may be at least one, and the number of target primer sequences may also be at least one, and the number of target biological tags and the number of target primer sequences are not limited in this embodiment.
Step 203, the server receives the target biological label, the target primer sequence and the target high-throughput sequencing data sent by the browser.
And 204, the server splits the target high-throughput sequencing data according to the target biological label and the target primer sequence to obtain at least one group of biological sequences.
Optionally, the server uses a galaxy development tool to integrate a data splitting tool based on a Needle Wunschman model using XML language, the data splitting tool is used to perform a step of splitting the target high-throughput sequencing data according to the target biological tag and the target primer sequence to obtain at least one group of biological sequences.
The Needle Wunschman model is used to perform global alignments of sequences. That is, an attempt was made to find the best alignment between the two complete sequences S1 and S2. If, for example, S1-GCCCTAGCG S2-gcgcgcaatg sets each matching character to be 1 point, each space to be-2 points, and each mismatch to be-1 points, then the following alignment is the globally optimal alignment: s1'═ GCCCTAGCG S2' ═ GCGC _ AATG, hyphen "_" represents a space. There are five matching characters in S2', one space (or conversely, one insert in S1'), and three non-matching characters. The fraction thus obtained is (5 × 1) + (1 × -2) + (3 × -1) ═ 0, which is the best result that can be achieved.
In step 205, the server analyzes at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results.
Optionally, the at least two bioinformatic analysis tools include: usearch, Qiime, Mothur, BLASTN and RDP naive Bayes classifiers.
The biological analysis tool is used to determine a classification of at least one set of biological sequences.
And step 206, the server adheres at least two analysis results through the adhesion language to obtain a biological classification report.
The adhesion language includes at least one of a utility report extraction language Perl and a Python language.
And step 207, the server performs key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result.
Optionally, the server performs key microorganism species analysis on the bio-taxonomy report by multivariate mathematical analysis using the R language.
Optionally, the analysis results comprise: at least one of microbial composition, architecture of the microflora, and the mechanisms by which the microbes respond to different environmental processes in the compost sample.
Such as: in the composting process, the abundance of bacteria is 2 orders of magnitude higher than that of fungi and actinomycetes, but the total change trends of the abundance of the three bacteria in the composting process are consistent, and the bacteria in the composting process rise firstly and then fall. The reason that the bacteria can dominate is that the bacteria has small volume and large specific surface area, and can rapidly utilize soluble substances to provide energy for self growth and proliferation. In the temperature raising stage of compost, mesophilic microorganisms decompose organic matters, such as pseudomonas, streptomycete, enterobacter and the like. After the high-temperature period, bacteria, fungi and actinomycetes which can adapt to the high-temperature condition continue to participate in the degradation of complex macromolecular substances, such as cellulose, lignin, protein and the like, but when the temperature of the pile exceeds 64 ℃, the fungi almost completely disappear, and the actinomycetes become dominant bacteria for decomposing cellulose.
In step 208, the server sends the analysis result to the browser.
And step 209, the browser receives and displays the analysis result sent by the server.
Optionally, the browser displays the analysis results in a graphical form. Such as: the types and numbers of microorganisms acting at different temperatures are shown graphically.
In summary, in the method for analyzing macro-genes of microorganisms in aerobic composting of kitchen waste provided by this embodiment, the server receives the target biological tag, the target primer sequence and the target high-throughput sequencing data sent by the browser, and splits the target high-throughput sequencing data according to the target biological tag and the target primer sequence to obtain at least one group of biological sequences; analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results; obtaining a biological classification report by at least two analysis results of adhesion language adhesion; performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result; sending the analysis result to a browser and displaying the analysis result by the browser; the problem that the efficiency of the analysis process of the microbial macro gene is low due to the fact that the installation process of the biological information analysis tool is complex and programming is often needed in the using process can be solved, and the analysis efficiency of the microbial macro gene can be improved.
In addition, a plurality of biological information tools are adhered through a series of programming languages, a macro-gene big data analysis platform is developed through a galaxy platform, and the purpose that the large genome data are directly separated through a browser is achieved. Meanwhile, according to the platform, the agricultural gene big data can be divided without mastering complicated computer knowledge such as R, Perl and other programming languages and various biological information tools; greatly reduces the difficulty of developing a novel microbial agent by using the technology.
Alternatively, steps 201, 204 and 209 may be implemented separately as a server-side method embodiment; steps 202, 203 and 210 can be implemented separately as an embodiment of the method on the browser side, which is not limited in this embodiment.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (7)
1. A macro-genetic analysis system for aerobic composting of kitchen waste, the system comprising a server and a browser communicatively coupled to the server: the server uses a gateway development tool to use an extensible markup language XML language and integrates a data splitting tool based on a Needle Wunschman model; the Needle Wunschman model was used to find the best alignment between the two complete sequences S1 and S2;
the browser is used for acquiring a target biological label, a target primer sequence and target high-throughput sequencing data input by a user; sending the target bio-tag, the target primer sequence and the target high throughput sequencing data to the server; the bio-tag is used to uniquely identify the classification of the microorganism that is used for composting; the primer sequence refers to a gene sequence including a primer, and the primer refers to a macromolecule which is stimulated to be synthesized and has a specific nucleotide sequence and is connected with a reactant in a covalent bond form when the nucleotide polymerization is started; its function is as a starting point for nucleotide polymerization;
the server is used for receiving the target biological label, the target primer sequence and the target high-throughput sequencing data; using the data splitting tool to split the target high-throughput sequencing data according to the target biological label and the target primer sequence to obtain at least one group of biological sequences; analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results; adhering the at least two analysis results by an adhesion language to obtain a biological classification report; performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result; sending the analysis result to the browser, wherein the adhesion language comprises a practical report extraction language Perl or Python language;
and the browser is used for displaying the analysis result.
2. The system of claim 1, wherein:
the at least two bioinformatic analysis tools include: at least two open source software drivers from Usearch, Qiime, Mothur, BLASTN, and RDP naive Bayes classifiers.
3. The system of claim 1, wherein the server is configured to:
performing key microorganism species analysis on the bio-taxonomy report by multivariate mathematical analysis using the R language.
4. The system of any of claims 1 to 3, wherein the browser is configured to:
the results of the analysis are displayed in graphical form.
5. The system of any one of claims 1 to 3, wherein the analysis results comprise:
at least one of microbial composition, architecture of the microflora, and the mechanisms by which the microbes respond to different environmental processes in the compost sample.
6. A kitchen waste aerobic composting microbial macro-gene analysis method is characterized in that the method is used in a server, the server uses a galaxy development tool and an extensible markup language XML language to integrate a data splitting tool based on a Needle Wunschman model; the Needle Wunschman model was used to find the best alignment between the two complete sequences S1 and S2; the method comprises the following steps:
receiving a target biological label, a target primer sequence and target high-throughput sequencing data sent by a browser; the bio-tag is used to uniquely identify the classification of the microorganism that is used for composting; the primer sequence refers to a gene sequence including a primer, and the primer refers to a macromolecule which is stimulated to be synthesized and has a specific nucleotide sequence and is connected with a reactant in a covalent bond form when the nucleotide polymerization is started; its function is as a starting point for nucleotide polymerization;
splitting the target high-flux sequencing data according to the target biological label and the target primer sequence by using the data splitting tool to obtain at least one group of biological sequences;
analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results;
adhering the at least two analysis results through an adhesion language to obtain a biological classification report, wherein the adhesion language comprises a practical report extraction language Perl or Python language;
performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result;
and sending the analysis result to the browser.
7. A macro-genetic analysis method for aerobic composting of kitchen waste, which is used in a browser, and comprises the following steps:
acquiring a target biological label, a target primer sequence and target high-throughput sequencing data input by a user; the bio-tag is used to uniquely identify the classification of the microorganism that is used for composting; the primer sequence refers to a gene sequence including a primer, and the primer refers to a macromolecule which is stimulated to be synthesized and has a specific nucleotide sequence and is connected with a reactant in a covalent bond form when the nucleotide polymerization is started; its function is as a starting point for nucleotide polymerization;
sending the target biological label, the target primer sequence and the target high-throughput sequencing data to a server, wherein the server uses a galaxy development tool to use an extensible markup language (XML) language to integrate a data splitting tool based on a Needle Wunschman model; the Needle Wunschman model was used to find the best alignment between the two complete sequences S1 and S2; the target biological label and the target primer sequence are used for the server to split the target high-throughput sequencing data by using the data splitting tool to obtain at least one group of biological sequences; analyzing at least one group of biological sequences by at least two biological information analysis tools to obtain at least two analysis results; adhering the at least two analysis results by an adhesion language to obtain a biological classification report; performing key microorganism species analysis on the biological classification report through multivariate mathematical analysis to obtain an analysis result, wherein the adhesion language comprises a practical report extraction language Perl or Python language;
and receiving and displaying the analysis result sent by the server.
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