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Pathogenic microorganism metagenome detection method based on third-generation sequencing

A pathogenic microorganism and metagenome technology, which is applied in the field of pathogenic microorganism metagenomic detection based on three-generation sequencing, can solve the problems of poor accuracy, retention, and low sequencing accuracy, and achieves the improvement of accuracy, accurate detection results, and improved detection accuracy. Effect

Active Publication Date: 2021-07-23
成都博欣医学检验实验室有限公司
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  • Summary
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

5) Nucleic acid-based PCR detection generally has high accuracy, and the detection speed only takes a few hours. However, due to the need to design specific primers and probes, only 10-20 species can be identified at a time, and each Species require targeted design of primers and probes
Therefore, the application of third-generation sequencing has great advantages in pathogen detection, but the sequencing accuracy of third-generation sequencing is lower than that of second-generation sequencing. These data characteristics determine that the second-generation data analysis method cannot be simply followed.
[0018] In addition, the data based on next-generation sequencing is generally based on the kmer-based algorithm for species identification due to the large amount of data. This method is less accurate in the identification of highly similar nucleic acids and can only be relatively accurately distinguished at the genus level. In order to improve the analysis speed, most processes only retain the genomic nucleic acid database of known pathogenic species that have been reported, and there are certain blind spots for the identification of pathogens that have not been reported.

Method used

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  • Pathogenic microorganism metagenome detection method based on third-generation sequencing
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  • Pathogenic microorganism metagenome detection method based on third-generation sequencing

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Experimental program
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Effect test

experiment example 1

[0123] The method of the present invention (referred to as MCP) was compared with the current mainstream microbial detection methods based on sequencing data, centrifuge and kraken2+bracken, and the corresponding comparison databases are relatively complete databases of species under the process of the method, respectively. NT and microbial-fatfree, where NT data is the NCBI all-species database, and the microbial-fatfree database mainly covers archaea, bacteria, fungi, protozoa, and viruses.

[0124] Because clinical samples are highly enriched with human data, and the 10-15% sequencing error in the third-generation sequencing will lead to unclean removal of human background data, and sometimes there are negative samples of autoimmune reactions similar to microbial infections , so first simulate and evaluate and compare the misclassification of species in a purely human background.

[0125] Human source data DNA comes from NCBI nucleic acid sequence CM000663.2, randomly gener...

experiment example 2

[0130] In order to evaluate the classification accuracy of microorganisms, the present invention randomly selected 10 common viruses, bacteria, and fungi, and randomly selected 500 sequences with a length of 300 bp from the nucleic acid sequences corresponding to each species as the starting sequence for analysis.

[0131] The nucleic acid sequence numbers involved in the simulation are:

[0132] Sequence 1: NC_006273.2; virus;

[0133] Sequence 2: NC_001798.2; virus;

[0134] Sequence 3: NC_002205.1; virus;

[0135] Sequence 4: NC_011071.1; Bacteria;

[0136] Sequence 5: NZ_CP014955.1; Bacteria;

[0137] Sequence 6: NC_007795.1; Bacteria;

[0138] SEQUENCE 7: NC_032089.1; Fungus;

[0139] SEQUENCE 8: NC_007445.1; Fungus;

[0140] Sequence 9: NC_013660.2; Fungus;

[0141] SEQ ID NO: CP022321.1; Fungus.

[0142] Detection method:

[0143] Method 1: MCP / ASD;

[0144] Method 2: centrifuge / NT;

[0145] Method 3: kraken2+bracken / microbial-fatfree.

[0146] Table 2: Expe...

experiment example 3

[0151] The whole process is demonstrated using the results of clinical blood samples with known drug-resistant types and microbial types. The clinical samples are Citrobacter freundii resistant to cephalosporins, and the initial sequencing data is PC001.fastq. Run the MCP program including preprocessing, mapping, classification, and drug resistance analysis modules under the Linux system:

[0152] MCP -i PC001.fastq -a preclean-mapping-ClassifyBlast-resistance -sPC001 -r y.

[0153] The whole block analysis took 7m36.839s. The result of the analysis of the drug resistance gene was the CMY beta-lactamase gene family, and the result of the detected microorganism was Citrobacter freundii, which was consistent with the results of clinical culture and drug resistance identification.

[0154] The results are displayed as follows:

[0155] 1) Raw sequence statistics

[0156] sample type of data Types of serial number number of bases shortest sequence Average seq...

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Abstract

The invention discloses a pathogenic microorganism metagenome detection method based on third-generation sequencing, the method comprises the following steps: acquiring original gene detection data of third-generation sequencing of a sample, removing interference sequences, and retaining non-human data; establishing a mapping relationship between the whole species nucleic acid database and the whole species classification database; removing invalid mapping relationships in the mapping relationship set to obtain an effective mapping relationship set of the non-human source data and the whole species classification database, and performing calculation according to the effective mapping relationship set to obtain a species identification result; constructing a microorganism annotation database to obtain microorganism annotation information; constructing a microbial drug resistance database to obtain microbial drug resistance information; and obtaining a microorganism detection report according to the species identification result, the microorganism annotation information and the microorganism drug resistance information. According to the method, the non-human source data is established, the mapping result is optimized, the detection precision is improved, the accuracy of species classification in similar regions is improved, and then species are obtained through prediction and comparison of sequence results.

Description

technical field [0001] The invention relates to the technical field of biological information, in particular to a method for detecting pathogenic microorganism metagenomics based on three-generation sequencing. Background technique [0002] Pathogenic microorganisms are one of the main factors causing human diseases. In the process of diagnosing human diseases, biological tests of human samples are usually required. [0003] Metagenomics is also called microbial environmental genomics and metagenomics. It directly extracts the DNA of all microorganisms from environmental samples, constructs a metagenomic library, and uses genomics research strategies to study the genetic composition and community functions of all microorganisms contained in environmental samples. It is a new concept and method developed on the basis of microbial genomics to study microbial diversity and develop new physiologically active substances (or obtain new genes). Its main meaning is: clone the tota...

Claims

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Application Information

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IPC IPC(8): G16B20/00G16B30/10G16B50/00
CPCG16B20/00G16B30/10G16B50/00
Inventor 邹珂珂赵科研马欣刘菲李珊
Owner 成都博欣医学检验实验室有限公司
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