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Method and system for detecting microorganisms and drug-resistant genes in sample

A technology of drug resistance genes and microorganisms, applied in the fields of genomics, bioinformatics, instruments, etc., can solve the problems of long time for off-machine data analysis, failure to effectively identify emerging pathogens, failure to effectively filter background and pollution, etc.

Active Publication Date: 2021-03-19
广东美格基因科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, the current methods of using metagenomic sequencing to detect microorganisms in samples have long data analysis time, low accuracy of microbial comparison, ineffective filtering of background and contaminating microorganisms, inability to effectively distinguish back-colonized or infected microorganisms, ineffective Insufficient identification of multi-drug resistant bacteria and mixed infections, failure to effectively establish associations between detected drug resistance genes and microorganisms, failure to effectively identify new pathogens, etc.

Method used

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  • Method and system for detecting microorganisms and drug-resistant genes in sample
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  • Method and system for detecting microorganisms and drug-resistant genes in sample

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0092] Embodiment 1 System and method for detecting microorganisms in a sample

[0093] This embodiment provides a system for detecting microorganisms in a sample, such as figure 1 shown, including:

[0094] Microbial analysis module set, including: microbial comparison module 101, microbial annotation module 103, preliminary filtering module 104 and further filtering module 105; and

[0095] The microbial database module group includes: microbial comparison database 201, microbial annotation database 202 and microbial representative genome database 203,

[0096] in,

[0097] The microbial comparison module 101 is connected to the microbial comparison database 201, and is used to compare and analyze the metagenomic sequencing data of the sample based on the K-mer algorithm using the microbial comparison database to obtain the microbial comparison result;

[0098] The microorganism annotation module 103 is connected with the microorganism comparison module 101 and the microo...

Embodiment 2

[0108] Embodiment 2 System and method for detecting microorganisms in a sample

[0109] This embodiment improves the system for detecting microorganisms in samples in Example 1. The point of improvement is that the microbial analysis module set further includes a microbial comparison correction module set 102 (such as figure 1 inside the dotted line box), located between the microorganism comparison module 101 and the microorganism annotation module, for correcting the microorganism comparison result obtained in S21 based on the following steps.

[0110] Search by family as a unit, if the sum of sequences annotated to each genus accounts for less than 50% of the total sequence of the family, and the relative abundance of the family is greater than 15%, then:

[0111] a) Extract and assemble the reads annotated to the family into a contig;

[0112] b) compare reads to contig, and record the corresponding relationship between read and contig;

[0113] c) compare the contig to ...

Embodiment 3

[0121] Embodiment 3 Detection system and method for microorganisms and drug-resistant genes in samples

[0122] This embodiment improves the system for detecting microorganisms in the sample of embodiment 1 or embodiment 2, such as figure 2 As shown, the point of improvement is to further include:

[0123] The drug-resistant gene analysis module set includes: a drug-resistant gene comparison module 301 and a drug-resistant gene filter module 302;

[0124] Drug-resistant gene database module group: including: drug-resistant gene comparison database module 401 and drug-resistant gene annotation database 402,

[0125] in,

[0126] The drug-resistant gene comparison module 301 is connected to the drug-resistant gene comparison database module 401, and is used to compare and analyze the metagenomic sequencing data of samples using the drug-resistant gene database to obtain predicted drug-resistant gene information;

[0127] The drug-resistant gene filtering module 302 is respec...

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Abstract

The invention discloses a method for detecting microorganisms in a sample, which belongs to the technical field of metagenome analysis and comprises the following steps: S1, acquiring metagenome sequencing data of the sample; and S2, performing species analysis on the metagenome sequencing data. The method further comprises a step of carrying out drug resistance gene analysis on the metagene sequencing data of the sample. The invention also discloses a system for detecting microorganisms and drug-resistant genes in a sample. On the basis of a comprehensive and accurate database and an intelligent analysis and screening algorithm, pathogenic microorganisms and drug-resistant genes are effectively identified by utilizing a metagenome sequencing method, false positive is effectively reduced,bacteria suspected to correspond to the detected drug-resistant genes can be prompted, and better technical support is provided for accurate diagnosis and treatment of infection; in addition, according to the method and the system, potential new pathogenic microorganisms can be accurately analyzed, and technical support is provided for early warning of new infectious diseases.

Description

technical field [0001] The invention belongs to the technical field of metagenomic analysis, and in particular relates to a method and system for detecting microorganisms and drug resistance genes in a sample. Background technique [0002] Infectious diseases caused by pathogenic microorganisms, especially severe pneumonia, sepsis and encephalitis and meningitis, are difficult to identify the pathogens of difficult and critical infectious diseases, which has always been a key problem faced by infectious disease clinicians. Therefore, accurate The identification of pathogenic microorganisms is a crucial step in precision infection treatment. [0003] Traditional pathogenic microorganism detection techniques are mainly divided into two categories: gene cell culture methods and methods based on specific primers or antibodies (molecular detection) such as PCR detection, multiplex PCR detection, and antigen-antibody hybridization reactions. At present, the routine clinical patho...

Claims

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Application Information

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IPC IPC(8): G16B20/20
CPCG16B20/20
Inventor 林德春金桃张智闵詹太平蒋华
Owner 广东美格基因科技有限公司
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