Rapid prediction system and method for bacterial drug resistance

Abstract

The invention discloses a rapid prediction system and method for bacterial drug resistance. The system comprises bacterial genomic DNA extraction equipment, bacterial genomic fingerprinting equipment,bacterial drug resistance phenotype determining equipment, bacterial drug resistance phenotype data collection and analysis equipment, an intelligent terminal, a cloud server and a bacterial databaseserver, wherein the bacterial genomic DNA extraction equipment is connected with the bacterial genomic fingerprinting equipment, the bacterial genomic fingerprinting equipment and the bacterial drugresistance phenotype data collection and analysis equipment are connected with the intelligent terminal through circuits or a wireless signals, the intelligent is connected with the cloud server through the Internet, and the cloud server is further connected with the bacterial database server. By utilizing the Internet and a safe cloud computing storage technique, the tolerance degrees of to-be-tested bacteria to different antibiotics can be accurately judged, and the heterogeneous drug resistance of the bacteria can be comprehensively judged according to information of genotypes and drug-resistant phenotypes.

Description

technical field [0001] The invention relates to a bacterial drug resistance prediction system, in particular to a bacterial heterogeneous drug resistance rapid prediction system and a prediction method thereof, belonging to the field of medicine and health. Background technique [0002] At present, the detection of bacterial drug resistance is mainly divided into two categories: the first category uses culture technology to culture bacteria in solid or liquid media containing different antibiotics and directly observe the inhibition of antibiotics on bacterial growth, because bacterial culture is prone to failure. Contamination generally takes 24 hours or more to detect growth, and each antibiotic must be added to the medium separately (adding two or more antibiotics at the same time may produce synergistic or antagonistic effects), so multiple cultures are required to determine A strain is resistant to multiple antibiotics, so this traditional method has great limitations. ...

AI Technical Summary

Problems solved by technology

[0002] At present, the detection of bacterial drug resistance is mainly divided into two categories: the first category uses culture technology to culture bacteria in solid or liquid media containing different antibiotics and directly observe the inhibition of antibiotics on bacterial growth, because bacterial culture is prone to failure. Contamination generally takes 24 hours or more to detect growth, and each antibiotic must be added to the medium separately (adding two or more antibiotics at the same time may produce synergistic or antagonistic effects), so multiple cultures are required to determine One strain is resistant to multiple antibiotics, so this traditional method has great limitations

The second category is the use of molecular biology methods to detect the presence of drug-resistant genes on the genome, such as a kit for detecting a specific drug-resistant gene by PCR. This kit can only use a specific gene. Due to the recombination and Mutations cause sequence changes very frequently, and the use of these kits is also very limited

Due to the difficulty in the detection of heterogeneous drug-resistant subgroups of bacteria, it is easy to miss detection by using only one analysis method, resulting in the failure of clinical anti-infection treatment, which has attracted widespread attention from infectious disease doctors, microbiological testing and related personnel

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