Rapid numerical identification method for enterobacteria of food-borne pathogenic bacteria

A food-borne pathogenic bacteria and identification method technology, which is applied in the field of numerical rapid identification of food-borne pathogenic bacteria Enterobacteriaceae, can solve problems such as inconsistent identification results

Active Publication Date: 2016-04-13
GUANGDONG INST OF MICROBIOLOGY GUANGDONG DETECTION CENT OF MICROBIOLOGY +2
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Problems solved by technology

We found that in the database, Citrobacteramalonaticus (non-malonated Citrobacter) has a certain difference between the API and MID systems on urine enzymes. The positive occurrence probability of API urine enzymes is 1%, while that of MID is 85%. This situation o

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  • Rapid numerical identification method for enterobacteria of food-borne pathogenic bacteria

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Embodiment Construction

[0028] The present invention will be further described in detail through specific examples below, but the embodiments of the present invention are not limited thereto.

[0029] Numerical rapid identification method of food-borne pathogenic bacteria Enterobacteriaceae strains of the present invention

[0030] (1) Determine the type of Enterobacteriaceae and its positive probability

[0031]In this example, the positive probability of biochemical tests of 31 genera and 139 species of Enterobacteriaceae, a total of 159 taxa and 47 species thereof (including the above-mentioned 24 biochemical tests) were determined. The 159 taxa are as follows: 1-Escherichiaspp (Escherichia), 2-Escherichiacoli (Escherichia coli), 3-Escherichiacol, inactive (Escherichia coli, inactive), 4-Escherichiablattae ( Cockroach Escherichia), 5-Escherichiafergusanii (Escherichia fergusanii), 6-Escherichiahermannii (Escherichia Hermannii), 7-Escherichia avulneris (Escherichia wound), 8-Budviciaaquatia (Aquat...

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Abstract

The invention discloses a rapid numerical identification method for enterobacteria of food-borne pathogenic bacteria. The rapid numerical identification method includes confirming enterobacteria types and positive probabilities; selecting biochemical reaction required in a numerical method; establishing an enterobacteria database and determining a calculating method in the numerical method; detecting and identifying the bacteria to be detected. The rapid numerical identification method for the enterobacteria of the food-borne pathogenic bacteria has the advantages that pure cultures can be subjected to Gram staining, oxidase and OF experiment in advance, and then the rapid numerical identification method is adopted, so that a satisfactory identification result on the enterobacteria can be obtained; by the rapid numerical identification method, 139 bacteria of 31 categories and 8 unclassified floras, namely 159 classified units in total of enterobacteriaceae can be identified, and Yersinia enterocolitica can be identified to 6 kinds of biochemical types; the rapid numerical identification method is much greater in identified bacteria quantity and much higher in identification accuracy than two existing internationally-recognized similar identification methods on the market.

Description

Technical field: [0001] The invention belongs to the technical field of biochemical identification, and in particular relates to a numerical rapid identification method for food-borne pathogenic bacteria Enterobacteriaceae. Background technique: [0002] Food safety is a major issue related to human health and national economy and people's livelihood, and microbiological safety is the top priority of food safety. Due to the rich nutrients in food, the number of rapid reproduction of microorganisms increases geometrically after contaminating food, thus causing serious food safety problems. According to statistics, there were 6,685 food poisoning incidents in my country in 2012, among which microbial food poisoning incidents accounted for the largest number of poisonings, accounting for 56.1% of the total; from 1988 to 2008, a total of 13,405 incidents were reported by the Electronic Foodborne Outbreak Reporting System (eFORS) in the United States. Outbreaks of foodborne disea...

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Application Information

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IPC IPC(8): C12Q1/10C12R1/19C12R1/01
CPCC12Q1/10C12Q2304/00
Inventor 吴清平叶青华张菊梅蔡芷荷阙绍辉
Owner GUANGDONG INST OF MICROBIOLOGY GUANGDONG DETECTION CENT OF MICROBIOLOGY
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