Protein fingerprint model, system and application thereof for anthrax

Abstract

The invention discloses a protein fingerprint model formed through drawing according to mass-to-charge ratios of a plurality of proteins and protein crest strength coefficients, wherein the mass-to-charge ratios are 1097, 1777, 2551, 2988, 3381, 3708, 5492, 6007, 7144 and 8012. The invention further discloses a protein detection and analysis system based on the model and a laser desorption/ionization time of flight mass spectrometry detection method for anthrax. In the detection method, protein spectrums of samples are compared with the model to detect the anthrax in the samples qualitatively. The protein fingerprint model contains specific protein spectrum information of the anthrax, is provided with a specific recognition function, and can be applied to commercialized detection and analysis systems of the anthrax. According to the protein fingerprint model, the system and an application thereof for the anthrax, the detection method which is high in sensitivity, specificity and detection rate is provided for the anthrax and is particularly suitable for port check and inspection departments.

Description

technical field [0001] The invention relates to the field of microorganism detection, in particular to a protein fingerprint model of anthrax bacteria and its application in the detection of anthrax bacteria. Background technique [0002] Coffee berry anthracnose (coffee berry disease) is a devastating disease on coffee caused by Colletotrichum kahawae J.M.Waller et Bridge. The main hosts are Coffea arabica, Coffea canephora and Coffea liberica. Coffee berry anthracnose bacteria are mainly distributed in Angola, Burundi, Cameroon, Central Africa, Congo (Brazzaville), Congo (Kinshasa), Ethiopia, Kenya, Malawi, Mozambique, Rwanda, Tanzania, Uganda, Zambia, Zimbabwe, Cuba and other countries, It seriously affects the coffee planting industry in these countries, and the economic loss can reach 60%. Cameroon has reported that the loss can reach as high as 90%. The germ can infect all stages from flower to ripe fruit. [0003] It mainly harms immature coffee berries. At the beg...

AI Technical Summary

Problems solved by technology

[0004] It can be seen that the identification of anthrax bacteria is very difficult, and the differences in the morphological characteristics of pathogenic bacteria are very small, and it needs to be distinguished through complex carbon source metabolism

In terms of analysis by molecular biology methods, the ITS segment is currently the most widely studied, but the publicly registered sequences have a high error rate and confusing naming, many non-type sequences, and relying on the analysis of a single gene fragment is not enough to solve the classification problem , can not completely solve the classification problem of anthrax

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