Construction method of microbial peptide mass fingerprint spectrum database based on time-of-flight mass spectrometry principle

Abstract

The invention discloses a construction method of a microbial peptide mass fingerprint spectrum database based on a time-of-flight mass spectrometry principle, wherein the method comprises the steps: carrying out pure culture of obtained strains according to physiological habits, and successively obtaining strains at logarithmic phase; identifying the strains through morphology, taxonomy and methodology; then pretreating the confirmed strains, drying, and then extracting peptide fingerprint spectra by an ethanol / formic acid method and an 80% TFA extraction method; collecting and treating the spectra by adopting an MALDI-TOF MS platform, then carrying out parameter determination of the strain spectra, unifying the determined standard spectra and strain names, labeling a database construction method of the strains, and completing the database construction of the strains; and analogizing by the construction methods of the other strains successively, and completing the construction of the microbial peptide mass fingerprint spectrum database. The invention provides a set of complete method from the investigation of the strains to the construction of the database. The database has complete types of microorganisms, and meets identification requirements of microorganism related industries.

Description

technical field [0001] The invention relates to a microorganism identification database, in particular to a method for constructing a microbial peptide mass fingerprint library based on the principle of time-of-flight mass spectrometry. Background technique [0002] Bacteria, fungi, actinomycetes, rickettsia, mycoplasma, chlamydia, spirochetes and other microorganisms all contain a large number of conserved proteins, usually ribosomal proteins. Compared with microbial metabolites and other cell components that are easily affected by culture conditions, The use of conserved proteins for microbial identification can ensure the stability and reproducibility of identification results. Therefore, rapid and accurate identification of bacteria, fungi, actinomycetes, mycoplasma, chlamydia, rickettsia, etc. is a basic requirement in the field of microbiology such as clinical diagnosis, food and disease control testing. [0003] Traditional identification mainly relies on biochemical...

AI Technical Summary

Problems solved by technology

[0005] At present, there are two microbial standard peptide fingerprint quality databases on the market (mainly referring to Bruker’s Biotyper database and Mérieux’s SARAMIS database), because the strains used to construct standard maps in these databases are mostly foreign microorganisms, and There are regional differences in microorganisms, so some strains in these two databases do not meet the actual needs of clinical, food, and disease monitoring in China, resulting in some microorganisms in China that cannot be identified or can only be identified at the genus level due to the lack of standard maps , which brings difficulties to clinical diagnosis and treatment

For example, Brucella does not exist in these two databases, and Brucella is a zoonotic pathogen with a high incidence in China, especially in cattle and sheep farms, where the frequency of occurrence of this pathogen is very high ; Some clinically high-frequency strains, such as Acinetobacter baumannii, Salmonella, Listeria monocytogenes, Candida, etc., are also difficult to identify at the species level

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