Weighted microbial clustering analysis method based on microbial mass spectrometer

Abstract

The invention discloses a weighted microbial clustering analysis method based on a microbial mass spectrometer. The weighted microbial clustering analysis method includes the steps: treating each of nstrains to be clustered into one class, calculating a similarity distance between the classes according to the specified strain similarity distance, and then combining the two classes with the nearest similarity distance into one new class, through this process, becoming n-1 class; and repeating the recursive process described above, reducing each class recursively until it is finally merged intoa class, wherein n is a natural number greater than or equal to 3. The weighted microbial clustering analysis method based on a microbial mass spectrometer has the advantages that the weighted microbial clustering analysis method is superior to a microbial DNA sequence analysis method in cost and classification speed, and is close to the DNA sequence analysis method in accuracy; and compared withthe existing microbial mass spectrometry cluster analysis method existing in the industry, the method has a clear advantage in accuracy and running speed.

Description

technical field [0001] The invention relates to a microbial cluster analysis method, in particular to a weighted microbial cluster analysis method based on a microbial mass spectrometer. Background technique [0002] The taxonomic study of microorganisms has a history of many years. In the early stage, it was carried out based on the physiological and biochemical characteristics, morphological characteristics and other phenotypic characteristics of microorganisms. However, these phenotypic characteristics are greatly affected by the environment, and there are no objective quantitative indicators, so they are not stable. Therefore, the classification results are somewhat random and cannot reflect the essential relationship between microorganisms. The microbial protein spectrum collected by mass spectrometry is relatively stable and reflects the essential characteristics of microorganisms. In the industry, the image of the spectrum collected by mass spectrometer is called "mic...

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Problems solved by technology

[0005] 1. Classify according to the phenotypic characteristics such as the morphological characteristics and physiological and biochemical characteristics of the cultured bacteria. This method is greatly affected by the culture environment of the strains, and at the same time, there is no objective quantitative index for the relationship between the strains, so this method has great potential Randomness does not reflect the kinship between microorganisms very accurately

[0006] 2. According to the microbial DNA sequence to analyze the genetic evolution relationship of microorganisms to classify, although this method has a high accuracy rate, the cost of reagents and chips used in the process of obtaining microbial DNA sequences is relatively high; on the other hand, the current DNA sequencing process is relatively It is tedious and takes a lot of time, and more professionals are required to analyze after the sequencing results are obtained; and for unknown strains, the time and price invested in the process of obtaining DNA sequences greatly restrict the application of this method in clinical and scientific research

[0007] 3. Cluster analysis is carried out according to the microbial mass spectrum. At present, the mainstream mass spectrometer analysis software in the market basically has the cluster analysis function, but the main disadvantage is that the accuracy rate is not high and the corresponding functions of the software run slowly.

For example, although Escherichia coli, Morganella morganii, and Klebsiella pneumoniae are consistent at the family level, Escherichia coli and Klebsiella pneumoniae are closer in proteomics. Most mass spectrometer cluster analysis functions on the market cannot tell the difference

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