Studies On Identification And Typing Of Pathogenic Microorganisms Based On Peptide Mass Fingerprinting

The microbial identification technology based on peptide mass fingerprinting (PMF) has emerged in recent years. Since the Biotyper system launch, PMF technology has been constantly validated and evaluated in various fields. Many pathogens cannot be identified, or identification is not ideal because of the lack of information on the pathogenic microorganisms in the commercial databases. To date, PMF technology has not been used for epidemiological studies of genotyping and traceability. However, the characterizations of organisms by rapid and high-throughput PMF is suitable for infectious disease prevention and control, which makes PMF a promising, effective diagnosis tool. Because the reference spectra in current commercial databases were constructed mainly based on European pathogens, some pathogenic organisms in our country cannot be identified or have a lower recognition rate using the database. Additionally, the database lacks information on highly pathogenic organisms. All of these factors severely limit the application of PMF in infectious disease prevention and control. There is no proprietary microorganism identification system in China, and the domestic market for such systems has been dominated by foreign companies. The development of a software system for which intellectual property is maintained in China is of vital importance for the country’s interests and security. Therefore, this study was intended to standardize the technical conditions for PMF, construct and evaluate a reference database, establish epidemiological and identification methods for recombinant pathogens and the pathogens in body fluids using this technology, develop the proprietary microorganism identification system, and promote and apply the PMF technique in the field of infectious disease prevention and control.This study determined that for the commercial system, pre-extraction with ethanol/formic acid was applicable for all bacterial strains except those of the genus Bacillus, which were pre-extracted with80%trifluoroacetic acid. For the bacteria cultured in liquid, one wash with PBS is suggensted prior to pre-extraction to meet the requirements of sensitivity and biological safety. The detection limit of the PMF system was1000cells. During bacterial passaging, the peptide series m/z2,000～20,000Da is relatively conserved, and the individual changes in these peptides do not affect the identification, which is based on the overall series of peptides. We constructed1019(bacteria886, mycoplasma64, spirochetes69) reference spectra that included31genera and94species using the standardized PMF technical conditions. The identification capability to the level of genus and species was increased by28.2%and42.3%, respectively, using this database. During this study,25species from8genera of bacteria were revealed usually incorrectly identified using PMF system. Regional analysis indicated that10strains appeared to have regional characteristics. This study provided the technical foundation for PMF application in clinical diagnosis, infectious disease prevention and control, food safety and quality control of material entering shipping ports.In this study, the naturally highly variable strain-Helicobacter pylori (HP), a strain with the smallest genome and simplest typing-Mycoplasma pneumonia (MP) and a strain typed based on ribosomal proteins-Leptospira were selected as model bacteria in an effort to create a more rapid and practical genotyping technology. Furthermore, the PMF technology was used for actual epidemiological analysis of a scarlet fever outbreak caused by Streptococcus pyogenes (group A Streptococcus, GAS). In this study, HP was classified as either type Plor P2using PMF technology. Nine characteristic peptides associated with HP type were confirmed. Thirty proteins expressed differentially between the P1and P2type were identified by label-free technology. Bioinformatics analysis showed that P1and P2HP had significant differences in proteins assoctiated with chemotaxis, ion regulation, metabolism, and the two-component system and endocrine systems. These differences should affect signal transduction pathways and host cell proliferation or apoptosis and lead to different pathological trends. These results will provide the research foundation for establishing the relationship of PMF type with the molecular mechanism of and correlation with diseases. For MP, we constructed a genetic algorithm (GA) model to distinguish type1and type2strains and the classification results were completely consistent with p1gene typing. The sensitivity and specificity of the GA model was100%. Seven characteristic peptides associated with PMF type were identified, which provided clues for revealing the typing mechanisms. Leptospira strains were classified into pathogenic and non-pathogenic strains based on PMF, which was consistent with the16S rRNA reference method. This study introduces the concept of super reference spectra in Biotyper by extracting the characteristic spectra of pathogenic and non-pathogenic Leptospira. The specificity of pathogenicity differentiation by super reference spectra was100%.108differentially expressed proteins associated with pathogenicity were identified by label-free technoloty. On the basis of previous research, the PMF technology was used in a scarlet fever epidemic in2011. The127GAS out of157β hemolytic isolates from298throat swab samples of scarlet fever and angina patients from Haerbin, Qingdao and Jinan were accurately identified. The detection period of PMF was reduced to36-48hours and the identification capacity increased by5.5%compared with the traditional bacitracin test and API20. The emm type distribution by matching reference spectra indicated that the scarlet fever outbreak was mainly caused by emm12GAS, which was completely consistent with the subsequent emm typing results. Therefore, the fast, accurate, and automated high-throughput of PMF can completely replace the traditional GAS molecular typing methods and be used for clinical diagnosis and monitoring of the scarlet fever epidemic.The PMF technology can be used to identify new pathogenic microorganisms and engineered recombinant pathogens. A method for rapidly classifying the recombinant organism at various stages during cloning and expression was constructed using the PMF technique with a four-dimensional classification model. The cross validation and recognition capacity of the best GA model was98.7%and100%, respectively, and the accuracy of the data validation was95%. The classification model built using a recombinant of the Yersinia pestis had the same classification capacity as Campylobacter jejuni and HP, which indicated that the classification model is a universal model. In view of the current situation regarding pathogen detection in body fluids, we constructed the characteristic peptide mass fingerprint model using the PMF technique and confirmed8characteristic fingerprint peptides. Ten out of32cases of suspected patients were identified as Brucella positive, which was consistent with the Tb phage specific lysis test.The reference spectra database constructed by this study has been successfully used for the development and application of the first PMF microorganism identification software—microorganism detection system (MicroID) with independent intellectual property rights.In conclusion, in this study, we standardized the PMF technical conditions, constructed a large number of reference spectra, performed a systematical analysis, and used the reference spectra database to generate the first version of PMF microorganism identification software. We explored the new typing method based on PMF and analyzed an actual epidemic outbreak using the PMF technique, which can provided new methods, a theoretical basis, and examples for the use of PMF in the field of public health. Additionally, we creatively used the PMF technology to identify recombinant pathogens and rapidly detect of pathogens in body fluids.