Objective:To characterize the antimicrobial resistance, resistance machanism and population genetics of Salmonella( S.) Derby in China, preliminarily reveal the population genetic characteristics of S. Derby in China, discover possible transmission patterns or potential transmission pathways, and provide certain reference for strengthening S. disease monitoring and developing prevention and control strategies. Methods:A total of 201 strains of S. Derby from different areas in China were used for the susceptible tests to 16 antibiotics and whole-genome sequencing. Finally, combined with the genome sequences of 134 strains of S. Derby from public databases, 335 strains of S. Derby were used for resistance genotype analysis and multi-locus sequence typing (MLST), and a phylogenetic tree based on the core genome single nucleotide polymorphisms was constructed for evolutionary analysis. Results:The results showed that 201 strains of S. Derby showed resistance to 16 kinds of antibiotics at different levels. The overall resistance rate was 97.51%. The resistance rates to antibiotics varied in S. Derby from different sources (human, animal, and food), the differences were significant (all P<0.05). A total of 38 resistance genes were carried by 335 strains of S. Derby, of which, fosfomycin gene fosA7 was found in all the strains (100.00%) and aminoglycoside genes aac(6')-Iaa accounted for 99.70%. The consistency of resistance genes and phenotypes varied with antibiotics. Except aminoglycosides and chloramphenicol, the consistencies of resistance genes and phenotypes for other antibiotics were high. MLST showed that 334 strains of S. Derby belonged to ST40. Phylogenetic trees indicated the risk for cross-infection between animal and human, food and human, and the possibility of long-distance interprovincial transmission of the bacteria by animal, to which further epidemiological studies are needed. Conclusions:The drug resistance of S. Derby is serious in China and the risk for cross-transmission between human and animal or food exists. It is necessary to establish and strengthen the comprehensive surveillance and risk assessment to prevent the spread of antibiotic resistant strains or elements through animal, food and human chains.

Objective:To establish a matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) assay for the identification of common Salmonella serotypes and provide etiology evidence for the early precise treatment of salmonellosis. Methods:A total of 500 strains were collected from different regions and sources and five predominant Salmonella serotypes ( Salmonella Typhi , Salmonella Paratyphi A , Salmonella Typhimurium , Salmonella Enteritidis , and Salmonella Indiana) of each strain was identified by agglutination test and whole-genome sequencing. The protein complex of the strains was extracted by using optimized pretreatment method to establish the fingerprint database of peptides for each Salmonella serotype. The new serotyping assays were established by using different modules based on the mass spectra database. Additional 155 strains with specified serotypes and variant sources were used to test and evaluate the accuracy of the new typing assays. Results:Five MALDI-TOF MS databases were established, and two new serotyping assays were established via peptide fingerprint mapping/matching and machine learning of the neuronal convolutional network respectively based on the databases. The results showed that the fingerprint matching approach could quickly identify five common Salmonella serotypes in clinical practice compared with the machine learning method, the accuracy of fingerprint matching assay to identify five Salmonella serotypes reached 100.00% and the serotyping can be conducted within a short time (15-20 minutes) and had a good reproducibility, while the machine learning method could not completely identify these serotypes. Moreover the sensitivity and specificity of fingerprint matching assay were all 100.00% respectively, while they were only 82.23% and 95.81% for machine learning method. Conclusion:The established Salmonella serotyping assay based on MALDI-TOF MS in this study can easily, rapidly and accurately identify different serotypes of Salmonella.