DOI: 10.57760/sciencedb.o00130.05070
title: Analysis of drug resistance and genomic characteristics of Salmonella in diarrhea patients in Jiamusi City from 2015 to 2023
title: 2015-2023年佳木斯市腹泻患者沙门菌耐药及基因组特征分析

description: Objective To elucidate the characteristics of drug resistance genes, virulence factors, and genotypes of Salmonella in Jiamusi City, with the aim of providing valuable insights for subsequent surveillance of Salmonella and rational use of antibiotics in clinical settings. Methods  Ninety-eight Salmonella strains isolated in Jiamusi City from 2015 to 2023 were collected for whole genome sequencing and drug sensitivity testing. Subsequently, an analysis was conducted on drug resistance genes, virulence factors, and molecular typing. Results The 98 strains of Salmonella could be classified into 25 serotypes, among which Salmonella enteritidis accounted for the highest proportion(44.89%,44/98). It mainly manifests as resistance to antibiotics such as streptomycin, ampicillin, tetracycline, and nalidixic acid, carrying 48 drug resistance genes belonging to 10 classes, among which the aminoglycoside resistance gene aac(6')-Iaa exhibited the highest rate of occurrence at 94.89%. Additionally, mutations were observed in the gyrA site of all 40 Salmonella strains, mainly as Asp87Tyr mutation. Two strains also occurred gyrA and parC site mutations simultaneously, while 14 strains occurred parC site mutation alone. All parC site mutations were Thr57Ser mutation. In terms of cgMLST classification analysis, cgMLST type 42449 accounted for the majority (8.16%,8/98). It is worth nothing that serotype identification showed correlation with both cgMLST and SNP typing. The virulence factors identified in these Salmonella strains were mainly associated with secretion system and fimbrial adherence determinants. Conclusion The prevalence of multidrug resistance in Salmonella isolates from Jiamusi City was significantly high, mainly associated with the presence of aminoglycoside resistance genes. These isolates exhibited intricate mechanisms of resistance and harbored multiple virulence factors, displaying a genetic correlation.
description: Objective To elucidate the characteristics of drug resistance genes, virulence factors, and genotypes of Salmonella in Jiamusi City, with the aim of providing valuable insights for subsequent surveillance of Salmonella and rational use of antibiotics in clinical settings. Methods  Ninety-eight Salmonella strains isolated in Jiamusi City from 2015 to 2023 were collected for whole genome sequencing and drug sensitivity testing. Subsequently, an analysis was conducted on drug resistance genes, virulence factors, and molecular typing. Results The 98 strains of Salmonella could be classified into 25 serotypes, among which Salmonella enteritidis accounted for the highest proportion(44.89%,44/98). It mainly manifests as resistance to antibiotics such as streptomycin, ampicillin, tetracycline, and nalidixic acid, carrying 48 drug resistance genes belonging to 10 classes, among which the aminoglycoside resistance gene aac(6')-Iaa exhibited the highest rate of occurrence at 94.89%. Additionally, mutations were observed in the gyrA site of all 40 Salmonella strains, mainly as Asp87Tyr mutation. Two strains also occurred gyrA and parC site mutations simultaneously, while 14 strains occurred parC site mutation alone. All parC site mutations were Thr57Ser mutation. In terms of cgMLST classification analysis, cgMLST type 42449 accounted for the majority (8.16%,8/98). It is worth nothing that serotype identification showed correlation with both cgMLST and SNP typing. The virulence factors identified in these Salmonella strains were mainly associated with secretion system and fimbrial adherence determinants. Conclusion The prevalence of multidrug resistance in Salmonella isolates from Jiamusi City was significantly high, mainly associated with the presence of aminoglycoside resistance genes. These isolates exhibited intricate mechanisms of resistance and harbored multiple virulence factors, displaying a genetic correlation.