摘要
      出身背景抗微生物耐药性（AMR）是一个全球性的健康问题，它在空间和时间上都在不断演变。对特定抗生素的耐药性可以作为相同或不同抗生素类别的选择和共选择标记。因此，本横断面研究旨在预测尿路致病性大肠杆菌（UPEC）表型和基因型抗性性状的相关性。方法对83份尿液样本中的42份UPEC进行了表型和基因型AMR特征的患病率和相关性调查。通过Kirby–Bauer椎间盘扩散法进行抗体谱分析，并通过PCR检测AMR基因（ARGs）。后果从50.60%（42/83）的检测样本中分离出UPEC。其中，80.95%的病例来自女性，38.10%的病例发生在21-30岁年龄组 年。分离株对四环素的耐药率较高（92.86%），其次是磺酰胺（71.43%）、氨苄青霉素（52.38%）、甲氧苄啶-磺胺甲恶唑（47.62%），对链霉素、氯霉素和红霉素的耐药率分别为28.57%。这些分离株中最常见的抗微生物耐药性基因（ARGs）是tet（A）（78.57%）、tet（B）（76.19%）、sul1（61.91%）、dfrA1（35.71%）、blaSHV（26.19%）、cmlA（19.05%）和CITM、，分别为dfrA1和qnrA。在环丙沙星-四环素、磺酰胺-红霉素对之间以及tet（A）和tet（B）基因之间观察到不显著的相关性。此外，在氯霉素抗性基因，即catA1和cmlA的情况下，也假设了共选择。结论在UPEC分离株中发现了表型和遗传抗性特征。还观察到AMR表型和基因型之间的统计关联和共选择现象，但需要在大规模研究中进行验证。然而，这些发现可能对开发AMR预测模型以应对未来AMR爆发具有重要意义。
Abstract
Background. Antimicrobial resistance (AMR) is a global health problem which is constantly evolving and varies spatially and temporally. Resistance to a particular antibiotic may serve as a selection and coselection marker for the same or different antibiotic classes. Therefore, this cross-sectional study was conducted to predict the association of phenotypic and genotypic resistance traits in uropathogenic Escherichia coli (UPEC). Method. A total of 42 UPEC from 83 urine samples were investigated for the prevalence and association of phenotypic and genotypic AMR traits. Antibiogram profiling was carried out by Kirby–Bauer’s disc diffusion method and AMR genes (ARGs) were detected by PCR. Result. UPECs were isolated from 50.60% (42/83) of the samples examined. Of these, 80.95% of cases were derived from females, and 38.10% of cases were found in the age group of 21–30 years. The isolates were shown to have a high frequency of resistance to tetracycline (92.86%), followed by sulfonamide (71.43%), ampicillin (52.38%), trimethoprim-sulfamethoxazole (47.62%), and 28.57% each to streptomycin, chloramphenicol, and erythromycin. The most prevalent antimicrobial resistance genes (ARGs) in these isolates were tet(A) (78.57%), tet(B) (76.19%), sul1 (61.91%), dfrA1 (35.71%), blaSHV (26.19%), cmlA (19.05%), and CITM, qnrA, and catA1 each at 11.91%. According to statistical analysis, ampicillin, sulfonamide, trimethoprim-sulfamethoxazole, and ciprofloxacin resistance were strongly correlated with the presence of blaSHV, sul1, dfrA1, and qnrA, respectively. Nonsignificant associations were observed between ciprofloxacin-tetracycline, sulfonamide-erythromycin pairs as well as between tet(A) and tet(B) genes. Besides, coselection was also assumed in the case of chloramphenicol resistance genes, namely, catA1 and cmlA. Conclusion. Both the phenotypic and genetic resistance traits were found in the UPEC isolates. Statistical association and coselection phenomena among AMR phenotypes and genotypes were also observed but required to be validated in a broad-scale study. However, these findings might have important implications for the development of an AMR prediction model to tackle future AMR outbreaks.

https://www.hindawi.com/journals/cjidmm/2022/4251486/