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.

Highlights

  • Antimicrobial resistance (AMR) is one of the world’s most urgent public health concerns. e increasing phenomena of AMR has been continuously affecting healthcare, veterinary, and agricultural settings globally which endangers the achievement of sustainable development goals [1].Coselection and persistence of resistance to common and critically important antimicrobial drugs are occurring due to massive and inappropriate antibiotic use. is in turn results in the continuous evolution and spread of multidrug-resistant (MDR) pathogens [2]

  • Resistant bacteria often serve as reservoir of diverse antimicrobial resistance genes (ARGs) [3]

  • AMR phenotypes may arise from different genetic determinants, each of which may present specific epidemiological features [9]. erefore, surveillance of antimicrobial resistance from phenotypic and genotypic perspectives in bacterial populations can be useful to predict AMR outcomes

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Summary

Introduction

Antimicrobial resistance (AMR) is one of the world’s most urgent public health concerns. e increasing phenomena of AMR has been continuously affecting healthcare, veterinary, and agricultural settings globally which endangers the achievement of sustainable development goals [1].Coselection and persistence of resistance to common and critically important antimicrobial drugs are occurring due to massive and inappropriate antibiotic use. is in turn results in the continuous evolution and spread of multidrug-resistant (MDR) pathogens [2]. Ey are sensitive to selection pressure exerted by antibiotic usage and carry genetic mobile elements to achieve such transmission [4] For this reason, multidrug resistance in E. coli is increasingly observed in human healthcare settings as well as in veterinary medicine globally. Erefore, surveillance of antimicrobial resistance from phenotypic and genotypic perspectives in bacterial populations can be useful to predict AMR outcomes. This type of study represents a potentially useful tool to extend the understanding of AMR epidemiology for future outbreak prediction and judicious choice of antibiotics. Erefore, this cross-sectional study was conducted to predict the association of phenotypic and genotypic resistance traits in uropathogenic Escherichia coli (UPEC). 80.95% of cases were derived from females, and 38.10% of cases were found in the age group of 21–30 years

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