Dataset Information

Diversity and Antimicrobial Resistance Genotypes in Non-Typhoidal Salmonella Isolates from Poultry Farms in Uganda.

ABSTRACT: Non-typhoidal Salmonella (NTS) are foodborne pathogens of global public health significance. The aim of this study was to subtype a collection of 85 NTS originating from poultry farms in Uganda, and to evaluate a subgroup of phenotypically resistant isolates for common antimicrobial resistance genes and associated integrons. All isolates were subtyped by pulsed-field gel electrophoresis (PFGE). Phenotypically resistant isolates (n = 54) were screened by PCR for the most relevant AMR genes corresponding to their phenotypic resistance pattern, and all 54 isolates were screened by PCR for the presence of integron class 1 and 2 encoding genes. These genes are known to commonly encode resistance to ampicillin, tetracycline, ciprofloxacin, trimethoprim, sulfonamide and chloramphenicol. PFGE revealed 15 pulsotypes representing 11 serotypes from 75 isolates, as 10 were non-typable. Thirty one (57.4%) of the 54 resistant isolates carried at least one of the seven genes (blaTEM-1,cmlA, tetA, qnrS,sul1,dhfrI,dhfrVII) identified by PCR and six (11%) carried class 1 integrons. This study has shown that a diversity of NTS-clones are present in Ugandan poultry farm settings, while at the same time similar NTS-clones occur in different farms and areas. The presence of resistance genes to important antimicrobials used in human and veterinary medicine has been demonstrated, hence the need to strengthen strategies to combat antimicrobial resistance at all levels.

SUBMITTER: Odoch T

PROVIDER: S-EPMC5858393 | biostudies-other | 2018 Feb

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:The burden of antimicrobial use in agricultural settings is one of the greatest challenges facing global health and food security in the modern era. Malaysian poultry operations are a relevant but understudied component of epidemiology of antimicrobial resistance. We aimed to identify the prevalence, resistance patterns, and risk factors associated with Salmonella isolates from poultry farms in three states of East Coast Peninsular Malaysia. Between 8 February 2019 and 23 February 2020, a total of 371 samples (cloacal swabs = 259; faecal = 84; Sewage = 14, Tap water = 14) was collected from poultry operations. Characteristics of the sampled farms and associated risk factors were obtained using semi-structured questionnaires. Presumptive Salmonella spp. isolates were identified based on colony morphology with subsequent biochemical and PCR confirmation. Susceptibility of isolates was tested against a panel of 12 antimicrobials using disk diffusion method. Our findings revealed that the proportion of Salmonella spp.-positive isolates across sample source were as following: cloacal swab (46.3%, 120/259); faecal (59.5%, 50/84); in tap water (14.3%, 2/14); and in sewage sample (35.7%, 5/14). Isolates from faecal (15.5%, 13/84), cloacal (1.2%, 3/259), and sewage (7.1%, 1/14) samples were significantly resistant to at least five classes of antimicrobials. Resistance to Sulfonamides class (52%, 92/177) was predominantly observed followed by tetracycline (39.5%, 70/177) and aminoglycosides (35.6%, 63/177). Multivariate regression analysis identified intensive management system (OR = 1.55, 95% CI = 1.00-2.40) as a leading driver of antimicrobial resistance (AMR) acquisition. A prevalence of resistance to common antimicrobials was recorded for sulfamethoxazole (33.9%), tetracycline (39.5%), and trimethoprim-sulphamethoxazole (37.9%). A close association between different risk factors and the prevalence of AMR of Salmonella strains suggests a concern over rising misuse of veterinary antimicrobials that may contribute to the emergence and evolution of multidrug-resistant pathogen isolates. One Health approach is recommended to achieve a positive health outcome for all species.

Dataset Information

Diversity and Antimicrobial Resistance Genotypes in Non-Typhoidal Salmonella Isolates from Poultry Farms in Uganda.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets