Within-sample and between-sample variation of antimicrobial resistance in fecal Escherichia coli isolates from pigs.

Section of Epidemiology, National Veterinary Institute, N-0033 Oslo, Norway.
Microbial Drug Resistance (Impact Factor: 2.52). 02/2002; 8(4):385-91. DOI: 10.1089/10766290260469660
Source: PubMed

ABSTRACT The present study was initiated to evaluate the effect of sampling time and within-sample variability on the diversity in antimicrobial resistance patterns in fecal Escherichia coli from healthy pigs. Isolates were tested against 11 antimicrobials. A total of 25 different profiles were observed, involving resistance to ampicillin, streptomycin, tetracycline, sulfonamides, trimethoprim, and/or a trimethoprim/sulfonamide combination. No isolates were resistant to enrofloxacin, gentamicin, or chloramfenicol, whereas resistance against neomycin and nalidixic acid was sporadically detected in isolates from grower pigs. A model that clusters pigs within-sampling time as a repeated factor and clusters isolates within individual pigs as a random factor was used. For sows, the variance component ratio of sampling time to residuals was 0.28-0.56 for the different antimicrobials (except ampicillin) and 0.85-1.79 for grower pigs. The variance components for within-sample variation were zero or close to zero, except in isolates from sows where resistance to ampicillin explained 14.8 times more of the variation compared to residuals. Thus, the effect of an animal's status at a given sampling time was more influential on the variability in antimicrobial resistance than within-animal diversity. We conclude that repeated sampling and analysis of one isolate per animal each time may be preferable for screening general tendencies, whereas several isolates have to be tested when individual animals are focused.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The emergence of antimicrobial-resistant microorganisms in both humans and food animals is a growing concern. Debate has centred on links between antimicrobial use in the production of food animals and the emergence of resistant organisms in the human population. Consequently, microbial risk assessment (MRA) is being used to facilitate scientific investigations of the risks related to the food chain, including quantification of uncertainty and prioritization of control strategies. MRA is a scientific tool that can be used to evaluate the level of exposure and the subsequent risk to human health relating to a specific organism or particular type of resistance. This paper reviews the recent applications of MRA in the area of antimicrobial resistance, and in particular, it focuses on the methods, assumptions and data limitations. Since MRA outputs are dependent on the quality of data inputs used in their development, we aim to promote the generation of good quality data by describing the properties that data should ideally possess for MRA and by highlighting the benefit of data generation specifically for inclusion in MRAs.
    Journal of Antimicrobial Chemotherapy 07/2004; 53(6):906-17. DOI:10.1093/jac/dkh182 · 5.44 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: An ideal national resistance monitoring program should deliver a precise estimate of the resistance situation for a given combination of bacteria and antimicrobial at a low cost. To achieve this, decisions need to be made on the number of samples to be collected at each of different possible sampling points. Existing methods of sample size calculation can not be used to solve this problem, because sampling decisions do not only depend on the prevalence of resistance and sensitivity and specificity of resistance testing, but also on the prevalence of the bacteria, and test characteristics of isolation of these bacteria. Our aim was to develop a stochastic simulation model that optimized a national resistance monitoring program, taking multi-stage sampling, imperfect sensitivity and specificity of diagnostic tests, and cost-effectiveness considerations into account. The process of resistance testing of Campylobacter spp. isolated from cloacal swab samples from poultry was modeled using a Markov Chain Monte Carlo model. Different sampling scenarios on the number of flocks to be tested, the number of birds from each flock, and the number of campylobacter colonies submitted to susceptibility testing were evaluated regarding the precision of the resulting prevalence estimate. Precision of the prevalence estimate was defined as the absolute difference between apparent and true prevalence of resistance. A partial budget approach was utilized to find the most cost-effective combination of samples to obtain a defined precision of the prevalence estimate. For a sampling scenario testing 100 flocks, five birds per flock, and one campylobacter colony per sample, the median error of the prevalence estimate was 2.5%, and 95% of the simulations resulted in an error of 7% or less. When the total number of samples was kept constant, maximizing the number of flocks tested, and only testing one bird per flock resulted in the most precise prevalence estimate. Submitting more than one campylobacter colony to resistance testing did not improve the prevalence estimate. Partial budget analysis indicated that the most cost-effective strategy was testing of two birds per flock, and submitting one colony per sample to resistance testing.
    Preventive Veterinary Medicine 09/2005; 70(1-2):29-43. DOI:10.1016/j.prevetmed.2005.02.017 · 2.51 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Pulsed-field gel electrophoresis (PFGE) was used to investigate the dissemination and diversity of ampicillin-resistant (Amp(r)) and nalidixic acid-resistant (Nal(r)) commensal Escherichia coli strains in a cohort of 48 newborn calves. Calves were sampled weekly from birth for up to 21 weeks and a single resistant isolate selected from positive samples for genotyping and further phenotypic characterization. The Amp(r) population showed the greatest diversity, with a total of 56 different genotype patterns identified, of which 5 predominated, while the Nal(r) population appeared to be largely clonal, with over 97% of isolates belonging to just two different PFGE patterns. Distinct temporal trends were identified in the distribution of several Amp(r) genotypes across the cohort, with certain patterns predominating at different points in the study. Cumulative recognition of new Amp(r) genotypes within the cohort was biphasic, with a turning point coinciding with the housing of the cohort midway through the study, suggesting that colonizing strains were from an environmental source on the farm. Multiply resistant isolates dominated the collection, with >95% of isolates showing resistance to at least two additional antimicrobials. Carriage of resistance to streptomycin, sulfamethoxazole, and tetracycline was the most common combination, found across several different genotypes, suggesting the possible spread of a common resistance element across multiple strains. The proportion of Amp(r) isolates carrying sulfamethoxazole resistance increased significantly over the study period (P < 0.05), coinciding with a decline in the most common genotype pattern. These data indicate that calves were colonized by a succession of multiply resistant strains, with a probable environmental source, that disseminated through the cohort over time.
    Applied and Environmental Microbiology 11/2005; 71(11):6680-8. DOI:10.1128/AEM.71.11.6680-6688.2005 · 3.95 Impact Factor
Show more