Search

Aims To obtain knowledge about (i) how to sample airborne methicillin-resistant Staphylococcus aureus (MRSA) and dust in the pig farm environment including effects of sampler on (a) measured exposure, (b) MRSA survival and (c) spatial and temporal variation in exposure, and (ii) the association between exposure to MRSA, dust and optical density OD. Methods and results Airborne dust was sampled on five pig farms using five active and one passive samplers. Staphylococcus aureus and MRSA (as a subset of S. aureus) were quantified using selective agar media and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The Andersen sampler, electrostatic dust collectors (EDC), and Gesamtstaubprobenahme (GSP) and Institute of Occupational Medicine samplers with polycarbonate or Teflon filters were applicable for sampling airborne MRSA. The half-life of MRSA was not reduced by active sampling. A significant correlation was found between dust and S. aureus exposure within, but not between, farm section and farms. A significant spatial and temporal variation in dust and MRSA exposure was found within a stable. The dust sampling rate and the concentration of MRSA in the sampled dust decreased after 5 days of sampling. Conclusion Sampling using the GSP can be performed for 1 h without affecting the following half-life of MRSA. Sampling for MRSA using the EDC should not exceed 3 days due to overloading and the die-off of MRSA. The measurement of OD may be used as a proxy measure for dust exposure. To obtain knowledge about potential exposure, samples should be taken repeatedly and in different areas within a stable section. Significance and impact of the study Sampling method, sampling time and number of samples taken, but not force of airflow on the filter, influence the measured potential exposure to MRSA and dust.

Aims To explore the predictions of a novel rearrangement of the Baranyi–Roberts model (BRM) with time to detection data obtained from optical density data of microbial growth. Methods and Results Growth of Escherichia coli and Salmonella Typhimurium under mild conditions of temperature (25–37°C), salt (0·086, 0·51 and 1·03 mol l−1) and pH (6·85–4·5) was examined using optical density. Time to detection (TTD) data were fitted to a model based on a rearrangement of the BRM. Observations showed compatibility with standard viable count studies and produced highly accurate specific growth rates and lag phase durations. At high salt and low pH, however, there was a substantial dependency on the initial inoculum for the observation of visible growth. At 30 and 37°C, with 1·03 mol l−1 salt, and at pH

N . B O T T E L D O O R N , M . H E Y N D R I C K X , N . R I J P E N S , K . G R I J S P E E R D T A N D L . H E R M A N . 2003. Aims: The purpose of this study was to investigate the prevalence of Salmonella in pigs at the moment of slaughter and in the slaughterhouse environment. Methods and Results: In total, five different commercial slaughterhouses were sampled during eight slaughterhouse visits. Carcass swabs, colon content and mesenteric lymph nodes were taken to reflect the animal status and from the slaughterhouse environmental samples were taken. Salmonella was isolated from 37% of the carcass samples as a mean value. High variations were noticed between different slaughterhouses (between 0 and 70%) and sampling days in the same abattoir (between 3 and 52%). A correlation was found between the carcass contamination and the status of the delivered animals (P ¼ 0AE01675). Cross contamination was estimated to account for 29% of the positive carcasses. The slaughterhouse environment was highly contaminated; before starting the slaughtering activities 25% of the samples were positive on average. The most prevalent serotypes isolated at the slaughterhouse environment and from the colon content were S. Typhimurium, S. Livingstone and S. Derby. On carcasses S. Typhimurium was predominately isolated (71%). The biggest variability of serotypes was found in the mesenteric lymph nodes. Serologically 56AE3% of the pigs were found positive for Salmonella using a cut-off level of the optical density percentage higher than 10 (O.D.% ‡ 10). While on individual pig level the correlation between the bacteriological and serological data was poor, because of recent Salmonella infections, a better correlation was found at the herd level on the moment of slaughtering. Conclusion: A high degree of carcass contamination is noticed after slaughtering. This contamination resulted from the delivery of Salmonella-positive pigs and cross-contamination from the slaughterhouse environment. Significance and Impact of the Study: In pigs, Salmonella carriage is high, but it is obvious that slaughterhouse hygiene is a determinative factor for managing carcass contamination.

Aims: To develop a set of kinetic equations which more ably describe the disinfection process. Methods and Results: A group of functions, the fat equations, based on the model used for the quantification of microbial inhibition, was produced. These functions introduce a limit to the numbers of micro-organisms capable of being disinfected. These new expressions were shown to be more general forms of currently-used (e.g. log-linear) disinfection models, and accommodate the lags and/or tails of non-linear log-survivor–time plots. An advance in the experimental procedures used to obtain disinfection data, using an optical density technique, was developed concomitantly. Conclusions: The methods of analyses (experimental and modelling) allow the researcher to examine, more ably, five-minute disinfection (or specific time disinfection tests) as well as the more important disinfection rate analyses. Significance and Impact of the Study: The fat equations are an improvement over commonly-used rate models of disinfection, which are shown to be special cases of these equations. This raises the question as to whether our current understanding of the kinetic basis of disinfection requires revision.

Investigations of biocide efficacy by automated methods involving optical density measurements, e.g. using the recently published 'Bioscreen' method, are complicated by the fact that a poor correlation often exists between the log reductions obtained using the automated method vs those obtained by the traditional plate count methods. It was hypothesized that the differences observed between the two methods were due to the level of cell injury, which was masked by the optical density methods but which was recognized by the plate counts. Comparisons of log reductions following a disinfection test always showed the Bioscreen method to be overestimating the log reductions with respect to the plate counts. A correlation between colony size on the plates and the 'Bioscreen' results for a fixed disinfectant concentration and contact time was found using Global Imaging software. The results obtained also suggested that the observed colony area was dependent on the amount of injury incurred by a microbe during the disinfection process. A mathematical model of injury was developed which predicted the observed differences between the Bioscreen and the traditional plate method. The model further suggested a possible reason for biocidal lags.

Aims: In this study, we have evaluated the impact of methodological approaches in the determination of biofilm formation by four clinical isolates of Escherichia coli in static assays. Methods and Results: The assays were performed in microtitre plates with two minimal and two enriched broths, with one- or two-steps protocol, and using three different mathematical formulas to quantify adherent bacteria. Different biofilm formation patterns were found depending on the E. coli strain, culture medium and reading optical density on one- and two-steps protocol. Strong or moderate biofilm formation occurred mostly in minimal media. The mathematical formulas used to quantify biofilm formation also gave different results and bacterial growth rate should be taken into account to quantify biofilm. Conclusions: Escherichia coli forms biofilms on static assays in a method-dependent fashion, depending on strain, and it is strongly modulated by culture conditions. Significance and Impact of the Study: As verified in the studied E. coli strains, biofilm formation by any organism should be cautiously interpreted, considering all variables in the experimental settings.

Aims: To develop a novel, rapid method for testing the ability of quenching agents to neutralize disinfectants. Methods and Results: Tests were performed to determine the suitability of different neutralizers for a range of disinfectants, using a new method based on the Bioscreen optical density analyser. Results showed that during disinfection tests, efficacy could be over-estimated due to poor, or no, neutralization of the disinfectant after a specified time of exposure to the bacteria. The failure to distinguish adequately between bacteriostatic and bactericidal effects can lead to false results during disinfectant testing. Experiments also showed that dilution of the disinfectant, following exposure to the bacteria, was not always sufficient to stop the activity of the disinfectant for chemicals with low dilution coefficients. Conclusions: The quench test proved to be very quick and easy to perform, with results being available within 18 h. Using the Bioscreen, the test is automated and determines whether dilution into a particular neutralizer is able to inactivate a disinfectant within 30 s. Significance and Impact of the Study: This new approach allows the efficacy of quenching agents to be determined, prior to undertaking each disinfection study, and can help in the development of more suitable quenching solutions. The test has also been used to find suitable neutralizers for mixtures of disinfectants which might be used during studies on synergistic biocide combinations.