Quantitative microbiological risk assessment as a tool to obtain useful information for risk managers - specific application to Listeria monocytogenes and ready-to-eat meat products

The presence of Listeria monocytogenes in a sliced cooked, cured ham-like meat product was quantitatively assessed. Sliced cooked, cured meat products are considered as high risk products. These ready-to-eat, RTE, products (no special preparation, e.g. thermal treatment, before eating is required), support growth of pathogens (high initial pH = 6.2–6.4 and water activity = 0.98–0.99) and has a relatively long period of storage at chilled temperatures with a shelf life equal to 60 days based on manufacturer's instructions. Therefore, in case of post-process contamination, even with low number of cells, the microorganism is able to reach unacceptable levels at the time of consumption. The aim of this study was to conduct a Quantitative Microbiological Risk Assessment (QMRA) on the risk of L. monocytogenes presence in RTE meat products. This may help risk managers to make decisions and apply control measures with ultimate objective the food safety assurance. Examples are given to illustrate the development of practical risk management strategies based on the results obtained from the QMRA model specifically developed for this pathogen/food product combinatio

Modeling Population Growth in R with the biogrowth Package

The growth of populations is of interest in a broad variety of fields, such as epidemiology, economics or biology. Although a large variety of growth models are available in the scientific literature, their application usually requires advanced knowledge of mathematical programming and statistical inference, especially when modelling growth under dynamic environmental conditions. This article presents the biogrowth package for R, which implements functions for modelling the growth of populations. It can predict growth under static or dynamic environments, considering the effect of an arbitrary number of environmental factors. Moreover, it can be used to fit growth models to data gathered under static or dynamic environmental conditions. The package allows the user to fix any model parameter prior to the fit, an approach that can mitigate identifiability issues associated to growth models. The package includes common S3 methods for visualization and statistical analysis (summary of the fit, predictions, . . . ), easing result interpretation. It also includes functions for model comparison/selection. We illustrate the functions in biogrowth using examples from food science and economy

A New Model for the Spectral Induced Polarization Signature of Bacterial Growth in Porous Media

The complex conductivity of porous materials and colloidal suspensions comprises two components: an in-phase conductivity associated with electromigration of the charge carriers and a quadrature conductivity associated with the reversible storage of the charges at some polarization length scales. We developed a quantitative model to investigate the frequency domain induced polarization response of suspensions of bacteria and bacteria growth in porous media. Induced polarization of bacteria (α polarization) is related to the properties of the electrical double layer of the bacteria. Surface conductivity and α polarization are due to the Stern layer of counterions occurring in a brush of polymers coating the surface of the bacteria. These phenomena can be related to their cation exchange capacity. The mobility of the counterions in this Stern layer is found to be very small (4.7 × 10-10 m2 s-1 V-1 at 25°C). This implies a very low relaxation frequency for the α polarization of the bacteria cells (typically around 0.1-5 Hz), in agreement with experimental observations. This new model can be coupled to reactive transport modeling codes in which the evolution of bacterial populations are usually described by Monod kinetics. We show that the growth rate and endogenous decay coefficients of bacteria in a porous sand can be inferred nonintrusively from time-lapse frequency domain induced polarization data

A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters

Biolog phenotype microarrays enable simultaneous, high throughput analysis of cell cultures in different environments. The output is high-density time-course data showing redox curves (approximating growth) for each experimental condition. The software provided with the Omnilog incubator/reader summarizes each time-course as a single datum, so most of the information is not used. However, the time courses can be extremely varied and often contain detailed qualitative (shape of curve) and quantitative (values of parameters) information. We present a novel, Bayesian approach to estimating parameters from Phenotype Microarray data, fitting growth models using Markov Chain Monte Carlo methods to enable high throughput estimation of important information, including length of lag phase, maximal ``growth'' rate and maximum output. We find that the Baranyi model for microbial growth is useful for fitting Biolog data. Moreover, we introduce a new growth model that allows for diauxic growth with a lag phase, which is particularly useful where Phenotype Microarrays have been applied to cells grown in complex mixtures of substrates, for example in industrial or biotechnological applications, such as worts in brewing. Our approach provides more useful information from Biolog data than existing, competing methods, and allows for valuable comparisons between data series and across different models

Residual viral and bacterial contamination of surfaces after cleaning and disinfection

Environmental surfaces contaminated with pathogens can be sources of indirect transmission, and cleaning and disinfection are common interventions focused on reducing contamination levels. We determined the efficacy of cleaning and disinfection procedures for reducing contamination by noroviruses, rotavirus, poliovirus, parechovirus, adenovirus, influenza virus, Staphylococcus aureus, and Salmonella enterica from artificially contaminated stainless steel surfaces. After a single wipe with water, liquid soap, or 250-ppm free chlorine solution, the numbers of infective viruses and bacteria were reduced by 1 log10 for poliovirus and close to 4 log10 for influenza virus. There was no significant difference in residual contamination levels after wiping with water, liquid soap, or 250-ppm chlorine solution. When a single wipe with liquid soap was followed by a second wipe using 250- or 1,000-ppm chlorine, an extra 1- to 3-log10 reduction was achieved, and except for rotavirus and norovirus genogroup I, no significant additional effect of 1,000 ppm compared to 250 ppm was found. A reduced correlation between reduction in PCR units (PCRU) and reduction in infectious particles suggests that at least part of the reduction achieved in the second step is due to inactivation instead of removal alone. We used data on infectious doses and transfer efficiencies to estimate a target level to which the residual contamination should be reduced and found that a single wipe with liquid soap followed by a wipe with 250-ppm free chlorine solution was sufficient to reduce the residual contamination to below the target level for most of the pathogens tested

Incorporating prior knowledge improves detection of differences in bacterial growth rate

BACKGROUND: Robust statistical detection of differences in the bacterial growth rate can be challenging, particularly when dealing with small differences or noisy data. The Bayesian approach provides a consistent framework for inferring model parameters and comparing hypotheses. The method captures the full uncertainty of parameter values, whilst making effective use of prior knowledge about a given system to improve estimation. RESULTS: We demonstrated the application of Bayesian analysis to bacterial growth curve comparison. Following extensive testing of the method, the analysis was applied to the large dataset of bacterial responses which are freely available at the web-resource, ComBase. Detection was found to be improved by using prior knowledge from clusters of previously analysed experimental results at similar environmental conditions. A comparison was also made to a more traditional statistical testing method, the F-test, and Bayesian analysis was found to perform more conclusively and to be capable of attributing significance to more subtle differences in growth rate. CONCLUSIONS: We have demonstrated that by making use of existing experimental knowledge, it is possible to significantly improve detection of differences in bacterial growth rate

Effects of preculturing conditions on lag time and specific growth rate of Enterobacter sakazakii in reconstituted powdered infant formula

Enterobacter sakazakii can be present, although in low levels, in dry powdered infant formulae, and it has been linked to cases of meningitis in neonates, especially those born prematurely. In order to prevent illness, product contamination at manufacture and during preparation, as well as growth after reconstitution, must be minimized by appropriate control measures. In this publication, several determinants of the growth of E. sakazakii in reconstituted infant formula are reported. The following key growth parameters were determined: lag time, specific growth rate, and maximum population density. Cells were harvested at different phases of growth and spiked into powdered infant formula. After reconstitution in sterile water, E. sakazakii was able to grow at temperatures between 8 and 47°C. The estimated optimal growth temperature was 39.4°C, whereas the optimal specific growth rate was 2.31 h-1. The effect of temperature on the specific growth rate was described with two secondary growth models. The resulting minimum and maximum temperatures estimated with the secondary Rosso equation were 3.6°C and 47.6°C, respectively. The estimated lag time varied from 83.3 ± 18.7 h at 10°C to 1.73 ± 0.43 h at 37°C and could be described with the hyperbolic model and reciprocal square root relation. Cells harvested at different phases of growth did not exhibit significant differences in either specific growth rate or lag time. Strains did not have different lag times, and lag times were short given that the cells had spent several (3 to 10) days in dry powdered infant formula. The growth rates and lag times at various temperatures obtained in this study may help in calculations of the period for which reconstituted infant formula can be stored at a specific temperature without detrimental impact on healt

Vitalum study design: RCT evaluating the efficacy of tailored print communication and telephone motivational interviewing on multiple health behaviors

Abstract Background A large proportion of adults fail to meet public health guidelines for physical activity as well as fruit, vegetable and fat intake. Interventions are needed to improve these health behaviors. Both computer tailoring and motivational interviewing have shown themselves to be promising techniques for health behavior change. The Vitalum project aims to compare the efficacy of these techniques in improving the health behaviors of adults aged 45–70. This paper describes the design of the Vitalum study. Methods/Design Dutch general medical practices (N = 23) were recruited via a registration network or by personal invitation. The participants were then enrolled through these general practices using an invitational letter. They (n = 2,881) received a written baseline questionnaire to assess health behaviors, and potential psychosocial and socio-demographic behavioral determinants. A power analysis indicated that 1,600 participants who were failing to meet the guidelines for physical activity and either fruit or vegetable consumption were needed. Eligible participants were stratified based on hypertension status and randomized into one of four intervention groups: tailored print communication, telephone motivational interviewing, combined, and control. The first two groups either received four letters or took part in four interviews, whereas the combined group received two letters and took part in two interviews in turns at 5, 13, 30 and 43 weeks after returning the baseline questionnaire. Each letter and interview focused on physical activity or nutrition behavior. The participants also took part in a telephone survey 25 weeks after baseline to gather new information for tailoring. There were two follow-up questionnaires, at 47 and 73 weeks after baseline, to measure short- and long-term effects. The control group received a tailored letter after the last posttest. The process, efficacy and cost-effectiveness of the interventions will be examined by means of multilevel mixed regression, cost-effectiveness analyses and process evaluation. Discussion The Vitalum study simultaneously evaluates the efficacy of tailored print communication and telephone motivational interviewing, and their combined use for multiple behaviors and people with different motivational stages and education levels. The results can be used by policymakers to contribute to evidence-based prevention of chronic diseases. Trial Registration Dutch Trial Register NTR1068http://deepblue.lib.umich.edu/bitstream/2027.42/112919/1/12889_2008_Article_1186.pd

A single point mutation in the Listeria monocytogenes ribosomal gene rpsU enables SigB activation independently of the stressosome and the anti-sigma factor antagonist RsbV

Microbial population heterogeneity leads to different stress responses and growth behavior of individual cells in a population. Previously, a point mutation in the rpsU gene (rpsUG50C) encoding ribosomal protein S21 was identified in a Listeria monocytogenes LO28 variant, which leads to increased multi-stress resistance and a reduced maximum specific growth rate. However, the underlying mechanisms of these phenotypic changes remain unknown. In L. monocytogenes, the alternative sigma factor SigB regulates the general stress response, with its activation controlled by a series of Rsb proteins, including RsbR1 and anti-sigma factor RsbW and its antagonist RsbV. We combined a phenotype and proteomics approach to investigate the acid and heat stress resistance, growth rate, and SigB activation of L. monocytogenes EGDe wild type and the ΔsigB, ΔrsbV, and ΔrsbR1 mutant strains. While the introduction of rpsUG50C in the ΔsigB mutant did not induce a SigB-mediated increase in robustness, the presence of rpsUG50C in the ΔrsbV and the ΔrsbR1 mutants led to SigB activation and concomitant increased robustness, indicating an alternative signaling pathway for the SigB activation in rpsUG50C mutants. Interestingly, all these rpsUG50C mutants exhibited reduced maximum specific growth rates, independent of SigB activation, possibly attributed to compromised ribosomal functioning. In summary, the increased stress resistance in the L. monocytogenes EGDe rpsUG50C mutant results from SigB activation through an unknown mechanism distinct from the classical stressosome and RsbV/RsbW partner switching model. Moreover, the reduced maximum specific growth rate of the EGDe rpsUG50C mutant is likely unrelated to SigB activation and potentially linked to impaired ribosomal function