Modelling the growth of Clostridium perfringens during the cooling of bulk meat

A dynamic predictive model was developed to describe the effects of temperature, pH and NaCl concentration on the growth of Clostridium perfringens type A. The model for the specific growth rate was based on 81 growth curves generated in our laboratory or obtained from the publicly available ComBase database. Growth curves obtained during cooling were fitted with the dynamic model of Baranyi and Roberts. This made it possible to determine the parameter value reflecting the physiological state of C. perfringens after heating profiles typically applied to bulk meat. The model with the obtained parameters provided a good description of growth of C. perfringens in 24 heating/cooling curves generated specifically for this work (various non-isothermal treatments with a range of combinations of pH and NaCl concentration), and also for existing literature data. The dynamic model was implemented in Perfringens Predictor, a web-based application that can be accessed free of charge via www.combase.cc. It is anticipated that the use of this model and Perfringens Predictor will contribute to a reduction in the food poisoning incidence associated with C. perfringens

Detection limit of Clostridium botulinum spores in dried mushroom samples sourced from China

A survey of dried mushrooms (Lentinula edodes (Shiitake) and Auricularia auricula (Wood Ear)) sourced from China was carried out to determine the natural contamination of these mushrooms with spores of proteolytic Clostridium botulinum and non-proteolytic C. botulinum. The mushrooms were collected from supermarkets and retailers in 21 cities in China during October 2008. Spore loads of C. botulinum in mushrooms have a degree of uncertainty and variability and this study contributes valuable data for determining prevalence of spores of C. botulinum in mushrooms. An optimized detection protocol that combined selective enrichment culture with multiplex PCR was used to test for spores of proteolytic and non-proteolytic C. botulinum. Detection limits were calculated, using a maximum likelihood protocol, from mushroom samples inoculated with defined numbers of spores of proteolytic C. botulinum or non-proteolytic C. botulinum. Based on the maximum likelihood detection limit, it is estimated that dried mushroom A. auricula contained <550spores/kg of proteolytic C. botulinum, and <350spores/kg of non-proteolytic C. botulinum. Dried L. edodes contained <1500spores/kg of proteolytic C. botulinum and it was not possible to determine reliable detection limits for spores of non-proteolytic C. botulinum using the current detection protocol

Development and application of a new method for specific and sensitive enumeration of spores of nonproteolytic Clostridium botulinum types B, E, and F in foods and food materials

The highly potent botulinum neurotoxins are responsible for botulism, a severe neuroparalytic disease. Strains of nonproteolytic Clostridium botulinum form neurotoxins of types B, E, and F and are the main hazard associated with minimally heated refrigerated foods. Recent developments in quantitative microbiological risk assessment (QMRA) and food safety objectives (FSO) have made food safety more quantitative and include, as inputs, probability distributions for the contamination of food materials and foods. A new method that combines a selective enrichment culture with multiplex PCR has been developed and validated to enumerate specifically the spores of nonproteolytic C. botulinum. Key features of this new method include the following: (i) it is specific for nonproteolytic C. botulinum (and does not detect proteolytic C. botulinum), (ii) the detection limit has been determined for each food tested (using carefully structured control samples), and (iii) a low detection limit has been achieved by the use of selective enrichment and large test samples. The method has been used to enumerate spores of nonproteolytic C. botulinum in 637 samples of 19 food materials included in pasta-based minimally heated refrigerated foods and in 7 complete foods. A total of 32 samples (5 egg pastas and 27 scallops) contained spores of nonproteolytic C. botulinum type B or F. The majority of samples contained <100 spores/kg, but one sample of scallops contained 444 spores/kg. Nonproteolytic C. botulinum type E was not detected. Importantly, for QMRA and FSO, the construction of probability distributions will enable the frequency of packs containing particular levels of contamination to be determined

Multiplex PCR for Detection of Botulinum Neurotoxin-Producing Clostridia in Clinical, Food, and Environmental Samples▿

Botulinum neurotoxin (BoNT), the most toxic substance known, is produced by the spore-forming bacterium Clostridium botulinum and, in rare cases, also by some strains of Clostridium butyricum and Clostridium baratii. The standard procedure for definitive detection of BoNT-producing clostridia is a culture method combined with neurotoxin detection using a standard mouse bioassay (SMB). The SMB is highly sensitive and specific, but it is expensive and time-consuming and there are ethical concerns due to use of laboratory animals. PCR provides a rapid alternative for initial screening for BoNT-producing clostridia. In this study, a previously described multiplex PCR assay was modified to detect all type A, B, E, and F neurotoxin genes in isolated strains and in clinical, food, environmental samples. This assay includes an internal amplification control. The effectiveness of the multiplex PCR method for detecting clostridia possessing type A, B, E, and F neurotoxin genes was evaluated by direct comparison with the SMB. This method showed 100% inclusivity and 100% exclusivity when 182 BoNT-producing clostridia and 21 other bacterial strains were used. The relative accuracy of the multiplex PCR and SMB was evaluated using 532 clinical, food, and environmental samples and was estimated to be 99.2%. The multiplex PCR was also used to investigate 110 freshly collected food and environmental samples, and 4 of the 110 samples (3.6%) were positive for BoNT-encoding genes

Symbolic Equivalences for Open Systems

Behavioural equivalences on open systems are usually defined by comparing system behaviour in all environments. Here, we introduce a hierarchy of behavioural equivalences for open systems in the setting of process calculi, building on a symbolic approach proposed in a previous paper. The hierarchy comprises both branching, bisimulation-based, and non-branching, trace-based, equivalences. Symbolic equivalences are amenable to effective analysis techniques (e.g., the symbolic transition system is finitely branching under mild assumptions), which result to be correct, but often not complete due to redundant information. Two kinds of redundancy, syntactic and semantic, are discussed and one class of symbolic equivalences is identified that deals satisfactorily with syntactic redundant transitions, which are a primary source of incompleteness

Validation of three rapid screening methods for detection of verotoxin-producing Escherichia coli in foods:interlaboratory study

An interlaboratory study was conducted for the validation of 3 methods for the detection of all verotoxin-producing Escherichia coli (VTEC) in foods. The methods were a multi-analyte 1-step lateral flow immunoassay (LFIA) for detection of E. coli O157 and verotoxin (VT); an enzyme-linked immunosorbent assay targeted against VT1, VT2, and VT2c (VT-ELISA); and a polymerase chain reaction (PCR) method for detection of VT genes (VT-PCR). Aliquots (25 g or 25 mL) of 4 food types (raw minced [ground] beef, unpasteurized milk, unpasteurized apple juice [cider], and salami) were individually inoculated with low numbers (<9 to 375 cells/25 g) of 6 test strains of E. coli (serogroups O26, O103, O111, O145, and O157) with differing VT-producing capabilities. Five replicates for each test strain and 5 uninoculated samples were prepared for each food type. Fourteen participating laboratories analyzed samples using the LFIA, 9 analyzed the samples by ELISA, and 9 by PCR. The LFIA for O157 and VT had a specificity (correct identification of negative samples) of 92 and 94%, respectively, and a sensitivity (correct identification of positive samples) of 94 and 55%, respectively. The VT-ELISA and VT-PCR had a specificity of 98 and 99%, respectively, and a sensitivity of 89 and 72%, respectively