Establishment and validation of molecular predictive models for understanding survival and susceptibility of Vibrio parahaemolyticus in seafood stored at low temperature
Type of DegreeMaster's Thesis
MetadataShow full item record
Vibrio parahaemolyticus has been a leading cause of pathogenic diseases to human health after consumption of contaminated seafood. Microbial predictive models have been very important parts in quantitative microbiological risk assessment (QMRA) to help people control pathogens. However, it has been known that predictive models based on traditional methods (i.e. plate counting methods) are time-consuming and lab-intensive. Also, these methods are not able to count the microorganisms occurring in special states (e.g. viable but nonculturable state, VBNC, stressed state), leading to underestimated risk results. In the first study, we simultaneously construct PCR-DGGE-based predictive models of Listeria monocytogenes and Vibrio parahaemolyticus on ready-to-eat shrimps when stored at 4oC and 10oC. A PCR-DGGE method was developed to enumerate V. parahaemolyticus. The Baranyi model was used to fit these data to molecular models (MMs). For L. monocytogenes, the MMs were growth models, which presented high goodness-of-fit as coefficients of determination (R2) > 0.92 and bias factors (Bf) and accuracy factors (Af) within the range of 1.0 to 1.1. In addition, compared with tradition models (TMs) based on plate counting methods, no significant difference (P > 0.05) was found when analyzing model parameters, lag phase (λ), or maximum growth rate (μmax). However for V. parahaemolyticus, the molecular models (MMs) were inactivation models, which showed significant differences when compared with TMs. In summary, the DNA-based PCR-DGGE method is accurate and reliable when used to construct growth models, but not suitable to establish inactivation models because DNA is also extracted from dead cells. In the second study, in order to establish accurate and reliable inactivation MMs for V. parahaemolyticus, the RNA-based real-time RT-PCR was applied to develop MMs of V. parahaemolyticus in Eastern oysters (Crassostrea virginica) during storage at 0, 4, and 10oC for 21 or 11 days. Also, we investigated the efficiency of an individual quick freezing (IQF) treatment on cold and non-cold adapted V. parahaemolyticus. MMs of V. parahaemolyticus were constructed based on real-time RT-PCR, and compared with TMs based on plate counting methods. The results were significantly different (P < 0.05) between the population reductions, inactivation rates, and the valid numbers of V. parahaemolyticus. Additionally, the result of IQF efficiency showed that cold adapted cells had a greater ability to resist adverse conditions resulting in less die-off. All indicate that MMs based on real-time RT-PCR are more specific, sensitive, and reliable to predict growth or inactivation of microorganisms.