The Influence of Heteroresistance on Minimum Inhibitory Concentration, Investigated Using Weak-Acid Stress in Food Spoilage Yeasts.

Populations of microbial cells may resist environmental stress by maintaining a high population-median resistance (IC) or, potentially, a high variability in resistance between individual cells (heteroresistance); where heteroresistance would allow certain cells to resist high stress, provided the population was sufficiently large to include resistant cells. This study sets out to test the hypothesis that both IC and heteroresistance may contribute to conventional minimal inhibitory concentration (MIC) determinations, using the example of spoilage-yeast resistance to the preservative sorbic acid. Across a panel of 26 diverse yeast species, both heteroresistance and particularly IC were positively correlated with predicted MIC.

Critical comparison of statistical methods for quantifying variability and uncertainty of microbial responses from experimental data.

Variability and uncertainty are important factors for quantitative microbiological risk assessment (QMRA). In this context, variability refers to inherent sources of variation, whereas uncertainty refers to imprecise knowledge or lack of it. In this work we compare three statistical methods to estimate variability in the kinetic parameters of microbial populations: mixed-effect models, multilevel Bayesian models, and a simplified algebraic method previously suggested.

Bayesian global regression model relating product characteristics of intermediate moisture food products to heat inactivation parameters for Salmonella Napoli and Eurotium herbariorum mould spores.

Thermal inactivation of pathogenic and spoilage organisms in low and intermediate moisture foods is of critical importance for guaranteeing microbiological safety and stability of these products. Producers tendentially reduce salt in low and intermediate moisture foods because of nutritional health considerations, but it is unclear how this affects microbial inactivation rates during pasteurization. In this study we predict the time to achieve a pre-defined 6-log reduction for Salmonella enterica subsp.

Phenotypic Prediction: Linking Virulence to the Genomics of 59 Strains.

The increased availability of whole-genome-sequencing techniques generates a wealth of DNA data on numerous organisms, including foodborne pathogens such as . However, how these data can be used to improve microbial risk assessment and understanding of epidemiology remains a challenge. The aim of this study was to assess variability in virulence and genetic characteristics between and within different serovars.