Listeria monocytogenes Growth Kinetics in Milkshakes Made from Naturally and Artificially Contaminated Ice Cream

This study assessed the growth of Listeria monocytogenes in milkshakes made using the process-contaminated ice cream associated with a listeriosis outbreak in comparison to milkshakes made with artificially contaminated ice cream. For all temperatures, growth kinetics including growth rates, lag phases, maximum populations, and population increases were determined for the naturally and artificially derived contaminants at 5, 10, 15, and 25°C storage for 144 h. The artificially inoculated L. monocytogenes presented lower growth rates and shorter lag phases than the naturally contaminated populations at all temperatures except for 5°C, where the reverse was observed. At 25°C, lag phases of the naturally and artificially contaminated L. monocytogenes were 11.6 and 7.8 h, respectively. The highest increase in population was observed for the artificially inoculated pathogen at 15°C after 96 h (6.16 log CFU/mL) of storage. Growth models for both contamination states in milkshakes were determined. In addition, this study evaluated the antimicrobial effectiveness of flavoring agents, including strawberry, chocolate and mint, on the growth of the pathogen in milkshakes during 10°C storage. All flavor additions resulted in decreased growth rates of L. monocytogenes for both contamination states. The addition of chocolate and mint flavoring also resulted in significantly longer lag phases for both contamination states. This study provides insight into the differences in growth between naturally and artificially contaminated L. monocytogenes in a food product

Metagenomics of pasteurized and unpasteurized gouda cheese using targeted 16S rDNA sequencing

Abstract Background The microbiome of cheese is diverse, even within a variety. The metagenomics of cheese is dependent on a vast array of biotic and abiotic factors. Biotic factors include the population of microbiota and their resulting cellular metabolism. Abiotic factors, including the pH, water activity, fat, salt, and moisture content of the cheese matrix, as well as environmental conditions (temperature, humidity, and location of aging), influence the biotic factors. This study assessed the metagenomics of commercial Gouda cheese prepared using pasteurized or unpasteurized cow milk or pasteurized goat milk via 16S rDNA sequencing. Results Results were analyzed and compared based on milk pasteurization and source, spatial variability (core, outer, and under the rind), and length of aging (2–4 up to 12–18 months). The dominant organisms in the Gouda cheeses, based on percentage of sequence reads identified at the family or genus levels, were Bacillaceae, Lactococcus, Lactobacillus, Streptococcus, and Staphylococcus. More genus- or family-level (e.g. Bacillaceae) identifications were observed in the Gouda cheeses prepared with unpasteurized cow milk (120) compared with those prepared with pasteurized cow milk (92). When assessing influence of spatial variability on the metagenomics of the cheese, more pronounced differences in bacterial genera were observed in the samples taken under the rind; Brachybacterium, Pseudoalteromonas, Yersinia, Klebsiella, and Weissella were only detected in these samples. Lastly, the aging length of the cheese greatly influenced the number of organisms observed. Twenty-seven additional genus-level identifications were observed in Gouda cheese aged for 12–18 months compared with cheese only aged 2–4 months. Conclusions Collectively, the results of this study are important in determining the typical microbiota associated with Gouda cheese and how the microbiome plays a role in safety and quality