Monte Carlo simulation model predicts bactofugation can extend shelf-life of pasteurized fluid milk, even when raw milk with low spore counts is used as the incoming ingredient.

Bacterial spores from raw milk that survive the pasteurization process are responsible for half of all the spoilage of fluid milk. Bactofugation has received more attention as a nonthermal method that can reduce the presence of bacterial spores in milk and with it the spoilage of fluid milk. The objective of this work was to determine the effectiveness of bactofugation in removing spores from raw milk and estimate the effect the spore removal could have on shelf-life of fluid milk. The study was conducted in a commercial fluid milk processing facility where warm spore removal was performed using one-phase bactofuge followed by warm cream separation and high temperature, short time pasteurization. Samples from different stages of fluid milk processing with and without the use of bactofuge were tested for total plate count, mesophilic spore count, psychrotolerant spore count (PSC), and somatic cell count. Results were evaluated to determine the count reductions during different stages of fluid milk processing and compare counts in fluid milk processed with and without bactofugation. Bactofugation on average reduced the total plate count by 1.81 ± 0.72 log cfu/mL, mesophilic spore count by 1.08 ± 0.71 log cfu/mL, PSC by 0.86 ± 0.59 log cfu/mL, and somatic cell count by 135,881 ± 43,942 cells/mL. Psychrotolerant spore count in final pasteurized skim milk processed with and without bactofugation was used to predict the shelf-life of the pasteurized skim milk using the Monte Carlo simulation model. Although PSC in the initial raw milk was already low (-0.63 ± 0.47 log cfu/mL), the predicted values from the simulation model showed that bactofugation would extend the shelf-life of pasteurized skim milk by approximately 2 d. The results of this study will directly help fluid milk processors evaluate the benefits of using bactofugation as an intervention in their plants, and also demonstrate the benefits of using mathematical modeling in decision making.

Development of a risk assessment model to predict the occurrence of late blowing defect in Gouda cheese and evaluate potential intervention strategies.

Late blowing defect (LBD) is an important spoilage issue in semi-hard cheese, with the outgrowth of Clostridium tyrobutyricum spores during cheese aging considered to be the primary cause. Although previous studies have explored the microbial and physicochemical factors influencing the defect, a risk assessment tool that allows for improved and rational management of LBD is lacking. The purpose of this study was to develop a predictive model to estimate the probability of LBD in Gouda cheese and evaluate different intervention strategies. The spore concentration distribution of butyric acid bacteria (BAB) in bulk tank milk was obtained from 8 dairy farms over 12 mo. The concentration of C. tyrobutyricum from raw milk to the end of aging was simulated based on Gouda brined for 2 d in saturated brine at 8°C and aged at 13°C. Predicted C. tyrobutyricum concentrations during aging and estimated concentration thresholds in cheese at onset of LBD were used to predict product loss due to LBD during a simulated 1-yr production. With the estimated concentration thresholds in cheese ranging from 4.36 to 4.46 log most probable number (MPN)/kg of cheese, the model predicted that 9.2% (±1.7%) of Gouda cheese showed LBD by d 60; cheeses predicted to show LBD at d 60 showed a mean pH of 5.39 and were produced with raw milk with a mean BAB spore count of 143 MPN/L. By d 90, 36.1% (±3.4%) of cheeses were predicted to show LBD, indicating that LBD typically manifests between d 60 and 90, which is consistent with observations from the literature and the cheese industry. Sensitivity analysis indicated that C. tyrobutyricum maximum growth rate as well as concentration threshold in cheese at onset of LBD are the most important variables, identifying key data needs for development of more accurate models. The implementation of microfiltration or bactofugation of raw milk (assumed to show 98% efficiency of spore removal) in our model prevented occurrence of LBD during the first 60 d of aging. Overall, our findings provide a framework for predicting the occurrence of LBD in Gouda as well as other cheeses and illustrate the value of developing digital tools for managing dairy product quality.

Development of a Monte Carlo simulation model to predict pasteurized fluid milk spoilage due to post-pasteurization contamination with gram-negative bacteria.

Psychrotolerant gram-negative bacteria introduced as post-pasteurization contamination (PPC) are a major cause of spoilage and reduced shelf life of high-temperature, short-time pasteurized fluid milk. To provide improved tools to (1) predict pasteurized fluid milk shelf life as influenced by PPC and (2) assess the effectiveness of different potential interventions that could reduce spoilage due to PPC, we developed a Monte Carlo simulation model that predicts fluid milk spoilage due to psychrotolerant gram-negative bacteria introduced as PPC. As a first step, 17 gram-negative bacterial isolates frequently associated with fluid milk spoilage were selected and used to generate growth data in skim milk broth at 6°C. The resulting growth parameters, frequency of isolation for the 17 different isolates, and initial concentration of bacteria in milk with PPC, were used to develop a Monte Carlo model to predict bacterial number at different days of shelf life based on storage temperature of milk. This model was then validated with data from d 7 and 10 of shelf life, collected from commercial operations. The validated model predicted that the parameters (1) maximum growth rate and (2) storage temperature had the greatest influence on the percentage of containers exceeding 20,000 cfu/mL standard plate count on d 7 and 10 (i.e., spoiling due to PPC), which indicates that accurate data on maximum growth rate and storage temperature are important for accurate predictions. In addition to allowing for prediction of fluid milk shelf life, the model allows for simulation of "what-if" scenarios, which allowed us to predict the effectiveness of different interventions to reduce overall fluid milk spoilage due to PPC through a set of proof-of-concept scenario (e.g., frequency of PPC in containers reduced from 100% to 10%; limiting distribution temperature to a maximum of 6°C). Combined with other models, such as previous models on fluid milk spoilage due to psychrotolerant spore-forming bacteria, the data and tools developed here will allow for rational, digitally enabled, fluid milk shelf life prediction and quality enhancement.

Stress survival islet 1 contributes to serotype-specific differences in biofilm formation in Listeria monocytogenes.

Listeria monocytogenes has a significant impact on the food industry by forming biofilms on food-processing equipment. Tandem analysis of whole-genome sequencing data with biofilm data from 166 environmental and food-related L. monocytogenes isolates has revealed serotypic and genetic factors that strongly correlate with adherence and biofilm formation, such as lineage, plasmid harbourage, a three-codon deletion in inlA and the presence of the stress survival islet 1 (SSI-1). Strains from serotype 1/2b, the majority of which contained SSI-1, formed the strongest biofilms, while serotype 4b strains, the majority of which did not contain SSI-1, formed the weakest biofilms. When serotype 1/2a was separated by its SSI-1 genotype, SSI-1-positive 1/2a strains demonstrated significantly higher capacity for biofilm formation after 3 days of growth at 30°C (P < 0·0001). Together, these findings indicate that SSI-1 may contribute to serotype-associated differences in the biofilm-forming capacity in L. monocytogenes. SIGNIFICANCE AND IMPACT OF THE STUDY: Parallel analysis of whole-genome sequences and serotype-specific data was performed to identify genetic markers that correlate with increased adherence and biofilm formation in L. monocytogenes. The analyses revealed the hitherto unrecognized role of SSI-1 in biofilm formation, contributing to deeper understanding of genetic factors that influence behaviour of the species in the food processing environment..

Pseudomonas fluorescens group bacterial strains are responsible for repeat and sporadic postpasteurization contamination and reduced fluid milk shelf life.

Postpasteurization contamination (PPC) of high temperature, short time-pasteurized fluid milk by gram-negative (GN) bacteria continues to be an issue for processors. To improve PPC control, a better understanding of PPC patterns in dairy processing facilities over time and across equipment is needed. We thus collected samples from 10 fluid milk processing facilities to (1) detect and characterize PPC patterns over time, (2) determine the efficacy of different media to detect PPC, and (3) characterize sensory defects associated with PPC. Specifically, we collected 280 samples of high temperature, short time-pasteurized milk representing different products (2%, skim, and chocolate) and different fillers over 4 samplings performed over 11 mo at each of the 10 facilities. Standard plate count (SPC) as well as total GN, coliform, and Enterobacteriaceae (EB) counts were performed upon receipt and after 7, 10, 14, 17, and 21 d of storage at 6°C. We used 16S rDNA sequencing to characterize representative bacterial isolates from (1) test days with SPC >20,000 cfu/mL and (2) all samples with presumptive GN, coliforms, or EB. Day-21 samples were also evaluated by a trained defect judging panel. By d 21, 226 samples had SPC >20,000 cfu/mL on at least 1 d of shelf life; GN bacteria were found in 132 of these 226 samples, indicating PPC. Crystal violet tetrazolium agar detected PPC with the greatest sensitivity. Spoilage due to PPC was predominantly associated with Pseudomonas (isolated from 101 of the 132 samples with PPC); coliforms and EB were found in 27 and 37 samples with spoilage due to PPC, respectively. Detection of Pseudomonas and Acinetobacter was associated with lower flavor scores; coagulated, fruity fermented, and unclean defects were more prevalent in d-21 samples with PPC. Repeat isolation of Pseudomonas fluorescens group strains with identical partial 16S rDNA sequence types was observed in 8 facilities. In several facilities, specific lines, products, or processing days were linked to repeat product contamination with Pseudomonas with identical sequence types. Our data show that PPC due to Pseudomonas remains a major challenge for fluid milk processors; the inability of coliform and EB tests to detect Pseudomonas may contribute to this. Our data also provide important initial insights into PPC patterns (e.g., line-specific contamination), supporting the importance of molecular subtyping methods for identification of PPC sources.

Consensus categorization of cheese based on water activity and pH-A rational approach to systemizing cheese diversity.

Development of science-based interventions in raw milk cheese production is challenging due to the large diversity of production procedures and final products. Without an agreed upon categorization scheme, science-based food safety evaluations and validation of preventive controls would have to be completed separately on each individual cheese product, which is not feasible considering the large diversity of products and the typically small scale of production. Thus, a need exists to systematically group raw milk cheeses into logically agreed upon categories to be used for food safety evaluations. This paper proposes and outlines one such categorization scheme that provides for 30 general categories of cheese. As a base for this systematization and categorization of raw milk cheese, we used Table B of the US Food and Drug Administration's 2013 Food Code, which represents the interaction of pH and water activity for control of vegetative cells and spores in non-heat-treated food. Building on this table, we defined a set of more granular pH and water activity categories to better represent the pH and water activity range of different raw milk cheeses. The resulting categorization scheme was effectively validated using pH and water activity values determined for 273 different cheese samples collected in the marketplace throughout New York State, indicating the distribution of commercially available cheeses among the categories proposed here. This consensus categorization of cheese provides a foundation for a feasible approach to developing science-based solutions to assure compliance of the cheese processors with food safety regulations, such as those required by the US Food Safety Modernization Act. The key purpose of the cheese categorization proposed here is to facilitate product assessment for food safety risks and provide scientifically validated guidance on effective interventions for general cheese categories. Once preventive controls for a given category have been defined, these categories would represent safe havens for cheesemakers, which would allow cheesemakers to safely and legally produce raw milk cheeses that meet appropriate science-based safety requirements (e.g., risk to human health equivalent to pasteurized milk cheeses).

Coliform detection in cheese is associated with specific cheese characteristics, but no association was found with pathogen detection.

Coliform detection in finished products, including cheese, has traditionally been used to indicate whether a given product has been manufactured under unsanitary conditions. As our understanding of the diversity of coliforms has improved, it is necessary to assess whether coliforms are a good indicator organism and whether coliform detection in cheese is associated with the presence of pathogens. The objective of this study was (1) to evaluate cheese available on the market for presence of coliforms and key pathogens, and (2) to characterize the coliforms present to assess their likely sources and public health relevance. A total of 273 cheese samples were tested for presence of coliforms and for Salmonella, Staphylococcus aureus, Shiga toxin-producing Escherichia coli, Listeria monocytogenes, and other Listeria species. Among all tested cheese samples, 27% (75/273) tested positive for coliforms in concentrations >10cfu/g. Pasteurization, pH, water activity, milk type, and rind type were factors significantly associated with detection of coliforms in cheese; for example, a higher coliform prevalence was detected in raw milk cheeses (42% with >10cfu/g) compared with pasteurized milk cheese (21%). For cheese samples contaminated with coliforms, only water activity was significantly associated with coliform concentration. Coliforms isolated from cheese samples were classified into 13 different genera, including the environmental coliform genera Hafnia, Raoultella, and Serratia, which represent the 3 genera most frequently isolated across all cheeses. Escherichia, Hafnia, and Enterobacter were significantly more common among raw milk cheeses. Based on sequencing of the housekeeping gene clpX, most Escherichia isolates were confirmed as members of fecal commensal clades of E. coli. All cheese samples tested negative for Salmonella, Staph. aureus, and Shiga toxin-producing E. coli. Listeria spp. were found in 12 cheese samples, including 5 samples positive for L. monocytogenes. Although no association was found between coliform and Listeria spp. detection, Listeria spp. were significantly more likely to be detected in cheese with the washed type of rind. Our data provide information on specific risk factors for pathogen detection in cheese, which will facilitate development of risk-based strategies to control microbial food safety hazards in cheese, and suggest that generic coliform testing cannot be used to assess the safety of natural cheese.

Identification and characterization of psychrotolerant coliform bacteria isolated from pasteurized fluid milk.

The presence of coliform bacteria in pasteurized fluid milk typically indicates that product contamination occurred downstream of the pasteurizer, but it may also indicate pasteurization failure. Although coliform detection is frequently used as a hygiene indicator for dairy products, our understanding of the taxonomic and phenotypic coliform diversity associated with dairy products is surprisingly limited. Therefore, using Petrifilm Coliform Count plates (3M, St. Paul, MN), we isolated coliforms from high-temperature, short-time (HTST)-pasteurized fluid milk samples from 21 fluid milk processing plants in the northeast United States. Based on source information and initial characterization using partial 16S rDNA sequencing, 240 nonredundant isolates were obtained. The majority of these isolates were identified as belonging to the genera Enterobacter (42% of isolates), Hafnia (13%), Citrobacter (12%), Serratia (10%), and Raoultella (9%); additional isolates were classified into the genera Buttiauxella, Cedecea, Kluyvera, Leclercia, Pantoea, and Rahnella. A subset of 104 representative isolates was subsequently characterized phenotypically. Cold growth analysis in skim milk broth showed that all isolates displayed at least a 2-log increase over 10 d at 6°C; the majority of isolates (n=74) displayed more than a 5-log increase. In total, 43% of the representative isolates displayed lipolysis when incubated on spirit blue agar at 6°C for 14 d, whereas 71% of isolates displayed proteolysis when incubated on skim milk agar at 6°C for 14 d. Our data indicate that a considerable diversity of coliforms is found in HTST-pasteurized fluid milk and that a considerable proportion of these coliforms have phenotypic characteristics that will allow them to cause fluid milk spoilage.

A standard bacterial isolate set for research on contemporary dairy spoilage.

Food spoilage is an ongoing issue that could be dealt with more efficiently if some standardization and unification was introduced in this field of research. For example, research and development efforts to understand and reduce food spoilage can greatly be enhanced through availability and use of standardized isolate sets. To address this critical issue, we have assembled a standard isolate set of dairy spoilers and other selected nonpathogenic organisms frequently associated with dairy products. This publicly available bacterial set consists of (1) 35 gram-positive isolates including 9 Bacillus and 15 Paenibacillus isolates and (2) 16 gram-negative isolates including 4 Pseudomonas and 8 coliform isolates. The set includes isolates obtained from samples of pasteurized milk (n=43), pasteurized chocolate milk (n=1), raw milk (n=1), cheese (n=2), as well as isolates obtained from samples obtained from dairy-powder production (n=4). Analysis of growth characteristics in skim milk broth identified 16 gram-positive and 13 gram-negative isolates as psychrotolerant. Additional phenotypic characterization of isolates included testing for activity of ß-galactosidase and lipolytic and proteolytic enzymes. All groups of isolates included in the isolate set exhibited diversity in growth and enzyme activity. Source data for all isolates in this isolate set are publicly available in the FoodMicrobeTracker database (http://www.foodmicrobetracker.com), which allows for continuous updating of information and advancement of knowledge on dairy-spoilage representatives included in this isolate set. This isolate set along with publicly available isolate data provide a unique resource that will help advance knowledge of dairy-spoilage organisms as well as aid industry in development and validation of new control strategies.

Expression of nisin genes in cheese--a quantitative real-time polymerase chain reaction approach.

The role of bacteriocins in different environments has not been thoroughly explained, mainly because of the difficulties related to the detection of their production. Nisin, an antimicrobial peptide produced by Lactococcus lactis has a long history of safe use in food products and has been studied from many aspects of genetics, biosynthesis, immunity, regulation, and mode of action. Still, some aspects concerning the dynamics of nisin gene expression remain unknown, especially in complex media like cheese. The main objective of the present study was to quantify in a cheese-like medium the expression of nisin genes in L. lactis M78, a well-characterized nisin A producer isolated from raw milk. The expression of all 11 genes involved in nisin biosynthesis was evaluated during cheese production by real-time reverse transcription-PCR. Total RNA was extracted from cheeses using a direct extraction method without prior separation of microbial cells. The M78 strain grew well in experimental cheeses, producing detectable amounts of nisin after 4 h of fermentation. The presence of nisin as an activator modified both the expression of nisin genes and the accumulation of active nisin. Four groups could be distinguished based on gene expression as a function of time: nisA, nisFEG, nisRK and nisBTCIP. Based on nisin-producing strain growth, nisin activity, function of nisin genes, and their location, correlations were established that contribute to the explanation of regulation of nisin biosynthesis and immunity. This study is the first in which the evolution of bacteriocin gene transcripts has been quantified rigorously in a cheese-like medium.

Short communication: culture-independent detection of lactic Acid bacteria bacteriocin genes in two traditional slovenian raw milk cheeses and their microbial consortia.

Two Slovenian traditional raw milk cheeses, Tolminc (from cows' milk) and Kraski (from ewes' milk), were examined for the presence of 19 lactic acid bacteria bacteriocin genes by PCR analysis of total DNA extracts from 9 cheeses and from consortia of strains isolated from these cheeses. Eleven bacteriocin genes were detected in at least one cheese or consortium, or from both. Different cheeses or consortia contained 3 to 9 bacteriocin determinants. Plantaricin A gene determinants were found in all cheese and consortia DNA extracts. Genes for enterocins A, B, P, L50A, and L50B, and the bacteriocin cytolysin were commonly detected, as were genes for nisin. These results indicate that bacteriocinogenic strains of Lactobacillus, Enterococcus, and Lactococcus genera with protective potential are common members of indigenous microbiota of raw milk cheeses, which can be a good source of new protective strains.