Development and Validation of Pathogen Environmental Monitoring Programs for Small Cheese Processing Facilities

Utilizing whole genome sequencing to characterize Listeria spp. persistence and transmission patterns in a farmstead dairy processing facility and its associated farm environment

Farmstead dairy processing facilities may be particularly susceptible to Listeria spp. contamination due to the close physical proximity of their processing environments (PE) to associated dairy farm environments (FE). In this case study, we supported the implementation of interventions focused on improving (i) cleaning and sanitation efficacy, (ii) hygienic zoning, and (iii) sanitary equipment/facility design and maintenance in a farmstead dairy processing facility, and evaluated their impact on Listeria spp. detection in the farmstead's PE over 1 year. Detection of Listeria spp. in the farmstead's PE was numerically reduced from 50% to 7.5% after 1 year of intervention implementation, suggesting that these interventions were effective at improving Listeria spp. control. In addition, environmental samples were also collected from the farmstead's FE to evaluate the risk of the FE as a potential source of Listeria spp. in the PE. Overall, detection of Listeria spp. was higher in samples collected from the FE (75%, 27/36) compared with samples collected from the PE (24%, 29/120). Whole genome sequencing (WGS) performed on select isolates collected from the PE and FE supported the identification of 6 clusters (range of 3 to 15 isolates per cluster) that showed ≤ 50 high quality single nucleotide polymorphism (hqSNP) differences. Of these 6 clusters, 3 (i.e., clusters 2, 4, and 5) contained isolates that were collected from both the PE and FE, suggesting that transmission between these 2 environments was likely. Moreover, all cluster 2 isolates represented a clonal complex (CC) of L. monocytogenes commonly associated with dairy farm environmental reservoirs (i.e., CC666), which may support that the farmstead's FE represented an upstream source of the cluster 2 isolates that were found in the PE. Overall, our data underscore that, while the FE can represent a potential upstream source of Listeria spp. contamination in a farmstead dairy processing facility, implementation of targeted interventions can help effectively minimize Listeria spp. contamination in the PE.

Is the persistence of Listeria monocytogenes in food processing facilities and its resistance to pathogen intervention linked to its phylogeny?

The foodborne pathogen Listeria monocytogenes is differentiated into four distinct lineages which differ in their virulence. It remains unknown, however, whether the four lineages also differ with respect to their ability to persist in food processing facilities, their resistance to high pressure, a preservation method that is used commercially for Listeria control on ready-to-eat meats, and their ability to form biofilms. This study aimed to determine differences in the pressure resistance and biofilm formation of 59 isolates of L. monocytogenes representing lineages I and II. Furthermore, the genetic similarity of 9 isolates of L. monocytogenes that were obtained from a meat processing facility over a period of 1 year and of 20 isolates of L. monocytogenes from food processing facilities was analyzed to assess whether the ability of the lineages of L. monocytogenes to persist in these facilities differs. Analysis of 386 genomes with respect to the source of isolation revealed that genomes of lineage II are over-represented in meat isolates when compared with clinical isolates. Of the 38 strains of Lm. monocytogenes that persisted in food processing facilities (this study or published studies), 31 were assigned to lineage II. Isolates of lineage I were more resistant to treatments at 400 to 600 MPa. The thickness of biofilms did not differ between lineages. In conclusion, strains of lineage II are more likely to persist in food processing facilities while strains of lineage I are more resistant to high pressure.IMPORTANCEListeria monocytogenes substantially contributes to the mortality of foodborne disease in developed countries. The virulence of strains of four lineages of L. monocytogenes differs, indicating that risks associated with the presence of L. monocytogenes are lineage specific. Our study extends the current knowledge by documentation that the lineage-level phylogeny of L. monocytogenes plays a role in the source of isolation, in the persistence in food processing facilities, and in the resistance to pathogen intervention technologies. In short, the control of risks associated with the presence of L. monocytogenes in food is also lineage specific. Understanding the route of contamination L. monocytogenes is an important factor to consider when designing improved control measures.

Intensive Environmental Sampling and Whole Genome Sequence-based Characterization of Listeria in Small- and Medium-sized Dairy Facilities Reveal Opportunities for Simplified and Size-appropriate Environmental Monitoring Strategies

Small- and medium-sized dairy processing facilities (SMDFs) may face unique challenges with respect to controlling Listeria in their processing environments, e.g., due to limited resources. The aim of this study was to implement and evaluate environmental monitoring programs (EMPs) for Listeria control in eight SMDFs in a ∼1-year longitudinal study; this included a comparison of pre-operation (i.e., after cleaning and sanitation and prior to production) and mid-operation (i.e., at least 4 h into production) sampling strategies. Among 2,072 environmental sponge samples collected across all facilities, 272 (13%) were positive for Listeria. Listeria prevalence among pre- and mid-operation samples (15% and 17%, respectively), was not significantly different. Whole genome sequencing (WGS) performed on select isolates to characterize Listeria persistence patterns revealed repeated isolation of closely related Listeria isolates (i.e., ≤20 high-quality single nucleotide polymorphism [hqSNP] differences) in 5/8 facilities over >6 months, suggesting Listeria persistence and/or reintroduction was relatively common among the SMDFs evaluated here. WGS furthermore showed that for 41 sites where samples collected pre- and mid-operation were positive for Listeria, Listeria isolates obtained were highly related (i.e., ≤10 hqSNP differences), suggesting that pre-operation sampling alone may be sufficient and more effective for detecting sites of Listeria persistence. Importantly, our data also showed that only 1/8 of facilities showed a significant decrease in Listeria prevalence over 1 year, indicating continued challenges with Listeria control in at least some SMDFs. We conclude that options for simplified Listeria EMPs (e.g., with a focus on pre-operation sampling, which allows for more rapid identification of likely persistence sites) may be valuable for improved Listeria control in SMDFs.

Context matters: environmental microbiota from ice cream processing facilities affected the inhibitory performance of two lactic acid bacteria strains against Listeria monocytogenes

IMPORTANCE

Antilisterial LAB strains have been proposed as biological control agents for application in food processing environments. However, the effect of resident food processing environment microbiota on the performance on antilisterial LAB strains is poorly understood. Our study shows that the presence of microbiota collected from ice cream processing facilities' environmental surfaces can affect the attachment and inhibitory effect of LAB strains against L. monocytogenes. Further studies are therefore needed to assess whether individual microbial taxa affect antilisterial properties of LAB strains and to characterize the underlying mechanisms.

A Critical Review of Risk Assessment Models for Listeria monocytogenes in Dairy Products

A review of the published quantitative risk assessment (QRA) models of L. monocytogenes in dairy products was undertaken in order to identify and appraise the relative effectiveness of control measures and intervention strategies implemented at primary production, processing, retail, and consumer practices. A systematic literature search retrieved 18 QRA models, most of them (9) investigated raw and pasteurized milk cheeses, with the majority covering long supply chains (4 farm-to-table and 3 processing-to-table scopes). On-farm contamination sources, either from shedding animals or from the broad environment, have been demonstrated by different QRA models to impact the risk of listeriosis, in particular for raw milk cheeses. Through scenarios and sensitivity analysis, QRA models demonstrated the importance of the modeled growth rate and lag phase duration and showed that the risk contribution of consumers' practices is greater than in retail conditions. Storage temperature was proven to be more determinant of the final risk than storage time. Despite the pathogen's known ability to reside in damp spots or niches, re-contamination and/or cross-contamination were modeled in only two QRA studies. Future QRA models in dairy products should entail the full farm-to-table scope, should represent cross-contamination and the use of novel technologies, and should estimate L. monocytogenes growth more accurately by means of better-informed kinetic parameters and realistic time-temperature trajectories.

Recent Advances in Microfluidics-Based Electrochemical Sensors for Foodborne Pathogen Detection

Using pathogen-infected food that can be unhygienic can result in severe diseases and an increase in mortality rate among humans. This may arise as a serious emergency problem if not appropriately restricted at this point of time. Thus, food science researchers are concerned with precaution, prevention, perception, and immunity to pathogenic bacteria. Expensive, elongated assessment time and the need for skilled personnel are some of the shortcomings of the existing conventional methods. Developing and investigating a rapid, low-cost, handy, miniature, and effective detection technology for pathogens is indispensable. In recent times, there has been a significant scope of interest for microfluidics-based three-electrode potentiostat sensing platforms, which have been extensively used for sustainable food safety exploration because of their progressively high selectivity and sensitivity. Meticulously, scholars have made noteworthy revolutions in signal enrichment tactics, measurable devices, and portable tools, which can be used as an allusion to food safety investigation. Additionally, a device for this purpose must incorporate simplistic working conditions, automation, and miniaturization. In order to meet the critical needs of food safety for on-site detection of pathogens, point-of-care testing (POCT) has to be introduced and integrated with microfluidic technology and electrochemical biosensors. This review critically discusses the recent literature, classification, difficulties, applications, and future directions of microfluidics-based electrochemical sensors for screening and detecting foodborne pathogens.

Whole-Genome Sequencing-Based Characterization of Listeria Isolates from Produce Packinghouses and Fresh-Cut Facilities Suggests Both Persistence and Reintroduction of Fully Virulent L. monocytogenes

The contamination of ready-to-eat produce with Listeria monocytogenes (LM) can often be traced back to environmental sources in processing facilities and packinghouses. To provide an improved understanding of Listeria sources and transmission in produce operations, we performed whole-genome sequencing (WGS) of LM (n = 169) and other Listeria spp. (n = 107) obtained from 13 produce packinghouses and three fresh-cut produce facilities. Overall, a low proportion of LM isolates (9/169) had inlA premature stop codons, and a large proportion (83/169) had either or both of the LIPI-3 or LIPI-4 operons, which have been associated with hypervirulence. The further analysis of the WGS data by operation showed a reisolation (at least 2 months apart) of highly related isolates (<10 hqSNP differences) in 7/16 operations. Two operations had highly related strains reisolated from samples that were collected at least 1 year apart. The identification of isolates collected during preproduction (i.e., following sanitation but before the start of production) that were highly related to isolates collected during production (i.e., after people or products have entered and begun moving through the operation) provided evidence that some strains were able to survive standard sanitation practices. The identification of closely related isolates (<20 hqSNPs differences) in different operations suggests that cross-contamination between facilities or introductions from common suppliers may also contribute to Listeria transmission. Overall, our data suggest that the majority of LM isolates collected from produce operations are fully virulent and that both persistence and reintroduction may lead to the repeat isolation of closely related Listeria in produce operations.

IMPORTANCEListeria monocytogenes is of particular concern to the produce industry due to its frequent presence in natural environments as well as its ability to survive in packinghouses and fresh-cut processing facilities over time. The use of whole-genome sequencing, which provides high discriminatory power for the characterization of Listeria isolates, along with detailed source data (isolation date and sample location) shows that the presence of Listeria in produce operations appears to be due to random and continued reintroduction as well as to the persistence of highly related strains in both packinghouses and fresh-cut facilities. These findings indicate the importance of using high-resolution characterization approaches for root cause analyses of Listeria contamination issues. In cases of repeat isolation of closely related Listeria in a given facility, both persistence and reintroduction need to be considered as possible root causes.

Biosensors and Microfluidic Biosensors: From Fabrication to Application

Biosensors are ubiquitous in a variety of disciplines, such as biochemical, electrochemical, agricultural, and biomedical areas. They can integrate various point-of-care applications, such as in the food, healthcare, environmental monitoring, water quality, forensics, drug development, and biological domains. Multiple strategies have been employed to develop and fabricate miniaturized biosensors, including design, optimization, characterization, and testing. In view of their interactions with high-affinity biomolecules, they find application in the sensitive detection of analytes, even in small sample volumes. Among the many developed techniques, microfluidics have been widely explored; these use fluid mechanics to operate miniaturized biosensors. The currently used commercial devices are bulky, slow in operation, expensive, and require human intervention; thus, it is difficult to automate, integrate, and miniaturize the existing conventional devices for multi-faceted applications. Microfluidic biosensors have the advantages of mobility, operational transparency, controllability, and stability with a small reaction volume for sensing. This review addresses biosensor technologies, including the design, classification, advances, and challenges in microfluidic-based biosensors. The value chain for developing miniaturized microfluidic-based biosensor devices is critically discussed, including fabrication and other associated protocols for application in various point-of-care testing applications.

Using agent-based modeling to compare corrective actions for Listeria contamination in produce packinghouses

The complex environment of a produce packinghouse can facilitate the spread of pathogens such as Listeria monocytogenes in unexpected ways. This can lead to finished product contamination and potential foodborne disease cases. There is a need for simulation-based decision support tools that can test different corrective actions and are able to account for a facility’s interior cross-contamination dynamics. Thus, we developed agent-based models of Listeria contamination dynamics for two produce packinghouse facilities; agents in the models represented equipment surfaces and employees, and models were parameterized using observations, values from published literature and expert opinion. Once validated with historical data from Listeria environmental sampling, each model’s baseline conditions were investigated and used to determine the effectiveness of corrective actions in reducing prevalence of agents contaminated with Listeria and concentration of Listeria on contaminated agents. Evaluated corrective actions included reducing incoming Listeria, modifying cleaning and sanitation strategies, and reducing transmission pathways, and combinations thereof. Analysis of Listeria contamination predictions revealed differences between the facilities despite their functional similarities, highlighting that one-size-fits-all approaches may not always be the most effective means for selection of corrective actions in fresh produce packinghouses. Corrective actions targeting Listeria introduced in the facility on raw materials, implementing risk-based cleaning and sanitation, and modifying equipment connectivity were shown to be most effective in reducing Listeria contamination prevalence. Overall, our results suggest that a well-designed cleaning and sanitation schedule, coupled with good manufacturing practices can be effective in controlling contamination, even if incoming Listeria spp. on raw materials cannot be reduced. The presence of water within specific areas was also shown to influence corrective action performance. Our findings support that agent-based models can serve as effective decision support tools in identifying Listeria-specific vulnerabilities within individual packinghouses and hence may help reduce risks of food contamination and potential human exposure.

In Silico Models for Design and Optimization of Science-Based Listeria Environmental Monitoring Programs in Fresh-Cut Produce Facilities

Food facilities need time- and cost-saving methods during the development and optimization of environmental monitoring for pathogens and their surrogates. Rapid virtual experimentation through in silico modeling can alleviate the need for extensive real-world, trial-and-error style program design. Two agent-based models of fresh-cut produce facilities were developed as a way to simulate the dynamics of Listeria in the built environment by modeling the different surfaces of equipment and employees in a facility as agents. Five sampling schemes at three time points were evaluated in silico on their ability to locate the presence of Listeria contamination in a facility with sample sites for each scheme (i.e., scenario, as modeled using scenario analysis) based on the following: the facilities' current environmental monitoring program (scenario 1), Food and Drug Administration recommendations (scenario 2), random selection (scenario 3), sites exclusively from zone 3 (i.e., sites in the production room but not directly adjacent to food contact surfaces) (scenario 4), or model prediction of elevated risk of contamination (scenario 5). Variation was observed between the scenarios on how well the Listeria prevalence of the virtually collected samples reflected the true prevalence of contaminated agents in the modeled operation. The zone 3 only (scenario 4) and model-based (scenario 5) sampling scenarios consistently overestimated true prevalence across time, suggesting that those scenarios could provide a more sensitive approach for determining if Listeria is present in the operation. The random sampling scenario (scenario 3) may be more useful for operations looking for a scheme that is most likely to reflect the true prevalence. Overall, the developed models allow for rapid virtual experimentation and evaluation of sampling schemes specific to unique fresh-cut produce facilities. IMPORTANCE Programs such as environmental monitoring are used to determine the state of a given food facility with regard to the presence of environmental pathogens, such as Listeria monocytogenes, that could potentially cross-contaminate food product. However, the design of environmental monitoring programs is complex, and there are infinite ways to conduct the sampling that is required for these programs. Experimentally evaluating sampling schemes in a food facility is time-consuming, costly, and nearly impossible. Therefore, the food industry needs science-based tools to aid in developing and refining sampling plans that reduce the risk of harboring contamination. Two agent-based models of two fresh-cut produce facilities reported here demonstrate a novel way to evaluate how different sampling schemes can be rapidly evaluated across multiple time points as a way to understand how sampling can be optimized in an effort to locate the presence of Listeria in a food facility.

Monitoring by a Sensitive Liquid-Based Sampling Strategy Reveals a Considerable Reduction of Listeria monocytogenes in Smeared Cheese Production over 10 Years of Testing in Austria

Most Austrian dairies and cheese manufacturers participated in a Listeria monitoring program, which was established after the first reports of dairy product-associated listeriosis outbreaks more than thirty years ago. Within the Listeria monitoring program, up to 800 mL of product-associated liquids such as cheese smear or brine are processed in a semi-quantitative approach to increase epidemiological sensitivity. A sampling strategy within cheese production, which detects environmental contamination before it results in problematic food contamination, has benefits for food safety management. The liquid-based sampling strategy was implemented by both industrial cheese makers and small-scale dairies located in the mountainous region of Western Austria. This report considers more than 12,000 Listeria spp. examinations of liquid-based samples in the 2009 to 2018 timeframe. Overall, the occurrence of L. monocytogenes in smear liquid samples was 1.29% and 1.55% (n = 5043 and n = 7194 tested samples) for small and industrial cheese enterprises, respectively. The liquid-based sampling strategy for Listeria monitoring at the plant level appears to be superior to solid surface monitoring. Cheese smear liquids seem to have good utility as an index of the contamination of cheese up to that point in production. A modelling or validation process should be performed for the new semi-quantitative approach to estimate the true impact of the method in terms of reducing Listeria contamination at the cheese plant level.

Identification of Closely Related Listeria monocytogenes Isolates with No Apparent Evidence for a Common Source or Location: A Retrospective Whole Genome Sequencing Analysis

ABSTRACT

Public health and regulatory agencies worldwide sequence all Listeria monocytogenes isolates obtained as part of routine surveillance and outbreak investigations. Many of these entities submit the sequences to the National Center for Biotechnology Information Pathogen Detection (NCBI PD) database, which groups the L. monocytogenes isolates into single nucleotide polymorphism (SNP) clusters based on a pairwise SNP difference threshold of 50 SNPs. Our goal was to assess whether isolates with metadata that suggest different sources or locations could show evidence for close genetic relatedness indicating a recent common ancestor and a possible unknown common source. We compared the whole genome sequencing (WGS) data of 249 L. monocytogenes isolates sequenced here, which have detailed metadata, with WGS data of nonclinical isolates on NCBI PD. The 249 L. monocytogenes isolates originated from natural environments (n = 91) as well as from smoked fish (n = 62), dairy (n = 56), and deli meat (n = 40) operations in the United States. Using a combination of subtyping by core genome multilocus sequence typing and high-quality SNP, we observed five SNP clusters in which study isolates and SNP cluster isolates seemed to be closely related and either (i) shared the same geolocation but showed different source types (one SNP cluster); (ii) shared the same source type but showed different geolocations (two SNP clusters); or (iii) shared neither source type nor geolocation (two SNP clusters). For one of the two clusters under (iii), there was, however, no strong bootstrap support for a common ancestor shared between the study isolates and SNP cluster isolates, indicating the value of in-depth evolutionary analyses when WGS data are used for traceback and epidemiological investigations. Overall, our results demonstrate that some L. monocytogenes subtypes may be associated with specific locations or commodities; these associations can help in investigations involving multi-ingredient foods such as sandwiches. However, at least some L. monocytogenes subtypes can be widespread geographically and can be associated with different sources, which may present a challenge to traceback investigations involving these subtypes.

HIGHLIGHTS

Listeria environmental sampling tests are compatible with polymorphic locus sequence typing

Food processors invest significant resources into environmental sampling to detect contamination with potential pathogens, particularly Listeria monocytogenes. To facilitate these efforts, multiple environmental sampling tests (ESTs) have been developed and commercialized that minimize workload, turnaround time, and cost while providing convenient colorimetric detection. For presumptive-positive ESTs, we hypothesized that a relatively minor additional investment could provide, in addition to species confirmation, valuable strain typing data for tracking pathogen spread through a facility, identifying harborage sites, and distinguishing sporadic from persistent or resident contaminants. This hypothesis is based on the demonstrated compatibility of polymorphic locus sequence typing (PLST) with crude samples including food enrichments. Five Listeria ESTs were tested here: broth-based InSite (Hygiena), Path-Chek (Mericon), and Pathfinder (Hardy Diagnositics); and gel-based Petrifilm (3M) and HardyChrom (Hardy Diagnostics). ESTs were inoculated with strains representing two common L. monocytogenes serotypes and nonpathogenic Listeria innocua. Following incubation, broths or suspended colonies were heat treated to inactivate bacteria. Lysates or purified DNAs were prepared and used as templates in PCRs targeting the previously described PLST loci LmiMT1 and LisMT2. Single clear products were obtained from all inoculated ESTs; uninoculated controls were negative. PCR products were subjected to Sanger sequencing, yielding high-quality chromatograms. Phylogenetic analysis confirmed identities to previously determined sequences and revealed relatedness to serotype-matched strains represented in GenBank databases. PRACTICAL APPLICATION: Multiple environmental sampling tests have been commercialized in recent years to facilitate the proactive detection of pathogens, particularly Listeria monocytogenes, within food processing facilities. Coupling a positive detection test with strain typing would enhance its value by providing data that can be used to track pathogen spread through a facility, identify harborage sites, and distinguish sporadic from resident contamination.

Detection and Prevalence of Listeria in U.S. Produce Packinghouses and Fresh-Cut Facilities

ABSTRACT

Listeria monocytogenes (LM) contamination of produce can often be traced back to the environment of packinghouses and fresh-cut facilities. Because there is limited information on the detection, prevalence, and distribution of this pathogen in produce operations, environmental "routine sampling" plans for LM and other Listeria spp. were developed and implemented in three packinghouses and five fresh-cut facilities in the United States. For routine sampling, a total of 2,014 sponge samples were collected over six to eight separate samplings per operation, performed over 1 year; vector and preproduction samples (n = 156) were also collected as needed to follow up on positive findings. In addition, a single "validation sampling" visit by an outside expert was used to evaluate the routine sampling. Among the 2,014 routine sponge samples collected, 35 and 30 were positive for LM and Listeria species other than LM (LS), respectively. LM prevalence varied from 0.8 to 5.8% for packinghouses and <0.4 to 1.6% for fresh-cut facilities. Among the 394 validation sponge samples, 23 and 13 were positive for LM and LS, respectively. Validation sampling found statistically significantly higher LM prevalence compared with routine sampling for three of eight operations. For all samples collected, up to eight isolates per sample were characterized by sequencing of sigB, which allowed for classification into sigB allelic types. Among the 97 samples with more than one Listeria isolate characterized, 28 had more than one sigB allelic type present, including 18 sponges that were positive for LM and another Listeria species and 13 sponges that were positive for more than one LM subtype. This indicates that collection of multiple isolates is necessary to capture Listeria diversity present in produce operations. Additionally, 17 of 77 sponges that were positive for LM were positive at only one enrichment time (i.e., 24 or 48 h), indicating that LM testing after two different enrichment times provides enhanced sensitivity.

HIGHLIGHTS

Tracing Listeria monocytogenes contamination in artisanal cheese to the processing environments in cheese producers in southern Chile

Artisanal cheese from southern Chile is made primarily by rural families who raise dairy cows and produce cheese as a way to add value to their milk. The most common cheese produced is chanco, a semi-hard cheese that is typically sold in unauthorized markets. The methods of chanco production do not always follow good manufacturing practices; however, the presence of Listeria monocytogenes contamination in this cheese has not been previously documented. To better understand production practices and L. monocytogenes contamination, 39 cheese producers were surveyed with regard to infrastructure, cleaning and sanitation, pest control, personal hygiene, training, raw materials, and manufacturing. During four sampling trips in 2016 (March, May, August, and November), 546 samples were collected (468 cheese samples and 78 milk samples). For producers that tested positive for L. monocytogenes, environmental monitoring was also conducted, for which 130 additional samples were collected. Presumptive L. monocytogenes isolates (N = 94) were further characterized and subtyped using standard techniques and qPCR-based species/subtype verification; a subset of 52 isolates were also subtyped by Pulsed Field Gel Electrophoresis (PFGE). L. monocytogenes was found in 19 cheeses (4.1%) from five producers (12.8%). The most frequent serotypes were 1/2b (48.9%), group 4B (4b, 4d, 4e) (45.7%), and serotype 1/2a (5.4%). Although no milk samples tested positive for L. monocytogenes, all cheese samples from two producers tested positive during two of the samplings. Distinct PFGE types were recovered from each facility, demonstrating persistence of certain subtypes of the pathogen that ultimately caused end-product contamination. Environmental monitoring of the five positive producers revealed a prevalence of L. monocytogenes ranging from 0 to 30%, with food contact surfaces having the highest incidence of this organism. The findings of this study contribute to the understanding of L. monocytogenes incidence in artisanal cheese in the region of southern Chile.

Evaluating Environmental Monitoring Protocols for Listeria spp. and Listeria monocytogenes in Frozen Food Manufacturing Facilities

Food processors face serious challenges due to Listeria monocytogenes contamination. Environmental monitoring is used to control L. monocytogenes from the processing environment. Although frozen foods do not support the growth of L. monocytogenes, the moist and cold conditions in frozen food production environments are favorable for growth of L. monocytogenes. The purpose of the study was to determine the current state of awareness and practices applied across a variety of frozen food facilities related to environmental monitoring for Listeria. A survey tool was created to elicit information on existing environmental monitoring programs within the frozen food industry. The topics included cleaning and sanitizing applications and frequency, microbiological testing, and environmental areas of concern. The survey was reviewed by academic and industry experts with knowledge of microbiology and frozen food processing and was field tested by industry personnel with extensive knowledge of environmental monitoring. The survey was distributed and analyzed electronically via Qualtrics among 150 frozen food contacts. Data were gathered anonymously with a response rate of 31% (n = 46). The survey indicated that facilities are more likely to test for Listeria spp. in environmental monitoring zones 2 to 4 (nonfood contact areas) on a weekly basis. The major areas of concern in facilities for finding Listeria-positive results are floors, walls, and drains. At the time of the survey, few facilities incorporated active raw material and finished product testing for Listeria; instead, programs emphasized the need to identify presence of Listeria in the processing environment and mitigate potential for product contamination. Recognition of environmental monitoring as a key component of a comprehensive food safety plan was evident, along with an industry focus to further improve and develop verification programs to reduce prevalence of L. monocytogenes in frozen food processing environments.

Predictive Modeling of Microbial Behavior in Food

Microorganisms can contaminate food, thus causing food spoilage and health risks when the food is consumed. Foods are not sterile; they have a natural flora and a transient flora reflecting their environment. To ensure food is safe, we must destroy these microorganisms or prevent their growth. Recurring hazards due to lapses in the handling, processing, and distribution of foods cannot be solved by obsolete methods and inadequate proposals. They require positive approach and resolution through the pooling of accumulated knowledge. As the industrial domain evolves rapidly and we are faced with pressures to continually improve both products and processes, a considerable competitive advantage can be gained by the introduction of predictive modeling in the food industry. Research and development capital concerns of the industry have been preserved by investigating the plethora of factors able to react on the final product. The presence of microorganisms in foods is critical for the quality of the food. However, microbial behavior is closely related to the properties of food itself such as water activity, pH, storage conditions, temperature, and relative humidity. The effect of these factors together contributing to permitting growth of microorganisms in foods can be predicted by mathematical modeling issued from quantitative studies on microbial populations. The use of predictive models permits us to evaluate shifts in microbial numbers in foods from harvesting to production, thus having a permanent and objective evaluation of the involving parameters. In this vein, predictive microbiology is the study of the microbial behavior in relation to certain environmental conditions, which assure food quality and safety. Microbial responses are evaluated through developed mathematical models, which must be validated for the specific case. As a result, predictive microbiology modeling is a useful tool to be applied for quantitative risk assessment. Herein, we review the predictive models that have been adapted for improvement of the food industry chain through a built virtual prototype of the final product or a process reflecting real-world conditions. It is then expected that predictive models are, nowadays, a useful and valuable tool in research as well as in industrial food conservation processes.

Design Elements of Listeria Environmental Monitoring Programs in Food Processing Facilities: A Scoping Review of Research and Guidance Materials

Occurrence of Listeria monocytogenes (Lm), the causative agent of listeriosis, in food processing facilities presents considerable challenges to food producers and food safety authorities. Design of an effective, risk-based environmental monitoring (EM) program is essential for finding and eliminating Lm from the processing environment to prevent product contamination. A scoping review was conducted to collate and synthesize available research and guidance materials on Listeria EM in food processing facilities. An exhaustive search was performed to identify all available research, industry and regulatory documents, and search results were screened for relevance based on eligibility criteria. After screening, 198 references were subjected to an in-depth review and categorized according to objectives for conducting Listeria sampling in food processing facilities and food sector. Mapping of the literature revealed research and guidance gaps by food sector, as fresh produce was the focus in only 10 references, compared to 72 on meat, 52 on fish and seafood, and 50 on dairy. Review of reported practices and guidance highlighted key design elements of EM, including the number, location, timing and frequency of sampling, as well as methods of detection and confirmation, and record-keeping. While utilization of molecular subtyping methods is a trend that will continue to advance understanding of Listeria contamination risks, improved study design and reporting standards by researchers will be essential to assist the food industry optimize their EM design and decision-making. The comprehensive collection of documents identified and synthesized in this review aids continued efforts to minimize the risk of Lm contaminated foods.

Diversity of Listeria monocytogenes strains isolated from Agaricus bisporus mushroom production

AIMS

The aims of this study were to characterize the genetic diversity of Listeria monocytogenes isolates obtained from commercial mushroom production, to establish the persistence, recontamination and the risk of cross-contamination from the working environment to the final products, creating awareness about the presence of L. monocytogenes thus helping to prevent the possibility of cross-contamination.

METHODS AND RESULTS

From an extensive analysis of commercial mushroom production, analysed with BS EN ISO 11290-1:1996/Amd 1:2004 and BS EN ISO 11290-2:1998/Amd 1:2004, 279 L. monocytogenes isolates were obtained. All of the isolates were characterized by pulsed-field gel electrophoresis, species PCR and serogroup PCR. All the isolates were confirmed as L. monocytogenes; 30·1% were serogroup 1/2b-3b-7, 40·8% were serogroup 1/2a-3a and 29·1% were serogroup 4b-4d-4e. There were 77 pulsotypes from the 279 isolates, 40 of the pulsotypes had only one strain and 37 had two or more strains, indicating great diversity in the isolates.

CONCLUSIONS

The high genetic diversity is indicative of the fact that current hygiene practices are successful at removing L. monocytogenes but that recontamination of the production environment is frequent.

SIGNIFICANCE AND IMPACT OF THE STUDY

The results obtained are very valuable in creating awareness of L. monocytogenes in mushroom production and for the improvement of hygiene practices.

Listeria monocytogenes in Foods

Listeria monocytogenes causes listeriosis, a rare foodborne disease with a mortality rate of 20%-30%. The elderly and immunocompromised are particularly susceptible to listeriosis. L. monocytogenes is ubiquitous in nature and can contaminate food-processing environments, posing a threat to the food chain. This is particularly important for ready-to-eat foods as there is no heat treatment or other antimicrobial step between production and consumption. Thus, occurrence and control of L. monocytogenes are important for industry and public health. Advances in whole-genome sequence technology are facilitating the investigation of disease outbreaks, linking sporadic cases to outbreaks, and linking outbreaks internationally. Novel control methods, such as bacteriophage and bacteriocins, can contribute to a reduction in the occurrence of L. monocytogenes in the food-processing environment, thereby reducing the risk of food contamination and contributing to a reduction in public health issues.