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

Phage-derived proteins: Advancing food safety through biocontrol and detection of foodborne pathogens

The emergence of antimicrobial-resistant foodborne pathogens poses a continuous health risk and economic burden as they can easily spread through contaminated food. Therefore, the demand for new antimicrobial agents to address this problem is steadily increasing. Similarly, the development of rapid, sensitive, and accurate pathogen detection tools is a prerequisite for ensuring food safety. Phage-derived proteins have become innovative tools for combating these pathogens because of their potent antimicrobial activity and host specificity. Phage proteins are relatively free from regulation compared to phages per se, and there are no concerns about the transduction of harmful genes. With recent progress in next-generation sequencing technology, the analysis of phage genomes has become more accessible, and numerous phage proteins with potential for biocontrol and detection have been identified. This review provides a comprehensive overview of phage protein research on food safety from 2006 to the present, a pivotal period marked by the certification of phages as Generally Recognized As Safe (GRAS). Emphasizing recent advancements, we investigated the diverse applications of various phage proteins for biocontrol and detection purposes. While highlighting the successful implementation of these proteins, we also address the current bottlenecks and propose strategies to overcome these challenges. By summarizing the current state of research on phage-derived proteins, this review contributes to a deeper understanding of their potential as effective antimicrobial agents and tools for detecting foodborne pathogens.

Training in quantitative microbial risk assessment of Listeria monocytogenes in processing chains: Quantification of biofilm-cells transfer integrating virulence and persistence factors

Food safety is a global challenge, with nearly 1 in 10 people worldwide falling ill each year from consuming contaminated food. The risk is particularly high in ready-to-eat (RTE) products, which are consumed without further cooking to eliminate harmful microorganisms. To address this, the University of Cordoba and the University of Bologna, in the framework of the EU-FORA programme, developed a training programme focused on quantitative microbial risk assessment (QMRA) for Listeria monocytogenes in RTE food processing chains, a significant public health concern due to its association with severe foodborne illnesses. The programme aimed to train the fellow in advanced food microbiology techniques, predictive modelling and comprehensive QMRA methodologies. The fellow gained hands-on experience with predictive microbiology models applied to real-world scenarios, particularly RTE meat and fish products. Activities included developing predictive models for microbial growth and conducting challenge tests to evaluate Listeria behaviour in various foods. Emphasising data collection and statistical analysis, the fellowship explores the dynamics of Listeria within the food supply chain. A case study on sliced cooked ham demonstrates QMRA's application, using Monte Carlo simulations to estimate Listeria concentrations at consumption, ultimately informing risk management strategies. This initiative aimed to increase the number of food safety risk assessment experts in Europe, thereby enhancing public health outcomes related to foodborne diseases.

Innovative Strategies in Drug Repurposing to Tackle Intracellular Bacterial Pathogens

Intracellular bacterial pathogens pose significant public health challenges due to their ability to evade immune defenses and conventional antibiotics. Drug repurposing has recently been explored as a strategy to discover new therapeutic uses for established drugs to combat these infections. Utilizing high-throughput screening, bioinformatics, and systems biology, several existing drugs have been identified with potential efficacy against intracellular bacteria. For instance, neuroleptic agents like thioridazine and antipsychotic drugs such as chlorpromazine have shown effectiveness against Staphylococcus aureus and Listeria monocytogenes. Furthermore, anticancer drugs including tamoxifen and imatinib have been repurposed to induce autophagy and inhibit bacterial growth within host cells. Statins and anti-inflammatory drugs have also demonstrated the ability to enhance host immune responses against Mycobacterium tuberculosis. The review highlights the complex mechanisms these pathogens use to resist conventional treatments, showcases successful examples of drug repurposing, and discusses the methodologies used to identify and validate these drugs. Overall, drug repurposing offers a promising approach for developing new treatments for bacterial infections, addressing the urgent need for effective antimicrobial therapies.

Prevalence of Listeria monocytogenes in Milk and Dairy Product Supply Chains: A Global Systematic Review and Meta-analysis

Listeria monocytogenes, one of the main foodborne pathogens, is commonly found in milk and dairy products. This study aimed to estimate the presence of L. monocytogenes in milk and dairy product supply chains using a meta-analysis based on PubMed, Embase, Web of Science, and Scopus databases. A total of 173 studies were included in this meta-analysis. The pooled prevalence in the supply chain environment was 8.69% (95% confidence interval [CI]: 5.30%-12.78%), which was higher than that in dairy products (4.60%, 95% CI: 1.72%-8.60%) and milk products (2.93%, 95% CI: 2.14%-3.82%). Subgroup analysis showed that L. monocytogenes prevalence in raw milk (3.44%, 95% CI: 2.61%-4.28%) was significantly higher than in pasteurized milk (0.60%, 95% CI: 0.00%-2.06%). The highest prevalence of L. monocytogenes in milk and dairy products was observed in North America (5.27%, 95% CI: 2.19%-8.35%) and South America (13.54%, 95% CI: 3.71%-23.37%). In addition, studies using culture and molecular methods (5.17%, 95% CI: 2.29%-8.06%) had higher prevalence than other detection methods. Serogroup 1/2a and 3a (45.34%, 95% CI: 28.74%-62.37%), serogroup 1/2b and 3b (14.23%, 95% CI: 6.05%-24.24%), and serogroup 4b/4e (13.71%, 95% CI: 6.18%-22.83%) were dominant in these studies. The results of this study provide a better understanding of the prevalence of L. monocytogenes in milk and dairy product supply chains and suggest a potential foodborne pathogen burden.

A Critical Review of Risk Assessment Models for Listeria monocytogenes in Produce

A review of quantitative risk assessment (QRA) models of Listeria monocytogenes in produce was carried out, with the objective of appraising and contrasting the effectiveness of the control strategies placed along the food chains. Despite nine of the thirteen QRA models recovered being focused on fresh or RTE leafy greens, none of them represented important factors or sources of contamination in the primary production, such as the type of cultivation, water, fertilisers or irrigation method/practices. Cross-contamination at processing and during consumer's handling was modelled using transfer rates, which were shown to moderately drive the final risk of listeriosis, therefore highlighting the importance of accurately representing the transfer coefficient parameters. Many QRA models coincided in the fact that temperature fluctuations at retail or temperature abuse at home were key factors contributing to increasing the risk of listeriosis. In addition to a primary module that could help assess current on-farm practices and potential control measures, future QRA models for minimally processed produce should also contain a refined sanitisation module able to estimate the effectiveness of various sanitisers as a function of type, concentration and exposure time. Finally, L. monocytogenes growth in the products down the supply chain should be estimated by using realistic time-temperature trajectories, and validated microbial kinetic parameters, both of them currently available in the literature.

A Critical Review of Risk Assessment Models for Listeria monocytogenes in Seafood

Invasive listeriosis, due to its severe nature in susceptible populations, has been the focus of many quantitative risk assessment (QRA) models aiming to provide a valuable guide in future risk management efforts. A review of the published QRA models of Listeria monocytogenes in seafood was performed, with the objective of appraising the effectiveness of the control strategies at different points along the food chain. It is worth noting, however, that the outcomes of a QRA model are context-specific, and influenced by the country and target population, the assumptions that are employed, and the model architecture itself. Studies containing QRA models were retrieved through a literature search using properly connected keywords on Scopus and PubMed®. All 13 QRA models that were recovered were of short scope, covering, at most, the period from the end of processing to consumption; the majority (85%) focused on smoked or gravad fish. Since the modelled pathways commenced with the packaged product, none of the QRA models addressed cross-contamination events. Many models agreed that keeping the product's temperature at 4.0-4.5 °C leads to greater reductions in the final risk of listeriosis than reducing the shelf life by one week and that the effectiveness of both measures can be surpassed by reducing the initial occurrence of L. monocytogenes in the product (at the end of processing). It is, therefore, necessary that future QRA models for RTE seafood contain a processing module that can provide insight into intervention strategies that can retard L. monocytogenes' growth, such as the use of bacteriocins, ad hoc starter cultures and/or organic acids, and other strategies seeking to reduce cross-contamination at the facilities, such as stringent controls for sanitation procedures. Since risk estimates were shown to be moderately driven by growth kinetic parameters, namely, the exponential growth rate, the minimum temperature for growth, and the maximum population density, further work is needed to reduce uncertainties.

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

A review of the published quantitative risk assessment (QRA) models of L. monocytogenes in meat and meat products was performed, with the objective of appraising the intervention strategies deemed suitable for implementation along the food chain as well as their relative effectiveness. A systematic review retrieved 23 QRA models; most of them (87%) focused on ready-to-eat meat products and the majority (78%) also covered short supply chains (end processing/retail to consumption, or consumption only). The processing-to-table scope was the choice of models for processed meats such as chorizo, bulk-cooked meat, fermented sausage and dry-cured pork, in which the effects of processing were simulated. Sensitivity analysis demonstrated the importance of obtaining accurate estimates for lag time, growth rate and maximum microbial density, in particular when affected by growth inhibitors and lactic acid bacteria. In the case of deli meats, QRA models showed that delicatessen meats sliced at retail were associated with a higher risk of listeriosis than manufacture pre-packed deli meats. Many models converged on the fact that (1) controlling cold storage temperature led to greater reductions in the final risk than decreasing the time to consumption and, furthermore, that (2) lower numbers and less prevalence of L. monocytogenes at the end of processing were far more effective than keeping low temperatures and/or short times during retail and/or home storage. Therefore, future listeriosis QRA models for meat products should encompass a processing module in order to assess the intervention strategies that lead to lower numbers and prevalence, such as the use of bio-preservation and novel technologies. Future models should be built upon accurate microbial kinetic parameters, and should realistically represent cross-contamination events along the food chain.