France has reported a decline in cases of a serious condition that can develop after an E. coli infection.
Hemolytic uremic syndrome (HUS) is a severe complication associated with E. coli infections that causes kidney failure.
Data from Santé publique France shows 143 HUS cases in 2023 compared to 252 in 2022. There were several serious outbreaks in 2022, including one linked to Nestlé Buitoni frozen pizzas.
There are two Salmonella species: Salmonella enterica (S. enterica) and Salmonella bongori (S. bongori). S. bongori strains predominantly colonize cold-blooded reptiles, whereas S. enterica strains are capable of infecting both humans and mammals.[1] Based on factors such as morphology, structure, mode of reproduction, and other criteria, the two species are further classified into subgroups called serotypes or serovars. More than 2,600 serotypes have been described for Salmonella, and they are characterized by the type(s) of animal they are found in or by the clinical symptoms they cause.[2] Of these, less than 100 are responsible for most human Salmonella infections.[3]
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We report on the collaborative investigation of an outbreak including about 200 cases of Salmonella enterica serotype Umbilo (S. Umbilo) that affected several European countries mainly between July and September 2024. The investigation enabled to rapidly identify and microbiologically confirm rocket salad (also known as arugula or rucola) from company A in Italy as the likely food vehicle. Baby spinach and possibly other items produced by the same company could be additional food vehicles. While case numbers appeared to decline in October 2024, some S. Umbilo infections (with genomic analysis pending to confirm these cases) continue to be detected at the time of writing.
Fresh produce safety is important for consumer health. Intervention technologies that can lessen the pathogen threat and produce contamination is needed. In this research, cold plasma (CP), pulsed light (PL) and their combinations were assessed for inactivating Escherichia coli O157:H7 on Romaine lettuce. The effects of treatment on native microflora and sensory attributes of lettuce was also determined. An inoculum of multiple E. coli O157:H7 strains was employed for this study. Lettuce leaves were spot inoculated and then treated with PL (1–60 s), CP (15–60 s) or their optimized treatment combinations. A 30 s treatment with PL (fluence dose of 31.5 J/cm2), was optimum which provided 2.7 log CFU/g reduction of the pathogen, while 45 s treatment of CP was optimum, that delivered 2.1 log CFU/g log reduction. Combinations of PL and CP treatments were investigated for enhanced inactivation. For PL-CP combination, inoculated lettuce was treated with PL for 30 s followed by 45 s of CP exposure. While for CP-PL combination, treatments sequences were 45 s of CP treatment followed by 30 s PL treatment. Both combination treatments, PL-CP and CP-PL, resulted in synergistic inactivation of E. coli cells with > 5 log reductions of the pathogen. These combination treatments significantly (p < 0.05) reduced native microbiota and slowed their growth during storage. Additionally, treatment effects on lettuce quality was not adversely impacted. PL and CP are both non-aqueous, sustainable technologies. This study demonstrated that integration of PL and CP technology can enhance microbial safety and preserve quality of Romaine lettuce.
In a rare occurrence of locally acquired typhoid fever in Canada, health officials in Ottawa recently traced an outbreak back to a chronic Salmonella Typhi carrier working as a food handler. The outbreak involved seven confirmed cases from Oct. 2018 to May 2022 and was linked to the asymptomatic carrier through whole genome sequencing (WGS) and social network analysis.
Typically, cases of typhoid fever in Canada are linked to international travel, making this localized outbreak unusual. The investigation led by Ottawa Public Health underscores the potential for chronic carriers, who may shed bacteria without symptoms and unintentionally transmit the disease over an extended period. All eight outbreak-related isolates matched genetically, confirming the cluster.
Food Safety Information Council
This Australian Food Safety Week 9 to 16 November, the Food Safety Information Council is advising consumers that air fryers could be a food safety risk if they don’t follow cooking instructions.
Lydia Buchtmann, the Council’s CEO, said that air fryers are becoming very popular with our recent research shows 2 in 3 Australians surveyed have an air fryer in their household, with 54% of those using it weekly and 38% several times a week.
‘Air fryers are convenient and easy to use, but there have been individual foodborne disease cases around the country linked to air fryers, especially when cooking crumbed products that may look cooked on the outside but aren’t fully cooked on the inside.
The recurring contamination of leafy greens with pathogenic Escherichia coli bacteria is a critical public health issue that has impacted consumers and the food industry alike. The high susceptibility of leafy greens to E. coli contamination is exacerbated by various factors, from field exposure to processing practices. This article delves into the technical aspects of E. coli contamination in leafy greens processing facilities, including environmental control measures, sanitation practices, and strategies to mitigate bacterial load.
The field of food safety is critical in ensuring that the food supply remains safe and nutritious from production to consumption. One of the most pressing challenges in this area is controlling microbial growth, which can significantly reduce the shelf life of food products and pose health risks. The composition and physicochemical characteristics of food can either inhibit or promote the growth of foodborne pathogens. Traditional microbial growth models, often used in laboratory settings, do not always translate well to real-world food environments due to the unique conditions present in food systems. Predictive microbiology has emerged as a valuable tool in this context, allowing researchers to predict the behavior of pathogenic and spoilage microorganisms under various controlled conditions. Despite advancements, there remain significant gaps in our understanding of how to effectively apply these models across different stages of the food processing chain. The need for more comprehensive and adaptable models is evident, particularly as the food industry continues to evolve its processing techniques to enhance food safety and shelf life.
This research topic aims to explore the development and application of predictive models in food safety throughout the processing chain. The primary objectives include understanding how new processing conditions impact microbial safety, examining the interactions between food ingredients and antimicrobials, and developing robust models that can predict microbial behavior in diverse food environments. Specific questions to be addressed include: How do changes in food composition affect microbial growth? What are the best practices for integrating machine learning into predictive microbiology? How can we construct and validate models that are applicable across various stages of food production?
To gather further insights into the boundaries of predictive models in food safety, we welcome articles addressing, but not limited to, the following themes:
– Impact of new food processing conditions on the microbial safety of the final product
– Interaction of added antimicrobials and food ingredients on food safety
– Use of growth/no growth models for the growth of pathogens
– Impact of food composition modifications on the growth of pathogens or concentration of toxins
– Development of empirical or theoretical models for assessing microbial growth under food system conditions
– Machine learning applications in predictive microbiology
– Construction and validation of tertiary predictive models
Posted in Food Micro Blog, Food Microbiology, Food Microbiology Blog, Food Microbiology Research, Food Microbiology Testing, microbial contamination, Microbial growth, Microbial Spoilage, Microbiological Risk Assessment, Microbiology, Microbiology Investigations, Microbiology Risk, Predictive Modelling, Research
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