An agent-based model to simulate SARS-CoV-2 contamination of surfaces and meat cuts in processing plants.

At the beginning of the COVID-19 pandemic, several contamination clusters were reported in food-processing plants in France and several countries worldwide. Therefore, a need arose to better understand viral transmission in such occupational environments from multiple perspectives: the protection of workers in hotspots of viral circulation; the prevention of supply disruption due to the closure of plants; and the prevention of cluster expansion due to exports of food products contaminated by the virus to other locations. This paper outlines a simulation-based approach (using agent-based models) to study the effects of measures taken to prevent the contamination of workers, surfaces, and food products. The model includes user-defined parameters to integrate characteristics relating to SARS-CoV-2 (variant of concern to be considered, symptom onset…), food-processing plants (dimensions, ventilation…), and other sociodemographic transmission factors based on laboratory experiments as well as industrial and epidemiological investigations. Simulations were performed for a typical meat-processing plant in different scenarios for illustration purposes. The results suggested that increasing the mask-wearing ratio led to great reductions in the probability of observing clusters of more than 25 infections. In the case of clusters, masks being worn by all workers limited the presence of contamination (defined as levels of at least 5 log10 viral RNA copies) on meat cuts at less than 0.05 % and maintained the production capacity of the plant at optimal levels. Increasing the average distance between two workers from less than 1 m to more than 2 m decreased the cluster-occurrence probability by up to 15 % as well as contamination of food products during cluster situations. The developed approach can open up several perspectives in terms of potential communication-support tools for the agri-food sector and further reuses or adaptations for other hazards and occupational environments.

Omnicrobe, an open-access database of microbial habitats and phenotypes using a comprehensive text mining and data fusion approach.

The dramatic increase in the number of microbe descriptions in databases, reports, and papers presents a two-fold challenge for accessing the information: integration of heterogeneous data in a standard ontology-based representation and normalization of the textual descriptions by semantic analysis. Recent text mining methods offer powerful ways to extract textual information and generate ontology-based representation. This paper describes the design of the Omnicrobe application that gathers comprehensive information on habitats, phenotypes, and usages of microbes from scientific sources of high interest to the microbiology community. The Omnicrobe database contains around 1 million descriptions of microbe properties. These descriptions are created by analyzing and combining six information sources of various kinds, i.e. biological resource catalogs, sequence databases and scientific literature. The microbe properties are indexed by the Ontobiotope ontology and their taxa are indexed by an extended version of the taxonomy maintained by the National Center for Biotechnology Information. The Omnicrobe application covers all domains of microbiology. With simple or rich ontology-based queries, it provides easy-to-use support in the resolution of scientific questions related to the habitats, phenotypes, and uses of microbes. We illustrate the potential of Omnicrobe with a use case from the food innovation domain.

Risk of Monkeypox virus (MPXV) transmission through the handling and consumption of food.

Monkeypox (MPX) is a zoonotic infectious disease caused by Monkeypox virus (MPXV), an enveloped DNA virus belonging to the Poxviridae family and the Orthopoxvirus genus. Since early May 2022, a growing number of human cases of Monkeypox have been reported in non-endemic countries, with no history of contact with animals imported from endemic and enzootic areas, or travel to an area where the virus usually circulated before May 2022. This qualitative risk assessment aimed to investigate the probability that MPXV transmission occurs through food during its handling and consumption. The risk assessment used "top-down" (based on epidemiological data) and "bottom-up" (following the agent through the food chain to assess the risk of foodborne transmission to human) approaches, which were combined. The "top-down" approach first concluded that bushmeat was the only food suspected as a source of contamination in recorded cases of MPXV, by contact or ingestion. The "bottom-up" approach then evaluated the chain of events required for a human to become ill after handling or consuming food. This approach involves several conditions: (i) the food must be contaminated with MPXV (naturally, by an infected handler or after contact with a contaminated surface); (ii) the food must contain viable virus when it reaches the handler or consumer; (iii) the person must be exposed to the virus and; (iv) the person must be infected after exposure. Throughout the risk assessment, some data gaps were identified and highlighted. The conclusions of the top-down and bottom-up approaches are consistent and suggest that the risk of transmission of MPXV through food is hypothetical and that such an occurrence was never reported. In case of contamination, cooking (e.g., 12 min at 70°C) could be considered effective in inactivating Poxviridae in foods. Recommendations for risk management are proposed. To our knowledge, this is the first risk assessment performed on foodborne transmission of MPXV.

Database of SARS-CoV-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants.

SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2), a virus causing severe acute respiratory disease in humans, emerged in late 2019. This respiratory virus can spread via aerosols, fomites, contaminated hands or surfaces as for other coronaviruses. Studying their persistence under different environmental conditions represents a key step for better understanding the virus transmission. This work aimed to present a reproducible procedure for collecting data of stability and inactivation kinetics from the scientific literature. The aim was to identify data useful for characterizing the persistence of viruses in the food production plants. As a result, a large dataset related to persistence on matrices or in liquid media under different environmental conditions is presented. This procedure, combining bibliographic survey, data digitalization techniques and predictive microbiological modelling, identified 65 research articles providing 455 coronaviruses kinetics. A ranking step as well as a technical validation with a Gage Repeatability & Reproducibility process were performed to check the quality of the kinetics. All data were deposited in public repositories for future uses by other researchers.

Guidance Level for Brevetoxins in French Shellfish.

Brevetoxins (BTXs) are marine biotoxins responsible for neurotoxic shellfish poisoning (NSP) after ingestion of contaminated shellfish. NSP is characterized by neurological, gastrointestinal and/or cardiovascular symptoms. The main known producer of BTXs is the dinoflagellate Karenia brevis, but other microalgae are also suspected to synthesize BTX-like compounds. BTXs are currently not regulated in France and in Europe. In November 2018, they have been detected for the first time in France in mussels from a lagoon in the Corsica Island (Mediterranean Sea), as part of the network for monitoring the emergence of marine biotoxins in shellfish. To prevent health risks associated with the consumption of shellfish contaminated with BTXs in France, a working group was set up by the French Agency for Food, Environmental and Occupational Health & Safety (Anses). One of the aims of this working group was to propose a guidance level for the presence of BTXs in shellfish. Toxicological data were too limited to derive an acute oral reference dose (ARfD). Based on human case reports, we identified two lowest-observed-adverse-effect levels (LOAELs). A guidance level of 180 µg BTX-3 eq./kg shellfish meat is proposed, considering a protective default portion size of 400 g shellfish meat.

Modeling the Inactivation of Viruses from the Coronaviridae Family in Response to Temperature and Relative Humidity in Suspensions or on Surfaces.

Temperature and relative humidity are major factors determining virus inactivation in the environment. This article reviews inactivation data regarding coronaviruses on surfaces and in liquids from published studies and develops secondary models to predict coronaviruses inactivation as a function of temperature and relative humidity. A total of 102 D values (i.e., the time to obtain a log10 reduction of virus infectivity), including values for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were collected from 26 published studies. The values obtained from the different coronaviruses and studies were found to be generally consistent. Five different models were fitted to the global data set of D values. The most appropriate model considered temperature and relative humidity. A spreadsheet predicting the inactivation of coronaviruses and the associated uncertainty is presented and can be used to predict virus inactivation for untested temperatures, time points, or any coronavirus strains belonging to Alphacoronavirus and Betacoronavirus genera.IMPORTANCE The prediction of the persistence of SARS-CoV-2 on fomites is essential in investigating the importance of contact transmission. This study collects available information on inactivation kinetics of coronaviruses in both solid and liquid fomites and creates a mathematical model for the impact of temperature and relative humidity on virus persistence. The predictions of the model can support more robust decision-making and could be useful in various public health contexts. A calculator for the natural clearance of SARS-CoV-2 depending on temperature and relative humidity could be a valuable operational tool for public authorities.

Text mining tools for extracting information about microbial biodiversity in food.

Information on food microbial diversity is scattered across millions of scientific papers. Researchers need tools to assist their bibliographic search in such large collections. Text mining and knowledge engineering methods are useful to automatically and efficiently find relevant information in Life Science. This work describes how the Alvis text mining platform has been applied to a large collection of PubMed abstracts of scientific papers in the food microbiology domain. The information targeted by our work is microorganisms, their habitats and phenotypes. Two knowledge resources, the NCBI taxonomy and the OntoBiotope ontology were used to detect this information in texts. The result of the text mining process was indexed and is presented through the AlvisIR Food on-line semantic search engine. In this paper, we also show through two illustrative examples the great potential of this new tool to assist in studies on ecological diversity and the origin of microbial presence in food.

CO2 and O2 solubility and diffusivity data in food products stored in data warehouse structured by ontology.

This data article contains values of oxygen and carbon dioxide solubility and diffusivity measured in various model and real food products. These data are stored in a public repository structured by ontology. These data can be retrieved through the @Web tool, a user-friendly interface to capitalise and query data. The @Web tool is accessible online at http://pfl.grignon.inra.fr/atWeb/.

Predictive Microbiology Coupled with Gas (O2 /CO2 ) Transfer in Food/Packaging Systems: How to Develop an Efficient Decision Support Tool for Food Packaging Dimensioning.

Coupling gas transfer with predictive microbiology is essential to rationally design modified atmosphere packaging (MAP) strategies to ensure and guarantee food safety. Nowadays, these strategies are generally empirically built and over-sized since packaging material with high barrier properties is often chosen by default even if such a high level of protection is not systematically required. Protection strategies could be improved using rational sizing based on quantitative analysis and mathematical modeling of mass transfer. This paper aims at reviewing the current knowledge available for developing such a tool and the further research needed. First there is a special focus on oxygen (O2 ) and carbon dioxide (CO2 ) solubility and diffusivity parameters, which are absolutely indispensable to accurately model mass transfer in MAP systems. Next, the current knowledge of the effect of O2 /CO2 on the growth of microorganisms is explored with an emphasis on predictive microbiology. The last part points out the main bottlenecks and further research needed to be carried out in order to develop an efficient MAP modeling tool for food safety coupling O2 /CO2 transfer and predictive microbiology.

Oxygen and Carbon Dioxide Solubility and Diffusivity in Solid Food Matrices: A Review of Past and Current Knowledge.

Oxygen and carbon dioxide solubility and diffusivity are 2 key parameters to understand gas transfer in food matrices. Knowledge of these parameters could help to predict gas concentration in modified atmosphere packaging and, consequently, to predict shelf-life of the product through the development of appropriate mathematical models. The aim of this review is to present the existing methodologies to quantify O2 and CO2 contents in food, especially in solid food matrices which is very challenging. There is a focus on how these methodologies could be used to determine gas transfers kinetics. Data of O2 /CO2 solubilities and diffusivities in food are collected and compared with a specific emphasis on the food characteristics and factors impacting them. An analysis of the current state of knowledge in solid food matrices is carried out to tentatively build a general predictive model of the O2 and CO2 solubility and diffusivity extendable to any kind of food matrix.