Bacterial contamination of table eggs and the influence of housing systems

With the introduction of alternative housing systems for laying hens in the EU, recent research has focussed on the bacterial contamination of table eggs, e.g. eggshell and egg content contamination. Contamination of eggshells with aerobic bacteria is generally higher for nest eggs from non-cage systems compared to nest eggs from furnished cages or eggs from conventional cages. Studies indicate limited or no systematic differences in eggshell contamination with aerobic bacteria between eggs laid in the nest boxes of furnished cages and eggs laid in conventional cages. The major differences found in experimental studies between cage- and non-cage systems are less pronounced under commercial conditions. The effect of housing system on eggshell contamination with specific groups of bacteria is variable. Limited information is available on the influence of housing system on egg content contamination. Recent research does not indicate large differences in egg content contamination between eggs from cage- and non-cage systems (ignoring outside nest and floor eggs). The microflora of the eggshell is dominated by Gram-positive bacteria, whereas Gram-negative bacteria are best equipped to overcome the antimicrobial defences of the egg content. Much of the research on eggshell and egg content contamination focuses on Salmonella, since infection with Salmonella enteritidis, resulting from the consumption of contaminated eggs or egg products, is still a major health problem. Observed Salmonella prevalence on the eggshell and in the egg content vary, depending on the fact whether investigations were based on randomly sampled table eggs or on eggs from naturally infected hens. The limited information available on other pathogens shows that they are exclusively isolated from the eggshell and not from the internal contents

Influence of food system conditions on N-acyl-L-homoserine lactones production by <i>Aeromonas</i> spp.

Eleven of 13 Aeromonas strains were shown to produce AHLs. Results of TLC showed that N-butanoyl-L-homoserine lactone (C4-HSL) was the main AHL produced in LB medium at 30 degrees C. The influence of different carbon sources, temperature, pH values and salt concentrations on AHL production was determined in eight A. hydrophila and one A. caviae strain. Additionally a quantitative study of C4-HSL production by A. hydrophila strain 519 under different conditions was performed. Positive results were found in the AHL induction assay for some Aeromonas strains in cultures in LB agar incubated at 12 degrees C after 72-96 h. The induction of the sensor strains by Aeromonas spp. occurred in LB medium supplemented with all carbon sources in a concentration of 0.5%. The production of C4-HSL by A. hydrophila 519 was found until 3.5% (w/v) of NaCl. For pHs close to the neutrality the C4-HSL production by A. hydrophila was evident after 24-48 h of incubation. A. hydrophila 519 produced C4-HSL under anaerobic conditions. Also, the AHL production by Aeromonas strains was studied in simulate agar of shrimp, fish and some vegetables. The production of AHLs was evident by almost all the test strains in shrimp simulated agar. In fish agar only for one of three fish species tested, positive results were found. Induction assay in vegetables simulated agar showed principally negative results, probably because of the presence of inhibitory compounds in these vegetables

Tools to support the self assessment of the performance of Food Safety Management Systems

Changes in food supply chains, health and demographic situations, lifestyle and social situations, environmental conditions, and increased legislative requirements have led to significant efforts in the development of quality and safety management systems in agribusiness and food industry worldwide (Ropkins and Beck, 2000; Efstratiadis, Karirti, and Arvanitoyannis, 2000; Jacxsens, et al, 2009a, Luning and Marcelis, 2009a). Nowadays, companies have implemented various quality assurance (QA) guidelines and standards, such as GMP and HACCP guidelines (like General Principles of food hygiene (Codex Alimentarius 2003), GFSI guidance document (GFSI (2007), and quality assurance standards (like ISO 9001:2008 (2008), ISO22000:2005 (2005), BRC (2008), and IFS (2007) into their company own food safety management system. The performance of such systems in practice is, however, still variable. Moreover, the continuous pressure on food safety management system (FSMS) performance and the dynamic environment wherein the systems operate (such as emerging pathogens, changing consumer demands, developments in preservation techniques) require that they can be systematically analysed to determine opportunities for improvement (Wallace, et al, 2005; Manning et al, 2006; Van der Spiegel et al, 2006; Cornier et al, 2007; Luning et al, 2009a). Within the European project entitled ‘PathogenCombat- EU FOOD-CT-2005-007081’ various tools have been developed to support food companies and establishments in systematically analysing and judging their food safety management system and its microbiological performance as basis for strategic choices on interventions to improve the FSMS performance. This chapter describes briefly principles of the major tools that have been developed and some others, which are still under still under construction

Incidence and identification of mesophilic <i>Aeromonas</i> spp. from retail foods

Sixty-eight food samples were examined for the presence of mesophilic Aeromonas species both qualitatively and quantitatively. Aeromonads were isolated from 26% of the vegetable samples, 70% of the meat and poultry samples and 72% of the fish and shrimps. Numbers of motile aeromonads present in the food samples varied from 2 cfu g-1 to >105 cfu g-1. GLC analysis of FAMEs was used to identify a selection of presumptive Aeromonas colonies to fenospecies or genomic species level. Aeromonas strains belonging to the Aer. caviae complex, which also includes the potentially pathogenic genospecies HG4, were mostly isolated from vegetables but were also found in meat, poultry and fish. In addition, three strains of the virulent taxon Aer. veronii biovar sobria HG8 were isolated from poultry and minced meat. All members of the Aer. hydrophila complex, predominant in the fish, meat and poultry samples, were classified in the non-virulent taxon HG3. Although the significance of Aeromonas in foods remains undefined, the isolation of Aeromonas HG4 and HG8 strains from a variety of retail foods may indicate that these products can act as possible vehicles for the dessimination of food-borne Aeromonas gastroenteritis

Evaluation of risk based microbiological criteria for Campylobacter in broiler carcasses in Belgium using TRiMiCri

Campylobacteriosis is the most frequently reported foodborne zoonosis worldwide. Consumer´s exposure to Campylobacter might be reduced by establishing a microbiological criterion (MC) for Campylobacter on broiler meat. In the present study two possible approaches were evaluated, using the freely available software tool for risk based microbiological criteria TRiMiCri (http://tools.food.dtu.dk/trimicri). The first approach was the traditional one that implies a microbiological limit (ML-MC) and the second one which is based on the relative risk estimate (RRL-MC). The analyses were based on Campylobacter quantitative data collected from 28 Campylobacter positive bathes processed in 6 Belgian broiler slaughterhouses. To evaluate the performance of ML-MC, n=6, different c (0,1,2) and m (100,1 000,10 000) were used. Results showed that more than 90% of Campylobacter positive batches were not complying with strict ML criteria based on the m=100 for all applied combination of c. The RRL approach requires a baseline risk which was estimated based on the Campylobacter baseline data collected in Belgium in 2008. Approximately 60% of evaluated Campylobacter positive batches account for higher risk than the baseline risk. For both approaches, application of less stringent criteria results in lower percentage of NC and higher minimum relative residual risks (MRRR; it refers to the change in risk when all batches are sampled and all NC batches undergo treatment that effectively eliminates Campylobacter so they are replaced by zero risk batches). It was also observed that the number of samples (n) had little effect on risk estimates. Additionally, the results from ML-MC and RRL-MC follow the same curve when plotting percentage of NC against MRRR. However, for RRL-MC the percentage of NC batches and MRRR was lower and higher, respectively. To conclude, obtained results indicate that TRiMiCri is a useful and user friendly tool to make a risk based decision on the choice of the MC

Exposing the human nude phenotype [4]

Peer reviewedSubmitted Versio

Risk ranking of pathogens in ready-to-eat unprocessed foods of non-animal origin (FoNAO) in the EU: Initial evaluation using outbreak data (2007-2011).

International audienceFoods of non-animal origin (FoNAO) are consumed in a variety of forms, being a major component of almost all meals. These food types have the potential to be associated with large outbreaks as seen in 2011 associated with VTEC 0104. In order to identify and rank specific food/pathogen combinations most often linked to human cases originating from FoNAO in the EU, a semi-quantitative model was developed using seven criteria: strength of associations between food and pathogen based on the foodborne outbreak data from EU Zoonoses Monitoring (2007-2011), incidence of illness, burden of disease, dose-response relationship, consumption, prevalence of contamination and pathogen growth potential during shelf life. The top ranking food/pathogen combination was Salmonella spp. and leafy greens eaten raw followed by (in equal rank) Salmonella spp. and bulb and stem vegetables, Salmonella spp. and tomatoes, Salmonella spp. and melons, and pathogenic Escherichia coli and fresh pods, legumes or grains. Despite the inherent assumptions and limitations, this risk model is considered a tool for risk managers, as it allows ranking of food/pathogen combinations most often linked to foodborne human cases originating from FoNAO in the EU. Efforts to collect additional data even in the absence of reported outbreaks as well as to enhance the quality of the EU-specific data, which was used as input for all the model criteria, will allow the improvement of the model outputs. Furthermore, it is recommended that harmonised terminology be applied to the categorisation of foods collected for different reasons, e.g. monitoring, surveillance, outbreak investigation and consumption. In addition, to assist future microbiological risk assessments, consideration should be given to the collection of additional information on how food has been processed, stored and prepared as part of the above data collection exercises

AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials

Computational catalysis is playing an increasingly significant role in the design of catalysts across a wide range of applications. A common task for many computational methods is the need to accurately compute the adsorption energy for an adsorbate and a catalyst surface of interest. Traditionally, the identification of low energy adsorbate-surface configurations relies on heuristic methods and researcher intuition. As the desire to perform high-throughput screening increases, it becomes challenging to use heuristics and intuition alone. In this paper, we demonstrate machine learning potentials can be leveraged to identify low energy adsorbate-surface configurations more accurately and efficiently. Our algorithm provides a spectrum of trade-offs between accuracy and efficiency, with one balanced option finding the lowest energy configuration 87.36% of the time, while achieving a 2000x speedup in computation. To standardize benchmarking, we introduce the Open Catalyst Dense dataset containing nearly 1,000 diverse surfaces and 100,000 unique configurations.Comment: 26 pages, 7 figures. Submitted to npj Computational Material

The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture

New methods for carbon dioxide removal are urgently needed to combat global climate change. Direct air capture (DAC) is an emerging technology to capture carbon dioxide directly from ambient air. Metal-organic frameworks (MOFs) have been widely studied as potentially customizable adsorbents for DAC. However, discovering promising MOF sorbents for DAC is challenging because of the vast chemical space to explore and the need to understand materials as functions of humidity and temperature. We explore a computational approach benefiting from recent innovations in machine learning (ML) and present a dataset named Open DAC 2023 (ODAC23) consisting of more than 38M density functional theory (DFT) calculations on more than 8,400 MOF materials containing adsorbed $CO_2$ and/or $H_2O$. ODAC23 is by far the largest dataset of MOF adsorption calculations at the DFT level of accuracy currently available. In addition to probing properties of adsorbed molecules, the dataset is a rich source of information on structural relaxation of MOFs, which will be useful in many contexts beyond specific applications for DAC. A large number of MOFs with promising properties for DAC are identified directly in ODAC23. We also trained state-of-the-art ML models on this dataset to approximate calculations at the DFT level. This open-source dataset and our initial ML models will provide an important baseline for future efforts to identify MOFs for a wide range of applications, including DAC