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O’Mahony Cian, Dennis L Seman
In book: The Stability and Shelf Life of Food, Edition: Second, Chapter: 9, Publisher: Elsevier, Editors: Persis Subramaniam, pp.253-284
01/12/2016

Modeling the Microbiological Shelf Life of Foods and Beverages

From about 1985 to 2015, the subject of predictive microbiology has become a mature area of study in and of itself. The ability to predict the growth of a bacterial species within a food matrix for a given set of intrinsic and environmental conditions offers many advantages and benefits to the food industry professional, and chief among these is the ability to determine shelf life using mathematical models.

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W.den Besten Heidy M., Alejandro Amézquita, Sara Bover-Cid, Stéphane Dagnas, Mariem Ellouze, Sandrine Guillou, George Nychas, Cian O’Mahony, Fernando Pérez-Rodriguez, Jeanne-Marie Membré
International Journal of Food Microbiology Volume 287, 20 December 2018, Pages 18-27
20/12/2018

Next generation of microbiological risk assessment: Potential of omics data for exposure assessment

In food safety and public health risk evaluations, microbiological exposure assessment plays a central role as it provides an estimation of both the likelihood and the level of the microbial hazard in a specified consumer portion of food and takes microbial behaviour into account. While until now mostly phenotypic data have been used in exposure assessment, mechanistic cellular information, obtained using omics techniques, will enable the fine tuning of exposure assessments to move towards the next generation of microbiological risk assessment. In particular, metagenomics can help in characterizing the food and factory environment microbiota (endogenous microbiota and potentially pathogens) and the changes over time under the environmental conditions associated with processing, preservation and storage. The difficulty lies in moving up to a quantitative exposure assessment, because the development of models that enable the prediction of dynamics of pathogens in a complex food ecosystem is still in its infancy in the food safety domain. In addition, collecting and storing the environmental data (metadata) required to inform the models has not yet been organised at a large scale. In contrast, progress in biomarker identification and characterization has already opened the possibility of making qualitative or even quantitative connection between process and formulation conditions and microbial responses at the strain level. In term of modelling approaches, without changing radically the usual model structure, changes in model inputs are expected: instead of (or as well as) building models upon phenotypic characteristics such as for example minimal temperature where growth is expected, exposure assessment models could use biomarker response intensity as inputs. These new generations of strain-level models will bring an added value in predicting the variability in pathogen behaviour. Altogether, these insights based upon omics techniques will increase our (quantitative) knowledge on pathogenic strains and consequently will reduce our uncertainty; the exposure assessment of a specific combination of pathogen and food will be then more accurate. This progress will benefit the whole community of safety assessors and research scientists from academia, regulatory agencies and industry.

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Feed to fork risk assessment of mycotoxins under climate change influences – recent developments

Background

Mycotoxins are toxins produced by toxigenic fungi and are potentially present in different feed and foodstuffs, including animal products, with the latter typically resulting from carry-over from feedstuffs. These toxins have been linked to various human health issues, including reduced immunity and liver cancer. The production of these toxins is dependent on several factors, including weather conditions like temperature and precipitation, which in turn may be influenced by climate change.

Scope and approach

This review undertakes a systematic approach to identify scientific studies that assess mycotoxin production in feed and cereals which may be influenced by weather variables or climate change scenarios. It also looks at human health risk assessments carried out in the past 20 years related to mycotoxins detected in animal products and the degree to which climate change influences are captured in these risk assessments.

Key findings and conclusions

This review presents a state of the art with regards to risk assessment and modelling approaches to managing mycotoxin contamination in the light of climate change influences. There are very limited human health risk assessments looking at mycotoxin contamination of animal products under climate change influences, whereas a few predictive crop-toxin models considered future climate change scenarios. Predictive crop-toxin models can be used in conjunction with health risk assessments to evaluate mycotoxin risk in animal products under future climate change scenarios. The review identifies scientific gaps including the need for better integration of mycotoxin predictive models, risk assessment and climate change variables to better understand potential climate change influences on food safety.

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Anvarian Amir H. P., Yu Cao, Shabarinath Srikumar, Séamus Fanning and Kieran Jordan
Teagasc, Food Research Centre, Fermoy, Ireland, UCD Centre for Food Safety, Science Centre South, University College Dublin, Dublin, Ireland
22/06/2016

Flow Cytometric and 16S Sequencing Methodologies for Monitoring the Physiological Status of the Microbiome in Powdered Infant Formula Production

The aim of this study was to develop appropriate protocols for flow cytometric (FCM) and 16S rDNA sequencing investigation of the microbiome in a powdered infant formula (PIF) production facility. Twenty swabs were collected from each of the three care zones of a PIF production facility and used for preparing composite samples. For FCM studies, the swabs were washed in 200 mL phosphate buffer saline (PBS). The cells were harvested by three-step centrifugation followed by a single stage filtration. Cells were dispersed in fresh PBS and analyzed with a flow cytometer for membrane integrity, metabolic activity, respiratory activity and Gram characteristics of the microbiome using various fluorophores. The samples were also plated on agar plates to determine the number of culturable cells. For 16S rDNA sequencing studies, the cells were harvested by centrifugation only. Genomic DNA was extracted using a chloroform-based method and used for 16S rDNA sequencing studies. Compared to the dry low and high care zones, the wet medium care zone contained a greater number of viable, culturable, and metabolically active cells. Viable but non-culturable cells were also detected in dry-care zones. In total, 243 genera were detected in the facility of which 42 were found in all three care zones. The greatest diversity in the microbiome was observed in low care. The genera present in low, medium and high care were mostly associated with soil, water, and humans, respectively. The most prevalent genera in low, medium and high care were Pseudomonas, Acinetobacter, and Streptococcus, respectively. The integration of FCM and metagenomic data provided further information on the density of different species in the facility.

frontiers in microbiology journal Flow Cytometric and 16S Sequencing Methodologies

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