(76b) On the Quantitative Evaluation of the Impact of the Concentration and Distribution of Fat on the Microbial Dynamics within Viscoelastic Triphasic Food Model Systems

Bacteria play a key role in food production for many different reasons. Some food related bacteria are beneficially used as starter cultures in the dairy industry, other spoilage bacteria cause organoleptic changes to the food product and other pathogenic bacteria are harmful and can lead to severe disease or death. To achieve microbiologically safe food products, it is important to understand the bacterial dynamics in single culture, but also in co-culture, as in a food system multiple bacteria can co-exist and bacterial communities behave vary differently to single cultures (Moons, Michiels and Aertsen, 2009; Fox et al., 2014; Zilelidou and Skandamis, 2018). Additionally, the bacterial behaviour is influenced by the environment. Food products are generally very complicated biochemically, structurally and biophysically. Therefore, to obtain a fundamental understanding of intra-species interactions as affected by the food environment, it is important to design simpler in vitromodels. Most quantitative studies on food related microbial kinetics (growth or inactivation) in in vitromodels are conducted in liquid broths and very few in simple mono-phase homogenous gel systems (with gelling agents such as agar, gelatine etc.) (Fröhlinget al., 2012; Bakaet al., 2017;Feiet al., 2020). Those studies have showed that the bacterial behaviour is different in liquid systems compared to solid systems, as the availability of nutritional components and oxygen changes and so does the bacterial communication (Wimpennyet al., 1995; Smetet al., 2017;Heiret al., 2018). Most food products are solid or solid-like and it is therefore important to account for more complex composition and structural properties of food models.

In this study, building on our recently developed biphasic protein/polysaccharide food model (Costelloet al., 2018, 2019), we have developed triphasic food models enriched with fat, as studies in real food have revealed that the fat concentration has a significant impact on the bacterial behaviour (Brocklehurst and Wilson, 2000; Skandamis and Nychas, 2012).

Our novel triphasic systems consist of Xanthan gum, Whey protein and vegetable oil. Various oil concentrations in the range 10-60% were considered (range similar to real food products). A microscopic comparison showed that these novel triphasic systems are structurally similar to real foods; like soft cheeses or meat patés. Furthermore, rheological analysis of the food models showed that the oil contentis a major factor affecting the rheological and structural behaviour, as well as the physicochemical properties and oil droplet size.

Quantitative analysis of the microbial dynamics in the tri-phase systems with oilconcentration of 0%, 20% and 60% was conducted. More specifically, the growth of the foodborne gram-positive pathogen Listeria monocytogenes, the gram-negative pathogen Escherichia coli, and the spoilage bacteria Pseudomonas aeroginosa was monitored at 37 °C, while the growth of the starter organism Lactococcus lactis was monitored at 30 °C. Furthermore, advanced confocal laser scanning microscopy(CLSM) was used for the spatial determination of the food model components and for the analysis of the distribution of bacterial colonies on the food models.

Overall, the oil concentration in the triphasic model did not affect the macroscale/macroscopic microbial growth kinetics (as evaluated by the Baranyi Roberts growth model) for all bacteria under study. However, at the microscopic scale, generally, the bacterial colonies reduced in size with increasing oil concentration. The higher oil concentration resulted in space limitations and diffusional limitations of nutrients. Furthermore, in terms of growth location most bacterial colonies/aggregates were located close to the oil droplets. Due to these microscopic differences, different levels of cell-cell and colony-colony interactions take place for different structural configurations of our models. This can allow bacteria to send signalling molecules, such as the so-called quorum sensing molecules which can lead to different levels of stress adaptation. Additionally, the size of the colonies can have a direct impact on the efficiency of mild preservation methods.

In conclusion, our results indicate the importance of accounting for food biochemical composition and microstructural complexities when monitoring food related bacteria. A multi-level complex analysis on both macro and microscale enables a better prediction of bacterial interactions: whilst the macroscopic microbial kinetics can be unaffected by small environmental changes, on a microscale level small alterations of the environment can result in substantial changes in the bacterial interactions, which can further impact the efficiency and the design of food decontamination treatments.

ACKNOWLEDGEMENTS:

This research was supported by the Doctoral College and the Department of Chemical and Process Engineering of the University of Surrey, the EPSRC and the Royal Society. E.V. is grateful for a Royal Academy of Engineering Industrial Fellowship.

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