Investigation of the effects of gastric pH on in vitro gastrointestinal digestion of solid food particles using innovative magnetic resonance imaging (MRI) approaches

Work environment, missions and activities

Solid food enters the stomach as particles between 0 and 5 mm in diameter. Depending on their structural and compositional properties, digestion of these particles can be limited by the diffusion of digestive enzymes within them, the resistance of microstructures to enzymatic attack (e.g. gluten, cell walls) or by pH conditions unfavourable to enzyme activity (buffering effect). The ability of MRI to characterise the composition and structure of food at different scales (from molecules to particles) in a non-invasive and non-destructive way makes it a method of choice for monitoring digestion kinetics and improving our understanding of the mechanisms involved in the disintegration of solid food particles.

The aim of this thesis is to study the mechanisms that limit the degradation of solid food particles and the release of their nutrients during in vitro digestion under MRI. Particular attention will be paid to the influence of gastric acidification kinetics, which are known to be highly variable between individuals (inter-individual variability or variability induced by the use of proton pump inhibitors), on gastrointestinal digestion kinetics. Firstly, the matrix effect of Emmental cheese, with its strong buffering effect, will be studied using 2 devices to study phenomena at the scale of a mixture of particles on the one hand, and a single particle on the other. Secondly, the matrix effect of apples, as a model of fleshy fruit, will also be studied.

The experiments will be performed on the 1.5 T whole body MRI imager (SOLA, Siemens) using original devices that has already been validated for performing in vitro digestion under MRI.

The PhD student will be integrated into the teams of the two research units, OPAALE and STLO (about 2 km apart), where all the equipment required for the thesis is available. The thesis will be co-supervised by:

Thesis supervisor: Maja Musse, researcher INRAE, UR OPAALE, IRM-Food team

Thesis co-supervisor: Steven Le Feunteun, researcher INRAE, UMR STLO, BN team