Rapeseed and milk protein exhibit a similar overall nutritional value but marked difference in postprandial regional nitrogen utilization in rats

Background: Rapeseed is an emerging and promising source of dietary protein for human nutrition and health. We previously found that rapeseed protein displayed atypical nutritional properties in humans, characterized by low bioavailability and a high postprandial biological value. The objective of the present study was to investigate the metabolic fate of rapeseed protein isolate (RPI) and its effect on protein fractional synthesis rates (FSR) in various tissues when compared to a milk protein isolate (MPI). Methods: Rats (n = 48) were given a RPI or MPI meal, either for the first time or after 2-week adaptation to a MPI or RPI-based diet. They were divided in two groups for measuring the fed-state tissue FSR 2 h after the meal (using a flooding dose of (13)C-valine) and the dietary N postprandial distribution at 5 h (using (15)N-labeled meals). Results: RPI and MPI led to similar FSR and dietary nitrogen (N) losses (ileal and deamination losses of 4% and 12% of the meal, respectively). By contrast, the dietary N incorporation was significantly higher in the intestinal mucosa and liver (+36% and +16%, respectively) and lower in skin (-24%) after RPI than MPI. Conclusions: Although RPI and MPI led to the same overall level of postprandial dietary N retention in rats (in line with our findings in humans), this global response conceals marked qualitative differences at the tissue level regarding dietary N accretion. The fact that FSR did not however differed between groups suggest a differential modulation of proteolysis after RPI or MPI ingestion, or other mechanisms that warrant further study

The Nature of the Dietary Protein Impacts the Tissue-to-Diet 15N Discrimination Factors in Laboratory Rats

Due to the existence of isotope effects on some metabolic pathways of amino acid and protein metabolism, animal tissues are 15N-enriched relative to their dietary nitrogen sources and this 15N enrichment varies among different tissues and metabolic pools. The magnitude of the tissue-to-diet discrimination (Δ15N) has also been shown to depend on dietary factors. Since dietary protein sources affect amino acid and protein metabolism, we hypothesized that they would impact this discrimination factor, with selective effects at the tissue level. To test this hypothesis, we investigated in rats the influence of a milk or soy protein-based diet on Δ15N in various nitrogen fractions (urea, protein and non-protein fractions) of blood and tissues, focusing on visceral tissues. Regardless of the diet, the different protein fractions of blood and tissues were generally 15N-enriched relative to their non-protein fraction and to the diet (Δ15N>0), with large variations in the Δ15N between tissue proteins. Δ15N values were markedly lower in tissue proteins of rats fed milk proteins compared to those fed soy proteins, in all sampled tissues except in the intestine, and the amplitude of Δ15N differences between diets differed between tissues. Both between-tissue and between-diet Δ15N differences are probably related to modulations of the relative orientation of dietary and endogenous amino acids in the different metabolic pathways. More specifically, the smaller Δ15N values observed in tissue proteins with milk than soy dietary protein may be due to a slightly more direct channeling of dietary amino acids for tissue protein renewal and to a lower recycling of amino acids through fractionating pathways. In conclusion, the present data indicate that natural Δ15N of tissue are sensitive markers of the specific subtle regional modifications of the protein and amino acid metabolism induced by the protein dietary source

ProVegOmics étude multi-omique, intégrative et translationnelle de la transition protéique

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L’espace urbain et la Loire à Tours

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Modélisation compartimentale du modélisme splanchnique et périphérique de l'azote alimentaire en phase postprandiale non stationnaire chez l'homme

PARIS-AgroParisTech Centre Paris (751052302) / SudocSudocFranceF

Development and calibration of a modeling tool for the analysis of clinical data in human nutrition

This paper addresses the problem of calibrating a compartmental model which describes the postprandial distribution of dietary nitrogen in humans after the ingestion of a protein meal. This type of problem (i.e., a classic inverse problem) requires optimization of an objective function that measures the goodness-of-fit of the model predictions to a given set of experimental data. In our particular case, traditional local, gradient-based optimization methods have failed to arrive at satisfactory solutions of the inverse problem because of the large number of parameters to be estimated, the high non-linearity of the objective function and the few experimental data accessible in humans. To overcome these limitations, we have developed a calibration method that uses all available information on the system behavior so as to divide the large inverse problem into many smaller sub-problems, on which a variant of the Nelder-Mead (NM) simplex search procedure was proven to be successful. This calibration method makes it possible to obtain solutions that are close to the optimal values of most of the model parameters, even when noisy experimental data are introduced in the objective function. Using these estimated parameters, it is now possible to correctly simulate the temporal evolution of all compartments of the physiological model, which constitutes a useful, explanatory tool to describe the different dynamic processes involved in the metabolic utilization of dietary proteins in humans

Exploring multidimensional and within-food group diversity for diet quality and long-term health in high-income countries

International audienceDietary diversity is a crucial component of healthy eating patterns because it ensures nutritional adequacy. Yet, concerns have been raised about the potential risks of its increase, which may reflect excessive consumption of unhealthy foods and higher obesity or cardiometabolic risk, particularly in high-income countries. However, the links between dietary diversity and different health outcomes remain inconclusive because of methodological differences in assessing dietary diversity. Numerous studies, mostly cross-sectional, have assessed dietary diversity using different indicators usually based only on the number of foods or food groups consumed. In this perspective, we emphasize that dietary diversity is a multidimensional concept encompassing the number of foods in the diet (food coverage) but also their relative proportions (food evenness) and the nutritional dissimilarity of foods consumed over time (food complementarity). Consequently, a comprehensive assessment of dietary diversity reflecting all its dimensions, both between and within-food groups, is needed to determine the optimal level of complementarity between and within-food groups required to improve health and diet quality. Moreover, given the prevailing context of abundant highly processed and energy-dense foods in high-income countries, promoting dietary diversity should prioritize nutrient-dense food groups. Until recently, within-food group diversity has received limited attention in research and public health recommendations. Still, it may play a role in improving diet quality and long-term health. This perspective aims to clarify the concept of dietary diversity and suggest research avenues that should be explored to better understand its associations with nutritional adequacy and health among adults in high-income countries

Box-modeling of 15N/14N in mammals

International audienceThe 15N/14N signature of animal proteins is now commonly used to understand their physiology and quantify the flows of nutrient in trophic webs. These studies assume that animals are predictably 15N-enriched relative to their food, but the isotopic mechanism which accounts for this enrichment remains unknown. We developed a box model of the nitrogen isotope cycle in mammals in order to predict the 15N/14N ratios of body reservoirs as a function of time, N intake and body mass. Results of modeling show that a combination of kinetic isotope fractionation during the N transfer between amines and equilibrium fractionation related to the reversible conversion of N-amine into ammonia is required to account for the well-established ≈4‰ 15N-enrichment of body proteins relative to the diet. This isotopic enrichment observed in proteins is due to the partial recycling of 15N-enriched urea and the urinary excretion of a fraction of the strongly 15N-depleted ammonia reservoir. For a given body mass and diet δ15N, the isotopic compositions are mainly controlled by the N intake. Increase of the urea turnover combined with a decrease of the N intake lead to calculate a δ15N increase of the proteins, in agreement with the observed increase of collagen δ15N of herbivorous animals with aridity. We further show that the low δ15N collagen values of cave bears cannot be attributed to the dormancy periods as it is commonly thought, but inversely to the hyperphagia behavior. This model highlights the need for experimental investigations performed with large mammals in order to improve our understanding of natural variations of δ15N collagen

Parameter Estimation for Linear Compartmental Models—A Sensitivity Analysis Approach

International audienceLinear compartmental models are useful, explanatory tools, that have been widely used to represent the dynamic behavior of complex biological systems. This paper addresses the problem of the numerical identification of such models, i.e., the estimation of the parameter values that will generate predictions closest to experimental observations. Traditional local optimization techniques find it difficult to arrive at satisfactory solutions to such a parameter estimation problem, especially when the number of parameters is large and/or few data are available from experiments. We present herewith a method based on a prior sensitivity analysis, which enables division of a large optimization problem into several smaller and simpler subproblems, on which only sensitive parameters are estimated, before the whole optimization problem is tackled from starting points that are already close to the optimum values. This method has been applied successfully to a linear 13-compartment, 21-parameter model describing the postprandial metabolism of dietary nitrogen in humans. The effectiveness of the method has been demonstrated using simulated and real data obtained in the intestine, blood and urine of healthy humans after the ingestion of a [ 15 N]-labeled protein meal