Search

Dietary proteins are energy macronutrients providing nitrogen, amino acids (AA), and energy. AAs are the main nitrogen-containing compounds in the body and are the precursors for the synthesis of body proteins and of several other AA-derived molecules. Among the 20 AAs included in protein sequence, 9 are classified as “nutritionally essential” or “indispensable” AA (IAA) because they cannot be synthesized in the body and must be provided by the diet. IAAs are limiting components for protein synthesis. An adequate intake of protein is required to support growth, maintenance, body functions, health and survival. Official definition of protein requirement is based on nitrogen balance. Protein quality is related to the capacity of protein to provide an adequate quantity of nitrogen and of each of the 9 IAAs for the different physiological situations in humans. Protein source is considered high quality for humans when the protein is readily digested, simultaneously providing an adequate quantity of nitrogen and of each of the 9 IAAs to maintain an adequate metabolic AA pool. The most accurate assessment of protein quality of foods for humans is through metabolic studies that measure nitrogen balance. The protein quality score is the ratio of the content of each IAA in the food and in a reference profile. This score corresponds to the calculated composition of a protein which, when meeting protein requirements, simultaneously meets the requirements of each of the 9 IAAs. AA scores as predictors of protein quality must be adjusted for protein and AA availability.

In the context of dietary transition toward plant proteins, it is necessary to ensure protein security in populations. It would thus be of interest to identify biomarkers of altered protein digestibility in populations. We examined the association between urinary metabolites and the acute intake of low- or highly digestible protein in healthy volunteers. The urine samples were collected before and 9 h after the ingestion of a meal containing either no protein, zein (low-digestible) or whey protein isolate (highly digestible). The liquid chromatography–high resolution mass spectrometry metabolomics approach was used for the profiling of the urinary metabolites. For the standardization of metabolomics data sets, osmolality-based, standard normal variates (SNV) and probabilistic quotient normalization (PQN) techniques were used. The ANOVA-based factorial method, AComDim_ICA, was used for chemometrics analysis. The osmolality adjustment has a beneficial effect and the subsequent mathematical normalization improves the chemometric analysis further. Some changes in the urinary metabolomes were observed 9 h after the meal in the three groups. However, there was no difference in the urine metabolome between groups. No biomarker of protein digestibility can be identified after the ingestion of a single meal, even when marked differences in the digestion efficiency of protein have been observed.

The rat model can be used to assess ileal protein digestibility rapidly and in first intention, but no standardised method exists. Our objective was to compare methods to assess protein digestibility, depending on collection site (ileum/caecum) and use of a non-absorbable marker. A meal containing either casein, gluten or pea protein and chromium oxide as non-absorbable marker was given to male Wistar rats and the entire digestive content was collected 6 h later. Total chromium recovery was incomplete and variable, depending on protein source. We observed no significant difference in digestibility between the methods for any of the protein sources tested. Although none of the methods tested is optimal, our results suggest that caecal digestibility can be used as a proxy of ileal digestibility in rats without using a non-absorbable marker. This simple method makes it possible to evaluate protein digestibility of new alternative protein sources for human consumption.

Binge eating (BE) is characterized by the consumption of large amounts of palatable food in a discrete period and compulsivity. Even though BE is a common symptom in bulimia nervosa (BN), binge eating disorder (BED), and some cases of other specified feeding or eating disorders, little is known about its pathophysiology. We aimed to identify brain regions and neuron subtypes implicated in the development of binge-like eating in a female rat model. We separated rats into binge eating prone (BEP) and binge eating resistant (BER) phenotypes based on the amount of sucrose they consumed following foot-shock stress. We quantified deltaFosB (ΔFosB) expression, a stably expressed Fos family member, in different brain regions involved in reward, taste, or stress processing, to assess their involvement in the development of the phenotype. The number of ΔFosB-expressing neurons was: (1) higher in BEP than BER rats in reward processing areas [medial prefrontal cortex (mPFC), nucleus accumbens (Acb), and ventral tegmental area (VTA)]; (2) similar in taste processing areas [insular cortex, IC and parabrachial nucleus (PBN)]; and (3) higher in the paraventricular nucleus of BEP than BER rats, but not different in the locus coeruleus (LC), which are stress processing structures. To study subtypes of ΔFosB-expressing neurons in the reward system, we performed in situ hybridization for glutamate decarboxylase 65 and tyrosine hydroxylase (TH) mRNA after ΔFosB immunohistochemistry. In the mPFC and Acb, the proportions of γ-aminobutyric acidergic (GABAergic) and non-GABAergic ΔFosB-expressing neurons were similar in BER and BEP rats. In the VTA, while the proportion of dopaminergic ΔFosB-expressing neurons was similar in both phenotypes, the proportion of GABAergic ΔFosB-expressing neurons was higher in BER than BEP rats. Our results suggest that reward processing brain regions, particularly the VTA, are important for the development of binge-like eating.

ABSTRACT Adequate protein intake during development is critical to ensure optimal bone gain and to attain a higher peak bone mass later. Using a mild protein restriction model in Balb/C mice consuming 6% of their total energy intake as soy protein (LP‐SOY)—for which we observed a significantly lower femoral cortical thickness, bone volume, trabecular number, and thickness reduction—we evaluated the effects of monosodium glutamate (MSG) supplementation at different concentrations (0.5, 1, 5, 10, and 20 g/kg of diet) on bone characteristics in LP‐SOY‐fed mice. After 6 and 12 weeks, LP‐SOY‐fed mice had lower BMD and reduced body weight related to lower lean mass, which was associated with a reduced IGF‐1 level. The negative effect of the LP‐SOY diet on BMD correlated with impaired bone formation. MSG supplementation, at 5, 10, and 20 g/kg of diet, and PTH injection, used as a positive control, were able to improve BMD and to increase osteoblast activity markers (P1NP and osteocalcin), as well as glutamine plasma concentration. An analysis of bone microarchitecture found that cortical bone was less sensitive to protein restriction than trabecular bone, and that MSG ingestion was able to preserve bone quality through an increase of collagen synthesis, although it did not allow normal bone growth. Our study reinforces the view that glutamate can act as a functional amino acid for bone physiology and support clinical investigation of glutamate supplementation in adults characterized by poor bone status, notably as a result of insufficient protein intake. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

Although animal trials are the most accurate approach to determine the metabolisable energy (ME) content of pet food, these are expensive and labour-intensive. Instead, various equations have been proposed to predict ME content, but no single method is universally recommended. Data from canine and feline feeding studies, conducted according to Association of American Feed Control Officials recommendations, over a 6-year period at a single research site, were utilised to determine the performance of different predictive equations. Predictive equations tested included the modified Atwater (MA equation), NRC 2006 equations using both crude fibre (NRC 2006cf) and total dietary fibre (NRC 2006tdf), and new equations reported in the most recent study assessing ME predictive equations (Hall equations; PLoS ONE 8(1): e54405). Where appropriate, equations were tested using both predicted gross energy (GE) and GE measured by bomb calorimetry. Associations between measured and predicted ME were compared with Deming regression, whilst agreement was assessed with Bland-Altman plots. 335 feeding trials were included, comprising 207 canine (182 dry food; 25 wet food) and 128 feline trials (104 dry food, 24 wet food). Predicted ME was positively associated with measured ME whatever the equation used (P