Optimization of Protein Quality of Plant-Based Foods Through Digitalized Product Development.

With the increasing availability of plant-based protein products that should serve as alternatives to animal-based protein products, it is necessary to develop not only environmentally friendly but also nutritious foods. Especially the protein content and quality are of concern in these products. The algorithm of NutriOpt was developed using linear programming to support the development of food products with a balanced amino acid profile while considering digestibility. The current version contains a database with 84 plant protein sources from different food groups (legumes, cereals, nuts, seeds) and with different grades of purification (flours, concentrates, isolates) from which NutriOpt can create mixtures with high protein quality while complying with constraints such as protein content, number of ingredients, and weight of the mixture. The program was tested through different case studies based on commercial plant-based drinks. It was possible to obtain formulations with a Protein Digestibility Corrected Amino Acid Score (PDCAAS) over 100 with ingredients and quantities potentially suitable for plant-based analogs. Our model can help to develop the second generation of plant-based product alternatives that can really be used as an alternative on long-term consumption. Further, there is still a great potential of expansion of the program for example to use press cakes or even to model whole menus or diets in the future.

Protein Quality Changes of Vegan Day Menus with Different Plant Protein Source Compositions.

To underline the importance of protein quality in plant-based diets, we estimated the protein quality of different exclusively plant-protein-based day menus that are based on the "planetary health diet" developed by the EAT-Lancet Commission. PDCAAS and DIAAS were used to estimate the protein quality (PQ) and fulfilling of the amino acid recommendation for adults in vegan daily menus based on the planetary health diet: 2 days with only low-quality (LQ) protein sources and 2 days with low + high-quality (HQ) protein sources. The protein quality of Day 1LQ (DIAAS 76, PDCAAS 88) was increased by the addition of high-quality protein sources (HQPS): Day 1HQ (DIAAS 94, PDCAAS 98). Day 2LQ had a low PQ (DIAAS 71, PDCAAS 74), but when HQPS were used (Day 2HQ), the PQ increased (DIAAS 83, PDCAAS 88). Scenarios (day 1HQ, day 1LQ, and day 2 HQ) were classified as of good PQ. However, day 1LQ had a low protein quality. Consuming HQPS in a vegan diet can help to fulfil the recommendation of essential amino acids. This work served to understand and apply methods to estimate protein quality that can be applied to optimize protein mixtures to fulfil amino acid requirements in the future.

Serum Metabolites Responding in a Dose-Dependent Manner to the Intake of a High-Fat Meal in Normal Weight Healthy Men Are Associated with Obesity.

Although the composition of the human blood metabolome is influenced both by the health status of the organism and its dietary behavior, the interaction between these two factors has been poorly characterized. This study makes use of a previously published randomized controlled crossover acute intervention to investigate whether the blood metabolome of 15 healthy normal weight (NW) and 17 obese (OB) men having ingested three doses (500, 1000, 1500 kcal) of a high-fat (HF) meal can be used to identify metabolites differentiating these two groups. Among the 1024 features showing a postprandial response, measured between 0 h and 6 h, in the NW group, 135 were dose-dependent. Among these 135 features, 52 had fasting values that were significantly different between NW and OB men, and, strikingly, they were all significantly higher in OB men. A subset of the 52 features was identified as amino acids (e.g., branched-chain amino acids) and amino acid derivatives. As the fasting concentration of most of these metabolites has already been associated with metabolic dysfunction, we propose that challenging normal weight healthy subjects with increasing caloric doses of test meals might allow for the identification of new fasting markers associated with obesity.

Caloric dose-responsive genes in blood cells differentiate the metabolic status of obese men.

We have investigated the postprandial transcriptional response of blood cells to increasing caloric doses of a meal challenge to test whether the dynamic response of the human organism to the ingestion of food is dependent on metabolic health. The randomized crossover study included seven normal weight and seven obese men consuming three doses (500/1000/1500 kcal) of a high-fat meal. The blood cell transcriptome was measured before and 2, 4, and 6 h after meal ingestion (168 samples). We applied univariate and multivariate statistics to investigate differentially expressed genes in both study groups. We identified 624 probe sets that were up- or down-regulated after the caloric challenge in a dose-dependent manner. These transcripts were most responsive to the 1500 kcal challenge in the obese group and were associated with postprandial insulin and oxidative phosphorylation. Furthermore, the data revealed a separation of the obese group into individuals whose response was close to the normal weight group and individuals with a transcriptional response indicative of a loss of metabolic flexibility. The molecular signature provided by the postprandial transcriptomic response of blood cells to increasing caloric doses of a high-fat meal challenge may represent a sensitive way to evaluate the qualitative impact of food on human health.

A dose-response strategy reveals differences between normal-weight and obese men in their metabolic and inflammatory responses to a high-fat meal.

A dose-response strategy may not only allow investigation of the impact of foods and nutrients on human health but may also reveal differences in the response of individuals to food ingestion based on their metabolic health status. In a randomized crossover study, we challenged 19 normal-weight (BMI: 20-25 kg/m(2)) and 18 obese (BMI: >30 kg/m(2)) men with 500, 1000, and 1500 kcal of a high-fat (HF) meal (60.5% energy from fat). Blood was taken at baseline and up to 6 h postprandially and analyzed for a range of metabolic, inflammatory, and hormonal variables, including plasma glucose, lipids, and C-reactive protein and serum insulin, glucagon-like peptide-1, interleukin-6 (IL-6), and endotoxin. Insulin was the only variable that could differentiate the postprandial response of normal-weight and obese participants at each of the 3 caloric doses. A significant response of the inflammatory marker IL-6 was only observed in the obese group after ingestion of the HF meal containing 1500 kcal [net incremental AUC (iAUC) = 22.9 ± 6.8 pg/mL × 6 h, P = 0.002]. Furthermore, the net iAUC for triglycerides significantly increased from the 1000 to the 1500 kcal meal in the obese group (5.0 ± 0.5 mmol/L × 6 h vs. 6.0 ± 0.5 mmol/L × 6 h; P = 0.015) but not in the normal-weight group (4.3 ± 0.5 mmol/L × 6 h vs. 4.8 ± 0.5 mmol/L × 6 h; P = 0.31). We propose that caloric dose-response studies may contribute to a better understanding of the metabolic impact of food on the human organism. This study was registered at clinicaltrials.gov as NCT01446068.

Validation of an in vitro digestive system for studying macronutrient decomposition in humans.

The digestive process transforms nutrients and bioactive compounds contained in food to physiologically active compounds. In vitro digestion systems have proven to be powerful tools for understanding and monitoring the complex transformation processes that take place during digestion. Moreover, the investigation of the physiological effects of certain nutrients demands an in vitro digestive process that is close to human physiology. In this study, human digestion was simulated with a 3-step in vitro process that was validated in depth by choosing pasteurized milk as an example of a complex food matrix. The evolution and decomposition of the macronutrients was followed over the entire digestive process to the level of intestinal enterocyte action, using protein and peptide analysis by SDS-PAGE, reversed-phase HPLC, size exclusion HPLC, and liquid chromatography-MS. The mean peptide size after in vitro digestion of pasteurized milk was 5-6 amino acids (AA). Interestingly, mostly essential AA (93.6%) were released during in vitro milk digestion, a significantly different relative distribution compared to the total essential AA concentration of bovine milk (44.5%). All TG were degraded to FFA and monoacylglycerols. Herein, we present a human in vitro digestion model validated for its ability to degrade the macronutrients of dairy products comparable to physiological ranges. It is suited to be used in combination with a human intestinal cell culture system, allowing ex vivo bioavailability measurements and assessment of the bioactive properties of food components.