Vicia faba Peptide Network Supplementation Does Not Differ From Milk Protein in Modulating Changes in Muscle Size During Short-Term Immobilization and Subsequent Remobilization, but Increases Muscle Protein Synthesis Rates During Remobilization in Healthy Young Men.

BACKGROUND: Muscle mass and strength decrease during short periods of immobilization and slowly recover during remobilization. Recent artificial intelligence applications have identified peptides that appear to possess anabolic properties in in vitro assays and murine models. OBJECTIVES: This study aimed to compare the impact of Vicia faba peptide network compared with milk protein supplementation on muscle mass and strength loss during limb immobilization and regain during remobilization. METHODS: Thirty young (24 ± 5 y) men were subjected to 7 d of one-legged knee immobilization followed by 14 d of ambulant recovery. Participants were randomly allocated to ingest either 10 g of the Vicia faba peptide network (NPN_1; n = 15) or an isonitrogenous control (milk protein concentrate; MPC; n = 15) twice daily throughout the study. Single-slice computed tomography scans were performed to assess quadriceps cross-sectional area (CSA). Deuterium oxide ingestion and muscle biopsy sampling were applied to measure myofibrillar protein synthesis rates. RESULTS: Leg immobilization decreased quadriceps CSA (primary outcome) from 81.9 ± 10.6 to 76.5 ± 9.2 cm2 and from 74.8 ± 10.6 to 71.5 ± 9.8 cm2 in the NPN_1 and MPC groups, respectively (P < 0.001). Remobilization partially recovered quadriceps CSA (77.3 ± 9.3 and 72.6 ± 10.0 cm2, respectively; P = 0.009), with no differences between the groups (P > 0.05). During immobilization, myofibrillar protein synthesis rates (secondary outcome) were lower in the immobilized leg (1.07% ± 0.24% and 1.10% ± 0.24%/d, respectively) than in the non-immobilized leg (1.55% ± 0.27% and 1.52% ± 0.20%/d, respectively; P < 0.001), with no differences between the groups (P > 0.05). During remobilization, myofibrillar protein synthesis rates in the immobilized leg were greater with NPN_1 than those with MPC (1.53% ± 0.38% vs. 1.23% ± 0.36%/d, respectively; P = 0.027). CONCLUSION: NPN_1 supplementation does not differ from milk protein in modulating the loss of muscle size during short-term immobilization and the regain during remobilization in young men. NPN_1 supplementation does not differ from milk protein supplementation in modulating the myofibrillar protein synthesis rates during immobilization but further increases myofibrillar protein synthesis rates during remobilization.

Preclinical Evaluation of a Food-Derived Functional Ingredient to Address Skeletal Muscle Atrophy.

Skeletal muscle is the metabolic powerhouse of the body, however, dysregulation of the mechanisms involved in skeletal muscle mass maintenance can have devastating effects leading to many metabolic and physiological diseases. The lack of effective solutions makes finding a validated nutritional intervention an urgent unmet medical need. In vitro testing in murine skeletal muscle cells and human macrophages was carried out to determine the effect of a hydrolysate derived from vicia faba (PeptiStrong: NPN_1) against phosphorylated S6, atrophy gene expression, and tumour necrosis factor alpha (TNF-α) secretion, respectively. Finally, the efficacy of NPN_1 on attenuating muscle waste in vivo was assessed in an atrophy murine model. Treatment of NPN_1 significantly increased the phosphorylation of S6, downregulated muscle atrophy related genes, and reduced lipopolysaccharide-induced TNF-α release in vitro. In a disuse atrophy murine model, following 18 days of NPN_1 treatment, mice exhibited a significant attenuation of muscle loss in the soleus muscle and increased the integrated expression of Type I and Type IIa fibres. At the RNA level, a significant upregulation of protein synthesis-related genes was observed in the soleus muscle following NPN_1 treatment. In vitro and preclinical results suggest that NPN_1 is an effective bioactive ingredient with great potential to prolong muscle health.

An Artificial Intelligence Characterised Functional Ingredient, Derived from Rice, Inhibits TNF-α and Significantly Improves Physical Strength in an Inflammaging Population.

Food-derived bioactive peptides offer great potential for the treatment and maintenance of various health conditions, including chronic inflammation. Using in vitro testing in human macrophages, a rice derived functional ingredient natural peptide network (NPN) significantly reduced Tumour Necrosis Factor (TNF)-α secretion in response to lipopolysaccharides (LPS). Using artificial intelligence (AI) to characterize rice NPNs lead to the identification of seven potentially active peptides, the presence of which was confirmed by liquid chromatography tandem mass spectrometry (LC-MS/MS). Characterization of this network revealed the constituent peptides displayed anti-inflammatory properties as predicted in vitro. The rice NPN was then tested in an elderly "inflammaging" population with a view to subjectively assess symptoms of digestive discomfort through a questionnaire. While the primary subjective endpoint was not achieved, analysis of objectively measured physiological and physical secondary readouts showed clear significant benefits on the ability to carry out physical challenges such as a chair stand test that correlated with a decrease in blood circulating TNF-α. Importantly, the changes observed were without additional exercise or specific dietary alterations. Further health benefits were reported such as significant improvement in glucose control, a decrease in serum LDL concentration, and an increase in HDL concentration; however, this was compliance dependent. Here we provide in vitro and human efficacy data for a safe immunomodulatory functional ingredient characterized by AI.

Following the digestion of milk proteins from mother to baby.

Little is known about the digestive process in infants. In particular, the chronological activity of enzymes across the course of digestion in the infant remains largely unknown. To create a temporal picture of how milk proteins are digested, enzyme activity was compared between intact human milk samples from three mothers and the gastric samples from each of their 4-12 day postpartum infants, 2 h after breast milk ingestion. The activities of 7 distinct enzymes are predicted in the infant stomach based on their observed cleavage pattern in peptidomics data. We found that the same patterns of cleavage were evident in both intact human milk and gastric milk samples, demonstrating that the enzyme activities that begin in milk persist in the infant stomach. However, the extent of enzyme activity is found to vary greatly between the intact milk and gastric samples. Overall, we observe that milk-specific proteins are cleaved at higher levels in the stomach compared to human milk. Notably, the enzymes we predict here only explain 78% of the cleavages uniquely observed in the gastric samples, highlighting that further investigation of the specific enzyme activities associated with digestion in infants is warranted.

A peptidomic analysis of human milk digestion in the infant stomach reveals protein-specific degradation patterns.

In vitro digestion of isolated milk proteins results in milk peptides with a variety of actions. However, it remains unclear to what degree protein degradation occurs in vivo in the infant stomach and whether peptides previously annotated for bioactivity are released. This study combined nanospray LC separation with time-of-flight mass spectrometry, comprehensive structural libraries, and informatics to analyze milk from 3 human mothers and the gastric aspirates from their 4- to 12-d-old postpartum infants. Milk from the mothers contained almost 200 distinct peptides, demonstrating enzymatic degradation of milk proteins beginning either during lactation or between milk collection and feeding. In the gastric samples, 649 milk peptides were identified, demonstrating that digestion continues in the infant stomach. Most peptides in both the intact milk and gastric samples were derived from ß-casein. The numbers of peptides from ß-casein, lactoferrin, α-lactalbumin, lactadherin, κ-casein, serum albumin, bile salt-associated lipase, and xanthine dehydrogenase/oxidase were significantly higher in the gastric samples than in the milk samples (P < 0.05). A total of 603 peptides differed significantly in abundance between milk and gastric samples (P < 0.05). Most of the identified peptides have previously identified biologic activity. Gastric proteolysis occurs in the term infant in the first 2 wk of life, releasing biologically active milk peptides with immunomodulatory and antibacterial properties of clinical relevance to the proximal intestinal tract. Data are available via ProteomeXchange (identifier PXD000688).

EnzymePredictor: a tool for predicting and visualizing enzymatic cleavages of digested proteins.

Mass spectrometric analysis of peptides contained in enzymatically digested hydrolysates of proteins is increasingly being used to characterize potentially bioactive or otherwise interesting hydrolysates. However, when preparations containing mixtures of enzymes are used, from either biological or experimental sources, it is unclear which of these enzymes have been most important in hydrolyzing the sample. We have developed a tool to rapidly evaluate the evidence for which enzymes are most likely to have cleaved the sample. EnzymePredictor, a web-based software, has been developed to (i) identify the protein sources of fragments found in the hydrolysates and map them back on it, (ii) identify enzymes that could yield such cleavages, and (iii) generate a colored visualization of the hydrolysate, the source proteins, the fragments, and the predicted enzymes. It tabulates the enzymes ranked according to their cleavage counts. The provision of odds ratio and standard error in the table permits users to evaluate how distinctively particular enzymes may be favored over other enzymes as the most likely cleavers of the samples. Finally, the method displays the cleavage not only according to peptides, but also according to proteins, permitting evaluation of whether the cleavage pattern is general across all proteins, or specific to a subset. We illustrate the application of this method using milk hydrolysates, and show how it can rapidly identify the enzymes or enzyme combinations used in generating the peptides. The approach developed here will accelerate the identification of enzymes most likely to have been used in hydrolyzing a set of mass spectrometrically identified peptides derived from proteins. This has utility not only in understanding the results of mass spectrometry experiments, but also in choosing enzymes likely to yield similar cleavage patterns. EnzymePredictor can be found at http://bioware.ucd.ie/∼enzpred/Enzpred.php.