Bioactive milk peptides: an updated comprehensive overview and database

Bioactive Dairy-Fermented Products and Phenolic Compounds: Together or Apart

Fermented dairy products (e.g., yogurt, kefir, and buttermilk) are significant in the dairy industry. They are less immunoreactive than the raw materials from which they are derived. The attractiveness of these products is based on their bioactivity and properties that induce immune or anti-inflammatory processes. In the search for new solutions, plant raw materials with beneficial effects have been combined to multiply their effects or obtain new properties. Polyphenols (e.g., flavonoids, phenolic acids, lignans, and stilbenes) are present in fruit and vegetables, but also in coffee, tea, or wine. They reduce the risk of chronic diseases, such as cancer, diabetes, or inflammation. Hence, it is becoming valuable to combine dairy proteins with polyphenols, of which epigallocatechin-3-gallate (EGCG) and chlorogenic acid (CGA) show a particular predisposition to bind to milk proteins (e.g., α-lactalbumin β-lactoglobulin, αs1-casein, and κ-casein). Reducing the allergenicity of milk proteins by combining them with polyphenols is an essential issue. As potential 'metabolic prebiotics', they also contribute to stimulating the growth of beneficial bacteria and inhibiting pathogenic bacteria in the human gastrointestinal tract. In silico methods, mainly docking, assess the new structures of conjugates and the consequences of the interactions that are formed between proteins and polyphenols, as well as to predict their action in the body.

Exploring novel ANGICon-EIPs through ameliorated peptidomics techniques: Can deep learning strategies as a core breakthrough in peptide structure and function prediction?

Dairy-derived angiotensin-I-converting enzyme inhibitory peptides (ANGICon-EIPs) have been regarded as a relatively safe supplementary diet-therapy strategy for individuals with hypertension, and short-chain peptides may have more relevant antihypertensive benefits due to their direct intestinal absorption. Our previous explorations have confirmed that endogenous goat milk short-chain peptides are also an essential source of ANGICon-EIPs. Nonetheless, there are limited explorations on endogenous ANGICon-EIPs owing to the limitations of the extraction and enrichment of endogenous peptides, currently. This review outlined ameliorated pre-treatment strategies, data acquisition methods, and tools for the prediction of peptide structure and function, aiming to provide creative ideas for discovering novel ANGICon-EIPs. Currently, deep learning-based peptide structure and function prediction algorithms have achieved significant advancements. The convolutional neural network (CNN) and peptide sequence-based multi-label deep learning approach for determining the multi-functionalities of bioactive peptides (MLBP) can predict multiple peptide functions with absolute true value and accuracy of 0.699 and 0.708, respectively. Utilizing peptide sequence input, torsion angles, and inter-residue distance to train neural networks, APPTEST predicted the average backbone root mean square deviation (RMSD) value of peptide (5-40 aa) structures as low as 1.96 Å. Overall, with the exploration of more neural network architectures, deep learning could be considered a critical research tool to reduce the cost and improve the efficiency of identifying novel endogenous ANGICon-EIPs.

Milk fat globule size: Unraveling the intricate relationship between metabolism, homeostasis, and stress signaling

Fat is an important component of milk which delivers energy, nutrients, and bioactive molecules from the lactating mother to the suckling neonate. Milk fat consists of a complex mixture of different types of lipids; hundreds of fatty acids, triglycerides, phospholipids, sphingolipids, cholesterol and cholesteryl ester, and glycoconjugates, secreted by the mammary gland epithelial cells (MEC) in the form of a lipid-protein assembly termed the milk fat globule (MFG). The mammary gland in general, and specifically that of modern dairy cows, faces metabolic stress once lactation commences, which changes the lipogenic capacity of MECs directly by reducing available energy and reducing factors required for both lipid synthesis and secretion or indirectly by activating a proinflammatory response. Both processes have the capacity to change the morphometric features (e.g., number and size) of the secreted MFG and its precursor-the intracellular lipid droplet (LD). The MFG size is tightly associated with its lipidome and proteome and also affects the bioavailability of milk fat and protein. Thus, MFG size has the potential to regulate the bioactivity of milk and dairy products. MFG size also plays a central role in the functional properties of milk and dairy products such as texture and stability. To understand how stress affects the structure-function of the MFG, we cover: (i) The mechanism of production and secretion of the MFG and the implications of MFG size, (ii) How the response mechanisms to stress can change the morphometric features of MFGs, and (iii) The possible consequences of such modifications.

Fingerprinting of Proteases, Protease Inhibitors and Indigenous Peptides in Human Milk

The presence of proteases and their resulting level of activity on human milk (HM) proteins may aid in the generation of indigenous peptides as part of a pre-digestion process, of which some have potential bioactivity for the infant. The present study investigated the relative abundance of indigenous peptides and their cleavage products in relation to the abundance of observed proteases and protease inhibitors. The proteomes and peptidomes in twelve HM samples, representing six donors at lactation months 1 and 3, were profiled. In the proteome, 39 proteases and 29 protease inhibitors were identified in 2/3 of the samples. Cathepsin D was found to be present in higher abundance in the proteome compared with plasmin, while peptides originating from plasmin cleavage were more abundant than peptides from cathepsin D cleavage. As both proteases are present as a system of pro- and active- forms, their activation indexes were calculated. Plasmin was more active in lactation month 3 than month 1, which correlated with the total relative abundance of the cleavage product ascribed to plasmin. By searching the identified indigenous peptides in the milk bioactive peptide database, 283 peptides were ascribed to 10 groups of bioactivities. Antimicrobial peptides were significantly more abundant in month 1 than month 3; this group comprised 103 peptides, originating from the β-CN C-terminal region.