Polyphenols, a complex group of secondary plant metabolites, including flavonoids and phenolic acids, have been studied in depth for their health-related benefits. The activity of polyphenols may, however, be hampered when consumed together with protein-rich food products, due to the interaction between polyphenols and proteins. To that end we have tested the bioavailability of representatives of a range of polyphenol classes when consumed for five days in different beverage matrices. In a placebo-controlled, randomized, cross-over study, 35 healthy males received either six placebo gelatine capsules consumed with 200 mL of water, six capsules with 800 mg polyphenols derived from red wine and grape extracts, or the same dose of polyphenols incorporated into 200 mL of either pasteurized dairy drink, soy drink (both containing 3.4% proteins) or fruit-flavoured protein-free drink . At the end of the intervention urine and blood was collected and analysed for a broad range of phenolic compounds using Gas Chromatography–Mass Spectrometry (GC-MS), Liquid Chromatography–Multiple Reaction Monitoring–Mass Spectrometry (LC-MRM-MS), and Nuclear Magnetic Resonance (NMR) spectroscopy techniques. The plasma and urine concentrations of the polyphenols identified increased with all formats, including the protein-rich beverages. Compared to capsule ingestion, consumption of polyphenol-rich beverages containing either dairy, soy or no proteins had minor to no effect on the bioavailability and excretion of phenolic compounds in plasma (118% ± 9%) and urine (98% ± 2%). We conclude that intake of polyphenols incorporated in protein-rich drinks does not have a major impact on the bioavailability of a range of different polyphenols and phenolic metabolites.

Peptides are an important group of compounds contributing to the desired, as well as the undesired taste of a food product. Their taste impressions can include aspects of sweetness, bitterness, savoury, umami and many other impressions depending on the amino acids present as well as their sequence. Identification of short peptides in foods is challenging. We developed a method to assign identities to short peptides including homologous structures, i.e. peptides containing the same amino acids with a different sequence order, by accurate prediction of the retention times during reversed phase separation. To train the method, a large set of well-defined short peptides with systematic variations in the amino acid sequence was prepared by a novel synthesis strategy called ‘swapped-sequence synthesis’. Additionally, several proteins were enzymatically digested to yield short peptides. Experimental retention times were determined after reversed phase separation and peptide MS² data was acquired using a high-resolution mass spectrometer operated in data-dependent acquisition mode (DDA). A support vector regression model was trained using a combination of existing sequence-independent peptide descriptors and a newly derived set of selected amino acid index derived sequence-specific peptide (ASP) descriptors. The model was trained and validated using the experimental retention times of the 713 small food-relevant peptides prepared. Whilst selecting the most useful ASP descriptors for our model, special attention was given to predict the retention time differences between homologous peptide structures. Inclusion of ASP descriptors greatly improved the ability to accurately predict retention times, including retention time differences between 157 homologous peptide pairs. The final prediction model had a goodness-of-fit (Q²) of 0.94; moreover for 93% of the short peptides, the elution order was correctly predicted. Graphical abstract

Faba bean (Vicia faba L.) is a valuable ingredient in plant-based foods such as meat and dairy analogues. However, its typical taste and aroma are considered off-flavours in these food applications, representing a bottleneck during processing. Breeding is needed to develop varieties with minimal off-flavours and high protein content. The genetic regulation of these traits is underexplored. To dissect their genetic architecture, we performed a genome-wide association study (GWAS). A total of 245 faba bean accessions (the CGN population) were genotyped using the 90K-SPET targeted assay. These accessions were phenotyped in 2021 and 2022 in the Netherlands for protein, oil, fatty acids, lipid-derived products, phenolic acids, flavonoids, and tannins. The CGN population showed large phenotypic variation and moderate-to-high narrow-sense heritability for most traits. The growing environment significantly affected all traits, with trait-specific genotype-by-year (GxY) interactions. Condensed tannins and fatty acids were the most stable across the two years and had the highest heritability estimates (h² > 0.6). GWAS identified a total of 148 single nucleotide polymorphisms (SNPs) loci in 2021 and 167 in 2022. Key candidate regulators included genes involved in lipid biosynthesis (ATS2, KAS, LPP), amino acid transport (CAT4) for protein storage, zero tannins locus-1 (zt-1), and regulators of the phenylpropanoid pathway, such as a shikimate kinase gene and transcription factors bHLH137-like and MYB. These results pave the way for validation studies and biotechnological applications to improve the quality of faba bean-based foods.