Prenylation of aromatic amino acids and plant phenolics by an aromatic prenyltransferase from Rasamsonia emersonii.

Dimethylallyl tryptophan synthases (DMATSs) are aromatic prenyltransferases that catalyze the transfer of a prenyl moiety from a donor to an aromatic acceptor during the biosynthesis of microbial secondary metabolites. Due to their broad substrate scope, DMATSs are anticipated as biotechnological tools for producing bioactive prenylated aromatic compounds. Our study explored the substrate scope and product profile of a recombinant RePT, a novel DMATS from the thermophilic fungus Rasamsonia emersonii. Among a variety of aromatic substrates, RePT showed the highest substrate conversion for L-tryptophan and L-tyrosine (> 90%), yielding two mono-prenylated products in both cases. Nine phenolics from diverse phenolic subclasses were notably converted (> 10%), of which the stilbenes oxyresveratrol, piceatannol, pinostilbene, and resveratrol were the best acceptors (37-55% conversion). The position of prenylation was determined using NMR spectroscopy or annotated using MS2 fragmentation patterns, demonstrating that RePT mainly catalyzed mono-O-prenylation on the hydroxylated aromatic substrates. On L-tryptophan, a non-hydroxylated substrate, it preferentially catalyzed C7 prenylation with reverse N1 prenylation as a secondary reaction. Moreover, RePT also possessed substrate-dependent organic solvent tolerance in the presence of 20% (v/v) methanol or DMSO, where a significant conversion (> 90%) was maintained. Our study demonstrates the potential of RePT as a biocatalyst for the production of bioactive prenylated aromatic amino acids, stilbenes, and various phenolic compounds. KEY POINTS: • RePT catalyzes prenylation of diverse aromatic substrates. • RePT enables O-prenylation of phenolics, especially stilbenes. • The novel RePT remains active in 20% methanol or DMSO.

Towards absolute quantification of protein genetic variants in Pisum sativum extracts.

In recent years, several studies have used proteomics approaches to characterize genetic variant profiles of agricultural raw materials. In such studies, the challenge is the quantification of the individual protein variants. In this study a novel UPLC-PDA-MS method with absolute and label-free UV-based peptide quantification was applied to quantify the genetic variants of legumin, vicilin and albumins in pea extracts. The aim was to investigate the applicability of this method and to identify challenges in determining protein concentration from the measured peptide concentrations. Analysis of the protein mass balance showed significant losses of proteins in extraction (37%) and of peptides in further sample preparation (69%). The challenge in calculating the extractable individual protein concentrations was how to deal with these insoluble peptides. The quantification approach using average amino acid concentrations in each position of the sequence showed most reproducible results and allowed comparison of the genetic protein composition of 8 different cultivars. The extractable protein composition (µM/µM) was remarkably similar for all cultivar extracts and consisted of legumins A1 (12.8 ± 1.2%), A2 (1.1 ± 0.4%), B (9.9 ± 1.6%), J (7.5 ± 1.0%) and K (10.3 ± 2.1%), vicilin (15.2 ± 1.7%), provicilin (15.7 ± 2.5%), convicilin (9.8 ± 0.8%), albumin A1 (7.4 ± 2.0%), albumin 2 (10.0 ± 1.5%) and protease inhibitor (0.4 ± 0.4%).

The path of proteolysis by bovine chymotrypsin.

Chymotrypsin is one of the major proteases in intestinal protein digestion. Observations about the type of bonds that are hydrolysed (specificity and preference) were in the past derived from the peptide composition after digestion or hydrolysis rates of synthetic peptides. In this study, the path of hydrolysis by bovine chymotrypsin, i.e formation and degradation of peptides, were described for α-lactalbumin, ß-lactoglobulin and ß-casein. The peptide compositions, determined with UPLC-PDA-MS at different time points were used to determine the digestion kinetics for individual cleavage sites. It was evaluated how statements on (secondary) specificity from literature were reflected in the release kinetics of peptides. ß-Lactoglobulin reached the highest degree of hydrolysis (10.9 ± 0.1 %) and was hydrolysed fastest (28 ± 1 mMpeptide bonds/s/mMenzyme), regardless of its globular (tertiary) structure. Chymotrypsin showed a preference towards aromatic amino acids, methionine and leucine, but was also tolerant to other amino acids. For the cleavage sites within this preference, Ì´73% of the cleavage sites were hydrolysed with high or intermediate selectivity. For the missed cleavages within the preference, 45 % was explained by hindrance of proline, which affected hydrolysis only when in positions P3, P1' or P2'. No clear indication (based on primary structure) was found to explain the other missed cleavages. A few cleavage sites were hydrolysed extremely efficient in α-lactalbumin (F9, F31, W104) and ß-casein (W143, L163, F190). This study gave unique and quantitative insight in peptide formation and degradation by chymotrypsin in the digestion of proteins. The approach used showed potential to explore the path of hydrolysis for other proteases with less defined specificity.

A method to identify and quantify the complete peptide composition in protein hydrolysates.

Automated approaches from proteomics are used to characterise peptides for food applications and in protein digests. Peptide annotations and confidence in these annotations are then based on the fragment spectra. Low reproducibility in repeat analyses has been reported even for annotations with high confidence. When analysing protein hydrolysates (in food) it is important to determine criteria that yield highly reproducible annotations. This study provides a structured approach to determine these criteria. Tryptic hydrolysates of α-lactalbumin, ß-lactoglobulin and ß-casein were analysed manually and automatically, using an UPLC-PDA-MS method for untargeted identification and absolute label-free quantification of peptides. A lock mass with two components was introduced resulting in an average mass error of 1 ppm. Processing filters were set to ensure reliable annotations based on MS/MS fragmentation, while maintaining maximum amount of information. Peptides in the individual hydrolysates with an MS intensity above the limit of annotation represented 99% of total MS intensity and were 100% consistently annotated between four replicates. Amino acid and peptide sequence coverages for the individual protein hydrolysates were 99-100% and 89-95%, respectively. Mixing the hydrolysates resulted in a loss of 11% of the peptide annotations above the LOA and lower reproducibility (97%) for the remaining annotations, as well as more co-eluting peptides. Calculated concentrations of co-eluting peptides in mixed hydrolysates varied 37 ± 21% from the value for single hydrolysates. The proposed approach allows complete description of peptide composition with highly repeatable annotations and quantification of peptides even in mixed hydrolysates.