Comprehensive species- and processing-specific peptide profiling of pasteurized, extended shelf-life and ultra-high temperature milk from cow, goat, sheep, buffalo, and mare.

The present study aimed to identify endogenous milk peptides for species differentiation independent of heat exposure. Thus, comprehensive milk peptide profiles from five species and three types of heat treatments were analyzed by micro-flow liquid chromatography ion mobility quadrupole time-of-flight mass spectrometry (microLC-IM-QTOF) with subsequent database search leading to ≥ 3000 identified peptides. In the milks, 1154 peptides were unique for cow, 712 for sheep, 466 for goat, 197 for buffalo, and 69 for mare. Most peptides were detected in extended-shelf life (ESL) milk (2010), followed by ultra-high temperature (UHT) processed (1474) and pasteurized milk (1459 peptides), with 693 peptides present in all milk types. A blind test set of 64 samples confirmed eight species-specific, but heat-independent marker peptides in milk from cow, seven from goat, six from sheep, nine from buffalo, and three from mare. The generated peptide profiles can also be used to identify species- and heat-specific markers.

Effects of gelatin concentration, adding temperature and mixing rate on texture and quality characteristics of model gels.

In this study, the effects of gelatin concentrations (GC) (5.0-10.0 g/100 g), mixing rate (MR) (100-1100 rpm), and gelatin addition temperature (GAT) (55, 60, and 65°C) were investigated on the main textural and various physicochemical properties of model gels (n = 72) prepared using sucrose and glucose syrup (40-42 DE). Considering the p-value of the F-statistic calculated by analysis of variance and the 5% significance level, the production parameters and their interactions had a significant effect on the quality parameters. The influence of the production parameters GC, MR, and GAT, and the interaction of these parameters, GC * MR, GC * GAT, MR * GAT, and GC * MR * GAT of the model gels on the quality characteristic were expressed by converting the Type III SS values into percent values. When all quality characteristics were considered together, MR was the most influential with a score of 58%. PCAmix, a combination of factorial analysis with PCA, was used to visualize the correlations between the production parameters and the quality characteristics of the modeled gels. A great influence was observed between MR and moisture content, color properties, and texture parameters, except springiness. A moderate effect of GC and a minor effect of GAT could be characterized. With the 2D-map of observations, the model gels could be clearly divided into two groups according to the MRs. In accordance with the observations diagram of PCAmix, the similarity dendrogram of AHC also formed two clusters, one cluster for the samples with MR 100 and 200 rpm and one cluster for the samples with MR 500 and 1100 rpm.

Identification of Potential Bioactive Peptides in Sheep Milk Kefir through Peptidomic Analysis at Different Fermentation Times.

Sheep farming is an important socioeconomic activity in most Mediterranean countries, particularly Spain, where it contributes added value to rural areas. Sheep milk is used in Spain mainly for making cheese, but it can be used also for making other dairy products, such as the lactic-alcoholic fermentation product known as kefir. Dairy products have health benefits because, among other reasons, they contain molecules with biological activity. In this work, we performed a proteomics strategy to identify the peptidome, i.e., the set of peptides contained in sheep milk kefir fermented for four different periods of time, aiming to understand changes in the pattern of digestion of milk proteins, as well as to identify potential bioactive peptides. In total, we identified 1942 peptides coming from 11 different proteins, and found that the unique peptides differed qualitatively among samples and their numbers increased along the fermentation time. These changes were supported by the increase in ethanol, lactic acid, and D-galactose concentrations, as well as proteolytic activity, as the fermentation progressed. By searching in databases, we found that 78 of the identified peptides, all belonging to caseins, had potential biological activity. Of these, 62 were not previously found in any milk kefir from other animal species. This is the first peptidomic study of sheep milk kefir comprising time-course comparison.

Cocoa polyphenols and milk proteins: covalent and non-covalent interactions, chocolate process and effects on potential polyphenol bioaccesibility.

In this study, we discussed covalent and non-covalent reactions between cocoa polyphenols and proteins (milk and cocoa) and the possible effects of these reactions on their bioaccessibility, considering environmental and processing conditions. Better insight into these interactions is crucial for understanding the biological effects of polyphenols, developing nutritional strategies, and improving food processing and storage. Protein-polyphenol reactions affect the properties of the final product and can lead to the formation of various precursors at various stages in the manufacturing process, such as fermentation, roasting, alkalization, and conching. Due to the complex composition of the chocolate and the various technological processes, comprehensive food profiling strategies should be applied to analyze protein-polyphenol covalent reactions covering a wide range of potential reaction products. This will help to identify potential effects on the bioaccessibility of bioactive compounds such as low-molecular-weight peptides and polyphenols. To achieve this, databases of potential reaction products and their binding sites can be generated, and the effects of various process conditions on related parameters can be investigated. This would then allow to a deeper insight into mechanisms behind protein-polyphenol interactions in chocolate, and develop strategies to optimize chocolate production for improved nutritional and sensory properties.

Identification of colupulone and lupulone as the main contributors to the antibacterial activity of hop extracts using activity-guided fractionation and metabolome analysis.

Hop is widely used in beer brewing and as a medicinal product. The present study comprehensively analyzed the main molecular determinants of the antibacterial activity of hop extracts. Minimum inhibitory concentrations (MIC) against Bacillus subtilis between 31.25 and 250 µg/mL were found in the ethanolic extracts of five hop varieties for beer brewing, but not in the tea hop sample. Activity-guided fractionation revealed the highest antibacterial activity for lupulone and adlupulone (MIC 0.98 µg/mL). Metabolome profiling and subsequent multistep statistical analysis detected 33 metabolites out of 1826 features to be associated with the antibacterial activity including humulone, adhumulone, colupulone, lupulone, and adlupulone. Xanthohumol, the three humulone- and three lupulone congeners were quantified in the hop extracts by a validated ultrahigh-performance liquid chromatography-mass spectrometry method. Considering concentrations and MICs, colupulone and lupulone were identified as major contributors to the antibacterial activity of hop extract with the highest antibacterial activity values (concentration/MIC) of 1.59 and 2.56.

A model study on the site-specificity of (-)-epicatechin-induced reactions in ß-lactoglobulin by high-resolution mass spectrometry in combination with bioinformatics.

Polyphenol-protein reactions in model solutions of ß-lactoglobulin (ß-LG) incubated with (-)-epicatechin at 37 °C and 60 °C were monitored by microLC-timsTOF Pro-MS/MS combined with bioinformatics strategies. The addition of (-)-epicatechin to the model solutions resulted in changes in tryptic peptide profiles. Covalent bond formation between (-)-epicatechin o-quinones and ß-LG was identified for the residues S27, S30, K60, C66, K69, and C160, with C160 being the predominant binding site. Furthermore, the incubation of ß-LG with (-)-epicatechin significantly promoted oxidation, especially for the residues M7 and M24. The reaction of monomeric (-)-epicatechino-quinone at C160 was also identified in the milk chocolate sample. The adaptation of this study by extending the scope of the reaction products offers significant potential for comprehensive food profiling strategies.

Identification of peptides reflecting the storage of UHT milk by MALDI-TOF-MS peptide profiling.

Proteolysis during the storage of UHT milk is associated with major technological problems, particularly bitter off-flavors and age gelation limiting the shelf life of milk. In this study, untargeted peptide profiling by MALDI-TOF-MS identified peptides that were formed by proteolysis and reflected the storage of UHT milk. Analysis of nine different commercial UHT samples recorded peptide profiles during and at the end of their shelf life. Relative quantification and sequencing of the peptides revealed that the concentrations of 22 peptides increased significantly during the storage of UHT milk due to the activity of endogenous milk proteases and microbial proteases as well as other unidentified proteolytic mechanisms. Based on highly discriminative AUC values from receiver operator characteristic (ROC) curve analysis, we selected ten peptides as marker candidates. Among those, the peptide ß-casein192-206 (m/z 1668.9) was the most suitable marker differentiating expired-UHT from regular-UHT samples with 100% accuracy. Additionally, ß-casein191-206 (m/z 1782.0) showed 100% specificity and ß-casein139-161 (m/z 2696.4) 100% sensitivity. Thus, ß-casein192-206, either by itself or in combination with ß-casein191-206 and ß-casein139-161, presents a reliable marker to monitor the storage of UHT milk based on proteolytic mechanisms. SIGNIFICANCE: Enzymatic hydrolysis is the main reason why processed milk spoils during storage. The present study recorded peptide profiles to monitor the release or degradation of peptides in stored UHT milk. Among the detected peptides, statistical analysis revealed that the relative concentration of ß-casein192-206 reflected those proteolytic processes most precisely. Food authorities can now refer to ß-casein192-206 as a reliable marker to differentiate between freshly processed milk and products at the end of their shelf life. Furthermore, the food industry can use this marker peptide to improve production processes by monitoring the proteolysis during storage. The recorded peptide profile helps to explain the basic mechanisms leading to storage-induced proteolysis.

Design of a Prediction Model for the Differentiation of Pasteurized Milk from Heated ESL Milk by Peptide Profiling.

This study designs a prediction model to differentiate pasteurized milk from heated extended shelf life (ESL) milk based on milk peptides. For this purpose, quantitative peptide profiles of a training set of commercial samples including pasteurized (n = 20), pasteurized-ESL (n = 13), and heated-ESL (n = 16) milk are recorded by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Seven peptides are selected as putative markers, and cutoff levels and performance measures of each marker are defined by receiver operating characteristic (ROC) analysis. The accuracy of these peptides in the training set range between 71% and 90%. A prediction model is established based on the combined cutoff levels and evaluated by an independent blind test set. The processing method of 19 out of 20 unknown milk samples is predicted correctly achieving 95% accuracy. Five peptides of the prediction model are identified as αS1 -casein182-199 (m/z 2014.0), αS1 -casein180-199 (m/z 2216.1), αS1 -casein1-24 (m/z 2910.6), ß-casein108-125 (m/z 2126.0), and ß-casein106-125 (m/z 2391.2) indicating thermal release and the action of plasmin and cathepsins. Thus, the present study demonstrates that the milk peptide profile reflects even minor differences in production parameters.

Identification of the Peptide PyroQ-ßCasein194-209 as a Highly Specific and Sensitive Marker to Differentiate between Ultrahigh-Temperature Processed (UHT) Milk and Mildly Heated Milk.

In this study, a new approach was introduced to identify marker peptides that reflect the thermal treatment of commercial milk samples and differentiate ultrahigh-temperature processed (UHT) milk from mildly heated milk. Peptide profiles of training set samples, pasteurized (n = 20), extended shelf life (n = 29), and UHT (n = 29) milk, were recorded by MALDI-TOF-MS after StageTip microextraction. As marker candidates, 13 peptides were selected, and their cutoff levels were defined. The quality of the cutoff levels was then tested with a blind test set. Thus, the peptide m/z 1701.0, which was identified as pyroQ-ßcasein194-209, could ideally differentiate UHT milk from mildly heated milk with an accuracy of 100%. Due to its high reliability and sensitivity, this peptide may be applied in routine analysis to monitor thermal processing of milk. An additional heating experiment showed that the marker peptide candidates are formed during milk processing by endogenous enzymes and selective thermal cleavage.