Analysis of the peptide profile of milk and its changes during thermal treatment and storage

Python workflow for the selection and identification of marker peptides-proof-of-principle study with heated milk

The analysis of almost holistic food profiles has developed considerably over the last years. This has also led to larger amounts of data and the ability to obtain more information about health-beneficial and adverse constituents in food than ever before. Especially in the field of proteomics, software is used for evaluation, and these do not provide specific approaches for unique monitoring questions. An additional and more comprehensive way of evaluation can be done with the programming language Python. It offers broad possibilities by a large ecosystem for mass spectrometric data analysis, but needs to be tailored for specific sets of features, the research questions behind. It also offers the applicability of various machine-learning approaches. The aim of the present study was to develop an algorithm for selecting and identifying potential marker peptides from mass spectrometric data. The workflow is divided into three steps: (I) feature engineering, (II) chemometric data analysis, and (III) feature identification. The first step is the transformation of the mass spectrometric data into a structure, which enables the application of existing data analysis packages in Python. The second step is the data analysis for selecting single features. These features are further processed in the third step, which is the feature identification. The data used exemplarily in this proof-of-principle approach was from a study on the influence of a heat treatment on the milk proteome/peptidome.

Biomolecular Profiling by MALDI-TOF Mass Spectrometry in Food and Beverage Analyses

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has frequently been applied to the analysis of biomolecules. Its strength resides not only in compound identification but particularly in acquiring molecular profiles providing a high discriminating power. The main advantages include its speed, simplicity, versatility, minimum sample preparation needs, and a relatively high tolerance to salts. Other benefits are represented by the possibility of automation, high throughput, sensitivity, accuracy, and good reproducibility, allowing quantitative studies. This review deals with the prominent use of MALDI-TOF MS profiling in food and beverage analysis ranging from the simple detection of sample constituents to quantifications of marker compounds, quality control, and assessment of product authenticity. This review summarizes relevant discoveries that have been obtained with milk and milk products, edible oils, wine, beer, flour, meat, honey, and other alimentary products. Marker molecules are specified: proteins and peptides for milk, cheeses, flour, meat, wine and beer; triacylglycerols and phospholipids for oils; and low-molecular-weight metabolites for wine, beer and chocolate. Special attention is paid to sample preparation techniques and the combination of spectral profiling and statistical evaluation methods, which is powerful for the differentiation of samples and the sensitive detection of frauds and adulterations.

Use of MALDI-TOF MS technology to evaluate adulteration of small ruminant milk with raw bovine milk

Detection of adulteration of small ruminant milk is very important for health and commercial reasons. New analytical and cost-effective methods need to be developed to detect new adulteration practices. In this work, we aimed to explore the ability of the MALDI-TOF mass spectrometry to detect bovine milk in caprine and ovine milk using samples from 18 dairy farms. Different levels of adulteration (0.5, 1, 5, 10, 20, 40, 60, and 80%) were analyzed during the lactation period of goat and sheep (in May, from 60 to 90 d in milk, and in August, from 150 to 180 d in milk). Two different ranges of peptide-protein spectra (500-4,000 Da; 4-20 kDa) were used to establish a calibration model for predicting the concentration of adulterant using partial least squares and generalized linear model with lasso regularization. The low molecular weight part of the spectra together with the generalized linear model with lasso regularization regression model appeared to have greater potential for our aim of detection of adulteration of small ruminants' milk. The subsequent prediction model was able to predict the concentration of bovine milk in caprine milk with a root mean square error of 11.4 and 17.0% in ovine milk. The results offer compelling evidence that MALDI-TOF can detect the adulteration of small ruminants' milk. However, the method is severely limited by (1) the complexity of the milk proteome resulting from the adulteration technique, (2) the potential degradation of thermolabile proteins, and (3) the genetic variability of tested samples. Additionally, the root mean square error of prediction based only on one individual sample adulteration series can drop down to 6.34% for quantification of adulterated caprine milk and 6.28% for adulterated ovine milk for the full set of concentrations or down to 2.33 and 4.00%, respectively, if we restrict only to low concentrations of adulteration (0, 0.5, 1, 5, 10%).

Proteomic Advances in Milk and Dairy Products

Proteomics is a new area of study that in recent decades has provided great advances in the field of medicine. However, its enormous potential for the study of proteomes makes it also applicable to other areas of science. Milk is a highly heterogeneous and complex fluid, where there are numerous genetic variants and isoforms with post-translational modifications (PTMs). Due to the vast number of proteins and peptides existing in its matrix, proteomics is presented as a powerful tool for the characterization of milk samples and their products. The technology developed to date for the separation and characterization of the milk proteome, such as two-dimensional gel electrophoresis (2DE) technology and especially mass spectrometry (MS) have allowed an exhaustive characterization of the proteins and peptides present in milk and dairy products with enormous applications in the industry for the control of fundamental parameters, such as microbiological safety, the guarantee of authenticity, or the control of the transformations carried out, aimed to increase the quality of the final product.

Milk Ingredients in Meat Products: Can Autoclaving and In Vitro Gastroduodenal Digestion Mitigate Their IgE-Binding Capacity?

The food industry commonly uses milk ingredients as technological aids in an uncounted number of products. On the other hand, milk contains allergenic proteins causing adverse allergic reactions in sensitized/allergic individuals. This work intends to evaluate the effect of autoclaving and in vitro digestion on the allergenicity of milk proteins incurred in meat products. Protein profiles of raw and autoclaved sausages without and with the addition of 10% of milk protein concentrates were analyzed by gel electrophoresis and liquid chromatography–mass spectrometry. Additionally, residual IgE-reactivity was evaluated by immunoblot analysis using pooled sera of cow’s-milk-allergic individuals followed by bioinformatic analysis. Results showed that autoclaving led to an increase in protein fragmentation (higher number of short peptides) and consequently to a higher digestion rate, that was found to be more pronounced in β-casein. The IgE-binding capacity of milk proteins seems to be reduced after autoclaving prior to digestion, with a residual reactivity in caseins, but was eliminated following digestion. This study highlights the importance of autoclaving as a processing strategy to produce hypoallergenic formulas.

Use of kefir and buttermilk to produce an innovative quark cheese

Quark cheese is a fermented soft fresh cheese categorised under acid-rennet coagulated cheeses. In this study, alternative raw materials such as kefir and yayik buttermilk were used to produce Quark cheese in comparison with the cheese produced by the acidification of skim milk with mesophilic lactic culture. Samples were kept individually under 35 °C and 100 °C for coagulum formation. Obtained cheeses, were evaluated in terms of some physicochemical, microbiological and sensorial properties in addition to the volatile and peptide profiles. Quark produced from kefir and buttermilk was determined to have preferred properties directly affect the cheese characteristics.

Identification and Detection of Bioactive Peptides in Milk and Dairy Products: Remarks about Agro-Foods

Food-based components represent major sources of functional bioactive compounds. Milk is a rich source of multiple bioactive peptides that not only help to fulfill consumers 'nutritional requirements but also play a significant role in preventing several health disorders. Understanding the chemical composition of milk and its products is critical for producing consistent and high-quality dairy products and functional dairy ingredients. Over the last two decades, peptides have gained significant attention by scientific evidence for its beneficial health impacts besides their established nutrient value. Increasing awareness of essential milk proteins has facilitated the development of novel milk protein products that are progressively required for nutritional benefits. The need to better understand the beneficial effects of milk-protein derived peptides has, therefore, led to the development of analytical approaches for the isolation, separation and identification of bioactive peptides in complex dairy products. Continuous emphasis is on the biological function and nutritional characteristics of milk constituents using several powerful techniques, namely omics, model cell lines, gut microbiome analysis and imaging techniques. This review briefly describes the state-of-the-art approach of peptidomics and lipidomics profiling approaches for the identification and detection of milk-derived bioactive peptides while taking into account recent progress in their analysis and emphasizing the difficulty of analysis of these functional and endogenous peptides.

Liquid Atmospheric Pressure Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Adds Enhanced Functionalities to MALDI MS Profiling for Disease Diagnostics

A liquid matrix-assisted laser desorption/ionization (liquid MALDI) method has been developed for high-throughput atmospheric pressure (AP) mass spectrometry (MS) analysis of the molecular content of crude bioliquids for disease diagnostics. The presented method is rapid and highly robust, enabling its application in environments where speed and low-cost high-throughput analyses are required. Importantly, because of the creation of multiply charged analyte ions, it provides additional functionalities that conventional solid MALDI MS profiling is lacking, including the use of high-performance mass analyzers with limited m/z range. The concomitant superior MS/MS performance that is achieved similar to ESI MS/MS adds greater analytical power and specificity to MALDI MS profiling while retaining the advantages of a fast laser-based analysis system and off-line large-scale sample preparation. The potential of this MALDI MS profiling method is demonstrated on the detection of dairy cow mastitis, which is a substantial economic burden on the dairy industry with losses of hundreds of dollars per diseased cow per year, equating to a total annual loss of billions of dollars, as well as leading to the use of large quantities of antibiotics, adding to the proliferation of antimicrobial resistance. Only small amounts of aliquots obtained from the daily farm milking process were prepared for liquid MALDI MS profiling using a simple one-pot/two-step analyte extraction. Automated analysis was performed using a custom-built AP-MALDI ion source, enabling the simultaneous detection of lipids, peptides, and proteins. Diagnostic, multiply charged, proteinaceous ions were easily sequenced and identified by MS/MS experiments. Samples were classified according to mastitis status using multivariate analysis, achieving 98.5% accuracy (100% specificity) determined by "leave 20% out" cross-validation. The methodology is generally applicable to AP-MALDI MS profiling on most commercial high-resolution mass spectrometers, with the potential for expansion into hospitals for rapid assessment of human and other biofluids.

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 β-casein_192-206 (m/z 1668.9) was the most suitable marker differentiating expired-UHT from regular-UHT samples with 100% accuracy. Additionally, β-casein_191-206 (m/z 1782.0) showed 100% specificity and β-casein_139-161 (m/z 2696.4) 100% sensitivity. Thus, β-casein_192-206, either by itself or in combination with β-casein_191-206 and β-casein_139-161, 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 β-casein_192-206 reflected those proteolytic processes most precisely. Food authorities can now refer to β-casein_192-206 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.

Peptidomic and glycomic profiling of commercial dairy products: identification, quantification and potential bioactivities

Peptidomics and glycomics are recently established disciplines enabling researchers to characterize functional characteristics of foods at a molecular level. Milk-derived bioactive peptides and oligosaccharides have garnered both scientific and commercial interest because they possess unique functional properties, such as anti-hypertensive, immunomodulatory and prebiotic activities; therefore, the objective of this work was to employ peptidomic and glycomic tools to identify and measure relative and absolute quantities of peptides and oligosaccharides in widely consumed dairy products. Specifically, we identified up to 2117 unique peptides in 10 commercial dairy products, which together represent the most comprehensive peptidomic profiling of dairy milk in the literature to date. The quantity of peptides, measured by ion-exchange chromatography, varied between 60 and 130 mg/L among the same set of dairy products, which the majority originated from caseins, and the remaining from whey proteins. A recently published bioactive peptide database was used to identify 66 unique bioactive peptides in the dataset. In addition, 24 unique oligosaccharide compositions were identified in all the samples by nano LC Chip QTOF. Neutral oligosaccharides were the most abundant class in all samples (66-91.3%), followed by acidic (8.6-33.7%), and fucosylated oligosaccharides (0-4.6%). Variation of total oligosaccharide concentration ranged from a high of 65.78 to a low of 24.82 mg/L. Importantly, characterizing bioactive peptides and oligosaccharides in a wider number of dairy products may lead to innovations that go beyond the traditional vision of dairy components used for nutritional purposes but that will rather focus on improving human health.

Identification of the Peptide PyroQ-βCasein194-209 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-βcasein_194-209, 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.

Identification of sixteen peptides reflecting heat and/or storage induced processes by profiling of commercial milk samples

Peptide profiles of different drinking milk samples were examined to study how the peptide fingerprint of milk reflects processing conditions. The combination of a simple and fast method for peptide extraction using stage tips and MALDI-TOF-MS enabled the fast and easy generation and relative quantification of peptide fingerprints for high-temperature short-time (HTST), extended shelf life (ESL) and ultra-high temperature (UHT) milk of the same dairies. The relative quantity of 16 peptides changed as a function of increasing heat load. Additional heating experiments showed that among those, the intensity of peptide β-casein 196-209 (m/z 1460.9Da) was most heavily influenced by heat treatment indicating a putative marker peptide for milk processing conditions. Storage experiments with HTST- and UHT milk revealed that the differences between different types of milk samples were not only caused by the heating process. Relevant was also the proteolytic activity of enzymes during storage, which were differently influenced by the heat treatment. These results indicate that the peptide profile may be suitable to monitor processing as well as storage conditions of milk.

SIGNIFICANCE

In the present study, peptide profiling of different types of milk was carried out by MALDI-TOF-MS after stage-tip extraction and relative quantification using an internal reference peptide. Although MALDI-TOF-MS covers only part of the peptidome, the method is easy and quick and is, therefore, suited for routine analysis to address several aspects of food authenticity. Using this method, 16 native peptides were detected in milk that could be modulated by different industrial processes. Subsequent heating and storage experiments with pasteurized and UHT milk confirmed that these peptides are indeed related to the production or storage conditions of the respective products. Furthermore, the heating experiments revealed one peptide, namely the β-casein-derived sequence β-casein 196-209, which underwent particularly sensitive modulation by heat treatment. The present results indicate that the modulated peptides, and especially β-casein 196-209, may be suitable markers to monitor processing parameters for industrial milk production. Furthermore, the model experiments suggest mechanisms leading to the formation or degradation of peptides, which help to evaluate putative marker peptides.

Formation and Degradation of Beta-casomorphins in Dairy Processing

Milk proteins including casein are sources of peptides with bioactivity. One of these peptides is beta-casomorphin (BCM) which belongs to a group of opioid peptides formed from β-casein variants. Beta-casomorphin 7 (BCM7) has been demonstrated to be enzymatically released from the A1 or B β-casein variant. Epidemiological evidence suggests the peptide BCM 7 is a risk factor for development of human diseases, including increased risk of type 1 diabetes and cardiovascular diseases but this has not been thoroughly substantiated by research studies. High performance liquid chromatography coupled to UV-Vis and mass spectrometry detection as well as enzyme-linked immunosorbent assay (ELISA) has been used to analyze BCMs in dairy products. BCMs have been detected in raw cow's milk and human milk and a variety of commercial cheeses, but their presence has yet to be confirmed in commercial yoghurts. The finding that BCMs are present in cheese suggests they could also form in yoghurt, but be degraded during yoghurt processing. Whether BCMs do form in yoghurt and the amount of BCM forming or degrading at different processing steps needs further investigation and possibly will depend on the heat treatment and fermentation process used, but it remains an intriguing unknown.

Immunoglobulin A in Bovine Milk: A Potential Functional Food?

Immunoglobulin A (IgA) is an anti-inflammatory antibody that plays a critical role in mucosal immunity. It is found in large quantities in human milk, but there are lower amounts in bovine milk. In humans, IgA plays a significant role in providing protection from environmental pathogens at mucosal surfaces and is a key component for the establishment and maintenance of intestinal homeostasis via innate and adaptive immune mechanisms. To date, many of the dairy-based functional foods are derived from bovine colostrum, targeting the benefits of IgG. IgA has a higher pathogenic binding capacity and greater stability against proteolytic degradation when ingested compared with IgG. This provides IgA-based products greater potential in the functional food market that has yet to be realized.

Peptidomic profile of milk of Holstein cows at peak lactation

Bovine milk is known to contain naturally occurring peptides, but relatively few of their sequences have been determined. Human milk contains hundreds of endogenous peptides, and the ensemble has been documented for antimicrobial actions. Naturally occurring peptides from bovine milk were sequenced and compared with human milk peptides. Bovine milk samples from six cows in second-stage peak lactation at 78-121 days postpartum revealed 159 peptides. Most peptides (73%) were found in all six cows sampled, demonstrating the similarity of the intramammary peptide degradation across these cows. One peptide sequence, ALPIIQKLEPQIA from bovine perilipin 2, was identical to another found in human milk. Most peptides derived from β-casein, αs1-casein, and αs2-casein. No peptides derived from abundant bovine milk proteins such as lactoferrin, β-lactoglobulin, and secretory immunoglobulin A. The enzymatic cleavage analysis revealed that milk proteins were degraded by plasmin, cathepsins B and D, and elastase in all samples.

Identification of multiphosphorylated peptides in milk

Multiphosphorylated peptides endogenously present in milk exert anticariogenic activity due to their calcium binding capacity. This study performed comprehensive analysis of multiphosphorylated peptides in raw milk using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Since phosphopeptides are often negatively discriminated during ionization, putative phosphopeptides were identified by three different methods: (i) selective detection in 4-chloro-α-cyanocinnamic acid MALDI matrix compared to α-cyano-4-hydroxycinnamic acid; (ii) higher relative signal intensity in negative compared to positive ionization mode; and (iii) detection of signal pairs with mass differences of -80 Da or multiples thereof before and after enzymatic dephosphorylation. Thus, 18 putative phosphopeptides from raw milk were annotated. Peptide structures were then determined by product ion spectra from targeted liquid chromatography electrospray ionization tandem-MS analysis. Thus, β-casein33-48, β-casein29-48, β-casein1-21, β-casein2-25, β-casein1-25, β-casein1-27, β-casein1-28, β-casein1-29, β-casein1-32, αS2-casein1-21, and αS2-casein1-24 were revealed as major peptides with one or four phosphorylation sites in raw milk.