Establishing an untargeted-to-MRM liquid chromatography-mass spectrometry method for discriminating reconstituted milk from ultra-high temperature milk

Discrimination of overheated pasteurized milk using mass spectrometry-based proteomics

Milk is one of the most widely consumed foods globally. To protect consumer interests, it is essential to establish an analytical method to detect the degree of heating in milk. A novel approach using nano liquid chromatography-orbitrap fusion mass spectrometer was developed for screening and identifing thermally sensitive peptides markers in the milk heating process (below 100 °C). This method integrates untargeted proteomics and chemometric tools to analyze protein quantitation data from differently heat-treated milk. Thirteen potential markers were screened out and identified, and further confirmed using by standard substances. Then, the accurate concentrations of 13 potential markers determined by isotope-dilution ultra-performance liquid chromatography-tandem triple quadrupole mass spectrometry were further mining the highly specific and thermally sensitive peptides markers. And Four peptides-INLFDTPLETQYVR, FELLGCELNGCTEPLGLK, QFQFIQVAGR, and GEADALNLDGGYIYTAGK-were selected as marker peptides to differentiate normal pasteurized milk from overheated pasteurized milk. The concentrations of INLFDTPLETQYVR ranges from 150 ± 11 µg/L to 350 ± 23 µg/L, while the concentrations of FELLGCELNGCTEPLGLK ranges from 40 ± 5 µg/L to 92 ± 3 µg/L, can distinguish normal pasteurized milk from overheated pasteurized milk. QFQFIQVAGR indicates overheated pasteurized milk at 230 ± 21 µg/L, and GEADALNLDGGYIYTAGK signifies 750 ± 43 µg/L. This study provides new insights for distinguishing overheated pasteurized milk.

Reveal the mechanism of hepatic oxidative stress in mice induced by photo-oxidation milk using multi-omics analysis techniques

INTRODUCTION

Photo-oxidation is recognized as a contributor to the deterioration of milk quality, posing potential safety hazards to human health. However, there has been limited investigation into the impact of consuming photo-oxidized milk on health.

OBJECTIVES

This study employs multi-omics analysis techniques to elucidate the mechanisms by which photo-oxidized milk induces oxidative stress in the liver.

METHODS

Mouse model was used to determine the effect of the gavage administration of milk with varying degrees of photo-oxidation on the mouse liver. The damage degree was established by measuring serum markers indicative of oxidative stress, and with a subsequent histopathological examination of liver tissues. In addition, comprehensive metabolome, lipidome, and transcriptome analyses were conducted to elucidate the underlying molecular mechanisms of hepatic damage caused by photo-oxidized milk.

RESULTS

A significant elevation in the oxidative stress levels and the presence of hepatocellular swelling and inflammation subsequent to the gavage administration of photo-oxidized milk to mice. Significant alterations in the levels of metabolites such as lumichrome, all-trans-retinal, L-valine, phosphatidylglycerol, and phosphatidylcholine within the hepatic tissue of mice. Moreover, photo-oxidized milk exerted a pronounced detrimental impact on the glycerophospholipid metabolism of mice liver. The peroxisome proliferator-activated receptors (PPAR) signaling pathway enrichment appreciated in the animals that consumed photo-oxidized milk further supports the substantial negative influence of photo-oxidized milk on hepatic lipid metabolism. Gene set enrichment and interaction analyses revealed that photo-oxidized milk inhibited the cytochrome P450 pathway in mice, while also affecting other pathways associated with cellular stress response and lipid biosynthesis.

CONCLUSION

This comprehensive study provides significant evidence regarding the potential health risks associated with photo-oxidized milk, particularly in terms of hepatic oxidative damage. It establishes a scientific foundation for assessing the safety of such milk and ensuring the quality of dairy products.

Evaluation of milk photooxidation based on peptidomics

Photooxidation is one of the main causes of the deterioration of milk quality during processing and marketing. This study aimed to investigate the variation in peptides after photooxidation using peptidomic techniques, and how cow species, oxygen content, and light intensity affect photooxidation. The different peptides were identified and quantified using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Eighteen milk samples were subjected to light treatment. Seven types of peptides were identified as photooxidation markers. Subsequently, the effects of milk variety, oxygen content, and light intensity on photooxidation were studied, and sensory evaluations were performed. Dairy cow breed, oxygen content, and light intensity all affect photooxidation. Sensory evaluation verified that light and oxygen are necessary for the photooxidation of milk. The peptide m/z+ 529.2783 (LLDEIKEVV), both in different varieties of milk and in different brands of commercially available milk, showed a large variation in multiplicity, and its content was closely related to oxygen and light. This peptide was not produced in the absence of oxygen and light, and its relative content increased with the duration of light exposure. These results suggest that the peptidomics method is an effective tool for distinguishing between normal and photooxidized milk.

Untargeted Metabolomic Analysis of Lactation-Stage-Matched Human and Bovine Milk Samples at 2 Weeks Postnatal

Epidemiological data demonstrate that bovine whole milk is often substituted for human milk during the first 12 months of life and may be associated with adverse infant outcomes. The objective of this study is to interrogate the human and bovine milk metabolome at 2 weeks of life to identify unique metabolites that may impact infant health outcomes. Human milk (n = 10) was collected at 2 weeks postpartum from normal-weight mothers (pre-pregnant BMI < 25 kg/m2) that vaginally delivered term infants and were exclusively breastfeeding their infant for at least 2 months. Similarly, bovine milk (n = 10) was collected 2 weeks postpartum from normal-weight primiparous Holstein dairy cows. Untargeted data were acquired on all milk samples using high-resolution liquid chromatography-high-resolution tandem mass spectrometry (HR LC-MS/MS). MS data pre-processing from feature calling to metabolite annotation was performed using MS-DIAL and MS-FLO. Our results revealed that more than 80% of the milk metabolome is shared between human and bovine milk samples during early lactation. Unbiased analysis of identified metabolites revealed that nearly 80% of milk metabolites may contribute to microbial metabolism and microbe-host interactions. Collectively, these results highlight untargeted metabolomics as a potential strategy to identify unique and shared metabolites in bovine and human milk that may relate to and impact infant health outcomes.

Analysis of milk with liquid chromatography–mass spectrometry: a review

As a widely consumed foodstuff, milk and dairy products are increasingly studied over the years. At the present time, milk profiling is used as a benchmark to assess the properties of milk. Modern biomolecular mass spectrometers have become invaluable to fully characterize the milk composition. This review reports the analysis of milk and its components using liquid chromatography coupled with mass spectrometry (LC–MS). LC–MS analysis as a whole will be discussed subdivided into the major constituents of milk, namely, lipids, proteins, sugars and the mineral fraction.

How Chemometrics Can Fight Milk Adulteration

Adulteration and fraud are amongst the wrong practices followed nowadays due to the attitude of some people to gain more money or their tendency to mislead consumers. Obviously, the industry follows stringent controls and methodologies in order to protect consumers as well as the origin of the food products, and investment in these technologies is highly critical. In this context, chemometric techniques proved to be very efficient in detecting and even quantifying the number of substances used as adulterants. The extraction of relevant information from different kinds of data is a crucial feature to achieve this aim. However, these techniques are not always used properly. In fact, training is important along with investment in these technologies in order to cope effectively and not only reduce fraud but also advertise the geographical origin of the various food and drink products. The aim of this paper is to present an overview of the different chemometric techniques (from clustering to classification and regression applied to several analytical data) along with spectroscopy, chromatography, electrochemical sensors, and other on-site detection devices in the battle against milk adulteration. Moreover, the steps which should be followed to develop a chemometric model to face adulteration issues are carefully presented with the required critical discussion.

Future perspectives on aptamer for application in food authentication

Food fraudulence and food contamination are major concerns, particularly among consumers with specific dietary, cultural, lifestyle, and religious requirements. Current food authentication methods have several drawbacks and limitations, necessitating the development of a simpler, more sensitive, and rapid detection approach for food screening analysis, such as an aptamer-based biosensor system. Although the use of aptamer is growing in various fields, aptamer applications for food authentication are still lacking. In this review, we discuss the limitations of existing food authentication technologies and describe the applications of aptamer in food analyses. We also project several potential targets or marker molecules to be targeted in the SELEX process. Finally, this review highlights the drawbacks of current aptamer technologies and outlines the potential route of aptamer selection and applications for successful food authentication. This review provides an overview of the use of aptamer in food research and its potential application as a molecular reporter for rapid detection in food authentication process. Developing databases to store all biochemical profiles of food and applying machine learning algorithms against the biochemical profiles are urged to accelerate the identification of more reliable biomarker molecules as aptamer targets for food authentication.

Metabolites in Milk after Enrofloxacin Treatment and Their Persistence to Temperature

In this work, metabolomic profile changes in milk from cows affected by mastitis and treated with enrofloxacin (ENR) have been studied using LC-HRMS techniques. Principal component analysis was applied to the obtained results, and the interest was focused on changes affecting compounds without a structural relationship to ENR. Most of the compounds, whose concentrations were modified as a result of the pharmacological treatment and/or the pathological status, were related to amino acids and peptides. Compounds that may become possible biomarkers for either disease or treatment have been detected. Additionally, the alterations caused by thermal processes, such as those applied to milk before consumption, on the identified metabolites have also been considered.

Differentiating ultra-high temperature milk and reconstituted milk using an untargeted peptidomic approach with chemometrics

An untargeted peptide profiling based on ultra-performance liquid chromatography quadrupole time-of flight mass spectrometry with chemometrics was performed to differentiate ultra-high temperature processed milk and reconstituted milk. Thirty-three marker peptides were identified, primarily released from the C- or N-terminal of β-casein and α_s1-casein. These peptides were produced by heating and protease hydrolysis. Additional heating and storage time experiments showed that the level of 18 marker peptides increased with heat load and storage time, whereas 15 peptides were solely influenced by heat load. The peptides from β-casein showed higher sensitivity to thermal stress compared to those from α_s1-casein. Additionally, eight modified peptides of casein were identified as indicators of milk thermal processing. The identified marker peptides can distinguish ultra-high temperature processed milk and reconstituted milk, and are suitable for monitoring heating processes and storage of milk.

Effects of the Oxygen Content and Light Intensity on Milk Photooxidation Using Untargeted Metabolomic Analysis

Photooxidation is the main cause of milk quality deterioration during processing and transportation. Oxygen and light are responsible for dairy milk photooxidation. The objective of this study was to determine the characteristic metabolites after photooxidation and how they are affected by oxygen exposure and light intensity. Ultra-performance liquid chromatography coupled with triple time-of-flight mass spectrometry and multivariate data analysis were used for the high-throughput evaluation of milk photooxidation. Four products were identified as biomarkers: uric acid, riboflavin, lumichrome, and indole-3-carboxaldehyde. Afterward, the effects of oxygen content and light intensity on the biomarkers were investigated, and a sensory evaluation was performed. Both oxygen exposure and light intensity affected the contents of photooxidation biomarkers in milk samples. The sensory score correlated well with the oxygen content but not with the light intensity. The untargeted metabolomic method was an effective tool to identify biomarkers for milk photooxidation evaluation.

Investigation of alterations in phospholipids during the production chain of infant formulas via HILIC-QTOF-MS and multivariate data analysis

Phospholipids play a key role in infant nutrition and cognitive function. In this study, hydrophilic interaction liquid chromatography coupled to quadrupole time-of-flight mass spectrometry method was firstly developed to analyze the composition of phospholipids. Then we characterized and quantified phospholipids extracted from raw, pasteurized, homogenized, and spray-dried milk to investigate the effect of the technological process on the composition of the phospholipids. Results indicate that the composition of the phospholipids underwent minor changes after pasteurization, while the concentration of phospholipids was significantly affected by the spray-drying process, especially phosphatidylethanolamine and phosphatidylinositol. Multivariate data analysis further verified the results and indicated that phospholipids containing polyunsaturated fatty acids had undergone significant changes during the production chain, especially in spray-drying. This work reveals the changes of phospholipids composition during the production chain of infant formulas and serve as a reference for the subsequent optimization of infant formulas to meet nutritional need of infants.

Integrated metabolomics and lipidomics profiling reveals beneficial changes in sensory quality of brown fermented goat milk

Fermentation and thermal processing can improve the sensory properties of foods. Chemical composition of fermented brown goat milk was investigated using an integrated lipomics and metabonomic method while the effects of changes in chemical composition on sensory quality were also explored. After fermentation, organic acid, peptide and medium- and long-chain fatty acid contents in brown goat milk samples increased significantly. A total of 108 metabolites and 174 lipids related to sensory quality were identified. Heterocyclic compounds, as intermediates of Maillard reaction, modified colour, taste, and aroma, while changes in triglyceride content reduced the impact of off-odour, greatly improving sensory quality of fermented brown goat milk. This study provided new approaches for examining goat milk sensory quality and insights into how these can be modified to further diversify dairy products on the market.