Selection of universal peptide biomarkers for the detection of the allergen hazelnut in food trough a comprehensive, high resolution mass spectrometric (HRMS) based approach

Development and validation of sensitive and rapid CRISPR/Cas12-based PCR method to detect hazelnut in unlabeled products

Hazelnut, one of the most popular tree nuts, is widely found in processed food and even very small amounts can trigger severe allergic reactions in susceptible people. Herein, we developed a sensitive and rapid method based on CRISPR and qPCR capable of detecting low-abundance hazelnut in processed food. The assay, known as CRISPR-based nucleic acid test method (Crinac) can detect 1 % of hazelnut in a mixture and allows the species to be identified in a complex processed sample. The detection process can be completed within 60 min. Contributed to amplification via PCR and CRISPR/Cas12a, enables end-fluorescence measurement for the quantification of hazelnut, thus reducing assay time and eliminating the need for costly real-time fluorescence PCR instruments. The assay based on CRISPR/Cas12 and PCR has potential as a sensitive and reliable analytical tool for the detection of food authenticity.

Advancing High-Throughput MS-Based Protein Quantification: A Case Study on Quantifying 10 Major Food Allergens by LC-MS/MS Using a One-Sample Multipoint External Calibration Curve

The LC-MS-based method has emerged as the preferred approach for quantifying food allergens. However, the preparation of a traditional calibration curve (MSCC) is labor-intensive and error-prone. Here, a sensitive and robust LC-MS/MS method for quantifying 10 major food allergens was developed and validated, where the one-sample multipoint external calibration curve (OSCC) was employed instead of MSCC. By employing the multiple isotopologue reaction monitoring (MIRM) technique with only one spiked level in the blank, OSCC can be effectively established. Results demonstrate that the proposed method exhibits excellent performance in selectivity, sensitivity, accuracy, and precision, comparable to that of the traditional MSCC. Additionally, this strategy allows for isotope sample dilution by monitoring the less abundant MIRM channel. Moreover, the developed method was successfully applied to investigate the contamination of 10 food allergens in commercial food products. With its high throughput and robustness, the MIRM-OSCC-LC-MS/MS methodology has many potential applications, especially in the MS-based protein quantification analysis.

UPLC-MS/MS profiling, antioxidant and anti-inflammatory activities, and potential health benefits prediction of phenolic compounds in hazel leaf

Hazel leaf, one of the by-products of hazelnut, which is widely used in traditional folk medicine around the world. In the present study, the profile of free, conjugated, and bound phenolic compounds from hazel leaf was detected and their antioxidant and anti-inflammatory activities were investigated. The potential health benefits of different phenolic compounds were also predicted. The results showed that the 35 phenolic substances of free, conjugated and bound forms were identified including phenolic acids, flavonoids and catechins. Most of the hazel leaf phenolics were presented in free form, followed by conjugated and bound form. All the fractions effectively inhibited the production of reactive oxygen species and malondialdehyde in TBHP-stimulated human umbilical vein endothelial cells by enhancing endogenous superoxide dismutase, and accordingly alleviated inflammatory cytokines (NO, IL-1β, TNF-α, and IL-6) in LPS-stimulated RAW264.7 cells, showing obvious antioxidant and anti-inflammatory capacity. Moreover, combined with network pharmacology, the potential therapeutic effects and functional pathways of hazel leaf phenolics were predicted, which provided value basis for exploring their treatment on diseases and developing health products in the future.

Qualitative and Quantitative Analysis of Ejiao-Related Animal Gelatins through Peptide Markers Using LC-QTOF-MS/MS and Scheduled Multiple Reaction Monitoring (MRM) by LC-QQQ-MS/MS

Donkey-hide gelatin, also called Ejiao (colla corii asini), is commonly used as a food health supplement and valuable Chinese medicine. Its growing popular demand and short supply make it a target for fraud, and many other animal gelatins can be found as adulterants. Authentication remains a quality concern. Peptide markers were developed by searching the protein database. However, donkeys and horses share the same database, and there is no specific marker for donkeys. Here, solutions are sought following a database-independent strategy. The peptide profiles of authentic samples of different animal gelatins were compared using LC-QTOF-MS/MS. Fourteen specific markers, including four donkey-specific, one horse-specific, three cattle-specific, and six pig-specific peptides, were successfully found. As these donkey-specific peptides are not included in the current proteomics database, their sequences were determined by de novo sequencing. A quantitative LC-QQQ multiple reaction monitoring (MRM) method was further developed to achieve highly sensitive and selective analysis. The specificity and applicability of these markers were confirmed by testing multiple authentic samples and 110 batches of commercial Ejiao products, 57 of which were found to be unqualified. These results suggest that these markers are specific and accurate for authentication purposes.

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

Discovery of marker peptides of spirulina microalga proteins for allergen detection in processed foodstuffs

Spirulina (Arthrospira platensis) proteins were extracted, digested, and analyzed by LC-ESI-FTMS/MS to find highly conserved peptides as markers of the microalga occurrence in foodstuffs. Putative markers were firstly chosen after in silico digestion of allergenic proteins, according to the FAO and WHO criteria, after assuring their presence in food supplements and in (un)processed foodsuffs. Parameters such as sensitivity, sequence size, and uniqueness for spirulina proteins were also evaluated. Three peptides belonging to C-phycocyanin beta subunit (P72508) were designated as qualifiers (ETYLALGTPGSSVAVGVGK and YVTYAVFAGDASVLEDR) and quantifier (ITSNASTIVSNAAR) marker peptides and used to validate the method for linearity, recovery, reproducibility, matrix effects, processing effects, LOD, and LOQ. The main aim was to determine spirulina in commercial foodstuffs like pasta, crackers, and homemade bread incurred with the microalga. The possible inclusion of the designated peptides in a standardized method, based on multiple reaction monitoring using a linear ion trap MS, was also demonstrated.

Tree Nuts and Peanuts as a Source of Beneficial Compounds and a Threat for Allergic Consumers: Overview on Methods for Their Detection in Complex Food Products

Consumption of tree nuts and peanuts has considerably increased over the last decades due to their nutritional composition and the content of beneficial compounds. On the other hand, such widespread consumption worldwide has also generated a growing incidence of allergy in the sensitive population. Allergy to nuts and peanuts represents a global relevant problem, especially due to the risk of the ingestion of hidden allergens as a result of cross-contamination between production lines at industrial level occurring during food manufacturing. The present review provides insights on peanuts, almonds, and four nut allergens—namely hazelnuts, walnuts, cashew, and pistachios—that are likely to cross-contaminate different food commodities. The paper aims at covering both the biochemical aspect linked to the identified allergenic proteins for each allergen category and the different methodological approaches developed for allergens detection and identification. Attention has been also paid to mass spectrometry methods and to current efforts of the scientific community to identify a harmonized approach for allergens quantification through the detection of allergen markers.

Selecting processing robust markers using high resolution mass spectrometry for the detection of milk in food products

BACKGROUND

Cow's milk allergy is one of the most reported food allergies in Europe. To help patients suffering from food allergies it is important to be able to detect milk in different foods. An analytical method that is gaining interest in the field of allergen detection is Ultra-High Performance Liquid Chromatography-tandem Mass Spectrometry, where the analyte is a target peptide. When these peptide biomarkers are selected the effect of food processing should be taken into account to allow a robust detection method.

OBJECTIVE

This works aims at identifying such processing stable peptide markers for milk for the Ultra-High Performance Liquid Chromatography-tandem Mass Spectrometry based detection of food allergens in different food products.

METHODS

Milk-incurred food materials that underwent several processing techniques were produced. This was followed by establishing tryptic peptide profiles from each matrix using Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry .

RESULT

A careful comparison of peptide profiles/intensities and the use of specific exclusion criteria resulted in the selection of 8 peptide biomarkers suitable for application in Ultra-High Performance Liquid Chromatography-tandem Mass Spectrometry based milk detection methods. One of these markers is a α-lactalbumin specific peptide, which has been determined to be stable in different incurred materials for the first time.

CONCLUSION

To our knowledge, this is the first systematic and experimentally based approach for the selection of suitable milk peptide biomarkers robust towards multiple, often applied food processing techniques for milk. Ensuring the exact knowledge of the food processing circumstances by starting from well-defined raw material and using fully controlled settings to produce incurred test material allowed the construction of a peptide database with robust markers. These robust markers can be used for the development of a robust detection method for milk in different food matrices.

Mass spectrometry-based protein and peptide profiling for food frauds, traceability and authenticity assessment

The ever-growing use of mass spectrometry (MS) methodologies in food authentication and traceability originates from their unrivalled specificity, accuracy and sensitivity. Such features are crucial for setting up analytical strategies for detecting food frauds and adulterations by monitoring selected components within food matrices. Among MS approaches, protein and peptide profiling has become increasingly consolidated. This review explores the current knowledge on recent MS techniques using protein and peptide biomarkers for assessing food traceability and authenticity, with a specific focus on their use for unmasking potential frauds and adulterations. We provide a survey of the current state-of-the-art instrumentation including the most reliable and sensitive acquisition modes highlighting advantages and limitations. Finally, we summarize the recent applications of MS to protein/peptide analyses in food matrices and examine their potential in ensuring the quality of agro-food products.

Peptide markers for distinguishing guinea fowl meat from that of other species using liquid chromatography-mass spectrometry

The inability to easily identify the animal species in highly processed meat products makes them highly susceptible to adulterations. Reliable methods for detecting the species origin of meat used in processed food are required to ensure adequate labelling and minimize food fraud and allergenic potential. Liquid chromatography high resolution mass spectrometry was employed to identify new heat-stable guinea-fowl-specific peptide markers that can differentiate guinea fowl meat from other commonly consumed animal species, including closely related poultry species, in highly processed food products. We identified 26 unique guinea-fowl-specific markers. The high stability of guinea-fowl-specific peptides was confirmed by analysing food products with guinea fowl meat content ranging from 4% to 100%. The findings indicate that sensitive and reliable LC-MS/MS methods can be developed for the targeted detection and quantification of guinea fowl meat in highly processed meat products.

Discovery based high resolution MS/MS analysis for selection of allergen markers in chocolate and broth powder matrices

Peptide marker identification is an important step in development of a mass spectrometry method for multiple allergen detection, since specificity, robustness and sensitivity of the overall analytical method will depend on the reliability of the proteotypic peptides. As part of the development of a multi-analyte reference method, discovery analysis of two incurred food matrices has been undertaken to select the most reliable peptide markers. Six allergenic ingredients (milk, egg, peanut, soybean, hazelnut, and almond) were incurred into either chocolate or broth powder matrix. Different conditions of protein extraction and purification were tested and the tryptic peptide pools were analysed by untargeted high resolution tandem mass spectrometry and the resulting fragmentation spectra were processed via a commercial software for sequence identification. The analysis performed on incurred foods provides both a prototype effective and straightforward sample preparation protocol and delivers reliable peptides to be included in a standardized selected reaction monitoring method.

Using Raman spectroscopy and an exponential equation approach to detect adulteration of olive oil with rapeseed and corn oil

This study presents a method to determine adulteration of olive oil (obtained from Olea europea, i.e. olives) with rapeseed oil (obtained from Brassica napus) or with corn oil (also named maize oil, obtained from Zea mays, i.e. maize) using Raman spectroscopy and a mathematical method based on exponential equation fit. The samples were prepared by mixing olive oil with volume fractions (0-100%) of rapeseed or corn oil. The oils were differentiated spectroscopically using intensity ratio for specific Raman peaks; Raman spectroscopy is able to detect changes within a liquid molecular environment without the need for sample treatment. It was possible to determine rapeseed or corn oil volume fractions added into the olive oil using the method proposed. Thus, the potential of Raman spectroscopy as a technique for determining adulteration of olive oil was corroborated clearly, opening the potential to investigate adulteration of other liquid foods, without any need for sample preparation.