In-house validation of an LC-MS method for the multiplexed quantitative determination of total allergenic food in chocolate.

Mass spectrometry has been widely accepted as a confirmatory tool for the sensitive detection of undeclared presence of allergenic ingredients. Multiple methods have been developed so far, achieving different levels of sensitivity and robustness, still lacking harmonization of the analytical validation and impairing comparability of results. In this investigation, a quantitative method has been validated in-house for the determination of six allergenic ingredients (cow's milk, hen's egg, peanut, soybean, hazelnut, and almond) in a chocolate-based matrix. The latter has been produced in a food pilot plant to provide a real and well-characterized matrix for proper assessment of method performance characteristics according to official guidelines. In particular, recent considerations issued by the European Committee for Standardization have been followed to guide a rigorous single-laboratory validation and to feature the main method performance, such as selectivity, linearity, and sensitivity. Synthetic surrogates of the peptide markers have been used both in native and labelled forms in matrix-matched calibration curves as external calibrants and internal standards, respectively. A two-order of magnitude range was investigated, focusing on the low concentration range for proper assessment of the detection and quantification limits (LOD and LOQ) by rigorous calibration approach. Conversion factors for all six allergenic ingredients have been determined for the first time to report the final quantitative information as fraction of total allergenic food protein (TAFP) per mass of food (µgTAFP/gfood), since such a reporting unit is exploitable in allergenic risk assessment plans. The method achieved good sensitivity with LOD values ranging between 0.08 and 0.2 µgTAFP/gfood, for all ingredients besides egg and soybean, whose quantitative markers reported a slightly higher limit (1.1 and 1.2 µgTAFP/gfood, respectively). Different samples of chocolate bar incurred at four defined concentration levels close to the currently available threshold doses have been analyzed to test the quantitative performance of the analytical method, with a proper estimate of the measurement uncertainty from different sources of variability. The sensitivity achieved resulted in compliance with the various threshold doses issued or recommended worldwide.

Multi-Allergen Quantification in Food Using Concatemer-Based Isotope Dilution Mass Spectrometry: An Interlaboratory Study.

BACKGROUND: Food allergen analysis is essential for the development of a risk-based approach for allergen management and labeling. MS has become a method of choice for allergen analysis, even if quantification remains challenging. Moreover, harmonization is still lacking between laboratories, while interlaboratory validation of analytical methods is necessary for such harmonization. OBJECTIVE: This interlaboratory study aimed to evaluate the potential of MS for food allergen detection and quantification using a standard addition quantification strategy and a stable isotope-labeled (SIL) concatemer as an internal standard. METHODS: In-house-produced test material (cookies), blank and incurred with four allergens (egg, milk, peanut, and hazelnut), allergen standards, an internal standard, and the complete methodology (including sample preparation and ultra-HPLC-MS/MS method) were provided to nine laboratories involved in the study. Method sensitivity and selectivity were evaluated with incurred test material and accuracy with spiked test material. Quantification was based on the standard addition strategy using certified reference materials as allergen protein standards and a SIL concatemer as an internal standard. RESULTS: All laboratories were able to detect milk, hazelnut, and peanut in the incurred cookies with sufficient sensitivity to reach the AOAC INTERNATIONAL Standard Method Performance Requirements (SMPR® 2016.002). Egg detection was more complicated due to food processing effects, yet five laboratories reached the sensitivity requirements. Recovery results were laboratory-dependent. Some milk and hazelnut peptides were quantified in agreement with SMPR 2016.002 by all participants. Furthermore, over 90% of the received quantification results agreed with SMPR 2016.002 for method precision. CONCLUSION: The encouraging results of this pioneering interlaboratory study represent an additional step towards harmonization among laboratories testing for allergens. HIGHLIGHTS: In this pioneering interlaboratory study, food allergens were analyzed by MS with characterized incurred and spiked test materials, calibrated with a certified reference material, and a single SIL concatemer used as an internal standard.

Development and Validation of a Quantitative Method for Multiple Allergen Detection in Food Using Concatemer-Based Isotope Dilution Mass Spectrometry.

BACKGROUND: Accurate food labeling is essential to protect allergic consumers. However, allergen contaminations may occur during the whole food production process. Reliable, sensitive, and robust methods for detecting multiple allergens in food are needed. OBJECTIVE: This work aims to develop and validate an LC coupled to tandem mass spectrometry (MS/MS) method for the detection and quantification of hazelnuts, peanuts, milk, and eggs in processed food products. METHODS: In-house-produced incurred test materials, cookies and chocolates, were used for the method development and validation. The quantification was based on the standard addition strategy using qualified reference materials as allergen protein standards and an innovative stable isotope-labeled concatemer as an internal standard. RESULTS: A method targeting 19 allergen-specific peptides was developed and validated in two laboratories, which strengthens its robustness. The AOAC INTERNATIONAL performance requirements for repeatability, intermediate precision, reproducibility, and recovery were reached for at least one peptide per allergen across both matrixes, and quantification limits complied with the action levels of the Food Industry Guide to the Voluntary Incidental Trace Allergen Labelling (VITAL®) Program Version 3.0. CONCLUSION: The combination of incurred test materials, standard addition strategy, and stable isotope-labeled concatemer as an internal standard allowed us to develop and validate a robust method for detecting and quantifying multiple allergens in food with sufficient sensitivity to protect allergic consumers. HIGHLIGHTS: The combination of characterized incurred test material, calibration with certified reference material, a single stable isotope labelled concatemer and cross-lab validation result in the required standardization and harmonization in food allergen detection according to the stakeholders' group to assess the robustness of our method.

Development of incurred chocolate bars and broth powder with six fully characterised food allergens as test materials for food allergen analysis.

The design and production of incurred test materials are critical for the development and validation of methods for food allergen analysis. This is because production and processing conditions, together with the food matrix, can modify allergens affecting their structure, extractability and detectability. For the ThRAll project, which aims to develop a mass spectrometry-based reference method for the simultaneous accurate quantification of six allergenic ingredients in two hard to analyse matrices. Two highly processed matrices, chocolate bars and broth powder, were selected to incur with six allergenic ingredients (egg, milk, peanut, soy, hazelnut and almond) at 2, 4, 10 and 40 mg total allergenic protein/kg food matrix using a pilot-scale food manufacturing plant. The allergenic activity of the ingredients incurred was verified using food-allergic patient serum/plasma IgE, the homogeneity of the incurred matrices verified and their stability at 4 °C assessed over at least 30-month storage using appropriate enzyme-linked immunosorbent assays (ELISA). Allergens were found at all levels from the chocolate bar and were homogenously distributed, apart from peanut and soy which could only be determined above 4 mg total allergenic ingredient protein/kg. The homogeneity assessment was restricted to analysis of soy, milk and peanut for the broth powder but nevertheless demonstrated that the allergens were homogeneously distributed. All the allergens tested were found to be stable in the incurred matrices for at least 30 months demonstrating they are suitable for method development.

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 ultrahigh 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 work aims at identifying such processing stable peptide markers for milk for the ultrahigh performance liquid chromatography-tandem mass spectrometry based detection of food allergens in different food products. METHOD: Milk-incurred food materials that underwent several processing techniques were produced. This was followed by establishing tryptic peptide profiles from each matrix using ultrahigh performance liquid chromatography-high resolution mass spectrometry. RESULTS: A careful comparison of peptide profiles/intensities and the use of specific exclusion criteria resulted in the selection of eight peptide biomarkers suitable for application in ultrahigh performance liquid chromatography-tandem mass spectrometry based milk detection methods. One of these markers is an α-lactalbumin specific peptide, which has been determined to be stable in different incurred materials for the first time. CONCLUSIONS: To our knowledge, this is the first systematic and experimentally based approach for the selection of suitable milk peptide biomarkers robust toward 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 matrixes. HIGHLIGHTS: To facilitate food allergen detection in processed food, processing stable peptide markers for the detection of milk in food products were determined using Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry on well-defined raw materials which were processed in accordance with often used processing techniques.

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.

Comparative study of concatemer efficiency as an isotope-labelled internal standard for allergen quantification.

Mass spectrometry-based methods coupled with stable isotope dilution have become effective and widely used methods for the detection and quantification of food allergens. Current methods target signature peptides resulting from proteolytic digestion of proteins of the allergenic ingredient. The choice of appropriate stable isotope-labelled internal standard is crucial, given the diversity of encountered food matrices which can affect sample preparation and analysis. We propose the use of concatemer, an artificial and stable isotope-labelled protein composed of several concatenated signature peptides as internal standard. With a comparative analysis of three matrices contaminated with four allergens (egg, milk, peanut, and hazelnut), the concatemer approach was found to offer advantages associated with the use of labelled proteins, ideal but unaffordable, and circumvent certain limitations of traditionally used synthetic peptides as internal standards. Although used in the proteomic field for more than a decade, concatemer strategy has not yet been applied for food analysis.

Critical review on proteotypic peptide marker tracing for six allergenic ingredients in incurred foods by mass spectrometry.

Peptide marker identification is one of the most important steps in the development of a mass spectrometry (MS) based method for allergen detection, since the robustness and sensitivity of the overall analytical method will strictly depend on the reliability of the proteotypic peptides tracing for each allergen. The European legislation in place issues the mandatory labelling of fourteen allergenic ingredients whenever used in different food formulations. Among these, six allergenic ingredients, namely milk, egg, peanut, soybean, hazelnut and almond, can be prioritized in light of their higher occurrence in food recalls for undeclared presence with serious risk decision. In this work, we described the results of a comprehensive evaluation of the current literature on MS-based allergen detection aiming at collecting all available information about proteins and peptide markers validated in independent studies for the six allergenic ingredients of interest. The main features of the targeted proteins were commented reviewing all details available about known isoforms and sequence homology particularly in plant-derived allergens. Several critical aspects affecting peptide markers reliability were discussed and according to this evaluation a final short-list of candidate markers was compiled likely to be standardized and implemented in MS methods for allergen analysis.

High-resolution mass spectrometry-based selection of peanut peptide biomarkers considering food processing and market type variation.

To protect allergic patients and guarantee correct food labeling, robust, specific and sensitive detection methods are urgently needed. Mass spectrometry (MS)-based methods could overcome the limitations of current detection techniques. The first step in the development of an MS-based method is the identification of biomarkers, which are, in the case of food allergens, peptides. Here, we implemented a strategy to identify the most salient peptide biomarkers in peanuts. Processed peanut matrices were prepared and analyzed using an untargeted approach via high-resolution MS. More than 300 identified peptides were further filtered using selection criteria to strengthen the analytical performance of a future, routine quantitative method. The resulting 16 peptides are robust to food processing, specific to peanuts, and satisfy sequence-based criteria. The aspect of multiple protein isoforms is also considered in the selection tree, an aspect that is essential for a quantitative method's robustness but seldom, if ever, considered.

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

The interest of using LC-MS/MS as a method for detection of allergens in food is growing. In such methods, peptides are used as biomarkers for the detection and quantification of the allergens. The selection of good biomarker peptides is of high importance to develop a specific, universal and sensitive method. Biomarkers should, for example, be robust to food processing. To evaluate robustness, test material incurred with hazelnut having undergone different food processing techniques was produced. Proteins of these materials were extracted, digested and further analyzed using HRMS. After peptide identification, selection was carried out using several criteria such as hazelnut specificity and amino acid composition. Further selection was done by comparing peptide MS intensities in the different food matrices. Only peptides showing processing robustness were retained. Eventually, eight peptides coming from three major hazelnut proteins were selected as the best biomarkers for hazelnut detection in processed foods.

Detection and Quantification of Allergens in Foods and Minimum Eliciting Doses in Food-Allergic Individuals (ThRAll).

Risk-based approaches to managing allergens in foods are being developed by the food industry and regulatory authorities to support food-allergic consumers to avoid ingestion of their problem food, especially in relation to the traces of unintended allergens. The application of such approaches requires access to good quality data from clinical studies to support identification of levels of allergens in foods that are generally safe for most food-allergic consumers as well as analytical tools that are able to quantify allergenic food protein. The ThRAll project aims to support the application of risk-based approaches to food-allergen management in two ways. First, a harmonized quantitative MS-based prototype reference method will be developed for the detection of multiple food allergens in standardized incurred food matrices. This will be undertaken for cow's milk, hen's egg, peanut, soybean, hazelnut, and almond incurred into two highly processed food matrices, chocolate and broth powder. This activity is complemented by a second objective to support the development and curation of data on oral food challenges, which are used to define thresholds and minimum eliciting doses. This will be achieved through the development of common protocols for collection and curation of data that will be applied to allergenic foods for which there are currently data gaps.

Optimizing the Use of Zebrafish Feeding Trials for the Safety Evaluation of Genetically Modified Crops.

In Europe, the toxicological safety of genetically modified (GM) crops is routinely evaluated using rodent feeding trials, originally designed for testing oral toxicity of chemical compounds. We aimed to develop and optimize methods for advancing the use of zebrafish feeding trials for the safety evaluation of GM crops, using maize as a case study. In a first step, we evaluated the effect of different maize substitution levels. Our results demonstrate the need for preliminary testing to assess potential feed component-related effects on the overall nutritional balance. Next, since a potential effect of a GM crop should ideally be interpreted relative to the natural response variation (i.e., the range of biological values that is considered normal for a particular endpoint) in order to assess the toxicological relevance, we established natural response variation datasets for various zebrafish endpoints. We applied equivalence testing to calculate threshold equivalence limits (ELs) based on the natural response variation as a method for quantifying the range within which a GM crop and its control are considered equivalent. Finally, our results illustrate that the use of commercial control diets (CCDs) and null segregant (NS) controls (helpful for assessing potential effects of the transformation process) would be valuable additions to GM safety assessment strategies.

A Novel Double-Blind, Placebo-Controlled Food Challenge Matrix for Milk and Raw Egg.

BACKGROUND: The double-blind, placebo-controlled food challenge (DBPCFC) is still considered to be the gold standard in food allergy diagnosis. This test is however not common practice in routine due to several practical limitations, especially for non-IgE-mediated food allergy with its typical delayed food allergic reactions. OBJECTIVE: The aim of this study was to develop and evaluate DBPCFC matrices for the diagnosis of milk and egg allergies which can be applied at home for the diagnosis of delayed food allergic reactions. The main focus was the blinding of milk and raw egg and the development of matrices which can be prepared and consumed conveniently at home with a sufficiently long shelf life (+/- 6 months or longer). METHODS: A sensory test evaluated the blinding of the egg and milk in the matrices. The microbiological analysis confirmed the safety and stability of the developed matrices. To assess the applicability of the matrices, a pilot DBPCFC study for milk including 7 patients was conducted. RESULTS: Sensory tests confirmed that the masking of the allergenic ingredients was sufficient. Microbial safety and stability of the matrices were confirmed up to 6 months of storage at ambient temperatures in the dark. The DBPCFC for milk showed different outcomes and proved its applicability for use at home. CONCLUSION: A novel stable DBPCFC matrix for milk and raw egg has been developed that allows convenient use at the patients' home.

Inulin chain length modification using a transgenic approach opening new perspectives for chicory.

Chicory capable of synthesizing long-chain inulin is of great interest. During the growing season, the sucrose-sucrose 1-fructosyltransferase (1-SST) activity is vital for production of long-chain inulin in chicory. With the purpose to increase inulin chain length, we employed Agrobacterium-mediated transformation method. Transgenic chicory plants (Cichorium intybus L. var. sativum) cv. 'Melci' has been developed to overexpress sucrose-sucrose 1-fructosyltransferase (1-SST) under the control of the CaMV 35S promoter. The integration of the T-DNA into the plant genome was confirmed by PCR on genomic DNA using gene-specific primers. Quantification of the 1-SST transcript expression level revealed that transgenic plants showed higher 1-SST expression than those in non-transgenic plants. Further analyses proved that the fructan content of the roots significantly increased in the transgenic plants. These results revealed that overexpression of the 1-SST, the key gene in inulin biosynthesis in chicory, might serve as a novel approach to develop plants with the long-chain inulin content.

Development and validation of a standardized double-blind, placebo-controlled food challenge matrix for raw hazelnuts.

BACKGROUND: Double-blind, placebo-controlled food challenge (DBPCFC) is considered the gold standard for food allergy diagnosis. However, this test is rarely performed routinely in clinical practice because of various practical issues, e.g. the lack of a standardized matrix preparation. The aim of this study was to develop and validate a convenient DBPCFC matrix, that can easily be implemented in daily clinical practice. The focus of this study was the blinding of hazelnuts, whereby the hazelnuts retained as much as possible their allergenicity and could be mixed homogenously in low-doses to the matrices. METHODS: A basophil-activation test (BAT), microbial tests and an LC-MS/MS test were performed to assess respectively the allergenicity of the used hazelnuts, the microbial stability of the novel developed matrices and the homogeneity of the hazelnuts in the matrices. A sensory test was conducted to validate the blinding of the hazelnuts in the matrices. A pilot DBPCFC study included eight patients as proof of concept. RESULTS: The BAT-test gave the first insights concerning the retained allergenicity of the hazelnuts. The microbial safety could be assured after 12 months of storage. Sufficient masking was assessed by several sensory tests. Homogeneous hazelnut distribution could be achieved for the different hazelnut concentrations. The DBPCFC's results showed diverse allergic responders (from no reactions to distinct objective symptoms). CONCLUSION: A novel stable and validated DBPCFC matrix using raw hazelnuts has been developed that allows easy preparation in a standardized way for convenient use in daily clinical practice.Trial registration EC Project number: EC/2015/0852; Date of registration: 13 Oct 2015; End date: 01 Feb 2017.

Development of an LC-MS/MS method for the detection of traces of peanut allergens in chili pepper.

The recent detection of nuts (including peanut) in spices across the globe has led to enormous recalls of several spices and food products in the last two years. The lack of validated detection methods specific for spices makes it difficult to assess allergen presence at trace levels. Because of the urgent need for confirmation of possible peanut presence in chili peppers, an LC-MS/MS method was optimized and developed for this particular food matrix. Although several studies optimized LC-MS detection strategies specific for peanuts, the presence of complex components in the spices (e.g., phenolic components) makes method optimization and validation necessarily. Focus was laid on validation of the method with real incurred chili peppers (whereby a known amount of peanut is added) at low concentrations, to deal with possible matrix interferences. LC-MS/MS proves to be a good alternative to the currently most applied methods (ELISA and RT-PCR) and can be used as a complementary method of analysis when results are unclear. Peanut marker peptides were selected based on their abundancy in digested incurred chili peppers. The limit of detection was determined to be 24 ppm (mg peanut/kg), a level whereby the risk for potential allergic reactions is zero, considering the typical portion size of spices. The chili pepper powder under investigation proved to contain low levels of peanuts after LC-MS/MS, ELISA, and RT-PCR testing. Graphical abstract Standard curve of the detected peanuts in chili pepper samples using the novel LC-MS/MS method.

An integrated strategy combining DNA walking and NGS to detect GMOs.

Recently, we developed a DNA walking system for the detection and characterization of a broad spectrum of GMOs in routine analysis of food/feed matrices. Here, we present a new version with improved throughput and sensitivity by coupling the DNA walking system to Pacific Bioscience® Next-generation sequencing technology. The performance of the new strategy was thoroughly assessed through several assays. First, we tested its detection and identification capability on grains with high or low GMO content. Second, the potential impacts of food processing were investigated using rice noodle samples. Finally, GMO mixtures and a real-life sample were analyzed to illustrate the applicability of the proposed strategy in routine GMO analysis. In all tested samples, the presence of multiple GMOs was unambiguously proven by the characterization of transgene flanking regions and the combinations of elements that are typical for transgene constructs.

How Can We Better Detect Unauthorized GMOs in Food and Feed Chains?

Current GMO detection systems have limited abilities to detect unauthorized genetically modified organisms (GMOs). Here, we propose a new workflow, based on next-generation sequencing (NGS) technology, to overcome this problem. In providing information about DNA sequences, this high-throughput workflow can distinguish authorized and unauthorized GMOs by strengthening the tools commonly used by enforcement laboratories with the help of NGS technology. In addition, thanks to its massive sequencing capacity, this workflow could be used to monitor GMOs present in the food and feed chain. In view of its potential implementation by enforcement laboratories, we discuss this innovative approach, its current limitations, and its sustainability of use over time.

Statistical framework for detection of genetically modified organisms based on Next Generation Sequencing.

Because the number and diversity of genetically modified (GM) crops has significantly increased, their analysis based on real-time PCR (qPCR) methods is becoming increasingly complex and laborious. While several pioneers already investigated Next Generation Sequencing (NGS) as an alternative to qPCR, its practical use has not been assessed for routine analysis. In this study a statistical framework was developed to predict the number of NGS reads needed to detect transgene sequences, to prove their integration into the host genome and to identify the specific transgene event in a sample with known composition. This framework was validated by applying it to experimental data from food matrices composed of pure GM rice, processed GM rice (noodles) or a 10% GM/non-GM rice mixture, revealing some influential factors. Finally, feasibility of NGS for routine analysis of GM crops was investigated by applying the framework to samples commonly encountered in routine analysis of GM crops.

Current and new approaches in GMO detection: challenges and solutions.

In many countries, genetically modified organisms (GMO) legislations have been established in order to guarantee the traceability of food/feed products on the market and to protect the consumer freedom of choice. Therefore, several GMO detection strategies, mainly based on DNA, have been developed to implement these legislations. Due to its numerous advantages, the quantitative PCR (qPCR) is the method of choice for the enforcement laboratories in GMO routine analysis. However, given the increasing number and diversity of GMO developed and put on the market around the world, some technical hurdles could be encountered with the qPCR technology, mainly owing to its inherent properties. To address these challenges, alternative GMO detection methods have been developed, allowing faster detections of single GM target (e.g., loop-mediated isothermal amplification), simultaneous detections of multiple GM targets (e.g., PCR capillary gel electrophoresis, microarray, and Luminex), more accurate quantification of GM targets (e.g., digital PCR), or characterization of partially known (e.g., DNA walking and Next Generation Sequencing (NGS)) or unknown (e.g., NGS) GMO. The benefits and drawbacks of these methods are discussed in this review.