The ETHYLENE RESPONSE FACTORs ERF6 and ERF11 Antagonistically Regulate Mannitol-Induced Growth Inhibition in Arabidopsis.

Leaf growth is a tightly regulated and complex process, which responds in a dynamic manner to changing environmental conditions, but the mechanisms that reduce growth under adverse conditions are rather poorly understood. We previously identified a growth inhibitory pathway regulating leaf growth upon exposure to a low concentration of mannitol and characterized the ETHYLENE RESPONSE FACTOR (ERF)/APETALA2 transcription factor ERF6 as a central activator of both leaf growth inhibition and induction of stress tolerance genes. Here, we describe the role of the transcriptional repressor ERF11 in relation to the ERF6-mediated stress response in Arabidopsis (Arabidopsis thaliana). Using inducible overexpression lines, we show that ERF6 induces the expression of ERF11. ERF11 in turn molecularly counteracts the action of ERF6 and represses at least some of the ERF6-induced genes by directly competing for the target gene promoters. As a phenotypical consequence of the ERF6-ERF11 antagonism, the extreme dwarfism caused by ERF6 overexpression is suppressed by overexpression of ERF11. Together, our data demonstrate that dynamic mechanisms exist to fine-tune the stress response and that ERF11 counteracts ERF6 to maintain a balance between plant growth and stress defense.

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.

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.

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.

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.

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.