Targeted proteomics: Current status and future perspectives for quantification of food allergens

Research Progress in Isotope Labeling/Tags-Based Protein Quantification and Metrology Technologies

Advanced liquid chromatogram-mass spectrometry (LC-MS) and automated large-scale data processing have made MS-based quantitative analysis increasingly useful for research in fields such as biology, medicine, food safety, and beyond. This is because MS-based quantitative analysis can accurately and sensitively analyze thousands of proteins and peptides in a single experiment. However, the precision, coverage, complexity, and resilience of conventional quantification methods vary as a result of the modifications to the analytic environment and the physicochemical characteristics of analytes. Therefore, specially designed approaches are necessary for sample preparation. Dozens of methods have been developed and adapted for these needs based on stable isotopic labeling or isobaric tagging, each with distinct characteristics. In this review, we will summarize the leading strategies and techniques used thus far for MS-based protein quantification as well as analyze the advantages and shortcomings of different approaches. Additionally, we provide an overview of protein metrology development.

Food allergen detection by mass spectrometry: From common to novel protein ingredients

Food allergens are molecules, mainly proteins, that trigger immune responses in susceptible individuals upon consumption even when they would otherwise be harmless. Symptoms of a food allergy can range from mild to acute; this last effect is a severe and potentially life-threatening reaction. The European Union (EU) has identified 14 common food allergens, but new allergens are likely to emerge with constantly changing food habits. Mass spectrometry (MS) is a promising alternative to traditional antibody-based assays for quantifying multiple allergenic proteins in complex matrices with high sensitivity and selectivity. Here, the main allergenic proteins and the advantages and drawbacks of some MS acquisition protocols, such as multiple reaction monitoring (MRM) and data-dependent analysis (DDA) for identifying and quantifying common allergenic proteins in processed foodstuffs are summarized. Sections dedicated to novel foods like microalgae and insects as new sources of allergenic proteins are included, emphasizing the significance of establishing stable marker peptides and validated methods using database searches. The discussion involves the in-silico digestion of allergenic proteins, providing insights into their potential impact on immunogenicity. Finally, case studies focussing on microalgae highlight the value of MS as an effective analytical tool for ensuring regulatory compliance throughout the food control chain.

Proteomics in Inherited Metabolic Disorders

Inherited metabolic disorders (IMD) are rare medical conditions caused by genetic defects that interfere with the body's metabolism. The clinical phenotype is highly variable and can present at any age, although it more often manifests in childhood. The number of treatable IMDs has increased in recent years, making early diagnosis and a better understanding of the natural history of the disease more important than ever. In this review, we discuss the main challenges faced in applying proteomics to the study of IMDs, and the key advances achieved in this field using tandem mass spectrometry (MS/MS). This technology enables the analysis of large numbers of proteins in different body fluids (serum, plasma, urine, saliva, tears) with a single analysis of each sample, and can even be applied to dried samples. MS/MS has thus emerged as the tool of choice for proteome characterization and has provided new insights into many diseases and biological systems. In the last 10 years, sequential window acquisition of all theoretical fragmentation spectra mass spectrometry (SWATH-MS) has emerged as an accurate, high-resolution technique for the identification and quantification of proteins differentially expressed between healthy controls and IMD patients. Proteomics is a particularly promising approach to help obtain more information on rare genetic diseases, including identification of biomarkers to aid early diagnosis and better understanding of the underlying pathophysiology to guide the development of new therapies. Here, we summarize new and emerging proteomic technologies and discuss current uses and limitations of this approach to identify and quantify proteins. Moreover, we describe the use of proteomics to identify the mechanisms regulating complex IMD phenotypes; an area of research essential to better understand these rare disorders and many other human diseases.

Smartphone-integrated fluorescent quenching immunochromatographic test strips designed for the determination of sesame allergens in food samples

A highly sensitive smartphone-integrated fluorescence quenching immunochromatographic assay (FQICA) for the detection of sesame allergen was proposed. Sesame antibodies were adsorbed on the surface of the gold nanoparticles to form fluorescent acceptors (AuNPs-Ab). Ovalbumin (OVA) protein was labeled with quantum dots (QDs) to form signal probes (QDs-OVA), which were coated on the C-line of the assay strips. A mixture of QDs-OVA and sesame protein was coated on the T-line of the strip. For FQICA, the concentration of the analyte was positively correlated with the fluorescence signal. The developed FQICA had high sensitivity for the detection of sesame protein, and its visual LOD was 80 μg/L and the quantitative LOD was 40 μg/L. In addition, the method had high specificity, except for a small cross-reaction between sesame and walnut. The visual LODs in bread, ham, and biscuits were 640 μg/L. The quantitative LODs were 320 μg/L for biscuits and 640 μg/L for bread and ham. Comparing the developed FQICA with a commercial ELISA kit, the recoveries of sesame protein in both methods were between 80% and 120%.

Comprehensive quantitation of multi-signature peptides originating from casein for the discrimination of milk from eight different animal species using LC-HRMS with stable isotope labeled peptides

Milk species adulteration has become an altering issue worldwide. In this study, a robust quantification method based on LC-HRMS for the simultaneous detection and differentiation of milk type from eight different animal species (namely: cow, water buffalo, wild yak, goat, sheep, donkey, horse, and camel) was established by detecting nine signature peptides originating from casein. The developed method was in-house validated in terms of sensitivity, accuracy, and precision. As a result, limits of quantification (LOQ) were ranging from 5 to 30 µg/L, recoveries ranged from 95.2% to 104.5%, and intra-day and inter-day variability were lower than 11.4% and 12.6%, respectively, for all the targeted peptides. Furthermore, this method was successfully applied to 46 commercial minor species' milk, in which 15 samples were false labeling. The obtained results indicate the necessity to monitor milk species adulteration in order to protect consumers from consuming misleading labeled minor species animal's milk.

Targeted proteomics and specific immunoassays reveal the presence of shared allergens between the zoonotic nematodes Anisakis simplex and Pseudoterranova decipiens

The family Anisakidae, mainly represented by Anisakis simplex s.l. and Pseudoterranova decipiens, encompasses zoonotic nematodes infecting many marine fish. Both are responsible for gastrointestinal disease in humans after ingestion of a live larva by consumption of undercooked fish, and, in the case of A. simplex, an allergic reaction may occur after consuming or even handling infected fish. Due to its phylogenetic relatedness with A. simplex, few studies investigated the allergenic potential of P. decipiens, yet none of them focused on its excretory/secretory (E/S) proteins that easily get missed when working solely on extracts from crushed nematodes. Moreover, these E/S allergens remain behind even when the larva has been removed during fish quality processing. Therefore, the aim was to investigate if Anisakis-like allergens could also be detected in both crushed and E/S P. decipiens protein extract using targeted mass spectrometry analysis and immunological methods. The results confirmed that at least five A. simplex allergens have homologous proteins in P. decipiens; a result that emphasizes the importance of also including E/S protein extracts in proteomic studies. Not only A. simplex, but also P. decipiens should therefore be considered a potential source of allergens that could lead to hypersensitivity reactions in humans.

Absolute quantification of Bet v 1 in birch polymerized allergenic extracts via mass spectrometry-targeted analysis

BACKGROUND

Quantifying major allergens is essential for evaluating the quality and efficacy of allergenic extracts. They are usually measured in non-polymerized extracts using immunoassays. However, the direct measurement of allergens in allergoids is currently not supported. This study set out to develop a method for quantifying Bet v 1 in polymerized birch extracts using mass spectrometry-based targeted analysis.

METHODS

Three isotopically labelled peptide sequences of Bet v 1 were synthetized and used as internal standards for the development of a mass spectrometry-based targeted analysis. The calibration curves of the three peptides to assess the linearity and limit of detection, as well as reverse calibration curves with a constant amount of sample, were constructed. The Bet v 1 content was determined and measured in 18 batches of depigmented (native extracts purified by a mild acid treatment) and depigmented-polymerized extracts.

RESULTS

Bet v 1 isoforms were identified in both type of extracts by mass spectrometry. According to mass spectrometry-targeted analysis depigmented and depigmented-polymerized extracts exhibited mean values of 70.5 and 73.5 µg Bet v 1/mg of lyophilized extract, respectively. A statistically significant correlation between the allergen content of both extracts was identified. Statistically significant differences were observed when the Bet v 1 content in non-polymerized extracts was measured via mass spectrometry (70.5 ± 11.6 µg/mg) or immunoassay (83.7 ± 19.8 µg/mg).

CONCLUSIONS

These results represent the first direct quantification of Bet v 1 in allergoids using mass spectrometry-based targeted analysis. The proposed method demonstrates robustness and reliability and constitutes a promising alternative for detailed characterization of polymerized allergenic extracts.

The History, Present and Future of Allergen Standardization in the United States and Europe

The topic of standardization in relation to allergen products has been discussed by allergists, regulators, and manufacturers for a long time. In contrast to synthetic medicinal products, the natural origin of allergen products makes the necessary comparability difficult to achieve. This holds true for both aspects of standardization: Batch-to-batch consistency (or product-specific standardization) and comparability among products from different manufacturers (or cross-product comparability). In this review, we focus on how the United States and the European Union have tackled the topic of allergen product standardization in the past, covering the early joint standardization efforts in the 1970s and 1980s as well as the different paths taken by the two players thereafter until today. So far, these two paths have been based on rather classical immunological methods, including the corresponding benefits like simple feasability. New technologies such as mass spectrometry present an opportunity to redefine the field of allergen standardization in the future.

Disposable electrochemical microfluidic device for ultrasensitive detection of egg allergen in wine samples

Food allergies have been increasing all over the world. Egg is an important component in the food industries and the second most common cause of food allergy, shortly after milk. In the wine industry, egg white is applied as a fining agent for tannin removal. In this study, a sandwich-based immunoassay for ultrasensitive detection of ovalbumin (OVA) in wine samples was developed. The assay involves the use of magnetic beads (MBs) decorated with a polyclonal anti-OVA antibody (Ab₂) and horseradish peroxidase (HRP), used as label for the quantification in a disposable electrochemical microfluidic device (DEμD) here developed. The Ab₂-MB-HRP prepared was applied to capture, separate, and pre-concentrate OVA from wine samples. In the DEμD, OVA was immune-magnetically captured (OVA-Ab₂-MB-HRP), producing a sandwich structure (GO-Ab₁-OVA-Ab₂-MB-HRP) on the electrode's surface. This arrangement results in an ultrasensitive device, achieving the ultralow limit of detection of 0.2 fg mL^-1 OVA. Five samples of wines were analyzed by using the immuno-magneto-assay which presents excellent accuracy compared with enzyme-linked immunosorbent assay (ELISA).

Proteomic Advances in Cereal and Vegetable Crops

The importance of vegetables in human nutrition, such as cereals, which in many cases represent the main source of daily energy for humans, added to the impact that the incessant increase in demographic pressure has on the demand for these plant foods, entails the search for new technologies that can alleviate this pressure on markets while reducing the carbon footprint of related activities. Plant proteomics arises as a response to these problems, and through research and the application of new technologies, it attempts to enhance areas of food science that are fundamental for the optimization of processes. This review aims to present the different approaches and tools of proteomics in the investigation of new methods for the development of vegetable crops. In the last two decades, different studies in the control of the quality of crops have reported very interesting results that can help us to verify parameters as important as food safety, the authenticity of the products, or the increase in the yield by early detection of diseases. A strategic plan that encourages the incorporation of these new methods into the industry will be essential to promote the use of proteomics and all the advantages it offers in the optimization of processes and the solution of problems.

Application of Mass Spectrometry-Based Proteomics to Barley Research

Barley (Hordeum vulgare) is the fourth most cultivated crop in the world in terms of production volume, and it is also the most important raw material of the malting and brewing industries. Barley belongs to the grass (Poaceae) family and plays an important role in food security and food safety for both humans and livestock. With the global population set to reach 9.7 billion by 2050, but with less available and/or suitable land for agriculture, the use of biotechnology tools in breeding programs are of considerable importance in the quest to meet the growing food gap. Proteomics as a member of the "omics" technologies has become popular for the investigation of proteins in cereal crops and particularly barley and its related products such as malt and beer. This technology has been applied to study how proteins in barley respond to adverse environmental conditions including abiotic and/or biotic stresses, how they are impacted during food processing including malting and brewing, and the presence of proteins implicated in celiac disease. Moreover, proteomics can be used in the future to inform breeding programs that aim to enhance the nutritional value and broaden the application of this crop in new food and beverage products. Mass spectrometry analysis is a valuable tool that, along with genomics and transcriptomics, can inform plant breeding strategies that aim to produce superior barley varieties. In this review, recent studies employing both qualitative and quantitative mass spectrometry approaches are explored with a focus on their application in cultivation, manufacturing, processing, quality, and the safety of barley and its related products.

Multi-Omics Approach in the Identification of Potential Therapeutic Biomolecule for COVID-19

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has a disastrous effect on mankind due to the contagious and rapid nature of its spread. Although vaccines for SARS-CoV-2 have been successfully developed, the proven, effective, and specific therapeutic molecules are yet to be identified for the treatment. The repurposing of existing drugs and recognition of new medicines are continuously in progress. Efforts are being made to single out plant-based novel therapeutic compounds. As a result, some of these biomolecules are in their testing phase. During these efforts, the whole-genome sequencing of SARS-CoV-2 has given the direction to explore the omics systems and approaches to overcome this unprecedented health challenge globally. Genome, proteome, and metagenome sequence analyses have helped identify virus nature, thereby assisting in understanding the molecular mechanism, structural understanding, and disease propagation. The multi-omics approaches offer various tools and strategies for identifying potential therapeutic biomolecules for COVID-19 and exploring the plants producing biomolecules that can be used as biopharmaceutical products. This review explores the available multi-omics approaches and their scope to investigate the therapeutic promises of plant-based biomolecules in treating SARS-CoV-2 infection.

Multi-Omics Approach in the Identification of Potential Therapeutic Biomolecule for COVID-19

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has a disastrous effect on mankind due to the contagious and rapid nature of its spread. Although vaccines for SARS-CoV-2 have been successfully developed, the proven, effective, and specific therapeutic molecules are yet to be identified for the treatment. The repurposing of existing drugs and recognition of new medicines are continuously in progress. Efforts are being made to single out plant-based novel therapeutic compounds. As a result, some of these biomolecules are in their testing phase. During these efforts, the whole-genome sequencing of SARS-CoV-2 has given the direction to explore the omics systems and approaches to overcome this unprecedented health challenge globally. Genome, proteome, and metagenome sequence analyses have helped identify virus nature, thereby assisting in understanding the molecular mechanism, structural understanding, and disease propagation. The multi-omics approaches offer various tools and strategies for identifying potential therapeutic biomolecules for COVID-19 and exploring the plants producing biomolecules that can be used as biopharmaceutical products. This review explores the available multi-omics approaches and their scope to investigate the therapeutic promises of plant-based biomolecules in treating SARS-CoV-2 infection.

Current Trends in Proteomic Advances for Food Allergen Analysis

Food allergies are a global food challenge. For correct food labelling, the detection and quantification of allergens are necessary. However, novel product formulations and industrial processes produce new scenarios, which require much more technological developments. For this purpose, OMICS technologies, especially proteomics, seemed to be relevant in this context. This review summarises the current knowledge and studies that used proteomics to study food allergens. In the case of the allergenic proteins, a wide variety of isoforms, post-translational modifications and other structural changes during food processing can increase or decrease the allergenicity. Most of the plant-based food allergens are proteins with biological functions involved in storage, structure, and plant defence. The allergenicity of these proteins could be increased by the presence of heavy metals, air pollution, and pesticides. Targeted proteomics like selected/multiple reaction monitoring (SRM/MRM) have been very useful, especially in the case of gluten from wheat, rye and barley, and allergens from lentil, soy, and fruit. Conventional 1D and 2-DE immunoblotting have been further widely used. For animal-based food allergens, the widely used technologies are 1D and 2-DE immunoblotting followed by MALDI-TOF/TOF, and more recently LC-MS/MS, which is becoming useful to assess egg, fish, or milk allergens. The detection and quantification of allergenic proteins using mass spectrometry-based proteomics are promising and would contribute to greater accuracy, therefore improving consumer information.

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.

LC-HRMS/MS for the simultaneous determination of four allergens in fish and swine food products

The inclusion on the label of packed foods of any ingredient or technological adjuvant causing allergies is required by EU food legislation. In this study a targeted proteomics method for detecting four allergens in animal-derived food matrices was developed. Liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) was used to select marker peptides from four allergens and develop a quantitative method able to simultaneously detect the presence of milk, egg, crustaceans and soy. The method was validated on fish or swine processed food products contaminated at 5 μg g^-1 for milk and egg and 10 μg g^-1 for soy and crustaceans. The method was tested by analyzing commercial food products with high protein content and was compared to the ELISA technique. Our results indicated the presence of soy not reported on the food label of some products, pointing out the need for efficient controls to protect allergic consumers.

Use of IHF-QD Microscopic Analysis for the Detection of Food Allergenic Components: Peanuts and Wheat Protein

The aim of the study was to analytically evaluate quantum dots in immunohistofluorescence (IHF-QD) microscopic imaging as detectors of food allergens—peanut and wheat. The experiment was designed as two in silico experiments or simulations: (a) models of pastry samples were prepared with the addition of allergenic components (peanut and wheat protein components) and without the addition of allergenic components, and (b) positive and negative commercial samples underwent food allergen detection. The samples from both simulations were tested by the ELISA and IHF-QD microscopic methods. The primary antibodies (secondary antibodies to a rabbit Fc fragment with labeled CdSe/ZnS QD) were labelled at 525, 585, and 655 nm emissions. The use of quantum dots (QDs) has expanded to many science areas and they are also finding use in food allergen detection, as shown in the study. The study indicated that differences between the ELISA and IHF-QD microscopic methods were not observable among experimentally produced pastry samples with and without allergenic components, although differences were observed among commercial samples. The important value of the study is certainly the differences found in the application of different QD conjugates (525, 585, and 655). The highest contrast was found in the application of 585 QD conjugates that can serve for the possible quantification of present food allergens—peanuts and wheat. The study clearly emphasized that QD can be used for the qualitative detection of food allergens and can represent a reliable analytical method for food allergen detection in different food matrixes.

Mycoprotein: environmental impact and health aspects

The term mycoprotein refers to the protein-rich food made of filamentous fungal biomass that can be consumed as an alternative to meat. In this paper, the impact caused by the substitution of animal-origin meat in the human diet for mycoprotein on the health and the environment is reviewed. Presently, mycoprotein can be found in the supermarkets of developed countries in several forms (e.g. sausages and patties). Expansion to other markets depends on the reduction of the costs. Although scarce, the results of life cycle analyses of mycoprotein agree that this meat substitute causes an environmental impact similar to chicken and pork. In this context, the use of inexpensive agro-industrial residues as substrate for mycoprotein production has been investigated. This strategy is believed to reduce the costs involved in the fungal cultivation and lower the environmental impact of both the mycoprotein and the food industry. Moreover, several positive effects in health have been associated with the substitution of meat for mycoprotein, including improvements in blood cholesterol concentration and glycemic response. Mycoprotein has found a place in the market, but questions regarding the consumer's experience on the sensory and health aspects are still being investigated.

The role of incurred materials in method development and validation to account for food processing effects in food allergen analysis

The issue of undeclared allergens represents a matter of great concern, being the subject of many alert notifications by the Rapid Alert System for Food and Feed portal of the European Commission, often leading to food recalls. The availability of reliable analytical approaches able to detect and quantify hidden allergens in processed foods is increasingly requested by the food industry, food safety authorities and regulatory bodies to protect sensitive consumers' health. The present review discusses the fundamental role of incurred materials for method development and analytical performance assessment in a metrology perspective on testing for undeclared allergens in processed foodstuffs. Due to the nature of the analytes and their susceptibility to various processing effects, reliability and comparability of results have posed a great challenge. In this context, the use of incurred samples as reference materials permits simulation of the effects of food processing on target analyte structure affecting analyte extractability and detectability. Graphical abstract ᅟ.

Determination of food allergens by LC-MS: Impacts of sample preparation, food matrix, and thermal processing on peptide detectability and quantification

Food allergies are a growing worldwide concern and the contamination of products with food allergens represents a significant health risk to allergic consumers. With the introduction of reference doses, quantitative methods are needed for the monitoring of allergen levels, and the potential of LC-MS/MS is of hugely growing interest. In this study, we demonstrate that relevant food matrices (bakery products and chocolates) and thermal food processing substantially influence the quantification of 18 marker peptides from various nut and peanut allergens via targeted proteomics. In addition, we characterize the individual release kinetics of marker peptides and provide examples for metastable marker peptide candidates. Matrix recovery rates overall ranged between 15 and 250% with the observed variation being linked to the individual peptide structure as well as to specific matrix interferences. In contrast, thermal processing considerably influences the detectability of allergens on the protein level as different marker peptides from the identical parent allergen are similarly affected, leading to a loss in signal of up to 83% in extreme cases after a 45-min simulated baking. Provided data are finally used for evaluation of different calibrators as well as the overall potential and challenges of LC-MS for the absolute quantification of food allergens. SIGNIFICANCE: With the scientific discussion moving towards a risk-based management of food allergens, including the establishment of threshold doses, robust methods for the absolute quantification of allergens in food samples are urgently needed. Because the currently used antibody- and DNA-based technologies show severe limitations in terms of specificity and reproducibility, LC-MS has emerged as a promising alternative. Its application to absolute quantification, however, first requires an understanding of the various impacts that affect quantification results, including different food matrices, sample preparation, and thermal processing of foodstuffs. Knowledge of these factors, which are assessed as part of a comprehensive survey in this study, is also an important prerequisite to evaluate means of calibration for an LC-MS-based quantification of food allergens.

Absolute Quantitation of Plant Proteins

Among targeted proteomic techniques, AQUA-MRM is considered as one of the most reliable for accurate protein quantitation. This method displays high sensitivity, specificity, and reproducibility compared to many common biochemical techniques by coupling the use of unique, heavy-labeled peptide standards and triple-quadrupole mass spectrometry. However, there are several important steps that are required for successful development and validation of a robust AQUA-MRM assay. The following protocol outlines and details the key steps necessary for plant sample preparation as well as AQUA-MRM development and validation, specifically for absolute quantitation of plant proteins in vivo. © 2018 by John Wiley & Sons, Inc.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

Detection of allergen coding sequences of kiwi, peach, and apple in processed food by qPCR

BACKGROUND

Food traceability becomes lifesaving for persons suffering severe allergy or intolerance, and therefore need a complete avoidance of the immune-trigger food. This paper describes how to fingerprint the presence of some allergenic species (kiwi, peach, and apple) in foods by quantitative real-time PCR (qPCR).

RESULTS

Five DNA extraction procedures were tested on fruits and foods. The results were statistically evaluated, and discussed. Analysis by qPCR with SYBR Green was developed to detect traces of these allergenic species in foods. Plasmids containing the target sequences of kiwi, peach and apple were employed as internal reference standard. Analysis of spiked food samples showed a limit of detection of 25 mg kg^-1 for kiwi, 20 mg kg^-1 for peach and 50 mg kg^-1 for apple.

CONCLUSION

The qPCR method here developed, combined with the use of internal plasmid reference standard, represents a specific system for the quick detection of allergenic species in complex food matrices, with a limit of detection comparable with those reported using more time-consuming methods. © 2017 Society of Chemical Industry.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Mass Spectrometric Analysis of N-Glycoforms of Soybean Allergenic Glycoproteins Separated by SDS-PAGE

Glycosylation of many proteins has been revealed to be closely related with food allergies, and screening and structural analysis of related glycoproteins and glycoallergens are essential for studies in this field. Herein, we describe detailed N-glycoform analysis of all glycoprotein fractions of soybean protein isolate (SPI) separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) to disclose structural features of the glycan moieties of more soybean glycoproteins. SPI was fractionated by SDS-PAGE, and the generated protein bands were recovered and subjected to in-gel N-glycan release and labeling using a one-pot method newly developed by our group, followed by detailed analysis by electrospray ionization mass spectrometry (ESI-MS) and online hydrophilic interaction liquid chromatography coupled with electrospray ionization tandem mass spectrometry (HILIC-ESI-MS/MS). As a result, we found seven bands mainly containing oligomannose-type glycans; two mainly contain core α1,3-fucosylated glycans, and six have no glycans. This study is the first report that discovers core α1,3-fucosylated N-glycans in bands 1, 2, and 6 and discloses bands 3, 4, 5, and 7 as glycoproteins and their N-glycoforms. Therefore, it can expand our knowledge about soybean protein glycosylation and provide significant structural reference for research of soybean allergens.

MRM3-based LC-MS multi-method for the detection and quantification of nut allergens

Food allergies have become a global challenge to food safety in industrialized countries in recent years. With governmental monitoring and legislation moving towards the establishment of threshold allergen doses, there is a need for sensitive and quantitative analytical methods for the determination of allergenic food contaminants. Targeted proteomics employing liquid chromatography-mass spectrometry (LC-MS) has emerged as a promising technique that offers increased specificity and reproducibility compared to antibody and DNA-based technologies. As the detection of trace levels of allergenic food contaminants also demands excellent sensitivity, we aimed to significantly increase the analytical performance of LC-MS by utilizing multiple reaction monitoring cubed (MRM³) technology. Following a bottom-up proteomics approach, including a straightforward sample preparation process, 38 MRM³ experiments specific to 18 proteotypic peptides were developed and optimized. This permitted the highly specific identification of peanut, almond, cashew, hazelnut, pistachio, and walnut. The analytical performance of the method was assessed for three relevant food matrices with different chemical compositions. Limits of detection were around 1 μg/g or below in fortified matrix samples, not accounting for the effects of food processing. Compared to an MRM-based approach, the MRM³-based method showed an increase in sensitivity of up to 30-fold. Regression analysis demonstrated high linearity of the MRM³ signal in spiked matrix samples together with robust intersample reproducibility, confirming that the method is highly applicable for quantitative purposes. To the best of our knowledge, we describe here the most sensitive LC-MS multi-method for food allergen detection thus far. In addition, this is the first study that systematically compares MRM³ with MRM for the analysis of complex foods. Graphical abstract Allergen detection by MRM³.

Using Proteomics to Understand How Leishmania Parasites Survive inside the Host and Establish Infection

Leishmania is a protozoan parasite that causes a wide range of different clinical manifestations in mammalian hosts. It is a major public health risk on different continents and represents one of the most important neglected diseases. Due to the high toxicity of the drugs currently used, and in the light of increasing drug resistance, there is a critical need to develop new drugs and vaccines to control Leishmania infection. Over the past few years, proteomics has become an important tool to understand the underlying biology of Leishmania parasites and host interaction. The large-scale study of proteins, both in parasites and within the host in response to infection, can accelerate the discovery of new therapeutic targets. By studying the proteomes of host cells and tissues infected with Leishmania, as well as changes in protein profiles among promastigotes and amastigotes, scientists hope to better understand the biology involved in the parasite survival and the host-parasite interaction. This review demonstrates the feasibility of proteomics as an approach to identify new proteins involved in Leishmania differentiation and intracellular survival.