Comprehensive analysis of the peanut allergome combining 2-DE gel-based and gel-free proteomics

Comparative Seed Proteome Profile Reveals No Alternation of Major Allergens in High-Yielding Mung Bean Cultivars

Mung bean contains up to 32.6% protein and is one of the great sources of plant-based protein. Because many allergens also function as defense-related proteins, it is important to determine their abundance levels in the high-yielding, disease-resistant cultivars. In this study, for the first time, we compared the seed proteome of high-yielding mung bean cultivars developed by a conventional breeding approach. Using a label-free quantitative proteomic platform, we successfully identified and quantified a total of 1373 proteins. Comparative analysis between the high-yielding disease-resistant cultivar (MC5) and the other three cultivars showed that a total of 69 common proteins were significantly altered in their abundances across all cultivars. Bioinformatic analysis of these altered proteins demonstrated that PDF1 (a defensin-like protein) exhibited high sequence similarity and epitope matching with the established peanut allergens, indicating a potential mung bean allergen that showed a cultivar-specific response. Conversely, known mung bean allergen proteins such as PR-2/PR-10 (Vig r 1), Vig r 2, Vig r 4, LTP1, β-conglycinin, and glycinin G4 showed no alternation in the MC5 compared to other cultivars. Taken together, our findings suggest that the known allergen profiles may not be impacted by the conventional plant breeding method to develop improved mung bean cultivars.

Proteomic characterization of extracellular vesicles in programmed cell death

Programmed cell death (PCD) is a fundamental biological process that plays a critical role in cell development, differentiation, and homeostasis. The secretion and uptake of extracellular vesicles (EVs) is one of the important regulatory mechanisms for PCD. EVs are natural membrane structures secreted by cells that contain a variety of proteins, lipids, nucleic acids, and other bioactive molecules. Due to their important roles in intercellular communication and disease progression, there is great interest in studying EVs and their cargo. Different protein components are sorted and packaged in EVs, allowing EVs to perform their functions. The study of EV proteomics helps us understand the role of PCD in the development of diseases. Meanwhile, proteomics is a powerful tool for studying the composition and function of EVs, which assists in the identification, quantification, and profiling of protein components of EVs, and provides insight into the molecular mechanisms involved in PCD and related diseases. In this review, we summarize the characteristics of EV proteomics in different types of PCD, compare different proteomic profiling strategies for EVs, and discuss the impact of EV proteomics on cell function and regulation during PCD, to understand its role in the pathogenesis of related diseases.

Crop Proteomics under Abiotic Stress: From Data to Insights

Food security is a major challenge in the present world due to erratic weather and climatic changes. Environmental stress negatively affects plant growth and development which leads to reduced crop yields. Technological advancements have caused remarkable improvements in crop-breeding programs. Proteins have an indispensable role in developing stress resilience and tolerance in crops. Genomic and biotechnological advancements have made the process of crop improvement more accurate and targeted. Proteomic studies provide the information required for such targeted approaches. The crosstalk among cellular components is being analyzed by subcellular proteomics. Additionally, the functional diversity of proteins is being unraveled by post-translational modifications during abiotic stress. The exploration of precise cellular responses and the networking among different cellular organelles help in the prediction of signaling pathways and protein-protein interactions. High-throughput mass-spectrometry-based protein studies are now possible due to incremental advancements in mass-spectrometry techniques, sample protocols, and bioinformatic tools as well as the increasing availability of plant genome sequence information for multiple species. In this review, the key role of proteomic analysis in identifying the abiotic-stress-responsive mechanisms in various crops was summarized. The development and availability of advanced computational tools were discussed in detail. The highly variable protein responses among different crops have provided a wide avenue for molecular-marker-assisted genetic buildup studies to develop smart, high-yielding, and stress-tolerant varieties to cope with food-security challenges.

Cross-linking reactions in food proteins and proteomic approaches for their detection

Various protein cross-linking reactions leading to molecular polymerization and covalent aggregates have been described in processed foods. They are an undesired side effect of processes designed to reduce bacterial load, extend shelf life, and modify technological properties, as well as being an expected result of treatments designed to modify raw material texture and function. Although the formation of these products is known to affect the sensory and technological properties of foods, the corresponding cross-linking reactions and resulting protein polymers have not yet undergone detailed molecular characterization. This is essential for describing how their generation can be related to food processing conditions and quality parameters. Due to the complex structure of cross-linked species, bottom-up proteomic procedures developed to characterize various amino acid modifications associated with food processing conditions currently offer a limited molecular description of bridged peptide structures. Recent progress in cross-linking mass spectrometry for the topological characterization of protein complexes has facilitated the development of various proteomic methods and bioinformatic tools for unveiling bridged species, which can now also be used for the detailed molecular characterization of polymeric cross-linked products in processed foods. We here examine their benefits and limitations in terms of evaluating cross-linked food proteins and propose future scenarios for application in foodomics. They offer potential for understanding the protein cross-linking formation mechanisms in processed foods, and how the inherent beneficial properties of treated foodstuffs can be preserved or enhanced.

Determination of Allergen Levels, Isoforms, and Their Hydroxyproline Modifications Among Peanut Genotypes by Mass Spectrometry

The recently published reference genome of peanuts enables a detailed molecular description of the allergenic proteins of the seed. We used LC-MS/MS to investigate peanuts of different genotypes to assess variability and to better describe naturally occurring allergens and isoforms. Using relative quantification by mass spectrometry, minor variation of some allergenic proteins was observed, but total levels of Ara h 1, 2, 3, and 6 were relatively consistent among 20 genotypes. Previously published RP-HPLC methodology was used for comparison. The abundance of three Ara h 3 isoforms were variable among the genotypes and contributed to a large proportion of total Ara h 3 where present. Previously unpublished hydroxyproline sites were identified in Ara h 1 and 3. Hydroxylation did not vary significantly where sites were present. Peanut allergen composition was largely stable, with only some isoforms displaying differences between genotypes. The resulting differences in allergenicity are of unknown clinical significance but are likely to be minor. The data presented herein allow for the design of targeted MS methodology to allow the quantitation and therefore control of peanut allergens of clinical relevance and observed variability.

IgE-Mediated Peanut Allergy: Current and Novel Predictive Biomarkers for Clinical Phenotypes Using Multi-Omics Approaches

Food allergy is a collective term for several immune-mediated responses to food. IgE-mediated food allergy is the best-known subtype. The patients present with a marked diversity of clinical profiles including symptomatic manifestations, threshold reactivity and reaction kinetics. In-vitro predictors of these clinical phenotypes are evasive and considered as knowledge gaps in food allergy diagnosis and risk management. Peanut allergy is a relevant disease model where pioneer discoveries were made in diagnosis, immunotherapy and prevention. This review provides an overview on the immune basis for phenotype variations in peanut-allergic individuals, in the light of future patient stratification along emerging omic-areas. Beyond specific IgE-signatures and basophil reactivity profiles with established correlation to clinical outcome, allergenomics, mass spectrometric resolution of peripheral allergen tracing, might be a fundamental approach to understand disease pathophysiology underlying biomarker discovery. Deep immune phenotyping is thought to reveal differential cell responses but also, gene expression and gene methylation profiles (eg, peanut severity genes) are promising areas for biomarker research. Finally, the study of microbiome-host interactions with a focus on the immune system modulation might hold the key to understand tissue-specific responses and symptoms. The immune mechanism underlying acute food-allergic events remains elusive until today. Deciphering this immunological response shall enable to identify novel biomarker for stratification of patients into reaction endotypes. The availability of powerful multi-omics technologies, together with integrated data analysis, network-based approaches and unbiased machine learning holds out the prospect of providing clinically useful biomarkers or biomarker signatures being predictive for reaction phenotypes.

In vitro gastroduodenal and jejunal brush border membrane digestion of raw and roasted tree nuts

Heat treatments induce chemical/physical modifications, which may affect the stability to enzymatic digestion and consequently the allergenicity of food proteins to a varying extent, depending on the time/temperature regimen. Herein, we evaluated the stability to digestion of whole tree nut (walnuts, hazelnuts and almonds) allergens in a food digestion model reflecting the real one by, taking into consideration the allergen-containing processed (roasted) food. To this aim, whole raw and roasted tree nuts were subjected to in vitro digestion combining the harmonized oral-gastric-duodenal digestion models with brush border membrane enzymes (BBM) to simulate the jejunal degradation of peptides. The degradation of allergens was monitored by integrated proteomic/peptidomic and bio-informatic tools. Roasting increased digestibility of tree nuts, since very few peptides were detected in digested samples (<6.5 kDa fraction). After BBM digestion step, the degradation of peptides was enhanced in roasted walnuts and hazelnuts compared to the raw counterpart. Conversely, almond allergens showed a different behaviour, since the presence of resistant peptides was more evident for roasted almonds, probably because of the hydrolysis of high molecular weight aggregates generated during roasting. Our results provide new insight into the relationship between thermal processing and metabolic fate of tree nut allergens, highlighting the importance of investigating the digestion stability of whole allergenic food, rather than purified proteins.

Quantitative proteomics analysis of high and low polyphenol expressing recombinant inbred lines (RILs) of peanut (Arachis hypogaea L.)

To facilitate selective breeding of polyphenol-rich peanuts, we looked for mass spectrometry-based proteomic evidence, investigating a subset of recombinant inbred lines (RILs) developed by the Australian peanut breeding program. To do this, we used label-free shotgun proteomics for protein and peptide quantitation, statistically analyzed normalized spectral abundance factors using R-package, as well as assayed important antioxidants. Results revealed statistically significant protein expression changes in 82 proteins classified between high or low polyphenols expressing RILs. Metabolic changes in polyphenol-rich RIL p27-362 point towards increased enzymatic breakdown of sugars and phenylalanine biosynthesis. The study revealed phenylpropanoid pathway overexpression resulting in increased polyphenols biosynthesis. Overexpression of antioxidant enzymes such as catalase, by 73.4 fold was also observed. A strong metabolic correlation exists with the observed phenotypic traits. Peanut RIL p27-362 presents a superior nutritional composition with antioxidant-rich peanut phenotype and could yield commercial profits. Data are available via ProteomeXchange with identifierPXD015493.

Food allergomics based on high-throughput and bioinformatics technologies

Food allergy is a serious food safety problem worldwide, and the investigation of food allergens is the foundation of preventing and treating them, but relevant knowledge is far from sufficient. With the advent of the "big data era", it has been possible to investigate food allergens by high-throughput methods, proposing the concept of allergomics. Allergomics is the discipline studying the repertoire of allergens, which has relatively higher throughput and is faster and more sensitive than conventional methods. This review introduces the basis of allergomics and summarizes its major strategies and applications. Particularly, strategies based on immunoblotting, phage display, allergen microarray, and bioinformatics are reviewed in detail, and the advantages and limitations of each strategy are discussed. Finally, further development of allergomics is predicted. This provides basic theories and recent advances in food allergomics research, which could be insightful for both food allergy research and practical applications.