Characteristic motifs for families of allergenic proteins. Mol Immunol. 2009;46:559-568. [PMID: 18951633 DOI: 10.1016/j.molimm.2008.07.034]

AllergenAI: a deep learning model predicting allergenicity based on protein sequence

Innovations in protein engineering can help redesign allergenic proteins to reduce adverse reactions in sensitive individuals. To accomplish this aim, a better knowledge of the molecular properties of allergenic proteins and the molecular features that make a protein allergenic is needed. We present a novel AI-based tool, AllergenAI, to quantify the allergenic potential of a given protein. Our approach is solely based on protein sequences, differentiating it from previous tools that use some knowledge of the allergens' physicochemical and other properties in addition to sequence homology. We used the collected data on protein sequences of allergenic proteins as archived in the three well-established databases, SDAP 2.0, COMPARE, and AlgPred 2, to train a convolutional neural network and assessed its prediction performance by cross-validation. We then used Allergen AI to find novel potential proteins of the cupin family in date palm, spinach, maize, and red clover plants with a high allergenicity score that might have an adverse allergenic effect on sensitive individuals. By analyzing the feature importance scores (FIS) of vicilins, we identified a proline-alanine-rich (P-A) motif in the top 50% of FIS regions that overlapped with known IgE epitope regions of vicilin allergens. Furthermore, using∼ 1600 allergen structures in our SDAP database, we showed the potential to incorporate 3D information in a CNN model. Future, incorporating 3D information in training data should enhance the accuracy. AllergenAI is a novel foundation for identifying the critical features that distinguish allergenic proteins.

The updated Structural Database of Allergenic Proteins (SDAP 2.0) provides 3D models for allergens and incorporated bioinformatics tools

Background

Allergenic proteins can cause IgE-mediated adverse reactions in sensitized individuals. Although the sequences of many allergenic proteins have been identified, bioinformatics data analysis with advanced computational methods and modeling is needed to identify the basis for IgE binding and cross-reactivity.

Objective

We aim to present the features and use of the updated Structural Database of Allergenic Proteins 2.0 (SDAP 2.0) webserver, a unique, publicly available resource to compare allergens using specially designed computational tools and new high-quality 3-D models for most known allergens.

Methods

Previously developed and novel software tools for identifying cross-reactive allergens using sequence and structure similarity are implemented in SDAP 2.0. A comprehensive set of high-quality 3-D models of most allergens was generated with the state-of-the-art AlphaFold 2 software. A graphics tool enables the interactive visualization of IgE epitopes on experimentally determined and modeled 3-D structures.

Results

A user can search for allergens similar to a given input sequence with the FASTA algorithm or the window-based World Health Organization/International Union of Immunological Societies (WHO/IUIS) guidelines on safety concerns of novel food products. Peptides similar to known IgE epitopes can be identified with the property distance tool and conformational epitopes by the Cross-React method. The updated database contains 1657 manually curated sequences including all allergens from the IUIS database, 334 experimentally determined X-ray or NMR structures, and 1565 3-D models. Each allergen/isoallergen is classified according to its protein family.

Conclusions

SDAP provides access to the steadily increasing information on allergenic structures and epitopes with integrated bioinformatics tools to identify and analyze their similarities. In addition to serving the research and regulatory community, it provides clinicians with tools to identify potential coallergies in a sensitive patient and can help companies to design hypoallergenic foods and immunotherapies.

PCP consensus protein/peptide alphavirus antigens stimulate broad spectrum neutralizing antibodies

Vaccines based on proteins and peptides may be safer and if calculated based on many sequences, more broad-spectrum than those designed based on single strains. Physicochemical Property Consensus (PCP_con) alphavirus (AV) antigens from the B-domain of the E2 envelope protein were designed, synthesized recombinantly and shown to be immunogenic (i.e. sera after inoculation detected the antigen in dotspots and ELISA). Antibodies in sera after inoculation with B-region antigens based on individual AV species (eastern or Venezuelan equine encephalitis (EEEV_con, VEEV_con), or chikungunya (CHIKV_con) bound only their cognate protein, while those designed against multiple species (Mosaik_con and EVC_con) recognized all three serotype specific antigens. The VEEV_con and EEEV_con sera only showed antiviral activity against their related strains (in plaque reduction neutralization assays (PRNT_50/80). Peptides designed to surface exposed areas of the E2-A-domain of CHIKV_con were added to CHIKV_con inocula to provide anti-CHIKV antibodies. EVC_con, based on three different alphavirus species, combined with E2-A-domain peptides from AllAV_con, a PCPcon of 24 diverse AV, generated broad spectrum, antiviral antibodies against VEEV, EEEV and CHIKV, AV with less than 35% amino acid identity to each other (>65% diversity). This is a promising start to a molecularly defined vaccine against all AV. Further study with these antigens can illuminate what areas are most important for a robust immune response, resistant to mutations in rapidly evolving viruses. The validated computational methods can also be used to design broad spectrum antigens against many other pathogen families.

Design of peptides with high affinity binding to a monoclonal antibody as a basis for immunotherapy

About half of the US population is sensitized to one or more allergens, as found by a National Health and Nutrition Examination Survey (NHANES). The most common treatment for seasonal allergic responses is the daily use of oral antihistamines, which can control some of the symptoms, but are not effective for nasal congestion, and can be debilitating in many patients. Peptide immunotherapy is a promising new approach to treat allergic airway diseases. The small size of the immunogens cannot lead to an unwanted allergic reaction in sensitized patients, and the production of peptides with sufficient amounts for immunotherapy is time- and cost-effective. However, it is not known what peptides are the most effective for an immunotherapy of allergens. We previously produced a unique monoclonal antibody (mAb) E58, which can inhibit the binding of multiple groups of mAbs and human IgEs from patients affected by the major group 1 allergens of ragweed (Amb a 1) and conifer pollens (Jun a 1, Cup s 1, and Cry j 1). Here, we demonstrated that a combined approach, starting from two linear E58 epitopes of the tree pollen allergen Jun a 1 and the ragweed pollen allergen Amb a 1, and residue modifications suggested by molecular docking calculations and peptide design could identify a large number of high affinity binding peptides. We propose that this combined experimental and computational approach by structural analysis of linear IgE epitopes and peptide design, can lead to potential new candidates for peptide immunotherapy.

Nutritional, functional, and allergenic properties of silkworm pupae

Edible insects are a food source that has high nutritional value. Domestic silkworm pupae are an important by-product of sericulture and have a long history as food and feed ingredients in East Asia. Silkworm pupae are a good source of protein, lipids, minerals, and vitamins and are considered a good source of nutrients for humans. Silkworm pupae are a valuable insect source of substances used in healthcare products, medicines, food additives, and animal feed. Because silkworm pupae are being increasingly used in the human diet, potential allergic reactions to the substances they contain must be elucidated. Here, we present an overview of the benefits of silkworm pupae. First, we describe their nutritional value. Second, we report their functional properties and applications, focusing on their potential use in the food and pharmaceutical industries. Finally, we consider the current state of research regarding silkworm pupae-induced allergies.

DGraph Clusters Flaviviruses and β-Coronaviruses According to Their Hosts, Disease Type, and Human Cell Receptors

Motivation

There is a need for rapid and easy-to-use, alignment-free methods to cluster large groups of protein sequence data. Commonly used phylogenetic trees based on alignments can be used to visualize only a limited number of protein sequences. DGraph, introduced here, is an application developed to generate 2-dimensional (2D) maps based on similarity scores for sequences. The program automatically calculates and graphically displays property distance (PD) scores based on physico-chemical property (PCP) similarities from an unaligned list of FASTA files. Such "PD-graphs" show the interrelatedness of the sequences, whereby clusters can reveal deeper connectivities.

Results

Property distance graphs generated for flavivirus (FV), enterovirus (EV), and coronavirus (CoV) sequences from complete polyproteins or individual proteins are consistent with biological data on vector types, hosts, cellular receptors, and disease phenotypes. Property distance graphs separate the tick- from the mosquito-borne FV, cluster viruses that infect bats, camels, seabirds, and humans separately. The clusters correlate with disease phenotype. The PD method segregates the β-CoV spike proteins of severe acute respiratory syndrome (SARS), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and Middle East respiratory syndrome (MERS) sequences from other human pathogenic CoV, with clustering consistent with cellular receptor usage. The graphs also suggest evolutionary relationships that may be difficult to determine with conventional bootstrapping methods that require postulating an ancestral sequence.

The importance of the 2S albumins for allergenicity and cross-reactivity of peanuts, tree nuts, and sesame seeds

Allergies to peanuts, tree nuts, and sesame seeds are among the most important food-related causes of anaphylaxis. Important clinical questions include: Why is there a variable occurrence of coallergy among these foods and Is this immunologically mediated? The clinical and immunologic data summarized here suggest an immunologic basis for these coallergies that is based on similarities among the 2S albumins. Data from component resolved diagnostics have highlighted the relationship between IgE binding to these allergens and the presence of IgE-mediated food allergy. Furthermore, in vitro and in vivo experiments provide strong evidence that the 2S albumins are the most important allergens in peanuts for inducing an allergic effector response. Although the 2S albumins are diverse, they have a common disulfide-linked core with similar physicochemical properties that make them prime candidates to explain much of the observed coallergy among peanuts, tree nuts, and sesame seeds. The well-established frequency of cashew and pistachio nut coallergy (64%-100%) highlights how the structural similarities among their 2S albumins may account for observed clinical cross-reactivity. A complete understanding of the physicochemical properties of the 2S albumins in peanuts, tree nuts, and sesame seeds will enhance our ability to diagnose, treat, and ultimately prevent these allergies.

D-graph clusters flaviviruses and β-coronaviruses according to their hosts, disease type and human cell receptors

Motivation:

There is a need for rapid and easy to use, alignment free methods to cluster large groups of protein sequence data. Commonly used phylogenetic trees based on alignments can be used to visualize only a limited number of protein sequences. DGraph, introduced here, is a dynamic programming application developed to generate 2D-maps based on similarity scores for sequences. The program automatically calculates and graphically displays property distance (PD) scores based on physico-chemical property (PCP) similarities from an unaligned list of FASTA files. Such “PD-graphs” show the interrelatedness of the sequences, whereby clusters can reveal deeper connectivities.

Results:

PD-Graphs generated for flavivirus (FV), enterovirus (EV), and coronavirus (CoV) sequences from complete polyproteins or individual proteins are consistent with biological data on vector types, hosts, cellular receptors and disease phenotypes. PD-graphs separate the tick- from the mosquito-borne FV, clusters viruses that infect bats, camels, seabirds and humans separately and the clusters correlate with disease phenotype. The PD method segregates the β-CoV spike proteins of SARS, SARS-CoV-2, and MERS sequences from other human pathogenic CoV, with clustering consistent with cellular receptor usage. The graphs also suggest evolutionary relationships that may be difficult to determine with conventional bootstrapping methods that require postulating an ancestral sequence.

Epitopes with similar physicochemical properties contribute to cross reactivity between peanut and tree nuts

Many individuals with peanut (PN) allergy have severe reactions to tree nuts (TN) such as walnuts or cashews. Although allergenic proteins in TN and PN have overall low identity, they share discrete sequences similar in physicochemical properties (PCP) to known IgE epitopes. Here, PCP-consensus peptides (cp, 13 aa and 31 aa) were identified from an alignment of epitope rich regions of walnut vicilin, Jug r 2, leader sequence (J2LS) and cross-reactive epitopes in the 2S albumins of peanut and synthesized. A peptide similarity search in the Structural Database of Allergenic Proteins (SDAP) revealed a network of peptides similar (low property distance, PD) to the 13 aa cp (13cp) in many different plant allergens. Peptides similar to the 13cp in PN and TN allergens bound IgE from sera of patients allergic to PN and TN in peptide microarray analysis. The 13cp was used to produce a rabbit consensus peptide antibody (cpAB) that detected proteins containing repeats similar to the 13cp in western blots of various nut extracts, in which reactive proteins were identified by mass spectrometry. The cpAB bound more specifically to allergens and nut extracts containing multiple repeats similar to the 13 cp, such as almond (Pru du 6), peanut (Ara h 2) and walnut (Jug r 2). IgE binding to various nut extracts is inhibited by recombinant J2LS sequence and synthetic 31cp. Thus, several repeated sequences similar to the 13cp are bound by IgE. Multiple similar repeats in several allergens could account for reaction severity and clinically relevant cross-reactivity to PN and TN. These findings may help improve detection, diagnostic, and therapeutic tools.

A robust method for the estimation and visualization of IgE cross-reactivity likelihood between allergens belonging to the same protein family

Among the vast number of identified protein families, allergens emanate from relatively few families which translates to only a small fraction of identified protein families. In allergy diagnostics and immunotherapy, interactions between immunoglobulin E and allergens are crucial because the formation of an allergen-antibody complex is necessary for triggering an allergic reaction. In allergic diseases, there is a phenomenon known as cross-reactivity. Cross-reactivity describes a situation where an individual has produced antibodies against a particular allergenic protein, but said antibodies fail to discriminate between the original sensitizer and other similar proteins that usually belong to the same family. To expound the concept of cross-reactivity, this study examines ten protein families that include allergens selected specifically for the analysis of cross-reactivity. The selected allergen families had at least 13 representative proteins, overall folds that differ significantly between families, and include relevant allergens with various potencies. The selected allergens were analyzed using information on sequence similarities and identities between members of the families as well as reports on clinically relevant cross-reactivities. Based on our analysis, we propose to introduce a new A-RISC index (Allergens’–Relative Identity, Similarity and Cross-reactivity) which describes homology between two allergens belonging to the same protein family and is used to predict the likelihood of cross-reactivity between them. Information on sequence similarities and identities, as well as on the values of the proposed A-RISC index is used to introduce four categories describing a risk of a cross-reactive reaction, namely: high, medium-high, medium-low and low. The proposed approach can facilitate analysis in component-resolved allergy diagnostics, generation of avoidance guidelines for allergic individuals, and help with the design of immunotherapy.

Assessment of the potential allergenicity of genetically-engineered food crops

An extensive safety assessment process exists for genetically-engineered (GE) crops. The assessment includes an evaluation of the introduced protein as well as the crop containing the protein with the goal of demonstrating the GE crop is "as-safe-as" non-GE crops in the food supply. One of the evaluations for GE crops is to assess the expressed protein for allergenic potential. Currently, no single factor is recognized as a predictor for protein allergenicity. Therefore, a weight-of-the-evidence approach, which accounts for a variety of factors and approaches for an overall assessment of allergenic potential, is conducted. This assessment includes an evaluation of the history of exposure and safety of the gene(s) source; protein structure (e.g. amino acid sequence identity to human allergens); stability of the protein to pepsin digestion in vitro; heat stability of the protein; glycosylation status; and when appropriate, specific IgE binding studies with sera from relevant clinically allergic subjects. Since GE crops were first commercialized over 20 years ago, there is no proof that the introduced novel protein(s) in any commercialized GE food crop has caused food allergy.

Insect (food) allergy and allergens

Insects represent an alternative for meat and fish in satisfying the increasing demand for sustainable sources of nutrition. Approximately two billion people globally consume insects. They are particularly popular in Asia, Latin America, and Africa. Most research on insect allergy has focussed on occupational or inhalation allergy. Research on insect food safety, including allergenicity, is therefore of great importance. The objective of this review is to provide an overview of cases reporting allergy following insect ingestion, studies on food allergy to insects, proteins involved in insect allergy including cross-reactive proteins, and the possibility to alter the allergenic potential of insects by food processing and digestion. Food allergy to insects has been described for silkworm, mealworm, caterpillars, Bruchus lentis, sago worm, locust, grasshopper, cicada, bee, Clanis bilineata, and the food additive carmine, which is derived from female Dactylopius coccus insects. For cockroaches, which are also edible insects, only studies on inhalation allergy have been described. Various insect allergens have been identified including tropomyosin and arginine kinase, which are both pan-allergens known for their cross-reactivity with homologous proteins in crustaceans and house dust mite. Cross-reactivity and/or co-sensitization of insect tropomyosin and arginine kinase has been demonstrated in house dust mite and seafood (e.g. prawn, shrimp) allergic patients. In addition, many other (allergenic) species (various non-edible insects, arachnids, mites, seafoods, mammals, nematoda, trematoda, plants, and fungi) have been identified with sequence alignment analysis to show potential cross-reactivity with allergens of edible insects. It was also shown that thermal processing and digestion did not eliminate insect protein allergenicity. Although purified natural allergens are scarce and yields are low, recombinant allergens from cockroach, silkworm, and Indian mealmoth are readily available, giving opportunities for future research on diagnostic allergy tests and vaccine candidates.

Distinguishing allergens from non-allergenic homologues using Physical-Chemical Property (PCP) motifs

Quantitative guidelines to distinguish allergenic proteins from related, but non-allergenic ones are urgently needed for regulatory agencies, biotech companies and physicians. In a previous study, we found that allergenic proteins populate a relatively small number of protein families, as characterized by the Pfam database. However, these families also contain non-allergenic proteins, meaning that allergenic determinants must lie within more discrete regions of the sequence. Thus, new methods are needed to discriminate allergenic proteins within those families. Physical-Chemical Properties (PCP)-motifs specific for allergens within a Pfam class were determined for 17 highly populated protein domains. A novel scoring method based on PCP-motifs that characterize known allergenic proteins within these families was developed, and validated for those domains. The motif scores distinguished sequences of allergens from a large selection of 80,000 randomly selected non-allergenic sequences. The motif scores for the birch pollen allergen (Bet v 1) family, which also contains related fruit and nut allergens, correlated better than global sequence similarities with clinically observed cross-reactivities among those allergens. Further, we demonstrated that the average scores of allergen specific motifs for allergenic profilins are significantly different from the scores of non-allergenic profilins. Several of the selective motifs coincide with experimentally determined IgE epitopes of allergenic profilins. The motifs also discriminated allergenic pectate lyases, including Jun a 1 from mountain cedar pollen, from similar proteins in the human microbiome, which can be assumed to be non-allergens. The latter lacked key motifs characteristic of the known allergens, some of which correlate with known IgE binding sites.

Functional classification of protein toxins as a basis for bioinformatic screening

Proteins are fundamental to life and exhibit a wide diversity of activities, some of which are toxic. Therefore, assessing whether a specific protein is safe for consumption in foods and feeds is critical. Simple BLAST searches may reveal homology to a known toxin, when in fact the protein may pose no real danger. Another challenge to answer this question is the lack of curated databases with a representative set of experimentally validated toxins. Here we have systematically analyzed over 10,000 manually curated toxin sequences using sequence clustering, network analysis, and protein domain classification. We also developed a functional sequence signature method to distinguish toxic from non-toxic proteins. The current database, combined with motif analysis, can be used by researchers and regulators in a hazard screening capacity to assess the potential of a protein to be toxic at early stages of development. Identifying key signatures of toxicity can also aid in redesigning proteins, so as to maintain their desirable functions while reducing the risk of potential health hazards.

Navigating through the Jungle of Allergens: Features and Applications of Allergen Databases

The increasing number of available data on allergenic proteins demanded the establishment of structured, freely accessible allergen databases. In this review article, features and applications of 6 of the most widely used allergen databases are discussed. The WHO/IUIS Allergen Nomenclature Database is the official resource of allergen designations. Allergome is the most comprehensive collection of data on allergens and allergen sources. AllergenOnline is aimed at providing a peer-reviewed database of allergen sequences for prediction of allergenicity of proteins, such as those planned to be inserted into genetically modified crops. The Structural Database of Allergenic Proteins (SDAP) provides a database of allergen sequences, structures, and epitopes linked to bioinformatics tools for sequence analysis and comparison. The Immune Epitope Database (IEDB) is the largest repository of T-cell, B-cell, and major histocompatibility complex protein epitopes including epitopes of allergens. AllFam classifies allergens into families of evolutionarily related proteins using definitions from the Pfam protein family database. These databases contain mostly overlapping data, but also show differences in terms of their targeted users, the criteria for including allergens, data shown for each allergen, and the availability of bioinformatics tools.

Deep sequencing transcriptional fingerprinting of rice kernels for dissecting grain quality traits

BACKGROUND

Rice represents one the most important foods all over the world. In Europe, Italy is the first rice producer and Italian production is driven by tradition and quality. All main rice grain quality traits, like cooking properties, texture, gelatinization temperature, chalkiness and yield, are related to the content and composition of starch and seed-storage proteins in the endosperm and to grain shape. In addition, a number of nutraceutical compounds and allergens are known to have a significant effect on grain quality determination. To investigate the genetic bases underlying the qualitative differences that characterize traditional Italian rice cultivars, a comparative RNA-Seq-based transcriptomic analysis of developing caryopsis was conducted at 14 days after flowering on six popular Italian varieties (Carnaroli, Arborio, Balilla, Vialone Nano, Gigante Vercelli and Volano) phenotypically differing for qualitative grain-related traits.

RESULTS

Co-regulation analyses of differentially expressed genes showing the same expression patterns in the six genotypes highlighted clusters of loci up or down-regulated in specific varieties, with respect to the others. Among them, we detected loci involved in cell wall biosynthesis, protein metabolism and redox homeostasis, classes of genes affecting in chalkiness determination. Moreover, loci encoding for seed-storage proteins, allergens or involved in the biosynthesis of specific nutraceutical compounds were also present and specifically regulated in the different clusters. A wider investigation of all the DEGs detected in pair-wise comparisons revealed transcriptional variation, among the six genotypes, for quality-related loci involved in starch biosynthesis (e.g. GBSSI, starch synthases and AGPase), genes encoding for transcription factors, additional seed storage proteins, allergens or belonging to additional nutraceutical compounds biosynthetic pathways and loci affecting grain size. Putative functional SNPs associated to amylose content in starch, gelatinization temperature and grain size were also identified.

CONCLUSIONS

The present work represents a more extended phenotypic characterization of a set of rice accessions that present a wider genetic variability than described nowadays in literature. The results provide the first transcriptional picture for several of the grain quality differences observed among the Italian rice varieties analyzed and reveal that each variety is characterized by the over-expression of a peculiar set of loci affecting grain appearance and quality. A list of candidates and SNPs affecting specific grain properties has been identified offering a starting point for further works aimed to characterize genes and molecular markers for breeding programs.

Genome-wide analysis of potential cross-reactive endogenous allergens in rice (Oryza sativa L.)

The proteins in the food are the source of common allergic components to certain patients. Current lists of plant endogenous allergens were based on the medical/clinical reports as well as laboratory results. Plant genome sequences made it possible to predict and characterize the genome-wide of putative endogenous allergens in rice (Oryza sativa L.). In this work, we identified and characterized 122 candidate rice allergens including the 22 allergens in present databases. Conserved domain analysis also revealed 37 domains among rice allergens including one novel domain (histidine kinase-, DNA gyrase B-, and HSP90-like ATPase, PF13589) adding to the allergen protein database. Phylogenetic analysis of the allergens revealed the diversity among the Prolamin superfamily and DnaK protein family, respectively. Additionally, some allergens proteins clustered on the rice chromosome might suggest the molecular function during the evolution.

Cross-reactivity between aeroallergens and food allergens

In patients with respiratory allergy, cross-reactivity between aeroallergens and foods may induce food allergy, symptoms ranging from oral allergy syndrome to severe anaphylaxis. Clinical entities due to IgE sensitization to cross-reactive aeroallergen and food allergen components are described for many sources of plant origin (pollen-food syndromes and associations, such as birch-apple, cypress-peach and celery-mugwort-spice syndromes, and mugwort-peach, mugwort-chamomile, mugwort-mustard, ragweed-melon-banana, goosefoot-melon associations), fungal origin (Alternaria-spinach syndrome), and invertebrate, mammalian or avian origin (mite-shrimp, cat-pork, and bird-egg syndromes). Clinical cases of allergic reactions to ingestion of food products containing pollen grains of specific plants, in patients with respiratory allergy to Asteraceae pollen, especially mugwort and ragweed, are also mentioned, for honey, royal jelly and bee polen dietary supplements, along with allergic reactions to foods contaminated with mites or fungi in patients with respiratory allergy to these aeroallergens. Medical history and diagnosis approach may be guided by the knowledge about the diverse cross-reacting allergens involved, and by the understanding of these clinical entities which may vary significantly or may be overlapping. The association between primary IgE sensitization with respiratory symptoms to inhaled allergens and food allergy due to cross-reactive allergen components is important to assess in allergy practice. The use of molecular-based diagnosis improves the understanding of clinically relevant IgE sensitization to cross-reactive allergen components from aeroallergen sources and foods.

Food allergy: a practice parameter update-2014

This parameter was developed by the Joint Task Force on Practice Parameters, representing the American Academy of Allergy, Asthma & Immunology (AAAAI); the American College of Allergy, Asthma & Immunology (ACAAI); and the Joint Council of Allergy, Asthma & Immunology (JCAAI). The AAAAI and the ACAAI have jointly accepted responsibility for establishing "Food Allergy: A practice parameter update-2014." This is a complete and comprehensive document at the current time. The medical environment is a changing one, and not all recommendations will be appropriate for all patients. Because this document incorporated the efforts of many participants, no single individual, including those who served on the Joint Task Force, is authorized to provide an official AAAAI or ACAAI interpretation of these practice parameters. Any request for information about or an interpretation of these practice parameters by the AAAAI or ACAAI should be directed to the Executive Offices of the AAAAI, ACAAI, and JCAAI. These parameters are not designed for use by pharmaceutical companies in drug promotion.

AllergenFP: allergenicity prediction by descriptor fingerprints

MOTIVATION

Allergenicity, like antigenicity and immunogenicity, is a property encoded linearly and non-linearly, and therefore the alignment-based approaches are not able to identify this property unambiguously. A novel alignment-free descriptor-based fingerprint approach is presented here and applied to identify allergens and non-allergens. The approach was implemented into a four step algorithm. Initially, the protein sequences are described by amino acid principal properties as hydrophobicity, size, relative abundance, helix and β-strand forming propensities. Then, the generated strings of different length are converted into vectors with equal length by auto- and cross-covariance (ACC). The vectors were transformed into binary fingerprints and compared in terms of Tanimoto coefficient.

RESULTS

The approach was applied to a set of 2427 known allergens and 2427 non-allergens and identified correctly 88% of them with Matthews correlation coefficient of 0.759. The descriptor fingerprint approach presented here is universal. It could be applied for any classification problem in computational biology. The set of E-descriptors is able to capture the main structural and physicochemical properties of amino acids building the proteins. The ACC transformation overcomes the main problem in the alignment-based comparative studies arising from the different length of the aligned protein sequences. The conversion of protein ACC values into binary descriptor fingerprints allows similarity search and classification.

AVAILABILITY AND IMPLEMENTATION

The algorithm described in the present study was implemented in a specially designed Web site, named AllergenFP (FP stands for FingerPrint). AllergenFP is written in Python, with GIU in HTML. It is freely accessible at http://ddg-pharmfac.net/Allergen FP.

CONTACT

idoytchinova@pharmfac.net or ivanbangov@shu-bg.net.

Food proteins from different allergen families sensitize Balb/c mice to family-specific immune responses

The classification of food allergens based on the structure and function of proteins contributes to the study of the relationship between bioinformatics and potential allergenicity of allergens. Food allergens always share sequence similarity with the allergens in the same allergen families. For that reason, food proteins from different allergen families may induce different patterns of immune responses in animal models. Female Balb/c mice (3-4-weeks-old) were sensitized with food proteins once per week for 4 weeks, and then challenged 2 weeks later (on Day 42 of study). Blood was collected (to obtain serum levels of histamine and protein-specific IgG1 and IgE antibodies) and measures of vascular permeability were performed 20 min after the challenge. Five food proteins (11S globulin, OVA [ovalbumin], HAS [human serum albumin] and LRP [lysine-responsive storage protein] of different allergen families, and Cry 1Ab/Ac [crystal protein]) were used to assess patterns of immune responses for each allergen family and then bioinformatics and digestive stability in simulated gastric fluid were employed to assess the overall utility of the Balb/c. The assay results indicated that, in this model, histamine and protein-specific IgE antibody levels and vascular permeability could be used to identify allergenicity of 11S globulin, OVA, and PAP (potato acid phosphatase) only. However, the results of the protein-specific IgG1 measures could only distinguish allergic food proteins with negative control. Based on bioinformatic analyses, the five different food proteins clearly induced distinct patterns of immune responses in the Balb/c model.

Vicilin and the basic subunit of legumin are putative chickpea allergens

IgE-mediated reactions to food allergens constitute a major health problem in industrialized countries. Chickpea is consumed in Mediterranean countries, and reportedly associated with IgE-mediated hypersensitivity reactions. However, the nature of allergic reactions to chickpea has not been characterized. A serum pool from paediatric patients allergic to chickpeas was used to detect IgE-binding proteins from chickpea seeds by immunoassay and immunoblot inhibition assay. Protein samples enriched in chickpea legumin and vicilin were obtained by anion exchange chromatography, and were identified by mass spectrometric analysis. IgE-immunoassays of globulin fractions from chickpeas revealed that vicilin (50 kDa) and the basic subunit of legumin (20 kDa) were bound by IgE from patient sera. Pea and lentil protein extracts strongly inhibited the IgE binding to chickpea globulin. We speculate that vicilin and the basic subunit of legumin are major chickpea allergens. Also, the globulin fraction of chickpea likely cross-reacts with the allergenic proteins of pea and lentil.

Assessment of 3D models for allergen research

Allergenic proteins must crosslink specific IgE molecules, bound to the surface of mast cells and basophils, to stimulate an immune response. A structural understanding of the allergen-IgE interface is needed to predict cross-reactivities between allergens and to design hypoallergenic proteins. However, there are less than 90 experimentally determined structures available for the approximately 1500 sequences of allergens and isoallergens cataloged in the Structural Database of Allergenic Proteins. To provide reliable structural data for the remaining proteins, we previously produced more than 500 3D models using an automated procedure, with strict controls on template choice and model quality evaluation. Here, we assessed how well the fold and residue surface exposure of 10 of these models correlated with recently published experimental 3D structures determined by X-ray crystallography or NMR. We also discuss the impact of intrinsically disordered regions on the structural comparison and epitope prediction. Overall, for seven allergens with sequence identities to the original templates higher than 27%, the backbone root-mean square deviations were less than 2 Å between the models and the subsequently determined experimental structures for the ordered regions. Further, the surface exposure of the known IgE epitopes on the models of three major allergens, from peanut (Ara h 1), latex (Hev b 2), and soy (Gly m 4), was very similar to the experimentally determined structures. For the three remaining allergens with lower sequence identities to the modeling templates, the 3D folds were correctly identified. However, the accuracy of those models is not sufficient for a reliable epitope mapping.

Group 10 allergens (tropomyosins) from house-dust mites may cause covariation of sensitization to allergens from other invertebrates

Group 10 allergens (tropomyosins) have been assumed to be a major cause of cross-reactivity between house-dust mites (HDMs) and other invertebrates. Despite all of the published data regarding the epidemiology, percent IgE binding and level of sensitization in the population, the role of tropomyosin as a cross-reactive allergen in patients with multiple allergy syndrome still remains to be elucidated. Homology between amino acid sequences reported in allergen databases of selected invertebrate tropomyosins was determined with Der f 10 as the reference allergen. The 66.9 and 54.4% identities were found with selected crustacean and insect species, respectively, whereas only 20.4% identity was seen with mollusks. A similar analysis was performed using reported B-cell IgE-binding epitopes from Met e1 (shrimp allergen) and Bla g7 (cockroach allergen) with other invertebrate tropomyosins. The percent identity in linear sequences was higher than 35% in mites, crustaceans, and cockroaches. The polar and hydrophobic regions in these groups were highly conserved. These findings suggest that tropomyosin may be a major cause of covariation of sensitization between HDMs, crustaceans, and some species of insects and mollusks.

Identification of aero-allergens from Rhizopus oryzae: an immunoproteomic approach

Airborne fungal spores bearing allergens are the causative agent for inducing immediate hypersensitive reaction in sensitive individuals. In this study the potential aeroallergens have been reported for the first time from Rhizopus oryzae a common airborne mold. Clinical data based on SPT was further confirmed by ELISA. IgE reactive bands were revealed by one-dimensional immunoblotting. A 44 kDa major reactive band was found in all immunoblots. For precise identification of allergens, an immuno-proteomic approach was taken with a combination of 2-Dimensional gel electrophoresis and Mass-spectrometry. 2D map of spore-mycelial protein was confronted with pooled sera and several IgE reactive spots were detected, most of which were glycoproteins and except for one, which has no antigenic determinacy after metaperiodate modification. Each of those spots was identified by MALDI-TOF-TOF. Some bioinformatic approaches were taken to predict the signal peptide and subcellular localization of each protein. Major 44 kDa allergen was identified as Aspartyl endopeptidase. Sequence information was extracted from MS/MS spectra of two tryptic peptides generated from the 44 kDa endopeptidase. Multiple alignments with other reported aspartyl protease allergens showed significant homology. Allergenicity assessment of this protein was performed in silico and identified as a potential putative allergen.

Innate immunostimulatory properties of allergens and their relevance to food allergy

Food allergy is an increasingly prevalent disease of immune dysregulation directed to a small subset of proteins. Shared structural and functional features of allergens, such as glycosylation, lipid-binding and protease activity may provide insight into the mechanisms involved in the induction of primary Th2 immune responses. We review the literature of innate Th2-type immune activation as a context for better understanding the properties of allergens that contribute to the induction of Th2-biased immune responses in at least a subset of individuals. Th2-priming signals have been largely identified in the context of parasite immunity and wound healing. Some of the features of parasite antigens and the innate immune responses to them are now understood to play a role in allergic inflammation as well. These include both exogenous and endogenous activators of innate immunity and subsequent release of key cytokine mediators such as thymic stromal lymphopoietin (TSLP), interleukin (IL)-25 and IL-33. Moreover, numerous innate immune cells including epithelium, dendritic cells, basophils, innate lymphoid cells and others all interact to shape the adaptive Th2 immune response. Progress toward understanding Th2-inducing innate immune signals more completely may lead to novel strategies for primary prevention and therapy of respiratory and food allergies.

Evaluation of the allergenicity potential of TcPR-10 protein from Theobroma cacao

BACKGROUND

The pathogenesis related protein PR10 (TcPR-10), obtained from the Theobroma cacao-Moniliophthora perniciosa interaction library, presents antifungal activity against M. perniciosa and acts in vitro as a ribonuclease. However, despite its biotechnological potential, the TcPR-10 has the P-loop motif similar to those of some allergenic proteins such as Bet v 1 (Betula verrucosa) and Pru av 1 (Prunus avium). The insertion of mutations in this motif can produce proteins with reduced allergenic power. The objective of the present work was to evaluate the allergenic potential of the wild type and mutant recombinant TcPR-10 using bioinformatics tools and immunological assays.

METHODOLOGY/PRINCIPAL FINDINGS

Mutant substitutions (T10P, I30V, H45S) were inserted in the TcPR-10 gene by site-directed mutagenesis, cloned into pET28a and expressed in Escherichia coli BL21(DE3) cells. Changes in molecular surface caused by the mutant substitutions was evaluated by comparative protein modeling using the three-dimensional structure of the major cherry allergen, Pru av 1 as a template. The immunological assays were carried out in 8-12 week old female BALB/c mice. The mice were sensitized with the proteins (wild type and mutants) via subcutaneous and challenged intranasal for induction of allergic airway inflammation.

CONCLUSIONS/SIGNIFICANCE

We showed that the wild TcPR-10 protein has allergenic potential, whereas the insertion of mutations produced proteins with reduced capacity of IgE production and cellular infiltration in the lungs. On the other hand, in vitro assays show that the TcPR-10 mutants still present antifungal and ribonuclease activity against M. perniciosa RNA. In conclusion, the mutant proteins present less allergenic potential than the wild TcPR-10, without the loss of interesting biotechnological properties.

A molecular and proteomic investigation of proteins rapidly released from triticale pollen upon hydration

Analysis of Triticale (×Triticosecale Wittmack cv. AC Alta) mature pollen proteins quickly released upon hydration was performed using two-dimensional gel electrophoresis followed by mass spectrometry. A total of 17 distinct protein families were identified and these included expansins, profilins, and various enzymes, many of which are pollen allergens. The corresponding genes were obtained and expression studies revealed that the majority of these genes were only expressed in developing anthers and pollen. Some genes including glucanase, glutathione peroxidase, glutaredoxin, and a profilin were found to be widely expressed in different reproductive and vegetative tissues. Group 11 pollen allergens, polygalacturonase, and actin depolymerizing factor were characterized for the first time in the Triticeae. This study represents a distinctive combination of proteomic and molecular analyses of the major cereal pollen proteins released upon hydration and therefore at the forefront of pollen-stigma interactions.

Computationally predicted IgE epitopes of walnut allergens contribute to cross-reactivity with peanuts

BACKGROUND

Cross-reactivity between peanuts and tree nuts implies that similar immunoglobulin E (IgE) epitopes are present in their proteins.

OBJECTIVE

To determine whether walnut sequences similar to known peanut IgE-binding sequences, according to the property distance (PD) scale implemented in the Structural Database of Allergenic Proteins, react with IgE from sera of patients with allergy to walnut and/or peanut.

METHODS

  Patient sera were characterized by western blotting for IgE binding to nut protein extracts and to peptides from walnut and peanut allergens, similar to known peanut epitopes as defined by low PD values, synthesized on membranes. Competitive enzyme-linked immunosorbent assay (ELISA) was used to show that peanut and predicted walnut epitope sequences compete with purified Ara h 2 for binding to IgE in serum from a cross-reactive patient.

RESULTS

Sequences from the vicilin walnut allergen Jug r 2, which had low PD values to epitopes of the peanut allergen Ara h 2, a 2S albumin, bound to IgE in sera from five patients who reacted to either walnut or peanut or both. A walnut epitope recognized by sera from six patients mapped to a surface-exposed region on a model of the N-terminal pro-region of Jug r 2. This predicted walnut epitope competed for IgE binding to Ara h 2 in serum as well as the known IgE epitope from Ara h 2.

CONCLUSIONS

Sequences with low PD value (< 8.5) to known IgE epitopes could contribute to cross-reactivity between allergens. This further validates the PD scoring method for predicting cross-reactive epitopes in allergens.

Suggested improvements for the allergenicity assessment of genetically modified plants used in foods

Genetically modified (GM) plants are increasingly used for food production and industrial applications. As the global population has surpassed 7 billion and per capita consumption rises, food production is challenged by loss of arable land, changing weather patterns, and evolving plant pests and disease. Previous gains in quantity and quality relied on natural or artificial breeding, random mutagenesis, increased pesticide and fertilizer use, and improved farming techniques, all without a formal safety evaluation. However, the direct introduction of novel genes raised questions regarding safety that are being addressed by an evaluation process that considers potential increases in the allergenicity, toxicity, and nutrient availability of foods derived from the GM plants. Opinions vary regarding the adequacy of the assessment, but there is no documented proof of an adverse effect resulting from foods produced from GM plants. This review and opinion discusses current practices and new regulatory demands related to food safety.

AllerML: markup language for allergens

Many concerns have been raised about the potential allergenicity of novel, recombinant proteins into food crops. Guidelines, proposed by WHO/FAO and EFSA, include the use of bioinformatics screening to assess the risk of potential allergenicity or cross-reactivities of all proteins introduced, for example, to improve nutritional value or promote crop resistance. However, there are no universally accepted standards that can be used to encode data on the biology of allergens to facilitate using data from multiple databases in this screening. Therefore, we developed AllerML a markup language for allergens to assist in the automated exchange of information between databases and in the integration of the bioinformatics tools that are used to investigate allergenicity and cross-reactivity. As proof of concept, AllerML was implemented using the Structural Database of Allergenic Proteins (SDAP; http://fermi.utmb.edu/SDAP/) database. General implementation of AllerML will promote automatic flow of validated data that will aid in allergy research and regulatory analysis.

An Allergen Portrait Gallery: Representative Structures and an Overview of IgE Binding Surfaces

Recent progress in the biochemical classification and structural determination of allergens and allergen-antibody complexes has enhanced our understanding of the molecular determinants of allergenicity. Databases of allergens and their epitopes have facilitated the clustering of allergens according to their sequences and, more recently, their structures. Groups of similar sequences are identified for allergenic proteins from diverse sources, and all allergens are classified into a limited number of protein structural families. A gallery of experimental structures selected from the protein classes with the largest number of allergens demonstrate the structural diversity of the allergen universe. Further comparison of these structures and identification of areas that are different from innocuous proteins within the same protein family can be used to identify features specific to known allergens. Experimental and computational results related to the determination of IgE binding surfaces and methods to define allergen-specific motifs are highlighted.

Characterization of potential allergens in fenugreek (Trigonella foenum-graecum) using patient sera and MS-based proteomic analysis

BACKGROUND

Fenugreek is a legume plant used as an ingredient of curry spice. Incidents of IgE-mediated food allergy to fenugreek have been reported. Coincidence with allergy to peanut, a major food allergen, seems to be common suggesting a rather high rate of cross-reactivity.

OBJECTIVE

Characterization of fenugreek allergens using patient sera and mass spectrometry-based proteomic analysis.

METHODS

Allergenic fenugreek proteins were detected by immunoblotting, using sera from 13 patients with specific IgE to peanut and fenugreek. IgE-binding proteins were analyzed by peptide mass fingerprinting and peptide sequencing.

RESULTS

A fenugreek protein quintet in the range from 50 kDa to 66 kDa showed high IgE-affinity, the protein at 50 kDa reaching the strongest signals in all patients. Proteomic analyses allowed the classification of several fenugreek proteins to a number of allergen families. Fenugreek 7S-vicilin and 11S-legumin were partly sequenced and revealed considerable homologies to peanut Ara h 1 and Ara h 3, respectively. The presence of a fenugreek 2S albumin and pathogenesis-related (PR-10) plant pollen protein was assumed by database searching results.

CONCLUSION

In this study, individual fenugreek proteins were characterised for the first time. Observed homologies to major peanut allergens provide a molecular explanation for clinical cross-reactivity.

Safety assessment of biotechnology products for potential risk of food allergy: implications of new research

Food allergy is a potential risk associated with use of transgenic proteins in crops. Currently, safety assessment involves consideration of the source of the introduced protein, in silico amino acid sequence homology comparisons to known allergens, physicochemical properties, protein abundance in the crop, and, when appropriate, specific immunoglobulin E binding studies. Recently conducted research presented at an International Life Sciences Institute/Health and Environmental Sciences Institute-hosted workshop adds to the scientific foundation for safety assessment of transgenic proteins in five areas: structure/activity, serum screening, animal models, quantitative proteomics, and basic mechanisms. A web-based tool is now available that integrates a database of allergenic proteins with a variety of computational tools which could be used to improve our ability to predict allergenicity based on structural analysis. A comprehensive strategy and model protocols have been developed for conducting meaningful serum screening, an extremely challenging process. Several animal models using oral sensitization with adjuvant and one dermal sensitization model have been developed and appear to distinguish allergenic from non-allergenic food extracts. Data presented using a mouse model suggest that pepsin resistance is indicative of allergenicity. Certain questions remain to be addressed before considering animal model validation. Gel-free mass spectrometry is a viable alternative to more labor-intensive approaches to quantitative proteomics. Proteomic data presented on four nontransgenic varieties of soy suggested that if known allergen expression in genetically modified crops falls within the range of natural variability among commercial varieties, there appears to be no need to test further. Finally, basic research continues to elucidate the etiology of food allergy.

Structural analysis of linear and conformational epitopes of allergens

In many countries regulatory agencies have adopted safety guidelines, based on bioinformatics rules from the WHO/FAO and EFSA recommendations, to prevent potentially allergenic novel foods or agricultural products from reaching consumers. We created the Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/) to combine data that had previously been available only as flat files on Web pages or in the literature. SDAP was designed to be user friendly, to be of maximum use to regulatory agencies, clinicians, as well as to scientists interested in assessing the potential allergenic risk of a protein. We developed methods, unique to SDAP, to compare the physicochemical properties of discrete areas of allergenic proteins to known IgE epitopes. We developed a new similarity measure, the property distance (PD) value that can be used to detect related segments in allergens with clinical observed cross-reactivity. We have now expanded this work to obtain experimental validation of the PD index as a quantitative predictor of IgE cross-reactivity, by designing peptide variants with predetermined PD scores relative to known IgE epitopes. In complementary work we show how sequence motifs characteristic of allergenic proteins in protein families can be used as fingerprints for allergenicity.

The property distance index PD predicts peptides that cross-react with IgE antibodies

Similarities in the sequence and structure of allergens can explain clinically observed cross-reactivities. Distinguishing sequences that bind IgE in patient sera can be used to identify potentially allergenic protein sequences and aid in the design of hypo-allergenic proteins. The property distance index PD, incorporated in our Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/), may identify potentially cross-reactive segments of proteins, based on their similarity to known IgE epitopes. We sought to obtain experimental validation of the PD index as a quantitative predictor of IgE cross-reactivity, by designing peptide variants with predetermined PD scores relative to three linear IgE epitopes of Jun a 1, the dominant allergen from mountain cedar pollen. For each of the three epitopes, 60 peptides were designed with increasing PD values (decreasing physicochemical similarity) to the starting sequence. The peptides synthesized on a derivatized cellulose membrane were probed with sera from patients who were allergic to Jun a 1, and the experimental data were interpreted with a PD classification method. Peptides with low PD values relative to a given epitope were more likely to bind IgE from the sera than were those with PD values larger than 6. Control sequences, with PD values between 18 and 20 to all the three epitopes, did not bind patient IgE, thus validating our procedure for identifying negative control peptides. The PD index is a statistically validated method to detect discrete regions of proteins that have a high probability of cross-reacting with IgE from allergic patients.