Databases and Algorithms in Allergen Informatics

Allergic diseases are considered as one of the major health problems worldwide due to their increasing prevalence. Advancements in genomic, proteomic, and analytical techniques have resulted in considerable progress in the field of allergology, which has led to accumulation of huge amount of data. Allergen bioinformatics comprises allergen-related data resources and computational methods/tools, which deal with an efficient archival, management, and analysis of allergological data. Significant work has been done in the area of allergen bioinformatics that has proven pivotal for the development and progress of this field. In this chapter, we describe the current status of databases and algorithms, encompassing the field of allergen bioinformatics by examining work carried out thus far with respect to features such as allergens and allergenicity, allergen databases, algorithms/tools for allergen/allergenicity prediction, allergen epitope prediction, and allergenic cross-reactivity assessment. This chapter illustrates concepts and algorithms in allergen bioinformatics, as well as it outlines the key areas for potential development in allergology field

Computational detection of allergenic proteins attains a new level of accuracy with in silico variable-length peptide extraction and machine learning

The placing of novel or new-in-the-context proteins on the market, appearing in genetically modified foods, certain bio-pharmaceuticals and some household products leads to human exposure to proteins that may elicit allergic responses. Accurate methods to detect allergens are therefore necessary to ensure consumer/patient safety. We demonstrate that it is possible to reach a new level of accuracy in computational detection of allergenic proteins by presenting a novel detector, Detection based on Filtered Length-adjusted Allergen Peptides (DFLAP). The DFLAP algorithm extracts variable length allergen sequence fragments and employs modern machine learning techniques in the form of a support vector machine. In particular, this new detector shows hitherto unmatched specificity when challenged to the Swiss-Prot repository without appreciable loss of sensitivity. DFLAP is also the first reported detector that successfully discriminates between allergens and non-allergens occurring in protein families known to hold both categories. Allergenicity assessment for specific protein sequences of interest using DFLAP is possible via [email protected]

Applying the adverse outcome pathway (AOP) for food sensitization to support in vitro testing strategies

Background Before introducing proteins from new or alternative dietary sources into the market, a compressive risk assessment including food allergic sensitization should be carried out in order to ensure their safety. We have recently proposed the adverse outcome pathway (AOP) concept to structure the current mechanistic understanding of the molecular and cellular pathways evidenced to drive IgE-mediated food allergies. This AOP framework offers the biological context to collect and structure existing in vitro methods and to identify missing assays to evaluate sensitizing potential of food proteins. Scope and approach In this review, we provide a state-of-the-art overview of available in vitro approaches for assessing the sensitizing potential of food proteins, including their strengths and limitations. These approaches are structured by their potential to evaluate the molecular initiating and key events driving food sensitization. Key findings and conclusions The application of the AOP framework offers the opportunity to anchor existing testing methods to specific building blocks of the AOP for food sensitization. In general, in vitro methods evaluating mechanisms involved in the innate immune response are easier to address than assays addressing the adaptive immune response due to the low precursor frequency of allergen-specific T and B cells. Novel ex vivo culture strategies may have the potential to become useful tools for investigating the sensitizing potential of food proteins. When applied in the context of an integrated testing strategy, the described approaches may reduce, if not replace, current animal testing approaches

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

Allermatch™, a webtool for the prediction of potential allergenicity according to current FAO/WHO Codex alimentarius guidelines

BACKGROUND: Novel proteins entering the food chain, for example by genetic modification of plants, have to be tested for allergenicity. Allermatch™ is a webtool for the efficient and standardized prediction of potential allergenicity of proteins and peptides according to the current recommendations of the FAO/WHO Expert Consultation, as outlined in the Codex alimentarius. DESCRIPTION: A query amino acid sequence is compared with all known allergenic proteins retrieved from the protein databases using a sliding window approach. This identifies stretches of 80 amino acids with more than 35% similarity or small identical stretches of at least six amino acids. The outcome of the analysis is presented in a concise format. The predictive performance of the FAO/WHO criteria is evaluated by screening sets of allergens and non-allergens against the Allermatch databases. Besides correct predictions, both methods are shown to generate false positive and false negative hits and the outcomes should therefore be combined with other methods of allergenicity assessment, as advised by the FAO/WHO. CONCLUSIONS: Allermatch™ provides an accessible, efficient, and useful webtool for analysis of potential allergenicity of proteins introduced in genetically modified food prior to market release that complies with current FAO/WHO guidelines

Guidance on allergenicity assessment of genetically modified plants

This document provides supplementary guidance on specific topics for the allergenicity risk assessment of genetically modified plants. In particular, it supplements general recommendations outlined in previous EFSA GMO Panel guidelines and Implementing Regulation (EU) No 503/2013. The topics addressed are non-IgE-mediated adverse immune reactions to foods, in vitro protein digestibility tests and endogenous allergenicity. New scientific and regulatory developments regarding these three topics are described in this document. Considerations on the practical implementation of those developments in the risk assessment of genetically modified plants are discussed and recommended, where appropriate. (C) 2017 European Food Safety Authority. EFSA Journal published by John Wiley and Sons Ltd on behalf of European Food Safety Authority

Nutrition, allergenicity and physicochemical qualities of food-grade protein extracts from Nannochloropsis oculata

Microalgae offer an opportunity to act as a sustainable source of dietary protein. This study aimed to evaluate the impact of different protein extraction methods on the nutritional and physicochemical properties of Nannochloropsis oculata. Food-grade protein extracts were obtained by hypotonic osmotic shock using milli-Q water. Food grade (FG) and non-food grade (NFG) extraction buffers were compared along with three cell disruption methods including bead beating, probe sonication and a combination of both methods for protein extraction. Mass spectrometry was used for protein and putative allergen identification in FG extracts. Bead beating led to a slightly higher number of identifiable proteins in FG extracts compared to control condition. Putative allergenic proteins were identified in FG extracts of N. oculata using different in-silico methods. These findings support the need to further evaluate the potential allergenic proteins in microalgae including N. oculata such as immunoglobulin E (IgE) binding tests

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

Comparison of protein extraction protocols and allergen mapping from black soldier fly Hermetia illucens

Exploration of important insect proteins — including allergens — and proteomes can be limited by protein extraction buffer selection and the complexity of the proteome. Herein, LC-MS/MS-based proteomics experiments were used to assess the protein extraction efficiencies for a suite of extraction buffers and the effect of ingredient processing on proteome and allergen detection. Discovery proteomics revealed that SDS-based buffer yields the maximum number of protein groups from three types of BSF samples. Bioinformatic analysis revealed that buffer composition and ingredient processing could influence allergen detection. Upon applying multi-level filtering criteria, 33 putative allergens were detected by comparing the detected BSF proteins to sequences from public allergen protein databases. A targeted LC-MRM-MS assay was developed for the pan-allergen tropomyosin and used to assess the influence of buffer composition and ingredient processing using peptide abundance measurements. Significance: We demonstrated that the selection of protein extraction buffer and the processing method could influence protein yield and cross-reactive allergen detection from processed and un-processed black soldier fly (BSF) samples. In total, 33 putative allergens were detected by comparing the detected BSF proteins to sequences from public allergen protein databases. An LC-MRM-MS assay was developed for tropomyosin, indicating the importance of buffer selection and processing conditions to reduce BSF samples\u27 allergenicity