Allergen databases

Bioinformatic resources for the investigation of proteins and proteomes

Experimental techniques in omics sciences need strong support of bioinformatics tools for the data management, analysis and interpretation. Scientific community develops continuously new databases and tools. They make it possible the comparison of new experimental data with the existing ones, to gain new knowledge. Bioinformatics assists proteomics scientists for protein identification from experimental data, management of the huge data produced, investigation of molecular mechanisms of protein functions, their roles in biochemical pathways, and functional interpretation of biological processes. This article introduces the main bioinformatics resources for investigation in the protein world, with references to analyses performed by means of free tools available on the net.

Unix interfaces, Kleisli, bucandin structure, etc. -- the heroic beginning of bioinformatics in Singapore

Remarkably, Singapore as one of today's hotspots for bioinformatics and computational biology research appeared de novo out of pioneering efforts of engaged local individuals in the early 90-s that, supported with increasing public funds from 1996 on, morphed into the present vibrant research community. This article brings to mind the pioneers, their first successes and early institutional developments.

Using databases and data mining in vaccinology

Throughout time functional immunology has accumulated vast amounts of quantitative and qualitative data relevant to the design and discovery of vaccines. Such data includes, but is not limited to, components of the host and pathogen genome (including antigens and virulence factors), T- and B-cell epitopes and other components of the antigen presentation pathway and allergens. In this review the authors discuss a range of databases that archive such data. Built on such information, increasingly sophisticated data mining techniques have developed that create predictive models of utilitarian value. With special reference to epitope data, the authors discuss the strengths and weaknesses of the available techniques and how they can aid computer-aided vaccine design deliver added value for vaccinology.

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.

Two-dimensional electrophoresis and IgE-mediated food allergy

Food allergy is recognized as one of the major health concerns. It is estimated that ca. 4% of the population is affected by food allergenic disorders. Food allergies are defined as IgE-mediated hypersensitivity reactions. Foods such as peanuts, tree nuts, wheat, soy, cow's milk, egg, fish and shellfish are regarded as responsible for the majority of reactions. The ubiquitous presence of allergens in the human foods coupled with an increased awareness of food allergies warrants to undertake appropriate preventive measures for protecting sensitive consumers from unwanted exposure to offending food allergens. 2-DE followed by immunoblotting and identification of IgE-reactive proteins, as a proteomic approach to identify new allergens in foods, are reviewed. Specific examples of identification of allergens in foods and beverages by using 2-DE and IgE are described. Protein profiling using 2-DE and allergens detection by IgE has become a powerful method for analyzing changes of allergens content in complex matrix during food processing.

Allergen Atlas: a comprehensive knowledge center and analysis resource for allergen information

Summary: A variety of specialist databases have been developed to facilitate the study of allergens. However, these databases either contain different subsets of allergen data or are deficient in tools for assessing potential allergenicity of proteins. Here, we describe Allergen Atlas, a comprehensive repository of experimentally validated allergen sequences collected from in-house laboratory, online data submission, literature reports and all existing general-purpose and specialist databases. Each entry was manually verified, classified and hyperlinked to major databases including Swiss-Prot, Protein Data Bank (PDB), Gene Ontology (GO), Pfam and PubMed. The database is integrated with analysis tools that include: (i) keyword search, (ii) BLAST, (iii) position-specific iterative BLAST (PSI-BLAST), (iv) FAO/WHO criteria search, (v) graphical representation of allergen information network and (vi) online data submission. The latest version contains information of 1593 allergen sequences (496 IUIS allergens, 978 experimentally verified allergens and 119 new sequences), 56 IgE epitope sequences, 679 links to PDB structures and 155 links to Pfam domains.

Availability: Allergen Atlas is freely available at http://tiger.dbs.nus.edu.sg/ATLAS/.

Contact:martti@nus.edu.sg.

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.

Identification of human-to-human transmissibility factors in PB2 proteins of influenza A by large-scale mutual information analysis

Background

The identification of mutations that confer unique properties to a pathogen, such as host range, is of fundamental importance in the fight against disease. This paper describes a novel method for identifying amino acid sites that distinguish specific sets of protein sequences, by comparative analysis of matched alignments. The use of mutual information to identify distinctive residues responsible for functional variants makes this approach highly suitable for analyzing large sets of sequences. To support mutual information analysis, we developed the AVANA software, which utilizes sequence annotations to select sets for comparison, according to user-specified criteria. The method presented was applied to an analysis of influenza A PB2 protein sequences, with the objective of identifying the components of adaptation to human-to-human transmission, and reconstructing the mutation history of these components.

Results

We compared over 3,000 PB2 protein sequences of human-transmissible and avian isolates, to produce a catalogue of sites involved in adaptation to human-to-human transmission. This analysis identified 17 characteristic sites, five of which have been present in human-transmissible strains since the 1918 Spanish flu pandemic. Sixteen of these sites are located in functional domains, suggesting they may play functional roles in host-range specificity. The catalogue of characteristic sites was used to derive sequence signatures from historical isolates. These signatures, arranged in chronological order, reveal an evolutionary timeline for the adaptation of the PB2 protein to human hosts.

Conclusion

By providing the most complete elucidation to date of the functional components participating in PB2 protein adaptation to humans, this study demonstrates that mutual information is a powerful tool for comparative characterization of sequence sets. In addition to confirming previously reported findings, several novel characteristic sites within PB2 are reported. Sequence signatures generated using the characteristic sites catalogue characterize concisely the adaptation characteristics of individual isolates. Evolutionary timelines derived from signatures of early human influenza isolates suggest that characteristic variants emerged rapidly, and remained remarkably stable through subsequent pandemics. In addition, the signatures of human-infecting H5N1 isolates suggest that this avian subtype has low pandemic potential at present, although it presents more human adaptation components than most avian subtypes.

Rule-based knowledge aggregation for large-scale protein sequence analysis of influenza A viruses

BACKGROUND

The explosive growth of biological data provides opportunities for new statistical and comparative analyses of large information sets, such as alignments comprising tens of thousands of sequences. In such studies, sequence annotations frequently play an essential role, and reliable results depend on metadata quality. However, the semantic heterogeneity and annotation inconsistencies in biological databases greatly increase the complexity of aggregating and cleaning metadata. Manual curation of datasets, traditionally favoured by life scientists, is impractical for studies involving thousands of records. In this study, we investigate quality issues that affect major public databases, and quantify the effectiveness of an automated metadata extraction approach that combines structural and semantic rules. We applied this approach to more than 90,000 influenza A records, to annotate sequences with protein name, virus subtype, isolate, host, geographic origin, and year of isolation.

RESULTS

Over 40,000 annotated Influenza A protein sequences were collected by combining information from more than 90,000 documents from NCBI public databases. Metadata values were automatically extracted, aggregated and reconciled from several document fields by applying user-defined structural rules. For each property, values were recovered from >/=88.8% of records, with accuracy exceeding 96% in most cases. Because of semantic heterogeneity, each property required up to six different structural rules to be combined. Significant quality differences between databases were found: GenBank documents yield values more reliably than documents extracted from GenPept. Using a simple set of semantic rules and a reasoner, we reconstructed relationships between sequences from the same isolate, thus identifying 7640 isolates. Validation of isolate metadata against a simple ontology highlighted more than 400 inconsistencies, leading to over 3,000 property value corrections.

CONCLUSION

To overcome the quality issues inherent in public databases, automated knowledge aggregation with embedded intelligence is needed for large-scale analyses. Our results show that user-controlled intuitive approaches, based on combination of simple rules, can reliably automate various curation tasks, reducing the need for manual corrections to approximately 5% of the records. Emerging semantic technologies possess desirable features to support today's knowledge aggregation tasks, with a potential to bring immediate benefits to this field.

Safety and nutritional assessment of GM plants and derived food and feed: the role of animal feeding trials

In this report the various elements of the safety and nutritional assessment procedure for genetically modified (GM) plant derived food and feed are discussed, in particular the potential and limitations of animal feeding trials for the safety and nutritional testing of whole GM food and feed. The general principles for the risk assessment of GM plants and derived food and feed are followed, as described in the EFSA guidance document of the EFSA Scientific Panel on Genetically Modified Organisms. In Section 1 the mandate, scope and general principles for risk assessment of GM plant derived food and feed are discussed. Products under consideration are food and feed derived from GM plants, such as maize, soybeans, oilseed rape and cotton, modified through the introduction of one or more genes coding for agronomic input traits like herbicide tolerance and/or insect resistance. Furthermore GM plant derived food and feed, which have been obtained through extensive genetic modifications targeted at specific alterations of metabolic pathways leading to improved nutritional and/or health characteristics, such as rice containing beta-carotene, soybeans with enhanced oleic acid content, or tomato with increased concentration of flavonoids, are considered. The safety assessment of GM plants and derived food and feed follows a comparative approach, i.e. the food and feed are compared with their non-GM counterparts in order to identify intended and unintended (unexpected) differences which subsequently are assessed with respect to their potential impact on the environment, safety for humans and animals, and nutritional quality. Key elements of the assessment procedure are the molecular, compositional, phenotypic and agronomic analysis in order to identify similarities and differences between the GM plant and its near isogenic counterpart. The safety assessment is focussed on (i) the presence and characteristics of newly expressed proteins and other new constituents and possible changes in the level of natural constituents beyond normal variation, and on the characteristics of the GM food and feed, and (ii) the possible occurrence of unintended (unexpected) effects in GM plants due to genetic modification. In order to identify these effects a comparative phenotypic and molecular analysis of the GM plant and its near isogenic counterpart is carried out, in parallel with a targeted analysis of single specific compounds, which represent important metabolic pathways in the plant like macro and micro nutrients, known anti-nutrients and toxins. Significant differences may be indicative of the occurrence of unintended effects, which require further investigation. Section 2 provides an overview of studies performed for the safety and nutritional assessment of whole food and feed. Extensive experience has been built up in recent decades from the safety and nutritional testing in animals of irradiated foods, novel foods and fruit and vegetables. These approaches are also relevant for the safety and nutritional testing of whole GM food and feed. Many feeding trials have been reported in which GM foods like maize, potatoes, rice, soybeans and tomatoes have been fed to rats or mice for prolonged periods, and parameters such as body weight, feed consumption, blood chemistry, organ weights, histopathology etc have been measured. The food and feed under investigation were derived from GM plants with improved agronomic characteristics like herbicide tolerance and/or insect resistance. The majority of these experiments did not indicate clinical effects or histopathological abnormalities in organs or tissues of exposed animals. In some cases adverse effects were noted, which were difficult to interpret due to shortcomings in the studies. Many studies have also been carried out with feed derived from GM plants with agronomic input traits in target animal species to assess the nutritive value of the feed and their performance potential. Studies in sheep, pigs, broilers, lactating dairy cows, and fish, comparing the in vivo bioavailability of nutrients from a range of GM plants with their near isogenic counterpart and commercial varieties, showed that they were comparable with those for near isogenic non-GM lines and commercial varieties. In Section 3 toxicological in vivo, in silico, and in vitro test methods are discussed which may be applied for the safety and nutritional assessment of specific compounds present in food and feed or of whole food and feed derived from GM plants. Moreover the purpose, potential and limitations of the 90-day rodent feeding trial for the safety and nutritional testing of whole food and feed have been examined. Methods for single and repeated dose toxicity testing, reproductive and developmental toxicity testing and immunotoxicity testing, as described in OECD guideline tests for single well-defined chemicals are discussed and considered to be adequate for the safety testing of single substances including new products in GM food and feed. Various in silico and in vitro methods may contribute to the safety assessment of GM plant derived food and feed and components thereof, like (i) in silico searches for sequence homology and/or structural similarity of novel proteins or their degradation products to known toxic or allergenic proteins, (ii) simulated gastric and intestinal fluids in order to study the digestive stability of newly expressed proteins and in vitro systems for analysis of the stability of the novel protein under heat or other processing conditions, and (iii) in vitro genotoxicity test methods that screen for point mutations, chromosomal aberrations and DNA damage/repair. The current performance of the safety assessment of whole foods is mainly based on the protocols for low-molecular-weight chemicals such as pharmaceuticals, industrial chemicals, pesticides, food additives and contaminants. However without adaptation, these protocols have limitations for testing of whole food and feed. This primarily results from the fact that defined single substances can be dosed to laboratory animals at very large multiples of the expected human exposure, thus giving a large margin of safety. In contrast foodstuffs are bulky, lead to satiation and can only be included in the diet at much lower multiples of expected human intakes. When testing whole foods, the possible highest concentration of the GM food and feed in the laboratory animal diet may be limited because of nutritional imbalance of the diet, or by the presence of compounds with a known toxicological profile. The aim of the 90-days rodent feeding study with the whole GM food and feed is to assess potential unintended effects of toxicological and/or nutritional relevance and to establish whether the GM food and feed is as safe and nutritious as its traditional comparator rather than determining qualitative and quantitative intrinsic toxicity of defined food constituents. The design of the study should be adapted from the OECD 90-day rodent toxicity study. The precise study design has to take into account the nature of the food and feed and the characteristics of the new trait(s) and their intended role in the GM food and feed. A 90-day animal feeding trial has a large capacity (sensitivity and specificity) to detect potential toxicological effects of single well defined compounds. This can be concluded from data reported on the toxicology of a wide range of industrial chemicals, pharmaceuticals, food substances, environmental, and agricultural chemicals. It is possible to model the sensitivity of the rat subchronic feeding study for the detection of hypothetically increased amount of compounds such as anti-nutrients, toxicants or secondary metabolites. With respect to the detection of potential unintended effects in whole GM food and feed, it is unlikely that substances present in small amounts and with a low toxic potential will result in any observable (unintended) effects in a 90-day rodent feeding study, as they would be below the no-observed-effect-level and thus of unlikely impact to human health at normal intake levels. Laboratory animal feeding studies of 90-days duration appear to be sufficient to pick up adverse effects of diverse compounds that would also give adverse effects after chronic exposure. This conclusion is based on literature data from studies investigating whether toxicological effects are adequately identified in 3-month subchronic studies in rodents, by comparing findings at 3 and 24 months for a range of different chemicals. The 90-day rodent feeding study is not designed to detect effects on reproduction or development other than effects on adult reproductive organ weights and histopathology. Analyses of available data indicate that, for a wide range of substances, reproductive and developmental effects are not potentially more sensitive endpoints than those examined in subchronic toxicity tests. Should there be structural alerts for reproductive/developmental effects or other indications from data available on a GM food and feed, then these tests should be considered. By relating the estimated daily intake, or theoretical maximum daily intake per capita for a given whole food (or the sum of its individual commercial constituents) to that consumed on average per rat per day in the subchronic 90-day feeding study, it is possible to establish the margin of exposure (safety margin) for consumers. Results obtained from testing GM food and feed in rodents indicate that large (at least 100-fold) 'safety' margins exist between animal exposure levels without observed adverse effects and estimated human daily intake. Results of feeding studies with feed derived from GM plants with improved agronomic properties, carried out in a wide range of livestock species, are discussed. The studies did not show any biologically relevant differences in the parameters tested between control and test animals. (ABSTRACT TRUNCATED)

Bioinformatics approaches to classifying allergens and predicting cross-reactivity

Allergenic proteins from very different environmental sources have similar sequences and structures. This fact may account for multiple allergen syndromes, whereby a myriad of diverse plants and foods may induce a similar IgE-based reaction in certain patients. Identifying the common triggering protein in these sources, in silico, can aid designing individualized therapy for allergen sufferers. This article provides an overview of databases on allergenic proteins, and ways to identify common proteins that may be the cause of multiple allergy syndromes. The major emphasis is on the relational Structural Database of Allergenic Proteins (SDAP []), which includes cross-referenced data on the sequence, structure, and IgE epitopes of over 800 allergenic proteins, coupled with specially developed bioinformatics tools to group all allergens and identify discrete areas that may account for cross-reactivity. SDAP is freely available on the Web to clinicians and patients.

ALLERDB database and integrated bioinformatic tools for assessment of allergenicity and allergic cross-reactivity

Databases and computational tools are increasingly important in the study of allergies, particularly in the assessment of allergenicity and allergic cross-reactivity. ALLERDB database contains sequences of allergens and information on reported cross-reactivity between allergens. It focuses on analysis of allergenicity and allergic cross-reactivity of clinically relevant protein allergens. The official IUIS allergen data were extracted from the IUIS Allergen Nomenclature Sub-Committee website, and their sequence information from the public databases, and reference publications. The analysis tools assist allergen data analysis and retrieval, and include keyword searching, BLAST, prediction of allergenicity, modification of BLAST that displays cross-reactive allergens, and graphics representation of cross-reactivity data. ALLERDB is new brand of allergen databases with a rich set of tools for sequence comparison, pattern identification, and visualization of results. It is accessible at http://research.i2r.a-star.edu.sg/Templar/DB/Allergen.

Allergen sequence databases

A number of specialized databases have been developed to facilitate studies of human allergens. These include molecular databases focused on protein sequences and structures, informational databases focused on clinical, biochemical and epidemiological data related to protein allergens, a database on allergen nomenclature, and other knowledge bases or informational websites that are peripherally-related to research on allergens. Examples of each type of databases are listed and described briefly in this review. Database construction and maintenance and their impact on database quality and usefulness are also discussed.

Introduction to bioinformatics

This article introduces the field of bioinformatics and describes bioinformatic approaches and their application to the study of protein allergens. The predominant bioinformatics tools and resources are listed and discussed.

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 ulfh@slv.se.

Building an allergens ontology and maintaining it using machine learning techniques

Ontologies are widely used for formalizing and organizing the knowledge of a particular domain of interest. This facilitates knowledge sharing and re-use by both people and systems. Ontologies are becoming increasingly important in the biomedical domain since they enable knowledge sharing in a formal, homogeneous and unambiguous way. Knowledge in a rapidly growing field such as biomedicine is usually evolving and therefore an ontology maintenance process is required to keep ontological knowledge up-to-date. This work presents our methodology for building a formally defined ontology, maintaining it exploiting machine learning techniques and domain specific corpora, and evaluating it using a well-defined experimental setting. The application of this methodology in the allergen domain is then discussed in detail presenting the ontology built, the specific techniques used and the evaluation settings.

The potential of proteomics and peptidomics for allergy and asthma research

Progress in the field of proteomics, the branch of biology that studies the full set of proteins derived from a given genome, is moving fast. Two-dimensional gel electrophoresis (2DG) separation of complex protein mixtures and the subsequent analysis of isolated protein spots by mass spectrometry allow fast and accurate identification of proteins. The comparison of spots from different samples separated on customized 2D gels allows the detection of punctual differences in their mobility and facilitates tracing back differences in protein expression, presence of isoforms, splice variants and posttranslational modifications by mass spectrometry. In spite of significant analytical challenges owing to the high complexity of the proteome and the challenge deriving from the necessity to process huge amounts of raw data generated by mass spectrometric profiling, proteomics has evolved to an indispensable tool in life sciences. A restricted window of the proteome that consists of peptides and small proteins not easily manageable by conventional gel electrophoresis prompted the development of separation methods based on liquid chromatography. This new research field termed peptidomics already contributed, together with proteomics to enlarge our knowledge about biological processes and supported by sophisticated bioinformatics tools, to the discovery of new diagnostic and therapeutic targets. The technological capabilities of biophysical separation, mass spectrometry and bioinformatics form the basis of discovery programs that aim at mining the proteome starting from microgram amounts of protein extracts derived from body fluids and tissues. Proteomics and peptidomics have a great potential to speed up allergy and asthma research, where disease- and tissue-specific samples are easy to obtain.

Analytical methodology for assessment of food allergens: Opportunities and challenges

This review summarizes the available in vitro, in vivo, and informatic methods designed to evaluate different aspects of the capacity of proteins to act as true food allergens. By now, there is no single method to fully assess the potential allergenicity of proteins. The characterization of many food allergens will help to uncover the sequential and structural motifs that determine the behaviour of proteins as food allergens.

Importance of databases in experimental and clinical allergology

Information technology (IT) is leading us to reconsider some of the approaches we have been using in both basic research and clinical work in allergology. Resources mainly coming from the advent of the Internet are further amplified by the parallel development of other new tools, such as molecular biology and nanotechnology. These three powerful tools are now available and are cross-linked to a certain degree to express their power when applied to biomedical fields. Bioinformatics applied to allergy simplifies our way of handling an increasing wealth of knowledge. This review assesses the current status of allergen databases that are mainly dedicated to sequence homology collection for computational purposes. Whether or not they integrate features that are now typical of IT in other biomedical fields is analyzed as well. The results of these analyses are discussed with a view to the critical need of integrating biochemical data with clinical, epidemiological information and how this goal can be reached by the use of proteomic microarrays for IgE detection. Future directions for a more comprehensive use of allergen databases are proposed.

Allergy assessment of foods or ingredients derived from biotechnology, gene-modified organisms, or novel foods

The introduction of novel proteins into foods carries a risk of eliciting allergic reactions in individuals sensitive to the introduced protein and a risk of sensitizing susceptible individuals. No single predictive test exists to perform a hazard assessment in relation to allergenic properties of newly expressed proteins in gene-modified organisms (GMOs). Instead, performance of a weighted risk analysis based on the decision tree approach has been suggested. The individual steps of this analysis comprise sequence homology to known allergens, specific or targeted serum screens for immunoglobulin E (IgE) cross-reactions to known allergens, digestability studies of the proteins in simulated gastric and/or intestinal fluids, and animal studies. These steps are discussed and five examples of risk evaluation of GMOs or novel foods are presented. These include ice-structuring protein derived from fish, microbial transglutaminase, GMO-soybeans, amylase and the Nangai nut.

Evaluation of the potential allergenicity of the enzyme microbial transglutaminase using the 2001 FAO/WHO Decision Tree

All novel proteins must be assessed for their potential allergenicity before they are introduced into the food market. One method to achieve this is the 2001 FAO/WHO Decision Tree recommended for evaluation of proteins from genetically modified organisms (GMOs). It was the aim of this study to investigate the allergenicity of microbial transglutaminase (m-TG) from Streptoverticillium mobaraense. Amino acid sequence similarity to known allergens, pepsin resistance, and detection of protein binding to specific serum immunoglobulin E (IgE) (RAST) have been evaluated as recommended by the decision tree. Allergenicity in the source material was thought unlikely, since no IgE-mediated allergy to any bacteria has been reported. m-TG is fully degraded after 5 min of pepsin treatment. A database search showed that the enzyme has no homology with known allergens, down to a match of six contiguous amino acids, which meets the requirements of the decision tree. However, there is a match at the five contiguous amino acid level to the major codfish allergen Gad c1. The potential cross reactivity between m-TG and Gad c1 was investigated in RAST using sera from 25 documented cod-allergic patients and an extract of raw codfish. No binding between patient IgE and m-TG was observed. It can be concluded that no safety concerns with regard to the allergenic potential of m-TG were identified.

An Update on the Functional Molecular Immunology (FIMM) Database

Data on the major histocompatibility complex, T-cell epitopes, B-cell epitopes, antigens and diseases are heterogeneous and scattered among different databases and the literature. Since it has become increasingly difficult to obtain an integrated view of functional immune response components, we have developed and updated over several years the Functional molecular IMMunology (FIMM) database (http:// research.i2r.a-star.edu.sg/fimm/). FIMM contains integrated expert-curated data on protein antigens, and on human immunological receptors that recognise and bind them in healthy or disease states. Interfaces with multiple, intuitive query options and query reports provide immunologists with prioritised information that aids data interpretation, vaccine target discovery and immune disease research.

Supervised identification of allergen-representative peptides for in silico detection of potentially allergenic proteins

MOTIVATION

Identification of potentially allergenic proteins is needed for the safety assessment of genetically modified foods, certain pharmaceuticals and various other products on the consumer market. Current methods in bioinformatic allergology exploit common features among allergens for the detection of amino acid sequences of potentially allergenic proteins. Features for identification still unexplored include the motifs occurring commonly in allergens, but rarely in ordinary proteins. In this paper, we present an algorithm for the identification of such motifs with the purpose of biocomputational detection of amino acid sequences of potential allergens.

RESULTS

Identification of allergen-representative peptides (ARPs) with low or no occurrence in proteins lacking allergenic properties is the essential component of our new method, designated DASARP (Detection based on Automated Selection of Allergen-Representative Peptide). This approach consistently outperforms the criterion based on identical peptide match for predicting allergenicity recommended by ILSI/IFBC and FAO/WHO and shows results comparable to the alignment-based criterion as outlined by FAO/WHO.

AVAILABILITY

The detection software and the ARP set needed for the analysis of a query protein reported here are properties of the Swedish National Food Agency and are available upon request. The protein sequence sets used in this work are publicly available on http://www.slv.se/templatesSLV/SLV_Page____9343.asp. Allergenicity assessment for specific protein sequences of interest is also possible via ulfh@slv.se

Computational tools for the study of allergens

Allergy is a major cause of morbidity worldwide. The number of characterized allergens and related information is increasing rapidly creating demands for advanced information storage, retrieval and analysis. Bioinformatics provides useful tools for analysing allergens and these are complementary to traditional laboratory techniques for the study of allergens. Specific applications include structural analysis of allergens, identification of B- and T-cell epitopes, assessment of allergenicity and cross-reactivity, and genome analysis. In this paper, the most important bioinformatic tools and methods with relevance to the study of allergy have been reviewed.