Screening of transgenic proteins expressed in transgenic food crops for the presence of short amino acid sequences identical to potential, IgE - binding linear epitopes of allergens

Common Amino Acid Subsequences in a Universal Proteome--Relevance for Food Science

A common subsequence is a fragment of the amino acid chain that occurs in more than one protein. Common subsequences may be an object of interest for food scientists as biologically active peptides, epitopes, and/or protein markers that are used in comparative proteomics. An individual bioactive fragment, in particular the shortest fragment containing two or three amino acid residues, may occur in many protein sequences. An individual linear epitope may also be present in multiple sequences of precursor proteins. Although recent recommendations for prediction of allergenicity and cross-reactivity include not only sequence identity, but also similarities in secondary and tertiary structures surrounding the common fragment, local sequence identity may be used to screen protein sequence databases for potential allergens in silico. The main weakness of the screening process is that it overlooks allergens and cross-reactivity cases without identical fragments corresponding to linear epitopes. A single peptide may also serve as a marker of a group of allergens that belong to the same family and, possibly, reveal cross-reactivity. This review article discusses the benefits for food scientists that follow from the common subsequences concept.

PREAL: prediction of allergenic protein by maximum Relevance Minimum Redundancy (mRMR) feature selection

BACKGROUND

Assessment of potential allergenicity of protein is necessary whenever transgenic proteins are introduced into the food chain. Bioinformatics approaches in allergen prediction have evolved appreciably in recent years to increase sophistication and performance. However, what are the critical features for protein's allergenicity have been not fully investigated yet.

RESULTS

We presented a more comprehensive model in 128 features space for allergenic proteins prediction by integrating various properties of proteins, such as biochemical and physicochemical properties, sequential features and subcellular locations. The overall accuracy in the cross-validation reached 93.42% to 100% with our new method. Maximum Relevance Minimum Redundancy (mRMR) method and Incremental Feature Selection (IFS) procedure were applied to obtain which features are essential for allergenicity. Results of the performance comparisons showed the superior of our method to the existing methods used widely. More importantly, it was observed that the features of subcellular locations and amino acid composition played major roles in determining the allergenicity of proteins, particularly extracellular/cell surface and vacuole of the subcellular locations for wheat and soybean. To facilitate the allergen prediction, we implemented our computational method in a web application, which can be available at http://gmobl.sjtu.edu.cn/PREAL/index.php.

CONCLUSIONS

Our new approach could improve the accuracy of allergen prediction. And the findings may provide novel insights for the mechanism of allergies.

Genetically modified foods: safety, risks and public concerns-a review

Genetic modification is a special set of gene technology that alters the genetic machinery of such living organisms as animals, plants or microorganisms. Combining genes from different organisms is known as recombinant DNA technology and the resulting organism is said to be 'Genetically modified (GM)', 'Genetically engineered' or 'Transgenic'. The principal transgenic crops grown commercially in field are herbicide and insecticide resistant soybeans, corn, cotton and canola. Other crops grown commercially and/or field-tested are sweet potato resistant to a virus that could destroy most of the African harvest, rice with increased iron and vitamins that may alleviate chronic malnutrition in Asian countries and a variety of plants that are able to survive weather extremes. There are bananas that produce human vaccines against infectious diseases such as hepatitis B, fish that mature more quickly, fruit and nut trees that yield years earlier and plants that produce new plastics with unique properties. Technologies for genetically modifying foods offer dramatic promise for meeting some areas of greatest challenge for the 21st century. Like all new technologies, they also pose some risks, both known and unknown. Controversies and public concern surrounding GM foods and crops commonly focus on human and environmental safety, labelling and consumer choice, intellectual property rights, ethics, food security, poverty reduction and environmental conservation. With this new technology on gene manipulation what are the risks of "tampering with Mother Nature"?, what effects will this have on the environment?, what are the health concerns that consumers should be aware of? and is recombinant technology really beneficial? This review will also address some major concerns about the safety, environmental and ecological risks and health hazards involved with GM foods and recombinant technology.

Epitopic hexapeptide sequences from Baltic cod parvalbumin beta (allergen Gad c 1) are common in the universal proteome

The aim of this study was to analyze the distribution of hexapeptide fragments considered as epitopes of Baltic cod parvalbumin beta (allergen Gad c 1) in the universal proteome. Cod (Gadus morhua subsp. callarias) parvalbumin hexapeptides cataloged in the Immune Epitope Database were used as query sequences. The UniProt database was screened using the WU-BLAST 2 program. The distribution of hexapeptide fragments was investigated in various protein families, classified according to the presence of the appropriate domains, and in proteins of plant, animal and microbial species. Hexapeptides from cod parvalbumin were found in the proteins of plants and animals which are food sources, microorganisms with various applications in food technology and biotechnology, microorganisms which are human symbionts and commensals as well as human pathogens. In the last case possible coverage between epitopes from pathogens and allergens should be avoided during vaccine design.

Allergenicity assessment of the papaya ringspot virus coat protein expressed in transgenic rainbow papaya

The virus-resistant, transgenic commercial papaya Rainbow and SunUp (Carica papaya L.) have been consumed locally in Hawaii and elsewhere in the mainland United States and Canada since their release to planters in Hawaii in 1998. These papaya are derived from transgenic papaya line 55-1 and carry the coat protein (CP) gene of papaya ringspot virus (PRSV). The PRSV CP was evaluated for potential allergenicity, an important component in assessing the safety of food derived from transgenic plants. The transgene PRSV CP sequence of Rainbow papaya did not exhibit greater than 35% amino acid sequence homology to known allergens, nor did it have a stretch of eight amino acids found in known allergens which are known common bioinformatic methods used for assessing similarity to allergen proteins. PRSV CP was also tested for stability in simulated gastric fluid and simulated intestinal fluid and under various heat treatments. The results showed that PRSV CP was degraded under conditions for which allergenic proteins relative to nonallergens are purported to be stable. The potential human intake of transgene-derived PRSV CP was assessed by measuring CP levels in Rainbow and SunUp along with estimating the fruit consumption rates and was compared to potential intake estimates of PRSV CP from naturally infected nontransgenic papaya. Following accepted allergenicity assessment criteria, our results show that the transgene-derived PRSV CP does not pose a risk of food allergy.

Safety evaluation of the double mutant 5-enol pyruvylshikimate-3-phosphate synthase (2mEPSPS) from maize that confers tolerance to glyphosate herbicide in transgenic plants

Glyphosate tolerance can be conferred by decreasing the herbicide's ability to inhibit the enzyme 5-enol pyruvylshikimate-3-phosphate synthase, which is essential for the biosynthesis of aromatic amino acids in all plants, fungi, and bacteria. Glyphosate tolerance is based upon the expression of the double mutant 5-enol pyruvylshikimate-3-phosphate synthase (2mEPSPS) protein. The 2mEPSPS protein, with a lower binding affinity for glyphosate, is highly resistant to the inhibition by glyphosate and thus allows sufficient enzyme activity for the plants to grow in the presence of herbicides that contain glyphosate. Based on both a review of published literature and experimental studies, the potential safety concerns related to the transgenic 2mEPSPS protein were assessed. The safety evaluation supports that the expressed protein is innocuous. The 2mEPSPS enzyme does not possess any of the properties associated with known toxins or allergens, including a lack of amino acid sequence similarity to known toxins and allergens, a rapid degradation in simulated gastric and intestinal fluids, and no adverse effects in mice after intravenous or oral administration (at 10 or 2000 mg/kg body weight, respectively). In conclusion, there is a reasonable certainty of no harm resulting from the inclusion of the 2mEPSPS protein in human food or in animal feed.

Recent advances in the development of transgenic papaya technology

Papaya with resistance to papaya ringspot virus (PRSV) is the first genetically modified tree and fruit crop and also the first transgenic crop developed by a public institution that has been commercialized. This chapter reviews the different transformation systems used for papaya and recent advances in the use of transgenic technology to introduce important quality and horticultural traits in papaya. These include the development of the following traits in papaya: resistance to PRSV, mites and Phytophthora, delayed ripening trait or long shelf life by inhibiting ethylene production or reducing loss of firmness, and tolerance or resistance to herbicide and aluminum toxicity. The use of papaya to produce vaccine against tuberculosis and cysticercosis, an infectious animal disease, has also been explored. Because of the economic importance of papaya, there are several collaborative and independent efforts to develop PRSV transgenic papaya technology in 14 countries. This chapter further reviews the strategies and constraints in the adoption of the technology and biosafety to the environment and food safety. Constraints to adoption include public perception, strict and expensive regulatory procedures and intellectual property issues.

EVALLER: a web server for in silico assessment of potential protein allergenicity

Bioinformatics testing approaches for protein allergenicity, involving amino acid sequence comparisons, have evolved appreciably over the last several years to increased sophistication and performance. EVALLER, the web server presented in this article is based on our recently published 'Detection based on Filtered Length-adjusted Allergen Peptides' (DFLAP) algorithm, which affords in silico determination of potential protein allergenicity of high sensitivity and excellent specificity. To strengthen bioinformatics risk assessment in allergology EVALLER provides a comprehensive outline of its judgment on a query protein's potential allergenicity. Each such textual output incorporates a scoring figure, a confidence numeral of the assignment and information on high- or low-scoring matches to identified allergen-related motifs, including their respective location in accordingly derived allergens. The interface, built on a modified Perl Open Source package, enables dynamic and color-coded graphic representation of key parts of the output. Moreover, pertinent details can be examined in great detail through zoomed views. The server can be accessed at http://bioinformatics.bmc.uu.se/evaller.html.

Non-redundant Peptidomes from DAPs: Towards “The Vaccine”?

Experimental analyses and literature survey reveal low-redundancy to the host proteins as a common denominator of immunogenic sequences mapped along tumor-, autoimmune-, and infectious disease-associated-proteins. The hypothesis that immunogenicity of peptide sequences is linked to proteomic redundancy is discussed.

Safety of virus-resistant transgenic plants two decades after their introduction: lessons from realistic field risk assessment studies

Potential safety issues have been raised with the development and release of virus-resistant transgenic plants. This review focuses on safety assessment with a special emphasis on crops that have been commercialized or extensively tested in the field such as squash, papaya, plum, grape, and sugar beet. We discuss topics commonly perceived to be of concern to the environment and to human health--heteroencapsidation, recombination, synergism, gene flow, impact on nontarget organisms, and food safety in terms of allergenicity. The wealth of field observations and experimental data is critically evaluated to draw inferences on the most relevant issues. We also express inside views on the safety and benefits of virus-resistant transgenic plants, and recommend realistic risk assessment approaches to assist their timely deregulation and release.

Practical and predictive bioinformatics methods for the identification of potentially cross-reactive protein matches

A bioinformatics comparison of proteins introduced into food crops through genetic engineering provides a mechanism to identify those proteins that may present an increased risk of allergic reactions for individuals with existing allergies. The goal is to identify proteins that are known to be allergens or are so similar to an allergen that they may induce allergic cross-reactions. Three comparative approaches have traditionally been used, or considered for safety evaluations. One identifies any short (6-8) amino acid segment of the protein that exactly matches a known allergen sequence. The second is an overall primary sequence comparison using Basic Local Alignment Search Tool (BLAST) or FASTA to find matches of greater than 35% identity over 80 amino acids. The third is based on 3-D prediction programs to identify 3-D similarities that might predict potential cross-reactivity. The utility of each of these approaches was debated in the bioinformatics workshop. The consensus agreement from the expert workshop participants was that the short-segment match (e. g., 6-8 amino acids) provides an unacceptably high rate of false positive matches and an uncertain rate of true positive matches, and was not particularly useful for an allergenicity evaluation performed in the context of comprehensive safety evaluation. There was no consensus regarding the most appropriate bioinformatics method, an acceptable scoring criteria for triggering closer examination subsequent to a positive match, or an acceptable scoring mechanism for ranking the utility of the various 3-D approaches that were discussed during the workshop. However, the general consensus was that the most practical approach at this time is to evaluate primary sequence identities to known allergens using either FASTA or BLAST. While there was good agreement that identities of greater than 35% over 80 or more amino acids (recommended by Codex in 2003) is quite conservative, the conclusion was that additional data or studies would be needed to justify changing this criterion as there is some evidence that some individuals sensitized to proteins in evolutionarily conserved protein families may experience cross-reactions to proteins sharing approximately 40% identity.

AlgPred: prediction of allergenic proteins and mapping of IgE epitopes

In this study a systematic attempt has been made to integrate various approaches in order to predict allergenic proteins with high accuracy. The dataset used for testing and training consists of 578 allergens and 700 non-allergens obtained from A. K. Bjorklund, D. Soeria-Atmadja, A. Zorzet, U. Hammerling and M. G. Gustafsson (2005) Bioinformatics, 21, 39-50. First, we developed methods based on support vector machine using amino acid and dipeptide composition and achieved an accuracy of 85.02 and 84.00%, respectively. Second, a motif-based method has been developed using MEME/MAST software that achieved sensitivity of 93.94 with 33.34% specificity. Third, a database of known IgE epitopes was searched and this predicted allergenic proteins with 17.47% sensitivity at specificity of 98.14%. Fourth, we predicted allergenic proteins by performing BLAST search against allergen representative peptides. Finally hybrid approaches have been developed, which combine two or more than two approaches. The performance of all these algorithms has been evaluated on an independent dataset of 323 allergens and on 101 725 non-allergens obtained from Swiss-Prot. A web server AlgPred has been developed for the predicting allergenic proteins and for mapping IgE epitopes on allergenic proteins (http://www.imtech.res.in/raghava/algpred/). AlgPred is available at www.imtech.res.in/raghava/algpred/.

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.

Evaluation of available IgE-binding epitope data and its utility in bioinformatics

This paper reviews the role played by IgE-binding epitopes in eliciting clinical symptoms, the types of IgE-binding epitopes in allergenic proteins, the methods used to identify IgE-binding epitopes, and the availability of IgE-binding epitopes in allergenic sources. Finally, bioinformatics methods to assess protein allergenicity using knowledge of IgE-binding epitopes are discussed.

External cross-validation for unbiased evaluation of protein family detectors: application to allergens

Key issues in protein science and computational biology are design and evaluation of algorithms aimed at detection of proteins that belong to a specific family, as defined by structural, evolutionary, or functional criteria. In this context, several validation techniques are often used to compare different parameter settings of the detector, and to subsequently select the setting that yields the smallest error rate estimate. A frequently overlooked problem associated with this approach is that this smallest error rate estimate may have a large optimistic bias. Based on computer simulations, we show that a detector's error rate estimate can be overly optimistic and propose a method to obtain unbiased performance estimates of a detector design procedure. The method is founded on an external 10-fold cross-validation (CV) loop that embeds an internal validation procedure used for parameter selection in detector design. The designed detector generated in each of the 10 iterations are evaluated on held-out examples exclusively available in the external CV iterations. Notably, the average of these 10 performance estimates is not associated with a final detector, but rather with the average performance of the design procedure used. We apply the external CV loop to the particular problem of detecting potentially allergenic proteins, using a previously reported design procedure. Unbiased performance estimates of the allergen detector design procedure are presented together with information about which algorithms and parameter settings that are most frequently selected.

Computer prediction of allergen proteins from sequence-derived protein structural and physicochemical properties

BACKGROUND

Computational methods have been developed for predicting allergen proteins from sequence segments that show identity, homology, or motif match to a known allergen. These methods achieve good prediction accuracies, but are less effective for novel proteins with no similarity to any known allergen.

METHODS

This work tests the feasibility of using a statistical learning method, support vector machines, as such a method. The prediction system is trained and tested by using 1005 allergen proteins from the Allergome database and 22,469 non-allergen proteins from 7871 Pfam families.

RESULTS

Testing results by an independent set of 229 allergen and 6717 non-allergen proteins from 7871 Pfam families show that 93.0% and 99.9% of these are correctly predicted, which are comparable to the best results of other methods. Of the 18 novel allergen proteins non-homologous to any other proteins in the Swissprot database, 88.9% is correctly predicted. A further screening of 168,128 proteins in the Swissprot database finds that 2.9% of the proteins are predicted as allergen proteins, which is consistent with the estimated numbers from motif-based methods.

CONCLUSIONS

Our study suggests that SVM is a potentially useful method for predicting allergen proteins and it has certain capability for predicting novel allergen proteins. Our software can be accessed at .

The Value of Short Amino Acid Sequence Matches for Prediction of Protein Allergenicity

Typically, genetically engineered crops contain traits encoded by one or a few newly expressed proteins. The allergenicity assessment of newly expressed proteins is an important component in the safety evaluation of genetically engineered plants. One aspect of this assessment involves sequence searches that compare the amino acid sequence of the protein to all known allergens. Analyses are performed to determine the potential for immunologically based cross-reactivity where IgE directed against a known allergen could bind to the protein and elicit a clinical reaction in sensitized individuals. Bioinformatic searches are designed to detect global sequence similarity and short contiguous amino acid sequence identity. It has been suggested that potential allergen cross-reactivity may be predicted by identifying matches as short as six to eight contiguous amino acids between the protein of interest and a known allergen. A series of analyses were performed, and match probabilities were calculated for different size peptides to determine if there was a scientifically justified search window size that identified allergen sequence characteristics. Four probability modeling methods were tested: (1) a mock protein and a mock allergen database, (2) a mock protein and genuine allergen database, (3) a genuine allergen and genuine protein database, and (4) a genuine allergen and genuine protein database combined with a correction for repeating peptides. These analyses indicated that searches for short amino acid sequence matches of eight amino acids or fewer to identify proteins as potential cross-reactive allergens is a product of chance and adds little value to allergy assessments for newly expressed proteins.

Arabitol dehydrogenase as a selectable marker for rice

Arabitol dehydrogenase has been adapted for use as a plant selectable marker. Arabitol is a five-carbon sugar alcohol that can be used by E. coli strain C, but not by the laboratory K12 strains. The enzyme converts the non-plant-metabolizable sugar arabitol into xylulose, which is metabolized by plant cells. Rice was transformed with a plant-expression-optimized synthetic gene using Biolistic-mediated transformation. Selection on 2.75% arabitol and 0.25% sucrose yielded a transformation efficiency (9.3%) equal to that obtained with hygromycin (9.2%). Molecular analyses showed that the atlD gene was integrated into the rice genome of selected plants and was inherited in a Mendelian manner. This study indicates that arabitol could serve as an effective means of plant selection.

Analysis of the composition of an immunoglobulin E reactive high molecular weight protein complex of peanut extract containing Ara h 1 and Ara h 3/4

Peanuts (Arachis hypogaea) contain some of the most potent food allergens. In recent years an increasing prevalence of peanut allergies both in children and adults has been observed in the USA and in Europe. In vitro identification and characterization of allergens including those from peanut have been frequently performed by Western blotting. However this method may alter the immunoglobulin E (IgE) antibody reactivity since the proteins are denatured by detergent treatment and/or reduction of disulfide bonds by reducing reagents and does not answer the question how peanut allergens interact with the human digestive apparatus and immune system. Size exclusion chromatography of peanut extract shows that approximately 90% of the total protein content is eluted as one peak in the exclusion volume with a molecular mass of over 200 kDa. The proteins of this fraction were analyzed by blue-native polyacrylamide gel electrophoresis (PAGE), immunoblotting, two-dimensional PAGE and Western blotting. A complex of Ara h 1 (Acc. no. P43237), Ara h 3/4 (AAM46958), Ara h 3 (AAC63045), Ara h 4 (AF086821), Gly 1 (AAG01363) and iso-Ara h 3 (AAT39430) was identified using patients' IgE and allergen-specific monoclonal antibodies; N-terminal sequencing and matrix-assisted laser desorption/ionisation-time of flight analysis verified these findings. A comparison of the peanut allergen sequences of Ara h 3/4, Ara h 3, Ara h 4 and peanut trypsin inhibitor (AF487543) and the proteins Gly 1 and iso-Ara h 3, not yet described as allergens, leads to the conclusion that these proteins are isoallergens of each other. It was shown that these isoallergens are post-translationally cleaved and held together by disulfide bonds in accordance to the 11S plant seed storage proteins signature.

Assessing Genetically Modified Crops to Minimize the Risk of Increased Food Allergy: A Review

The first genetically modified (GM) crops approved for food use (tomato and soybean) were evaluated for safety by the United States Food and Drug Administration prior to commercial production. Among other factors, those products and all additional GM crops that have been grown commercially have been evaluated for potential increases in allergenic properties using methods that are consistent with the current understanding of food allergens and knowledge regarding the prediction of allergenic activity. Although there have been refinements, the key aspects of the evaluation have not changed. The allergenic properties of the gene donor and the host (recipient) organisms are considered in determining the appropriate testing strategy. The amino acid sequence of the encoded protein is compared to all known allergens to determine whether the protein is a known allergen or is sufficiently similar to any known allergen to indicate an increased probability of allergic cross-reactivity. Stability of the protein in the presence of acid with the stomach protease pepsin is tested as a risk factor for food allergenicity. In vitro or in vivo human IgE binding are tested when appropriate, if the gene donor is an allergen or the sequence of the protein is similar to an allergen. Serum donors and skin test subjects are selected based on their proven allergic responses to the gene donor or to material containing the allergen that was matched in sequence. While some scientists and regulators have suggested using animal models, performing broadly targeted serum IgE testing or extensive pre- or post-market clinical tests, current evidence does not support these tests as being predictive or practical. Based on the evidence to date, the current assessment process has worked well to prevent the unintended introduction of allergens in commercial GM crops.

Bcipep: a database of B-cell epitopes

Background

Bcipep is a database of experimentally determined linear B-cell epitopes of varying immunogenicity collected from literature and other publicly available databases.

Results

The current version of Bcipep database contains 3031 entries that include 763 immunodominant, 1797 immunogenic and 471 null-immunogenic epitopes. It covers a wide range of pathogenic organisms like viruses, bacteria, protozoa, and fungi. The database provides a set of tools for the analysis and extraction of data that includes keyword search, peptide mapping and BLAST search. It also provides hyperlinks to various databases such as GenBank, PDB, SWISS-PROT and MHCBN.

Conclusion

A comprehensive database of B-cell epitopes called Bcipep has been developed that covers information on epitopes from a wide range of pathogens. The Bcipep will be source of information for investigators involved in peptide-based vaccine design, disease diagnosis and research in allergy. It should also be a promising data source for the development and evaluation of methods for prediction of B-cell epitopes. The database is available at .

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.

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.

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

Assessment of the safety of foods derived from genetically modified (GM) crops

This paper provides guidance on how to assess the safety of foods derived from genetically modified crops (GM crops); it summarises conclusions and recommendations of Working Group 1 of the ENTRANSFOOD project. The paper provides an approach for adapting the test strategy to the characteristics of the modified crop and the introduced trait, and assessing potential unintended effects from the genetic modification. The proposed approach to safety assessment starts with the comparison of the new GM crop with a traditional counterpart that is generally accepted as safe based on a history of human food use (the concept of substantial equivalence). This case-focused approach ensures that foods derived from GM crops that have passed this extensive test-regime are as safe and nutritious as currently consumed plant-derived foods. The approach is suitable for current and future GM crops with more complex modifications. First, the paper reviews test methods developed for the risk assessment of chemicals, including food additives and pesticides, discussing which of these methods are suitable for the assessment of recombinant proteins and whole foods. Second, the paper presents a systematic approach to combine test methods for the safety assessment of foods derived from a specific GM crop. Third, the paper provides an overview on developments in this area that may prove of use in the safety assessment of GM crops, and recommendations for research priorities. It is concluded that the combination of existing test methods provides a sound test-regime to assess the safety of GM crops. Advances in our understanding of molecular biology, biochemistry, and nutrition may in future allow further improvement of test methods that will over time render the safety assessment of foods even more effective and informative.

Allergic cross-reactivity: from gene to the clinic

A large number of allergenic proteins have now their complete cDNA sequences determined and in some cases also the 3D structures. It turned out that most allergens could be grouped into a small number of structural protein families, regardless of their biological source. Structural similarity among proteins from diverse sources is the molecular basis of allergic cross-reactivity. The clinical relevance of immunoglobulin E (IgE) cross-reactivity seems to be influenced by a number of factors including the immune response against the allergen, exposure and the allergen. As individuals are exposed to a variable number of allergenic sources bearing homologous molecules, the exact nature of the antigenic structure inducing the primary IgE immune response cannot be easily defined. In general, the 'cross-reactivity' term should be limited to defined clinical manifestations showing reactivity to a source without previous exposure. 'Co-recognition', including by definition 'cross-reactivity', could be used to describe the large majority of the IgE reactivity where co-exposure to a number of sources bearing homologous molecules do not allow unequivocal identification of the sensitizing molecule. The analysis of reactivity clusters in diagnosis allows the interpretation of the patient's reactivity profile as a result of the sensitization process, which often begins with exposure to a single allergenic molecule.

Statistical Evaluation of Local Alignment Features Predicting Allergenicity Using Supervised Classification Algorithms

BACKGROUND

Recently, two promising alignment-based features predicting food allergenicity using the k nearest neighbor (kNN) classifier were reported. These features are the alignment score and alignment length of the best local alignment obtained in a database of known allergen sequences.

METHODS

In the work reported here a much more comprehensive statistical evaluation of the potential of these features was performed, this time for the prediction of allergenicity in general. The evaluation consisted of the following four key components. (1) A new high quality database consisting of 318 carefully selected, non-redundant allergens and 1,007 sequences carefully selected to be non-allergens. (2) Three different supervised algorithms: the kNN classifier, the Bayesian linear Gaussian classifier, and the Bayesian quadratic Gaussian classifier. (3) A large set of local alignment procedures defined using the FASTA3 alignment program by means of a wide range of different parameter settings. (4) Novel performance curves, alternative to conventional receiver-operating characteristic curves, to display not only average behaviors but also statistical variations due to small data sets.

RESULTS

The linear Gaussian classifier proved most useful among the tested supervised machine learning algorithms, closely followed by the quadratic Gaussian equivalent and kNN. The overall best classification results were obtained with a novel feature vector consisting of the combined alignment scores derived from local alignment procedures using different substitution matrices.

CONCLUSIONS

The models reported here should be useful as a part of an integrated assessment scheme for potential protein allergenicity and for future comparisons with alternative bioinformatic approaches.

Presence of potential allergy-related linear epitopes in novel proteins from conventional crops and the implication for the safety assessment of these crops with respect to the current testing of genetically modified crops

Mitochondria of cytoplasmic male sterile crop plants contain novel, chimeric open reading frames. In addition, a number of crops carry endogenous double-stranded ribonucleic acid (dsRNA). In this study, the novel proteins encoded by these genetic components were screened for the presence of potential binding sites (epitopes) of allergy-associated IgE antibodies, as was previously done with transgenic proteins from genetically modified crops. The procedure entails the identification of stretches of at least six contiguous amino acids that are shared by novel proteins and known allergenic proteins. These stretches are further checked for potential linear IgE-binding epitopes. Of the 16 novel protein sequences screened in this study, nine contained stretches of six or seven amino acids that were also present in allergenic proteins. Four cases of similarity are of special interest, given the predicted antigenicity of the identical stretch within the allergenic and novel protein, the IgE-binding by a peptide containing an identical stretch reported in literature, or the multiple incidence of identical stretches of the same allergen within a novel protein. These selected stretches are present in novel proteins derived from oilseed rape and radish (ORF138), rice (dsRNA), and fava bean (dsRNA), and warrant further clinical testing. The frequency of positive outcomes and the sizes of the identical stretches were comparable to those previously found for transgenic proteins in genetically modified crops. It is discussed whether novel proteins from conventional crops should be subject to an assessment of potential allergenicity, a procedure which is currently mandatory for transgenic proteins from genetically modified crops.