Grantee Research Project Results
2011 Progress Report: Prediction of Allergenicity by Linear and Conformational Epitopes
EPA Grant Number: R834823Title: Prediction of Allergenicity by Linear and Conformational Epitopes
Investigators: Braun, Werner , Schein, Catherine H. , Ivanciuc, Ovidiu I
Institution: The University of Texas Medical Branch - Galveston
EPA Project Officer: Aja, Hayley
Project Period: September 15, 2010 through September 30, 2014
Project Period Covered by this Report: September 15, 2010 through September 14,2011
Project Amount: $425,000
RFA: Approaches to Assessing Potential Food Allergy from Genetically Engineered Plants (2009) RFA Text | Recipients Lists
Research Category: Human Health
Objective:
Recombinant genetic tools are increasingly used by the biotechnology industry to introduce novel proteins into crops for protection against pesticides, as plant-incorporated protectants (PIP) or to increase the nutritional value. Appropriate safeguards must be in place to insure that this will not introduce new proteins that are potentially allergenic in the plants. The goal of this project is to provide quantitative bioinformatics criteria to determine the potential allergenicity of transgenic proteins in food products and PIPs from allergen specific motifs.
Progress Summary:
(1) We maintained the Structural Database of Allergenic Proteins (SDAP) as a user-friendly webserver (SDAP, http://fermi.utmb.edu/SDAP/ Exit ) to the allergenic community, regularly updated the database for new detected allergens, and introduced new bioinformatics tools on the website. SDAP is heavily used by the allergenic community with approximately 1,500 unique users who submit more than 100,000 requests each month.
(2) We proposed a new Markup Language, AllerML, as a standard computer readable format in storing and exchanging allergen data between different databases, bioinformatics servers, and users. The information exchange between major allergen services, databases and users is currently hindered by the absence of a common standard language. Our proposal should enable a consortium of database providers to develop a standardized database as a basis for regulatory guidelines for novel plant products of the biotechnology industry. AllerML has been implemented for all entries in SDAP, thus providing a computer-readable access to our allergen database. The AllerML language may be extended with new tags to accommodate information from other allergen databases. Details for the AllerML tags have been published in a paper in the journal Regulatory Toxicology and Pharmacology.
(3) Several software updates were performed as a consequence of changes in external protein databases and bioinformatics servers. New classifications for allergenic proteins using InterPro and Superfamily categories were added to the SDAP entries. InterPro is an integrated database of predictive protein signatures used for the classification and automatic annotation of proteins and genomes. The protein annotation in Superfamily is based on a collection of hidden Markov models, which represent structural protein domains at the SCOP superfamily level. We also included a cleavage site prediction for all SDAP entries by linking all allergen sequences in SDAP with the PeptideCutter service offered by Expasy. The user can select from a comprehensive list of proteases, but the most relevant for allergen digestion are pepsin, trypsin and chymotrypsin.
The development of new linear and conformational motif search tools is progressing.
Our studies are important to provide a solid scientific foundation in the general discussion on the potential risk of genetically modified (GM) foods. The statistical results and the novel bioinformatics tools can help the agency to formulate more specific bioinformatics guidelines for companies that would like to bring new recombinant crops to the market place. Since food allergies can result in fatal reactions, the allergenic potential of genetically-engineered food products needs to be carefully assessed prior to their entry into the market. There is a vital need for faster and reliable methods to evaluate the potential allergenicity of proteins that have not previously been part of the food supply. Our novel approaches can reduce some uncertainty for those crops that may be potentially allergenic for some sensitive sub-population.
Future Activities:
(1) We will continue to update the SDAP database with novel allergens.
(2) We will test the validity of our motif search method with experimental data. Dr. Schein and her coworkers (Dr. Soheila Maleki, Ph.D., of the USDA, New Orleans, and Dr. Suzanne Teuber, M.D., of the UC-Davis) conduct experimental tests, separately funded by EPA grant RE-83406601-0, designed to identify common epitopes of peanut and tree nuts that could account for cross reactivity. These data will be used in validating the computational tools on finding allergenic specific motifs.
(3) We will apply our new 3-D search methods for new allergens with known conformational epitopes.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
| Other project views: | All 19 publications | 6 publications in selected types | All 6 journal articles |
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Ivanciuc O, Gendel SM, Power TD, Schein CH, Braun W. AllerML: markup language for allergens. Regulatory Toxicology and Pharmacology 2011;60(1):151-160. |
R834823 (2011) R834823 (2013) R834823 (Final) R834066 (Final) |
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Supplemental Keywords:
relational database, large scale 3-D modeling of proteins, WHO/EFSA recommendations for risk assessment of proteinsRelevant Websites:
(1) Home page of the Structural Database of Allergens (SDAP): http://fermi.utmb.edu/SDAP/ Exit
(2) Site to download publications from the laboratory of the PI:
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.