Literature DB >> 16338955

The value of short amino acid sequence matches for prediction of protein allergenicity.

Andre Silvanovich1, Margaret A Nemeth, Ping Song, Rod Herman, Laura Tagliani, Gary A Bannon.   

Abstract

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.

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Year:  2005        PMID: 16338955     DOI: 10.1093/toxsci/kfj068

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  19 in total

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

Authors:  Wenzhe Lu; Surendra S Negi; Catherine H Schein; Soheila J Maleki; Barry K Hurlburt; Werner Braun
Journal:  Mol Immunol       Date:  2018-04-06       Impact factor: 4.407

Review 3.  Bioinformatics approaches to classifying allergens and predicting cross-reactivity.

Authors:  Catherine H Schein; Ovidiu Ivanciuc; Werner Braun
Journal:  Immunol Allergy Clin North Am       Date:  2007-02       Impact factor: 3.479

Review 4.  Allergen databases: current status and perspectives.

Authors:  Adriano Mari; Chiara Rasi; Paola Palazzo; Enrico Scala
Journal:  Curr Allergy Asthma Rep       Date:  2009-09       Impact factor: 4.806

5.  Guidelines for Sanger sequencing and molecular assay monitoring.

Authors:  Beate M Crossley; Jianfa Bai; Amy Glaser; Roger Maes; Elizabeth Porter; Mary Lea Killian; Travis Clement; Kathy Toohey-Kurth
Journal:  J Vet Diagn Invest       Date:  2020-02-18       Impact factor: 1.279

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

Authors:  Catherine H Schein; Ovidiu Ivanciuc; Terumi Midoro-Horiuti; Randall M Goldblum; Werner Braun
Journal:  Bioinform Biol Insights       Date:  2010-10-11

7.  wksl3, a New biocontrol agent for Salmonella enterica serovars enteritidis and typhimurium in foods: characterization, application, sequence analysis, and oral acute toxicity study.

Authors:  Hyun-Wol Kang; Jae-Won Kim; Tae-Sung Jung; Gun-Jo Woo
Journal:  Appl Environ Microbiol       Date:  2013-01-18       Impact factor: 4.792

Review 8.  Safety assessment of biotechnology products for potential risk of food allergy: implications of new research.

Authors:  MaryJane K Selgrade; Christal C Bowman; Gregory S Ladics; Laura Privalle; Susan A Laessig
Journal:  Toxicol Sci       Date:  2009-04-10       Impact factor: 4.849

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

Authors:  Joo Chuan Tong; Shen Jean Lim; Hon Cheng Muh; Fook Tim Chew; Martti T Tammi
Journal:  Bioinformatics       Date:  2009-02-11       Impact factor: 6.937

10.  Value of eight-amino-acid matches in predicting the allergenicity status of proteins: an empirical bioinformatic investigation.

Authors:  Rod A Herman; Ping Song; Arvind Thirumalaiswamysekhar
Journal:  Clin Mol Allergy       Date:  2009-10-29
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