Literature DB >> 24953553

Evaluation of global sequence comparison and one-to-one FASTA local alignment in regulatory allergenicity assessment of transgenic proteins in food crops.

Ping Song1, Rod A Herman2, Siva Kumpatla2.   

Abstract

To address the high false positive rate using >35% identity over 80 amino acids in the regulatory assessment of transgenic proteins for potential allergenicity and the change of E-value with database size, the Needleman-Wunsch global sequence alignment and a one-to-one (1:1) local FASTA search (one protein in the target database at a time) using FASTA were evaluated by comparing proteins randomly selected from Arabidopsis, rice, corn, and soybean with known allergens in a peer-reviewed allergen database (http://www.allergenonline.org/). Compared with the approach of searching >35%/80aa+, the false positive rate measured by specificity rate for identification of true allergens was reduced by a 1:1 global sequence alignment with a cut-off threshold of ≧30% identity and a 1:1 FASTA local alignment with a cut-off E-value of ≦1.0E-09 while maintaining the same sensitivity. Hence, a 1:1 sequence comparison, especially using the FASTA local alignment tool with a biological relevant E-value of 1.0E-09 as a threshold, is recommended for the regulatory assessment of sequence identities between transgenic proteins in food crops and known allergens.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Allergen; Bioinformatics; Cross-reactivity; Protein; Transgenic

Mesh:

Substances:

Year:  2014        PMID: 24953553     DOI: 10.1016/j.fct.2014.06.008

Source DB:  PubMed          Journal:  Food Chem Toxicol        ISSN: 0278-6915            Impact factor:   6.023


  4 in total

1.  Bioinformatic screening and detection of allergen cross-reactive IgE-binding epitopes.

Authors:  Scott McClain
Journal:  Mol Nutr Food Res       Date:  2017-03-27       Impact factor: 5.914

2.  The COMPARE Database: A Public Resource for Allergen Identification, Adapted for Continuous Improvement.

Authors:  Ronald van Ree; Dexter Sapiter Ballerda; M Cecilia Berin; Laurent Beuf; Alexander Chang; Gabriele Gadermaier; Paul A Guevera; Karin Hoffmann-Sommergruber; Emir Islamovic; Liisa Koski; John Kough; Gregory S Ladics; Scott McClain; Kyle A McKillop; Shermaine Mitchell-Ryan; Clare A Narrod; Lucilia Pereira Mouriès; Syril Pettit; Lars K Poulsen; Andre Silvanovich; Ping Song; Suzanne S Teuber; Christal Bowman
Journal:  Front Allergy       Date:  2021-08-06

3.  1:1 FASTA update: Using the power of E-values in FASTA to detect potential allergen cross-reactivity.

Authors:  Ping Song; Rod Herman; Siva Kumpatla
Journal:  Toxicol Rep       Date:  2015-08-20

4.  Allergen false-detection using official bioinformatic algorithms.

Authors:  Rod A Herman; Ping Song
Journal:  GM Crops Food       Date:  2020-01-06       Impact factor: 3.074

  4 in total

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