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Allergen false-detection using official bioinformatic algorithms
Bioinformatic amino acid sequence searches are used, in part, to assess the potential allergenic risk of newly expressed proteins in genetically engineered crops. Previous work has demonstrated that the searches required by government regulatory agencies falsely implicate many proteins from rarely a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289518/ https://www.ncbi.nlm.nih.gov/pubmed/31906791 http://dx.doi.org/10.1080/21645698.2019.1709021 |
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author | Herman, Rod A. Song, Ping |
author_facet | Herman, Rod A. Song, Ping |
author_sort | Herman, Rod A. |
collection | PubMed |
description | Bioinformatic amino acid sequence searches are used, in part, to assess the potential allergenic risk of newly expressed proteins in genetically engineered crops. Previous work has demonstrated that the searches required by government regulatory agencies falsely implicate many proteins from rarely allergenic crops as an allergenic risk. However, many proteins are found in crops at concentrations that may be insufficient to cause allergy. Here we used a recently developed set of high-abundance non-allergenic proteins to determine the false-positive rates for several algorithms required by regulatory bodies, and also for an alternative 1:1 FASTA approach previously found to be equally sensitive to the official sliding-window method, but far more selective. The current investigation confirms these earlier findings while addressing dietary exposure. |
format | Online Article Text |
id | pubmed-7289518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-72895182021-01-06 Allergen false-detection using official bioinformatic algorithms Herman, Rod A. Song, Ping GM Crops Food Research Paper Bioinformatic amino acid sequence searches are used, in part, to assess the potential allergenic risk of newly expressed proteins in genetically engineered crops. Previous work has demonstrated that the searches required by government regulatory agencies falsely implicate many proteins from rarely allergenic crops as an allergenic risk. However, many proteins are found in crops at concentrations that may be insufficient to cause allergy. Here we used a recently developed set of high-abundance non-allergenic proteins to determine the false-positive rates for several algorithms required by regulatory bodies, and also for an alternative 1:1 FASTA approach previously found to be equally sensitive to the official sliding-window method, but far more selective. The current investigation confirms these earlier findings while addressing dietary exposure. Taylor & Francis 2020-01-06 /pmc/articles/PMC7289518/ /pubmed/31906791 http://dx.doi.org/10.1080/21645698.2019.1709021 Text en © 2020 The Author(s). Published with license by Taylor & Francis Group, LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
spellingShingle | Research Paper Herman, Rod A. Song, Ping Allergen false-detection using official bioinformatic algorithms |
title | Allergen false-detection using official bioinformatic algorithms |
title_full | Allergen false-detection using official bioinformatic algorithms |
title_fullStr | Allergen false-detection using official bioinformatic algorithms |
title_full_unstemmed | Allergen false-detection using official bioinformatic algorithms |
title_short | Allergen false-detection using official bioinformatic algorithms |
title_sort | allergen false-detection using official bioinformatic algorithms |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289518/ https://www.ncbi.nlm.nih.gov/pubmed/31906791 http://dx.doi.org/10.1080/21645698.2019.1709021 |
work_keys_str_mv | AT hermanroda allergenfalsedetectionusingofficialbioinformaticalgorithms AT songping allergenfalsedetectionusingofficialbioinformaticalgorithms |