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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...

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Detalles Bibliográficos
Autores principales: Herman, Rod A., Song, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
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.
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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
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