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Allergen false-detection using official bioinformatic algorithms
- Source :
- GM Crops & Food
- Publication Year :
- 2020
-
Abstract
- 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.
- Subjects :
- 0106 biological sciences
0301 basic medicine
cross-reactivity
Genetically modified crops
Biology
medicine.disease_cause
01 natural sciences
03 medical and health sciences
Allergen
medicine
Amino Acid Sequence
Plant Proteins
Dietary exposure
selectivity
Computational Biology
bioinformatics
Allergens
030104 developmental biology
exposure
False detection
Agronomy and Crop Science
Algorithm
Algorithms
010606 plant biology & botany
Food Science
Biotechnology
Research Paper
Subjects
Details
- ISSN :
- 21645701
- Volume :
- 11
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- GM cropsfood
- Accession number :
- edsair.doi.dedup.....156e5d53c8092c6bef768d177b1e750e