Allergen false-detection using official bioinformatic algorithms.

GM Crops & Food Pub Date : 2020-04-02 Epub Date: 2020-01-06 DOI:10.1080/21645698.2019.1709021
Rod A Herman, Ping Song
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引用次数: 5

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.

使用官方生物信息学算法检测过敏原。
生物信息学氨基酸序列搜索在一定程度上用于评估转基因作物中新表达的蛋白质的潜在致敏风险。先前的工作已经证明,政府监管机构要求的搜索错误地将许多来自很少致敏作物的蛋白质暗示为具有致敏风险。然而,在农作物中发现的许多蛋白质的浓度可能不足以引起过敏。在这里,我们使用了一组最近开发的高丰度非过敏性蛋白来确定监管机构要求的几种算法的假阳性率,以及先前发现的与官方滑动窗口方法同样敏感的替代1:1 FASTA方法,但选择性更强。目前的调查证实了这些早期的发现,同时解决了饮食暴露问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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