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Updated: Dec 31, 2025

Application of Biochip Microfluidic Technology to Detect Serum Allergen-specific Immunoglobulin E sIgE

Application of Biochip Microfluidic Technology to Detect Serum Allergen-specific Immunoglobulin E sIgE

Published on: April 21, 2019

Allergen false-detection using official bioinformatic algorithms.

Rod A Herman¹, Ping Song¹

¹Regulatory and Stewardship, Corteva Agriscience, Indianapolis, IN, USA.

GM Crops & Food

|January 8, 2020

Summary

This summary is machine-generated.

Bioinformatic searches for allergenic risk in genetically engineered crops often yield false positives. This study confirms a more selective FASTA approach, improving accuracy in assessing potential food allergies from novel proteins.

Keywords:

Allergen bioinformatics cross-reactivity exposure selectivity

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Removal and Replacement of Endogenous Ligands from Lipid-Bound Proteins and Allergens

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Published on: February 24, 2021

Area of Science:

Agricultural biotechnology
Food safety
Computational biology

Background:

Bioinformatic amino acid sequence searches are crucial for assessing allergenic risk in genetically engineered (GE) crops.
Current regulatory methods often produce false positives, implicating proteins from low-allergenicity crops.
Protein concentration, not just sequence homology, is critical for allergenic potential.

Purpose of the Study:

To evaluate the false-positive rates of regulatory bioinformatic algorithms for allergenic risk assessment.
To compare the selectivity of regulatory methods with an alternative 1:1 FASTA approach.
To address dietary exposure considerations in the context of allergenic risk assessment.

Main Methods:

Utilized a set of high-abundance, non-allergenic proteins from crops.
Determined false-positive rates for several government-required bioinformatic search algorithms.
Assessed the performance of a 1:1 FASTA search method, known for its sensitivity and selectivity.

Main Results:

The study confirmed that regulatory algorithms generate a high rate of false positives for allergenic risk.
The alternative 1:1 FASTA approach demonstrated superior selectivity compared to official methods.
Earlier findings on method sensitivity and selectivity were corroborated.

Conclusions:

The 1:1 FASTA approach offers a more accurate and selective method for allergenic risk assessment in GE crops.
Refining bioinformatic tools is essential to avoid unnecessary restrictions on novel crop development.
Considering dietary exposure alongside sequence analysis enhances the reliability of allergenicity evaluations.