The Utility of Genomic and Transcriptomic Data in the Construction of Proxy Protein Sequence Databases for...

Area of Science:

• Food science
• Allergen detection
• Genomics

Background:

• Rising incidence of tree nut allergies necessitates improved food analysis methods.
• Current mass spectrometry (MS) analyses for tree nuts are limited by scarce protein sequence data.
• Walnut (Juglans regia) serves as a model organism for developing new protein databases.

Purpose of the Study:

• To evaluate the utility of translated genomic and transcriptomic data for constructing protein databases for tree nut allergen identification.
• To improve the accuracy and comprehensiveness of protein databases for non-model organisms.
• To enhance mass spectrometry (MS) methods for detecting tree nuts in food.

Main Methods:

• Nano-liquid chromatography-mass spectrometry (n-LC-MS/MS) was used to analyze extracted walnut proteins.
• Mass spectrometry spectra were searched against databases derived from six-frame translation of the genome (6FT), transcriptome, and proteomes.
• RNA-Seq read processing methods were adjusted to optimize transcriptomic database performance.

Main Results:

• Proteomic databases identified 1156-1275 peptides; the 6FT database yielded only ten additional unique peptides.
• The transcriptomic database performed comparably to the NCBI proteome database (1200 vs. 1275 peptides).
• Optimized RNA-Seq processing improved the transcriptomic database, increasing identified seed allergen peptides by approximately 20%.

Conclusions:

• Translated genomic and transcriptomic data are valuable for creating proxy protein databases for tree nuts.
• Optimizing data processing enhances the identification of specific allergen proteins.
• This approach provides a pathway for developing robust databases for non-model organisms, aiding in allergy detection.