International Journal of Agricultural Sciences

ISSN 2167-0447

International Journal of Agricultural Sciences ISSN 2167-0447 Vol. 10 (3), pp. 001-009, March, 2020. © International Scholars Journals

Full Length Research Paper

Proteomics-based identification of storage, metabolic, and allergenic proteins in wheat seed from 2-DE gels

Liming Yang1, Dagang Tian2, Yuming Luo1*, Ruiyue Zhang1, Chongmiao Ren1 and Xin Zhou1

1School of Life Sciences, Huaiyin Normal University, Jiangsu Key Laboratory for Eco-Agricultural Biotechnology around Hongze Lake, Huai’an 223300, Jiangsu, China.

2Biotechnology Institute, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China.

Accepted 21 January, 2020

Abstract

Proteomic approach combining two -dimensional gel electrophoresis (2-DE), mass spectrometry and bioinformatics analysis were applied to identify major proteins in extracts of mature wheat seeds. About 920 or 700 protein spots were detected on 2-DE gels by silver staining or colloidal Coomassie Brilliant Blue staining. Eighty spots with higher abundance were selected to cut for in-gel digestion followed by matrix-assisted laser desorption/ionization-mass spectrometry-peptide map fingerprint analysis and electrospray ionization mass spectrometry-peptide sequence tags analysis. Database searches using measured peptide masses or peptide sequence tags querying wheat expressed sequence tags determined protein identities of 73 spots. These identified proteins were categorized into six classes according to the functional annotation including those with unknown functions and difficult to classify. Proteins involved in storage proteins, metabolism, defense, chaperones and allergy were the major categories. The present identification of proteins in major spots from 2-D gels includes 11 different proteins from 29 spots from wheat seed extract. It is suggested that post-translational processing or isoforms causes the same proteins to occur in different spots. In addition, we also discussed the efficiency of protein identification using species-specific EST databases.

Key words: Wheat seed, proteome profile, protein identification, expressed sequence tags, allergens, storage proteins.