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United States Department of Agriculture

Agricultural Research Service

Title: High-Throughput Peptide Mass Fingerprinting of Soybean Seed Proteins: Automated Workflow and Utility of Unigene Expressed Sequence Tag Databases for Protein Identification

Authors
item Mooney, Brian - UNIVERSITY OF MISSOURI
item Krishnan, Hari
item Thelen, Jay - UNIVERSITY OF MISSOURI

Submitted to: Phytochemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 1, 2004
Publication Date: June 7, 2004
Citation: Mooney, B., Krishnan, H.B., Thelen, J.J. 2004. High-throughput peptide mass fingerprinting of soybean seed proteins: automated workflow and utility of unigene expressed sequence tag databases for protein identification. Phytochemistry. 65(12):1733-1744.

Interpretive Summary: Soybeans provide 70% of the world’s vegetable protein. The predominant storage proteins are represented by two groups of salt-soluble proteins, 7S and 11S globulins. Because of their abundance these proteins play an important role in determining the quality of soy proteins. In addition, soybean accumulates several other proteins which could influence the protein quality but their identity remains unknown mainly because of low abundance. Recent developments in protein analysis have enabled the identification and characterization of low abundant proteins. In this basic study, we have utilized two-dimensional (2-D) gel electrophoresis and peptide mass fingerprinting to identify these proteins in soybean seed. Utilizing these techniques we report the identification of several proteins from soybean seeds. Additionally, this technology will enable soybean researchers to identify proteins that are nutritionally superior. Increasing the accumulation of such proteins would benefit soybean farmers by providing them with a marketable value-added trait.

Technical Abstract: Identification of anonymous proteins from two-dimensional (2-D) gels by peptide mass fingerprinting is one area of proteomics that can greatly benefit from a simple, automated workflow to minimize sample contamination and facilitate high-throughput sample processing. In this investigation we outline a workflow employing robotic automation at each step subsequent to 2-D gel electrophoresis. As proof-of-concept, 96 protein spots from a 2-D gel were analyzed using this approach. Whole protein (1 mg) from mature, dry soybean (Glycine max [L.] Merr.) cv. Jefferson seed was resolved by high resolution 2-D gel electrophoresis. Approximately 150 proteins were observed after staining with Coomassie Blue. The rather low number of detected proteins was due to the fact that the dynamic range of protein expression was greater than 100-fold. The most abundant proteins were seed storage proteins which in total represented over 60% of soybean seed protein. Using peptide mass fingerprinting, 44 protein spots were identified. Identification of soybean proteins was greatly aided by the use of annotated, contiguous Expressed Sequence Tag (EST) databases which are available for public access (UniGene, ftp.ncbi.nih.gov/repository/UniGene/). Searches were orders of magnitude faster when compared to searches of unannotated EST databases and resulted in a higher frequency of valid, high-scoring matches. Some abundant, non seed storage proteins identified in this investigation include an isoelectric series of sucrose binding proteins, alcohol dehydrogenase and seed maturation proteins. This survey of anonymous seed proteins will serve as the basis for future comparative analysis of seed-filling in soybean as well as comparisons with other soybean varieties.

Last Modified: 10/25/2014
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