Title

Authors

Affiliation

¹Department of Computer and Information Sciences, Towson University, Towson, MD 21252, USA; ²USDA-ARS, Soybean Genomics and Improvement Laboratory, Beltsville, MD 20705, USA

Email

savi.natarajan@ars.usda.gov; *Corresponding authors

Article Type

Database

Date

Received August 28, 2014; Accepted August 31, 2014; Published September 30, 2014

Soybeans are an important legume crop that contain 2 major storage proteins, β-conglycinin and glycinin, which account about 70-80% of total seed proteins. These abundant proteins hinder the isolation and characterization of several low abundant proteins in soybean seeds. Several protein extraction methodologies were developed in our laboratory to decrease these abundant storage proteins in seed extracts and to also decrease the amount of ribulose-1, 5-bisphosphate carboxylase/oxygenase (RuBisCO), which is normally very abundant in leaf extracts. One of the extraction methodologies used 40% isopropanol and was more effective in depleting soybean storage proteins and enhancing low abundant seed proteins than similar methods using 10-80% isopropanol. Extractions performed with 40% isopropanol decreased the amount of storage proteins and revealed 107 low abundant proteins when using the combined approaches of two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and Mass Spectrometry (MS). The separation of proteins was achieved by iso-electric focusing (IEF) and 2D-PAGE. The proteins were analyzed with MS techniques to provide amino acid sequence. The proteins were identified by comparing their amino acid sequences with those in different databases including NCBI-non redundant, UniprotKB and MSDB databases. In this investigation, previously published results on low abundant soybean seed proteins were used to create an online database (SoyProLow) to provide a data repository that can be used as a reference to identify and characterize low abundance proteins. This database is freely accessible to individuals using similar techniques and can be for the subsequent genetic manipulation to produce value added soybean traits. An intuitive user interface based on dynamic HTML enables users to browse the network and the profiles of the low abundant proteins.

Availability

http://bioinformatics.towson.edu/Soybean_low_abundance_proteins_2D_Gel_DB/Gel1.aspx

Citation

Tavakolan  et al. Bioinformation 10(9): 599-601 (2014)
 

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.