Research

Comparison of two label-free global quantitation methods, APEX and 2D gel electrophoresis, applied to the Shigella dysenteriae proteome

Srilatha Kuntumalla¹ , John C Braisted¹ , Shih-Ting Huang¹ , Prashanth P Parmar¹ , David J Clark¹ , Hamid Alami¹ , Quanshun Zhang² , Arthur Donohue-Rolfe² , Saul Tzipori² , Robert D Fleischmann¹ , Scott N Peterson¹ and Rembert Pieper¹

¹  Pathogen Functional Genomics Resource Center, J Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA

²  Cummings School of Veterinary Medicine, Tufts University, 200 Westboro Road, North Grafton, MA 01536, USA

author email corresponding author email

Proteome Science 2009, 7:22doi:10.1186/1477-5956-7-22

Published:	29 June 2009

Abstract

The in vitro stationary phase proteome of the human pathogen Shigella dysenteriae serotype 1 (SD1) was quantitatively analyzed in Coomassie Blue G250 (CBB)-stained 2D gels. More than four hundred and fifty proteins, of which 271 were associated with distinct gel spots, were identified. In parallel, we employed 2D-LC-MS/MS followed by the label-free computationally modified spectral counting method APEX for absolute protein expression measurements. Of the 4502 genome-predicted SD1 proteins, 1148 proteins were identified with a false positive discovery rate of 5% and quantitated using 2D-LC-MS/MS and APEX. The dynamic range of the APEX method was approximately one order of magnitude higher than that of CBB-stained spot intensity quantitation. A squared Pearson correlation analysis revealed a reasonably good correlation (R² = 0.67) for protein quantities surveyed by both methods. The correlation was decreased for protein subsets with specific physicochemical properties, such as low M_r values and high hydropathy scores. Stoichiometric ratios of subunits of protein complexes characterized in E. coli were compared with APEX quantitative ratios of orthologous SD1 protein complexes. A high correlation was observed for subunits of soluble cellular protein complexes in several cases, demonstrating versatile applications of the APEX method in quantitative proteomics.