Evaluating the Performance of New Approaches to Spot Quantification and Differential Expression in 2-Dimensional Gel Electrophoresis Studies

Abstract

Spot detection and quantification for 2-DE are challenging and important tasks to fully extract the proteomic information from these data. Traditional analytical methods have significant weaknesses, including spot mismatching and missing data, which require time-consuming manual editing to correct, dramatically decreasing throughput and compromising the objectivity and reproducibility of the analysis. To address this issue, we developed Pinnacle, a novel, quick, automatic, noncommercial method that borrows strength across gels in spot detection and has been shown to yield more precise spot quantifications than traditional methods. New commercial software, notably SameSpots, has also recently been developed as an improvement over traditional workflows. In this paper, we briefly describe Pinnacle and compare its performance to SameSpots in spot detection, spot quantification precision, and differential expression. Our analysis is performed in a rigorous fashion that, unlike other comparisons in the literature, summarizes performance across all spots detected on the gels, and we manually optimize SameSpots results while simply running Pinnacle with standard settings and no manual editing. While both methods showed marked improvement over a commercially available traditional method PG240, Pinnacle consistently yielded spot quantifications with greater validity and reliability, avoided spot delineation problems, and detected more differentially expressed proteins than SameSpots, and represents a significant noncommercial alternative for 2-DE processing.