Proven quantitative accuracy and objectivity for your 2D gel analysis
Independent research published in the Journal of Proteome Research has validated the workflow driven approach to 2D gel image analysis using Progenesis SameSpots. Researchers at Imperial College London's Institute of Biomedical Engineering compared three commercially available software packages for DIGE analysis and determined that based on matching accuracy Progenesis SameSpots performed best.
Quantitative accuracy for your proteomics analysis
Following up this publication we have produced data to demonstrate the quantiative performance of Progenesis SameSpots using spiked same-same experiments. 7 groups of 4 replicate gels were loaded with diluted quantities of a single sample of E.Coli (0.5μg, 7.5μg, 10μg, 15μg, 30μg, 40μg and 50μg) and post-stained with Sypro™ Ruby. We can measure the accuracy of Progenesis SameSpots in capturing the protein loading effect across the seven experiment groups and reproducing protein values over a 100-fold range. The results of fully automatic analysis are shown below.
Figure 1: Measuring linearity of dilution for a selected spot (R2 of 0.9986) within a single stain experiment1 analysed by Progenesis SameSpots v3.2. All analysis was fully automatic with no editing.
Figure 2: Measuring linearity of dilution based on correlation coefficients for ALL MATCHED SPOTS within a single stain experiment1 analysed by Progenesis SameSpots v3.2. All analysis was fully automatic with no editing.
Figure 3: Measuring within-data variation for a single stain experiment1 using Progenesis SameSpots v3.2. All analysis was fully automatic with no editing.
Figure 4: Measuring the performance of normalisation for a selected spot (CV of 0.018) within a single stain experiment1 analysed by Progenesis SameSpots v3.2. All analysis was fully automatic with no editing.
Figure 5: Demonstrating the independence of variance and mean for log normalised volumes from 2D gel analysis of a single stain experiment1 using Progenesis SameSpots v3.2. This independent relationship between variance and mean is essential for valid statistical analysis of proteomics data. Progenesis SameSpots uses these values for statistical analysis of a complete data set i.e. no missing values due to its unique analysis approach.
How can I be sure this applies to gels run in my own lab?
In a different experiment 6 samples were prepared containing different amounts of 3 spike proteins (BSA, conalbumin and GAPDH) and added into 2 samples of Pseudomonas, one mutant and one wild type. A pool was created from all six samples and loaded onto 3 DIGE gels2. These were analysed automatically using Progenesis SameSpots v3.2 and the results demonstrate that we can reliably and accurately detect the expected protein expression changes.
Figure 1: Progenesis SameSpots v3.2 correctly identified the expected protein expression changes within a spiked same-same DIGE experiment2 on a whole image view. All analysis was fully automatic with no editing and only spots with a significant anova p-value (<0.05) and high power (>0.8) were automatically displayed. Experiment was spiked with varying concentrations of (A) BSA (B) Conalbumin (C) GAPDH.
Figure 2: Progenesis Stats correctly displays the expected protein expression changes within a spiked same-same DIGE experiment2 using correlation analysis. All analysis was fully automatic with no editing. Experiment was spiked with varying concentrations of (A) BSA (B) Conalbumin (C) GAPDH.
Figure 3: Progenesis Stats correctly displays the expected protein expression changes within a spiked same-same DIGE experiment2 using expression profiles. All analysis was fully automatic with no editing. Experiment was spiked with varying concentrations of (A) BSA (B) Conalbumin (C) GAPDH.
The examples above help demonstrate that Progenesis SameSpots has been developed to reduce error in quantitation as well as making your analysis more objective so you can have confidence in your results from using our software with either single stain or DIGE images.
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1 Quantitative evaluation of proteins in one- and two-dimensional polyacrylamide gels using a fluorescent stain, Nishihara, J.C. , and Champion, K.M. Electrophoresis (2002) 23: 2203-2215
2 Images kindly provided by Dr. Kathryn Lilley, Facility Group Leader, Cambridge Centre for Proteomics, University of Cambridge
