Software-induced variance in two-dimensional gel electrophoresis image analysis.

Area of Science:

• Proteomics
• Biotechnology
• Analytical Chemistry

Background:

• Experimental variability is a known issue in two-dimensional gel electrophoresis (2-DE).
• Postexperimental quantitative analysis using 2-DE software packages is a less studied source of variability.
• Accurate protein quantification is crucial for reproducible proteomics research.

Purpose of the Study:

• To evaluate and compare the performance of two 2-DE analysis software programs: Phoretix 2D Expression v2004 and PDQuest 7.2.
• To determine the impact of different algorithms and image processing parameters on quantitative variance.
• To identify sources of software-induced variance in 2-DE quantitative proteomics.

Main Methods:

• Tested background subtraction and smoothing algorithms on single 2-DE gel images and authentic replicate gel sets (n=5).
• Evaluated variance induced by slight shifts in image boundaries ('cropping area').
• Quantified protein spots using both Expression and PDQuest software.

Main Results:

• Both software packages introduced variance in protein spot quantification, even with identical gel images.
• PDQuest exhibited approximately twice the variance (CV(mean) = 8%) compared to Expression (CV(mean) = 4%) due to image boundary shifts.
• Omitting background subtraction algorithms resulted in the least software-based variance.
• Software-induced variance contributed significantly to the total observed variance in replicate gels.

Conclusions:

• 2-DE gel analysis software is a significant source of variance in quantitative proteomics.
• The choice of software and specific algorithms, particularly background subtraction, can impact the reliability of results.
• Optimizing software parameters and potentially omitting certain algorithms may reduce variance in 2-DE-based quantitative proteomics.