Comparative evaluation of two two-dimensional gel electrophoresis image analysis software applications using synovial fluids from patients with joint disease.
The proteomic composition of synovial fluid (SF) may hold clues to understanding the molecular basis of arthritis. However, the highly viscous nature and proteomic complexity of SF present a challenge when analyzing results obtained by two-dimensional gel electrophoresis (2D-GE). Several software applications are available for analyzing 2D-GE images. Despite inherent strengths and weaknesses, no comparison between these applications has been reported using SF or any human fluid specimens. We evaluated two common software packages--PDQuest and Progenesis Workstation--for spot detection, matching, and quantitation of 2D-GE images of SF from four patients with arthritic disease. Initially, whole 2D-gel images were analyzed for spot detection, which suggested that PDQuest is more consistent than Progenesis; however, PDQuest appeared to require more user intervention than Progenesis. Subsequently, two small areas (spots well resolved and spots not well resolved) were selected from each gel image, which were analyzed by the software for spot detection, matching, volume, and resolution. These analyses suggest that both tools can quantify well-resolved spots relatively consistently when compared with manual spot detection (the "gold standard"). The "3D viewer" option offered by both tools enables correct spot identification and matching. The strengths and weaknesses of these computer tools can provide guidance in the choice of a particular workstation for identifying biomarkers of arthritis.
Arora
Pankaj S
PS
Department of Orthopedic Research, 3-93 Medical Science Building, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Yamagiwa
Hiroshi
H
Srivastava
Alok
A
Bolander
Mark E
ME
Sarkar
Gobinda
G
D000328:Adult; D001168:Arthritis / Q000378:metabolism*; D015415:Biomarkers / Q000032:analysis; D015180:Electrophoresis, Gel, Two-Dimensional; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D012984:Software; D013582:Synovial Fluid / Q000737:chemistry*
D015415:Biomarkers