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Syngene’s 2d Image Analysis Systems being used in Critical Research

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Syngene has announced that its Dyversity 2D image analyzer and Dymension 2D analysis software are being used at US biopharmaceutical company, the Burzynski Research Institute (BRI), to determine the molecular effects compounds have on brain tumors.

Researchers at BRI are using Dyversity and Dymension to analyze Coomassie blue stained 2D gels of proteins derived from glioblastoma cells. Dyversity is also being utilized to image chemiluminescent Western blots of these proteins labelled with ECL. The information generated is helping to determine what effects different compounds have on proteins associated with brainstem glioma; an aggressive type of brain tumor and could lead to the introduction of novel treatments for this life threatening disease.

Dr Sonali Patil, a Scientist at BRI explained: “In 2007, we decided to use a proteomics approach to see what affects the anti-cancer compounds we are developing have at the molecular level. We saw a Dyversity at another medical institute in Houston and were so impressed with all the features it had for the price that we knew we had to have one.”

Dr Patil continued, “Since then we have used our own Dyversity in conjunction with the Dymension 2D analysis software to quantify spots on 2D gels because the two integrate well and the software layout makes this complicated analysis easy. We are extremely happy with the way it presents data and have even identified a couple of protein spots which look promising. Additionally, the technical support we have had from Syngene has been exceptional and I thoroughly recommend Dyversity and Dymension for 2D work.”

Paula Maia, Syngene’s Product Specialist stated: “We are proud to know our Dyversity 2D image analyzer and Dymension software are making a contribution to such important cancer research. The promising 2D results the BRI are seeing from the system and software combination shows scientists that Dyversity and Dymension are the complete package for rapidly producing high integrity data in any proteomics project.”