Friday 18th June 2010
Cambridge, UK: Syngene, a world-leading manufacturer of image analysis solutions, is pleased to announce that one of the USA’s foremost Medical Research Centers, the Albert Einstein College of Medicine in New York is using Dyversity, Syngene’s 2D gel imaging system, to assist in understanding the proteomic basis of human ageing.
Scientists in the Departments of Medicine and Molecular Genetics at the Albert Einstein College of Medicine are isolating proteins from the serum of Ashkenazi Jewish centenarians, their offspring and age-matched offspring controls. The proteins are extracted and then run on 1D gels stained with Coomassie blue and are also transferred onto Western blots, probed with different antibodies and then stained with Horse Radish Peroxidase. The 1D protein gels and Western blots produced are imaged and analysed using a Dyversity system, enabling researchers to detect specific proteins and establish if these are connected with a longer life.
Dr Cagdas Tazearslan, Research Associate at the Albert Einstein College of Medicine, commented: “We have been using the Dyversity since 2008 and we installed this system because we needed to accurately detect small amounts of proteins and also assess phosphorylation levels of different signal transduction molecules which may have an impact on the human aging process.”
Dr Tazearslan continued: “By using the Dyversity we have been able to rapidly generate reproducible image data to measure how different IGF1R gene variants found in centenarians differentially modulate phosphorylation levels of downstream kinases and transcription factors. By using Dyversity, we are able to avoid saturation problems experienced when using X-ray films, therefore we have more confidence in the band quantification. Because of this, not only our group, but also different labs within the college prefer to use the Dyversity system to produce images and quantify their bands.”
Paula Maia, Syngene’s Vice President of Sales stated: “We are delighted the Albert Einstein College of Medicine, which is well known for its top class research, is generating such exciting results using the Dyversity system. Their work leads the way for other scientists looking for an image analyzer to rapidly produce high integrity data with even small amounts of protein, and proves that assessing a Dyversity system for any proteomics project is a well-informed decision.”
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