iPS Proteomes in Health and Disease
Deep mining of proteomes, using mass spectrometry (MS) based proteomics technology, can provide invaluable insights, at a systems level, into both physiological responses in healthy cells and mechanisms causing disease phenotypes. This allows unbiased, global, quantitative measurements linking cellular phenotypes with changes in protein dynamics in both healthy and diseased cells. A major challenge that emerges from this ability to generate very large sets of proteomics and parallel ‘poly-omics’ data is how to manage, analyse and integrate the huge resulting volumes of complex information. I will describe our progress in a large-scale, poly-omics project where we have used quantitative proteomics to analyse many different human induced pluripotent stem cell lines (iPSCs), derived from both healthy donors and patient cohorts with inherited genetic disorders. This project highlights some of the technical and analytical challenges inherent in performing proteomic analyses at this scale. I will also describe user-friendly, computational tools we have built for the effective management and sharing of these large, multidimensional data sets (www.peptracker.com/epd). Our results show that disease causing mutations result in alterations in the proteomes of iPSC lines that reflect phenotypic defects observed in differentiated adult tissue in patients.
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