Powerful New Life-Science Research and Translational Research Workflow
Product News Jun 08, 2017
Bruker’s novel Proteoform Profiling™ 1.0 solution enables a powerful new life-science research and translational research workflow, i.e. the systematic, large-scale, label-free study of all expressed proteoforms, including protein mutations, splice variants, post-translational modifications, as well as protein processing or degradation products. Detailed proteoform characterization is of tremendous importance in cell biology and in clinical proteomics research, where traditional bottom-up proteomics analysis of digested proteins scrambles key biological information. While the human genome only has about 25-30,000 coding sequences, or ‘genes’, for transcription and translation into protein families, the human body may have up to 1 billion different proteoforms expressed.
Bruker’s new nanoElute® nano-flow UHPLC system, together with the new Proteoform Profiling™ 1.0 solution, aims to bring enhanced ease-of-use to nano-spray mass spectrometry, which is essential for label-free discovery workflows on intact protein mixtures.
Professor Leonard Foster at the Department of Biochemistry & Molecular Biology of the University of British Columbia in Vancouver, Canada, stated: “LC-MS experts and biologists alike require trouble-free operation and ease-of-use, along with top performance. Our experience has shown that the nanoElute system readily meets those high demands.”
Both innovations take advantage of the superior performance of Bruker’s impact II and ETD-enabled maXis II UHR-QTOFs, which deliver accurate and reproducible proteoform profiles from complex intact, undigested protein mixtures. Unlike common Top-Down approaches, these UHR-QTOFs deliver information from proteoform mixtures with a reduced level of pre-fractionation, enabling the analysis of large sample sets from clinically relevant cohorts, or for longitudinal studies. The Proteoform Profiling 1.0 workflow automates the use of Bruker’s proprietary Dissect™ and SNAP™ algorithms, together with advanced molecular filtering functions, to generate a non-redundant list of monoisotopic masses, intensities and retention time from the isotopically resolved proteins.