Robust ultra-high sensitivity proteomic technologies for limited samples - PROJECT SUMMARY The majority of highly diverse biological processes are enabled through proteins, protein post-translational modifications (e.g., glycosylation), proteoforms, protein interactions, as well as other biological molecules (e.g., lipids, RNAs, etc.). Aberrations of abundance, activity, function, integrity, and localization of these biological molecules and their diverse interactions can lead to severe diseases. Furthermore, disruption of molecular profiles and structural characteristics by novel targeted therapies can be an important biomarker for the response to these drugs in personalized medicine approaches. Clinical and biological specimens are often available in limited amounts, which greatly hampers the progress in diagnostics, therapy development, and biomedical research. Microbiopsy and liquid biopsies may contain small populations of rare cells, macromolecular complexes, or other biomolecular structures and species. Traditional analytical techniques cannot be readily used for the analysis of small cell populations, microscopic clinical samples, and individual cells, mainly due to limitations in sensitivity. Therefore, many biological and clinically relevant studies have not been undertaken because of the lack of technology for such low-level samples. Here, we propose to develop analytical platforms that will enable high sensitivity spatial multiomic analysis of scarce biomedical samples. This task will demand the development of novel approaches in sample preparation, ultra-low flow liquid phase separations interfaced with MS, MS data acquisition, and data analysis. Developing such novel methods for thorough profiling of microscale samples and integrating them in innovative, robust, and reproducible automated platforms capable of efficient and high sensitivity quantitative and structural characterization of released glycans, peptides, intact proteoforms, protein complexes, and PTMs by MS will be highly desirable for gaining biological insights into molecular mechanisms of the disease and discovery of therapeutic targets and biomarkers for diagnostic and prognostic purposes. The developed platforms will be evaluated using well-controlled model systems and applied in the most clinically relevant settings to examine model line-based systems and primary samples.
