Sunday, November 24, 2024
11/24/2024
ABSTRACT The brain is the most complex organ in the mammalian body. Bulk analysis obscures heterogeneity of cell types present even in the smallest brain regions. Multi-omics single-cell resolution 3D-characterization of brain tissue is critically important to create comprehensive brain cell censuses and altas. Recent technological advances allow for single-cell transcriptome mapping of mammalian brains, but single-cell proteomics technologies are lagging far behind transcriptomics technologies. The lack of high-resolution proteome characterization of brain tissues in the BICCN consortium represents a significant knowledge gap between protein and mRNA for achieving a more complete understanding of how diverse brain cells are organized into distinct anatomical and functional regions. The objective of this application is to address this gap by developing a robust scalable mass spectrometry (MS) platform for high-resolution 3D-proteome mapping of brain tissues. The feasibility is strongly supported by our recent progress in technology development and our experiences in proteome mapping of mouse tissues. Aim 1 will focus on the development of a robust scalable MS platform through 1) further improving sample preparation for rapid effective processing of single cells and small tissue voxels, and 2) leveraging multiple disruptive technologies developed at our group for significantly improving detection sensitivity and sample throughput. The new platform is expected to allow for reliable quantification of >3,000 proteins in single cells and >6500 proteins in 100 cells with ~500 samples per day. Aim 2 will optimize and demonstrate the scalable MS platform for 2D-proteome mapping of mouse MOp and human M1 when combined with laser capture microdissection for tissue voxels. Aim 3 will apply the new platform for 3D-proteome mapping of MOp/M1 within the BICCN consortium and integrate proteomic data with existing transcriptomic data for proteogenomic analysis. We envision that the new platform will become a convenient indispensable tool for high-resolution 3D-proteome mapping of brain tissues in the BICCN consortium and extend the BICCN toolbox. In turn, it could make substantial contributions to improve our understanding of brain function in health and disease.
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