Transformative Technology Development

A streamlined platform for phosphoproteome mapping of human tissues

The objective of this TTD application is to develop a convenient streamlined platform for enabling automated high-resolution 3D-phosphoproteome mapping of human tissues. In the UG3 phase, Aim 1 focuses on the development of a streamlined platform through 1) improving phospho-recovery by developing an improved CASP/online IMAC platform for automated processing and phospho-enrichment, and 2) leveraging multiple disruptive technologies with integration of a high-efficiency multi-emitter SPIN (mSPIN) source and BASIL-based sample multiplexing for significantly improving MS sensitivity by ~50-fold and sample throughput by >20-fold. The streamlined platform allows for precise quantification of ~1,000 phosphosites in single cells and ~7000 phosphosites in 10 cells with >1000 samples per day. Aim 2 will demonstrate the streamlined platform for enabling 2D-phosphoproteome mapping of mouse uterine tissues when combined with laser capture microdissection (LCM) and standard tube-based voxel collection. In the UH3 phase (Aim 3) they will further optimize the streamlined platform for automated robust phosphoproteomic analysis of LCM-dissected human tissue sections. Then, an easy- to-use visualization tool will be developed to generate 3D maps that can be quickly and easily accessible by the research community. With its antibody-free feature, the streamlined platform can be equally applicable to any types of tissues. The streamlined platform will become an indispensable tool for high-resolution 3D-phosphoproteome mapping of human tissues in the HuBMAP consortium and extend the HuBMAP toolbox for 3D-mapping of functional modifications. In turn, it will make substantial contributions to improve understanding of tissue biology and accelerate the movement toward precision medicine.

Fast Facts
Project title: A streamlined platform for phosphoproteome mapping of human tissues
PI:Tujin Shi
Co-Investigator:Huiping Liu, Northwestern University
Project Manager:Chia-Feng Tsai
Grant number:1UG3CA256967-01
Learn more: Visit the lab website.


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