Section A technology capable of generating robust protein data across various biological states, with the sensitivity and coverage available to next-generation sequencing, would drastically change our understanding of cellular proteomes and ability to detect rare proteins in limited samples. Mass spectrometry is a powerful tool for proteomics. However, it suffers from limited sensitivity (>10{6} molecules required) preventing the identification of low-abundance proteins and single-cell proteomics. A high-throughput single-molecule protein identification method remains a key technical challenge for the proteomic community. Addressing this challenge will dramatically improve the ability to discover and assay novel biomarkers, with transformative impact in our understanding of cancer, immunology and brain research. We propose a robust high-throughput strategy for single-molecule protein identification. This approach will be based on our recent technological breakthrough on developing the highly multiplexed (10-plex; Nature Methods 2014), precisely quantitative (>90% precision and accuracy; Nature Methods 2016), and ultra-high resolution (sub-5 nm; Nature Nanotechnology 2016) DNA-PAINT super-resolution imaging method. Using DNA-PAINT to image a DNA-barcoded and stretched protein will provide a unique optical signature for accurate identification of any proteins in a complex mixture. This method will enable parallel identification of proteins with single-molecule sensitivity, resulting in broadly transformative impacts on fundamental and translational biomedical studies. To address the unmet testing need for the current COVID-19 pandemic, we will also work to develop a rapid diagnostics device.
Section High-throughput single-molecule protein identification approaches would enable single-cell proteomics, and benefit the development of new and robust biomarker panels, which would improve the early detection of the onset of infection, cancer, and neurodegeneration. We propose to solve this challenge by leveraging methods from the fields of superresolution imaging and DNA nanotechnology. Our project will enable proteomic studies to match the high sensitivity of next-generation sequencing.
