An integrated microtechnology platform for spatially resolved mass spectrometry-based proteomics

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Project Summary The spatial organization of cells and molecules in biological tissues plays a critical role in pathophysiology. For example, spatial heterogeneity in the tumor microenvironment determines tumor initiation, metastasis, and drug response. Despite advances in spatial transcriptomics to map RNA in tissues, it is proteins, rather than RNA, that drive most cellular processes and determine disease state. As protein abundance cannot be inferred precisely from transcriptomic data, it is important to measure protein abundance and their spatial distribution to better predict pathophysiological phenomena, as well as to identify biomarkers and therapeutic targets. Previous work on spatial proteomics is based on antibody recognition, mass spectrometry imaging, or physical dissection of the tissue followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Antibody-based and mass spectrometry imaging approaches have low proteome coverage (<100 proteins). The only approach with deep coverage (>3000 proteins) is tissue dissection followed by LC-MS/MS. This method leverages the power of state-of-the-art LC-MS/MS to achieve in-depth quantification of thousands of proteins along with their post-translational modifications. However, this approach is limited by current dissection methods. Manual dissection has low throughput and poor spatial resolution. Laser capture microdissection (LCM) has high resolution, but the isolation of many pixels, required for tissue mapping, is tedious and suffers from sample loss. The goal of this project is to develop a high throughput and scalable technology to perform tissue microdissection that preserves tissue spatial information and couples directly to established LC-MS/MS workflow for deep and unbiased spatial mapping of the proteome. We will demonstrate our technology on tumor slices of cutaneous squamous cell carcinoma. Our approach integrates a novel tissue micro-dicing device (“µDicer”), a nanodroplet sample preparation platform (“nanoPOTS”) for LC-MS/MS analysis with single-cell sensitivity, and a microfluidic device (“µMapper”) to transfer the diced tissue pixels from the µDicer to the nanoPOTS array while preserving their spatial order. Our approach is innovative because no technology currently exists to perform tissue micro-dissection and their transfer to macroscopic wells in parallel for LC-MS/MS while preserving spatial information. The specific aims are to optimize the µDicer for dicing fixed tissue slices into 10-100 µm micro-tissue pixels, develop and validate the µMapper to transfer tissue pixels from the µDicer onto nanoPOTS chips, and develop a high throughput and integrated spatial proteomics workflow and apply it to map human tumor slices. The project is significant because it will accelerate mass spectrometry-based spatial proteomics, thereby advancing our understanding of the role of tissue heterogeneity in pathophysiology, such as the role of the tumor microenvironment on cancer progression, and will enable the identification of novel protein biomarkers and therapeutic targets to facilitate the early detection, diagnosis, and intervention of diseases.