Single-cell Cyclic Multiplex in Situ Tagging to Advance Kidney Research

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Since the kidney is composed of many functionally unique cell types, there is a dire need for tools to investigate the disease mechanisms and identify targets for clinical treatment at the single cell level. Recent sequencing-based transcriptomic technologies have revolutionized kidney research by their capability of thorough classification of cell subtypes and their varied gene expression. However, genome-wide protein information that bridges the gap between gene expression and clinical diagnosis has been lacking particularly at the single-cell resolution. Functional proteins (hundreds as known so far) have been well known for representing phenotypes, physiological activities, drug targets, signaling pathways and regulations for cells. The current functional proteome tools either only analyze dozens of proteins in single cells or lack spatial context. In this project, we will develop a single-cell spatial multiplex in situ tagging (MIST) technology and apply it to kidney biopsy samples for functional proteome studies. Our prior studies show the cyclic MIST technology measures >450 proteins for T cells and ~200 proteins for other tissue samples. With the unprecedented high multiplexity, this technology will be further developed to be applied to kidney diseases by measuring hundreds of functional proteins that include almost all known biomarkers, important signaling proteins and transcription factors after thorough validation and optimization. The completion of this project will generate an enabling technology and method widely accessible in the kidney research community to investigate kidney diseases from a new, clinically relevant perspective. This technology will lay the foundation for future mechanistic studies driving kidney disease pathogenesis and identification of potential therapeutic targets.