MAP-IT: Spatial Protein Interactome Mapping in Human Tissue Sections Using Photocatalytic Labeling

Background & Unmet Need

• Protein-protein interactions (PPIs) represent a promising class of potential drug targets
• However, PPIs are typically identified in settings (e.g., cells, lysate, or model organisms) which lack crucial features of human physiology, limiting biological and clinical relevance
• Identifying PPIs directly in patient tissue may uncover physiologically-relevant interactions, but developing such methods remains challenging
• Proximity labeling, in which a photocatalyst or enzyme at a protein of interest (POI) generates reactive intermediates which flag nearby protein interactors, is a potentially attractive strategy
• However, current applications of tissue-based proximity labeling, such as µMap-FFPE, are limited by large labeling radii and high false positive rates
• Unmet Need: Improved methods for PPI discovery in human tissue samples

Technology Overview

• The Technology: MAP-IT, an optimized photocatalytic proximity labeling method for direct PPI mapping in primary human tissue sections
• Photocatalyst-decorated secondary antibodies are paired with primary antibodies to target labeling of endogenous POIs in intact tissue samples
• Selective blue-light irradiation of subcellular locations or specific cell types can be used to facilitate spatial interrogation of protein interactions
• The inventors have further developed a customized microscope setup and neural network-powered spatial segmentation to automatically identify and irradiate regions of interest
• PoC Data: MAP-IT successfully profiled and spatially deconvoluted the interactome of CD45 for interactions in B vs. T cells in human tonsils
• Global tissue irradiation with MAP-IT was used to identify interactors of EGFR which are exclusive to colon cancer tissue but absent in healthy tissues

Technology Applications

• Identification of PPIs unique to certain tissue types, subcellular structures, mesoscale structures, or disease states for research use or target identification for novel therapeutics
• Identification of protein interaction pairs for development of bispecific antibodies and next-generation AND-gated biologics

Technology Advantages

• Enables direct target discovery in human samples with a disease state of interest
• Tight labeling radius enables identification of PPIs with low false positive and false negative rates
• Spatially-specific activation enables the identification of location or cell-type specific interactions
• Integration of neural networks for image-guided irradiation provides a high flexibility and scalability