A novel spatial biology platform for protein profiling which is cost effective and scalable

ABSTRACT Spatial biology platforms are revolutionizing the study of biology and are rapidly becoming indispensable for the understanding and treatment of cancer. However, the platforms on the market now, whether for proteomics profiling or transcriptomics analyses, are costly and are not scalable for widespread adoption. Current imaging- based approaches used for proteomics profiling provide exquisite detail but are slow and are limited in the number of protein targets that can be analyzed on a single tissue slide. Imageless systems allow simplified data acquisition via next generation sequencing (NGS) readouts but these platforms have difficulty achieving subcellular resolution. The goal of this application is to develop a scalable, low-cost, image-free spatial biology platform with sub-cellular resolution that is suitable for adoption into basic research and CLIA environments. The proposed project is based on proprietary barcoded tags that enable a unique isothermal workflow that allows information transfer to a spatially encoded array in a single hands-free step. The workflow is non-destructive to the tissue and requires no specialized instrumentation to produce digital “images” of protein presence and abundance at sub-cellular resolution. The goal of this proposal is to combine technologies licensed by RyboDyn, Inc. to create a novel platform that enables coordinate spatial and architectural analysis of cellular proteomic profiles for deployment into research as well as clinical labs. This proposal aims to: 1) Demonstrate a semi- ordered spatial capture array; 2) Demonstrate sub-cellular resolution of a 4-plex panel of DS-tag labeled antibodies. At the conclusion of this phase, we will have 1) Demonstrated a novel spatial capture array that is useful for the spatial encoding of information retrieved from bound antibody probes conjugated with RyboDyn’s proprietary tags, and 2) Demonstrated the isothermal spatial encoding workflow with decoding of the retrieved information by NGS, to enable digital display of protein profiles in biological samples.