Identification of orphan ligand-receptor relationships using a cell-based CRISPRa enrichment screening platform
Abstract
Secreted proteins, which include cytokines, hormones and growth factors, are extracellular ligands that control key signaling pathways mediating cell-cell communication within and between tissues and organs. Many drugs target secreted ligands and their cell-surface receptors. Still, there are hundreds of secreted human proteins that either have no identified receptors ('orphans') and are likely to act through cell surface receptors that have not yet been characterized. Discovery of secreted ligand-receptor interactions by high-throughput screening has been problematic, because the most commonly used high-throughput methods for protein-protein interaction (PPI) screening do not work well for extracellular interactions. Cell-based screening is a promising technology for definition of new ligand-receptor interactions, because multimerized ligands can enrich for cells expressing low affinity cell-surface receptors, and such methods do not require purification of receptor extracellular domains. Here, we present a proteo-genomic cell-based CRISPR activation (CRISPRa) enrichment screening platform employing customized pooled cell surface receptor sgRNA libraries in combination with a magnetic bead selection-based enrichment workflow for rapid, parallel ligand-receptor deorphanization. We curated 80 potentially high value orphan secreted proteins and ultimately screened 20 secreted ligands against two cell sgRNA libraries with targeted expression of all single-pass (TM1) or multi-pass (TM2+) receptors by CRISPRa. We identified previously unknown interactions in 12 of these screens, and validated several of them using surface plasmon resonance and/or cell binding. The newly deorphanized ligands include three receptor tyrosine phosphatase (RPTP) ligands and a chemokine like protein that binds to killer cell inhibitory receptors (KIR's). These new interactions provide a resource for future investigations of interactions between the human secreted and membrane proteomes.
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All data generated or analyzed during this study are included in the manuscript and supporting files.
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Funding
Howard Hughes Medical Institute
- Kenan Christopher Garcia
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Siepe et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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