Generation and Performance of a DNA Barcode-Based Nuclear Receptor Reporter Library 2267335

Abstract Introduction Nuclear receptors (NRs) are a large and distinctive class of ligand-regulated transcription factors that enable cellular sensing of hormone and metabolite gradients within and between tissues. They play essential roles in the regulation of immune cell development, function, and inflammation, making them among the most durable and efficacious drug targets for human diseases. However, roughly one-third of the 48 human NRs remain classified as ‘orphan’ receptors with no currently known physiological ligands. Conventional transcriptional reporter assays, though foundational in NR ligand discovery, are tedious, transient, and singleplex (one NR at a time), inherently favoring hypothesis- over discovery-driven research. Methods We develop a DNA barcode-based NR library that features 52 bi-component lentiviral vectors, including reporters for all 48 human NRs plus the Aryl hydrocarbon receptor (AhR), as well as one positive and two negative control constructs. Each reporter construct uses a dual anti-sense configuration to: (i) stably express one NR LBD-GAL4 fusion protein plus a barcoded mCherry reporter; and (ii) inducibly express a separately barcoded GAL4-responsive GFP reporter. Hence, NR activities can be quantified by either GFP/mCherry fluorescence ratios (singleplex; flow cytometry) or GFP/mCherry-linked barcode abundance ratios (multiplex; RNA-seq). Results We show that this barcode-based lentiviral reporter system performs similarly to a prior commercial multiplex NR reporter assay (trans-FACTORIAL; Attagene), but leverages workflows that are faster, more durable, more cost-effective, and more technically accessible. Conclusion We report the development and performance of a novel, stable, versatile, and multiplexable NR reporter library readable by either flow cytometry (singleplex) or RNA-seq (multiplex). Democratization of this multiplex reporter platform will support the expansion of NR ligand and drug discovery research. Funding Source n/a Topic Categories Technological Innovations in Immunology (TECH)