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Biology subjects

Call, C. C.

Publications and source records attributed to Call, C. C..

5 recordsLinked to original sources

Targeted cancer ablation via programmable sensing of amplified oncogenic RNA

Selectively eliminating cancer cells based on their oncogenic drivers holds great promise but remains challenging for targeted cancer therapy. Here, we present ORCA (Oncogenic RNA-triggered Cancer Ablation), a programmable and modular platform that couples RADAR-based detection of oncogenic RNA with conditional expression of therapeutic payloads in cancer cells. We identify RADAR sensors targeting the transcripts of endogenously amplified oncogenes, including MYC, FGFR2 and wild-type KRAS in colorectal and gastric cancer cells. Focusing on colorectal cancer (CRC) driven by extrachromosomal DNA-amplified MYC, we demonstrate targeted ablation of high-MYC cancer cells using two orthogonal strategies: anti-CD19 CAR-T therapy and enzyme-prodrug therapy. In vivo delivery of ORCA using adeno-associated virus (AAV) suppresses tumor growth in a subcutaneous xenograft model and prolongs survival in a CRC liver metastasis model. ORCA establishes oncogenic RNAs as actionable inputs for targeted cancer therapy via programmable RNA sensing, thus offering a strategy to target tumors through the transcripts of otherwise difficult-to-drug oncogenes such as MYC.

synthetic biology↗

An in planta single-cell screen to accelerate functional genetics

Genetic screens in whole plants are a powerful tool for functional genetics. However, elucidating gene function in highly redundant genetic programs such as signaling pathways remains challenging in both model and non-model plants. Here, we report a single-cell screening platform, PIVOT (Protoplast Isolation after Virus Overexpression in planTa), to accelerate identification and functional characterization of plant genes. We used Nicotiana benthamiana as a heterologous host to test gene libraries arrayed in a single leaf. Two elements of our system made pooled screens possible in planta: (1) we harnessed viral superinfection exclusion to ensure single multiplicity of infection per cell during pooled library delivery, and (2) we engineered a cell surface protein as a phenotypic marker for isolating cells of interest from a heterogeneous population. Using this system, we recovered known and new regulators of cytokinin signaling from an Arabidopsis open reading frame library. We anticipate PIVOT will be broadly applicable for high-throughput, single-cell functional genetic screening across the plant kingdom.

plant biology↗

Post-Transcriptional Modular Synthetic Receptors

Inspired by the power of transcriptional synthetic receptors and hoping to complement them to expand the toolbox for cell engineering, we establish LIDAR (Ligand-Induced Dimerization Activating RNA editing), a modular post-transcriptional synthetic receptor platform that harnesses RNA editing by ADAR. LIDAR is compatible with various receptor architectures in different cellular contexts, and enables the sensing of diverse ligands and the production of functional outputs. Furthermore, LIDAR can sense orthogonal signals in the same cell and produce synthetic spatial patterns, potentially enabling the programming of complex multicellular behaviors. Finally, LIDAR is compatible with compact encoding and can be delivered as synthetic mRNA. Thus, LIDAR expands the family of synthetic receptors, holding the promise to empower basic research and therapeutic applications.

synthetic biology↗

Compact Programmable Control of Protein Secretion in Mammalian Cells

Synthetic biology has developed powerful tools to program complex behaviors, often using genetic control. Protein circuits offer a compact alternative, yet applications with intercellular signals often lack key regulatory capabilities and tunability. Here, we employ a parts-based engineering strategy to develop a single processing and output module for synthetic protein circuits, enabling complex logic, tunable sensitivity, and control over output magnitude. Using high-throughput assays, we systematically analyze the impact of human transmembrane domains on surface expression and circuit performance. We demonstrate the utility of these optimizations by encoding an open-loop circuit within translational delivery vectors, including viral and mRNA platforms, and validate its performance in vivo. Furthermore, we demonstrate multi-input logic and showcase a novel, protein-level NIMPLY gate to regulate CAR T-cell activation. Our modular design strategy provides new insights into domain-based protein engineering and establishes a versatile and complete protein-level platform to control intercellular signaling for translational cell therapies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/560774v2_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@4f96f7org.highwire.dtl.DTLVardef@1404cf5org.highwire.dtl.DTLVardef@7c948corg.highwire.dtl.DTLVardef@fcad06_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

Modular and programmable RNA sensing using ADAR editing in living cells

With the increasing availability of single-cell transcriptomes, RNA signatures offer a promising basis for targeting living cells. Molecular RNA sensors would enable the study of and therapeutic interventions for specific cell types/stats in diverse contexts, particularly in human patients and non-model organisms. Here we describe a modular and programmable design for live RNA sensing using adenosine deaminases acting on RNA (RADAR). We validated and then expanded our basic design, characterized its performance, and thoroughly analyzed its compatibility with the human/mouse transcriptomes. We also identified strategies to further boost output levels and improve the dynamic range. We show that RADAR is programmable and modular, and uniquely enables compact AND logic. In addition to being quantitative, RADAR can distinguish disease-relevant point mutations. Finally, we demonstrate that RADAR is a self-contained system with the potential to function in diverse organisms.

bioengineering↗