Published March 2026
| Version v1
Dissertation
Synthetic Biology Approaches for Recording Diffusible Cell-Cell Communications
Description
Cells must exchange information via diffusible signals to sustain life. Such cell-cell communications are extracellular, transient, and disseminated by nature, making it incredibly challenging to track in any experimental system. Therefore, many fundamental questions about the structure and function of intercellular signaling cascades mediated by secreted factors remain unanswered. Here, we prototype intracellular sensors to record the release and receipt of cytokine signals, both at the protein (Chapter 2) and RNA (Chapter 3) levels. First, we establish nanobody-DNA writer fusions that become active upon target antigen recognition. We benchmark our sensors in vitro by recording the release and receipt of type I interferons in an inducible cell-cell circuit, which we construct in human lung epithelial cells. We find that sensor-based recordings closely recapitulate the patterns of interferon signaling between sender and receiver cells, as reported by time-lapse microscopy of fluorescent reporters. Next, we apply these tools in vitro and in vivo to capture the release and receipt of type II interferon between T lymphocytes and cancer cells in mouse models of solid and hematologic malignancies. To this end, we employ both retroviral delivery and engineered transgenic mice carrying integrated cytokine-sensing circuits, which enable stable, lineage-resolved recording of interferon-γ signaling events within T-cells. Using these complementary systems, we aim to define how the transcriptional and functional states of T cells and tumor cells evolve as a function of their history of intercellular interferon-γ signaling during tumor initiation, progression, therapeutic response, and relapse. Finally, we develop a new class of gRNAs that couple Cas13, Cas9, and Csy4 activity to enable programmable, transcript-responsive CRISPR editing. Together, these approaches open new avenues for systematic studies of how past intercellular communication shapes the present and future behavior of multicellular systems.
Additional details
Identifiers
- Other
- oai:uchicago.tind.io:16738