Single Cells in Context: A Dyad View that Bridges Single-Cell and Spatial Biology

Single-cell sequencing has revolutionized cell atlases, but it is inherently context-poor: it catalogs cell states after dissociation, while many of the most important biological programs are relational: triggered by contact, proximity, or short-range signaling between specific partners. In this talk, I will present a dyad-centered framework and enabling technologies that treat cell??"cell interactions as a measurable layer between single-cell and spatial biology.

The central idea is simple: a cell’s induced transcriptomic change in response to a partner cell is itself a quantitative readout of the partner’s function. If one cell activates, suppresses, kills, rescues, or instructs another, the responder’s state encodes information about what the first cell did, often more directly than measuring the first cell’s basal transcriptome alone.

I will describe our Lab-on-a-Particle platform, which creates millions of standardized microscale assay environments compatible with conventional workflows and downstream sequencing. Using Nanovials, cavity-containing hydrogel microparticles with selectively functionalized interiors, we can capture secreted proteins and binding events while keeping cells viable??"enabling secretion-encoded functional screening followed by recovery for single-cell RNA-seq and targeted sequence identification. Building on this, I will introduce Cell-Cell-seq, which uses nanovials to co-compartmentalize defined cell pairs and couple dyad-specific functional measurements with transcriptomic profiling of a composite induced dyad-level transcriptome. By comparing paired interactions to matched single-cell controls, we can isolate interaction-induced programs, infer directionality, and map how heterogeneous immune and tumor populations engage. Together, these approaches provide a scalable route to connect function, interaction context, and molecular identity, offering a practical bridge from dissociated single-cell genomics toward the contextual logic needed for predictive multicellular biology and therapeutic discovery.

Speaker: Dino Di Carlo, UC Los Angeles