Cells & Tissues

Quantitative spatial biology in intact tissues:

Cells do not function in isolation. Their molecular states are shaped by developmental history, local tissue environments, neighboring cells, and spatially organized regulatory programs. To understand how molecular regulation gives rise to cell identity and tissue function, we need to measure many molecular species simultaneously while preserving their native spatial context.

Our genome-imaging work revealed that 3D chromatin organization controls gene co-expression programs in single cells. To understand how these programs are deployed across tissues, cell types, tissue compartments, and developmental stages, we needed a way to measure hundreds of genes and proteins deep inside intact tissue with subcellular resolution. No existing method could do all of this, so we built one.

The technology - cycleHCR:

cycleHCR is a highly multiplexed, deep-tissue spatial transcriptomics and proteomics platform that combines iterative hybridization chain reaction (HCR) amplification with automated fluidics and high-resolution confocal imaging (Gandin & Kim et al., Science 2025).

Key engineering advances include:

Scale. Simultaneous imaging of hundreds of RNA + protein targets within the same tissue volume.

Depth. Imaging through more than 500 µm of intact tissue, approximately 20 times deeper than standard multiplexed FISH methods, while maintaining subcellular resolution and morphological detail.

Throughput. A 30-fold improvement in acquisition speed over prior HCR-based approaches, enabled by new probe chemistry and optimized imaging cycles.

Automation. A fully automated fluidics system that executes multi-day imaging experiments with minimal user intervention.

Instrument design and custom engineering:

cycleHCR runs on a custom-built imaging platform with automated fluidics, environmental control, and microscope-control software developed in our lab.

The platform integrates optical design, molecular chemistry, fluidics, automation, and computation. This ability to build complete measurement systems around specific biological questions is central to our lab's approach.

From molecular maps to cell states:

We are using cycleHCR to construct 3D cell-fate maps of early mouse embryos, decode spatial gene-expression programs in the adult brain, including the hippocampus and cortex, and characterize cell-type-specific molecular architectures across tissues and disease models.

By measuring RNA, proteins, and cellular structures in the same cells, we can move beyond assigning cell types toward understanding how molecular states and subcellular organization vary within and between cell populations.

Combined with genetic and chemical perturbations, functional measurements, and machine-learning-based analysis, these experiments allow us to ask how molecular regulation gives rise to cell identity, tissue organization, and biological function.

Connecting cells and tissues across scales:

Cells and tissues represent the largest scale of our quantitative imaging program.

Single-molecule imaging measures the dynamics of individual regulatory molecules. 3D ATAC-PALM reveals how these interactions are organized within the genome. cycleHCR reads out the resulting molecular states across cells in their native tissue context.

By connecting these measurements, we aim to understand how molecular behavior and genome organization propagate across scales to shape cell states, spatial organization, and tissue function.