Spatial Biology Redefined: How Cleary’s Team Is Rethinking Cellular Communication
In living tissues, cells are constantly shaped by their surroundings. They respond to nearby signals, alter their own behavior, and influence the fate of neighboring cells, creating patterns that drive both health and disease. Yet for a long time, scientists had to choose between two imperfect options: they could isolate cells to study their inner workings, or observe tissues as a whole and lose the details of individual interactions. Techniques like CRISPR screening allowed researchers to map genetic changes inside cells, but only by breaking apart the natural structures that connect them. As a result, much of how genetic activity spreads through real cellular environments remained invisible. In a recent study published in Cell, Boston University Assistant Professor Brian Cleary and his collaborators introduced Perturb-FISH, a method that captures genetic changes within and between cells while preserving the spatial architecture of living systems.
Cleary and his collaborators developed Perturb-FISH by integrating CRISPR-based genetic screening with high-resolution spatial transcriptomics. The method marks a technical and conceptual shift: rather than isolating cells from their environments, it allows scientists to study gene expression and cell-to-cell effects within intact tissue. Each cell is tagged with a unique RNA guide that records its genetic perturbation, and these are read out alongside spatial maps of gene activity, giving researchers a multidimensional view of how cells respond, —both individually and as part of a living system. In contrast to earlier tools that revealed only the internal consequences of a mutation, Perturb-FISH uncovers how a single genetic edit can ripple across nearby cells, shaping overall tissue behavior. “One could use that to study cancer,” Cleary said. “One could use that to study healthy or abnormal development, or sort of any number of other diseases. But our focus isn’t on any of those. This is a core foundational technology that was missing.” One early demonstration focused on autism-linked genes, showing how certain mutations altered calcium signaling within neurons. By enabling researchers to ask spatially aware genetic questions across diverse systems, Perturb-FISH establishes a flexible platform that can serve a wide range of biomedical and developmental research efforts.
Cleary’s development of Perturb-FISH reflects a larger ambition that defines his lab: to understand how living systems build complexity from local interactions. His group focuses on the underlying architecture of biology, examining how cells coordinate within tissues, how interactions scale across space, and how disruptions unfold in development and disease. “We’re interested in biological organization,” he says, “particularly at the scale of single cells and small multicellular environments, like an ecosystem of cells in a tissue.” Many of their projects begin not with data collection, but with conceptual models and ideas about how complexity might emerge. Those ideas are then translated into experimental designs that anticipate the computational methods required to analyze them. The lab moves fluidly across wet-lab biology, statistical modeling, and theory, treating empirical and computational work as parts of a single process. “We organically integrate data science perspectives throughout the entire process of approaching a question,” Cleary explains.
In his view, biology’s complexity is not a barrier to scientific understanding, but the reason a more integrated approach is necessary.
Cleary’s interest in biological organization also shapes the future direction of his research. Beyond experimental tools like Perturb-FISH, he is developing theoretical models that challenge the gene as the central object of evolutionary study. “A gene, on its own, produces no interesting phenotype,” he explains. “It only has meaning in the context of the collective activity happening around it.” His group aims to build a framework for understanding how natural selection acts not on individual genes, but on networks of coordinated biological activity. This work proposes that the most meaningful units of organization in living systems are not isolated genetic elements, but the dynamic, interdependent processes they create. It’s a shift that redefines how we think about inheritance and evolution, and one that Cleary’s team is methodically translating into a usable scientific framework.
- Neeza Singh, (CDS'25) Research Communications Intern