Biological Systems We Study
Many biological measurements focus either on molecular detail without system context or on system-level behavior without resolving underlying molecular mechanisms. Our work aims to bridge these scales. Across viruses, brains, and cellular membranes, we develop measurement frameworks that reveal how molecular variation shapes collective biological behavior. In many cases, progress requires reconsidering what the appropriate measurement unit should be for a given biological problem. Our research therefore combines experimental platform development with analytical framework development to enable new ways of examining heterogeneous biological systems. Each flagship project addresses a conceptual limitation in existing measurement strategies and introduces new experimental and analytical approaches to overcome it.
Single Virus Genomics and Influenza Evolution
Viral evolution is shaped by heterogeneity among individual viral particles. However, most genomic measurements average across large viral populations, obscuring genome-level variation that drives evolutionary dynamics. We develop droplet-based single-virus genomic strategies that isolate and characterize individual viral genomes directly from samples without relying on virus culture. By integrating microfluidics, molecular barcoding, and high-throughput sequencing, we quantify genome composition and reassortment structure at single-particle resolution. This work treats the individual virus particle as the primary measurement unit for studying viral genomic diversity. These measurements allow us to link viral genome architecture to population-level evolutionary behavior, enabling quantitative models of influenza evolution grounded in experimentally resolved heterogeneity. More broadly, this work aims to improve our ability to monitor viral diversity and anticipate evolutionary dynamics relevant to pandemic surveillance and vaccine preparedness.
Spatial Omics for Systems-Level Brain Function
The brain is one of the most complex biological systems, where interactions among molecules, cells, and circuits give rise to behavior. Traditionally, brain research has been divided between molecular studies and circuit-level approaches such as electrophysiology, leaving a gap between molecular states and neural function. Our lab develops quantitative spatial omics frameworks that bridge this gap by measuring molecular organization across intact neural circuits. These measurements allow molecular states to be examined within their spatial and circuit-level context, enabling comparisons of molecular organization across brain regions and behavioral conditions.
A. Comparative Whole-Brain Spatial Omics
We generate molecular maps of entire brains to understand how circuit-level phenotypes and behavioral specialization arise from distributed gene-expression patterns. Using the honey bee as a model system, we compare whole-brain spatial transcriptomic maps between soldiers and foragers, two behavioral roles performed by genetically similar individuals. By analyzing how molecular networks reorganize across neural circuits, we investigate how large-scale gene-expression programs support distinct behavioral phenotypes. This approach treats the whole brain as a measurable molecular system, enabling quantitative comparison of spatial molecular organization across individuals and conditions. More broadly, this work aims to clarify how differences in molecular organization across brain circuits give rise to behavioral diversity.
B. Process Biology
A key insight from the honey bee work is that a substantial portion of brain molecular information resides outside the cell body: in axons, dendrites, and glial processes. These structures are structurally fragile and difficult to segment, making them poorly represented in conventional reference-based analyses. To address this challenge, we developed a computational method that separates cell-body-associated signals from spatial expression patterns that cannot be explained by existing reference datasets. These residual signals correspond to gene expression in neuronal and glial processes in brain, revealing a previously inaccessible layer of molecular organization. Using these approaches, we study how molecular programs differ between cell bodies and neural processes and how these spatially distinct states reorganize across different biological conditions. This work expands the measurable unit of brain biology beyond the soma and enables quantitative study of molecular regulation within intact neural circuits. This work expands the measurable components of brain molecular organization beyond the cell body.
Membrane Protein Signaling in Membrane Environments
Cell signaling occurs within a structured membrane environment that shapes molecular interactions and collective behavior. Yet signaling pathways are often modeled as isolated ligand–receptor interactions, neglecting the chemical composition and physical organization of the membrane. We develop controlled membrane systems that incorporate membrane proteins into defined lipid environments, allowing systematic investigation of how membrane composition and physical properties influence receptor behavior and signaling dynamics. By integrating experimental measurements with theoretical modeling, we aim to connect membrane-scale physical properties to emergent cellular signaling responses. These platforms allow ligand–receptor interactions to be studied within a controlled membrane context. Understanding these relationships may provide new insights into how membrane environments influence receptor pharmacology and drug response.
Chemical Biology Tools for Biomedicine
In addition to our flagship research themes, we develop chemical and measurement tools for biomedical applications. These efforts include diagnostic assay development, aptamer screening platforms, and molecular systems for targeted therapeutic delivery. These projects translate the measurement technologies and chemical biology tools developed in our lab into practical platforms for studying and detecting biomolecular processes.
