BRAIN CONNECTS: Synaptic resolution whole-brain circuit mapping of molecularly defined cell types using a barcoded rabies virus

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ABSTRACT Single-cell transcriptomics has revolutionized our understanding of neuronal diversity and enabled high-throughput characterization of molecular cell types across brain areas and species. We and others have pioneered multi- modal technologies such as Patch-seq and spatial transcriptomics to link molecularly-defined cell types with their physiology, cytomorphology, and anatomical features, but we still lack high-throughput, cost-effective methods that can provide comprehensive synaptic resolution wiring diagrams of entire mammalian brains and integrate these connectomes with molecularly defined cell types. We propose to further develop and validate Rabies Barcode Interaction Detection followed by sequencing (RaBID-seq) to enable high-throughput, scalable, and cost-effective mapping of brain-wide synaptic-level con- nectivity and transcriptomic profiling of the mapped neurons. We have optimized rabies virus production and packaging to achieve barcoded libraries containing more than 1.7 million unique barcodes, two orders of mag- nitude higher compared to prior studies, enough to map the inputs to thousands of post-synaptic neurons in a single animal. However, this technology still faces several experimental and computational challenges to realize its full potential. In Aim 1, we will address three potential challenges that may arise when scaling RaBID-seq to study brain-wide, densely labeled circuits: stochasticity of initial infection and spread, toxicity, and the potential for polysynaptic events when many founder cells are labeled. In addition, we will develop a new variant of Ra- bies featuring an evolvable barcode that can disambiguate monosynaptic vs polysynaptic spread in the setting of dense labeling. In Aim 2, we will benchmark RaBID-seq connectomes against other gold standard techniques measuring connectivity using multipatch-seq and spatial transcriptomics. In Aim 3, we will develop new algorithms using graph neural networks to reconstruct monosynaptic connectomes from barcoded viral datasets, assess the robustness of these algorithms under different experimental parameters in silico, and test whether an evolvable barcode can improve monosynaptic circuit reconstruction. If successful, these studies will establish RaBID-seq as a scalable, cost-effective tool for brain-wide connectivity mapping that can integrate transcriptomic cell types with their synaptic-level wiring diagram at single-cell resolution. By reducing the problem of synaptic connectivity into a problem of barcode sequencing, our approach has the potential to dramatically increase throughput, decrease costs and provide a direct link to the transcriptome of each mapped cell. RaBID-seq will transform brain-wide circuit mapping into a routine experiment that can be performed in any lab with modest resources, making it possible to explore how circuits differ between treatment conditions, in disease states, between the sexes, and across the lifespan. We will also generate pilot data in both mice and human slice cultures to demonstrate the utility of this tool across species.