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We develop an automatic method for synaptic partner identification in insect brains and use it to predict synaptic partners in a whole-brain electron microscopy dataset of the fruit fly. The predictions can be used to infer a connectivity graph with high accuracy, thus allowing fast identification of neural pathways. To facilitate circuit reconstruction using our results, we develop CIRCUITMAP, a user interface add-on for the circuit annotation tool CATMAID. A deep-learning-based approach enables automatic identification of synaptically connected neurons in electron microscopy datasets of the fly brain.

Animal behavior is encoded in neuronal circuits in the brain. To elucidate the function of these circuits, it is necessary to identify, record from and manipulate networks of connected neurons. Here we present BAcTrace (Botulinum-Activated Tracer), a genetically encoded, retrograde, transsynaptic labeling system. BAcTrace is based on Clostridium botulinum neurotoxin A, Botox, which we engineered to travel retrogradely between neurons to activate an otherwise silent transcription factor. We validated BAcTrace at three neuronal connections in the Drosophila olfactory system. We show that BAcTrace-mediated labeling allows electrophysiological recording of connected neurons. Finally, in a challenging circuit with highly divergent connections, BAcTrace correctly identified 12 of 16 connections that were previously observed by electron microscopy. BAcTrace is a predominantly retrograde tracing tool for connectomic analyses in Drosophila.