Reverse-engineering mechanisms of neural circuit wiring in the fly visual system

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Project Summary A central question in neuroscience is how neural circuits self-organize during development into functional structures. Neural circuit function relies on the precise specification of synapses, while alterations of synaptic connectivity are associated with numerous neurodevelopmental disorders. Seminal studies have identified mutations and molecular mechanisms that alter brain wiring. Yet, how this genetic information ultimately leads to self-assembly of neural circuits is poorly understood. What developmental programs lead to functional neuronal structures? What rules describe these programs? How do cells implement these rules? The Drosophila visual system represents a remarkable instance of the circuit self-assembly problem in the developing brain. The compound eye (consisting of ~800 ommatidia) is wired through a principle of “neural superposition” (NSP): 800 times six photoreceptors that see the same point in space, yet originate from six different ommatidia, find each other in the lamina and ‘wire together’ in synaptic cartridges. The correct sorting of photoreceptor growth cones results in a six-fold increase in light-gathering sensitivity without loss of spatial resolution. However, it is poorly understood how 4800 elongating growth cones stop at target cartridges with an astonishing accuracy of greater than 99%. In preliminary studies, we established the ability to use non-invasive, live-imaging based on multi-photon microscopy of intact and normally developing pupae to assay photoreceptor growth cone dynamics during NSP. Using this approach, we obtained the first quantitative measurements of individual growth cone dynamics throughout the entire NSP process and established that the complex program of NSP could arise from three simple local rules, which govern how growth cones anchor, elongate and stop in the lamina. Our work suggested the hypothesis that a cellular decision to stop wiring could arise from collective interactions with neighboring cells, and that these interactions could buffer biological variation, such as imperfect direction of growth cone elongation. To investigate collective stop decisions during NSP, we will: (Aim 1) experimentally determine potential times and places where growth cone fronts, backs and target cells could physically interact; (Aim 2) use these data to constrain computational models that systematically compare different models of stop rules; and (Aim 3) experimentally search for signatures of error propagation of NSP wiring in mutant conditions and identify molecular components that participate in the implementing the stop rule. 1