A neuron’s function depends critically on the shape, size, and territory of its dendritic field. We have only recently begun to understand how diverse dendritic arbors are built and how the morphology and territory of these arbors support diverse neural functions. In this thesis, I use the Drosophila larval peripheral nervous system (PNS) as a model for studying these questions, as these neurons are very amenable to genetic manipulation and in vivo imaging.
First, I examined the relationship between dendritic fields and sensory activity in the proprioceptive neurons of the body wall. In collaboration with Elizabeth Hillman’s lab, we used a high-speed volumetric microscopy technique, Swept Confocally Aligned Planar Excitation (SCAPE) microscopy, to simultaneously image the dendrite deformation dynamics and sensory activity of body wall neurons in crawling Drosophila larvae. We imaged a set of proprioceptive neurons with diverse dendrite morphologies and territories, revealing that each neuron subtype responds in sequence during crawling. These activities could conceivably provide a continuum of position encoding during locomotion. Activity timing is related to the dynamics of each neuron’s dendritic arbors, suggesting arbor shape and targeting endow each proprioceptor with a specific role in monitoring body wall deformation. Furthermore, our results provide new insights into the body-wide activity dynamics of the proprioceptive system, which will inform models of sensory feedback during locomotion.
To investigate how dendritic arbors are built to support sensory function, I focused on proprioceptive (class I) and touch-sensing (class II-III) dendritic arborization (da) neurons. Proprioceptive and touch-sensing dendrite territories tend to target non-overlapping, neighboring, areas of the body wall. How is territory coverage specified during development, and how does this coverage support a specific sensory function? Ablation studies indicate that repulsive interactions between heterotypic dendrites are not required for territory patterning. Instead, dendrite boundaries correlate with Anterior (A)-Posterior (P) compartment boundaries in the underlying epidermal substrate: proprioceptive class I dendrites target the P compartment, while touch-sensing dendrites tend to avoid that region. I found that genetic expansion of the P compartment leads to expansion of class I proprioceptive dendrites, suggesting compartmentalized epidermal cues instruct dendrite targeting. Furthermore, SCAPE imaging revealed that the P compartment coincides with a major body wall fold that occurs during crawling. These results support a model in which dendrite targeting by compartment cues reliably tunes neurons for predictable stimuli on the body wall: proprioceptive dendrites target areas that bend predictably during crawling, while touch-sensing dendrites could be avoiding those areas to be tuned for external mechanosensory stimuli.
To investigate the molecular identity of the substrate cues guiding the compartmental organization of dendrites, I tested candidate cues and sought new potential cues. I first tested cues that are known to be expressed in a compartmental fashion (Hedgehog and EGFR pathways). Interestingly, the overall dendrite territory footprint of class I proprioceptive cells is unaffected by known compartment cues. To reveal new candidates, I performed cell sorting and RNA sequencing. I identified 290 cell surface and secreted molecules with differential expression in the A and P compartments. I provide initial findings from a knockdown and misexpression screen testing the role of these candidates for class I and class III territory patterning. Taken together, these results provide new insights into how dendritic fields are patterned to support proper neural function.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-9f48-0354 |
| Date | January 2020 |
| Creators | Vaadia, Rebecca Danielle |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
Page generated in 0.0022 seconds