Dr Adrian Moore (Riken): Mechanisms of dendrite arbor differentiation School of Psychology and Neuroscience seminar series

The School of Psychology and Neuroscience seminar series presents a talk by Dr Adrian Moore, titled “Mechanisms of Dendrite Arbor Differentiation,” on Tuesday 10 September 2024, 1pm to 2pm. The seminar will be held in The Old Library and will also be accessible online via Teams.

Abstract:
Nervous system activity depends on neurons differentiating into a wide diversity of neuron types, each with characteristic arbor morphology, connectivity, and functional properties. Disruption of these differentiation processes leads to neurodevelopmental disorders.

Our recent work has emphasized the role of microtubule nucleation in shaping the specialized microtubule networks that build dendrite arbors. To examine this, we optimized long-term imaging of Drosophila arbor differentiation in vivo and coupled it with computer vision-based image analyses. We associate individual subcellular events with resultant arbor pattern features and examine cytoskeletal regulator families associated with neurodevelopmental disorders for their roles.

Previously, we and others showed how transcription factors specify neuron subtypes and the consequent diversification of their stereotyped arbor patterns. However, how downstream effector networks are organized to decode these genetic instructions remains to be seen. Now, to address this, we have performed a systems-level analysis of how the neuron transcriptome is organized by class-specific transcription factor activity. We then manipulate this network and develop rapid machine-learning-based software to quantify thousands of arbor morphologies. In this way, we have identified an effector network organization based on bi-directional feedback between transcription factors and Calcium-binding proteins that control dendrite arbor morphogenesis.

Ultimately, human sequencing studies are uncovering an ever-growing number of predisposition loci contributing to neurodevelopmental disorders. By examining the relationship between predisposition loci and the arbor effector networks we describe, we aim to gain new insight into the etiology of these disorders.