Thesis Defense: Mike Leone | August 28, 2025 | 9am
CPCB and CBD are proud to announce the following thesis defense:
Title: Computational Selection, Design, and Parallel Screening of Enhancers for Targeted Control of Dorsal Spinal Neurons
Mike Leone
Thursday, August 28th @ 9am, ESTConnan Room, Cohon University Center
Committee:
Andreas Pfenning, Chair, CMUDavid R. Koes, Pitt
Martin Zhang, CMU
Rebecca Seal, Center for Neuroscience, Pitt
Abstract:
A central goal of neuroscience is the precise control of neural circuits. A leading strategy to achieve targeted control is to use cis-regulatory enhancers to drive transgene expression in specific cell types. Such enhancer tools can refine our understanding of somatosensensory processing in the spinal cord, and may enable a new class of targeted gene therapies for intractable chronic pain.
In this dissertation, I first establish a harmonized, cross-species taxonomy of dorsal spinal cord neurons, via single-nucleus transcriptomic analysis (rhesus macaque, human, mouse, rat, and pig) and chromatin accessibility analysis (macaque, mouse). I demonstrate the applicability of this conserved taxonomy by investigating the impact of chronic pain genetics on specific neuron subtypes, by investigating the cellular mechanisms of opioid tolerance, and by contributing to the investigation of the effects of spinal cord stimulation on sympathetic regulation following ischemia.
Next, I develop machine learning models to prioritize enhancers most likely to drive cell-type-specific expression of target neuron subtypes, identifying enhancers that, when paired with chemogenetic receptors, drive differential behavioral effects in mice. To achieve further cell-type-specificity, I develop in vivo machine-guided enhancer design.
Finally, I provide a computational strategy to accelerate the screening of enhancer specificity from multiplexed, in situ spatial transcriptomics. My strategy combines accurate, automated cell labeling followed by a regression approach that adjusts for sources of spatial confounding, providing new insight into screening biases such as viral tropism and injection variability, and ultimately enabling the direct comparison between enhancer candidates in the same experiment.
In summary, I provide a broad set of computational tools for identifying species-conserved dorsal spinal neurons, prioritizing and designing enhancer candidates to target these neurons, and evaluating their specificity in parallel.