A Boolean Model of Neuronal Death upon Cell Cycle Re-entry
Class of 2018
Biography:
- Education
- Bloomfield Central School, Rochester, NY 2014
- The College of Wooster, BA in Neuroscience, 2018
- Professional experience
- experience with Python, C++
- data science internship, IBM Watson, 2017
- co-founder of createHER @ Wooster, an initiative to inspire women to lead
IS Thesis Abstract:
Despite efforts to understand the causes of neurodegeneration, nearly one in six of the world’s population still suffer from associated diseases. Recent work points to a common underlying path to neuronal death. It appears most of the damage is caused by abnormal cell cycle, which results in cell death in neurons. In order to test whether the molecular mechanisms linked to this process can explain neuronal cell death when the cell cycle block is weakened, we built a Boolean network model of growth signaling, cell cycle, and apoptosis. The non-neuronal version of this model undergoes normal cell cycle and does not respond to the types of damage experienced by neurons during neurodegenerative diseases. In contrast, the neuronal version of the model maintains a robust cell cycle block in the absence of these stressors. In their presence, the model mimics cell cycle re-entry and mitotic catastrophe due to dysregulation of neuronal Tau proteins and caspase-2 induced apoptosis. To our knowledge, this is the first neuronal specific model of cell cycle arrest and aberrant re-entry.
Figure 1. Molecules in cellular environments characteristic to neurodegenerative disease can send neurons into a cell cycle they cannot complete.