Apoptotic cell death signaling and diseases
Apoptosis (genetically programmed cell death) is a crucial cellular process that maintains the cellular balance between life and death. Our lab has established the role of intrinsic cell-to-cell stochastic variability in apoptosis signaling and related diseases: different types of cancer that are linked to apoptosis inhibition, and degenerative disorders that are caused by excessive apoptosis. A synergistic approach based on minimal model based theory, detailed computer simulations (Monte Carlo), and biological experiments has provided crucial mechanistic insight into some of the fundamental questions in biology of apoptosis and related diseases:
Experimental studies have shown that apoptotic cell death can occur either fast (~minutes) or very slow (~hours). Results from our Monte Carlo study showed apoptosis can switch from slow (~ hours) stochastic signaling through the intrinsic pathway to fast (~ minutes), deterministic signaling in the extrinsic pathway as the strength of an apoptotic stimulus increase.
Our systems level Monte Carlo study of neural cell apoptosis, combined with parallel cellular experiments, demonstrated that anti-apoptotic action of neuroglobin (a newly discovered protein) can explain the unusual resistance of neural cells to apoptosis, despite frequent apoptotic stress induced by calcium fluxes. Our study also elucidated how multi-molecular complex apoptosome formation can generate post-mitochondrial stochastic variability in apoptosis activation. This finding, a key result obtained from our Monte Carlo study, has been supported by independent experiments. Cell-to-cell stochastic variability in apoptotic activation (in neural cells) can provide important new insights into the fundamental biology of Alzheimer’s disease such as slow progressive death of neural cells over a long period of time.
Our recent work has impacted the field of cancer biology by elucidating the mechanisms of clonal origin (i.e. from a single cell) of a tumor and fractional killing of cancer cells. Our result has implications for the mechanisms of cancer stem cells (supposedly having higher tumerigenic potential). Current focus is on exploring the mechanism of apoptotic activation of cancer cells through low probability reaction of BH3 only proteins; such low probability reactions can generate large cell-to-cell stochastic variability in apoptosis resistance of cancer cells. The advantages of our approach: (i) its explicit simulation of spatial details, and (ii) it could elucidate the role of both cellular variations in protein levels and inherent stochastic fluctuations on cell-to-cell variability in apoptotic cell death.
1. Raychaudhuri, S., Willgohs, E., Nguyen T. N., Khan, E.M., Goldkorn, T (2008) Monte Carlo simulation of cell death signaling predicts large cell-to-cell stochastic fluctuations through the type 2 pathway of apoptosis. Biophysical Journal 95:3559-62.
2. Raychaudhuri, S., Skommer, J., Henty, K., Birch, N., and Brittain, T. (2010) Neuroglobin protects nerve cells from apoptosis by inhibiting the intrinsic pathway of cell death. Apoptosis 15:401-11.
3. Raychaudhuri, S. (2010) Minimal model of a signaling network elucidates cell-to-cell stochastic variability in apoptosis. PLoS One 5:e11930.
4. Skommer, J., Brittain, T., Raychaudhuri, S. (2010) Bcl-2 inhibits apoptosis by increasing the time-to-death and intrinsic cell-to-cell variations in the mitochondrial pathway of cell death. Apoptosis 15:1223-1233.
5. Skommer, J., Das S., Nair A., Brittain T, Raychaudhuri S. (2011) Nonlinear regulation of commitment to apoptosis by simultaneous inhibition of Bcl-2 and XIAP in leukemia and lymphoma cells. Apoptosis 16:619-26.