11 research outputs found
On chaotic dynamics in transcription factors and the associated effects in differential gene regulation
It is becoming clear that the dynamics of transcription factors may be important for gene regulation. Here, the authors study the implications of oscillatory and chaotic dynamics of NF-κB and demonstrate that it allows a degree of control of gene expression and can generate phenotypic heterogeneity
Spatiotemporal model of cellular mechanotransduction via Rho and YAP
How cells sense and respond to mechanical stimuli remains an open question.
Recent advances have identified the translocation of Yes-associated protein
(YAP) between nucleus and cytoplasm as a central mechanism for sensing
mechanical forces and regulating mechanotransduction. We formulate a
spatiotemporal model of the mechanotransduction signalling pathway that
includes coupling of YAP with the cell force-generation machinery through the
Rho family of GTPases. Considering the active and inactive forms of a single
Rho protein (GTP/GDP-bound) and of YAP (non-phosphorylated/phosphorylated), we
study the cross-talk between cell polarization due to active Rho and YAP
activation through its nuclear localization.
For fixed mechanical stimuli, our model predicts stationary
nuclear-to-cytoplasmic YAP ratios consistent with experimental data at varying
adhesive cell area. We further predict damped and even sustained oscillations
in the YAP nuclear-to-cytoplasmic ratio by accounting for recently reported
positive and negative YAP-Rho feedback. Extending the framework to time-varying
mechanical stimuli that simulate cyclic stretching and compression, we show
that the YAP nuclear-to-cytoplasmic ratio's time dependence follows that of the
cyclic mechanical stimulus. The model presents one of the first frameworks for
understanding spatiotemporal YAP mechanotransduction, providing several
predictions of possible YAP localization dynamics, and suggesting new
directions for experimental and theoretical studies
Chaotic Dynamics Mediate Brain State Transitions, Driven by Changes in Extracellular Ion Concentrations
Inferring Leading Interactions in the p53/Mdm2/Mdmx Circuit through Live-Cell Imaging and Modeling
Biophysical Modeling of Dopaminergic Denervation Landscapes in the Striatum Reveals New Therapeutic Strategy
Parkinson’s disease (PD) results from a loss of dopaminergic neurons. What triggers the break-down of neuronal signaling, and how this might be compensated, is not understood. The age of onset, progression and symptoms vary between patients, and our understanding of the clinical variability remains incomplete. In this study, we investigate this, by characterizing the dopaminergic landscape in healthy and denervated striatum, using biophysical modeling. Based on currently proposed mechanisms, we model three distinct denervation patterns, and show how this affect the dopaminergic network. Depending on the denervation pattern, we show how local and global differences arise in the activity of striatal neurons. Finally, we use the mathematical formalism to suggest a cellular strategy for maintaining normal dopamine (DA) signaling following neuronal denervation. This strategy is characterized by dual enhancement of both the release and uptake capacity of DA in the remaining neurons. Overall, our results derive a new conceptual framework for the impaired dopaminergic signaling related to PD and offers testable predictions for future research directions