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Open AccessFeature PaperArticle

Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations

1
Sage Bionetworks, Seattle, WA 98109, USA
2
Institute for Chemical and Bioengineering, ETH Zurich, Zurich 8093, Switzerland
3
Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
*
Author to whom correspondence should be addressed.
Processes 2018, 6(2), 9; https://doi.org/10.3390/pr6020009
Received: 21 December 2017 / Revised: 16 January 2018 / Accepted: 18 January 2018 / Published: 23 January 2018
(This article belongs to the Special Issue Biological Networks)
Studies performed at single-cell resolution have demonstrated the physiological significance of cell-to-cell variability. Various types of mathematical models and systems analyses of biological networks have further been used to gain a better understanding of the sources and regulatory mechanisms of such variability. In this work, we present a novel sensitivity analysis method, called molecular density function perturbation (MDFP), for the dynamical analysis of cellular heterogeneity. The proposed analysis is based on introducing perturbations to the density or distribution function of the cellular state variables at specific time points, and quantifying how such perturbations affect the state distribution at later time points. We applied the MDFP analysis to a model of a signal transduction pathway involving TRAIL (tumor necrosis factor-related apoptosis-inducing ligand)-induced apoptosis in HeLa cells. The MDFP analysis shows that caspase-8 activation regulates the timing of the switch-like increase of cPARP (cleaved poly(ADP-ribose) polymerase), an indicator of apoptosis. Meanwhile, the cell-to-cell variability in the commitment to apoptosis depends on mitochondrial outer membrane permeabilization (MOMP) and events following MOMP, including the release of Smac (second mitochondria-derived activator of caspases) and cytochrome c from mitochondria, the inhibition of XIAP (X-linked inhibitor of apoptosis) by Smac, and the formation of the apoptosome. View Full-Text
Keywords: mathematical modeling; biological networks; sensitivity analysis; programmed cell death; single cell dynamics; cell population mathematical modeling; biological networks; sensitivity analysis; programmed cell death; single cell dynamics; cell population
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Perumal, T.M.; Gunawan, R. Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations. Processes 2018, 6, 9.

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