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Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations
Version 1
: Received: 21 December 2017 / Approved: 22 December 2017 / Online: 22 December 2017 (01:48:00 CET)
A peer-reviewed article of this Preprint also exists.
Perumal, T.M.; Gunawan, R. Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations. Processes 2018, 6, 9. Perumal, T.M.; Gunawan, R. Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations. Processes 2018, 6, 9.
Abstract
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 signal transduction pathway involved in TRAIL (tumor necrosis factor-related apoptosis-inducing ligand)-induced apoptosis in HeLa cells. The MDFP analysis showed 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 depended 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 apoptosome.
Keywords
mathematical modeling; biological networks; sensitivity analysis; programmed cell death; single cell dynamics; cell population
Subject
Computer Science and Mathematics, Analysis
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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