Publications

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18 Publications visible to you, out of a total of 18

Abstract (Expand)

Chemical reaction networks are ubiquitous in biology, and their dynamics is fundamentally stochastic. Here, we present the software library pSSAlib, which provides a complete and concise implementation of the most efficient partial-propensity methods for simulating exact stochastic chemical kinetics. pSSAlib can import models encoded in Systems Biology Markup Language, supports time delays in chemical reactions, and stochastic spatiotemporal reaction-diffusion systems. It also provides tools for statistical analysis of simulation results and supports multiple output formats. It has previously been used for studies of biochemical reaction pathways and to benchmark other stochastic simulation methods. Here, we describe pSSAlib in detail and apply it to a new model of the endocytic pathway in eukaryotic cells, leading to the discovery of a stochastic counterpart of the cut-out switch motif underlying early-to-late endosome conversion. pSSAlib is provided as a stand-alone command-line tool and as a developer API. We also provide a plug-in for the SBMLToolbox. The open-source code and pre-packaged installers are freely available from http://mosaic.mpi-cbg.de.

Authors: Oleksandr Ostrenko, Pietro Incardona, Rajesh Ramaswamy, Lutz Brusch, Ivo F. Sbalzarini

Date Published: 4th Dec 2017

Publication Type: Not specified

Abstract (Expand)

Bile, the central metabolic product of the liver, is transported by the bile canaliculi network. The impairment of bile flow in cholestatic liver diseases has urged a demand for insights into its regulation. Here, we developed a predictive 3D multi-scale model that simulates fluid dynamic properties successively from the subcellular to the tissue level. The model integrates the structure of the bile canalicular network in the mouse liver lobule, as determined by high-resolution confocal and serial block-face scanning electron microscopy, with measurements of bile transport by intravital microscopy. The combined experiment-theory approach revealed spatial heterogeneities of biliary geometry and hepatocyte transport activity. Based on this, our model predicts gradients of bile velocity and pressure in the liver lobule. Validation of the model predictions by pharmacological inhibition of Rho kinase demonstrated a requirement of canaliculi contractility for bile flow in vivo. Our model can be applied to functionally characterize liver diseases and quantitatively estimate biliary transport upon drug-induced liver injury.

Authors: K. Meyer, O. Ostrenko, G. Bourantas, H. Morales-Navarrete, N. Porat-Shliom, F. Segovia-Miranda, H. Nonaka, A. Ghaemi, J. M. Verbavatz, L. Brusch, I. Sbalzarini, Y. Kalaidzidis, R. Weigert, M. Zerial

Date Published: 18th Mar 2017

Publication Type: Not specified

Abstract (Expand)

Bile, the central metabolic product of the liver, is transported by the bile canaliculi network. The impairment of bile flow in cholestatic liver diseases has urged a demand for insights into its regulation. Here, we developed a predictive 3D multi-scale model that simulates fluid dynamic properties successively from the subcellular to the tissue level. The model integrates the structure of the bile canalicular network in the mouse liver lobule, as determined by high-resolution confocal and serial block-face scanning electron microscopy, with measurements of bile transport by intravital microscopy. The combined experiment-theory approach revealed spatial heterogeneities of biliary geometry and hepatocyte transport activity. Based on this, our model predicts gradients of bile velocity and pressure in the liver lobule. Validation of the model predictions by pharmacological inhibition of Rho kinase demonstrated a requirement of canaliculi contractility for bile flow in vivo. Our model can be applied to functionally characterize liver diseases and quantitatively estimate biliary transport upon drug-induced liver injury.

Authors: Kirstin Meyer, Oleksandr Ostrenko, Georgios Bourantas, Hernan Morales-Navarrete, Natalie Porat-Shliom, Fabian Segovia-Miranda, Hidenori Nonaka, Ali Ghaemi, Jean-Marc Verbavatz, Lutz Brusch, Ivo Sbalzarini, Yannis Kalaidzidis, Roberto Weigert, Marino Zerial

Date Published: 1st Mar 2017

Publication Type: Not specified

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