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3 Publications visible to you, out of a total of 3
FitMultiCell: simulating and parameterizing computational models of multi-scale and multi-cellular processes.

Abstract (Expand)

MOTIVATION: Biological tissues are dynamic and highly organized. Multi-scale models are helpful tools to analyse and understand the processes determining tissue dynamics. These models usually depend … on parameters that need to be inferred from experimental data to achieve a quantitative understanding, to predict the response to perturbations, and to evaluate competing hypotheses. However, even advanced inference approaches such as approximate Bayesian computation (ABC) are difficult to apply due to the computational complexity of the simulation of multi-scale models. Thus, there is a need for a scalable pipeline for modeling, simulating, and parameterizing multi-scale models of multi-cellular processes. RESULTS: Here, we present FitMultiCell, a computationally efficient and user-friendly open-source pipeline that can handle the full workflow of modeling, simulating, and parameterizing for multi-scale models of multi-cellular processes. The pipeline is modular and integrates the modeling and simulation tool Morpheus and the statistical inference tool pyABC. The easy integration of high-performance infrastructure allows to scale to computationally expensive problems. The introduction of a novel standard for the formulation of parameter inference problems for multi-scale models additionally ensures reproducibility and reusability. By applying the pipeline to multiple biological problems, we demonstrate its broad applicability, which will benefit in particular image-based systems biology. AVAILABILITY AND IMPLEMENTATION: FitMultiCell is available open-source at https://gitlab.com/fitmulticell/fit.

Authors: E. Alamoudi, Y. Schalte, R. Muller, J. Starruss, N. Bundgaard, F. Graw, L. Brusch, J. Hasenauer

Date Published: 1st Nov 2023

Publication Type: Journal

FitMultiCell: Simulating and parameterizing computational models of multi-scale and multi-cellular processes

Abstract (Expand)

Motivation Biological tissues are dynamic and highly organized. Multi-scale models are helpful tools to analyze and understand the processes determining tissue dynamics. These models usually depend on … parameters that need to be inferred from experimental data to achieve a quantitative understanding, to predict the response to perturbations, and to evaluate competing hypotheses. However, even advanced inference approaches such as Approximate Bayesian Computation (ABC) are difficult to apply due to the computational complexity of the simulation of multi-scale models. Thus, there is a need for a scalable pipeline for modeling, simulating, and parameterizing multi-scale models of multi-cellular processes. Results Here, we present FitMultiCell, a computationally efficient and user-friendly open-source pipeline that can handle the full workflow of modeling, simulating, and parameterizing for multi-scale models of multi-cellular processes. The pipeline is modular and integrates the modeling and simulation tool Morpheus and the statistical inference tool pyABC. The easy integration of high-performance infrastructure allows to scale to computationally expensive problems. The introduction of a novel standard for the formulation of parameter inference problems for multi-scale models additionally ensures reproducibility and reusability. By applying the pipeline to multiple biological problems, we demonstrate its broad applicability, which will benefit in particular image-based systems biology. Availability FitMultiCell is available open-source at https://gitlab.com/fitmulticell/fit Supplementary data are available at https://doi.org/10.5281/zenodo.7646287

Authors: Emad Alamoudi, Yannik Schälte, Robert Müller, Jörn Starruß, Nils Bundgaard, Frederik Graw, Lutz Brusch, Jan Hasenauer

Date Published: 21st Feb 2023

Publication Type: Misc

Bile canaliculi remodeling activates YAP via the actin cytoskeleton during liver regeneration

Abstract (Expand)

The mechanisms of organ size control remain poorly understood. A key question is how cells collectively sense the overall status of a tissue. We addressed this problem focusing on mouse liver regeneration. … Using digital tissue reconstruction and quantitative image analysis, we found that the apical surface of hepatocytes forming the bile canalicular network expands concomitant with an increase in F‐actin and phospho‐myosin, to compensate an overload of bile acids. These changes are sensed by the Hippo transcriptional co‐activator YAP, which localizes to apical F‐actin‐rich regions and translocates to the nucleus in dependence of the integrity of the actin cytoskeleton. This mechanism tolerates moderate bile acid fluctuations under tissue homeostasis, but activates YAP in response to sustained bile acid overload. Using an integrated biophysical–biochemical model of bile pressure and Hippo signaling, we explained this behavior by the existence of a mechano‐sensory mechanism that activates YAP in a switch‐like manner. We propose that the apical surface of hepatocytes acts as a self‐regulatory mechano‐sensory system that responds to critical levels of bile acids as readout of tissue status.

Authors: Kirstin Meyer, Hernan Morales‐Navarrete, Sarah Seifert, Michaela Wilsch‐Braeuninger, Uta Dahmen, Elly M Tanaka, Lutz Brusch, Yannis Kalaidzidis, Marino Zerial

Date Published: 24th Feb 2020

Publication Type: Not specified

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