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4 Publications visible to you, out of a total of 4

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

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

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

Abstract (Expand)

The Hedgehog (Hh) and Wnt/β-Catenin (Wnt) cascades are morphogen pathways whose pronounced influence on adult liver metabolism has been identified in recent years. How both pathways communicate and control liver metabolic functions are largely unknown. Detecting core components of Wnt and Hh signaling and mathematical modeling showed that both pathways in healthy liver act largely complementary to each other in the pericentral (Wnt) and the periportal zone (Hh) and communicate mainly by mutual repression. The Wnt/Hh module inversely controls the spatiotemporal operation of various liver metabolic pathways, as revealed by transcriptome, proteome, and metabolome analyses. Shifting the balance to Wnt (activation) or Hh (inhibition) causes pericentralization and periportalization of liver functions, respectively. Thus, homeostasis of the Wnt/Hh module is essential for maintaining proper liver metabolism and to avoid the development of certain metabolic diseases. With caution due to minor species-specific differences, these conclusions may hold for human liver as well.

Authors: Erik Kolbe, Susanne Aleithe, Christiane Rennert, Luise Spormann, Fritzi Ott, David Meierhofer, Robert Gajowski, Claus Stöpel, Stefan Hoehme, Michael Kücken, Lutz Brusch, Michael Seifert, Witigo von Schoenfels, Clemens Schafmayer, Mario Brosch, Ute Hofmann, Georg Damm, Daniel Seehofer, Jochen Hampe, Rolf Gebhardt, Madlen Matz-Soja

Date Published: 1st Dec 2019

Publication Type: Not specified

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