Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics

Cell Communication and Signaling

Research

Verena Lang¹  Anne Hamacher-Brady¹  Christoph S Börlin²  Nathan R Brady² 

[1] Bioquant, Heidelberg University, INF 267, 69120, Heidelberg, Germany;Lysosomal Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany;Systems Biology of Cell Death Mechanisms, German Cancer Research Center (DKFZ), Heidelberg, Germany;Department of Surgery, Heidelberg University Hospital, Heidelberg, Germany;Bioquant, Heidelberg University, INF 267, 69120, Heidelberg, Germany;

关键词: Agent-based modeling;    Autophagy;    Autophagic flux;    Cell-to-cell variability;    Systems biology;    Computational biology;    mTOR;    Lysosomes;   

DOI  :  10.1186/s12964-014-0056-8

 received in 2014-07-03, accepted in 2014-08-31,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundAutophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies.ResultsWe applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3 hours) under basal and activated autophagy conditions, and to measure the degree of cell-to-cell variability. Moreover, we experimentally confirmed two model predictions, namely (i) peri-nuclear concentration of autophagosomes and (ii) inhibitory lysosomal feedback on mTOR signaling.ConclusionAgent-based modeling represents a novel approach to investigate autophagy dynamics, function and dysfunction with high biological realism. Our model accurately recapitulates short-term behavior and cell-to-cell variability under basal and activated conditions of autophagy. Further, this approach also allows investigation of long-term behaviors emerging from biologically-relevant alterations to vesicle trafficking and metabolic state.

【 授权许可】

Unknown   
© Börlin et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.