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@ARTICLE{Brlin:119673,
author = {C. S. Börlin$^*$ and V. Lang$^*$ and A. Hamacher-Brady$^*$
and N. Brady$^*$},
title = {{A}gent-based modeling of autophagy reveals emergent
regulatory behavior of spatio-temporal autophagy dynamics.},
journal = {Cell communication and signaling},
volume = {12},
number = {1},
issn = {1478-811X},
address = {London},
publisher = {Biomed Central},
reportid = {DKFZ-2017-00304},
pages = {56},
year = {2014},
abstract = {Autophagy 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.We 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.Agent-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.},
keywords = {Macrolides (NLM Chemicals) / bafilomycin A1 (NLM Chemicals)
/ MTOR protein, human (NLM Chemicals) / TOR Serine-Threonine
Kinases (NLM Chemicals)},
cin = {B190},
ddc = {610},
cid = {I:(DE-He78)B190-20160331},
pnm = {312 - Functional and structural genomics (POF3-312)},
pid = {G:(DE-HGF)POF3-312},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:25214434},
pmc = {pmc:PMC4172826},
doi = {10.1186/s12964-014-0056-8},
url = {https://inrepo02.dkfz.de/record/119673},
}