000119673 001__ 119673
000119673 005__ 20240228134949.0
000119673 0247_ $$2doi$$a10.1186/s12964-014-0056-8
000119673 0247_ $$2pmid$$apmid:25214434
000119673 0247_ $$2pmc$$apmc:PMC4172826
000119673 037__ $$aDKFZ-2017-00304
000119673 041__ $$aeng
000119673 082__ $$a610
000119673 1001_ $$0P:(DE-HGF)0$$aBörlin, Christoph S$$b0$$eFirst author
000119673 245__ $$aAgent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.
000119673 260__ $$aLondon$$bBiomed Central$$c2014
000119673 3367_ $$2DRIVER$$aarticle
000119673 3367_ $$2DataCite$$aOutput Types/Journal article
000119673 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1488542756_12068
000119673 3367_ $$2BibTeX$$aARTICLE
000119673 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000119673 3367_ $$00$$2EndNote$$aJournal Article
000119673 520__ $$aAutophagy 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.
000119673 536__ $$0G:(DE-HGF)POF3-312$$a312 - Functional and structural genomics (POF3-312)$$cPOF3-312$$fPOF III$$x0
000119673 588__ $$aDataset connected to CrossRef, PubMed,
000119673 650_7 $$2NLM Chemicals$$aMacrolides
000119673 650_7 $$088899-55-2$$2NLM Chemicals$$abafilomycin A1
000119673 650_7 $$0EC 2.7.1.1$$2NLM Chemicals$$aMTOR protein, human
000119673 650_7 $$0EC 2.7.1.1$$2NLM Chemicals$$aTOR Serine-Threonine Kinases
000119673 7001_ $$0P:(DE-He78)929b2109a63146eb30e74f712ad74596$$aLang, Verena$$b1$$udkfz
000119673 7001_ $$0P:(DE-HGF)0$$aHamacher-Brady, Anne$$b2
000119673 7001_ $$0P:(DE-He78)5bf984e94f0a31773a103cd293e01f92$$aBrady, Nathan$$b3$$eLast author$$udkfz
000119673 773__ $$0PERI:(DE-600)2126315-2$$a10.1186/s12964-014-0056-8$$gVol. 12, no. 1, p. 56$$n1$$p56$$tCell communication and signaling$$v12$$x1478-811X$$y2014
000119673 909CO $$ooai:inrepo02.dkfz.de:119673$$pVDB
000119673 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-HGF)0$$aDeutsches Krebsforschungszentrum$$b0$$kDKFZ
000119673 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)929b2109a63146eb30e74f712ad74596$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000119673 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-HGF)0$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000119673 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)5bf984e94f0a31773a103cd293e01f92$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000119673 9131_ $$0G:(DE-HGF)POF3-312$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vFunctional and structural genomics$$x0
000119673 9141_ $$y2014
000119673 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bCELL COMMUN SIGNAL : 2015
000119673 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000119673 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000119673 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000119673 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal
000119673 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ
000119673 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ
000119673 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000119673 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000119673 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000119673 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000119673 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000119673 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000119673 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000119673 9201_ $$0I:(DE-He78)B190-20160331$$kB190$$le:Bio Nachwuchsgruppe Lysosomale Systembiologie$$x0
000119673 980__ $$ajournal
000119673 980__ $$aVDB
000119673 980__ $$aI:(DE-He78)B190-20160331
000119673 980__ $$aUNRESTRICTED