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Journal article
Rule-based cell systems model of aging using feedback loop motifs mediated by stress responses
PLoS computational biology, v 6(6), e1000820
17 Jun 2010
PMID: 20585546
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Investigating the complex systems dynamics of the aging process requires integration of a broad range of cellular processes describing damage and functional decline co-existing with adaptive and protective regulatory mechanisms. We evolve an integrated generic cell network to represent the connectivity of key cellular mechanisms structured into positive and negative feedback loop motifs centrally important for aging. The conceptual network is casted into a fuzzy-logic, hybrid-intelligent framework based on interaction rules assembled from a priori knowledge. Based upon a classical homeostatic representation of cellular energy metabolism, we first demonstrate how positive-feedback loops accelerate damage and decline consistent with a vicious cycle. This model is iteratively extended towards an adaptive response model by incorporating protective negative-feedback loop circuits. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-kappaB and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration, metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis. Our work establishes a novel extendable and scalable computational approach capable to connect tractable molecular mechanisms with cellular network dynamics underlying the emerging aging phenotype.
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Details
- Title
- Rule-based cell systems model of aging using feedback loop motifs mediated by stress responses
- Creators
- Andres Kriete (Corresponding Author) - Drexel UniversityWilliam J Bosl - Harvard Medical SchoolGlenn Booker - Drexel University
- Publication Details
- PLoS computational biology, v 6(6), e1000820
- Publisher
- Public LIbrary of Science (PLOS); United States
- Number of pages
- 12
- Grant note
- 2R01GM059964 / NIGMS NIH HHS R01 GM059964 / NIGMS NIH HHS K01 HG003418-04 / NHGRI NIH HHS K01 HG003418 / NHGRI NIH HHS 1-R01-ES-014483-01 / NIEHS NIH HHS 5K01HG003418 / NHGRI NIH HHS R01 ES014483 / NIEHS NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000279341000026
- Scopus ID
- 2-s2.0-77955476576
- Other Identifier
- 991014877989904721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Biochemical Research Methods
- Mathematical & Computational Biology