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@ARTICLE{Dalmasso:119460,
      author       = {G. Dalmasso$^*$ and P. A. Marin Zapata$^*$ and N. Brady$^*$
                      and A. Brady$^*$},
      title        = {{A}gent-{B}ased {M}odeling of {M}itochondria {L}inks
                      {S}ub-{C}ellular {D}ynamics to {C}ellular {H}omeostasis and
                      {H}eterogeneity.},
      journal      = {PLoS one},
      volume       = {12},
      number       = {1},
      issn         = {1932-6203},
      address      = {Lawrence, Kan.},
      publisher    = {PLoS},
      reportid     = {DKFZ-2017-00202},
      pages        = {e0168198 -},
      year         = {2017},
      abstract     = {Mitochondria are semi-autonomous organelles that supply
                      energy for cellular biochemistry through oxidative
                      phosphorylation. Within a cell, hundreds of mobile
                      mitochondria undergo fusion and fission events to form a
                      dynamic network. These morphological and mobility dynamics
                      are essential for maintaining mitochondrial functional
                      homeostasis, and alterations both impact and reflect
                      cellular stress states. Mitochondrial homeostasis is further
                      dependent on production (biogenesis) and the removal of
                      damaged mitochondria by selective autophagy (mitophagy).
                      While mitochondrial function, dynamics, biogenesis and
                      mitophagy are highly-integrated processes, it is not fully
                      understood how systemic control in the cell is established
                      to maintain homeostasis, or respond to bioenergetic demands.
                      Here we used agent-based modeling (ABM) to integrate
                      molecular and imaging knowledge sets, and simulate
                      population dynamics of mitochondria and their response to
                      environmental energy demand. Using high-dimensional
                      parameter searches we integrated experimentally-measured
                      rates of mitochondrial biogenesis and mitophagy, and using
                      sensitivity analysis we identified parameter influences on
                      population homeostasis. By studying the dynamics of cellular
                      subpopulations with distinct mitochondrial masses, our
                      approach uncovered system properties of mitochondrial
                      populations: (1) mitochondrial fusion and fission activities
                      rapidly establish mitochondrial sub-population homeostasis,
                      and total cellular levels of mitochondria alter fusion and
                      fission activities and subpopulation distributions; (2)
                      restricting the directionality of mitochondrial mobility
                      does not alter morphology subpopulation distributions, but
                      increases network transmission dynamics; and (3) maintaining
                      mitochondrial mass homeostasis and responding to
                      bioenergetic stress requires the integration of
                      mitochondrial dynamics with the cellular bioenergetic state.
                      Finally, (4) our model suggests sources of, and stress
                      conditions amplifying, cell-to-cell variability of
                      mitochondrial morphology and energetic stress states.
                      Overall, our modeling approach integrates biochemical and
                      imaging knowledge, and presents a novel open-modeling
                      approach to investigate how spatial and temporal
                      mitochondrial dynamics contribute to functional homeostasis,
                      and how subcellular organelle heterogeneity contributes to
                      the emergence of cell heterogeneity.},
      cin          = {B190},
      ddc          = {500},
      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:28060865},
      pmc          = {pmc:PMC5217980},
      doi          = {10.1371/journal.pone.0168198},
      url          = {https://inrepo02.dkfz.de/record/119460},
}