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Autophagy capacity and sub-mitochondrial heterogeneity shape Bnip3-induced mitophagy regulation of apoptosis.

Choe SC, Hamacher-Brady A, Brady NR - Cell Commun. Signal (2015)

Bottom Line: Previously, we have shown that Bnip3-activated mitophagy prior to apoptosis induction can reduce mitochondrial activation of caspases, suggesting that a reduction to mitochondrial levels may be pro-survival.Our model identifies mechanisms and conditions that alter the mitophagy decision within mitochondrial subpopulations to an extent sufficient to shape cellular outcome to apoptotic stimuli.Overall, our modeling approach provides means to suggest new experiments and implement findings at multiple scales in order to understand how network topologies and subcellular heterogeneities can influence signaling events at individual organelle level, and hence, determine the emergence of heterogeneity in cellular decisions due the actions of the collective intra-cellular population.

View Article: PubMed Central - PubMed

Affiliation: Systems Biology of Cell Death Mechanisms, German Cancer Research Center (DKFZ), Heidelberg, Germany.

ABSTRACT

Background: Mitochondria are key regulators of apoptosis. In response to stress, BH3-only proteins activate pro-apoptotic Bcl2 family proteins Bax and Bak, which induce mitochondrial outer membrane permeabilization (MOMP). While the large-scale mitochondrial release of pro-apoptotic proteins activates caspase-dependent cell death, a limited release results in sub-lethal caspase activation which promotes tumorigenesis. Mitochondrial autophagy (mitophagy) targets dysfunctional mitochondria for degradation by lysosomes, and undergoes extensive crosstalk with apoptosis signaling, but its influence on apoptosis remains undetermined. The BH3-only protein Bnip3 integrates apoptosis and mitophagy signaling at different signaling domains. Bnip3 inhibits pro-survival Bcl2 members via its BH3 domain and activates mitophagy through its LC3 Interacting Region (LIR), which is responsible for binding to autophagosomes. Previously, we have shown that Bnip3-activated mitophagy prior to apoptosis induction can reduce mitochondrial activation of caspases, suggesting that a reduction to mitochondrial levels may be pro-survival. An outstanding question is whether organelle dynamics and/or recently discovered subcellular variations of protein levels responsible for both MOMP sensitivity and crosstalk between apoptosis and mitophagy can influence the cellular apoptosis decision event. To that end, here we undertook a systems biology analysis of mitophagy-apoptosis crosstalk at the level of cellular mitochondrial populations.

Results: Based on experimental findings, we developed a multi-scale, hybrid model with an individually adaptive mitochondrial population, whose actions are determined by protein levels, embedded in an agent-based model (ABM) for simulating subcellular dynamics and local feedback via reactive oxygen species signaling. Our model, supported by experimental evidence, identified an emergent regulatory structure within canonical apoptosis signaling. We show that the extent of mitophagy is determined by levels and spatial localization of autophagy capacity, and subcellular mitochondrial protein heterogeneities. Our model identifies mechanisms and conditions that alter the mitophagy decision within mitochondrial subpopulations to an extent sufficient to shape cellular outcome to apoptotic stimuli.

Conclusion: Overall, our modeling approach provides means to suggest new experiments and implement findings at multiple scales in order to understand how network topologies and subcellular heterogeneities can influence signaling events at individual organelle level, and hence, determine the emergence of heterogeneity in cellular decisions due the actions of the collective intra-cellular population.

No MeSH data available.


Related in: MedlinePlus

Impact of AV level on homogeneous mitochondrial population. a Imagestream X analysis of normalized GFP-LC3 AV intensities in cell populations under basal, activated and Bafilomycin A1 (Baf)-inhibited autophagy conditions for 3 h. Autophagic flux is reported as fold change, calculated from mean normalized steady state and cumulative (Baf-treated) GFP-LC3 AV intensities. (left) Experiments under conditions of autophagy activation by nutrient deprivation (ND), and ND with lysosomal inhibitor Baf (100 nM) treatment in cell lines: Capan1 and Panc1 (pancreatic cancer), HPDE (non-tumorgenic pancreatic epithelial), HeLa (ovarian cancer), MCF7 (breast cancer), MCF10A (non-tumorgenic breast epithelial). (right) Autophagy activation via treatment with mTOR inhibitor RAD001 (100 nM), and in RAD001 combined with Baf under conditions of full medium (FM). b Model simulations using similar fold changes in AV content as in (a), in absence of tBid activation for homogeneous mitochondrial population. Results indicate mitophagy activation rate during an “activation” phase (light gray region), beginning (solid black line) of a “competition” phase (dark gray region), and point of mitophagy phenotype commitment (dashed red line) for all Bnip3 mutants. Spread in curves for each condition indicates cell-to-cell variability. c (left) Total number of mitochondria in a cell committed to mitophagy as final phenotype after tBid activation (at t = 5) and 20 % Bnip3 pre-activation with increasing AV levels for all three Bnip3 mutants and (middle) corresponding total cytochrome c release. (inset, bottom) Total cytochrome c release per time step by all mitochondria and (inset, top) total cumulative cytochrome c release for Bnip3 WT (d) Impact of delayed tBid activation (at t = 10) on cellular mitophagic response and total cytochrome c release for increasing AV levels. All simulated conditions had sample size of 50 runs with scatter points indicating a single run
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Fig4: Impact of AV level on homogeneous mitochondrial population. a Imagestream X analysis of normalized GFP-LC3 AV intensities in cell populations under basal, activated and Bafilomycin A1 (Baf)-inhibited autophagy conditions for 3 h. Autophagic flux is reported as fold change, calculated from mean normalized steady state and cumulative (Baf-treated) GFP-LC3 AV intensities. (left) Experiments under conditions of autophagy activation by nutrient deprivation (ND), and ND with lysosomal inhibitor Baf (100 nM) treatment in cell lines: Capan1 and Panc1 (pancreatic cancer), HPDE (non-tumorgenic pancreatic epithelial), HeLa (ovarian cancer), MCF7 (breast cancer), MCF10A (non-tumorgenic breast epithelial). (right) Autophagy activation via treatment with mTOR inhibitor RAD001 (100 nM), and in RAD001 combined with Baf under conditions of full medium (FM). b Model simulations using similar fold changes in AV content as in (a), in absence of tBid activation for homogeneous mitochondrial population. Results indicate mitophagy activation rate during an “activation” phase (light gray region), beginning (solid black line) of a “competition” phase (dark gray region), and point of mitophagy phenotype commitment (dashed red line) for all Bnip3 mutants. Spread in curves for each condition indicates cell-to-cell variability. c (left) Total number of mitochondria in a cell committed to mitophagy as final phenotype after tBid activation (at t = 5) and 20 % Bnip3 pre-activation with increasing AV levels for all three Bnip3 mutants and (middle) corresponding total cytochrome c release. (inset, bottom) Total cytochrome c release per time step by all mitochondria and (inset, top) total cumulative cytochrome c release for Bnip3 WT (d) Impact of delayed tBid activation (at t = 10) on cellular mitophagic response and total cytochrome c release for increasing AV levels. All simulated conditions had sample size of 50 runs with scatter points indicating a single run

Mentions: Different cell types likely have varying autophagy capacities, which may determine how AVs influence mitophagy induction. Hence, in order to explore the contribution of cellular autophagic capacity on the emergence of subcellular and cellular heterogeneity, we sought to systematically simulate different AV levels. To qualitatively model a physiological range of cellular autophagy capacity, we first experimentally measured autophagy flux in populations of cancer and non-cancer cell lines. Cells were submitted to 3 h of nutrient deprivation (ND), and ND in the presence of the lysosomal inhibitor Bafilomycin A1 (Baf) to measure flux [49]. Single cell analysis of autophagy in cell populations was performed with image-based flow cytometry analysis using Imagestream [14, 50]. As a measure of AV content, steady-state GFP-LC3 vesicles intensity was normalized to cumulative cell GFP-LC3 intensity, which allowed for direct comparison of population responses between cell types and conditions (Fig. 4a, Additional file 8: Figures S8A-B). The mean steady-state (orange traces) and cumulative (Baf-inhibited) AV content (olive traces) showed ranges of 1.3–4.3 fold differences between cell types. Similarly, we compared basal autophagy response by inducing autophagy with the mTOR inhibitor RAD001 under full medium (FM) conditions in breast cancer MCF7 cells and human pancreatic duct epithelial (HPDE) cells. Both cell types showed high autophagy flux after treatment with Baf and RAD001 showing approximately 3–7 fold increases.Fig. 4


Autophagy capacity and sub-mitochondrial heterogeneity shape Bnip3-induced mitophagy regulation of apoptosis.

Choe SC, Hamacher-Brady A, Brady NR - Cell Commun. Signal (2015)

Impact of AV level on homogeneous mitochondrial population. a Imagestream X analysis of normalized GFP-LC3 AV intensities in cell populations under basal, activated and Bafilomycin A1 (Baf)-inhibited autophagy conditions for 3 h. Autophagic flux is reported as fold change, calculated from mean normalized steady state and cumulative (Baf-treated) GFP-LC3 AV intensities. (left) Experiments under conditions of autophagy activation by nutrient deprivation (ND), and ND with lysosomal inhibitor Baf (100 nM) treatment in cell lines: Capan1 and Panc1 (pancreatic cancer), HPDE (non-tumorgenic pancreatic epithelial), HeLa (ovarian cancer), MCF7 (breast cancer), MCF10A (non-tumorgenic breast epithelial). (right) Autophagy activation via treatment with mTOR inhibitor RAD001 (100 nM), and in RAD001 combined with Baf under conditions of full medium (FM). b Model simulations using similar fold changes in AV content as in (a), in absence of tBid activation for homogeneous mitochondrial population. Results indicate mitophagy activation rate during an “activation” phase (light gray region), beginning (solid black line) of a “competition” phase (dark gray region), and point of mitophagy phenotype commitment (dashed red line) for all Bnip3 mutants. Spread in curves for each condition indicates cell-to-cell variability. c (left) Total number of mitochondria in a cell committed to mitophagy as final phenotype after tBid activation (at t = 5) and 20 % Bnip3 pre-activation with increasing AV levels for all three Bnip3 mutants and (middle) corresponding total cytochrome c release. (inset, bottom) Total cytochrome c release per time step by all mitochondria and (inset, top) total cumulative cytochrome c release for Bnip3 WT (d) Impact of delayed tBid activation (at t = 10) on cellular mitophagic response and total cytochrome c release for increasing AV levels. All simulated conditions had sample size of 50 runs with scatter points indicating a single run
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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Fig4: Impact of AV level on homogeneous mitochondrial population. a Imagestream X analysis of normalized GFP-LC3 AV intensities in cell populations under basal, activated and Bafilomycin A1 (Baf)-inhibited autophagy conditions for 3 h. Autophagic flux is reported as fold change, calculated from mean normalized steady state and cumulative (Baf-treated) GFP-LC3 AV intensities. (left) Experiments under conditions of autophagy activation by nutrient deprivation (ND), and ND with lysosomal inhibitor Baf (100 nM) treatment in cell lines: Capan1 and Panc1 (pancreatic cancer), HPDE (non-tumorgenic pancreatic epithelial), HeLa (ovarian cancer), MCF7 (breast cancer), MCF10A (non-tumorgenic breast epithelial). (right) Autophagy activation via treatment with mTOR inhibitor RAD001 (100 nM), and in RAD001 combined with Baf under conditions of full medium (FM). b Model simulations using similar fold changes in AV content as in (a), in absence of tBid activation for homogeneous mitochondrial population. Results indicate mitophagy activation rate during an “activation” phase (light gray region), beginning (solid black line) of a “competition” phase (dark gray region), and point of mitophagy phenotype commitment (dashed red line) for all Bnip3 mutants. Spread in curves for each condition indicates cell-to-cell variability. c (left) Total number of mitochondria in a cell committed to mitophagy as final phenotype after tBid activation (at t = 5) and 20 % Bnip3 pre-activation with increasing AV levels for all three Bnip3 mutants and (middle) corresponding total cytochrome c release. (inset, bottom) Total cytochrome c release per time step by all mitochondria and (inset, top) total cumulative cytochrome c release for Bnip3 WT (d) Impact of delayed tBid activation (at t = 10) on cellular mitophagic response and total cytochrome c release for increasing AV levels. All simulated conditions had sample size of 50 runs with scatter points indicating a single run
Mentions: Different cell types likely have varying autophagy capacities, which may determine how AVs influence mitophagy induction. Hence, in order to explore the contribution of cellular autophagic capacity on the emergence of subcellular and cellular heterogeneity, we sought to systematically simulate different AV levels. To qualitatively model a physiological range of cellular autophagy capacity, we first experimentally measured autophagy flux in populations of cancer and non-cancer cell lines. Cells were submitted to 3 h of nutrient deprivation (ND), and ND in the presence of the lysosomal inhibitor Bafilomycin A1 (Baf) to measure flux [49]. Single cell analysis of autophagy in cell populations was performed with image-based flow cytometry analysis using Imagestream [14, 50]. As a measure of AV content, steady-state GFP-LC3 vesicles intensity was normalized to cumulative cell GFP-LC3 intensity, which allowed for direct comparison of population responses between cell types and conditions (Fig. 4a, Additional file 8: Figures S8A-B). The mean steady-state (orange traces) and cumulative (Baf-inhibited) AV content (olive traces) showed ranges of 1.3–4.3 fold differences between cell types. Similarly, we compared basal autophagy response by inducing autophagy with the mTOR inhibitor RAD001 under full medium (FM) conditions in breast cancer MCF7 cells and human pancreatic duct epithelial (HPDE) cells. Both cell types showed high autophagy flux after treatment with Baf and RAD001 showing approximately 3–7 fold increases.Fig. 4

Bottom Line: Previously, we have shown that Bnip3-activated mitophagy prior to apoptosis induction can reduce mitochondrial activation of caspases, suggesting that a reduction to mitochondrial levels may be pro-survival.Our model identifies mechanisms and conditions that alter the mitophagy decision within mitochondrial subpopulations to an extent sufficient to shape cellular outcome to apoptotic stimuli.Overall, our modeling approach provides means to suggest new experiments and implement findings at multiple scales in order to understand how network topologies and subcellular heterogeneities can influence signaling events at individual organelle level, and hence, determine the emergence of heterogeneity in cellular decisions due the actions of the collective intra-cellular population.

View Article: PubMed Central - PubMed

Affiliation: Systems Biology of Cell Death Mechanisms, German Cancer Research Center (DKFZ), Heidelberg, Germany.

ABSTRACT

Background: Mitochondria are key regulators of apoptosis. In response to stress, BH3-only proteins activate pro-apoptotic Bcl2 family proteins Bax and Bak, which induce mitochondrial outer membrane permeabilization (MOMP). While the large-scale mitochondrial release of pro-apoptotic proteins activates caspase-dependent cell death, a limited release results in sub-lethal caspase activation which promotes tumorigenesis. Mitochondrial autophagy (mitophagy) targets dysfunctional mitochondria for degradation by lysosomes, and undergoes extensive crosstalk with apoptosis signaling, but its influence on apoptosis remains undetermined. The BH3-only protein Bnip3 integrates apoptosis and mitophagy signaling at different signaling domains. Bnip3 inhibits pro-survival Bcl2 members via its BH3 domain and activates mitophagy through its LC3 Interacting Region (LIR), which is responsible for binding to autophagosomes. Previously, we have shown that Bnip3-activated mitophagy prior to apoptosis induction can reduce mitochondrial activation of caspases, suggesting that a reduction to mitochondrial levels may be pro-survival. An outstanding question is whether organelle dynamics and/or recently discovered subcellular variations of protein levels responsible for both MOMP sensitivity and crosstalk between apoptosis and mitophagy can influence the cellular apoptosis decision event. To that end, here we undertook a systems biology analysis of mitophagy-apoptosis crosstalk at the level of cellular mitochondrial populations.

Results: Based on experimental findings, we developed a multi-scale, hybrid model with an individually adaptive mitochondrial population, whose actions are determined by protein levels, embedded in an agent-based model (ABM) for simulating subcellular dynamics and local feedback via reactive oxygen species signaling. Our model, supported by experimental evidence, identified an emergent regulatory structure within canonical apoptosis signaling. We show that the extent of mitophagy is determined by levels and spatial localization of autophagy capacity, and subcellular mitochondrial protein heterogeneities. Our model identifies mechanisms and conditions that alter the mitophagy decision within mitochondrial subpopulations to an extent sufficient to shape cellular outcome to apoptotic stimuli.

Conclusion: Overall, our modeling approach provides means to suggest new experiments and implement findings at multiple scales in order to understand how network topologies and subcellular heterogeneities can influence signaling events at individual organelle level, and hence, determine the emergence of heterogeneity in cellular decisions due the actions of the collective intra-cellular population.

No MeSH data available.


Related in: MedlinePlus