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Computational analysis of an autophagy/translation switch based on mutual inhibition of MTORC1 and ULK1.

Szymańska P, Martin KR, MacKeigan JP, Hlavacek WS, Lipniacki T - PLoS ONE (2015)

Bottom Line: The model incorporates reciprocal regulation of mTORC1 and ULK1 by AMPK, mutual inhibition of MTORC1 and ULK1, and ULK1-mediated negative feedback regulation of AMPK.A sensitivity analysis indicates that the prediction of oscillatory behavior is robust to changes of the parameter values of the model.The model provides testable predictions about the behavior of the AMPK-MTORC1-ULK1 network, which plays a central role in maintaining cellular energy and nutrient homeostasis.

View Article: PubMed Central - PubMed

Affiliation: College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw, Warsaw, Poland.

ABSTRACT
We constructed a mechanistic, computational model for regulation of (macro)autophagy and protein synthesis (at the level of translation). The model was formulated to study the system-level consequences of interactions among the following proteins: two key components of MTOR complex 1 (MTORC1), namely the protein kinase MTOR (mechanistic target of rapamycin) and the scaffold protein RPTOR; the autophagy-initiating protein kinase ULK1; and the multimeric energy-sensing AMP-activated protein kinase (AMPK). Inputs of the model include intrinsic AMPK kinase activity, which is taken as an adjustable surrogate parameter for cellular energy level or AMP:ATP ratio, and rapamycin dose, which controls MTORC1 activity. Outputs of the model include the phosphorylation level of the translational repressor EIF4EBP1, a substrate of MTORC1, and the phosphorylation level of AMBRA1 (activating molecule in BECN1-regulated autophagy), a substrate of ULK1 critical for autophagosome formation. The model incorporates reciprocal regulation of mTORC1 and ULK1 by AMPK, mutual inhibition of MTORC1 and ULK1, and ULK1-mediated negative feedback regulation of AMPK. Through analysis of the model, we find that these processes may be responsible, depending on conditions, for graded responses to stress inputs, for bistable switching between autophagy and protein synthesis, or relaxation oscillations, comprising alternating periods of autophagy and protein synthesis. A sensitivity analysis indicates that the prediction of oscillatory behavior is robust to changes of the parameter values of the model. The model provides testable predictions about the behavior of the AMPK-MTORC1-ULK1 network, which plays a central role in maintaining cellular energy and nutrient homeostasis.

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Results from bifurcation analysis of the system without negative feedback from ULK1 to AMPK.Each panel is a one-dimensional bifurcation diagram showing stable steady-state levels of phosphorylated AMBRA1 (red curves, top panels) or phosphorylated EIF4EBP1 (blue curves, bottom panels) as a function of the level of AMPK* (left panels) or the level of rapamycin* (right panels). Thus, we took the inputs of the model as our bifurcation parameters. For the left panels, the abundance of rapamycin* is fixed at zero. For the right panels, the abundance of AMPK* is fixed at 30,000 copies per cell. For all panels, the parameters considered in Table 1 are held fixed at their nominal values. The labels SN1, SN2, and SN3 indicate saddle node bifurcation points. Bifurcation analysis was performed numerically (see Materials and Methods).
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pone.0116550.g003: Results from bifurcation analysis of the system without negative feedback from ULK1 to AMPK.Each panel is a one-dimensional bifurcation diagram showing stable steady-state levels of phosphorylated AMBRA1 (red curves, top panels) or phosphorylated EIF4EBP1 (blue curves, bottom panels) as a function of the level of AMPK* (left panels) or the level of rapamycin* (right panels). Thus, we took the inputs of the model as our bifurcation parameters. For the left panels, the abundance of rapamycin* is fixed at zero. For the right panels, the abundance of AMPK* is fixed at 30,000 copies per cell. For all panels, the parameters considered in Table 1 are held fixed at their nominal values. The labels SN1, SN2, and SN3 indicate saddle node bifurcation points. Bifurcation analysis was performed numerically (see Materials and Methods).

Mentions: In our parameterization of the model (Table 1), the negative feedback from ULK1 to AMPK (Fig. 1) is slow compared to other interactions. Thus, on short time scales, the system behaves as if the negative feedback is absent. For this reason, we first analyzed system behavior in the absence of negative feedback (i.e., without ULK1-mediated inhibitory phosphorylation of AMPK). As described in Materials and Methods, we found stable steady states of the system through simulation for different values of bifurcation parameters. The results are summarized in Fig. 3, where curves mark stable steady states. As can be seen, the system without negative feedback exhibits bistability over a broad range of each of the bifurcation parameters, the levels of AMPK* (left panels) and rapamycin* (right panels). It should be noted that, for the scenario under consideration, AMPK is always active when the kinase domain in the α subunit is phosphorylated (Fig. 2). In other words, for this scenario, AMPK* is equivalent to active AMPK.


Computational analysis of an autophagy/translation switch based on mutual inhibition of MTORC1 and ULK1.

Szymańska P, Martin KR, MacKeigan JP, Hlavacek WS, Lipniacki T - PLoS ONE (2015)

Results from bifurcation analysis of the system without negative feedback from ULK1 to AMPK.Each panel is a one-dimensional bifurcation diagram showing stable steady-state levels of phosphorylated AMBRA1 (red curves, top panels) or phosphorylated EIF4EBP1 (blue curves, bottom panels) as a function of the level of AMPK* (left panels) or the level of rapamycin* (right panels). Thus, we took the inputs of the model as our bifurcation parameters. For the left panels, the abundance of rapamycin* is fixed at zero. For the right panels, the abundance of AMPK* is fixed at 30,000 copies per cell. For all panels, the parameters considered in Table 1 are held fixed at their nominal values. The labels SN1, SN2, and SN3 indicate saddle node bifurcation points. Bifurcation analysis was performed numerically (see Materials and Methods).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4356596&req=5

pone.0116550.g003: Results from bifurcation analysis of the system without negative feedback from ULK1 to AMPK.Each panel is a one-dimensional bifurcation diagram showing stable steady-state levels of phosphorylated AMBRA1 (red curves, top panels) or phosphorylated EIF4EBP1 (blue curves, bottom panels) as a function of the level of AMPK* (left panels) or the level of rapamycin* (right panels). Thus, we took the inputs of the model as our bifurcation parameters. For the left panels, the abundance of rapamycin* is fixed at zero. For the right panels, the abundance of AMPK* is fixed at 30,000 copies per cell. For all panels, the parameters considered in Table 1 are held fixed at their nominal values. The labels SN1, SN2, and SN3 indicate saddle node bifurcation points. Bifurcation analysis was performed numerically (see Materials and Methods).
Mentions: In our parameterization of the model (Table 1), the negative feedback from ULK1 to AMPK (Fig. 1) is slow compared to other interactions. Thus, on short time scales, the system behaves as if the negative feedback is absent. For this reason, we first analyzed system behavior in the absence of negative feedback (i.e., without ULK1-mediated inhibitory phosphorylation of AMPK). As described in Materials and Methods, we found stable steady states of the system through simulation for different values of bifurcation parameters. The results are summarized in Fig. 3, where curves mark stable steady states. As can be seen, the system without negative feedback exhibits bistability over a broad range of each of the bifurcation parameters, the levels of AMPK* (left panels) and rapamycin* (right panels). It should be noted that, for the scenario under consideration, AMPK is always active when the kinase domain in the α subunit is phosphorylated (Fig. 2). In other words, for this scenario, AMPK* is equivalent to active AMPK.

Bottom Line: The model incorporates reciprocal regulation of mTORC1 and ULK1 by AMPK, mutual inhibition of MTORC1 and ULK1, and ULK1-mediated negative feedback regulation of AMPK.A sensitivity analysis indicates that the prediction of oscillatory behavior is robust to changes of the parameter values of the model.The model provides testable predictions about the behavior of the AMPK-MTORC1-ULK1 network, which plays a central role in maintaining cellular energy and nutrient homeostasis.

View Article: PubMed Central - PubMed

Affiliation: College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw, Warsaw, Poland.

ABSTRACT
We constructed a mechanistic, computational model for regulation of (macro)autophagy and protein synthesis (at the level of translation). The model was formulated to study the system-level consequences of interactions among the following proteins: two key components of MTOR complex 1 (MTORC1), namely the protein kinase MTOR (mechanistic target of rapamycin) and the scaffold protein RPTOR; the autophagy-initiating protein kinase ULK1; and the multimeric energy-sensing AMP-activated protein kinase (AMPK). Inputs of the model include intrinsic AMPK kinase activity, which is taken as an adjustable surrogate parameter for cellular energy level or AMP:ATP ratio, and rapamycin dose, which controls MTORC1 activity. Outputs of the model include the phosphorylation level of the translational repressor EIF4EBP1, a substrate of MTORC1, and the phosphorylation level of AMBRA1 (activating molecule in BECN1-regulated autophagy), a substrate of ULK1 critical for autophagosome formation. The model incorporates reciprocal regulation of mTORC1 and ULK1 by AMPK, mutual inhibition of MTORC1 and ULK1, and ULK1-mediated negative feedback regulation of AMPK. Through analysis of the model, we find that these processes may be responsible, depending on conditions, for graded responses to stress inputs, for bistable switching between autophagy and protein synthesis, or relaxation oscillations, comprising alternating periods of autophagy and protein synthesis. A sensitivity analysis indicates that the prediction of oscillatory behavior is robust to changes of the parameter values of the model. The model provides testable predictions about the behavior of the AMPK-MTORC1-ULK1 network, which plays a central role in maintaining cellular energy and nutrient homeostasis.

Show MeSH