Signaling Logic of Activity-Triggered Dendritic Protein Synthesis: An mTOR Gate But Not a Feedback Switch

Jain, Pragati; Bhalla, Upinder S.

doi:10.1371/journal.pcbi.1000287

Cited by 35 publications

(41 citation statements)

References 83 publications

(126 reference statements)

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“…There are several other systems modelling studies of the mTOR network (for example, Jain and Bhalla, 2009; ref. 41), but only one has attempted to model multiple aa inputs42 and found that a single input via mTORC1 was sufficient to explain a set of reported observations. Using time-course data only, our computational strategy for exploring alternative aa inputs allowed us to comprehensively cover model structures that showed an improvement to the canonical single aa-mTORC1 input.…”

Section: Discussionmentioning

confidence: 99%

A systems study reveals concurrent activation of AMPK and mTOR by amino acids

et al. 2016

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Amino acids (aa) are not only building blocks for proteins, but also signalling molecules, with the mammalian target of rapamycin complex 1 (mTORC1) acting as a key mediator. However, little is known about whether aa, independently of mTORC1, activate other kinases of the mTOR signalling network. To delineate aa-stimulated mTOR network dynamics, we here combine a computational–experimental approach with text mining-enhanced quantitative proteomics. We report that AMP-activated protein kinase (AMPK), phosphatidylinositide 3-kinase (PI3K) and mTOR complex 2 (mTORC2) are acutely activated by aa-readdition in an mTORC1-independent manner. AMPK activation by aa is mediated by Ca2+/calmodulin-dependent protein kinase kinase β (CaMKKβ). In response, AMPK impinges on the autophagy regulators Unc-51-like kinase-1 (ULK1) and c-Jun. AMPK is widely recognized as an mTORC1 antagonist that is activated by starvation. We find that aa acutely activate AMPK concurrently with mTOR. We show that AMPK under aa sufficiency acts to sustain autophagy. This may be required to maintain protein homoeostasis and deliver metabolite intermediates for biosynthetic processes.

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Section: Discussionmentioning

confidence: 99%

A systems study reveals concurrent activation of AMPK and mTOR by amino acids

et al. 2016

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“…Modelling of fatty acid metabolism was included in a model of glycolysis by Dash et al [105]. Other work has already been done, which could be combined with that reported here, including for example insulin signalling combined with mTOR [29,106], AMPK [107], and the ERK pathway [31]. Significantly, other recent models of insulin signalling [33], as well as including mTOR signalling, have combined the cell signalling model with a whole body model of insulin/glucose dynamics [108].…”

Section: Discussionmentioning

confidence: 99%

Computational modelling of the regulation of Insulin signalling by oxidative stress

Smith

Shanley

2013

BMC Systems Biology

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BackgroundExisting models of insulin signalling focus on short term dynamics, rather than the longer term dynamics necessary to understand many physiologically relevant behaviours. We have developed a model of insulin signalling in rodent adipocytes that includes both transcriptional feedback through the Forkhead box type O (FOXO) transcription factor, and interaction with oxidative stress, in addition to the core pathway. In the model Reactive Oxygen Species are both generated endogenously and can be applied externally. They regulate signalling though inhibition of phosphatases and induction of the activity of Stress Activated Protein Kinases, which themselves modulate feedbacks to insulin signalling and FOXO.ResultsInsulin and oxidative stress combined produce a lower degree of activation of insulin signalling than insulin alone. Fasting (nutrient withdrawal) and weak oxidative stress upregulate antioxidant defences while stronger oxidative stress leads to a short term activation of insulin signalling but if prolonged can have other effects including degradation of the insulin receptor substrate (IRS1) and FOXO. At high insulin the protective effect of moderate oxidative stress may disappear.ConclusionOur model is consistent with a wide range of experimental data, some of which is difficult to explain. Oxidative stress can have effects that are both up- and down-regulatory on insulin signalling. Our model therefore shows the complexity of the interaction between the two pathways and highlights the need for such integrated computational models to give insight into the dysregulation of insulin signalling along with more data at the individual level.A complete SBML model file can be downloaded from BIOMODELS (https://www.ebi.ac.uk/biomodels-main) with unique identifier MODEL1212210000.Other files and scripts are available as additional files with this journal article and can be downloaded from https://github.com/graham1034/Smith2012_insulin_signalling.

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“…Several optimization routines are offered, such as genetic algorithm, particle swarm and simulated annealing. All of these approaches become more difficult as parameter space is enlarged, and thus one work-around is to subdivide the system into modules and optimize each module independently (Jain and Bhalla, 2009). …”

Section: Simulationmentioning

confidence: 99%

Approaches and tools for modeling signaling pathways and calcium dynamics in neurons

Blackwell

2013

Journal of Neuroscience Methods

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Signaling pathways are cascades of intracellular biochemical reactions that are activated by transmembrane receptors, and ultimately lead to transcription in the nucleus. In neurons, both calcium permeable synaptic and ionic channels as well as G protein coupled receptors initiate activation of signaling pathway molecules that interact with electrical activity at multiple spatial and time scales. At small temporal and spatial scales, calcium modifies the properties of ionic channels, whereas at larger temporal and spatial scales, various kinases and phosphatases modify the properties of ionic channels, producing phenomena such as synaptic plasticity and homeostatic plasticity. The elongated structure of neuronal dendrites and the organization of multi-protein complexes by anchoring proteins implies that the spatial dimension must be explicit. Therefore, modeling signaling pathways in neurons utilizes algorithms for both diffusion and reactions. The small size of spines coupled with small concentrations of some molecules implies that some reactions occur stochastically. The need for stochastic simulation of many reaction and diffusion events coupled with the multiple temporal and spatial scales makes modeling of signaling pathways a difficult problem. Several different software programs have achieved different aspects of these capabilities. This review explains some of the mathematical formulas used for modeling reactions and diffusion. In addition, it briefly presents the simulators used for modeling reaction-diffusion systems in neurons, together with scientific problems addressed.

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Signaling Logic of Activity-Triggered Dendritic Protein Synthesis: An mTOR Gate But Not a Feedback Switch

Cited by 35 publications

References 83 publications

A systems study reveals concurrent activation of AMPK and mTOR by amino acids

A systems study reveals concurrent activation of AMPK and mTOR by amino acids

Computational modelling of the regulation of Insulin signalling by oxidative stress

Approaches and tools for modeling signaling pathways and calcium dynamics in neurons

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