Dataset Information

Musante2017 - Switching behaviour of PP2A inhibition by ARPP-16 - mutual inhibitions and PKA inhibits MAST3

ABSTRACT: Musante2017 - Switching behaviour of PP2A inhibition by ARPP-16 - mutual inhibitions and PKA inhibits MAST3 This model is described in the article: Reciprocal regulation of ARPP-16 by PKA and MAST3 kinases provides a cAMP-regulated switch in protein phosphatase 2A inhibition. Musante V, Li L, Kanyo J, Lam TT, Colangelo CM, Cheng SK, Brody AH, Greengard P, Le Novère N, Nairn AC. Elife 2017 Jun; 6: Abstract: ARPP-16, ARPP-19, and ENSA are inhibitors of protein phosphatase PP2A. ARPP-19 and ENSA phosphorylated by Greatwall kinase inhibit PP2A during mitosis. ARPP-16 is expressed in striatal neurons where basal phosphorylation by MAST3 kinase inhibits PP2A and regulates key components of striatal signaling. The ARPP-16/19 proteins were discovered as substrates for PKA, but the function of PKA phosphorylation is unknown. We find that phosphorylation by PKA or MAST3 mutually suppresses the ability of the other kinase to act on ARPP-16. Phosphorylation by PKA also acts to prevent inhibition of PP2A by ARPP-16 phosphorylated by MAST3. Moreover, PKA phosphorylates MAST3 at multiple sites resulting in its inhibition. Mathematical modeling highlights the role of these three regulatory interactions to create a switch-like response to cAMP. Together, the results suggest a complex antagonistic interplay between the control of ARPP-16 by MAST3 and PKA that creates a mechanism whereby cAMP mediates PP2A disinhibition. This model is hosted on BioModels Database and identified by: BIOMD0000000644. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Lu Li

PROVIDER: BIOMD0000000644 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000000644?filename=ARPP-16_Layer1and2_mutualInhibitions_PKAinhibitsMAST3.cps	Other
	BIOMD0000000644?filename=ARPP-16_Layer1and2_mutualInhibitions_PKAinhibitsMAST3.sedml	Other
	BIOMD0000000644?filename=BIOMD0000000644-biopax2.owl	Owl
	BIOMD0000000644?filename=BIOMD0000000644-biopax3.owl	Owl
	BIOMD0000000644?filename=BIOMD0000000644-matlab.m	Other

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Publications

Reciprocal regulation of ARPP-16 by PKA and MAST3 kinases provides a cAMP-regulated switch in protein phosphatase 2A inhibition.

Musante Veronica V Li Lu L Kanyo Jean J Lam Tukiet T TT Colangelo Christopher M CM Cheng Shuk Kei SK Brody A Harrison AH Greengard Paul P Le Novère Nicolas N Nairn Angus C AC

eLife 20170614

ARPP-16, ARPP-19, and ENSA are inhibitors of protein phosphatase PP2A. ARPP-19 and ENSA phosphorylated by Greatwall kinase inhibit PP2A during mitosis. ARPP-16 is expressed in striatal neurons where basal phosphorylation by MAST3 kinase inhibits PP2A and regulates key components of striatal signaling. The ARPP-16/19 proteins were discovered as substrates for PKA, but the function of PKA phosphorylation is unknown. We find that phosphorylation by PKA or MAST3 mutually suppresses the ability of th ...[more]

PMID: 28613156

Publication: 1/3

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Project description:Musante2017 - Switching behaviour of PP2A inhibition by ARPP-16 - mutual inhibitions and PKA inhibits MAST3 and dominant negative effect This model is described in the article: Reciprocal regulation of ARPP-16 by PKA and MAST3 kinases provides a cAMP-regulated switch in protein phosphatase 2A inhibition. Musante V, Li L, Kanyo J, Lam TT, Colangelo CM, Cheng SK, Brody AH, Greengard P, Le Novère N, Nairn AC. Elife 2017 Jun; 6: Abstract: ARPP-16, ARPP-19, and ENSA are inhibitors of protein phosphatase PP2A. ARPP-19 and ENSA phosphorylated by Greatwall kinase inhibit PP2A during mitosis. ARPP-16 is expressed in striatal neurons where basal phosphorylation by MAST3 kinase inhibits PP2A and regulates key components of striatal signaling. The ARPP-16/19 proteins were discovered as substrates for PKA, but the function of PKA phosphorylation is unknown. We find that phosphorylation by PKA or MAST3 mutually suppresses the ability of the other kinase to act on ARPP-16. Phosphorylation by PKA also acts to prevent inhibition of PP2A by ARPP-16 phosphorylated by MAST3. Moreover, PKA phosphorylates MAST3 at multiple sites resulting in its inhibition. Mathematical modeling highlights the role of these three regulatory interactions to create a switch-like response to cAMP. Together, the results suggest a complex antagonistic interplay between the control of ARPP-16 by MAST3 and PKA that creates a mechanism whereby cAMP mediates PP2A disinhibition. This model is hosted on BioModels Database and identified by: BIOMD0000000645. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Musante2017 - Switching behaviour of PP2A inhibition by ARPP-16 - mutual inhibitions This model is described in the article: Reciprocal regulation of ARPP-16 by PKA and MAST3 kinases provides a cAMP-regulated switch in protein phosphatase 2A inhibition. Musante V, Li L, Kanyo J, Lam TT, Colangelo CM, Cheng SK, Brody AH, Greengard P, Le Novère N, Nairn AC. Elife 2017 Jun; 6: Abstract: ARPP-16, ARPP-19, and ENSA are inhibitors of protein phosphatase PP2A. ARPP-19 and ENSA phosphorylated by Greatwall kinase inhibit PP2A during mitosis. ARPP-16 is expressed in striatal neurons where basal phosphorylation by MAST3 kinase inhibits PP2A and regulates key components of striatal signaling. The ARPP-16/19 proteins were discovered as substrates for PKA, but the function of PKA phosphorylation is unknown. We find that phosphorylation by PKA or MAST3 mutually suppresses the ability of the other kinase to act on ARPP-16. Phosphorylation by PKA also acts to prevent inhibition of PP2A by ARPP-16 phosphorylated by MAST3. Moreover, PKA phosphorylates MAST3 at multiple sites resulting in its inhibition. Mathematical modeling highlights the role of these three regulatory interactions to create a switch-like response to cAMP. Together, the results suggest a complex antagonistic interplay between the control of ARPP-16 by MAST3 and PKA that creates a mechanism whereby cAMP mediates PP2A disinhibition. This model is hosted on BioModels Database and identified by: BIOMD0000000643. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Yapo2017 - A2AR/cAMP/PKA signalling in D2 dopamine receptor expressing medium-spiny neurons This model is described in the article: Detection of phasic dopamine by D1 and D2 striatal medium spiny neurons. Yapo C, Nair AG, Clement L, Castro LR, Hellgren Kotaleski J, Vincent P. J. Physiol. (Lond.) 2017 Aug; : Abstract: The phasic release of dopamine in the striatum determines various aspects of reward and action selection, but the dynamics of dopamine effect on intracellular signalling remains poorly understood. We used genetically-encoded FRET biosensors in striatal brain slices to quantify the effect of transient dopamine on cAMP or PKA-dependent phosphorylation level, and computational modelling to further explore the dynamics of this signalling pathway. Medium-sized spiny neurons (MSNs), which express either D1 or D2 dopamine receptors, responded to dopamine by an increase or a decrease in cAMP, respectively. Transient dopamine showed similar sub-micromolar efficacies on cAMP in both D1 and D2 MSNs, thus challenging the commonly accepted notion that dopamine efficacy is much higher on D2 than on D1 receptors. However, in D2 MSNs, the large decrease in cAMP level triggered by transient dopamine did not translate in a decrease in PKA-dependent phosphorylation level, owing to the efficient inhibition of Protein Phosphatase 1 by DARPP-32. Simulations further suggested that D2 MSNs can also operate in a "tone-sensing" mode, allowing them to detect transient dips in basal dopamine. Overall, our results show that D2 MSNs may sense much more complex patterns of dopamine than previously thought. This article is protected by copyright. All rights reserved. This model is hosted on BioModels Database and identified by: MODEL1701170001. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Yapo2017- cAMP/PKA signalling in D1 dopamine receptor expressing medium-spiny neurons This model is described in the article: Detection of phasic dopamine by D1 and D2 striatal medium spiny neurons. Yapo C, Nair AG, Clement L, Castro LR, Hellgren Kotaleski J, Vincent P. J. Physiol. (Lond.) 2017 Aug; : Abstract: The phasic release of dopamine in the striatum determines various aspects of reward and action selection, but the dynamics of dopamine effect on intracellular signalling remains poorly understood. We used genetically-encoded FRET biosensors in striatal brain slices to quantify the effect of transient dopamine on cAMP or PKA-dependent phosphorylation level, and computational modelling to further explore the dynamics of this signalling pathway. Medium-sized spiny neurons (MSNs), which express either D1 or D2 dopamine receptors, responded to dopamine by an increase or a decrease in cAMP, respectively. Transient dopamine showed similar sub-micromolar efficacies on cAMP in both D1 and D2 MSNs, thus challenging the commonly accepted notion that dopamine efficacy is much higher on D2 than on D1 receptors. However, in D2 MSNs, the large decrease in cAMP level triggered by transient dopamine did not translate in a decrease in PKA-dependent phosphorylation level, owing to the efficient inhibition of Protein Phosphatase 1 by DARPP-32. Simulations further suggested that D2 MSNs can also operate in a "tone-sensing" mode, allowing them to detect transient dips in basal dopamine. Overall, our results show that D2 MSNs may sense much more complex patterns of dopamine than previously thought. This article is protected by copyright. All rights reserved. This model is hosted on BioModels Database and identified by: MODEL1701170000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Nair2015 - Interaction between neuromodulators via GPCRs - Effect on cAMP/PKA signaling (D1 Neuron) This model is described in the article: Sensing Positive versus Negative Reward Signals through Adenylyl Cyclase-Coupled GPCRs in Direct and Indirect Pathway Striatal Medium Spiny Neurons. Nair AG, Gutierrez-Arenas O, Eriksson O, Vincent P, Hellgren Kotaleski J. J. Neurosci. 2015 Oct; 35(41): 14017-14030 Abstract: Transient changes in striatal dopamine (DA) concentration are considered to encode a reward prediction error (RPE) in reinforcement learning tasks. Often, a phasic DA change occurs concomitantly with a dip in striatal acetylcholine (ACh), whereas other neuromodulators, such as adenosine (Adn), change slowly. There are abundant adenylyl cyclase (AC) coupled GPCRs for these neuromodulators in striatal medium spiny neurons (MSNs), which play important roles in plasticity. However, little is known about the interaction between these neuromodulators via GPCRs. The interaction between these transient neuromodulator changes and the effect on cAMP/PKA signaling via Golf- and Gi/o-coupled GPCR are studied here using quantitative kinetic modeling. The simulations suggest that, under basal conditions, cAMP/PKA signaling could be significantly inhibited in D1R+ MSNs via ACh/M4R/Gi/o and an ACh dip is required to gate a subset of D1R/Golf-dependent PKA activation. Furthermore, the interaction between ACh dip and DA peak, via D1R and M4R, is synergistic. In a similar fashion, PKA signaling in D2+ MSNs is under basal inhibition via D2R/Gi/o and a DA dip leads to a PKA increase by disinhibiting A2aR/Golf, but D2+ MSNs could also respond to the DA peak via other intracellular pathways. This study highlights the similarity between the two types of MSNs in terms of high basal AC inhibition by Gi/o and the importance of interactions between Gi/o and Golf signaling, but at the same time predicts differences between them with regard to the sign of RPE responsible for PKA activation.Dopamine transients are considered to carry reward-related signal in reinforcement learning. An increase in dopamine concentration is associated with an unexpected reward or salient stimuli, whereas a decrease is produced by omission of an expected reward. Often dopamine transients are accompanied by other neuromodulatory signals, such as acetylcholine and adenosine. We highlight the importance of interaction between acetylcholine, dopamine, and adenosine signals via adenylyl-cyclase coupled GPCRs in shaping the dopamine-dependent cAMP/PKA signaling in striatal neurons. Specifically, a dopamine peak and an acetylcholine dip must interact, via D1 and M4 receptor, and a dopamine dip must interact with adenosine tone, via D2 and A2a receptor, in direct and indirect pathway neurons, respectively, to have any significant downstream PKA activation. This model is hosted on BioModels Database and identified by: BIOMD0000000635. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.