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Regulation of adenylyl cyclase 5 in striatal neurons confers the ability to detect coincident neuromodulatory signals
Heidelberg Inst Theoret Studies, Mol & Cellular Modeling Grp, Schloss Heidelberg, Germany..
Ecole Polytech Fed Lausanne, Inst Sci & Ingn Chim, CH-1015 Lausanne, Switzerland..ORCID iD: 0000-0003-2731-6286
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Electrical Engineering and Computer Science (EECS).
Ecole Polytech Fed Lausanne, Inst Sci & Ingn Chim, CH-1015 Lausanne, Switzerland.;Stanford Univ, Dept Comp Sci, Stanford, CA 94305 USA..
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2019 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 15, no 10, article id e1007382Article in journal (Refereed) Published
Abstract [en]

Author summary Adenylyl cyclases (ACs) are enzymes that can translate extracellular signals into the intracellular molecule cAMP, which is thus a 2nd messenger of extracellular events. The brain expresses nine membrane-bound AC variants, and AC5 is the dominant form in the striatum. The striatum is the input stage of the basal ganglia, a brain structure involved in reward learning, i.e. the learning of behaviors that lead to rewarding stimuli (such as food, water, sugar, etc). During reward learning, cAMP production is crucial for strengthening the synapses from cortical neurons onto the striatal principal neurons, and its formation is dependent on several neuromodulatory systems such as dopamine and acetylcholine. It is, however, not understood how AC5 is activated by transient (subsecond) changes in the neuromodulatory signals. Here we combine several computational tools, from molecular dynamics and Brownian dynamics simulations to bioinformatics approaches, to inform and constrain a kinetic model of the AC5-dependent signaling system. We use this model to show how the specific molecular properties of AC5 can detect particular combinations of co-occuring transient changes in the neuromodulatory signals which thus result in a supralinear/synergistic cAMP production. Our results also provide insights into the computational capabilities of the different AC isoforms. Long-term potentiation and depression of synaptic activity in response to stimuli is a key factor in reinforcement learning. Strengthening of the corticostriatal synapses depends on the second messenger cAMP, whose synthesis is catalysed by the enzyme adenylyl cyclase 5 (AC5), which is itself regulated by the stimulatory G alpha(olf) and inhibitory G alpha(i) proteins. AC isoforms have been suggested to act as coincidence detectors, promoting cellular responses only when convergent regulatory signals occur close in time. However, the mechanism for this is currently unclear, and seems to lie in their diverse regulation patterns. Despite attempts to isolate the ternary complex, it is not known if G alpha(olf) and G alpha(i) can bind to AC5 simultaneously, nor what activity the complex would have. Using protein structure-based molecular dynamics simulations, we show that this complex is stable and inactive. These simulations, along with Brownian dynamics simulations to estimate protein association rates constants, constrain a kinetic model that shows that the presence of this ternary inactive complex is crucial for AC5's ability to detect coincident signals, producing a synergistic increase in cAMP. These results reveal some of the prerequisites for corticostriatal synaptic plasticity, and explain recent experimental data on cAMP concentrations following receptor activation. Moreover, they provide insights into the regulatory mechanisms that control signal processing by different AC isoforms.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2019. Vol. 15, no 10, article id e1007382
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Basic Medicine
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URN: urn:nbn:se:kth:diva-266317DOI: 10.1371/journal.pcbi.1007382ISI: 000500776600040PubMedID: 31665146Scopus ID: 2-s2.0-85074411384OAI: oai:DiVA.org:kth-266317DiVA, id: diva2:1382978
Note

QC 20200107

Available from: 2020-01-07 Created: 2020-01-07 Last updated: 2020-01-07Bibliographically approved

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Hällgren Kotaleski, Jeanette

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Narzi, DanieleTrpevski, DanielNair, Anu G.Hällgren Kotaleski, Jeanette
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