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Modeling receptor induced signaling in MSNs: Interaction between molecules involved in striatal synaptic plasticity
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0002-1952-9583
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Basal Ganglia are evolutionarily conserved brain nuclei involved in several physiologically important animal behaviors like motor control and reward learning. Striatum, which is the input nuclei of basal ganglia, integrates inputs from several neurons, like cortical and thalamic glutamatergic input and local GABAergic inputs. Several neuromodulators, such as dopamine, accetylcholine and serotonin modulate the functional properties of striatal neurons. Aberrations in the intracellular signaling of these neurons lead to several debilitating neurodegenerative diseases, like Parkinson’s disease. In order to understand these aberrations we should first identify the role of different molecular players in the normal physiology.

The long term goal of this research is to understand the molecular mechanisms responsible for the integration of different neuromodulatory signals by striatal medium spiny neurons (MSN). This signal integration is known to play important role in learning. This is manifested via changes in the synaptic weights between different neurons. The group of synpases taken into consideration for the current work is the corticostriatal one, which are synapses between the cortical projection neurons and MSNs. One of the molecular processes of considerable interest is the interaction between dopaminergic and cholinergic inputs. In this thesis I have investigated the interactions between the biochemical cascades triggered by dopaminergic, cholinergic (ACh) and glutamatergic inputs to the striatal MSN. The dopamine induced signaling increases the levels of cAMP in the striatonigral MSNs. The sources of dopamine and acetylcholine are dopaminergic neurons (DAN) from midbrain and tonically active cholinergic interneurons (TAN) of striatum, respectively. A sub-second burst activity in DAN along with a simultaneous pause in TAN is a characteristic effect elicited by a salient stimulus. This, in turn, leads to a dopamine peak and, possibly, an acetylcholine (ACh) dip in striatum.

I have looked into the possibility of sensing this ACh dip and the dopamine peak at striatonigral MSNs. These neurons express D1 dopamine receptor (D1R) coupled to Golf and M4 Muscarinic receptor (M4R) coupled to Gi/o . These receptors are expressed significantly in the dendritic spines of these neurons where the Adenylate Cyclase 5 (AC5) is a point of convergence for these two signals. Golf stimulates the production of cAMP by AC5 whereas Gi/o inhibits the Golf mediated cAMP production. I have performed a kinetic-modeling exercise to explore how dopamine and ACh interacts with each other via these receptors and what are the effects on the downstream signaling events.

The results of model simulation suggest that the striatonigral MSNs are able to sense the ACh dip via M4R. They integrate the dip with the dopamine peak to activate AC5 synergistically. We also found that the ACh tone may act as a potential noise filter against noisy dopamine signals. The parameters for the G-protein GTPase activity indicate towards an important role of GTPase Activating Proteins (GAPs), like RGS, in this process. Besides this we also hypothesize that M4R may have therapeutic potential.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2014. , viii, 33 p.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2014:04
Keyword [en]
Striatal synaptic plasticity, LTP, Dopamine, Acetylcholine, Synergy, Medium spiny neurons, MSNs
National Category
Bioinformatics (Computational Biology) Neurosciences
Identifiers
URN: urn:nbn:se:kth:diva-143338ISBN: 978-91-7595-064-8 (print)OAI: oai:DiVA.org:kth-143338DiVA: diva2:706666
Presentation
2014-04-14, Fantum, Lindstadsvägen 24, KTH, Stockholm, 14:00 (English)
Opponent
Supervisors
Note

QC 20140325

Available from: 2014-03-25 Created: 2014-03-19 Last updated: 2014-03-25Bibliographically approved
List of papers
1. Can MSNs listen to the cholinergic pause via M4R?
Open this publication in new window or tab >>Can MSNs listen to the cholinergic pause via M4R?
(English)Manuscript (preprint) (Other academic)
National Category
Bioinformatics (Computational Biology) Neurosciences
Identifiers
urn:nbn:se:kth:diva-143344 (URN)
Funder
Swedish e‐Science Research Center
Note

AGN and OGA contributed equally to this study. QS 2014

Available from: 2014-03-19 Created: 2014-03-19 Last updated: 2014-03-25Bibliographically approved
2. Modeling Intracellular Signaling Underlying Striatal Function in Health and Disease
Open this publication in new window or tab >>Modeling Intracellular Signaling Underlying Striatal Function in Health and Disease
Show others...
2014 (English)In: Computational Neuroscience / [ed] Blackwell, K.T., Elsevier, 2014, Vol. 123, 277-304 p.Chapter in book (Refereed)
Abstract [en]

Striatum, which is the input nucleus of the basal ganglia, integrates cortical and thalamic glutamatergic inputs with dopaminergic afferents from the substantia nigra pars cornpacta. The combination of dopamine and glutamate strongly modulates molecular and cellular properties of striatal neurons and the strength of corticostriatal synapses. These actions are performed via intracellular signaling networks, containing several intertwined feedback loops. Understanding the role of dopamine and other neuromodulators requires the development of quantitative dynamical models for describing the intracellular signaling, in order to provide precise unambiguous descriptions and quantitative predictions. Building such models requires integration of data from multiple data sources containing information regarding the molecular interactions, the strength of these interactions, and the subcellular localization of the molecules. Due to the uncertainty, variability, and sparseness of these data, parameter estimation techniques are critical for inferring or constraining the unknown parameters, and sensitivity analysis evaluates which parameters are most critical for a given observed macroscopic behavior. Here, we briefly review the modeling approaches and tools that have been used to investigate biochemical signaling in the striatum, along with some of the models built around striatum. We also suggest a future direction for the development of such models from the, now becoming abundant, high-throughput data.

Place, publisher, year, edition, pages
Elsevier, 2014
Series
Progress in Molecular Biology and Translational Science, ISSN 1877-1173 ; 123
Keyword
DARPP32, Dopamine, Kinetic models, LTP, Medium spiny neurons, Neural data integration, Postsynaptic signaling, Striatum, Synaptic plasticity
National Category
Neurosciences Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:kth:diva-143341 (URN)10.1016/B978-0-12-397897-4.00013-9 (DOI)000333380100012 ()24560149 (PubMedID)2-s2.0-84964315450 (Scopus ID)978-0-12-397897-4 (ISBN)
Funder
Swedish e‐Science Research CenterSwedish Research Council, 2010-3149, 2010-4429NIH (National Institute of Health)
Note

QC 20140325

Available from: 2014-03-19 Created: 2014-03-19 Last updated: 2014-05-23Bibliographically approved

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Nair, Anu G.

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