Computational model for astroglial cell function in Alzheimer's disease
-
1
Tampere University of Technology, Finland
-
2
Kidney Care Center at DCI, United States
-
3
University of Jyväskylä, Finland
Neuritic plaques, consisting mostly of aggregated amyloid-β peptide, are some of the pathological findings in brains of Alzheimer's disease patients. The aggregated amyloid-β disturbs the cellular homeostasis, which can be monitored by e.g. measuring changes in the intracellular Ca2+ concentrations [Ca2+]. As an intracellular second messenger, Ca2+ functions as a mediator in transporting extracellular signals into the cell. Normally, the Ca2+ concentration in the cytosol is kept very low, but when signaling pathways are activated, oscillations of elevated Ca2+ levels can be measured. The aim of this study is to reproduce with a computational model the experimental data of the amyloid-β and serotonin induced Ca2+ oscillations in astrocytes.
To measure the effects of amyloid-β peptide aggregates and serotonin on Ca2+ oscillations, primary cortical astrocyte cultures were prepared from newborn Sprague-Dawley rat brain by growing the isolated astrocytes on coverslips in culture dishes in an incubator (37°C, 5 % CO2) for 1 - 4 weeks. Cells were then exposed to both amyloid-β peptide and serotonin. Ca2+ oscillation measurements were done using 4 μM fura-2 acetoxymethyl ester (Fura-2AM) and a monochromator-based spectrophotofluorimetric system (model RF D-4010 Deltascan; PTI, South Brunswick, NJ, U.S.A.) with dual excitation at the 340 and 380 nm wavelengths, bandpass of 2 nm, and the fluorescence emission measurements at 510 nm wavelength.
The aim of this study is to reproduce the experimental data with a computational model. Ca2+ oscillations in astrocytes can be modeled by deterministic differential equations as Lavrentovich and Hemkin have recently done in (J. Theor. Biol. 251(4), 553 - 560, 2008). In their model, three processes affecting the cytosolic [Ca2+] have been described; namely the flux of Ca2+ from/to ECM (extracellular matrix) and ER (endoplasmic reticulum), and the two feedback loops releasing Ca2+ via inositol (1,4,5)-trisphosphate receptors. In this work however, Ca2+ oscillations in astrocytes are modeled using stochastic differential equations to describe the experimentally measured Ca2+ oscillations.
In the Figure, there are stochastic Ca2+ oscillations obtained with the computational model designed for simulation of astroglial Ca2+ changes. The model makes it possible to study pathological phenomena associated with Alzheimer's disease. In particular, the model may help to clarify the basic mechanisms of Alzheimer's disease by modeling the effects of amyloid-β peptide aggregations on the important transmitter-induced intracellular Ca2+ fluctuations.
Conference:
Neuroinformatics 2008, Stockholm, Sweden, 7 Sep - 9 Sep, 2008.
Presentation Type:
Poster Presentation
Topic:
Computational Neuroscience
Citation:
Mäkiraatikka
E,
Manninen
T,
Nahata
AK,
Jalonen
TO and
Linne
M
(2008). Computational model for astroglial cell function in Alzheimer's disease.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2008.
doi: 10.3389/conf.neuro.11.2008.01.049
Copyright:
The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers.
They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.
The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.
Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.
For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.
Received:
28 Jul 2008;
Published Online:
28 Jul 2008.
*
Correspondence:
Eeva Mäkiraatikka, Tampere University of Technology, Tampere, Finland, eeva.makiraatikka@tut.fi