Figures
Abstract
Background
To better understand the complex molecular level interactions seen in the
pathogenesis of Alzheimer's disease, the results of the wet-lab and
clinical studies can be complemented by mathematical models. Astrocytes are
known to become reactive in Alzheimer's disease and their ionic
equilibrium can be disturbed by interaction of the released and accumulated
transmitters, such as serotonin, and peptides, including
amyloid- peptides
(A
). We have here studied the effects of small amounts
of A
25–35 fragments on the transmitter-induced
calcium signals in astrocytes by Fura-2AM fluorescence measurements and
running simulations of the detected calcium signals.
Methodology/Principal Findings
Intracellular calcium signals were measured in cultured rat cortical
astrocytes following additions of serotonin and glutamate, or either of
these transmitters together with A25–35.
A
25–35 increased the number of astrocytes
responding to glutamate and exceedingly increased the magnitude of the
serotonin-induced calcium signals. In addition to
A
25–35-induced effects, the contribution of
intracellular calcium stores to calcium signaling was tested. When using
higher stimulus frequency, the subsequent calcium peaks after the initial
peak were of lower amplitude. This may indicate inadequate filling of the
intracellular calcium stores between the stimuli. In order to reproduce the
experimental findings, a stochastic computational model was introduced. The
model takes into account the major mechanisms known to be involved in
calcium signaling in astrocytes. Model simulations confirm the principal
experimental findings and show the variability typical for experimental
measurements.
Conclusions/Significance
Nanomolar A25–35 alone does not cause persistent change in
the basal level of calcium in astrocytes. However, even small amounts of
A
25–35, together with transmitters, can have
substantial synergistic effects on intracellular calcium signals.
Computational modeling further helps in understanding the mechanisms
associated with intracellular calcium oscillations. Modeling the mechanisms
is important, as astrocytes have an essential role in regulating the
neuronal microenvironment of the central nervous system.
Citation: Toivari E, Manninen T, Nahata AK, Jalonen TO, Linne M-L (2011) Effects of Transmitters and Amyloid-Beta Peptide on Calcium Signals in Rat Cortical Astrocytes: Fura-2AM Measurements and Stochastic Model Simulations. PLoS ONE 6(3): e17914. https://doi.org/10.1371/journal.pone.0017914
Editor: Matjaz Perc, University of Maribor, Slovenia
Received: December 9, 2010; Accepted: February 14, 2011; Published: March 29, 2011
Copyright: © 2011 Toivari et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported in part by Tampere University of Technology Doctoral Programme (www.tut.fi), Tampere Doctoral Programme in Information Science and Engineering (TISE) (www.cs.tut.fi/tise/), the Academy of Finland, No. 213462, and 129657 (Finnish 320 Programme for Centres of Excellence in Research 2006–2011), 106030, 107694, 124615, and 126556 (www.aka.fi), Emil Aaltonen Foundation (www.emilaaltonen.fi), and Finnish Concordia Fund (www.konkordia-liitto.com). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative
disorder that leads to cognitive impairment and emotional disturbances. Symptoms
result from the degeneration of brain tissue, seen as shrinkage of certain brain
regions, which are involved in cognitive processes, learning, and memory formation
(reviewed in [1]). In addition to brain shrinkage, AD patients suffer from
accumulation of amyloid-beta (A) containing neuritic
plaques and neurofibrillary tangles (tau protein in neuronal somata), which are
considered as hallmarks of AD. Though the pathological changes in the brain can be
detected using MRI and PET imaging techniques, the exact molecular mechanisms
leading to the severe symptoms are not yet known. Early diagnosis together with a
possibility of specific targeted treatment would provide the patients with more
years of quality life.
Amyloid plaques containing aggregated A fragments have been
shown to disturb the homeostasis of intracellular calcium ions
(Ca
) and contribute to the altered
Ca
signaling in the brain cells [1]. The plaques typically consist
of 39–42 amino acid A
fragments, and the
plasma ratio of 42 and 40 amino acids long fragments
(A
42/A
40) is suggested of
being useful for identifying the risk of developing mild cognitive impairment and AD
[2], [3]. Based on the
classification of amino acids by Branden and Tooze [4], 25 amino acids out of the
total 42 have hydrophobic side chains in A
42. Therefore,
A
42 tends to aggregate easier than the shorter
A
fragments. A
42 and the shorter 11
amino acids long synthetic derivative (A
25–35) are both
fragments which are widely used in Alzheimer's disease research (see recent
studies [5]–[10]) with specifically A
25–35 having
Ca
-mediated neurotoxic properties [11], [12].
So far the in vitro studies of the effects of
A peptide on the cellular Ca
responses have failed
to give any definite answers to the mechanisms involved. Together with the longer
fragments, A
25–35 has been shown to depress hippocampal long-term
potentiation [13]
and to potentiate the long-term depression [14], both of which depend on the
increases in intracellular Ca
concentration in
neurons. A
25–35 has been shown to induce transient changes in
intracellular Ca
concentration in astrocytes [15], [16]. These effects may be
important in explaining the loss of new memory formation and learning seen in AD.
The detailed mechanisms behind the A
-induced neuronal and
glial Ca
fluctuations, as well as the changes triggered by these,
require further studies.
One of the central functions of astrocytes is gliotransmitter/neurotransmitter
release and uptake in the neuronal synaptic cleft of the tripartite synapse [17] together
with more complex regulation of the neuronal microenvironment [18]–[23]. Astrocytes thus have a vital
role in the synaptic information processing and in the metabolism of the central
nervous system. Astrocytes release transmitters and have receptors and transporters
for different neurotransmitters in their plasma membranes, such as for serotonin
(5-hydroxytryptamine; 5-HT), ATP, and glutamate [17], [24]. Astrocytes, as well as
other glial cells, use both spontaneous and stimulated variations of the
Ca concentration for intra- and intercellular signaling [25], [26]. Previous
electrophysiological and Ca
imaging studies have
shown how already micromolar concentration of 5-HT cause transient release of
Ca
from intracellular stores followed by prolonged
transmembrane inward Ca
flow [17], [27]. We here have
used rat cortical astrocytes, similarly to our earlier studies on
A
25–35 and A
1–40 [16], to study the
special effects of A
25–35 to
Ca
signals when added together with transmitters. We now show
that A
25–35 increases the initial peak of
Ca
release when added together with 5-HT, compared to the
effects of 5-HT alone.
Despite the rapid advancements in computing technology, it is currently not possible
to model mathematically the biological systems of realistic complexity over
interesting time scales by only using the molecular dynamic approach [28]. Typically,
the details of the state of the system (such as the position, orientation, and
momentum of individual particles) are excluded in the modeling of whole-cell level
phenomena. Here, we describe a model of astrocyte Ca signals as a
macroscopic flow of Ca
ions rather than as a
model of each individual Ca
channel in the
membranes. In the case of AD, abnormal Ca
signals could be among
the first hallmarks of disturbed brain function (the correlation between
Ca
and A
is reviewed in [29]). A
computational model which closely mimics the experimentally measured
Ca
signals in rat cortical astrocytes helps in understanding
the interaction of the various components of Ca
dynamics in healthy
cells versus the cells with dysfunctional metabolism.
Methods
Experimental methods and data
Ethics Statement.
Confluent primary astrocyte cultures were prepared from cortices of newborn Sprague-Dawley rat pups as previously described [30], with minor modifications. Pups were killed by decapitation according to the procedure conforming to the Public Health Service Policy on Humane Care and Use of Laboratory Animals and approved by the Albany Medical College Institutional Animal Care and Use Committee for Dr. H.K. Kimelberg, Protocol ID 006038 entitled “Neurotransmitter receptors and ion channels on astrocytes”.
Cell culture.
Primary astrocyte cultures were prepared from new-born Sprague-Dawley rat
pups. In brief, the cerebral hemispheres were removed, freed from the
meninges and mechanically dissociated using Dispase (Sigma, St. Louis, MO,
USA) into culture medium (Eagle's Medium with Earle's salts,
Gibco, U.K.) supplemented with 10% heat-inactivated horse serum (HS,
Gibco, U.K.), 25 mM sodium bicarbonate and antibiotics (penicillin and
streptomycin). Deoxyribonuclease I (Sigma, St. Louis, MO, USA) was added to
prevent cell clumping during the second extraction. Cells were grown on
coverslips in culture dishes and kept at 37°C in an air-ventilated
humidified incubator containing 5% CO. The medium
was first changed after one day and subsequently twice a week. About
95% of the cells routinely stained positively for glial fibrillary
acidic protein (GFAP+), with polyclonal rabbit anti-cow GFAP used as
the primary antibody and either rhodamine or fluorescein conjugated gamma
& light chain goat anti-rabbit IgGs as secondary antibody. The studies
were performed on cells kept for 1 to 4 weeks in culture.
Calcium imaging.
Fura-2-acetoxymethyl ester (Fura-2AM) is a membrane penetrating derivative of
the radiometric Ca indicator
Fura-2 used to measure intracellular Ca
concentrations
by fluorescence. Inside the cell, the acetoxymethyl groups in Fura-2AM are
removed by cellular esterases resulting to generate Fura-2, the
pentacarboxylate Ca
indicator. The
ratio of the emissions at 340 and 380 nm wavelengths is directly correlated
to the amount of intracellular Ca
concentration
(as presented in [17]). Calcium imaging of Fura-2AM-loaded astrocytes
was performed using a monochromator based spectrophotofluorimetric system
(Model RF D-4010 Deltascan, PTI, USA, PC computer and software together with
Nikon Diaphot microscope) with dual excitation at the 340 and 380 nm
wavelengths, bandpass of 2 nm and the fluorescence emission measurements at
510 nm wavelength. Astrocytes on the coverslips were loaded for 30 minutes
at 37°C in a HEPES-buffered Ringer's solution containing 4
M Fura-2AM (Molecular Probes, Inc., Eugine, OR). The
coverslips were then rinsed and placed in a Sykes-Moore Culture Chamber
(Bellco Biotech, Vineland, NJ, USA). Experiments were made at room
temperature. For determining the effects of transmitters, a stable baseline
for intracellular Ca
concentration
was first obtained, after which the solution was replaced normally for 30 s
by a buffer solution containing 5-HT or glutamate. After this the
transmitter was rinsed away by several successive applications of a fresh
buffer solution. Results are shown as a ratio of the emissions obtained by
the two wavelengths of 340 nm and 380 nm.
Solutions.
Solutions of the following composition were used and the chemicals were obtained from Sigma, St.Louis, MO. USA, if not otherwise stated.
- Ca
-imaging Ringer (mM): NaCl 122, KCl 3.3, MgSO
0.4, CaCl
1.3, KH
PO
1.2, HEPES 25, Glucose 10, and sucrose to balance the osmolarity to
320 mOsmol., pH 7.35–7.4.
- A
25–35 peptide (RBI, Natick, MA, USA) was first dissolved in water and then diluted in buffer solution. 10 nM, 200 nM and 1
M final concentration of the peptide was used either acutely or with incubation.
- 1 or 10
M final concentration of 5-HT HCl (for references see [17], [27]), or 50
M L-glutamate were added in the recording chamber.
The obtained experimental data together with the known components affecting
cellular Ca concentration
(presented in Figure 1)
were used to design the type of the computational model. Because of the
variability of detected Ca
levels (see
Figure 2),
stochasticity was introduced into the computational model which was
validated by the data obtained from Fura-2AM measurements.
For the explanation of model components 1–6, see text. In
short, according to general knowledge, the primary messengers pass
their effects via their respective receptors and G proteins on the
plasma membrane. Once activated, the G protein activates the
membrane-bound phospholipase C (PLC). Furthermore, active PLC
propagates its signal by cleaving a lipid molecule
phosphatidyl-inositol 4,5-bisphosphate (PIB) that is in attendance
in small quantities in the inner half of the plasma membrane lipid
bilayer. By disassociating the sugar-phosphate head of the PIB, PLC
generates two separate second messenger molecules; inositol
1,4,5-trisphosphate (IP) and
diacylglyserol (DAG). While DAG remains embedded in the plasma
membrane, hydrophilic IP
diffuses into the cytosol, binds to its receptor
(IP
R) on
ER causing Ca
liberation to cytosol.
Changes in cytosolic Ca
concentration is measured with Fura-2AM. Similar experimental
conditions (incubation for 48 hours with 200 nM
A
25–35 and an acute addition of 10
M 5-HT
at t = 180 s) were used for all curves.
Although there is variability in the measured
Ca
signals, the trend in the curves is the same.
Stochastic model for Ca
signals
Computational modeling, in general, means mathematical description of the
functional properties of the system components and the analysis of the model
predictions. One of the challenges in computational modeling is the lack of
precise experimental data for model components. In other words, a specific
experimental data set with proper statistics is needed for selecting relevant
range of values for model parameters. Validation of the model is typically done
by comparing the predicted output of the model with the experimental data. To
ensure the relevant parameter values, a computational model for
Ca signaling in astrocytes by Di Garbo et al. [31] was taken
as a reference model. The model takes into account the physiological phenomena
known to be the major contributors in the intracellular
Ca
oscillations. In summary, it describes the
Ca
concentration in cytosol as a six-component system (a
graphical illustration in Figure
1). Namely, 1) Ca
leak from/to
extracellular matrix (ECM), 2) capacitive Ca
entry (CCE) from
ECM, 3) Ca
entry via ionotropic receptors, 4)
Ca
leak from intracellular stores, such as endoplasmic
reticulum (ER), 5) storage of Ca
to ER via
sarco(endo)plasmic Ca
ATPase (SERCA)
pumps, and 6) Ca
release from ER
mediated by inositol 1,4,5-trisphosphate (IP
). The reference
model carefully addresses a widely accepted mechanism for astrocytic
Ca
increases via the canonical G protein/phospholipase C
(PLC)/IP
pathway [32] where the
IP
released into the cytosol binds to its receptor
(IP
R) on ER, the Ca
channels open, and
Ca
ions inside the ER are liberated to cytosol causing a
sharp rise in the cytosolic concentration of free
Ca
which is normally kept very low (see also [33], [34]). The
parameters used for both the reference model (deterministic; Di Garbo et al.
[31]) and
the here developed stochastic model are presented in Table 1.
The kinetics of biological processes are typically stochastic, i.e. random, in nature [28]. Therefore, the cellular functions cannot be properly understood with purely deterministic models (see, e.g., [35]–[37]) and both the intrinsic and extrinsic stochastic phenomena need to be accounted for in silico models. Intrinsic stochasticity is caused by the dynamics of the system from the random timing of individual reaction events. The importance of intrinsic stochasticity becomes obvious in systems with low numbers of molecules. However, stochasticity included in the model may not always be able to explain the large diversity observed in experimental measurements (as shown in [38]). The low numbers make individual reaction events, which change molecular numbers by one or two, more significant. At the same time the extrinsic stochasticity is caused by the system interacting with other stochastic systems in the cell or its environment. Mathematically, stochasticity means that the trajectories for each simulation are slightly different from one another and computationally intensive simulations are often required to follow the time evolution of the system dynamics. Our earlier studies [39], [40] have shown the potential of stochastic differential equations in the kinetics of signal transduction and ion channels. Mathematical analysis alone may be able to completely describe all the properties of interest in the case of simple random systems. However, mathematical analysis is not possible for more complex stochastic models, i.e. the complex stochastic models are analytically intractable.
The exact method to model chemical reactions, when diffusion is not taken into
account, is the discrete-state chemical master equation (CME, [41]).
However, the CME can rarely be solved and thus an algorithm called Gillespie
stochastic simulation algorithm (SSA, [42], [43]) has been developed. The
SSA presents an easy way to simulate the actual CME process and it is used more
and more in computational modeling studies. In many cases, the SSA is slow to
simulate and thus, we have chosen to introduce stochasticity into the reference
model [31],
[44] by
the chemical Langevin equation (CLE, [45]), that is one type of
stochastic differential equation. The CLE represents the continuous-state Markov
model approximated from the exact CME. The CLE is much faster to simulate than
the actual SSA when large volumes are considered but it can produce negative
values when low concentrations are simulated [39]. However, for the system
modeled in this study the CLE produce realistic results and can be thus used.
When making the stochastic extension of the model, we need to assume volumes for
the cytosol () and ER (
) (see Table 1 for more
information).
To describe the time-series behavior of the model, a set of equations (Equations
1–4) was introduced. ,
, and
represent
concentrations of cytosolic Ca
,
Ca
in the ER, and cytosolic
, respectively. The
fraction of active
receptors on the
ER membrane was termed
. In the stochastic
terms of Equations 1–4,
=
stands for the
Brownian motion and
. Furthermore,
represents the Avogadro's
number.
(1)
(2)
(3)
(4)
Due to the lack of fully understanding the phenomena related to CCE, the rate
regulating capacitive Ca influx was assumed
to be a nonlinear function of
, as described in
[31]:
(5)
Earlier experimental results (cited in [31]) indicated that the
transient component in cytosolic Ca concentration was
induced by the activation of the metabotropic receptor
due to stimuli/input-evoked
Ca
release from the intracellular stores, whereas the
activation of the ionotropic receptor
mediated the
sustained component (similarly to our results; see Results and Figure
3A). In the reference model by Di Garbo et al. [31], ATP has an effect on
via both ionotropic and metabotropic receptors. The same
is here assumed to 5-HT. Thus, the parts of the model (Equations 6 and 7)
describing the ATP-induced Ca
response in [31] is here
used with some modifications to activate the model for astrocytic
Ca
signaling with 5-HT and A
.
A. Fast Ca transient
and a more sustained component are seen when 10
M 5-HT is
added at t = 80 s. B. Changes in
cytosolic Ca
concentration induced by 1
M 5-HT at
t = 170 s in Ca
free
media. Fast Ca
transient
is seen but the more sustained component seen in Figure 2A is cut off. C.
Model simulations of changes in cytosolic
Ca
concentration induced by 10
M input at
t = 80 s. Fast Ca
transient
and a more sustained component are seen. D. Model
simulations of changes in cytosolic Ca
concentration induced by 1
M input at
t = 170 in simulated
Ca
free media
conditions: model rates
, and
are set to
zero. Fast Ca
transient
is seen but the more sustained component is cut off.
In this study, the rate of Ca influx, induced by
ionotropic receptors, from ECM to cytosol was modeled as in [31]:
(6)
Similarly, the activation of G protein and PLC pathways, induced
by metabotropic receptors, to promote the IP
production were
reformed from [31], [46] and modeled as:
(7)
The remaining rate terms used in Equations 1–4 were taken from [46] and are
explicitly formulated as Equations 8–16.(8)
(9)
(10)
(11)
(12)
(13)
(14)
(15)
(16)
In addition, the following initial values were used:
,
,
, and
.
Results
To specifically study how the non-aggregated A25–35 affects the
metabotropic 5-HT receptor function, we added small amyloid peptide concentrations
together with the transmitter and measured the ratio of emissions at 340 and 380 nm
in Fura-2AM loaded rat cortical astrocytes in primary cultures. In some experiments
L-glutamate was also added in aim to study the possible differences between
glutamate and 5-HT receptor activation in these cells. The ratio of emissions is
directly correlated to cytosolic Ca
concentration
. A deterministic model, introduced by Di Garbo et al. [31], was used as a
reference model to which stochasticity was introduced by CLE in aim to reproduce the
Ca
data measured with the used experimental conditions. Below
we present the results obtained by combining the Fura-2AM measurements and
computational simulations.
Effects of 5-HT on the levels of cytosolic Ca
When the experiments were performed in solutions with normal external
Ca, the addition of 5-HT every time induced a transient
peak together with a more sustained increase in
(Figures 3A and 4). When a lesser amount of 1
M 5-HT was added for 20 seconds in
Ca
free medium, a single peak was seen, indicating release
of Ca
from intracellular stores (Figure 3B). The simulation of this is seen in
Figure 3D. In Figures 3C and 3D, one
realization of the chemical Langevin equation is printed in gray while the black
traces represent the means and standard deviations for 1000 realizations. The
lack of external Ca
caused three of
the components to be restrained in the six-component computational model,
namely: 1) Ca
leak from extracellular matrix (ECM), 2) capacitive
Ca
entry from ECM, and 3) Ca
entry via
ionotropic receptors. When rates
,
, and
were set to zero
the model simulations indeed produced fast transients without any sustained
component. The model simulation closely resembled the experimental peak, except
the peak duration was found to be shorter in simulations than in experiments
(compare Figures 3B and 3D).
With external Ca
present, the
simulation (illustrated in Figure
3C) shows a sustained component which, however, is shorter than seen
in the experiments (compare Figures
3A and 3C).
Small change in cytosolic Ca
concentration is seen when 10
M 5-HT is
added at t = 180 s. 50
M glutamate
reduces the 5-HT-induced enhancement of cytosolic
Ca
concentration at t = 700 s, whereas additions of 1
M
A
25–35
do not show an increment to cytosolic Ca
concentration at t = 1050, 1100, and 1130 s.
Effects of A
25–35 on the
basal levels of cytosolic Ca
Our earlier studies [16] showed that only 36% of astrocytes responded
to A25–35 additions by transient increase in
, which returned back to baseline level after 1–4
minutes. In the present study, the mean value for the baseline
in control astrocytes was
2.39
0.40 (mean in ratio 340/380 units
s.d.; n = 32), and
2.69
0.60 (n = 8) in those astrocytes
which were similarly cultured and then incubated with 200 nM
A
25–35 for 48 h (see the baseline at
t = 0 … 180 s in Figure 2). There is no significant difference
in the baseline values of the control and A
25–35-treated
astrocytes (p = 0.098, which is
0.05; statistics were made using Anova module,
Statistica, Statsoft Inc.), indicating that A
25–35 does
not cause persistent change in the basal level of calcium in these cells.
Synergistic effects of A
25–35 and
transmitters on the levels of cytosolic Ca
The mean amplitude of increase with
simultaneous addition of 5-HT and A
25–35 was
statistically significantly different (p
0.001) from the
amplitude when 5-HT alone was added. 100% (n = 43)
of studied astrocytes, with or without A
25–35
present, responded to 10
M 5-HT with a
transient peak of increased
.
A
25–35 addition did not significantly change the
mean duration or time constant of the first Ca
peak, but
increased the peak amplitude, which reflects the magnitude of
Ca
release from intracellular stores (compare traces in
Figures 4 and 5). 1
M A
25–35, when
added simultaneously with 10
M 5-HT, caused a
significant 163% increase in the mean Ca
peak amplitude
(n = 5) from the control value of
induced by 5-HT alone (n = 13). A
lesser 75% increase was detected in cells incubated with 200 nM
A
25–35 for 48
prior to adding
5-HT (n = 6, Figure 2). Astrocytes were also incubated with 10 nM
A
25–35, but the detected 5-HT-induced changes in
were then not significantly different from the control
values.
Substantial change in cytosolic Ca
concentration due to synergistic effect of 10
M 5-HT and
1
M A
25–35
added at t = 180 s. 50
M
glutamate, added at t = 350 s, reduces the
enhancement of cytosolic Ca
concentration.
Glutamate has earlier been shown to induce increase in intracellular
Ca
[17], and
also in the present study 50
M glutamate induced
increase in intracellular Ca
in 25%
(n = 4) out of 16 astrocytes. Incubation of astrocytes with
10 nM or 200 nM A
25–35 for 48
h increased the number of cells responding to glutamate to two cells out of four
tested. When A
25–35 was added simultaneously with glutamate,
100% (n = 6) of astrocytes responded with a
Ca
increase (data not shown). Furthermore, this study
revealed another interesting interaction between intracellular
Ca
and glutamate: glutamate seems to be able to decrease
, which has first been elevated by 5-HT, and to inhibit
the Ca
-oscillations and return the
Ca
levels close to baseline (Figures 4, 5, and 6A). Glutamate may thus be able, by
activating separate metabotropic receptors, to both increase
via release from intracellular stores and influx through
L-type Ca
channels, and inhibit the
Ca
channel-mediated Ca
influx and
oscillations. This phenomenon was seen in every cell tested (in 8 control
astrocytes, 10 astrocytes incubated with 10 or 200 nM of
A
25–35, and 12 astrocytes where
A
25–35 had been added simultaneously with
glutamate). These effects of glutamate were not included in the computational
model and synergistic effects of 5-HT and glutamate with
A
peptide fragments require further testing.
A. 1 M
A
25–35
and 10
M 5-HT are
added together at t = 150 s and
t = 940 s. Glutamate is added at
t = 300 s and t = 1100 s. The
interval between the external stimuli is long enough to enable the
intracellular Ca
stores to
fill up between the stimuli. Thus, the peak amplitude of the latter peak
is not lower than the preceding one. B. Simulations of
changes in cytosolic Ca
concentration induced by 10
M external
stimuli given at t = 150 s and
t = 940 s. Model simulations reproduces the
phenomena seen in Figure
6A.
The importance of intracellular Ca
stores in
Ca
signaling
The ability of recurrent additions of the transmitter to induce a
Ca release from intracellular stores was tested using
different frequencies of stimuli. If the stimuli (simultaneous addition of
A
25–35 and 5-HT in experimental measurements) were
given to the system more frequently, the peak amplitudes of the latter
measurements were lower. This indicated the incomplete recovery from the
desensitization of the receptor or the inadequate filling of the intracellular
Ca
stores between the stimuli. However, the more sustained
components, originating from Ca
flux through
plasma membrane, were similar, regardless of the frequency of stimuli.
Simulations run with less/more frequent stimuli mimicked the experimental
measurements (compare Figures 6A,
6B and 7). Thus,
the Ca
responses in simulations indeed depend on the preceding
events. The more sustained component of Ca
release seemed to
remain both in the experimental results and simulations, regardless of the
frequencies of the stimuli. In Figures 6B and 7, one realization of the chemical Langevin equation is printed in gray
while the black traces represent the means and standard deviations for 1000
realizations.
Model simulation of changes in cytosolic
Ca
concentration induced by external stimuli. 10
M stimuli,
applied with a short interval at t = 115 s and
t = 315 s, decrease the peak amplitude of the
latter peak.
Discussion
One of the hallmarks of AD are the neuritic A plaques. It is still
an unresolved question how A
fragments start to
form aggregates and at what concentrations they begin to affect the cellular
interactions in the brain. We have here shown that even small amounts of
A
25–35 fragments in the rat cortical astrocytes can,
together with 5-HT and glutamate, induce meaningful changes in the intracellular
Ca
concentration. A
25–35 together
with 5-HT caused an enhanced first peak of intracellular
Ca
representing the release from intracellular stores mediated
by 5-HT2A receptor. The glutamate induced increase in
Ca
release from stores would most probably be mediated by a
Group I (type 1 or 5) mGluR found in cortical astrocytes [17]. The observed additional
inhibitory effect of glutamate could be the result of the activation of the group II
metabotropic glutamate receptors which are known to reduce the voltage-sensitive
Ca
currents and be potential targets for neurological disorders
(see [47],
[48]).
In this study, we used data and a computational model to characterize the
Ca transients associated with synergistic effects of
A
25–35 and transmitter 5-HT in rat cortical astrocytes.
To our knowledge, this is the first such study. In the experimental part of this
study, it was shown that 5-HT and A
25–35, when added
together, clearly increased the amplitudes of the Ca
signals. Addition of
A
25–35, 5-HT, or glutamate alone was not able to induce
that several-fold increment to the intracellular Ca
, which was seen when
A
25–35 and 5-HT were added together. The abnormal
increase in intracellular Ca
may in its turn
trigger a complex cascade of a variety of molecular events in the intracellular
signaling pathways [16], [17], [49]–[53]. The measured Ca
signals indicate the
activation of 5-HT2A receptor followed by G protein, PLC, and
IP
mediated Ca
release from
intracellular Ca
stores. An additional Ca
influx through
voltage-sensitive and -insensitive Ca
channels might be
involved, as presented in [27]. Changes in astrocytic Ca
signaling are prone to
cause widespread alterations in neuronal network function and can lead to
neurological disorders (reviewed in [54]).
In the computational part of this study, a mathematical model by Di Carbo et al.
[31], for
simulating intracellular Ca processes, was
selected to be the basis for developing a more adequate model. Other models
presenting Ca
signaling in astrocytes (such as in [55]) include the flux of
Ca
from/to ECM, pumping Ca
to ER, and
Ca
release from ER. The model selected for the present study
includes six components which affect the intracellular
Ca
concentration: 1) Ca
leak from/to ECM, 2)
capacitive Ca
entry from ECM, 3) Ca
entry via ionotropic
receptors, 4) Ca
leak from intracellular stores, such as ER, 5) storage of
Ca
to ER via SERCA pumps, and 6)
Ca
release from ER mediated by
IP
. Due to different experimental setups, some of the
components in the six-component model had to be restrained. The hypothesis about
Ca
liberation from the intracellular stores was first
experimentally verified, and then reproduced by simulations. The simulations
supported the experimental findings in both Ca
free media and with
normal extracellular Ca
containing
environment. The variability of biological signals cannot be accurately mimicked by
deterministic models alone, which justified the use of stochastic methods.
A mathematical model, presented in this study, integrates data from several
experimental sources and thus provides a way to computationally follow
Ca changes in biologically relevant conditions. Here, the
stochastic model was able to reproduce the Ca
signals seen in the
experimental Fura-2AM measurements. Potential pitfall of modeling, in general, is
the inadequate experimental data. Experiments should originally be designed also to
fulfill the demands of a modeling approach, including the need of considerable
amount of repetitions, relevant statistics, and adequate metadata. When new
components, describing cellular functions, will be added in the model, it will help
to explore further the possible mechanisms behind the measured
Ca
signals. This may advance the study of astrocytic
Ca
signals and their effects on neuronal networking in the
central nervous system, by adding information of the intracellular targets activated
by Ca
transients (studies on astrocytic
Ca
waves are reviewed in [56]). Calcium transients are known
to affect the important intracellular Ca
sensitive peptides,
such as protein kinases and phosphatases. In addition, the passage of
Ca
signals could lead to the priming of the astrocytes, thus
modifying forthcoming astrocytic responses, setting the cellular basis for
plasticity in glial cells [56]. Leissring et al. [57] have discussed the
possibility that mutations in presenilin 1 (one of the factors in familial AD
involved in the accumulation of amyloid
fragments in the
brain) may change the activity of the ER Ca
-ATPases, e.g., SERCA.
ATPases are associated with pumping the cytosolic Ca
into the ER lumen,
leading eventually to higher concentration of Ca
in ER. Amyloid
peptide accumulation may lead to higher-amplitude
[Ca
]
signals, have an
effect on other Ca
-induced release, and increase intracellular
IP
sensitivity [57]. Thus, the exceptional
cytosolic Ca
signals via ER, overfilled with
Ca
, may explain the Ca
changes detected in
the familial AD. Possible extension of the here developed stochastic model could be
the incorporation of some specific IP
R model into the
proposed model to study the role of altered IP
sensitivity on the
overall Ca
signaling.
The simulations run with our stochastic model did not take into account the
possibility that the synergistic effects of A25–35 and 5-HT
could be due to increased activation of, e.g., SERCA pumps. In addition, the pitfall
of the here introduced stochastic model is that it does not take into account
spontaneous Ca
signaling in astrocytes (modeled, e.g., in [55]). To
include these phenomena into our stochastic model would need further studies and
tuning of model parameters. Progressive inclusion of additional components could
lead to a still more realistic model of the Ca
signaling in
astrocytes. In general, a better understanding of the involvement of astrocytes in
the developing pathology of Alzheimer's disease is of great importance for the
future development of diagnosis and treatment. Early diagnosis of AD is important
for initiating treatment and for understanding the pathobiology of the disease [58].
A
-induced astrocyte activation is thought to have a critical
role in the mechanisms of neurodegeneration in AD [59], as astrocytes signal to
neurons in response to a physiological stimulus (see, e.g., [60]). The active participation of
astrocytes in synaptic processes is of utmost importance for physiology of the
nervous system [61], [62]. Studies combining experimental and computational
experiments, like the present one, are required as they may provide us novel
viewpoints and help explaining the possible mechanisms behind certain experimental
findings.
Acknowledgments
We thank professor H. K. Kimelberg (Albany Medical College, NY, USA) for providing facilities for a subset of the experiments, and C. J. Charniga for skillful technical assistance.
Author Contributions
Conceived and designed the experiments: ET TM TJ ML. Performed the experiments: ET TM AN TJ. Analyzed the data: ET TM TJ. Wrote the paper: ET TM TJ ML.
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