First cases that point at a correlation between SARS-CoV-2 infections and the development of Parkinson's disease (PD) have been reported. Currently, it is unclear if there is also a direct causal link between these diseases. To obtain first insights into a possible molecular relation between viral infections and the aggregation of α-synuclein protein into amyloid fibrils characteristic for PD, we investigated the effect of the presence of SARS-CoV-2 proteins on α-synuclein aggregation. We show, in test tube experiments, that SARS-CoV-2 spike protein (S-protein) has no effect on α-synuclein aggregation, while SARS-CoV-2 nucleocapsid protein (N-protein) considerably speeds up the aggregation process. We observe the formation of multiprotein complexes and eventually amyloid fibrils. Microinjection of N-protein in SH-SY5Y cells disturbed the α-synuclein proteostasis and increased cell death. Our results point toward direct interactions between the N-protein of SARS-CoV-2 and α-synuclein as molecular basis for the observed correlation between SARS-CoV-2 infections and Parkinsonism.
First cases that point at a correlation between SARS-CoV-2 infections and the development of Parkinson's disease (PD) have been reported. Currently, it is unclear if there is also a direct causal link between these diseases. To obtain first insights into a possible molecular relation between viral infections and the aggregation of α-synuclein protein into amyloid fibrils characteristic for PD, we investigated the effect of the presence of SARS-CoV-2 proteins on α-synuclein aggregation. We show, in test tube experiments, that SARS-CoV-2 spike protein (S-protein) has no effect on α-synuclein aggregation, while SARS-CoV-2 nucleocapsid protein (N-protein) considerably speeds up the aggregation process. We observe the formation of multiprotein complexes and eventually amyloid fibrils. Microinjection of N-protein in SH-SY5Y cells disturbed the α-synuclein proteostasis and increased cell death. Our results point toward direct interactions between the N-protein of SARS-CoV-2 and α-synuclein as molecular basis for the observed correlation between SARS-CoV-2 infections and Parkinsonism.
Entities:
Keywords:
Covid-19; Parkinson’s disease; SARS-CoV-2; amyloids; neurodegeneration; protein aggregation
Symptoms of SARS-CoV-2
infections that cause the current Covid-19
pandemic are not limited to the respiratory tract. The virus also
affects other organs and tissues. SARS-CoV-2 has been found in neurons
in different brain regions.[1,2] For many of the patients
infected with SARS-CoV-2, acute and subacute neurological complications
have been reported.[3−5] One of these complications, the loss of smell, is
a common premotor symptom in Parkinson’s disease (PD). This
symptom and the recent reports of cases of Parkinsonism in relatively
young patients after a SARS-CoV-2 infection suggests that there may
be a link between SARS-CoV-2 infections and the development of PD.[6−9]The link between viral infections and neurodegeneration is
established
for some viruses.[10−13] The most well-known example is the 1918 influenza pandemic (Spanish
flu) which coincided with an increase in encephalitis lethargica,
followed by numerous cases of post-encephalitic Parkinsonism.[14,15] In more recent times, multiple indications of a relation between
PD and viral infections have been reported.[13,16] Whether viral infections indirectly cause neurodegeneration via
the immune system or if the effect is direct is unclear.[17] Neurodegenerative diseases such as Alzheimer’s
disease (AD) and PD are protein aggregation diseases in which specific
proteins, tau and Aβ peptide in AD and α-synuclein (αS)
in PD, assemble into amyloid aggregates. Once started, the aggregation
process spreads from cell to cell and the formed aggregates and deposits
hamper brain function.[18−20] In a direct mechanism, the virus itself triggers
the protein aggregation process. The virus would thus be responsible
for the onset of the pathological protein aggregation process. Indeed,
such a direct relation has been found for Aβ peptide aggregation
(AD) in model cell lines and animals infected with herpes simplex
and respiratory syncytial virus.[21]Motivated by the first reports on a potential relation between
SARS-CoV-2 infections and the development of Parkinsonism, we set
out to investigate if there are indications that these two diseases
are molecularly linked. We investigate the direct effect of SARS-CoV-2
proteins on αS aggregation and αS proteostasis in model
systems. We show, in test tube experiments, that the SARS-Cov-2 spike
protein (S-protein) has no effect on αS aggregation, while SARS-CoV-2
nucleocapsid protein (N-protein) considerably speeds up the aggregation
process. N-protein and αS directly interact and this interaction
results in the formation of complexes that contain multiple proteins
and eventually amyloid fibrils. Microinjection of N-protein in SH-SY5Y
cells disturbed the αS proteostasis and increased cell death.
Our results suggest that the observed link between SARS-CoV-2 infection
and PD might originate from a molecular interaction between virus
protein and αS.
Results and Discussion
The N-protein
and S-protein are the most abundant, (partly) soluble
structural SARS-CoV-2 proteins with copy numbers of ∼1000 and
∼300 monomers per virus particle, respectively.[21] The net positively charged N-protein packs the
negatively charged viral genome into a higher order structure.[22] The N-protein has been assigned additional functions
during viral infection.[23] The S-protein
is anchored to the membrane where it is exposed on the virus surface
and plays a role in receptor recognition, docking, and virus entry.[24,25] The S-protein is the main target in vaccination strategies since
it induces the immune response of the infected host. The N-protein
is also considered as a target for vaccine development because in
the SARS family of viruses, the N-protein gene is more conserved and
stable than the S-protein gene.[26]Considering their abundance in infected cells, we assess if interactions
between αS and N-protein or S-protein affect the aggregation
of αS into amyloid fibrils in in vitro experiments. In these
experiments, we followed the aggregation of αS in the presence
and absence of N-protein and S-protein using Thioflavin T (ThT) fluorescence
assays. The fluorescence of the dye ThT increases upon binding to
amyloid fibrils. ThT fluorescence can therefore be used as a direct
readout for fibril formation. A key parameter in such assays is the
time to the first (visible) onset of aggregation or aggregation lag
time. This time reflects how fast aggregation prone nuclei appear
and amyloid fibrils are formed. It thus quantifies the impact of external
triggers, such as additional proteins, on the aggregation of αS.
In the absence of additional proteins, the onset of aggregation of
αS is observed at time scales >240 h (Figure a). We observe no change in the outcome of
the aggregation assay in the presence of S-protein (Figure a). Although a computational
study recently suggested binding between S-protein and αS, we
see no indication that this interaction promotes aggregation.[27] In the presence of N-protein, we see a strong
decrease in the time to the onset of aggregation which reduces to
<24 h (Figure b).
On long time scales, a transition to a second plateau is observed
in the presence of N-protein as discussed later in the text.
Figure 1
Aggregation
of αS in the absence and presence of SARS-CoV-2
proteins. (a) Aggregation assay of αS in the absence (black)
and presence (color) of S-protein. The aggregation process is followed
by recording the fluorescence of the amyloid-binding dye ThT. The
assay was performed at a NaCl concentration of 10 mM with 50 μM
αS and 0.1 μM (red), 0.5 μM (orange), and 1 μM
(blue) S-protein. The ThT fluorescence intensity (I) is normalized to the plateau value. (b) ThT-based aggregation assay
of αS in the presence of N-protein. The assay was performed
at a salt concentration of 10 mM NaCl with 50 μM αS and
0 μM (black) 0.1 μM (red), 0.5 μM (orange), 0.8
μM (green), and 1 μM (blue) N-protein. The ThT intensity
(I) is normalized to the initial plateau value. (c)
Influence of the salt concentration on aggregation lag time for N-protein
concentrations of 0.5 μM (orange), 0.8 μM (green), and
1 μM (blue) at an αS concentration of 50 μM. The
points represent the mean of three independent measurements, and error
bars show the standard deviation.
Aggregation
of αS in the absence and presence of SARS-CoV-2
proteins. (a) Aggregation assay of αS in the absence (black)
and presence (color) of S-protein. The aggregation process is followed
by recording the fluorescence of the amyloid-binding dye ThT. The
assay was performed at a NaCl concentration of 10 mM with 50 μM
αS and 0.1 μM (red), 0.5 μM (orange), and 1 μM
(blue) S-protein. The ThT fluorescence intensity (I) is normalized to the plateau value. (b) ThT-based aggregation assay
of αS in the presence of N-protein. The assay was performed
at a salt concentration of 10 mM NaCl with 50 μM αS and
0 μM (black) 0.1 μM (red), 0.5 μM (orange), 0.8
μM (green), and 1 μM (blue) N-protein. The ThT intensity
(I) is normalized to the initial plateau value. (c)
Influence of the salt concentration on aggregation lag time for N-protein
concentrations of 0.5 μM (orange), 0.8 μM (green), and
1 μM (blue) at an αS concentration of 50 μM. The
points represent the mean of three independent measurements, and error
bars show the standard deviation.We exclude that the increase in ThT fluorescence is the result
of N-protein aggregation; at identical concentrations, incubation
of N-protein alone does not increase the ThT fluorescence intensity
(see Figure S1). To quantify the change
in the onset of αS aggregation, we determine the aggregation
lag time. With increasing N-protein concentration, the αS aggregation
lag time decreases. This concentration-dependent decrease evidences
that direct interactions between αS and N-protein trigger αS
aggregation.N-protein and αS are net oppositely charged;
near neutral
pH (7.4), the calculated net charge amounts to +24e and −9e,
respectively. Electrostatic attraction is therefore likely to play
a role in the intermolecular interactions. Increasing the ionic strength
of the solution, and thus screening the electrostatic charge, indeed
increases the aggregation lag time (Figure c). However, also under higher salt conditions,
the lag time is still considerably shorter in the presence of N-protein
compared to the control. Moreover, the N-protein concentration dependence
of the decrease in the lag time is conserved. Even at the highest
salt concentration tested, the timescale at which we observe αS
aggregation do not revert to the >240 h observed for αS alone.
We therefore conclude that besides electrostatics, other attractive
forces contribute to the interaction between αS and N-protein.To obtain insights into the strength of the interaction between
αS and N-protein, we performed a microscale thermophoresis (MST)
assay. MST relies on changes in the diffusion coefficient of a particle
upon binding to a partner. In the experiment, one of the partners
needs to be fluorescently labeled and labeling the one with the lower
molecular weight provides optimal contrast. In our experiments, we
therefore fluorescently labeled αS. The concentration of fluorescently
labeled αS was kept constant and the MST response was studied
as a function of the N-protein concentration. The lower and higher
plateau in the MST signal were interpreted as free αS and αS
bound to N-protein, respectively (Figure a). We observe a sharp transition from the
unbound to bound state of αS and an EC50 of approximately
0.3 μM. The steepness of the transition indicates that binding
is cooperative.
Figure 2
Interaction between αS and N-protein. (a) Binding
curve characterizing
the interaction between αS and N-protein obtained from MST experiments.
MST data points are shown in black. The lines indicate binding with
a Hill coefficient of 1 (orange) and 4 (blue) and an EC50 of 0.3 μM. These curves serve as a guide to the eye. (b) FCS
autocorrelation curves normalized to G(t0) (where t0 = 0.001 ms) (hollow
symbols) of fluorescently labeled αS in the presence of 0 μM
(black), 0.1 μM (red), 0.3 μM (orange), 0.9 μM (green),
and 1.0 μM (blue) N-protein. Not all data points are shown for
clarity. Fits to the autocorrelation curves are visible as lines with
the corresponding color. In fitting the curves, a triplet fraction
was considered and a fast and a slow diffusing component when necessary.
(c) Fractions (f) of the slow (red) and fast (black)
diffusing components obtained from the fits to the autocorrelation
curves shown in (b). (d) Average particle brightness as a function
of the N-protein concentration. The errors bars show the standard
deviation in the observed brightness.
Interaction between αS and N-protein. (a) Binding
curve characterizing
the interaction between αS and N-protein obtained from MST experiments.
MST data points are shown in black. The lines indicate binding with
a Hill coefficient of 1 (orange) and 4 (blue) and an EC50 of 0.3 μM. These curves serve as a guide to the eye. (b) FCS
autocorrelation curves normalized to G(t0) (where t0 = 0.001 ms) (hollow
symbols) of fluorescently labeled αS in the presence of 0 μM
(black), 0.1 μM (red), 0.3 μM (orange), 0.9 μM (green),
and 1.0 μM (blue) N-protein. Not all data points are shown for
clarity. Fits to the autocorrelation curves are visible as lines with
the corresponding color. In fitting the curves, a triplet fraction
was considered and a fast and a slow diffusing component when necessary.
(c) Fractions (f) of the slow (red) and fast (black)
diffusing components obtained from the fits to the autocorrelation
curves shown in (b). (d) Average particle brightness as a function
of the N-protein concentration. The errors bars show the standard
deviation in the observed brightness.Fluorescence correlation spectroscopy (FCS) experiments were performed
to obtain first insights into the number of αS molecules in
αS/N-protein complexes. In the FCS experiment, αS was
fluorescently labeled. Upon increasing the N-protein concentration,
we observe a strong shift in the correlation curves to longer times,
indicating the formation of slow diffusing complexes (Figure b). For αS alone, the
FCS autocorrelation curve can be fitted to a single diffusing species
with a diffusion coefficient of approximately 86 μm2/s, in agreement with the expected size of the protein and earlier
findings.[28] With increasing N-protein concentration,
a second slower diffusing species with a diffusion coefficient of
approximately 27 μm2/s appears. In Figure c, we plot the fraction of
both the slow and fast diffusing species as a function of the N-protein
concentration. In agreement with the MST data, we observe a transition
from the unbound to bound state that is cooperative and an EC50 of ∼0.2 μM. Concomitant with the appearance
of the αS/N-protein complex, we observe an increase in the average
brightness of the diffusing protein complexes (Figure d). In the αS/N-protein complex, the
brightness increased by a factor of 1.8 times compared to unbound
αS. Considering that of the total αS concentration of
20 nM, only half was labeled and ignoring the possible fluorescence
quenching due to fluorophore–fluorophore interactions that
have been observed in other protein systems under certain conditions,
this indicates that on average, 3 to 4 αS proteins are present
in an αS/N-protein complex.[29] Note
that although this indicates that N-proteins accumulate αS,
the FCS experiment was performed in excess of N-protein. The aggregation
experiments were performed in excess of αS; accumulation of
even higher numbers of αS on N-protein is therefore likely.
We conclude that the decrease in αS aggregation lag time in
the presence of N-protein results from direct interactions between
the two protein species and the accumulation of αS on N-proteins.The increase in ThT fluorescence intensity during αS aggregation
in the presence of N-protein deviates from the typically observed
pattern. Instead of the typical single step nucleation and growth
process, we observe two growth steps. At longer time scales, a second,
higher, plateau in the ThT fluorescence intensity appears (Figure a). To verify that
in both plateaus the observed ThT fluorescence results from the formation
of amyloid fibrils, we performed atomic force microscopy (AFM) experiments.
We obtained samples for AFM experiments that cover both the first
and second plateau in ThT fluorescence. AFM images obtained from samples
in both plateaus in ThT fluorescence show the presence of helical
amyloid fibrils with a mean height of approximately 8 nm (Figure b,c). The AFM images,
however, indicate that the morphology of the fibrils is different
in both plateaus. In the first plateau, fibrils of two different morphologies
can be discriminated. These fibrils differ in helical periodicity.
To determine the periodicity of the helix, a discrete Fourier transform
(DFT) was performed on the images of fibrils formed in both plateaus.
We observe two clear peaks in the DFT analysis at periodicities of
approximately ≈130 and ≈90 nm (Figure d). The morphology of fibrils in the samples
obtained in the second plateau is homogeneous (Figure d). DFT analysis shows that these fibrils
have a periodicity of 130 nm (Figure d). This periodicity agrees with previous AFM and cryo-electron
microscopy studies on the structure of αS amyloid fibrils in
the absence of N-protein.[30] N-protein speeds
up the formation of αS fibrils but does not change the morphology
of fibrils observed after long time incubation.
Figure 3
Aggregation of αS
into amyloid fibrils in the presence of
N-protein. (a) Full ThT aggregation curve of αS in the presence
of N-protein (1 μM N-protein, 50 μM αS, and 50 mM
NaCl). The data are normalized to the final plateau in ThT intensity.
The colors refer to the color coding in (d). (b,c) In the AFM images,
two distinctly different fibril populations, with different morphologies,
can be discriminated. The cross sections along the length of the fibrils
(top) show that these fibrils differ in helical periodicity. (d) Discrete
Fourier analysis on fibrils obtained in the first (green) and second
(orange) plateau. In first plateau, two populations with different
periodicities (p) of ≈90 and ≈130 nm
are observed (green line). The peak at low 1/p values
is an analysis artifact. In the second plateau, fibrils with a p = 130 nm dominate the population and in the analysis,
fibrils with a periodicity p = 90 nm are no longer
visible (orange line). A total of 79 and 72 fibrils were analyzed
for the first and second plateau, respectively.
Aggregation of αS
into amyloid fibrils in the presence of
N-protein. (a) Full ThT aggregation curve of αS in the presence
of N-protein (1 μM N-protein, 50 μM αS, and 50 mM
NaCl). The data are normalized to the final plateau in ThT intensity.
The colors refer to the color coding in (d). (b,c) In the AFM images,
two distinctly different fibril populations, with different morphologies,
can be discriminated. The cross sections along the length of the fibrils
(top) show that these fibrils differ in helical periodicity. (d) Discrete
Fourier analysis on fibrils obtained in the first (green) and second
(orange) plateau. In first plateau, two populations with different
periodicities (p) of ≈90 and ≈130 nm
are observed (green line). The peak at low 1/p values
is an analysis artifact. In the second plateau, fibrils with a p = 130 nm dominate the population and in the analysis,
fibrils with a periodicity p = 90 nm are no longer
visible (orange line). A total of 79 and 72 fibrils were analyzed
for the first and second plateau, respectively.Above we have shown proof that the direct interaction between N-protein
and αS triggers αS aggregation into amyloid fibrils in
in vitro experiments. Next, we have conducted microinjection experiments
to investigate the effect of the presence of N-protein in a cellular
context. After infection, SARS-CoV N-proteins are predominantly found
in the cytoplasm.[26,31−34] From literature data, we estimate
the concentration of N-protein in infected cells to be of the order
of 500 nM.[35] The injected N-protein concentration
and injection volume were chosen to approximately result in this concentration
in the cells and to mimic concentrations expected in infections (see
the Materials and Methods).The intrinsically
disordered protein αS has been suggested
to have many functions. In the cell, αS is found on trafficking
vesicles and its main function most likely involves membrane remodeling
in membrane trafficking processes.[36−43] Bound to the membranes of vesicles, αS adopts an α-helical
conformation that can be discriminated from the unstructured protein
(or other conformational states) in Förster resonance energy
transfer (FRET) experiments.[44,45] The FRET probes used
in in vitro experiments have also been applied to identify and localize
membrane-bound αS in cells.[46] It
is thus possible to use FRET to discriminate between conformational
sub-ensembles that potentially represent different functions and thereby
gain insights into the αS proteostasis.SH-SY5Y cells
express αS and are a well-established neuronal
cell model in PD research. With these cells, two different sets of
experiments were performed. In one set, single cells were microinjected
with both FRET-labeled αS and N-protein and fixed 5 days after
injection. In a second set of experiments, the cells were injected
with FRET-labeled αS and N-protein and additional unlabeled
αS and fixed 3 days after injection. We expect that the redistribution
of αS from functional to dysfunctional states is a slow process.
We hypothesize that by either giving the cells more time or by increasing the αS
concentration, this redistribution may become visible. In these experiments,
the cells injected with only FRET-labeled αS served as a control.
After fixation, cells were counterstained with 4′,6-diamidino-2-phenylindole
(DAPI) and imaged using a confocal fluorescence microscope.Compared to the control where approximately 10% rounded up/dead
cells are observed, we find approximately double the amount of dead
cells after microinjection of N-protein. Typical images of the surviving
injected cells are presented in Figure a. In the control, we see the previously reported distribution
of αS between a high FRET vesicle-bound and a low FRET cytosolic
αS population.[46] Vesicle-bound αS
is clearly present in orange (high FRET) fluorescent puncta, while
cytosolic αS is visible as a spread-out green (low FRET) background.
The overall appearance of the FRET signal from cells that were co-injected
with N-protein is very similar, both high FRET fluorescent puncta
and a low FRET spread-out cytosolic signal can be found. However,
in the cells that were microinjected with N-protein, we observe a
less high FRET (orange) signal compared to the control group (Figure a). This indicates
that in the presence of N-protein, the αS proteostasis is disturbed
resulting in less vesicle-bound αS.
Figure 4
Distribution of αS
in SH-SY5Y cells is affected by N-protein.
(a) FRET images of cells microinjected with the αS FRET probe.
The color coding represents EFRET (green:
low EFRET; yellow: mid EFRET; and orange: high EFRET). The cell nucleus is counterstained with DAPI and visible in blue.
A representative image of cells co-injected with N-protein and the
αS FRET probe is shown on the left, and the control cells on
the right were only injected with the αS FRET-probe. (b) Distribution
of average FRET efficiencies of αS per image for all cells injected
with N-protein (red) and control cells (black). The cumulative histograms
contain data from at least 80 images for both the control and the
N-protein-injected samples. The average FRET efficiency of αS
in cells injected with N-protein is shifted to lower EFRET values.
Distribution of αS
in SH-SY5Y cells is affected by N-protein.
(a) FRET images of cells microinjected with the αS FRET probe.
The color coding represents EFRET (green:
low EFRET; yellow: mid EFRET; and orange: high EFRET). The cell nucleus is counterstained with DAPI and visible in blue.
A representative image of cells co-injected with N-protein and the
αS FRET probe is shown on the left, and the control cells on
the right were only injected with the αS FRET-probe. (b) Distribution
of average FRET efficiencies of αS per image for all cells injected
with N-protein (red) and control cells (black). The cumulative histograms
contain data from at least 80 images for both the control and the
N-protein-injected samples. The average FRET efficiency of αS
in cells injected with N-protein is shifted to lower EFRET values.To substantiate the visual
impression that in the presence of N-protein
an overall average lower FRET value is observed, we estimated the
αS FRET efficiency [EFRET = intensity
acceptor/(intensity donor + intensity acceptor)] averaged over all
pixels for each image made (Materials and Methods). Subsequently, we plotted cumulative histograms for the averaged
αS FRET efficiency per image for the N-protein-injected cells
together with the controls (see Figure S2). The histograms obtained for 3 and 5 days after microinjection
agree well. For both sets of experiments, the distribution of the
αS FRET efficiencies for the N-protein-injected cells is shifted
to lower values compared to the control. For the control samples,
the mean αS FRET efficiencies quantitatively agree (see Figure S2). The width of the distribution is
slightly enhanced for the control data obtained 5 days after microinjection.
The good agreement between the data sets justifies accumulation of
the data. In Figure b, we show the cumulative distribution of FRET efficiencies of αS
in all control cells and all cells injected with N-protein. Compared
to the control, the FRET efficiency distribution of αS in cells
injected with N-protein is systematically shifted to lower values.
Our data show that the presence of N-protein results in redistribution
of αS between (dis)functional conformational states. In vitro
experiments show that the observed change in FRET efficiency does
not result from a direct interaction between the N-terminus of αS
and N-protein. Even in the presence of excess N-protein where we expect
all αS to be bound, we do not observe a change in FRET efficiency
of the FRET-labeled αS compared to the control (see Figure S3). The N-protein does apparently not
interact with αS in the FRET-labeled N-terminal region or this
binding does not induce measurable conformational changes in αS.In summary, the in vitro experiments on recombinantly expressed
proteins show that SARS-CoV-2 S-protein does not affect the aggregation
of αS into amyloid fibrils. The SARS-CoV-2 N-protein, however,
very effectively decreases the time to the onset of αS aggregation.
Additionally, the aggregation process in the presence of N-protein
differs from the aggregation process of αS alone. In the presence
of N-protein, aggregation of αS proceeds in two steps, represented
by two plateaus in the ThT fluorescence. The analysis of AFM images
of fibrils shows that two populations of fibrils with a helical periodicity
of approximately 90 and 130 nm are present during the first plateau
phase. Only a single population of fibrils with a helical periodicity
of 130 nm is found in the second plateau. The fibrils with the smaller
helical periodicity are no longer observed. Although aggregation of
αS in the presence of N-protein proceeds in two steps, first
fibril nucleation is fast. The first plateau in the ThT fluorescence
is found at a relatively low ThT intensity which indicates that the
produced fibril mass is not very high. The fibrils formed in the first
phase trigger the formation of or conversion to a second, thermodynamically
more stable, fibril polymorph. The higher stability of this polymorph
results in an increase in fibril mass and a plateau of higher ThT
intensity. Note that the time scales on which the second polymorph
appears are still fast compared to amyloid fibril formation in the
absence of N-protein.The MST and FCS data show that there is
a direct interaction between
N-protein and αS. The binding of the αS to the net positively
charged N-protein appears to be mediated by attractive electrostatic
interactions. This indicates that the interaction involves the negatively
charged C-terminus of αS. The absence of a change in the FRET
efficiency of the αS FRET probe confirms that the interaction
with the N-protein is likely mediated via the C-terminal region or
the aggregation-prone central NAC region of αS. In solution,
electrostatic repulsion between net negatively charged αS proteins
prevents their aggregation. Charge compensation due to binding to
N-protein not only exposes the aggregation-prone NAC region of αS
but also eliminates electrostatic repulsion of other αS proteins.
Our data also show that the complexes contain multiple αS proteins.
The close proximity of multiple αS proteins in the complex in
an aggregation-prone conformation potentially facilitates the formation
of a nucleus that triggers further aggregation and thus decreases
the time to the onset of aggregation.[47]Even in the complex environment of the cell, we see clear
signs
that the presence of the N-protein markedly affects αS proteostasis.
In the cell, αS exists in at least two different conformational
sub-ensembles. The presence of the N-protein results in a change in
the FRET efficiency distribution and hence in either a change in the
population of microinjected FRET-labeled αS sub-ensembles or
in the appearance of a new conformation. In the microinjection experiments
on cells, the concentration of N-protein is low compared to the concentration
of αS. It is therefore rather remarkable that we can detect
a clear shift in the distribution of the αS FRET efficiencies.The presence of N-protein indirectly affects the FRET efficiency
of the αS FRET probe by disturbing αS proteostasis. The
affinity of αS for N-protein is of the same order of magnitude
or higher as the affinity reported for other αS interactions.[48−50] Therefore, the N-protein will compete with other αS-binding
partners for interactions inside the cell. For reliable cellular performance,
protein interaction networks must be robust. Small changes and additional
binding partners are therefore not expected to easily disturb interaction
networks. We, however, do see a clear redistribution of αS over
(dis)functional states even at the rather short time scales studied.
The observed increase in the fraction of images containing dead cells
further supports the idea of an imbalance in the cells proteostasis
after injection with N-protein. We cannot confirm that this imbalance
is the result of αS aggregation and the presence of amyloid
fibrils in the cells injected with N-protein, although we observe
elongated and fibril mesh-like structures. Considering that PD typically
develops on very long time scales, the absence of fibrils in the microinjected
cells would not be surprising.
Conclusions
We have identified a
SARS-CoV-2 protein that induces the aggregation
of αS in the test tube. In the initial interaction between the
SARS-CoV-2 N-protein and αS, multiprotein complexes are formed.
In the presence of N-protein, the onset of αS aggregation into
amyloid fibrils is strongly accelerated, indicating that N-protein
facilitates the formation of a critical nucleus for aggregation. Fibril
formation is not only faster but it also proceeds in an unusual two-step
process. In cells, the presence of N-protein changes the distribution
of αS over different conformations that likely represent different
functions at already short time scales. Disturbance of αS proteostasis
might be a first step toward nucleation of fibrils. Our results point
toward a direct interaction between the N-protein of SARS-CoV-2 and
αS as a molecular basis for the observed relations between virus
infections and Parkinsonism. The observed molecular interactions thus
suggest that SARS-CoV-2 infections may have long-term implications
and that caution is required in considering N-protein as an alternative
target in vaccination strategies.
Materials
and Methods
αS Production
Expression of recombinant human
αS, the 140C mutant αS(140C) with a single alanine to
cysteine substitution at residue 140 and the double cysteine mutant
αS(9C/69C), was performed in Escherichia coli B121 (DE3) using the pT7-7-based expression system. Details on the
purification procedure are described elsewhere.[51]
Preparation of Labeled αS
To visualize the microinjected
αS in cells, the αS(9C/69C) was labeled with a FRET pair
as described before.[46] In short, the cysteines
in the αS(9C/69C) were reduced with dithiothreitol (DTT). After
removal of DTT, an equimolar concentration of the maleimide derivative
of AF488 was added to 0.5 mL of 200 μM αS(9C/69C) and
incubated for 1 h at room temperature. To remove unreacted dye or
DTT, a Zeba Spin desalting column (Pierce Biotechnology) was used.
The labeled protein was applied to a Thiopropyl Sepharose 6B column
(GE Healthcare Life Sciences) to remove double-labeled protein. Column-bound
single-labeled and/or unlabeled αS was eluted using 10–15
mL of 10 mM Tris–HCl, pH 7.4 buffer, containing β-mercaptoethanol.
Subsequently, a 2–3× molar excess of maleimide-functionalized
AF568 was added. After incubation for 1 h at room temperature, free
dye was removed using two desalting steps and the solution was filtered
through a Microcon YM100 filter (Millipore, Bedford, MA). In the main
text, the FRET-labeled αS(9C/69C) protein is referred to as
the αS FRET probe. Single-labeled αS was prepared using
the αS140C cysteine mutant which was incubated with a 2–3×
molar excess of AF488 or AF647 maleimide. The free dye was removed
using the protocol mentioned above.
Aggregation Assays
The SARS-CoV-2 S-protein was obtained
commercially (10549-CV-100, R&D systems, UK). The SARS-CoV-2 N-protein
was obtained commercially (PKSR030485, Elabscience, US) and for additional
control experiments, it was also recombinantly produced in our laboratory
following the procedure mentioned in ref 52.[52] Both the N-protein and αS have been reported to phase-separate
into liquid condensates at high concentrations. In phase contrast
microscopy, we observe no signs of phase separation at the protein
concentrations and buffer conditions used here.In the aggregation
assays, 50 μM αS was incubated with the commercially obtained
SARS-CoV-2 N-protein and S-protein at the concentrations specified
in the main text, 20 mM Tris buffer (Sigma-Aldrich, UK), pH = 7.4,
5 μM ThT (Fluka, Sigma-Aldrich, UK), and different concentrations
of NaCl (Sigma-Aldrich, USA) as mentioned in the main text. The aggregations
were performed in a 96-well half-area clear flat-bottom polystyrene
NBS (low bind) microplate (3881, Corning, US) while shaking at 500
rpm and 37 °C. To follow the formation of amyloid fibrils, the
increase in ThT fluorescence was monitored using a plate reader (Infinite
200 Pro, Tecan Ltd., Switzerland). The ThT dye was excited at 446
nm and the fluorescence signal was measured at 485 nm every 10 min.
Samples were prepared in 3–5 replicates of 50 μL. The
lag time is defined as the time point at which a twofold increase
in the fluorescence intensity compared to the initial intensity value
(baseline) is observed. To verify reproducibility of the αS
aggregation data, experiments were performed with N-protein from different
sources. We observe no differences in the decrease in the αS
aggregation lag time between different batches of commercially obtained
N-protein and between the commercially and in house-produced N-protein
(Figure S4).
Microscale Thermophoresis
The binding between αS
and N-protein was studied using a Monolith NT.115 (NanoTemperTechnologies
GmbH, Germany) MST system. The thermophoretic movement was monitored
at a constant 20 nM concentration of αS140C-AF488 and a dilution
series of concentrations of N-protein. Samples were prepared in 20
mM Tris–HCl, pH 7.4, and 10 mM NaCl and transferred to capillaries
(Standard treated, NanoTemper Technologies GmbH, Germany); measurements
were performed at 37 °C with a constant blue LED power of 20%
and at MST infrared laser powers of 40% to induce thermophoretic motion.
For each capillary, the infrared laser was switched on 10 s after
the start of the measurement for a 30 s period, followed by another
10 s period with a turned-off infrared laser to record the back diffusion.
Data were analyzed with the MO. Affinity Analysis software.
Fluorescence
Microscopy and FCS
Fluorescence images
were obtained on a laser scanning confocal microscope (MicroTime 200
with a FlimBee scanner, PicioQuant, Germany). To excite either DAPI-
or FRET-labeled αS, sequential 405 and 485 nm laser excitation
in combination with a dichroic mirror (ZT405/485rpc-UF3, Chroma, USA)
was used. A UPlanSApo, 60×, 1.2 NA objective (Olympus, Japan)
was used for imaging. Emission was detected with single photon-counting
modules (SPCM-AQRH-15, Excelitas, Canada). DAPI emission was detected
via a bandpass filter (F02-447/60-25, Semrock, USA), emission from
the FRET pair via a 488 long pass emission filter (LP02-488RU-25,
Semrock, USA). The FRET signal was further split by a 585 nm dichroic
beam splitter (T585lpxr, Chroma, USA) into a green channel (bandpass
FF01-520/35-25, Semrock, USA) for detection of the FRET-donor signal
and a red channel (longpass BA590, Olympus, Japan) for detection of
the FRET-acceptor signal. Fluorescence intensity images were exported
as raw data and used for image analysis and visualization purposes.The FCS experiments were performed on the same setup. For the FCS
experiments, samples were prepared containing 10 nM αS140C-AF647,
10 nM αS (total of 20 nM αS), and a range of N-protein
concentrations in 20 mM Tris buffer, pH 7.4. To excite AF647-labeled
αS, a 640 nm laser was used. Excitation light was reflected
toward the sample, and emission was separated from excitation light
using a dichroic mirror (ZT488/640rpc-UF3, Chroma, USA). The emission
was further filtered spectrally by a 690 nm bandpass. Before detection,
the emission was filtered spatially by a 100 μm pinhole. Autocorrelation
curves were calculated and analyzed using the SymPhoTime 64 software.
A diffusion model that includes the triplet state population was used
to fit the data. For each experimental condition, 10 measurements
with a duration of 10 s were recorded and analyzed.
Atomic Force
Microscopy
A 10 μL volume of the
five times diluted aggregated sample (initial αS concentration
= 50 μM and N-protein concentration = 0.2–1 μM)
was deposited onto freshly cleaved mica (Muscovite mica, V-1quality,
EMS, US) and left to rest for 5 min. Then, the sample was carefully
washed four times with 20 μL of demineralized water (Milli-Q)
and gently dried under a low flow of nitrogen gas. AFM images were
acquired using a BioScope Catalyst (Bruker, US) in the soft tapping
mode using a silicon probe, NSC36 tip B with a force constant of 1.75
N/m (MikroMasch, Bulgaria). Images were captured with a resolution
of 512 × 512 (10 μm × 10 μm) pixels per image
at a scan rate of 0.2 to 0.5 Hz. AFM images were processed with the
scanning probe image processor (SPIP, Image Metrology, Denmark) and
the Nanoscope Analysis (Bruker, US) packages. Fibril morphology was
analyzed using a custom fibril analysis Matlab script adapted from
the FiberApp package.[53]
Fluorescence
Spectroscopy
A Varian Eclipse spectrofluorometer
was used to record bulk emission spectra of the FRET-labeled αS(9C/69C)
(500 nM) and SARS CoV-2 N-protein (5 μM) mixtures in 1×
PBS buffer. The samples were pipetted into a 3 mm quartz cuvette and
excited at 488 nm wavelength, and emission was collected from 500
to 700 nm, with a slit width of 5 nm both for excitation and emission.
Cell Culture, Microinjection, and Nuclear Counterstaining
SH-SY5Y cells (ATCC, USA) were grown in proliferation medium (DMEM-F12
GlutaMAX + 10% heat inactivated FBS + 1% non-essential amino acids
+ 10 mM HEPES buffer + 1% penicillin/streptomycin; Gibco, Invitrogen,
USA). For microinjection, the cells were not differentiated, they
were seeded on glass bottom μ-dishes with a cell location grid
(grid-50, 35 mm, ibidi, Germany). Dishes in which the cell confluency
reached 70 to 90% were used for microinjection.The microinjections
were performed as described before.[46] In
short, the microinjections were performed using a FemtoJet (Eppendorf,
Germany), equipped with a manual hydraulic 3D micromanipulator (Narishige,
Japan). For injection, UV-O3-cleaned glass micropipettes
with an inner diameter of approximately 400 nm (WPI, USA) were used.
For microinjection, the following concentrations of proteins in PBS
were used, 500 nM FRET-labeled αS(9C/69C) for 5 days of incubation,
500 nM FRET-labeled αS(9C/69C) and 20 μM αS for
3 days of incubation, with and without 500 nM N-protein. The prepared
solutions were used to backfill the glass micropipettes. For injection,
the following settings were used: an injection pressure of 150 hPa,
a constant pressure of 15 hPa, and a duration of the injection of
0.1 s. During injections, the sample was observed on a Nikon TE2000
microscope (Nikon, Japan).After microinjection, the cells were
incubated for either 3 or
5 days. Subsequently, the samples were washed with PBS (3×) and
fixed in 3.7% paraformaldehyde/PBS solution for 10 min at room temperature,
followed by an additional washing step with PBS. The cell nuclei were
counterstained with DAPI at a final concentration of 300 nM for 10
min.
Analysis of Cell Images
To estimate the FRET efficiency,
we first applied a threshold to the recorded fluorescence intensity
images. Only intensities exceeding the mean intensity + 3 × SD
of each image were taken into account for the analysis of the FRET
efficiencies. This thresholding was used to exclude background and
noise from the analysis. From the thresholded FRET donor and acceptor
fluorescence images, the EFRET value per
pixel was estimated as the ratio between intensity in the FRET acceptor
channel divided by the sum of the intensities in the FRET donor and
FRET acceptor channels. Note that these FRET efficiency values are
estimates. We did not correct for acceptor cross-excitation and donor
bleed through in the acceptor channel since we only focus on differences
within an image and changes between conditions. The mean FRET efficiency
of all pixels in an image is represented as a single count in the
cumulative histograms.
Authors: Monique H Verheije; Marne C Hagemeijer; Mustafa Ulasli; Fulvio Reggiori; Peter J M Rottier; Paul S Masters; Cornelis A M de Haan Journal: J Virol Date: 2010-08-25 Impact factor: 5.103
Authors: Jaehwan You; Brian K Dove; Luis Enjuanes; Marta L DeDiego; Enrique Alvarez; Gareth Howell; Paul Heinen; Maria Zambon; Julian A Hiscox Journal: J Gen Virol Date: 2005-12 Impact factor: 3.891
Authors: Raymond R R Rowland; Vinita Chauhan; Ying Fang; Andrew Pekosz; Maureen Kerrigan; Miriam D Burton Journal: J Virol Date: 2005-09 Impact factor: 5.103
Authors: Mohammad A A Fakhree; Niels Zijlstra; Christian C Raiss; Carolus J Siero; Heinrich Grabmayr; Andreas R Bausch; Christian Blum; Mireille M A E Claessens Journal: Sci Rep Date: 2016-08-01 Impact factor: 4.379
Authors: Theodora Myrto Perdikari; Anastasia C Murthy; Veronica H Ryan; Scott Watters; Mandar T Naik; Nicolas L Fawzi Journal: EMBO J Date: 2020-12-04 Impact factor: 14.012
Authors: Alexander Grotemeyer; Rhonda Leah McFleder; Jingjing Wu; Jörg Wischhusen; Chi Wang Ip Journal: Front Immunol Date: 2022-05-18 Impact factor: 8.786