Martina Banchelli1, Roberta Cascella2, Cristiano D'Andrea1, Giovanni La Penna3,4, Mai Suan Li5,6, Fabrizio Machetti3,7, Paolo Matteini1, Silvia Pizzanelli8. 1. National Research Council of Italy, Institute of Applied Physics "Nello Carrara", Sesto Fiorentino, I-50019 FI, Italy. 2. University of Florence, Department of Experimental and Clinical Biomedical Sciences, I-50134 Firenze, Italy. 3. National Research Council of Italy (CNR), Institute of Chemistry of Organometallic Compounds (ICCOM), Sesto Fiorentino, I-50019 FI, Italy. 4. National Institute for Nuclear Physics (INFN), Section of Roma-Tor Vergata, I-00133 Roma, Italy. 5. Institute of Physics, Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland. 6. Institute for Computational Science and Technology, 6 Quarter, Linh Trung Ward, Thu Duc District, 700000 Ho Chi Minh City, Vietnam. 7. University of Florence, Department of Chemistry "Ugo Schiff", Sesto Fiorentino, I-50019 FI, Italy. 8. National Research Council of Italy (CNR), Institute of Chemistry of Organometallic Compounds (ICCOM), I-56124 Pisa, Italy.
Abstract
Structural models of the toxic species involved in the development of Alzheimer's disease are of utmost importance to understand the molecular mechanism and to describe early biomarkers of the disease. Among toxic species, soluble oligomers of amyloid-β (Aβ) peptides are particularly important, because they are responsible for spreading cell damages over brain regions, thus rapidly impairing brain functions. In this work we obtain structural information on a carefully prepared Aβ(1-42) sample, representing a toxic state for cell cultures, by combining electron spin resonance spectroscopy and computational models. We exploited the binding of Cu2+ to Aβ(1-42) and used copper as a probe for estimating Cu-Cu distances in the oligomers by applying double electron-electron resonance (DEER) pulse sequence. The DEER trace of this sample displays a unique feature that fits well with structural models of oligomers formed by Cu-cross-linked peptide dimers. Because Cu is bound to the Aβ(1-42) N-terminus, for the first time structural constraints that are missing in reported studies are provided at physiological conditions for the Aβ N-termini. These constraints suggest the Aβ(1-42) dimer as the building block of soluble oligomers, thus changing the scenario for any kinetic model of Aβ(1-42) aggregation.
Structural models of the toxic species involved in the development of Alzheimer's disease are of utmost importance to understand the molecular mechanism and to describe early biomarkers of the disease. Among toxic species, soluble oligomers of amyloid-β (Aβ) peptides are particularly important, because they are responsible for spreading cell damages over brain regions, thus rapidly impairing brain functions. In this work we obtain structural information on a carefully prepared Aβ(1-42) sample, representing a toxic state for cell cultures, by combining electron spin resonance spectroscopy and computational models. We exploited the binding of Cu2+ to Aβ(1-42) and used copper as a probe for estimating Cu-Cu distances in the oligomers by applying double electron-electron resonance (DEER) pulse sequence. The DEER trace of this sample displays a unique feature that fits well with structural models of oligomers formed by Cu-cross-linked peptide dimers. Because Cu is bound to the Aβ(1-42) N-terminus, for the first time structural constraints that are missing in reported studies are provided at physiological conditions for the Aβ N-termini. These constraints suggest the Aβ(1-42) dimer as the building block of soluble oligomers, thus changing the scenario for any kinetic model of Aβ(1-42) aggregation.
Alzheimer’s
Disease (AD) is the most representative form
of dementia in humans. The disease is associated with cognitive degradation
caused by neuron death. The most investigated molecular event associated
with cell death is the aggregation of amyloid-β (Aβ, hereafter)
peptides to form extracellular fibrils.[1−6] Aβ peptides are the byproduct of amyloid precursor protein
(APP).[7] The relative abundance of amyloid
peptides in both normal subjects and AD patients is still debated.[8,9] Recent analyses reported the ranking of abundance as Aβ(4-42)
∼ Aβ(1-42) > Aβ(1-40), with strong indications
of Aβ(4-42) peptide as the most abundant in AD patients (see
ref (10) and discussion
therein). Most of the in vitro studies, however,
are still concentrated on Aβ(1-42).The short-living monomeric
form of any Aβ species is an intrinsically
disordered protein, as definitely shown by nuclear magnetic resonance
(NMR)[11] and Förster resonance energy
transfer (FRET)[12] experiments. Monomers
rapidly form relatively soluble oligomers, then highly ordered insoluble
protofibrils, and eventually extended fibrils and plaques.[13,14] Soluble oligomers are toxic,[2,15−21] because they induce membrane disorder and pores,[22,23] affect membrane lipid order and permeability,[24,25] inhibit hippocampal long-term potentiation,[2] induce τ hyperphosphorilation and cytoskeleton changes,[26] and interact with cell receptors.[27,28] The Aβ dimers already show neurotoxicity.[29−31] The characterization
of Aβ oligomers is crucial to understand their role as diffusible
toxic species before the late aggregation process occurs.[32−36] Aβ oligomers are, therefore, early biomarkers of AD.Metal ions such as zinc, copper, and iron are found at high concentrations
in fibrils and plaques extracted from the AD-affected area of the
brain.[37−41] Metal ions interact with APP and Aβ, and complexes between
metal ions and Aβ are potentially important species before the
aggregation of Aβ occurs. In addition to its biological relevance,
the affinity of magnetic ions, like Cu2+, for Aβ
peptides can be used to probe structural features characteristic of
the oligomerization state of Aβ.In this work we combined
extended molecular models[42] that have been
used to explain ion mobility mass spectrometry
(IM-MS) data[43] and oxidative pathways,[44] with advanced electron spin resonance (ESR)
techniques, like double electron–electron resonance (DEER),
to estimate Cu–Cu distance distribution in Cu–Aβ(1-42)
oligomers. Copper ions are used as ancillary magnetic probes to address
oligomer structure.The 1:1 Cu–Aβ(1-42) complex
is suitable to DEER measurements
irrespective of the aggregation state. The possibility to observe
changes in DEER measurement with incubation time, concentration, and
other conditions is extremely important to monitor the change of Cu–Cu
distance with the aggregation state. Soluble compact oligomers are
observed by IM-MS as species coexisting with protofibrils and fibrils.
Indeed, according to computational models consistent with the IM-MS
data of soluble oligomers, the minimal distance between Cu2+ ions in compact dimers and tetramers is around 2 nm. The shape of
the Cu–Cu distance distribution can in theory discriminate
between globular and shaped oligomers, the latter behaving as template
protofibrils and inducing the formation of elongated fibrils. Globular
toxic oligomers are supposed to be off-pathway to elongated protofibrils,
and they are more suitable to diffuse in the cerebrospinal fluid compared
to larger aggregates, thus providing a mechanism for the propagation
of toxicity in the central nervous system.Recently, a reproducible
protocol for isolating toxic globular
oligomers[45] has been applied to spectroscopic
investigations.[46] This study shows that
by properly tuning sample preparation, specific properties of samples
that represent the AD toxic agents can be investigated. The oligomers
representative of toxic state are indicated as A+. Surface enhanced
Raman spectroscopy (SERS) allows a characterization of this toxic
state, correlated with atomic force microscopy (AFM) approximate measurements
of oligomers’ sizes. In this work, we report DEER experiments
probing Cu2+ centers. Experiments are performed on Aβ
samples prepared as in previous studies, apart from the addition of
Cu2+ in conditions that do not perturb the morphology of
the A+ toxic state.While electron spin echo envelope modulation
(ESEEM) measurements
have been reported for Cu–Aβ models,[47] the DEER experiment has been performed only on different
systems of biological interest.[48,49] The Cu complex of the
prion N-terminus (octarepeat) binds, in humans, up to 4 Cu2+ ions. Each of the 4 N-terminal repeats PHGGGWGQ binds one Cu ion.
This system has been widely investigated with ESEEM experiments,[50] and only recently, DEER experiments were performed
on prion complexes.[51] The Cu,Zn-superoxidedismutase
(Cu,Zn-SOD) enzyme has also been investigated, because it is dimeric
in water solution at physiological conditions.[52] Therefore, the present work describes, for the first time,
a DEER experiment for Cu–Aβ(1-42) oligomers.
Results and Discussion
According to our previous work,[46] where
the conditions of oligomer formation were tightly controlled, we prepared
two samples displaying different aggregation pathways: sample 1, producing cytotoxic oligomers[45] (indicated as A+) and slowly evolving into less toxic amorphous
aggregates (indicated as A−); sample 2, constituted
by protofibrils slowly evolving into mature fibrils. In the former
sample, Cu–Aβ(1-42) concentration is 25 μM, whereas
in the latter, it is 75 μM. The preparation of the samples traces that
reported
in ref (46), and it
is described, along with the techniques used in this work, in the Materials and Methods. In this work the procedure
adopted in order to add Cu2+ ions to the peptide minimizes
the perturbation of the peptide behavior (see Materials
and Methods).The morphology of both samples (Figure b,d) is identical
to that displayed by a
Cu-free sample[46] (Figure c,e). In particular, the cross section profiles
reveal height values of 4.4 ± 2.4 nm for the oligomers, in agreement
with the values observed in the Cu-free samples. Sample 2 contains small fibrils together with small irregular particles (Figure d), a picture
that is consistent with the
protofibril stage where large fibrils are not yet the dominant aggregated
form. In the absence of Cu, protofibrils are more clearly the dominant
form (Figure e). The
presence of the small irregular particles in sample 2 is in line with previous observations showing that the addition
of Cu to Aβ(1-42) favors amorphous aggregates.[53,54] The comparison between images of samples with and without Cu shows
that the amount of AFM visible particles is lower with Cu than in
the absence of Cu at the same incubation time. This is consistent
with the low aggregation rate of monomers observed in the 1:1 Cu–Aβ(1-42)
ratio compared to Cu-free Aβ.[53] The
presence of significant amounts of soluble monomers and oligomers
is therefore expected for 1:1 Cu–Aβ(1-42) even at long
incubation times (48 h).
Figure 1
AFM images and cross section profiles (graphs)
along the lines
drawn on the corresponding images: (a) PBS solution only; (b) Aβ(1-42)
oligomers (A+) with Cu2+ (sample 1, 25 μM
1:1 Aβ(1-42)–Cu molar ratio), (c) same sample with no
Cu; (d) Aβ(1-42) fibrils with Cu2+ (sample 2, 75 μM 1:1 Aβ(1-42)–Cu molar ratio),
(e) same sample with no Cu.
AFM images and cross section profiles (graphs)
along the lines
drawn on the corresponding images: (a) PBS solution only; (b) Aβ(1-42)
oligomers (A+) with Cu2+ (sample 1, 25 μM
1:1 Aβ(1-42)–Cu molar ratio), (c) same sample with no
Cu; (d) Aβ(1-42) fibrils with Cu2+ (sample 2, 75 μM 1:1 Aβ(1-42)–Cu molar ratio),
(e) same sample with no Cu.In order to gain insight into copper coordination, the X-band continuous
wave spectra of sample 1 were recorded along with incubation time.
Because copper coordination depends on pH, the pH of sample 1 was also measured, and spectra at different pH values were
collected (see Materials and Methods for details).
These spectra are displayed in Figure , with panels A, B, and C showing those recorded at
time zero and after 24 and 48 h of incubation, respectively. The spectra
recorded at time zero represent the monomeric references. The pH measured
on the original samples after the three incubation times is equal
to 7.7–7.8. This value is slightly shifted compared to that
expected for the used PBS buffer (7.4) and does not depend on the
incubation time. It is due to the NaOH added before PBS addition in
order to start with a monomeric state (see Materials
and Methods).
Figure 2
X-band CW ESR spectrum of sample 1 at different
pH
(different colors in each panel) and at different incubation times
(different panels). (A) Time zero; (B) after 24 h; (C) after 48 h.
Black pH = 5; red pH = 6; blue pH = 7; purple the pH of the sample
before any pH shift (see Materials and Methods); dark green pH = 8; orange pH = 9; light green pH = 10. Panel A
can be compared with Figure 1 in ref (55) for Aβ(1-28) 50 μM. The vertical
lines indicate the leftmost parallel band of the two different species
(components I and II) identified for Aβ(1-28).
X-band CW ESR spectrum of sample 1 at different
pH
(different colors in each panel) and at different incubation times
(different panels). (A) Time zero; (B) after 24 h; (C) after 48 h.
Black pH = 5; red pH = 6; blue pH = 7; purple the pH of the sample
before any pH shift (see Materials and Methods); dark green pH = 8; orange pH = 9; light green pH = 10. Panel A
can be compared with Figure 1 in ref (55) for Aβ(1-28) 50 μM. The vertical
lines indicate the leftmost parallel band of the two different species
(components I and II) identified for Aβ(1-28).The spectra recorded at this pH value after the three times
are
represented by the purple lines in Figure . They show that the copper coordination
mode assumed in our model (indicated as I in Figure ) dominates over II, which involves the deprotonation
of the Ala 2 amide group. The coordination modes detected at different
pH values are quite insensitive to the incubation time and reflect
those observed for Cu–Aβ(1-28) at the same selected pH
values in NEM buffer (Figure 1 of ref (55)) and for Cu–Aβ(1-16) in PBS (pH
= 6.3, 6.9, 8.0; Figure 1, right panel of ref (56)). Both Aβ(1-16)
and Aβ(1-28) peptides contain the Aβ(1-42) relevant Cu-binding
ligand atoms in the disordered N-terminus. Compared to Aβ(1-42),
the shorter peptides aggregate at a lower rate, and thus, the published
ESR spectra display mainly the behavior of Cu–Aβ monomers.
One should notice that, for Aβ(1-42), the transition between
the two coordination modes, I and II, begins at a slightly lower pH
compared to that of Aβ(1-28), in line with the trend observed
in ref (55) with the
Aβ peptide length, where the transition is observed at pH =
8.0 in Aβ(1-28) and 8.7 in Aβ(1-16).We remark here
that the change of Cu-binding atoms when ESR component
II becomes dominant strongly affects oxidoreductive properties of
Cu–Aβ,[57−59] but there is no evidence about possible consequences
in the cross-talk between N- and C-termini in the peptide.In
order to test the presence of Cu coordination sites regularly
distributed in space within a distance ranging between 1 and 8 nm,
we applied DEER to samples 1 and 2.The DEER time trace for sample 1 is shown in Figure a. It displays sufficiently
pronounced oscillations, characteristic of a single dominant dipolar
interaction within the optimal DEER distance range. Figure b shows the DEER time trace
where the background is removed from the original data. The Fourier
transform of the background corrected signal is reported in Figure c. The data were
analyzed by using the model-free Tikhonov regularization method[60] to obtain most probable distances. This method
is acceptable if an error of 1–3 Å on most probable distances
is tolerated and when orientational selectivity effects are weak.[61] Unfortunately, the low signal-to-noise of the
data and instrumental limitations prevented us from probing the significance
of the orientational effects by collecting additional data sets. On
the other hand, simulated DEER data show that orientational effects
are substantially reduced by sufficiently large distributions of the
relative orientations of the g tensors located on
the two interacting Cu2+.[61,62] Indeed, the
atomistic models of tetramers reveal a broad distribution of the angle
between the vectors normal to the Cu binding ligand planes for copper
ions in the same dimer, as displayed in Figure . The normal vectors tend to be parallel
with a quite large standard deviation, which is about 20°.
Figure 3
DEER measurement
for sample 1 after 24 h of incubation.
(a) DEER time trace (black line) and background fitting curve (red
line). (b) Background corrected DEER time trace (black line) and best
fitting curve (red line). (c) Frequency spectra corresponding to the
time traces shown in part b. (d) Distance distribution. The analysis
of the DEER time trace was conducted using DeerAnalysis2019 software,[93] freely available at http://www.epr.ethz.ch/software/index.
Figure 4
Distribution P of orientation
of different Cu-coordination
planes represented by the scalar product between the unit vectors
normal to coordination plane (u) in different monomers. The z direction is
determined as that perpendicular to the plane formed in each configuration
by Cu–Nδ(His 6) and Cu–Nϵ(His 13) bonds.
The black curve is obtained averaging over tetramers formed by Cu-cross-linked
dimers; AB and CD pairs are averaged. The red curve is obtained averaging
over AC, AD, BC, and BD pairs in separated dimers, where Cu-coordination
planes are not correlated.
DEER measurement
for sample 1 after 24 h of incubation.
(a) DEER time trace (black line) and background fitting curve (red
line). (b) Background corrected DEER time trace (black line) and best
fitting curve (red line). (c) Frequency spectra corresponding to the
time traces shown in part b. (d) Distance distribution. The analysis
of the DEER time trace was conducted using DeerAnalysis2019 software,[93] freely available at http://www.epr.ethz.ch/software/index.Distribution P of orientation
of different Cu-coordination
planes represented by the scalar product between the unit vectors
normal to coordination plane (u) in different monomers. The z direction is
determined as that perpendicular to the plane formed in each configuration
by Cu–Nδ(His 6) and Cu–Nϵ(His 13) bonds.
The black curve is obtained averaging over tetramers formed by Cu-cross-linked
dimers; AB and CD pairs are averaged. The red curve is obtained averaging
over AC, AD, BC, and BD pairs in separated dimers, where Cu-coordination
planes are not correlated.By applying this simplified analysis, the dominant frequency shift
is attributed to a unimodal Cu–Cu distance distribution (Figure d), with a maximum
corresponding to a distance of 2.2–2.3 nm.In order to
relate the distribution of Cu–Cu distance estimated
by the DEER analysis with structural constraints for Aβ oligomers,
we used the statistics of Cu–Aβ(1-42) tetramers (say
ABCD, indicating the monomers with letters A–D) collected starting
from the assembling of 2 × Cu–Aβ(1-42) (non-Cu-cross-linked)
and [Cu–Aβ(1-42)]2 (Cu-cross-linked) preformed
dimers[42,63] (see Materials and Methods for details). A third model of 1:2 Cu–Aβ(1-42) tetramers
2 × [Cu–Aβ(1-42)–Aβ(1-42)] was also
used for comparison. We are reminded that, in our models, the Cu binding
to Aβ(1-42) is constrained to the dominant species contributing
to ESR spectra at pH ∼ 7,[64−66] which is component I
shown in the ESR spectra described above. The binding is quite stable,
being characterized by a dissociation constant Kd ranging from 10–9 M for the Aβ monomer[67,68] to 10–11 M for aggregated forms.[69] Recent measurements for Cu(II)–Aβ(1-16) show
a significant dependence of Kd on pH and
chain modifications;[70] yet, they confirm
a value of log Kd = −9.8 M for
Cu–Aβ(1-16) (i.e., the Cu-binding region of Aβ)
at pH = 7.4.In Figure , the
distribution of Cu–Cu distances obtained by these statistics
is displayed. It can be noticed that the Cu1 model displays two peaks
at distance of 1 and 1.6 nm, when the Cu ions belong to the same preformed
dimer (indicated as AB in the figure, thick black line), while a single
peak at 2.1 nm is displayed for the Cub model at the same conditions
(red thick line). This shows that, when dimers are formed as Cu-cross-linked
monomers, the Cu centers tend to be kept at larger distances than
when the Cu ions are not involved in cross-links between two peptides.
As for distances involving Cu centers not involved in preformed dimers
(indicated as AC in the figure, thin lines), the distribution is broad
in all models, though a small contribution of Cu1 and Cuh models is
still visible at 1 nm. In model Cuh, only one monomer in each preformed
dimer contains Cu; therefore, only contributions by AC pairs are computed.
The distribution of Cu–Cu AC distance (blue thin line in Figure ) is broader than
Cu1 and Cub, displaying a larger number of assembled structures able
to accommodate two separated Cu-binding sites in tetramers, when Cu-bound
peptides are intercalated by Cu-free peptides. Average distance is
for Cu1 1.7 ± 0.5 and 3.3 ± 0.8 nm for AB and AC pairs,
respectively; for Cub 2.0 ± 0.2 and 3.6 ± 0.9 nm for AB
and AC pairs, respectively; and for Cuh 3.6 ± 1.3 nm for AC pairs.
Total average distance is 2.7 ± 1 and 3.0 ± 1 for Cu1 and
Cub tetramers, respectively.
Figure 5
Distribution P of Cu–Cu
distances (d) in simulated ABCD tetramers.[42] Thick lines are Cu–Cu distances within
AB and CD dimers:
black line non-Cu-cross-linked dimers (Cu1 AB); red line Cu-cross-linked
dimers (Cub AB). Thin lines are Cu–Cu distances between monomers
not involved in preformed dimers: AC, AD, BC, BD pairs (4 samples)
for Cub (black line); AC, AD, BC, BD pairs (4 samples) for Cu1 (red
line); AC pairs (1 sample) for Cuh model (blue line). All the curves
are normalized to give the same integral, despite the number of samples
being different.
Distribution P of Cu–Cu
distances (d) in simulated ABCD tetramers.[42] Thick lines are Cu–Cu distances within
AB and CD dimers:
black line non-Cu-cross-linked dimers (Cu1 AB); red line Cu-cross-linked
dimers (Cub AB). Thin lines are Cu–Cu distances between monomers
not involved in preformed dimers: AC, AD, BC, BD pairs (4 samples)
for Cub (black line); AC, AD, BC, BD pairs (4 samples) for Cu1 (red
line); AC pairs (1 sample) for Cuh model (blue line). All the curves
are normalized to give the same integral, despite the number of samples
being different.It is possible to determine
the statistical difference between
the two data sets related to AB dimers in tetramers (Figure , the two thick curves) and
between those of AC dimers (thin curves). This difference is given
by the p-value, where the tolerance for a significant
difference is usually assumed when p < 0.05. The p-value is lower than 0.001 for thick curves, and it is
0.025 for thin curves, both in Cu1 and Cub models. Therefore, despite
the large error affecting the average obtained by each distribution,
distributions corresponding to black and red curves are statistically
different, and on average, the Cu–Cu distance within non-Cu-cross-linked
dimers is significantly shorter than that within Cu-cross-linked dimers.The comparison between the distance dominating the dipolar interactions
between Cu ions obtained in sample 1 and the molecular
statistics for oligomers (so far tetramers) obtained by atomistic
simulations shows that a Cu-cross-linked dimer assembled into larger
oligomers is more consistent with the DEER data than non-Cu-cross-linked
oligomers. The 1:1 non-Cu-cross-linked binding of Cu to Aβ produces
configurations where preformed dimers approach one each other with
Cu ions too close to be consistent with the DEER experiment. Cu–Cu
distances where ions are not involved in an AB dimer are expected
to contribute to the background.The dominant distance indicated
by the analysis of DEER data of
sample 1 encompasses many possible structures of Cu–Aβ(1-42)
oligomers. Possible structures displaying a Cu–Cu distance
shorter than 1 nm or longer than 8 nm are transparent to the DEER
technique. However, the detection of DEER signal corresponding to
a Cu–Cu distance of ∼2 nm shows that not many of such
structures occur.The structures contributing to the ∼2
nm distance can be
soluble dimers or structures with Cu pairs with regular Cu–Cu
distance embedded in larger oligomers, like those displayed by AFM
images. For instance, Cu-cross-linked soluble dimers can coexist with
oligomers where only two Cu ions are embedded. However, the consistency
between the mostly unimodal DEER distribution and the tetramer models
built by assembling Cu-cross-linked dimers reveals that the topology
of dimers can be easily preserved in tetramers. Inspired by this observation,
we are exploiting the assembly of dimers into larger models of oligomers,
up to dodecamers. This bias of pairing monomers in the assembling
process has been suggested by early IM-MS measurements.[32]Further models will also be useful to
explore more intricate possible
Cu-cross-linking, like the assembly of tetramers where monomers are
Cu-cross-linked in annular topologies and Cu–Cu pairs display
more than one regular distance in the 1–8 nm range. Indeed,
the occurrence of more than one regular distance can not be fully
excluded by the DEER measurement of sample 1 after 24
h of incubation, and further studies are required. We remark that
the DEER signal of sample 1 after 24 h is the first affirmative
DEER measurement for Cu–Aβ complexes, so far.The
constraint of Cu–Cu separation in each [Cu–Aβ(1-42)]2 cross-linked dimer is due to the separation of A and B N-termini
because of the interaction between the N-terminus of peptide A and
His 13 (or His 14) in peptide B, mediated by Cu. This constraint forces
an antiparallel arrangement of N-termini of A and B monomers. The
absence of Cu-cross-links allows for a parallel arrangement of N-termini
that has the consequence of separating the C-termini of the two approaching
dimers. Representative tetramer configurations (see Materials and Methods for details) contributing to the maximum
of Cu(A)–Cu(B) distribution in Figure (thick black and red lines) are displayed
in Figure , parts
a and b, respectively.
Figure 6
Representative configurations (see text for details) of
simulated
tetramers. (a) Tetramer formed by non-Cu-cross-linked dimers, d(Cu(A)–Cu(B)) = 1.6 nm, Rg = 2.0 nm, 1 individual. (b) Tetramer formed by Cu-cross-linked dimers, d(Cu(A)–Cu(B)) = 2.1 nm, Rg = 1.9 nm, 1 of 14 individuals. The N-termini (residues 1–16)
of A and B monomers are in blue; those of C and D are in purple. All
the other residues are in gray. Cu is the orange sphere. Atomic and
bond radii are arbitrary. H atoms are not displayed. The VMD program[100] is used for molecular drawing.
Representative configurations (see text for details) of
simulated
tetramers. (a) Tetramer formed by non-Cu-cross-linked dimers, d(Cu(A)–Cu(B)) = 1.6 nm, Rg = 2.0 nm, 1 individual. (b) Tetramer formed by Cu-cross-linked dimers, d(Cu(A)–Cu(B)) = 2.1 nm, Rg = 1.9 nm, 1 of 14 individuals. The N-termini (residues 1–16)
of A and B monomers are in blue; those of C and D are in purple. All
the other residues are in gray. Cu is the orange sphere. Atomic and
bond radii are arbitrary. H atoms are not displayed. The VMD program[100] is used for molecular drawing.The structural constraint due to Cu-cross-links is also responsible
for the approach of Tyr 10(A) to Tyr 10(B), as well as other residues
sensitive to oxidation. Indeed, a short Tyr–Tyr distance is
found, both in experiments[44] and in simulations,[42] more probable in Cu-cross-linked dimers (Cub
model) than in non-Cu-cross-linked ones (Cu1 model).As for
sample 2, no DEER time trace was detected.
The absence of DEER time trace for sample 2, that is,
in a fibril state obtained in an environment identical to that of
sample 1, shows that an arrangement of N-terminal regions
(residue 1-16) of peptides different from that in soluble oligomers
is achieved in protofibrils. It is unlikely that the absence of DEER
time trace is due to the collapse of copper spins in the fibrils.
Copper spin silencing because of the formation of a S = 0 spin state does not occur even in the prion N-terminus, where
the Cu–Cu distance approaches 3.5 Å.[71] The absence of a detectable dipolar coupling between Cu
ions can be either due to a Cu–Cu distance shorter than 1 nm,
where DEER technique is not sensitive, or to a broad distribution
of Cu–Cu distances, with a few contributions of distances in
the 2–8 nm range. A low chance for a regular positioning of
N-termini in the fibril is shown by the structural disorder affecting
N-termini observed in most of the available experimental studies.
The DEER trace observed for sample 1, and not observed
in sample 2, demonstrates that regular positioning of
N-termini is favored in small toxic oligomers.We finally performed
the DEER measurement for sample 1 incubated for 72 h.
In the conditions of sample 1 (25
μM concentration and quiescent incubation at 25 °C) Aβ(1-42)
fibrils never form, even at long incubation times:[46] The aggregation pathway is definitely diverted from fibrils
to amorphous particles. This final state of sample 1,
termed A–, is also less toxic than early soluble species (termed
A+). No DEER signal is present for this sample. This shows that, in
any of the late stages and less toxic forms of aggregation, the N-terminal
chains do not form regular registers. The regular Cu–Cu distance
displayed by the DEER measurement after 24 h is a fingerprint of early
and more toxic species on the pathway toward aggregated forms. After
we consider that the ESR spectra at pH 7.7–7.8 are quite insensitive
to the incubation time up to 48 h (Figure ), a change of Cu coordination after 72 h
of incubation is likely to be excluded.The change in structure
of N- and C-termini in protein oligomers
has been correlated to toxicity in the well-studied HypF-N protein.[72] The type A toxic oligomers of HypF-N protein
contain N-terminal regions that are less disordered than in nontoxic
type B oligomers. The difference in N-termini structure has the consequence
of exposing hydrophobic residues of the C-termini to the solvent in
toxic species, while nontoxic species have more chances to settle
C-termini into stable aggregates. A similar transition between closed
fibrillar aggregates and globular or open forms of Aβ(1-40)
has been hypothesized on the basis of ion mobility mass spectrometry
(IM-MS) data.[43,73]More generally, the effect
of N-termini on the aggregation propensity
of Aβ and on interactions with lipid membranes has been investigated
because of the polar and hydrophilic nature of region 1-16.[74,75] Indeed, the modulation of N-terminal charge by metal ion binding
has been proposed as a key effect in cell toxicity.[76] The N-terminal charge and its screening because of binding
cations like Cu(II) is also the basis of the relevance of N-truncated
forms in Aβ aggregation and toxicity.[77]Due to the lack of experimental structural information concerning
Aβ N-termini and to the potential interest of such domains,
many computational studies have been performed to provide such missing
information. The distribution of distance between metal ions bound
to Aβ peptides has been investigated, for instance, in ref (78), where Zn-Aβ(1-42)
was modeled in 12 different fibril states. The binding of Zn was different
than that assumed for Cu in this work; yet, the metal ion binding
was confined to the N-terminus in all models. In all of the different
arrangements reported, regular Zn–Zn distances can be estimated
in the 2–4 nm range when the parallel arrangement of C-termini[79] was used. In these cases, Zn-cross-linked dimers
also become possible. A similar result was obtained for Cu–Aβ(1-40)
models,[80] where regular registers of Cu–Cu
distance were obtained by using the parallel arrangement of C-termini.It must be noticed that all of the structures in the Protein Data
Bank (PDB) of Aβ(1-42) fibrils[79,81−84] display monomers assembled into β sheets with interpeptide
hydrogen bonds mostly oriented along a direction perpendicular to
the z (long) axis of the fibril. As for this arrangement,
the peptides are parallel to each other. The assembly formed by each
parallel arrangement is associated with one or more assemblies forming
a fiber. The mutual orientation of peptides in the xy plane of the fiber is always antiparallel in the interface region.
The transition between antiparallel and parallel arrangement in the xy plane of the fiber has been particularly investigated,
because the parallel xy orientation favors the antiparallel
arrangement along the z axis, thus destabilizing
the fibril. For instance, the Iowa D23N mutation induces a fibril
destabilization and a higher toxicity of Aβ(1-42) peptides.[85,86]By combining available modeling studies with the structural
information
in the PDB, we can argue that, in fibrils, there is a chance for an
organization of pairs of N-termini induced by metal ion binding, but
this chance is limited to separated pairs of tails. This limitation
is due to the strong interactions between pairs of C-termini, which
can form long registers as β sheets, while N-termini act, even
when involved in metal-bridged dimers, as separated entities. On the
contrary, oligomers have a larger chance for a structural organization
of N-termini, with the consequence of hindering a stable assembly
of C-termini.We remark that oligomer morphology does not change
with Cu addition,
as shown by AFM images. The relevance of the observation of a dominant
Cu–Cu dipolar coupling in the observed oligomers is broader
than the experimental support for Cu–Aβ(1-42) oligomers
formed by dimers with a defined Cu-cross-linked topology. The constraint
concerning peptide N-termini arrangement can be relevant for Cu-free
peptides as well. Therefore, these ESR experiments and the structures
consistent with them add an important piece of information to the
relative position of peptide termini in toxic oligomers in a physiological
environment. This information has rarely been obtained by other experimental
techniques, and in those reported cases, like cryo-EM or ssNMR results,
effects of solid state packing may affect the results.[84]The preparation of the samples is a crucial
step of this work.
The established procedure used for preparing the cytotoxic oligomers
commonly indicated as amyloid derived diffusible ligands (ADDLs),
which resemble those found in the brain of AD patients,[87] could not be adopted here. In fact, the F12
medium used in that preparation contains many amino acids and anions
that sequester copper ions from Aβ binding, with the result
that copper cannot be used as a probe for oligomer structure.
Conclusions
We performed DEER experiments on Cu–Aβ(1-42) samples
in toxic oligomeric state (A+), in protofibrillar state, and in low-toxicity
amorphous state (A−). The addition of the Cu2+ magnetic
probe was performed with no change in oligomers’ morphologies
with respect to Cu-free samples in the same conditions, as monitored
by atomic force microscopy.We observed oscillations in DEER
time trace only for the A+ state.
By comparing the Cu–Cu distance distribution obtained by analyzing
the DEER time trace with atomistic models of Cu–Aβ(1-42)
tetramers, we demonstrate that assembly of Cu-cross-linked dimers
into globular tetramers well-explains the DEER experiment.The
approach of Aβ(1-42) N-termini monitored by Cu–Cu
distance shows that interactions between N-termini in A+ toxic state
disfavor the parallel assembly of C-termini typical of most fibril
structures. Therefore, we confirm the hypothesis that N-termini assembly
induces the stabilization of toxic oligomers that are off-pathway
to protofibrils, similar to other proteins that aggregate into fibrils.
Materials and Methods
Sample Preparation and
pH Measurement
We prepared two samples displaying different
morphology: sample 1, constituted by cytotoxic oligomers,[45] indicated as A+ or A-, depending on incubation
time; sample 2, constituted by protofibrils.[46] The preparation is the same as of Cu-free samples
except for the
introduction of Cu2+. Briefly, Aβ(1–42) monomers
were prepared from the commercial peptide powder (Cayman Chemical,
USA). The powder was dissolved in 100% hexafluoroisopropanol (HFiP,
Sigma-Aldrich, Saint Louis, MO, USA) and stock solutions were stored
at −20 °C. Before preparing the oligomers, the solvent
was evaporated and Aβ(1–42) was dissolved in 50 mM NaOH
reaching a peptide concentration of 1 mg/mL, corresponding to 221
μM. The solution was sonicated for 30 s. A solution of copper
acetate and PBS characterized by a copper concentration of 221 μM
was prepared. This copper solution was added to an equal volume of
that containing the peptide, and PBS was added up to achieving the
desired final concentration. All additions were performed by gently
mixing volumes. The dilution was such that the resulting concentration
of Aβ(1-42) was 25 and 75 μM in the case of samples 1 and 2, respectively. Ultrapure water was used.
The preparation was centrifuged at 22 000 g for 30 min to remove possible small insoluble particles, and the
supernatant solution was incubated at 25 °C under quiescent conditions.[45]The pH of sample 1 was measured
after incubation times of 0, 24, and 48 h. In addition, in order to
monitor copper coordination as a function of pH by ESR, the pH of
the original samples, incubated for different times, was adjusted
to values ranging between 5 and 10 by the addition of small aliquots
of H2SO4 or NaOH aqueous solutions. Specifically,
the pH was set to 6 values in the order 10, 9, 8, 7, 6, 5, which are
the values investigated in previous reports about Aβ(1-16) and
Aβ(1-28).[55] After the pH measurement
in the original 5 mL sample at a given incubation time, 200 μL
was extracted for ESR measurement. The extracted aliquot was added
to glycerol (10% volume addition), inserted in the ESR tube, and frozen
in liquid nitrogen. The stirred solution was then added to 11 μL
of NaOH (0.5 M) to obtain pH = 10. The solution was stirred for a
few minutes before a second 200 μL extraction of the sample
for the ESR measurement was done, as in the previous stage. The stirred
solution was then added to 26 μL of sulfuric acid (0.5%) to
obtain pH = 9. Extraction and pH shift were repeated to obtain samples
at the different pH values. Added volumes of sulfuric acid changed
to a maximal value of 90 μL when in the buffer region of PBS.
The peptide concentration for the lowest pH = 5 was 23.5 μM,
and the volume was 3.9 mL. This procedure was repeated for sample 1 at the three different incubation times. At each incubation
time, the time elapsed since the first pH measurement until the last
insertion into ESR tube was shorter than 1 h.The pH was measured
at 21 °C with a Fisher Scientific accumet
(TM) AE150 equipment connected to a pH electrode (single junction
and epoxy body VWR electrode) according to a well-tested protocol.[88,89] The system was calibrated before every measurement with two standard
pH buffers at pH 4.01 and 7.01 (HI 7004, HI 7007).For all sample
preparations Ultrapure Milli-Q water was used, together
with glycerol (99.5%, Aldrich), copper acetate (anydrous, 99.99%,
Aldrich), NaOH (98%, Aldrich), and H2SO4 (95–97%,
Fluka). All compounds were used as supplied. Copper acetate was kept
in the stove before the weighting.
Atomic Force Microscopy
Morphology
and size of samples 1 and 2 were inspected
by tapping mode AFM, according to previous works.[46,90,91] A 10 μL volume of the sample was dried
on top of freshly cleaved mica substrates at room temperature for
1 h, followed by rinsing in Milli-Q water to remove salts and drying
under a gentle nitrogen flow. PBS solution was also measured as a
control experiment. Samples were immediately imaged using a JPK NanoWizard
III Sense (Berlin, Germany) scanning probe microscope operating in
AFM mode (maximum z-scan size 15 μm). Single-beam uncoated silicon
cantilevers (μMash HQ:NSC15 Cr–Au BS) were used. Drive
frequency was between 250 and 300 kHz, and the scan rate was 0.5 Hz.
Electron Spin Resonance
The ESR measurements
were conducted on a Bruker ELEXSYS E580 spectrometer provided by the
INSTRUCT-ERIC EU infrastructure. All samples were rapidly frozen after
addition of glycerol at 10% in volume (1 volume of glycerol mixed
to 10 volumes of the sample).X-band (9.4 GHz) continuous-wave
(CW) ESR spectra were collected using the ELEXSYS Super High Sensitivity
Probehead (ER 4122SHQE) resonator, equipped with an Oxford helium
temperature regulation unit, at the temperature of 20 K. The parameters
used were as follows: The microwave power was 0.2 mW, and the magnetic
field modulation amplitude was 10 G; the modulation frequency was
100 kHz, and the receiver gain was 60 dB. The spectra were accumulated
16 times to increase the signal-to-noise ratio.The DEER experiment,
used to measure distances between the unpaired
electron spins of Cu2+ ions, was conducted on the same
spectrometer at Q-band using the standard EN 5107D2 resonator. The
system was equipped with an Oxford helium temperature regulation unit,
and the data were acquired at 15 K at a repetition rate of 1 kHz.The well-described 4-pulse DEER sequence was applied.[92] The scheme consists of π/2 – τ1 – π – τ1 + τ2 – π – τ2 applied at
the observer frequency. In addition, a pump pulse of flip angle π
at the pump frequency is applied at a variable delay time t between the second pulse of the observer sequence and
the pump pulse. The lengths of the π and π/2 pulses of
the observer sequence were 64 and 32 ns, respectively, whereas the
length of the pump pulse was 60 ns. The interpulse delay τ1 was 200 ns, and the τ2 was set according
to the spin–spin relaxation time of the sample. Initial t of 100 ns was set with an increment step of 10 ns and
a total number of increments of 200. The field positions of pump and
detection pulses, located at the Cu2+ spectrum maximum
in the g region, were
separated by 25 G. The total acquisition time was 5–6 h. The
measurements were performed with an eight-step nuclear modulation
average.The DeerAnalysis2013 open-source software,[93] available for MatLab,[94] was used for
processing and analyzing DEER data. Background echo decay was corrected
by using a homogeneous three-dimensional spin distribution. Tikhonov
regularization[60] was applied to the corrected
dipolar evolution data set to obtain interspin distance distributions
(see also discussion about orientational selectivity in the Results and Discussion section).
Molecular Statistics
We analyze experimental
data using tetramer structures obtained as described in our previous
works.[42,63,95] The sampling,
based on computational empirical models, is summarized below, as for
Cu–Aβ(1-42) tetramers of stoichiometry 1:1 and 1:2.We used two models of Cu–Aβ binding. In the first model,
each Cu ion is bound to a single peptide via N and O of Asp 1, Nδ
of His 6, and Nϵ of His 13. This will be indicated as non-Cu-cross-linked
model (Cu1), hereafter. In the second model, each Cu ion is bound
to Asp 1 and His 6 of one peptide (say A) and His 13 of the other
peptide (B), via the same ligand atoms in each residue. This will
be indicated as Cu-cross-linked model (Cub), hereafter. A further
model uses the same Cu-binding model of Cu1 but in a 1:2 Cu–Aβ
ratio. In this model, Cu is bound to monomer A and forms a dimer with
Cu-free monomer B. This will be indicated as model Cuh.Tetramers
are built as dimers of dimers (AB and CD). A schematic
picture of the type of models used in this work is displayed in Figure . In model Cu1, each
dimer is composed by monomers, with each peptide bound to a Cu ion
and no cross-links connecting the monomers. In model Cub each dimer
contains two Cu-cross-links connecting the two monomer peptides. In
model Cuh (not displayed), each dimer contains only one Cu ion bound
as in Cu1. Monomers A and C are, therefore, bound to Cu ions as in
Cu1, and Cu-free peptides (B and D) are intercalated within the Cu-bound
monomers (A and C). Summarizing, tetramer models are indicated as
Cu1 (4 × Cu–Aβ(1-42), Figure a), Cub (2 × [Cu–Aβ(1-42)]2, Figure b),
and Cuh (2 × [Cu–Aβ(1-42)–Aβ(1-42)],
not displayed), respectively. The Cu binding to Aβ(1-42) in
Cu1, Cub, and Cuh tetramers is that consistent with the dominant species
identified by interpretation of ESR spectra at pH ∼ 7.[64−66] Even though slight differences occur between the cited studies in
terms of the ligand atoms, the models include the experimental constraint
of Asp 1 and His 6 and one of the two His in the 13–14 pair
coordinated to Cu2+.
Figure 7
Schematic representations of computational
models of tetramers
used in this work: The circle represents Cu ion; the curves represent
Aβ(1-42) peptides. (a) Cu1 model, with each Cu ion bound to
each peptide. (b) Cub model, with Cu ions forming cross-links between
the monomers in each preformed dimer. Top and bottom dimers represent
the preformed AB and CD dimers that approach each other to form the
ABCD tetramer.
Schematic representations of computational
models of tetramers
used in this work: The circle represents Cu ion; the curves represent
Aβ(1-42) peptides. (a) Cu1 model, with each Cu ion bound to
each peptide. (b) Cub model, with Cu ions forming cross-links between
the monomers in each preformed dimer. Top and bottom dimers represent
the preformed AB and CD dimers that approach each other to form the
ABCD tetramer.Initial configurations of Cu–Aβ(1-42)
monomers, [Cu–Aβ(1-42)]2 Cu-cross-linked dimers,
and [Cu–Aβ(1-42)–Aβ(1-42)
dimers were selected as the most representative structures obtained
with 1 μs atomistic molecular dynamics (MD) simulations performed
in explicit water solvent.[95] The selection
of initial configurations was performed according to the maximally
populated peak in the gyration radius (Rg) and solvent accessible surface area (SASA) probability map in all
cases. The force field was Amber 99SB,[96] integrated with the parametrization of the chosen Cu-binding site.[95]Indicating the monomers with letters A–D,
we built different
assemblies of A and B monomers into dimers and built assemblies of
AB and CD dimers into tetramers. This was done by placing two particles
in space, monomers and dimers, for building dimers and tetramers,
respectively. We placed the particles with the selected structures
and with random orientations with centers of mass at an approximate
distance of 2 nm. The particles were inserted into orthorhombic simulation
cells filled of water molecules described as in the TIP3P model[97] and a neutralizing amount of NaCl 0.1 M.We performed MD simulations with time-step of 2 fs and rigid constraints
for bonds involving hydrogen atoms, in the NPT statistical ensemble
of 128 initial mutual orientations of the particles. Pressure was
1 bar and temperature was 300 K. We used the multiple-walkers metadynamics
to separate the independent trajectories, one with respect to each
other. The diversity among different walkers is limited, here, to
the mutual orientation of the peptide that forms each assembly: monomers,
when dimers are built, and dimers, when tetramers are built. We performed
a single multiple-walkers simulation for 128 replica of the system.
The spreading of walkers among independent trajectories was performed
by adding a bias potential constructed according to the altruistic
method,[98] with a collective variable chosen
as the number of salt bridges within each monomer. This choice was
dictated by the observation that this variable is particularly effective
in changing the peptide structure,[95] thus
allowing a wider sampling of different structures within the multiple
walkers. After MD simulation of 20 ns in the presence of the progressively
built (history-dependent) bias, 2 ns were performed with no bias.
The last 1 ns was used for averaging, using one configuration every
10 ps of simulation (100 configurations per walker). The NAMD 2.10
package[99] was used for the simulations,
with most of the MD simulation parameters chosen according to standard
procedures. Because some walkers were unstable, the total number of
collected configurations for Cu1 was 126 × 100 (2 walkers ignored)
and 127 × 100 (1 walker ignored), for Cub and Cuh, respectively.As in previous published analysis, tetramers are defined when,
in the collected statistics, the ratio between the total solvent accessible
surface area (SASA(ABCD)) divided by the sum of the SASA of the two
constituent dimers (SASA(AB) + SASA(CD)) is lower than 0.95. Tetramers
were 5650 over 12 600 (45%), 3037 over 12 700 (24%),
and 4792 over 12 700 (38%) for Cu1, Cub, and Cuh, respectively.The selection of representative structures among the tetramers
was performed by finding individuals that are contained in peaks of
maximal population of distributions of different structural quantities.
Here, we used the Cu–Cu distance within preformed dimers (AB)
and the radius of gyration, Rg.
Authors: Lisa M Miller; Qi Wang; Tejas P Telivala; Randy J Smith; Antonio Lanzirotti; Judit Miklossy Journal: J Struct Biol Date: 2005-11-14 Impact factor: 2.867
Authors: Michael T Colvin; Robert Silvers; Qing Zhe Ni; Thach V Can; Ivan Sergeyev; Melanie Rosay; Kevin J Donovan; Brian Michael; Joseph Wall; Sara Linse; Robert G Griffin Journal: J Am Chem Soc Date: 2016-07-14 Impact factor: 15.419
Authors: Claudia Capitini; Jayneil R Patel; Antonino Natalello; Cristiano D'Andrea; Annalisa Relini; James A Jarvis; Leila Birolo; Alessia Peduzzo; Michele Vendruscolo; Paolo Matteini; Christopher M Dobson; Alfonso De Simone; Fabrizio Chiti Journal: Chem Commun (Camb) Date: 2018-07-18 Impact factor: 6.222
Authors: Laila Abdel-Hafiz; Andreas Müller-Schiffmann; Carsten Korth; Benedetta Fazari; Owen Y Chao; Susanne Nikolaus; Sandra Schäble; Arne Herring; Kathy Keyvani; Valéria Lamounier-Zepter; Joseph P Huston; Maria A de Souza Silva Journal: Neurobiol Aging Date: 2018-04-17 Impact factor: 4.673