Frederick Hsu1, Giovanna Park1, Zhefeng Guo1. 1. Department of Neurology, Brain Research Institute, Molecular Biology Institute, University of California, 710 Westwood Plaza, Los Angeles, California 90095, United States.
Abstract
Formation of amyloid fibrils by Aβ42 protein is a pathological hallmark of Alzheimer's disease. Aβ42 fibrillization is a nucleation-dependent polymerization process, in which nucleation is the rate-limiting step. Structural knowledge of the fibril nucleus is important to understand the molecular mechanism of Aβ aggregation and is also critical for successful modulation of the fibrillization process. Here, we used a scanning mutagenesis approach to study the role of each residue position in Aβ42 fibrillization kinetics. The side chain we used to replace the native residue is a nitroxide spin label called R1, which was introduced using site-directed spin labeling. In this systematic study, all residue positions of Aβ42 sequence were studied, and we identified six key residues for the Aβ42 fibril formation: H14, E22, D23, G33, G37, and G38. Our results suggest that charges at positions 22 and 23 and backbone flexibilities at positions 33, 37, and 38 play key roles in Aβ42 fibrillization kinetics. Our results also suggest that the formation of a β-strand at residues 15-21 is an important feature in Aβ42 fibril nucleus. In overall evaluation of all of the mutational effects on fibrillization kinetics, we found that the thioflavin T fluorescence at the aggregation plateau is a poor indicator of aggregation rates.
Formation of amyloid fibrils by Aβ42 protein is a pathological hallmark of Alzheimer's disease. Aβ42 fibrillization is a nucleation-dependent polymerization process, in which nucleation is the rate-limiting step. Structural knowledge of the fibril nucleus is important to understand the molecular mechanism of Aβ aggregation and is also critical for successful modulation of the fibrillization process. Here, we used a scanning mutagenesis approach to study the role of each residue position in Aβ42 fibrillization kinetics. The side chain we used to replace the native residue is a nitroxidespin label called R1, which was introduced using site-directed spin labeling. In this systematic study, all residue positions of Aβ42 sequence were studied, and we identified six key residues for the Aβ42 fibril formation: H14, E22, D23, G33, G37, and G38. Our results suggest that charges at positions 22 and 23 and backbone flexibilities at positions 33, 37, and 38 play key roles in Aβ42 fibrillization kinetics. Our results also suggest that the formation of a β-strand at residues 15-21 is an important feature in Aβ42 fibril nucleus. In overall evaluation of all of the mutational effects on fibrillization kinetics, we found that the thioflavin T fluorescence at the aggregation plateau is a poor indicator of aggregation rates.
Formation
of amyloid fibrils is a key process underlying the pathogenesis
of a wide range of human disorders, including Alzheimer’s disease,
Parkinson’s disease, and type 2 diabetes.[1,2] The
fibrillization process is a nucleation-dependent polymerization, in
which nucleation is the rate-limiting step. The nucleation step is
manifested as the lag phase of the sigmoidal aggregation curve, during
which the fibril nucleus accumulates to exceed certain threshold concentrations
and thus the elongation of fibril nuclei becomes the dominant process,
leading to the formation of mature fibrils. In the last decade, significant
progress has been made in the understanding of the microscopic aggregation
processes.[3−5] It has been shown that both primary and secondary
nucleation reactions may take place in the lag phase,[6,7] and determination of the nucleation rate is best achieved by global
fitting of the aggregation data over a wide range of protein concentrations.[8,9] Regardless of the exact mechanism of aggregation, structural knowledge
of the fibril nucleus is important for a complete understanding of
the fibrillization process and is critical for successful design of
fibrillization modulators.Amyloid-β (Aβ) protein
is the major component of amyloid
plaques, a pathological hallmark of Alzheimer’s disease.[10] There are two major variants of Aβ protein:
Aβ40 and Aβ42. Although Aβ40 is severalfold more
abundant than Aβ42 in the brain,[11−13] Aβ42 is the major
component of the amyloid plaques.[14−17] Aβ aggregation and the
structure of Aβ aggregates have been under intensive investigation.
Several recent structural studies have produced detailed knowledge
on the structure of the final aggregation product of Aβ42, the
amyloid fibrils.[18−21] The structure of the Aβ42 fibril nucleus, in contrast, is
still poorly understood.To gain insights into the structure
of Aβ42 fibril nuclei,
here we used a scanning mutagenesis approach to study the role of
each residue position in fibrillization kinetics. The rationale is
that if a residue is of structural importance to the fibril nucleus,
then mutation at that residue position may affect fibrillization in
a dramatic way. Depending on whether a mutation is stabilizing or
destabilizing the fibril nucleus, it will either promote or slow down
fibrillization. The side chain we used to replace the native residue
is a nitroxidespin label called R1 (Figure A), which was introduced using site-directed
spin labeling.[22] Modeling of the spin label
on a parallel β-sheet[23] suggests
that the crystal structure of the spin label[24] can be accommodated in the amyloid core (Figure B). The use of spin label stems from our
routine structural studies of spin-labeled Aβ42 aggregates using
electron paramagnetic resonance spectroscopy.[25,26] Crystal structures of spin-labeled T4 lysozyme have shown that the
R1 side chain is well tolerated in T4 lysozyme when labeled on a solvent-exposed
helical site, but could cause local structural changes when introduced
at the hydrophobic core.[27,28] In this systematic
study, all residue positions of Aβ42 sequence were studied in
aggregation kinetics experiments, and we identified six key residues
for the Aβ42 fibril formation: H14, E22, D23, G33, G37, and
G38. Our results also suggest the formation of a β-strand in
the fibril nucleus at residues 15–21. The potential roles of
these structural features in the aggregation of Aβ42 are discussed.
Figure 1
Structure
of the spin label R1. (A) Chemical structure of R1. (B)
Cartoon representation of the spin label R1 in a parallel in-register
β-sheet. This model is based on the crystal structures of the
NNQQNY peptide[23] and the spin labeling
reagent 1-oxyl-2,2,5,5-tetramethylpyrroline-3-methyl methanethiosulfonate
(MTSSL).[24]
Structure
of the spin label R1. (A) Chemical structure of R1. (B)
Cartoon representation of the spin label R1 in a parallel in-register
β-sheet. This model is based on the crystal structures of the
NNQQNY peptide[23] and the spin labeling
reagent 1-oxyl-2,2,5,5-tetramethylpyrroline-3-methyl methanethiosulfonate
(MTSSL).[24]
Results and Discussion
Formation of Aβ42 amyloid fibrils
is a nucleation-dependent
polymerization process. Structural knowledge of the fibril nucleus
is important for the mechanistic understanding of Aβ fibrillization
and also for structure-based intervention targeting the aggregation
process. Here, we used the spin label R1 (Figure ), a bulky hydrophobic side chain, to scan
through the full sequence of Aβ42 and investigate the effect
of spin label substitution on fibrillization kinetics. Because nucleation
is a rate-limiting step, the free energy of the fibril nucleus is
higher than those of both Aβ monomers and fibrils. Substitutions
that lower the energy of the fibril nucleus would accelerate the rate
of nucleation, whereas substitutions that destabilize the fibril nucleus
would slow down the rate of nucleation and, consequently, the rate
of fibrillization. The approach of proline scanning mutagenesis has
been previously used to study the aggregation of Aβ42 by Morimoto
et al.,[29] but the rate of aggregation was
not determined for all residue positions. To our best knowledge, this
work is the first report of a comprehensive study of fibrillization
kinetics in combination with scanning mutagenesis at all 42 residue
positions in the Aβ42 sequence.The fibrillization kinetics
of wild-type and 42 spin-labeled variants
of Aβ42 were performed at 37 °C under quiescent conditions.
Two Aβ42 concentrations at 5 and 10 μM were used in the
first set of aggregation assays. The fibril formation was monitored
with thioflavin T fluorescence. As shown in Figure , wild-type and most of the Aβ42 mutants
show sigmoidal aggregation kinetics, typical of nucleation-dependent
fibrillization. Six Aβ42 mutants did not show typical sigmoidal
aggregation curves: H14R1, E22R1, D23R1, G33R1, G37R1, and G38R1.
These six mutants are characterized by a very broad growth phase or
no growth phase and very low thioflavin T amplitude at the end of
the aggregation period (40 h). We then increased the Aβ concentration
to 20 and 40 μM for these six mutants and repeated the aggregation
experiments. As shown in Figure , the aggregation curves of H14R1, G33R1, G37R1, and
G38R1 were restored to a more typical sigmoid shape, but E22R1 and
D23R1 did not display sigmoidal curves even at these higher concentrations.
Therefore, these results suggest that six residue positions, H14,
E22, D23, G33, G37, and G38, are important for the nucleation-dependent
polymerization of Aβ42 fibrils. Among these six residues, E22
and D23 are essential for the sigmoidal aggregation kinetics.
Figure 2
Aggregation
kinetics of wild-type and 42 spin-labeled Aβ42
mutants. R1 represents the spin label. Aβ aggregation was performed
at two concentrations, 5 and 10 μM, in phosphate-buffered saline
(PBS) buffer (pH 7.4) at 37 °C without agitation.
Figure 3
Aggregation kinetics of Aβ42 H14R1, E22R1, D23R1,
G33R1,
G37R1, and G38R1 at 20 and 40 μM. R1 represents the spin label.
Aggregation was performed at 37 °C without agitation.
Aggregation
kinetics of wild-type and 42 spin-labeled Aβ42
mutants. R1 represents the spin label. Aβ aggregation was performed
at two concentrations, 5 and 10 μM, in phosphate-buffered saline
(PBS) buffer (pH 7.4) at 37 °C without agitation.Aggregation kinetics of Aβ42 H14R1, E22R1, D23R1,
G33R1,
G37R1, and G38R1 at 20 and 40 μM. R1 represents the spin label.
Aggregation was performed at 37 °C without agitation.To quantitatively evaluate the effect of site-specific
substitutions,
we determined the half time of aggregation directly from the aggregation
curves without relying on fitting to any specific sigmoidal functions.
The half time is the time of aggregation at which the thioflavin T
fluorescence has reached 50% of the fluorescence at the aggregation
plateau. Even though we chose to use this type of rudimentary data
analysis, our analysis is rooted in recent advances in the mechanistic
understanding of protein aggregation. First, we chose to use half
time, not lag time, as a measure of mutational effects on nucleation.
As discussed previously by Arosio et al.,[7] primary nucleation is not the only microscopic process during the
lag time of aggregation. Most notably, fibril-catalyzed secondary
nucleation has been observed for the aggregation of Aβ42,[6] Aβ40,[30] and
α-synuclein.[31] Whereas primary nucleation
is the most active in the beginning of the lag phase, secondary nucleation
would soon dominate and reach maximal rate near the half time of aggregation.[7] Therefore, half time is a better indicator for
the overall nucleation rate when both primary and secondary nucleation
reactions are present. Second, kinetic analysis has been shown to
be a powerful approach to reveal detailed molecular events during
the aggregation process.[32,33] A number of mathematical
models have been used to fit the aggregation data.[3,34] For
Aβ aggregation, experimental evidence also suggests a mechanism
of nucleated conformational conversion,[35,36] which would
add another layer of complexity to the mechanism of primary nucleation.
It is not straightforward to obtain microscopic rate constants from
kinetic data as similar kinetic profiles can be obtained from different
mathematical models. In case of primary and secondary nucleation,
this issue is alleviated by global fitting of the kinetic data over
a wide range of protein concentrations.[8,9] And because
our kinetic data consist of only two protein concentrations, we refrained
from fitting of our data to specific kinetic models. The goal of this
investigation is to obtain structural insights into the fibril nucleus,
so data analysis aiming at understanding the aggregation mechanism
is beyond the scope of this work. Third, half time of aggregation
is not a direct measure of nucleation rate, as it can be affected
by primary nucleation, secondary nucleation, fibril elongation, and
fragmentation. In this study, fibril formation was performed under
quiescent conditions, so fibril fragmentation is not the main driving
force of aggregation rate. If we can assume that fibril elongation
rate remains unchanged by mutagenesis, then the changes in half time
of aggregation can be used to evaluate the effects on fibril nucleation,
without distinguishing primary and secondary nucleation.In Figure , we
plot the half time of aggregation as a function of residue positions.
The half time was not determined for the six mutants that did not
show sigmoidal aggregation curves: H14, E22R1, D23R1, G33R1, G37R1,
and G38R1. When looking at the overall pattern of residue-specific
aggregation rate, we found that spin labeling at the N-terminal region
(residues 1–10) did not lead to dramatic differences in the
half time of aggregation from one residue to the next, suggesting
that the N-terminal region may play a lesser role. We also observed
that spin labeling at positions 16, 18, and 20 dramatically delayed
Aβ42 aggregation, whereas spin labeling at positions 15, 17,
19, and 21 led to faster aggregation kinetics. The opposite effects
on aggregation for alternating residue positions in this region suggest
that residues 15–21 may adopt a β-strand structure, which
has a periodicity of two, in the fibril nucleus. In the recent high-resolution
structures of Aβ42 fibrils based on cryoEM,[19] residues 15–21 adopt a β-strand structure,
and the side chains of residues 15, 17, and 19 point inside the fibril
core. This confirms the notion that spin labeling at the fibril core
(such as residues 15, 17, 19, and 21) does not disrupt core packing
in the fibril nucleus. It is not immediately clear why spin labeling
at residues 16, 18, and 20, whose side chains point outside the amyloid
core, delayed Aβ42 fibril formation.
Figure 4
Plot of the half time
of aggregation as a function of residue positions.
Half time is defined as the time at which the thioflavin T fluorescence
is at half of the fluorescence at the aggregation plateau and is determined
directly from the kinetics curves. Each data point is an average of
multiple repeats, and the error bars are the standard deviation. The
gray box highlights residues 15–21, which show a periodicity
of two in the half time of aggregation. Light red and light blue dotted
lines denote the half time for wild-type Aβ42 at 5 and 10 μM,
respectively.
Plot of the half time
of aggregation as a function of residue positions.
Half time is defined as the time at which the thioflavin T fluorescence
is at half of the fluorescence at the aggregation plateau and is determined
directly from the kinetics curves. Each data point is an average of
multiple repeats, and the error bars are the standard deviation. The
gray box highlights residues 15–21, which show a periodicity
of two in the half time of aggregation. Light red and light blue dotted
lines denote the half time for wild-type Aβ42 at 5 and 10 μM,
respectively.In this work, we obtained
a large dataset of Aβ42 aggregation
kinetics, which allowed us to evaluate the overall relationship between
the rate of aggregation and the thioflavin T fluorescence at the aggregation
plateau. We have previously reported that thioflavin T fluorescence
intensity is directly proportional to the amount of amyloid fibrils.[37] However, it is an open question whether thioflavin
T fluorescence intensity is a representative measure of aggregation
rate. Therefore, we plotted the thioflavin T fluorescence intensity
at the aggregation plateau for the kinetics data versus the half time
of aggregation for all of the spin-labeled Aβ42 mutants (Figure ). Overall, these results show that there is not
a clear correlation
between thioflavin T fluorescence intensity and half time of aggregation.
Therefore, when evaluating the effect of mutations on aggregation,
it is preferable to use aggregation kinetics rather than simply the
thioflavin T fluorescence at the end of aggregation.
Figure 5
Plot of thioflavin T
fluorescence at completion of aggregation
versus the half time of aggregation. The thioflavin T fluorescence
was measured at the end of aggregation, at which the aggregation time
is at 40 h. Averages and standard deviations are calculated based
on multiple repeats of aggregation experiments.
Plot of thioflavin T
fluorescence at completion of aggregation
versus the half time of aggregation. The thioflavin T fluorescence
was measured at the end of aggregation, at which the aggregation time
is at 40 h. Averages and standard deviations are calculated based
on multiple repeats of aggregation experiments.Summary of important structural features for Aβ42 fibril
formation. Key residues are highlighted in pink. A potential β-strand
region at residues 15–21 is represented by a block arrow.Among the six residue positions
that show aberrant aggregation
kinetics upon spin labeling (Figure ), two of them are charged residues: E22 and D23. There
are nine charged residues in Aβ42 sequence: D1, E3, R5, D7,
E11, K16, E22, D23, and K28. Because spin labeling at other charged
residue positions shows only a mild effect on aggregation kinetics,
the effect at E22 and D23 cannot be explained simply by changes in
the isoelectric point of Aβ42. We also considered the possibility
that either E22 or D23 is involved in a salt bridge with another charged
residue. If such a salt bridge exists and plays a critical role in
aggregation, we would expect to see a similar effect when the other
partner of the salt bridge is mutated. There are three positively
charged residues in the Aβ42 sequence: R5, K16, and K28. R5R1
shows similar aggregation kinetics as that of the wild-type Aβ42,
and K28R1 shows faster aggregation kinetics. Only K16R1 shows slower
aggregation kinetics than wild-type Aβ42. However, K16R1 still
shows a sigmoid aggregation curve, unlike E22 or D23. Therefore, our
data suggest that E22 and D23 are not forming salt bridges with other
positively charged residues. We propose that the role of E22 and D23
is to ensure this part of the protein is exposed to solvent because
burial of two negative charges would be energetically unfavorable.
Residues E22 and D23 are sites of several familial mutations, including
E22G (Arctic),[38,39] E22K (Italian),[40,41] E22Q (Dutch),[42−44] E22Δ (Osaka),[45] and
D23N (Iowa).[46] These familial mutants can
be rationalized in a way that they reduce or neutralize the local
charges and thus divert the Aβ aggregation from fibrillization
to oligomerization pathways. This would produce more toxic oligomers
and lead to early-onset Alzheimer’s disease.
Figure 6
Summary of important structural features for Aβ42 fibril
formation. Key residues are highlighted in pink. A potential β-strand
region at residues 15–21 is represented by a block arrow.
The six
residue positions with aberrant aggregation kinetics include
three glycine residues: G33, G37, and G38. Without side chains, glycine
offers maximum backbone flexibility because glycine can be found almost
anywhere on the Ramachandran plot.[47] There
are a total of six glycine residues in Aβ sequence: G9, G25,
G29, G33, G37, and G38. The four glycines at G25, G29, G33, and G37
comprise a GXXXG motif commonly found in transmembrane helices, called
glycine zipper.[48] However, only mutations
at two of these four glycine zipper positions resulted in delayed
aggregation, suggesting that the mutations did not act on the formation
of glycine zipper. Therefore, the importance of G33, G37, and G38
in aggregation is likely due to the backbone flexibility at these
residue positions. Previously, Harmeier et al.[49] showed that G33I and G33A in Aβ42 displayed higher
propensity to form higher oligomers. Fonte et al.[50] showed that the expression of G37L mutant of Aβ42
in Caenorhabditis elegans did not show
detectable amyloid formation. These studies show that mutation to
different amino acids can all affect fibril formation, supporting
the notion that the role of these glycine residues in aggregation
is primarily providing backbone flexibility.There are three
histidine residues in Aβ42 sequence: H6,
H13, and H14. Only H14R1 shows markedly different aggregation kinetics,
whereas H6R1 and H13R1 display typical sigmoidal aggregation curves.
Previous structural studies using spin labeling and electron paramagnetic
resonance suggest that H14 is part of a turn in Aβ42 fibrils.[25] Molecular dynamics studies of Aβ42 also
consistently show a turn motif at residues 12–15.[51] Therefore, we suggest that the importance of
H14 in Aβ42 fibrillization is likely to stabilize the turn around
residue 14. Even though H13 is the adjacent residue and is of the
same residue type, our data suggest that H13 and H14 play different
roles in fibril nucleation and elongation. A mutagenesis study[52] using d-amino acids showed that d-histidine at position 14 caused substantial changes in Aβ42
aggregation, suggesting that the effect at H14 may also be related
to the direction to which the H14 side chain is pointing.Previously,
Morimoto et al.[29] used the
proline scanning mutagenesis approach to study the site-specific effect
on Aβ42 aggregation. Proline is a β-strand breaker, and
proline substitution at β-structure would presumably lead to
reduced fibril formation. Out of 34 residue positions studied, Morimoto
et al. identified three turn regions at residues 22–23, 33–34,
and 38–39, which are insensitive to proline mutations. Interestingly,
these residue positions coincide with the key residues (E22, D23,
G33, G37, and G38) for Aβ42 aggregation that we identified in
this work (Figure ). In recent structural models of Aβ42 fibrils based on solid-state
NMR[18,20,21] and cryoEM,[19] these key residues are not all located in turn
regions, suggesting that structural features important for nucleation
may be different from those for the final aggregation product, amyloid
fibrils.
Materials and Methods
Preparation of Aβ42 Proteins and Spin
Labeling
Cysteine mutants of Aβ42 were introduced using
the QuikChange
site-directed mutagenesis kit (Agilent), and all mutations were confirmed
with DNA sequencing. For protein expression, the plasmids containing
Aβ42 constructs were transformed into Escherichia
coli C41 cells, and the protein expression was induced
with isopropyl β-d-1-thiogalactopyranoside as previously
described.[25,53] Full-length Aβ was then
cleaved from the fusion protein with Usp2-cc using previously published
methods.[54] WT Aβ42 was buffer exchanged
to 30 mM NH4 acetate (pH 10), lyophilized, and stored at
−80 °C. For spin labeling, the spin labeling reagent (1-oxyl-2,2,5,5-tetramethylpyrroline-3-methyl
methanethiosulfonate (MTSSL), AdipoGen Life Sciences) was used, and
the detailed procedure has been previously published.[25,54] The spin-labeled Aβ42 proteins were then lyophilized and stored
at −80 °C.
Aggregation Kinetics
Forty-three
tubes of lyophilized
powder corresponding to the wild-type and 42 spin-labeled Aβ42
mutants were dissolved in hexafluoroisopropanol (HFIP) to a final
concentration of 100 μM and then incubated overnight with shaking
at 1000 rpm. Then, HFIP was evaporated in the chemical hood at room
temperature overnight. These samples were dissolved in 50 μL
of CU buffer (20 mM CAPS, 8 M urea, pH 11). The wild-type Aβ
concentration was determined using absorbance at 280 nm in CU buffer
with an extinction coefficient of 1280 M cm–1, which
was previously determined in a denaturing buffer.[55] The spin-labeled Aβ concentration was determined
using an extinction coefficient of 1740 M cm–1,
with the consideration of absorbance from disulfide bond and the nitroxide
ring. Because Y10R1 does not have a tyrosine, the extinction coefficient
of 460 M cm–1 was used. Then, Aβ stock solutions
at 200 and 100 μM were made using CU buffer to dilute the original
stock. For aggregation reaction, 2.5 μL of Aβ42 stock
at either 200 or 100 μM was mixed with 42.5 μL of PBS
(50 mM phosphate, 140 mM NaCl, pH 7.4) and 5 μL of thioflavin
T (200 μM in PBS buffer). Therefore, each mutant of Aβ
was aggregated at both 10 and 5 μM. Mutants H14R1, E22R1, D23R1,
G33R1, G37R1, and G38R1 were also prepared at higher concentrations
in CU buffer to set up aggregation at 20 and 40 μM with the
same protocol of 20-fold dilution to PBS. To start aggregation, the
50 μL aggregation assay was transferred to a black 384-well
Nonbinding Surface microplate with clear bottom (Corning product 3655)
and sealed with a polyester-based sealing film (Corning product PCR-SP).
The fluorescence was measured from the bottom with an excitation filter
of 450 nm and an emission filter of 490 nm in a Victor 3V plate reader
(Perkin Elmer). The aggregation was performed at 37 °C without
agitation. The aggregation data are reported as fold change in fluorescence
by dividing the average of thioflavin T fluorescence at each time
point of measurement.
Authors: Sanguk Kim; Tae-Joon Jeon; Amit Oberai; Duan Yang; Jacob J Schmidt; James U Bowie Journal: Proc Natl Acad Sci U S A Date: 2005-09-22 Impact factor: 11.205
Authors: S A Gravina; L Ho; C B Eckman; K E Long; L Otvos; L H Younkin; N Suzuki; S G Younkin Journal: J Biol Chem Date: 1995-03-31 Impact factor: 5.157
Authors: Georg Meisl; Xiaoting Yang; Erik Hellstrand; Birgitta Frohm; Julius B Kirkegaard; Samuel I A Cohen; Christopher M Dobson; Sara Linse; Tuomas P J Knowles Journal: Proc Natl Acad Sci U S A Date: 2014-06-17 Impact factor: 11.205
Authors: Virginia Fonte; Vishantie Dostal; Christine M Roberts; Patrick Gonzales; Pascale N Lacor; Pascale Lacor; Pauline T Velasco; Jordi Magrane; Natalie Dingwell; Emily Y Fan; Michael A Silverman; Gretchen H Stein; Christopher D Link Journal: Mol Neurodegener Date: 2011-08-23 Impact factor: 14.195
Authors: Alexander K Buell; Céline Galvagnion; Ricardo Gaspar; Emma Sparr; Michele Vendruscolo; Tuomas P J Knowles; Sara Linse; Christopher M Dobson Journal: Proc Natl Acad Sci U S A Date: 2014-05-09 Impact factor: 11.205
Authors: Samuel I A Cohen; Sara Linse; Leila M Luheshi; Erik Hellstrand; Duncan A White; Luke Rajah; Daniel E Otzen; Michele Vendruscolo; Christopher M Dobson; Tuomas P J Knowles Journal: Proc Natl Acad Sci U S A Date: 2013-05-23 Impact factor: 11.205