Edward H Egelman1. 1. Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, United States.
Abstract
Helical polymers are found throughout biology and account for a substantial fraction of the protein in a cell. These filaments are very attractive for three-dimensional reconstruction from electron micrographs due to the fact that projections of these filaments show many different views of identical subunits in identical environments. However, ambiguities exist in defining the symmetry of a helical filament when one has limited resolution, and mistakes can be made. Until one reaches a near-atomic level of resolution, there are not necessarily reality-checks that can distinguish between correct and incorrect solutions. A recent paper in eLife (Xu et al., 2014) almost certainly imposed an incorrect helical symmetry and this can be seen using filament images posted by Xu et al. A comparison between the atomic model proposed and the published three-dimensional reconstruction should have suggested that an incorrect solution was found.
Helical polymers are found throughout biology and account for a substantial fraction of the protein in a cell. These filaments are very attractive for three-dimensional reconstruction from electron micrographs due to the fact that projections of these filaments show many different views of identical subunits in identical environments. However, ambiguities exist in defining the symmetry of a helical filament when one has limited resolution, and mistakes can be made. Until one reaches a near-atomic level of resolution, there are not necessarily reality-checks that can distinguish between correct and incorrect solutions. A recent paper in eLife (Xu et al., 2014) almost certainly imposed an incorrect helical symmetry and this can be seen using filament images posted by Xu et al. A comparison between the atomic model proposed and the published three-dimensional reconstruction should have suggested that an incorrect solution was found.
Helical polymers are ubiquitous in biology, and are found extensively in viruses (Ge and Zhou, 2011), bacteria (Polka et al., 2009; Ozyamak et al., 2013), eukaryotes (Galkin et al., 2010) and archaea (Yu et al., 2012). Because of the symmetry inherent in helical
filaments (where identical subunits are rotated and translated along a filament axis)
projections of helical filaments can provide all of the information needed to generate a
three-dimensional reconstruction from a limited number of images, and this property was
exploited in the first electron microscopic (EM) three dimensional reconstruction, which
was made from a helical bacteriophage tail (DeRosier
and Klug, 1968). New advances in both computational approaches (Egelman, 2000) and cryo-imaging with direct
electron detectors (Bai et al., 2013) have meant
that the determination of structures of helical polymers at near-atomic resolution
(Lu et al., 2014; Wu et al., 2014) is becoming much more common. However, the
assignment of the correct symmetry to a helical polymer can still be problematic (Egelman, 2010; Desfosses et al., 2014), and examples exist where the wrong symmetry has been
mistakenly imposed (Okorokov et al., 2010;
Sen et al., 2010; Yu and Egelman, 2010; Heymann et
al., 2013). Insufficient understanding exists about how solutions
(three-dimensional structures) may be obtained that are stable under iterative
refinement, consistent with the images, but simply wrong. This arises from imposing a
helical symmetry that is incorrect, but the available resolution does not allow one to
distinguish between wrong symmetries and the correct one. This short communication seeks
to reconcile the very different reconstructions of the MAVS filament by two groups
(Wu et al., 2014; Xu et al., 2014) and in the process raise some general issues
about helical reconstruction. While the points may appear to be quite technical to the
non-specialist, they raise important questions about the expertise needed to evaluate
some cryo-EM results.The reconstruction of the MAVS filament presented in Wu et al. had a stated resolution
of 3.6 Å and had a helical symmetry of a rotation of −101.1° (the
negative rotation corresponding to a left-handed helix) and a rise of 5.1 Å per
subunit. In contrast, the reconstruction of Xu et al. had a stated resolution of 9.6
Å, a C3 point group rotational symmetry, with a rotation of −53.6° and
a rise of 16.8 Å for every ring of three subunits. One of the differences between
the two reconstructions is that in Wu et al. not only are α-helices clearly
resolved, but bulky aromatic side-chains can be seen that are consistent with not only
the sequence but a crystal structure of the subunit which can be fit quite well as a
rigid body into the reconstruction. In the Comment appended to their paper (Jiang, 2014), Xu et al. do not dispute the
validity of the reconstruction in Wu et al., but argue that the filament being
reconstructed by Wu et al. is an artifact of harsh preparative procedures, and that
their filaments have a different symmetry and represent a more native conformation. They
advance three arguments for why their filaments have a different symmetry. Given that
the authors of Xu et al. have deposited the images that they used in the EMPIAR
database, these arguments can be directly tested.Their first argument for a different helical symmetry is that a layer line at
∼1/(17 Å) in their power spectrum has intensity on the meridian, while the
corresponding layer line in Wu et al. does not and is clearly arising from an n =
−1 Bessel order. Figure 1 shows how the
power spectrum of an image is the central section of the three-dimensional power
spectrum of the object being projected onto the image. As such, the projection is
sensitive to any tilt of the axis of the object out of the plane of projection. An
untilted central section (Figure 1B) would
generate the two separated peaks on both sides of the meridian seen in Figure 1D (arrow), while a sufficiently tilted
central section (Figure 1C) would generate a
single intensity on the meridian (Figure 1E). For
negatively stained polymers, where filaments are adsorbed to a carbon film, out-of-plane
tilt can be largely ignored. In cryo-EM, where filaments are imaged within an ice film
of finite thickness, such tilt cannot be ignored, particularly as one becomes more
sensitive to it the higher the resolution. The first question I asked is whether there
was any substantial out-of-plane tilt for the filaments imaged by Xu et al. I used an
approach of providing references with different tilt angles to generate the histogram
shown in Figure 2A. The large peaks at
−20° and +20° correspond to segments with tilt angles greater than
20°, showing the unexpectedly large degree of tilt for these filaments. If one only
takes the segments in the three central bins (−4°, 0°, +4°) a
power spectrum is generated (Figure 2B) that
clearly shows (arrow) an n = −1 layer line with no intensity on the
meridian. This power spectrum looks to be the same as that shown by Wu et al.,
undercutting the argument that the filaments being used by the two groups are different.
One can calculate the tilt that would be needed to make the two separated peaks in Figure 2B appear as a single peak on the meridian,
and it is ∼9°, entirely consistent with the histogram in Figure 2A.
Figure 1.
The three-dimensional power spectrum of a helical filament and power
spectra from projections of the filament.
The three-dimensional power spectrum of a helical filament is shown
(A). The power spectrum from a cryo-EM image of a helical
filament (where the image is a projection of a three-dimensional object onto a
two-dimensional plane) is the central section of the three-dimensional power
spectrum, and this would be given by the intersection of the red plane in
(B) with the power spectrum. The yellow arrows in
(B) show the intersection of this plane with a layer plane that
arises from a 1-start helix. The intensities on this central section are shown
in (D), which would be the power spectrum from untilted filaments,
i.e., those whose filament axis is parallel to the plane of projection. The
yellow arrow in (D) shows the layer line from the 1-start helix,
with peak intensities on both sides of the meridian. Now consider what happens
when the filament axis is tilted away from parallel to the plane of projection.
The central section (C) would now intersect the 1-start layer
plane at the positions given by the two yellow arrows, and in the
two-dimensional power spectrum the two peaks would collapse to a single peak on
the meridian (E, yellow arrow). If one did not know that the
filament was tilted, such intensity would be mistaken for a meridional layer
line with the Bessel order n = 0.
DOI:
http://dx.doi.org/10.7554/eLife.04969.002
Figure 2.
Out-of-plane tilt cannot be ignored in the images of Xu et al.
A histogram (A) of the out-of-plane tilt seen in the filaments of
Xu et al. A reconstruction was generated from these filaments while allowing
for out-of-plane tilt, and this reconstruction was used as a reference,
generating 90 different azimuthal projections (4° increments) for tilt
angles from −20° to +20° (also with 4° increments),
generating 990 reference projections. The large peaks at both ends of the
distribution arise from truncating the search range to smaller values than
actually found in the filament population. Using filament segments in the three
central bins (−4°, 0°, 4°) for generating a power
spectrum (B) it can be seen that there is no meridional intensity
on the layer line indicated by the arrow at ∼1/(18 Å), and the
appearance of this layer line is now the same as in Wu et al. The log of the
power spectrum is shown to better display the large dynamic range.
DOI:
http://dx.doi.org/10.7554/eLife.04969.003
The three-dimensional power spectrum of a helical filament and power
spectra from projections of the filament.
The three-dimensional power spectrum of a helical filament is shown
(A). The power spectrum from a cryo-EM image of a helical
filament (where the image is a projection of a three-dimensional object onto a
two-dimensional plane) is the central section of the three-dimensional power
spectrum, and this would be given by the intersection of the red plane in
(B) with the power spectrum. The yellow arrows in
(B) show the intersection of this plane with a layer plane that
arises from a 1-start helix. The intensities on this central section are shown
in (D), which would be the power spectrum from untilted filaments,
i.e., those whose filament axis is parallel to the plane of projection. The
yellow arrow in (D) shows the layer line from the 1-start helix,
with peak intensities on both sides of the meridian. Now consider what happens
when the filament axis is tilted away from parallel to the plane of projection.
The central section (C) would now intersect the 1-start layer
plane at the positions given by the two yellow arrows, and in the
two-dimensional power spectrum the two peaks would collapse to a single peak on
the meridian (E, yellow arrow). If one did not know that the
filament was tilted, such intensity would be mistaken for a meridional layer
line with the Bessel order n = 0.DOI:
http://dx.doi.org/10.7554/eLife.04969.002
Out-of-plane tilt cannot be ignored in the images of Xu et al.
A histogram (A) of the out-of-plane tilt seen in the filaments of
Xu et al. A reconstruction was generated from these filaments while allowing
for out-of-plane tilt, and this reconstruction was used as a reference,
generating 90 different azimuthal projections (4° increments) for tilt
angles from −20° to +20° (also with 4° increments),
generating 990 reference projections. The large peaks at both ends of the
distribution arise from truncating the search range to smaller values than
actually found in the filament population. Using filament segments in the three
central bins (−4°, 0°, 4°) for generating a power
spectrum (B) it can be seen that there is no meridional intensity
on the layer line indicated by the arrow at ∼1/(18 Å), and the
appearance of this layer line is now the same as in Wu et al. The log of the
power spectrum is shown to better display the large dynamic range.DOI:
http://dx.doi.org/10.7554/eLife.04969.003Is it possible that the sorting I have done for out-of-plane tilt is completely wrong,
since it has involved the application of a helical symmetry, and the power spectrum in
Figure 2B is actually from a highly tilted
subset, while the power spectrum in Xu et al. is from an untilted subset? The answer is
no, since we can see from Figure 1 how the 2D
power spectrum will change with tilt. The two separated peaks seen in Figure 2B would also need to be present as secondary
maxima in the power spectrum shown in Xu et al. to appear as a result of tilt, and they
simply are not present there. On the other hand, the power spectrum in Figure 2B, if assumed to be representative of
filaments with little tilt, can explain the power spectrum of Xu et al. when that is
assumed to represent a large tilt.The second argument advanced by Xu et al. in their Comment is that the symmetry used by
Wu et al. is unstable in the Iterative Helical Real Space Reconstruction (IHRSR)
approach when applied to their filaments, and therefore their filaments must have a
different symmetry. Since I developed the IHRSR method (Egelman, 2000), I have some experience with the application of the algorithm
to many helical systems. I have argued (Egelman,
2007, 2010) that a stable solution in
IHRSR is a necessary, but not sufficient, requirement for the solution to be correct,
since it has been clear that many wrong solutions can also be stable. However, it has
become apparent in cryo-EM, when out-of-plane tilt cannot be ignored, that correct
solutions can be unstable when this tilt is ignored. Figure 3 shows the symmetry parameters (rotation and axial rise per subunit)
for the filaments of Xu et al. when references are included with out-of-plane tilt. It
can be seen that the symmetry determined by Wu et al. can be applied to the filaments of
Xu et al. and that this is quite stable in IHRSR cycles, again undercutting their
argument that the two sets of filaments are different.
Figure 3.
In the IHRSR method, the helical parameters (rotation and rise per subunit)
are refined each cycle.
The starting parameters were the symmetry determined by Wu et al., and it can
be seen that when using the images of Xu et al. these parameters are perfectly
stable. The first seven cycles were run with images decimated from 2.3
Å/px to 4.6 Å/px, ignoring out-of-plane tilt. The subsequent cycles
were run with the undecimated images and allowing for out-of-plane tilt.
DOI:
http://dx.doi.org/10.7554/eLife.04969.004
In the IHRSR method, the helical parameters (rotation and rise per subunit)
are refined each cycle.
The starting parameters were the symmetry determined by Wu et al., and it can
be seen that when using the images of Xu et al. these parameters are perfectly
stable. The first seven cycles were run with images decimated from 2.3
Å/px to 4.6 Å/px, ignoring out-of-plane tilt. The subsequent cycles
were run with the undecimated images and allowing for out-of-plane tilt.DOI:
http://dx.doi.org/10.7554/eLife.04969.004The third and last argument advanced by Xu et al. in their Comment is that their
reconstruction has a hole in the center, while the model of Wu et al. that has been
built into the 3.6 Å resolution reconstruction would have no such hole. They
correctly state that such a hole can be seen in their filaments independently of the
symmetry simply by cylindrically averaging their 3D density map. If one takes the
cryo-EM density map deposited by Wu et al. (EMDB-5922) and filters it to 12 Å
resolution a hole is seen in the center (Figure
4B, arrow). The reason that this is consistent with the deposited model
(3j6j.PDB) is simply that the subunits are helically arranged and do not pack to form a
solid core. Since the packing of protein is less dense in the center of the filament
than it is at higher radius, a cylindrically averaged density distribution will show a
continuous hole in the center of the filament. The reason that I have chosen 12 Å
for this comparison is that this is the actual resolution of the reconstruction (Figure 4A,C) that I have been able to generate from
the images of Xu et al. Why is the resolution so poor? The most obvious differences are
that the Xu et al. images appear to be from thick ice, there is a very noisy background,
and they have applied a carbon film which degrades the signal-to-noise ratio. Since they
are sampling at 2.3 Å/px, the best one might hope to achieve would be ∼7
Å resolution (2/3 Nyquist) but given the problems with the images one would never
get even close to this.
Figure 4.
A reconstruction has been made from the filaments of Xu et al.
(A and C) by applying the helical symmetry described
in Wu et al. For purposes of comparison, the reconstruction of Wu et al.
(EMDB-5922) has been filtered to 12 Å resolution (B and
D). It can be seen that with similar thresholds, both
reconstructions show a hole in the center (A and B,
arrows), arising from the helical procession of the subunits about the filament
axis. The atomic model (3J6J.PDB) from Wu et
al. (2014) is shown fit into both reconstructions.
DOI:
http://dx.doi.org/10.7554/eLife.04969.005
A reconstruction has been made from the filaments of Xu et al.
(A and C) by applying the helical symmetry described
in Wu et al. For purposes of comparison, the reconstruction of Wu et al.
(EMDB-5922) has been filtered to 12 Å resolution (B and
D). It can be seen that with similar thresholds, both
reconstructions show a hole in the center (A and B,
arrows), arising from the helical procession of the subunits about the filament
axis. The atomic model (3J6J.PDB) from Wu et
al. (2014) is shown fit into both reconstructions.DOI:
http://dx.doi.org/10.7554/eLife.04969.005I have thus shown that the three arguments for why their filaments are different from
those of Wu et al., advanced by Xu et al. in their Comment, are not true. This does not
establish, however, that the filaments are the same. Establishing that would require a
high resolution reconstruction from the filaments of Xu et al. which I fear would be
impossible. But we can look at their published reconstruction, which gets to the most
important point: given all of the potential problems and ambiguities in helical
reconstruction, how does one know that a structure is correct? The great success of
protein x-ray crystallography lies in the fact that structures are being solved that all
have a known stereochemistry. One has prior knowledge about what an α-helix and a
β-sheet look like, as well as knowing the amino acid sequence that must be built
into a model. At lower resolution by EM most of these reality-checks are simply absent,
and one needs to generate methods, such as the tilt-pair validation used for
single-particle cryo-EM (Rosenthal and Henderson,
2003) that can distinguish between correct and incorrect reconstructions. As
the field of cryo-EM is now rapidly moving to near-atomic resolution, seeing
recognizable secondary structure provides a necessary and sufficient validation of a
reconstruction. In the case of Wu et al. having a map with near-atomic detail, showing
right-handed α-helices, confirmed not only the symmetry but the absolute hand of
the reconstruction, whereas in the absence of this level of detail one must use means
such as metal-shadowing or tomography to resolve the enantiomorphic ambiguity present.
But at lower resolution one can still ask how well a reconstruction agrees with a model.
Unfortunately, there is vanishingly little agreement between their deposited map
(EMDB-5890) and their deposited model (PDB 3j6c).I show a comparison between their actual reconstruction (Figure 5A,C), and their model filtered to 9.6 Å (Figure 5B,D), the stated resolution of their reconstruction. One
sees at these higher thresholds than used in Xu et al. that there is actually no match
between the features in one and in the other. A reasonable question is whether such
comparisons are fair, since the atomic models are free from any noise, while the
reconstruction may contain noise at the resolution limit. Several published examples
suggest that this method is reasonable, and might be the best gauge of the actual
reconstruction. In a 9 Å resolution reconstruction of an actin-cofilin filament a
comparison with an atomic model filtered to this resolution (Supplementary figure 1D,
Galkin et al., 2011) shows an excellent
match. Similarly, a 7.5 Å resolution reconstruction of a naked actin filament shows
an excellent match with an atomic model filtered to this resolution (Supplementary
figure 2, Fujii et al., 2010).
Figure 5.
Comparisons between a model and the actual map are informative.
The reconstruction (A and C) of Xu et al. (EMDB-5890)
is compared with their model 3j6c.PDB (B and D). In
all four panels (A–D) the same model
(3j6c.PDB) is shown as magenta ribbons, but the transparent surfaces in
B and D have been generated by filtering the model
density to 9.6 Å, the stated resolution of the reconstruction shown in
(A and C). The surfaces in (C and
D) are shown at a higher threshold than in (A and
B). It can be seen that with these thresholds, there is
virtually no correlation between the map (A and C)
and the model (B and D). A Fourier Shell Correlation
between their model and reconstruction (E) shows that at FSC
= 0.5 the resolution is ∼22 Å, which is consistent with the
visual comparison of the map and model
(A–D).
DOI:
http://dx.doi.org/10.7554/eLife.04969.006
Comparisons between a model and the actual map are informative.
The reconstruction (A and C) of Xu et al. (EMDB-5890)
is compared with their model 3j6c.PDB (B and D). In
all four panels (A–D) the same model
(3j6c.PDB) is shown as magenta ribbons, but the transparent surfaces in
B and D have been generated by filtering the model
density to 9.6 Å, the stated resolution of the reconstruction shown in
(A and C). The surfaces in (C and
D) are shown at a higher threshold than in (A and
B). It can be seen that with these thresholds, there is
virtually no correlation between the map (A and C)
and the model (B and D). A Fourier Shell Correlation
between their model and reconstruction (E) shows that at FSC
= 0.5 the resolution is ∼22 Å, which is consistent with the
visual comparison of the map and model
(A–D).DOI:
http://dx.doi.org/10.7554/eLife.04969.006This comparison between a map and a model can be made quantitatively, and Figure 5E shows a Fourier Shell Correlation (FSC)
plot between the map and model of Xu et al., with a resolution estimate of ∼22
Å. Such a resolution suggests that the only agreement between the map and the model
is for compact ‘blobs’ (which is what this small subunit looks like at a
resolution of 22 Å) related by the same imposed helical symmetry. This type of
comparison, had it been done by the authors, should have raised many questions. One is
whether the helical symmetry imposed was actually correct. Another is whether the FSC,
which is only a measure of internal consistency between two halves of the image set and
not a measure of actual resolution, has any meaning in this instance since it yields
such a different result between two reconstructions (each generated from half of the
image set) and between the overall reconstruction and the model.In conclusion, the arguments of Xu et al. for a different symmetry in their filaments
than that in Wu et al. collapse completely when one actually examines the publicly
deposited data.
Materials and methods
The micrographs in set04 within the EMPIAR-10014 deposition (http://pdbe.org/empiar) from Xu et al. (2014) were used for analysis. Of the
581 images, the first 160 were used for filament extraction. The Contrast Transfer
Function was measured using CTFFIND3 (Mindell and
Grigorieff, 2003). For the 160 images, the mean defocus was 3.2 μ and
the range was from 1.7 μ to 5.4 μ. The images were then multiplied by the
theoretical CTF function to correct the phases and improve the SNR. From these 160
images, 1066 long filament boxes were cut using the e2helixboxer routine within EMAN2
(Tang et al., 2007). The SPIDER software
package (Frank et al., 1996) was used for all
further steps. Overlapping boxes 192 px long (2.3 Å/px) were cut from the long
filament boxes using a shift of 6 px (97% overlap), generating 64,980 boxes. These were
used for IHRSR (Egelman, 2000) which converged
to a symmetry of −101.2° rotation with an axial rise of 5.3 Å, starting
from a solid cylinder as an initial reference. Due to the very poor resolution
(∼17 Å), an attempt was made to improve this by only using the 58 images
with a defocus less than 3.0 μ, which yielded 15,624 overlapping boxes. Because
segments with a very large out-of-plane tilt were excluded, the final reconstruction was
generated from 8600 segments. The modulation of the amplitudes of the final
reconstruction by the CTF (the phase reversals of the CTF were previously corrected when
the images were multiplied by the CTF) was corrected by dividing the Fourier
coefficients in the reconstruction by the sum of the squared CTFs, imposing a negative
B-factor of 2000 to correct for the decay of the high frequencies, and filtering to 12
Å.eLife posts the editorial decision letter and author response on a selection of the
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concerns or comments; minor concerns are not usually shown. Reviewers have the
opportunity to discuss the decision before the letter is sent (see review
process). Similarly, the author response typically shows only responses
to the major concerns raised by the reviewers.Thank you for sending your work entitled “Ambiguities in Helical
Reconstruction” for consideration at eLife. Your article has
been favorably evaluated by John Kuriyan (Senior editor), Wes Sundquist (Reviewing
editor), and three reviewers, of whom Niko Grigorieff and Carsten Sachse have agreed to
reveal their identity. A third reviewer remains anonymous.The Reviewing editor and the three reviewers discussed their comments before we reached
this decision, and the Reviewing editor has assembled the following comments to help you
prepare a revised submission.Dr Egelman analyzes the validity of a cryoEM helical reconstruction of the prion-like
filament formed by the CARD domain of the RIG-I adaptor molecule MAVS, as reported by Xu
et al. in eLife (Xu et al. eLife, 2014, 3:e01489). The
study by Xu et al. was published before a related study was published by Wu et al. in
Molecular Cell (Wu et al. Molecular Cell 2014,
55:511-524). The situation merits follow-up because the two reported MAVS structures are
entirely different. There is no dispute that the Wu et al. study contained high quality
EM data, that their reconstruction was technically correct, and that they successfully
generated a near-atomic resolution structure of their MAVS filaments. The central
question is whether differences in sample preparation generated distinct MAVS filaments
with different physical structures, or whether the differences in the reported
structures instead reflect methodological problems in the Xu et al study. Dr Jiang (one
of the corresponding authors on the Xu et al. paper) has posted a Comment that
accompanies the original eLife manuscript in which he argues that the
reported differences in the filament helical symmetries and structures reflect genuine
physical differences in the MAVS filaments generated by the two groups. Here, Egelman
analyzes the central claims of that Comment and also discusses the validity of the
original Xu et al. reconstruction.Egelman downloaded part of the original data deposited by Xu et al. in the EMPIAR data
base and performed image analyses to test the arguments put forth by Jiang that the
filaments used in the two studies were indeed different. He shows convincingly that the
three central pieces of evidence presented in the Jiang Comment are invalid. He makes
several important points, including that Xu et al. did not appreciate that their
filaments had significant out-of-plane tilt and that convergence stability in a symmetry
search is not sufficient to establish the validity of that symmetry. Importantly, he
also shows that the Xu et al. structure does not agree with its own PDB model beyond a
resolution of ∼20 Å, suggesting that the computed EM density is not correct.
These arguments convincingly rebut the points raised in Jiang's Comment, reveal
potential inconsistencies in the processing procedure used by Xu et al., and raise
substantial doubts about the validity of the Xu et al. reconstruction. These analyses
are therefore an important contribution.The Egelman analysis could be strengthened even further by providing additional evidence
that Xu et al. must have imposed the wrong helical symmetry. The author could do this by
computing a structure with the symmetry parameters from Wu et al. imposed on the EMPIAR
data set from Xu et al. (which he has already been analyzing). Such a structure should
contain clearer densities and recognizable secondary structure features.[…] The Egelman analysis could be strengthened even further by providing
additional evidence that Xu et al. must have imposed the wrong helical symmetry. The
author could do this by computing a structure with the symmetry parameters from Wu et
al. imposed on the EMPIAR data set from Xu et al. (which he has already been
analyzing). Such a structure should contain clearer densities and recognizable
secondary structure features.I have been able to improve the resolution that I initially obtained with their images
by excluding those with a defocus greater than 3.0μ. This reduced the data set
from ∼64k segments to ∼15k segments, but the reconstruction is clearly
improved. I have expanded Figure 4 to show a
better comparison of the reconstruction from Xu et al. with the correct symmetry with
the one from Wu et al. filtered to 12 Å resolution, and shown the atomic model of
Wu et al. fit into both volumes.
Authors: Vitold E Galkin; Albina Orlova; Dmitri S Kudryashov; Alexander Solodukhin; Emil Reisler; Gunnar F Schröder; Edward H Egelman Journal: Proc Natl Acad Sci U S A Date: 2011-12-07 Impact factor: 11.205
Authors: Weili Zheng; Fengbin Wang; Nicholas M I Taylor; Ricardo C Guerrero-Ferreira; Petr G Leiman; Edward H Egelman Journal: Structure Date: 2017-07-27 Impact factor: 5.006
Authors: Mark A B Kreutzberger; Cheryl Ewing; Frederic Poly; Fengbin Wang; Edward H Egelman Journal: Proc Natl Acad Sci U S A Date: 2020-07-08 Impact factor: 11.205
Authors: E H Egelman; C Xu; F DiMaio; E Magnotti; C Modlin; X Yu; E Wright; D Baker; V P Conticello Journal: Structure Date: 2015-01-22 Impact factor: 5.006
Authors: Nicolas Coudray; Ralph Lasala; Zhening Zhang; Kathy M Clark; Mark E Dumont; David L Stokes Journal: J Struct Biol Date: 2016-05-30 Impact factor: 2.867