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electronic reprint
ISSN: 2053-2733
journals.iucr.org/a
MicroED data collection and processing
Johan Hattne, Francis E. Reyes, Brent L. Nannenga, Dan Shi, M. Jason de
la Cruz, Andrew G. W. Leslie and Tamir Gonen
Acta Cryst. (2015). A71, 353–360
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Acta Cryst. (2015). A71, 353–360 Johan Hattne et al. · MicroED data collection and processing
feature articles
Acta Cryst. (2015). A71, 353–360 http://dx.doi.org/10.1107/S2053273315010669 353
MicroED data collection and processing
Johan Hattne,a Francis E. Reyes,a Brent L. Nannenga,a Dan Shi,a M. Jason de la
Cruz,a Andrew G. W. Leslieb and Tamir Gonena*
aJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA, and bMedical Research Council
Laboratory of Molecular Biology, Cambridge, England. *Correspondence e-mail: gonent@janelia.hhmi.org
MicroED, a method at the intersection of X-ray crystallography and electron
cryo-microscopy, has rapidly progressed by exploiting advances in both fields
and has already been successfully employed to determine the atomic structures
of several proteins from sub-micron-sized, three-dimensional crystals. A major
limiting factor in X-ray crystallography is the requirement for large and well
ordered crystals. By permitting electron diffraction patterns to be collected from
much smaller crystals, or even single well ordered domains of large crystals
composed of several small mosaic blocks, MicroED has the potential to
overcome the limiting size requirement and enable structural studies on
difficult-to-crystallize samples. This communication details the steps for sample
preparation, data collection and reduction necessary to obtain refined, highresolution, three-dimensional models by MicroED, and presents some of its
unique challenges.
1. Introduction
X-ray crystallography hinges on the availability of large, well
ordered crystals for accurate structure determination. The
shortest side of a crystal for diffraction data collection at a
regular synchrotron source is typically >50 mm in length.
Particularly for difficult targets, such as membrane proteins
and large protein complexes, the path from protein purification to initial crystallization hits and finally to large, well
diffracting crystals may prove prohibitively resource-intensive.
Furthermore, large crystals effectively preclude time-resolved
studies of diffusion-triggered processes (Hajdu et al., 2000).
The ability to collect high-quality diffraction data from crystals
smaller than 10–20 mm3 in volume is thus most desirable.
Both microfocus beamlines (Moukhametzianov et al., 2008)
and more recently X-ray free-electron lasers (XFELs) (Boutet
et al., 2012) allow high-resolution structure determination
from such samples. In the case of microfocus beamlines,
crystals with side lengths around 20 mm are routinely used for
structure determination. XFELs allow data collection from
crystals 1 mm and larger. Here the diffraction data are
recorded, one pattern per crystal, before the crystal is
destroyed by the high-powered X-ray pulse (Barty et al., 2012;
Chapman et al., 2014). Millions of crystals are continuously
streamed through the X-ray beam, giving rise to thousands of
independent diffraction ‘stills’, and the data are then indexed
and merged to generate a seemingly damage-free structure.
More recent studies, however, suggest that radiation damage is
still experienced by the sample even in XFEL experiments
(Nass et al., 2015). While XFELs show great promise in nanocrystallography, the high sample requirement, milligrams of
protein when using liquid jets (Weierstall, 2014), coupled with
ISSN 2053-2733
Received 11 December 2014
Accepted 2 June 2015
Edited by J. Miao, University of California, Los
Angeles, USA
Keywords: MicroED; electron diffraction;
crystallography; cryo-EM; nanocrystals.
Supporting information: this article has
supporting information at journals.iucr.org/a
electronic reprint
limited infrastructure and high cost are currently limiting
factors.
MicroED is a recently developed method in cryo-EM
(electron cryo-microscopy) that allows the collection of highresolution electron diffraction data from extremely small
three-dimensional crystals that are in the range of 0.1–0.4 mm
thick (Shi et al., 2013) using a transmission electron microscope. Electrons are excellent probes of atomic structure
because they interact more strongly with matter and deposit
less energy in the crystal than X-rays (Henderson, 1995).
Not surprisingly, electron diffraction has been repeatedly
attempted on three-dimensional crystals over the past
decades, but has until recently consistently failed to yield any
refined atomic structures. Because of the traditional experimental setup, typically only a single electron diffraction
pattern would be collected per crystal, but unlike in X-ray
crystallography, indexing single diffraction patterns in electron
microscopy is exceedingly challenging as often insufficient
information is contained in a single diffraction pattern (x2.3).
In 2013 we unveiled the MicroEDmethod in which a complete
diffraction tilt series was collected from a single nanocrystal,
up to 90 wedge of data, allowing us to index and solve the
structure of lysozyme first at 2.9 Å resolution (Shi et al., 2013)
and later with the improved continuous-rotation method at
2.5 Å resolution (Nannenga, Shi, Leslie & Gonen, 2014).
Currently, the procedure of continuous rotation has been
employed in a number of laboratories using different electron
microscopes and different detectors (Nederlof, van Genderen
et al., 2013; Nannenga, Shi, Hattne et al., 2014; Nannenga,
Shi, Leslie & Gonen, 2014; Yonekura et al., 2015). Highresolution structures using this method have been reported for
lysozyme, catalase and the membrane protein calcium ATPase
(Nannenga, Shi, Hattne et al., 2014; Nannenga, Shi, Leslie &
Gonen, 2014; Yonekura et al., 2015; Table 1).
2. Methods
While sample preparation, microscope setup and data collection likely vary from laboratory to laboratory, we detail below
the protocols we employ for a successful MicroED experiment.
2.1. Sample preparation
Owing to their small size, initial identification of nanocrystals suitable for MicroED can be difficult. While secondorder non-linear optical imaging of chiral crystals (SONICC)
(Kissick et al., 2011) could provide an automated and objective
means to identify small crystals, we have so far relied on visual
judgment of e.g. the cloudiness of the drops, followed by
negative-stain electron microscopy. When suitable crystals are
found, about 4 ml of microcrystals in solution is dispensed onto
a holey carbon or continuous carbon grid that has been
cleaned in a glow-discharge device. The crystals are allowed to
settle for 30 s and excess solution is removed from the grids
by blotting with filter paper. Enough solution needs to be
removed to minimize background contribution and allow the
electron beam to penetrate the sample during subsequent
exposure; however, too much blotting can dehydrate and
damage the crystals. Because it can be difficult to strike the
right balance between a sample that is too thick and one that
has been damaged by excessive blotting, it is often beneficial
to prepare several grids with a wide range of blotting times,
temperatures and humidity levels.
Grids can be blotted and frozen either by hand or using an
automated vitrification apparatus. Automated systems are
generally preferable owing to their high reproducibility and
fine control over blotting conditions, such as time and force. If
the buffer is too viscous to be effectively removed, the crystals
are fragile, or if too many crystals are carried off by the flow of
the solution, the grids may need to be blotted manually by
gently touching the backs of the grids with filter paper.
Immediately following blotting, the grids are plunged into
liquid ethane. The high thermal conductivity of liquid ethane
ensures the sample is frozen fast enough to prevent disruption
of the crystal lattice during cooling, even in the absence of a
cryo-protectant. The frozen grids are then quickly transferred
into a cryo-grid box where they can be stored for long periods
of time at cryogenic temperatures. Alternatively, grids may be
examined in the electron microscope immediately after they
are prepared. Successful blotting and freezing is a trial-anderror process and will have to be optimized individually for
each sample.
2.1.1. Setting up the transmission electron microscope for
low-dose electron diffraction. The alignment of the electronoptic system and the astigmatism of the lenses need to be
checked and possibly corrected according to the instructions
from the microscope manufacturer. The direct beam should be
focused and aligned to the center of the screen and completely
blocked by the beam stop. Furthermore, the grid’s z height
should be adjusted to near the eucentric height, where the
image of the sample is unaffected by the tilt of the stage on
which it is mounted. A rough estimate may be found by
wobbling the specimen up to 15; the quantifoil holes, or any
other identifying thin feature, should remain centered when
the grid is at the eucentric height.
Initial grid screening is done at ultra low dose rates
(<106 e Å2 s1) and low magnification (100) in bright
field (Fig. 1a). In this configuration the entire grid can be
quickly surveyed for the location and density of crystals and
the thickness of the enveloping ice. Once crystal-containing
regions are identified where the thickness of the ice, as judged
by the contrast between the carbon support and the holes, is as
thin as possible, the microscope is switched to over-focused
diffraction mode (Fig. 1b). In this configuration, individual
crystals can be inspected, the z height fine-tuned for eucentricity, and the center spot accurately focused by minimizing
the size of the spot of the direct beam at a dose rate
<103 e Å2 s1. This should be verified using the microscope’s phosphor screen as the direct beam could otherwise
damage the detector. Moreover, electron hysteresis deserves
special attention so that neither the spot of the direct beam
nor the image shifts when switching among the various
configurations. Typically, the diffraction pattern should be
354 Johan Hattne et al.  MicroED data collection and processing Acta Cryst. (2015). A71, 353–360
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recorded at a dose rate of 0.01–0.05 e Å2 s1, with the beam
configured to be approximately 5–10 mm in diameter, the
objective aperture fully open and the selected area aperture
set to closely match the size of the crystal. Detailed step-bystep procedures for microscope setup were published earlier
(Gonen, 2013).
2.1.2. Microcrystal screening and diffraction data collection. After finding a crystal on the grid, the crystal is centered,
the eucentric height adjusted by tilting the crystal through the
desired rotation range, and the selected area aperture and
beam stop are inserted. An initial diffraction pattern is
recorded with an exposure of 2–5 s at a dose rate of 0.01–
0.05 e Å2 s1. If the diffraction pattern shows high-quality
diffraction, a full data set is collected from that crystal. The
edge of the cryo-holder limits the tilt range to approximately
70 from the untilted orientation, in which the grid is normal
to the electron beam. The combined thickness of the sample
and its surrounding solvent may further restrict the useful tilt
range as the amount of matter the electron beam has to
traverse may become prohibitive at high tilts (Shi et al., 2013).
To avoid further confinement of the tilt range it should be
verified that no other crystals or grid bars block the view
throughout the rotation range when the selected area aperture
and the beam stop are removed. If the aim of data collection is
to complement an existing data set, it is often possible to
approximate the crystal orientation from an initial, untilted
exposure. This allows the tilt range to be optimized for
measuring the desired reflections.
Initial MicroED data sets were collected as a sequence of
still shots, where the crystal is held stationary during the
exposure and rotated to discrete orientations only while the
electron beam is blanked (Shi et al., 2013). The exposure time
is adjusted depending on the diffraction strength of the
crystal. In this mode of data collection the TVIPS TemCamF416 CMOS-based camera operates at its best; there is sufficient time to recharge the read-out electronics for each
pixel, and consequently the signal-to-noise ratio is maximized.
However, still shots introduce complications for subsequent
data interpretation: the vast majority of reflections from a
motionless crystal hit by an electron beam with narrow
bandpass (E/E ’ 5  106 for a field emission gun at
200 kV) are only partially recorded. To meaningfully relate
multiple observations of the same reflection to each other, the
individual partial observations are either summed or
converted to their full-intensity equivalent, and the accuracy
of this operation decreases as the range of observed partialities increases. This issue can be overcome by oscillating the
crystal during the exposure, as has long been standard practice
in goniometer-based X-ray crystallography (Arndt & Wonacott, 1977). On an electron microscope crystal oscillation is
complicated by difficulties in accurately positioning the stage,
which is typically optimized to reduce vibrations during long
exposures.
This leads to the continuous-rotation mode for MicroED
data collection (Nannenga & Gonen, 2014; Nannenga, Shi,
Leslie & Gonen, 2014), which captures a greater portion of
each reflection because the crystal is rotated in the electron
beam, but avoids absolute repositioning of the stage by
moving it continuously. The stage is rotated at a constant rate
where the optimal rotation rate reflects a compromise
between conflicting goals, and is tuned in coordination with
the exposure time (Holton & Frankel, 2010). For a given
exposure time, a high rotation rate will increase the recorded
fraction of each reflection on an individual frame, but a low
rotation rate will ensure that even weak, high-resolution
reflections accumulate enough counts on the detector before
leaving their diffracting condition. Furthermore, a too high
rate may result in spot overlap, while a too low rate will yield
too few spots on each image.
Continuous-rotation data sets from single crystals are
collected in shutterless mode in about 10 min. The detector is
constantly exposed and read out at regularly spaced intervals.
This mode of operation trades detector accuracy for simplified
experimental setup; in particular we find that the effects of
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Acta Cryst. (2015). A71, 353–360 Johan Hattne et al.  MicroED data collection and processing 355
Table 1
Atomic structures determined by three-dimensional electron crystallography.
The first four data sets were collected on a TVIPS TemCam-F416 using a field emission gun at 200 kV, corresponding to a de Broglie wavelength of 0.025 Å. Ca2+ATPase and the second catalase structure were collected at 300 kV (0.020 Å) on a TVIPS TemCam-F224HD.
Lysozyme
(PDB id: 3j4g;
EMDB id: EMD-2945;
Shi et al., 2013)
Lysozyme
(PDB id: 3j6k;
EMDB id: EMD-6313;
Nannenga, Shi, Leslie
& Gonen, 2014)
Lysozyme
(PDB id: 5a3e;
EMDB id: EMD-6342;
Nannenga, Shi, Leslie
& Gonen, 2014)
Catalase
(PDB id: 3j7b;
EMDB id: EMD-6314;
Nannenga, Shi,
Hattne et al., 2014)
Ca2+-ATPase
(PDB id: 3j7t;
Yonekura et al.,
2015)
Catalase
(PDB id: 3j7u;
Yonekura et al.,
2015)
Number of crystals 3 2 1 1 99 58
Space group P43212 P43212 P43212 P212121 C2 P212121
Unit cell
a, b, c (Å) 77, 77, 37 76.0, 76.0, 37.2 75.9, 75.9, 36.9 67.8, 172.1, 182.1 166.3, 64.4, 147.3 69.0, 173.5, 206.0
, ,  () 90, 90, 90 90, 90, 90 90, 90, 90 90, 90, 90 90, 98.3, 90 90, 90, 90
Resolution (Å)† 2.9 (3.1–2.9) 2.5 (2.6–2.5) 2.5 (2.6–2.5) 3.2 (3.4–3.2) 3.40 (3.47–3.40) 3.20 (3.27–3.20)
Multiplicity 34 4.8 3.4 2.4 15.8 20.8
Completeness (%)† 92 (57) 97.2 (90.2) 80.1 (80.1) 79.4 (75.5) 67.5 (65.7) 73.0 (72.8)
Rwork/Rfree (%) 25.5/27.8 22.0/25.5 21.3/25.3 26.2/30.8 27.7/31.5 27.2/31.7
R.m.s.d. bonds (Å) 0.051 0.003 0.003 0.006 0.01 0.01
R.m.s.d. angles () 1.587 0.60 0.60 1.05 1.03 1.04
† Values in parentheses reflect the highest resolution shell.
electronic reprint
intensity accumulation and uninterrupted sample rotation
during the 0.1 s read-out time of the detector are negligible
(Fig. 2 and x2 in the supporting information).
2.2. Image conversion
All MicroED measurements so far in our group have been
performed using a TVIPS TemCam-F416 camera. This
16 Mpixel camera performs rudimentary image corrections
internally using pre-recorded dark and gain maps, which
should be selected to match the energy of the electron
microscope, the exposure time and the signal strength of the
sample. To satisfy the real-time constraints of the system in
shutterless, or ‘rolling-shutter’, mode, the data rate is reduced
by 2  2 binning, yielding an effective camera size of 2028 
2048 square pixels with side length 31.2 mm. Furthermore, all
synchronous read-back of any of the microscope’s dynamically
changing parameters is disabled. In contrast to typical X-ray
diffraction experiments at a synchrotron source (Meyer et al.,
2014), the user must therefore supply additional information
to allow downstream processing software to reconstruct the
geometry of the experiment.
(a) The beam center. The intersection of the direct beam
with the surface of the detector plane is refined from userdefined initial values during data processing (Sauter et al.,
2004). With the procedure outlined in x2.1.1 above, the center
of the image is a good starting point. A computational alternative, which refines the initial estimate based on the intensity
variation in a single image (Baldwin & Henderson, 1984;
Vonrhein et al., 2011; Nederlof, van Genderen et al., 2013), is
given in x1 of the supporting information. This may be particularly useful if the image of the direct beam is drifting over
the course of data collection because of instabilities in the
electron-optical system.
356 Johan Hattne et al.  MicroED data collection and processing Acta Cryst. (2015). A71, 353–360
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Figure 1
After interacting with the sample the beam (amber rays) passes through the objective lens, which forms a diffraction pattern at the cross-section plane
and an image of the sample at the image plane. Only the diffraction pattern corresponding to the image of the crystal within the selected area aperture
will be visible. Several rays are omitted in these simplified illustrations and the size of the image plane is exaggerated for clarity. The scattering angle (2)
is indicated. (a) In bright field, the image of the crystal is magnified onto the detector (yellow rays). (b) In diffraction mode, the diffraction lens is
positioned to form a magnified image of the diffraction pattern (green rays) on the detector. The objective aperture at the cross-section plane is fully
open. (c) Owing to the magnification of the lenses, the distance d from the sample to the physical detector is typically much smaller than the distanceD to
the virtual detector. The distance to the virtual detector corresponds to the sample–detector distance in a lensless measurement using e.g. X-rays.
electronic reprint
(b) Rotation rate of the stage. While this is not directly
necessary for data reduction, it is used to determine the
rotation angle and range of each frame (see x2 in the
supporting information for details). Because the stage of an
electron microscope can generally be tilted both clockwise and
counterclockwise, and the small wavelengths (x2.3) make it
difficult to distinguish the handedness of the rotation, special
attention needs to be paid to the sign of the rotation rate.
(c) The virtual sample–detector distance (Fig. 1c). In principle, this can be determined from the magnification of the
electron microscope, but is preferably calibrated using the ring
spacing of a known powder diffraction pattern from e.g. gold
or graphite. The circularity of the observed rings also provides
a means to verify any astigmatism, which would result in a
non-circular pattern. Alternatively an accurate calibration can
be performed with standard crystals of known unit-cell
dimensions.
We have developed conversion tools that parse a sweep of
frames and output a corresponding set of diffraction images.
By combining the information provided by the camera system
in its output stream with information supplied by the user,
these tools produce images in the Super Marty View (SMV)
format, which is directly suitable for further processing in
several existing data reduction packages originally developed
for X-ray crystallography such as DIALS (Waterman et al.,
2013), MOSFLM (Leslie & Powell, 2007) and XDS (Kabsch,
2010b).
Owing to limitations in the SMV format, processing
programs are unaware of the specific details of the detector.
The parameters below are input directly into the processing
package, and can be determined from the data themselves.
(a) The precise interpretation of the detector gain, and
therefore its estimation, depends on the downstream processing software. Typically, it is determined as the ratio of the
variance and the mean of the intensities in a sufficiently large
region of background pixels (Leslie, 2006; Kabsch, 2010b).
Assuming the pixels are statistically independent, processing
programs can treat detector noise as the result of a Poisson
process after gain-correcting the intensity values.
(b) The camera does not flag dead, hot or otherwise
malfunctioning pixels. If their presence impairs data processing, these pixels can be discovered using ad hoc statistical
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Acta Cryst. (2015). A71, 353–360 Johan Hattne et al.  MicroED data collection and processing 357
Figure 2
Rocking curve of the catalase (0, 10, 8) reflection at d = 13.7 Å, recorded in ‘rolling shutter’ mode. In all panels ’ = 0 denotes the start of the data
collection, at which point the stage is not necessarily untilted. The rotation range in all images is ’ = 0.36. (a)–(h) The pixel intensities from eight
successive frames as recorded by the camera, such that each node in the mesh corresponds to one pixel. (i) The profile-fitted intensities as integrated by
MOSFLM, where the vertical error bars span one standard deviation. Additional rocking curves for several other spots from catalase and lysozyme are
given in x3 of the supporting information.
electronic reprint
methods outlined in x1 of the supporting information. Procedures on the TVIPS F416 camera can also help eliminate these
pixels.
(c) To minimize radiation damage to the sample, MicroED
data sets are collected in low-dose mode, and so far even the
strongest low-resolution reflections have been within the
linear response range of the detector. To date, there has been
no need to handle overloaded pixels.
2.3. Diffraction geometry and indexing
As of this writing, we are routinely indexing and integrating
MicroED data for various samples using MOSFLM/
AIMLESS (Leslie & Powell, 2007; Evans & Murshudov, 2013)
and XDS (Kabsch, 2010b). As these software packages are
primarily developed for X-ray crystallography, it is worthwhile
to keep the unique aspects of electron diffraction in mind
during data reduction.
The de Broglie wavelengths used for MicroED data
collection at an acceleration voltage of 200 kV are about 50
shorter than the corresponding electromagnetic wavelengths
typically used for crystallographic structure determination
with X-rays. Consequently, scattering angles are smaller, the
Ewald sphere is less curved, and for any orientation of the
crystal in the beam, the reflections in a diffracting condition
fall within an almost planar wedge of reciprocal space
(Nannenga & Gonen, 2014). This presents a challenge for
autoindexing procedures, which rely on the periodicity in a
three-dimensional space to recover both the spacing and
orientation of the crystal’s lattice (Steller et al., 1997; Kabsch,
2010a; Gildea et al., 2014).
In a MicroED experiment, the number of spots must be
large enough for their periodic arrangement to become
apparent, and their spanned volume must be big enough for
the three-dimensional lattice to be determined. These
requirements are generally satisfied by well diffracting crystals
measured by continuous rotation, and we find that five to ten
images spanning a 20 wedge provide sufficient information
for autoindexing to work without a priori knowledge of the
unit-cell parameters. More images may be required because,
for well ordered crystals, the narrow bandpass of the electron
beam (x2.1.2) leads to relatively few discernible Bragg spots
on each image. If the unit cell of the crystal is known and its
side lengths are unique, it is in principle possible to determine
the crystal’s orientation from a single image (Jiang et al., 2009)
but for unknown samples the above should suffice.
Diffraction data processing generally requires accurate
knowledge of the geometry of the measurement, particularly
the rotation range of the sample during each exposure. In
MicroED, the sample orientation is calculated during image
conversion as the product of the rotation rate and the timestamp of the exposure relative to the start of the measurement
(x2.2 and x2 in the supporting information). The uncertainties
in both factors are relatively large, resulting in even larger
inaccuracies in the derived rotation angle. Furthermore, under
the assumption that the error in the timestamp is symmetrically distributed around zero, any error in the rotation rate
causes the deviation of the calculated rotation angle from its
true value to compound over time. For this reason it is advisable to first attempt autoindexing with several frames spaced
widely enough to cover a sufficiently large wedge of reciprocal
space, but recorded close enough in time such that the relative
error in the rotation angle is small.
If the data reduction software fails to completely account
for errors in the crystal orientation by means of the refined
mis-setting angles, the residual may oftentimes be absorbed in
the mosaicity. In such cases, the mosaicity acts as an error sink
rather than an accurate model of lattice disorder. For small
unit cells this approach may work at the price of reduced
integration accuracy; for large unit cells, the ensuing spot
overlap may prevent successful processing altogether.
2.4. Integration, scaling and merging
The intensities in the first MicroED data sets were integrated and scaled using in-house software, which for simplicity
assumed proportionality between the maximum intensity
integrated for any reflection and the corresponding full
intensity (Iadanza & Gonen, 2014). This worked well because
the temporal intensity fluctuations in the electron beam are
very small. The ability to use existing software developed for
X-ray crystallography makes it straightforward to use more
sophisticated integration, scaling and merging protocols. In
particular, it is advisable to use the three-dimensional profile
of the integrated intensities whenever a reflection is observed
across multiple exposures of similar crystal orientations (Fig.
2). This profile-fitted intensity better estimates the corresponding full-intensity equivalent and helps to discriminate
against spurious noise peaks. While it is difficult to obtain
reliable estimates of the random and systematic errors in the
measured intensities, both the merging and the refinement
statistics for structures solved by MicroED (Table 1) suggest
that the data quality is comparable to that obtained using
conventional X-ray techniques.
In two of our studies a single nanocrystal was sufficient to
allow us to collect data sets with 80% completeness (Table
1). For certain lattice symmetries it may, however, be difficult
to collect a complete single-crystal data set because of the
limited tilt range of the stage (x2.1.2). Where several isomorphous data sets are available, merging the integrated intensities from multiple crystals can generally increase the
completeness. Multi-crystal merging does not necessarily
increase completeness if the crystals tend to align with their
crystallographic axes in similar directions (Nannenga, Shi,
Hattne et al., 2014; Yonekura et al., 2015). In the case of bovine
liver catalase, which commonly crystallizes as plates with the
crystallographic c axis aligned perpendicular to the plane of
the crystal, the limited tilt angle prevents a cone of reciprocal
space from entering a diffractive condition. If the stage can
only be tilted through  in such a case, the fraction of
reciprocal space that can be observed, assuming all possible
rotations around the c axis can be measured, is given by
sin (). In our setup, where the tilt angle is limited to 70, at
most 94% of reciprocal space can be integrated for a system
358 Johan Hattne et al.  MicroED data collection and processing Acta Cryst. (2015). A71, 353–360
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such as catalase (Glaeser et al., 1989). Examples of the effects
of systematically missing data on the final density in MicroED
were given in Nannenga & Gonen (2014). However, for cases
where the crystals do not exhibit a preferred orientation on
the grid, merging data from multiple crystals can yield data
sets with 100% completeness (Shi et al., 2013).
2.5. Phasing and refinement
All our MicroED structures to date have been phased by
molecular replacement, using standard programs from X-ray
crystallography (Vagin & Teplyakov, 1997; McCoy et al., 2007).
Subsequent manual rebuilding with interactive tools such as
Coot (Emsley et al., 2010) and refinement using standard
refinement packages (Murshudov et al., 2011; Afonine et al.,
2012) yield results of similar quality as models derived from
X-ray diffraction data to the same resolution (Nannenga, Shi,
Hattne et al., 2014; Nannenga, Shi, Leslie & Gonen, 2014). As
in X-ray crystallography, automated tools such as BUCCANEER or phenix.ligand_identification can be used to reduce
the manual labor and subjective bias from visual interpretation of density maps (Cowtan, 2006; Terwilliger et al., 2007).
Currently CNS (Brunger, 2007), Phaser, phenix.refine and
REFMAC take electron scattering factors into account during
structure-factor calculation; other software may assume the
diffracted intensities are due to the scattering of X-rays. At the
resolution of the data sets determined by MicroED so far
(Table 1), the electron scattering factors can have a noticeable
impact on the refined model (Yonekura et al., 2015). For
molecular replacement, where the precise details of the fit of
the search model to the processed data are less important, the
significance of electron scattering factors is minor.
3. Conclusion
MicroED builds on decades of work, both in X-ray crystallography and cryo-EM. With the recent determination of
catalase and Ca2+-ATPase, the method matured beyond the
lysozyme benchmark commonly used to evaluate new techniques in crystallography. The fundamental bottlenecks that
prevented the success of electron diffraction structure solution
from three-dimensional crystals have been overcome by
advancements in the way in which data are collected,
improvements in detector hardware and more powerful software algorithms, such that crystal structures can now be
determined using a transmission electron microscope and
equipment standard in most cryo-EM laboratories. The use of
continuous rotation not only addresses issues with the partiality of the integrated intensities and the imperfect orientation
of the stage, but appears to offset the adverse effects of diffuse
and dynamic scattering (Nannenga, Shi, Leslie & Gonen,
2014). In particular, as long as the crystals are <400 nm thick,
the integrated intensities are accurate enough to allow phasing
by molecular replacement and subsequent atomic refinement.
It is not clear where the upper limits on sample thickness lie, as
there appears to be a disconnect between theory and experiment. Recent simulations on perfect lysozyme crystals suggest
<100 nm to be the upper limit for refinement to Rwork < 30% at
2.5 Å resolution (Subramanian et al., 2015), but the authors
note that effects not accounted for by the simulation may
influence the estimate. Certainly, in our hands, and in the
hands of other laboratories, the upper limit has been closer to
400 nm.
Depending on the quality of the microscope’s calibration
there are various corrections that may need to be applied to
electron diffraction images. Several aberrations (e.g. astigmatism, x2.2) can be corrected by calibrating the electron
microscope, and for these, diagnostic tools are sufficient.
Other anomalies, such as a variable rotation rate of the stage
or the beam center drift, are more efficiently corrected during
data analysis. Improved corrections in the analysis software, as
well as investigations of the effects of instrument improvements such as energy filters, are a topic of future research,
which will lead to more accurate integrated intensities.
The next frontier for MicroED appears to be experimental
phasing, which relies on accurately integrated intensities and
improved electron scattering tables for mapping atomic
models to structure factors. While several laboratories are
working on heavy metal isomorphous replacement, other
strategies may also be possible. Imaging crystals followed by
image processing can yield initial phase information that could
then be extended by established procedures (Henderson et al.,
1986; Gipson et al., 2011; Wisedchaisri & Gonen, 2011;
Nederlof, Li et al., 2013; Scherer et al., 2014). Single-particle
reconstructions of the particles of interest quite routinely yield
a low-resolution density map that could then be used to phase
the MicroED data. These avenues highlight the strengths of
using a transmission electron microscope for structure determination as both phase and amplitude can be recorded
accurately. As MicroED matures we expect that the method
will have a long and lasting impact on the field of structural
biology.
4. Software availability
The source code for the image conversion software is available
for download from http://cryoem.janelia.org/pages/MicroED.
Acknowledgements
We thank Kay Diederichs (Universität Konstanz), Garib
Murshudov (MRC LMB), Pavel Afonine (LBNL) and
Nathaniel Echols (LBNL) for advice with data processing and
model refinement. We also thank Hans Tietz (TVIPS), Peter
Sparlinek (TVIPS), Reza Ghadimi (TVIPS) and Matthias
Stumpf (Fischione) for technical support. Work in the Gonen
laboratory is supported by the Howard Hughes Medical
Institute. AGWL is supported by CCP4, the Medical Research
Council (U105184325) and BBSRC (BB/F020384/1).
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