

beamlines

VMXi: a fully automated, fully remote, high-flux in situ macromolecular crystallography beamline
aDiamond Light Source, Harwell Science and Innovation Campus, Chilton, Didcot, Oxfordshire
OX11 0DE, UK, and bDepartment of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej
10, 8000 Aarhus C, Denmark
*Correspondence e-mail: [email protected], [email protected]
VMXi is a new high-flux microfocus macromolecular crystallography beamline at Diamond Light Source. The beamline, dedicated to fully automated and fully remote data collection of macromolecular crystals in situ, allows rapid screening of hundreds of crystallization plates from multiple user groups. Its main purpose is to give fast feedback at the complex stages of crystallization and crystal optimization, but it also enables data collection of small and delicate samples that are particularly difficult to harvest using conventional cryo-methods, crystals grown in the lipidic cubic phase, and allows for multi-crystal data collections in drug discovery programs. The beamline is equipped with two monochromators: one with a narrow band-pass and fine energy resolution (optimal for regular oscillation experiments), and one with a wide band-pass and a high (optimal for fast screening). The beamline has a state-of-the-art detector and custom goniometry that allows fast data collection. This paper describes the beamline design, current status and future plans.
Keywords: room-temperature data collection; in situ diffraction experiments; automated beamline operation; serial crystallography.
1. Introduction
As we are looking for answers to ever more complex scientific questions in structural biology, projects are becoming increasingly challenging. Many of the samples we are studying are difficult to express and purify, target proteins are likely to be flexible, crystallization from miniscule amounts of sample is highly demanding, and, when crystals are obtained, they are often small and diffract poorly.
Here we introduce the VMXi beamline at Diamond Light Source (DLS), a new microfocus macromolecular crystallography (MX) beamline dedicated to fully automatic screening and data collection from crystals in situ. The VMXi beamline addresses a number of related current needs in MX: (1) identifying diffraction-quality crystals for biological systems that are difficult and expensive to crystallize (e.g. membrane proteins; large complexes), (2) obtaining diffraction datasets for the biological systems of which crystals are routinely resistant to cryogenic harvesting (e.g. large complexes; viruses; membrane proteins), and (3) characterizing protein–ligand interactions rapidly by collecting large numbers of datasets from similar crystals with different compounds added (fragment screening and industrial drug development).
Crystallization is often a very long and iterative process where initial `promising' conditions are optimized until crystals suitable for the diffraction experiments are obtained. Crystallization optimization is frequently undertaken without X-ray diffraction information. Crystals are more often than not optimized based on their appearance, due to the difficulty of cryo-cooling and shipping every potential sample to the synchrotron. Standard procedures when preparing crystals for cryo-cooled data collection involve the manual manipulation of individual crystals, soaking them in cryo-protectants and subsequent cryo-cooling. Inevitably, the mechanical and osmotic stress that occurs during these steps may significantly affect the diffraction capabilities of the crystal.
The in situ diffraction approach that VMXi is providing means that (1) experiments can be carried out without any manipulation of individual crystals, thus preserving the crystal integrity, (2) immediate feedback on the diffraction, crystal quality, unit-cell parameters and even in the case of micro-crystals, and (3) the method can be fully automated with high reliability.
The ability to rapidly characterize the diffraction properties of crystals using in situ diffraction provides a particular competitive edge for the analysis of unstable large
macromolecular complexes, membrane proteins, and for the assessment of initial micro-crystal
hits. At VMXi it is possible to test whether your `micro crystal' hits are protein
and whether they diffract, providing essential and immediate feedback, so that either
crystals can be further optimized or, equally importantly, false positives can be
rapidly discarded, saving both time and money for the researcher. This is particularly
valuable in the case of membrane protein crystals grown in the lipidic cubic phase
where the harvesting step is extremely problematic (Caffrey, 2003).
The development of VMXi has benefitted from recent developments in automation and
in situ data collection at other beamlines around the world and from significant technological
developments. As synchrotron beams have become brighter and better focused, and detector
readout has become faster and more sensitive (Casanas et al., 2016; Rajendran et al., 2011
; Aishima et al., 2010
), we have seen a surge in multi-crystal room-temperature data collection (Broecker
et al., 2018
; Aller et al., 2015
). Crystal radiation damage can be outrun due to the increased dose-rate (Owen et al., 2012
; Schubert et al., 2016
; Chapman et al., 2014
) making it possible to collect small wedges of data at room temperature. Data collection
and data processing tools have evolved around these new developments and it is now
standard practice using in situ data collection to be able to obtain full structural information from partial datasets
on multiple samples (Foadi et al., 2013
; Zander et al., 2015
; Santoni et al., 2017
; Stellato et al., 2014
). It is a huge step forward for many challenging projects to be able to analyse samples
in situ, bypassing the additional sample manipulation associated with cryo-cooling methods.
In situ crystallography is possible using a laboratory-based X-ray source (PlateMate, Rigaku)
(Hargreaves, 2012), but is now also offered routinely at a number of synchrotron facilities around
the world, including the DLS beamlines I03 and I24 (Aller et al., 2015
; Axford et al., 2012
; Materlik et al., 2015
; Allan et al., 2015
), the SLS beamline X06DA (PXIII) (Bingel-Erlenmeyer et al., 2011
), the ESRF beamlines BM30 and BM14 (le Maire et al., 2011
), the APS beamline GM/CA (Broecker et al., 2016
) and the PETRA beamline P14 (DESY, Hamburg, Germany).
1.1. Beamline overview
The VMXi beamline replaces the tunable MX beamline I02 (Allan et al., 2015; Grimes et al., 2018
) which ended operations in August 2016. The original beamline layout has been extended
by moving the sample position downstream and adding an additional experimental hutch
and sample storage area. This configuration has provided a completely new sample area
and allowed I02 to continue user operations during the build and installation of the
VMXi beamline. The optical path has been reconfigured by repurposing components from
the original I02 layout while extending specifications by adding a multilayer monochromator,
a secondary source point and a pair of microfocus bimorph mirrors. In addition, the
beamline is equipped with a new state-of-the-art detector and custom goniometry allowing
very fast and precise data collections.
1.2. Operational overview
The VMXi beamline introduces a fundamentally different approach to how scientists
use and interact with a beamline. The extensive level of automation introduced means
that users no longer operate the beamline directly and have no specific beam time
slot allocated. Instead, crystallization plates are stored at the beamline and users
evaluate the crystallization results via a bespoke GUI in SynchWeb (Fisher et al., 2015). Data collection requests are detailed and submitted from the web interface and
all requested beamline operations are carried out in a fully automated fashion. Data
are processed automatically and the users are only notified when new data are available
for review. This operating principle ensures optimal use of the available X-rays by
decoupling the decision making of which data to collect and how to collect the data
from beam time. It is matched to the unpredictable nature of the crystallization process
where beam access is required once crystals appear rather than the other way around.
2. X-ray beam path
The VMXi X-ray beam path stretches 47 m from the source at the 2 m in vacuum U23 undulator (located in the centre of the 02 straight section of the DLS storage
ring) to the sample position as outlined in Fig. 1 and detailed in Table 1
.
|
![]() |
Figure 1 Schematic of the beamline outline detailing the main optical components along the beam path from source to sample. Figure not drawn to scale but distances to the source in metres for each component are marked. |
2.1. Monochromators
The beamline has a unique configuration with two separate monochromators which can be used depending on the experimental requirements: the original double-crystal monochromator (DCM) for narrow band-pass beam with lower
and the new double-multilayer monochromator (DMM) for broader band-pass beam with higher The monochromators are designed to enable beamline operation in either DCM or DMM configuration.The DCM is an in-house upgrade of an original FMB Oxford design (Allan et al., 2015). The cryo-cooled Si(111) fixed-exit monochromator delivers a full energy range from
5 to 25 keV with a band-pass (ΔE/E) of <10−4 giving a at 13 keV of >2 × 1012 photons s−1 at the sample position. The DCM is the preferred standard option for MX data collection
typically used for collecting oscillation data on single crystals and for measuring
for phasing purposes or low-dose X-ray scanning for locating small crystals.
The DMM is an in-house design described elsewhere (manuscript in preparation). This
monochromator has two separate silicon crystals with two distinct multilayer coatings
stripes each. The multilayers coatings are built of alternate layers of ruthenium
(Ru) and boron carbide (B4C) with layer thicknesses of 2.0 nm and 2.4 nm for the two stripes, respectively (Rigaku).
By using either of the stripes, the DMM delivers beam across the energy range 10–25 keV
with a band-pass (ΔE/E) of <5 × 10−2 giving a at 13 keV of >1014 photons s−1 at the sample position. The DMM is primarily used when a higher and broader band-pass is advantageous such as for raster scanning across large regions
of a crystallization drop. The higher increases the speed at which large area scans can be completed, while the broader
band-pass also improves the likelihood of correct cell parameters being assigned from
still images by generating an effect akin to a small oscillation (Nave, 2014). Initial tests (see the Results section
) suggest that, despite severe radiation damage, single-crystal oscillation data collections
using the DMM can be processed with standard software and produce good quality data.
We expect that, as the crystal lifetime is better defined and optimized, the DMM will
also be routinely used for oscillation data collection.
We have also installed a low band-pass diamond filter upstream from the DMM to prevent
low-energy radiation from the storage ring being reflected off the multilayer surfaces
due to the very shallow operating angles used. This could cause low-energy contamination
of diffraction as well as significant radiation damage to hardware further along the
beam path. The specification and operational ranges for these diamond filters have
been summarized in Table 1.
2.2. Focusing optics
2.2.1. Horizontal pre-focusing mirror and the secondary source
To achieve a micro-focused beam at the sample position, we have introduced a secondary
source point in the horizontal plane at 32 m by repurposing the horizontal-focusing
bimorph mirror (HFM) previously used on the I02 beamline (Allan et al., 2015; Grimes et al., 2018
). The mirror angle of 2.7 mrad has been maintained but the bimorph voltages were
increased to adjust the curvature to move the focus from the 40 m it had been previously
to the new secondary source point at 32 m. This enables us to obtain a horizontal
beam size at the sample position of 6 µm (FWHM) which can be further reduced down
to 1–2 µm by trimming the beam at the secondary source point.
The new secondary source combines movable slits, a beam-position monitor, a diamond scintillator screen and a camera imaging the beam to facilitate optimization of the secondary source beam properties.
2.2.2. Microfocusing mirrors
The beamline is equipped with a horizontal microfocus mirror (HMFM) and a vertical
microfocus mirror (VMFM). The microfocus mirrors are located at the front of the new
VMXi mini-hutch, 2 m and 1 m from the sample, respectively. To achieve optimal focused
beam given the very tight location restrictions, both mirrors share a single vacuum
vessel. The microfocus mirrors are super-polished SiO2 substrate with 16 side-mounted piezo elements for shape adjustment (Alcock et al., 2015). The mirrors are polished to an elliptical shape to enable optimal focusing and
defocusing and operate at 3 mrad. The mirrors have three different 12 mm-wide reflective
areas to provide optimal reflectivity and harmonic rejection across the full energy
range: one uncoated area used below 10 keV, a rhodium-coated area used between 10
and 18 keV, and finally a platinum-coated area providing optimal reflectivity at energies
above 18 keV. Beam size and focal point can be modified by adjusting the voltage supplied
to the 16 piezo actuators from the high-voltage power supply (CAEN ELS SRL). To achieve
the focal range of 0 to 300 mm downstream from the sample and focal sizes ranging
from 5 µm × 5 µm to 30 µm × 30 µm, the mirror voltages are operated between −1500 V
and +1500 V (Fig. 2
).
![]() |
Figure 2 Current beam profile measured on a PIN diode while scanning a 10 µm-diameter aperture across the beam vertically and horizontally at the sample position. The insert shows an image of the attenuated beam on a YAG scintillator. The image depicts a 30 µm × 30 µm area and the beam is approximately 10 µm across. Further optimization of the beam focus is ongoing. |
The mirror vessel also includes a `dissector' located upstream of the mirrors. The
dissector has dual functionality and is designed to help with mirror optimization
and also to act as a beam monitoring aperture. The small tungsten apertures of 10
and 20 µm in the horizontal and vertical planes are used to optimize the beam focus,
using pencil-beam scans required for piezo voltage optimization (Sutter et al., 2012). A third aperture in each dissector (3 mm in the horizontal and 1.2 mm in the vertical)
is used to trim the incoming beam to match the optical aperture of the mirrors. In
addition, these beam-trimming apertures allow drain current measurement providing
beam position feedback for the upstream optics.
2.3. Beam conditioning
As the beam converges towards the sample position a final set of elements are used to condition and fine-tune the beam. The beam passes through a set of slits, which are set to the nominal beam size to eliminate any unwanted scatter produced upstream. These slits can also be used to create a smaller aperture to reduce beam divergence. This will generate sharper Bragg reflections at the detector to improve the signal-to-noise ratio and resolve Bragg reflections for larger unit cells.
The beam can be attenuated by using aluminium and silver foils of various thickness
(from 10 µm to 1.5 mm Al and 0.1 mm to 0.8 mm Ag). The filters are mounted on three
motorized wheels each holding sets of ten foils [Fig. 3(a)] that can be placed in the beam path giving rise to 1000 individual filter combinations,
giving a fine range of beam attenuation across the energy range 10–25 keV for both
DCM and DMM beams. The beam position is carefully monitored using a four-quadrant
diamond-based beam-position monitor (XBPM) (CIVIDEC Instrumentation GmbH) [Fig. 3(b)
]. Attenuator filters and the XBPM are housed in a helium-filled environment to prevent
oxidation and to aid motor cooling. The oxygen level in the chamber is monitored by
using an InPro oxygen sensor (Mettler Toledo).
![]() |
Figure 3 (a) The attenuator wheel assembly. The foils are held inside each of the inserts and the beam passes through the point where all three wheels intersect. (b) CIVIDEC XBPM mount. The four active pads used for monitoring beam intensity and position are coloured pink. (c) Sample shutter showing the stepped arrangement of the blades that allow for altering patterns of opening and closing. Blue is 50/50 and pink is 75/25. (d) Goniometer assembly showing the air-bearing, the scissor-like x–y translation stages, the z motion, the mirror interferometers and the tilt mechanism. |
Having passed through the XBPM, the beam reaches the rotary shutter. The shutter is
a rotating disk positioned perpendicular to the beam axis and is driven by an EC-type
motor (Maxon Motors) [Fig. 3(c)]. The design of the shutter allows it to be used in a stop–start mode as a very fast
conventional shutter with an opening time from fully closed to fully opened of only
50 µs. It is also possible to operate the shutter in continuous mode where the disk
rotates and the beam is `chopped' eight times per revolution of the wheel. The motor
is able to reach a speed of 5625 rev min−1 enabling 750 Hz data collection frequency, matching the frame rate capabilities of
the beamline detector. The blades on the chopper disk have a tiered design that allows
the ratio of open/close time to be varied between 50/50 and re-focusing 70/25 in the
current configuration by translating the chopper across the beam. To minimize background,
the `chopper' mode can be synchronized with the detector to allow a sample to only
be exposed to X-rays for a fraction of each collected frame rather than in a continuous
exposure. This mode will be used when collecting serial crystallography data.
The final element before the sample is a set of three platinum–iridium apertures,
10, 50 or 200 µm in diameter (Agar Scientific) [Fig. 4(a)]. The apertures remove any unwanted scatter, helping to reduce background on the
detector.
![]() |
Figure 4 (a) Global view of the sample environment while a sample well is being imaged. (b) Overview of the VMXi experimental hutch, the Rock Imager storage units and the six-axis robot. (c) View of the 293 K sample local storage section. Empty and loaded sample holders are shown as well as a loaded sample holder in transit to the goniometer. The internal drum of the rotation load lock that allows samples to be loaded and unloaded through the closed radiation enclosure is also shown. |
The beamstop is the final component in the beam path after the sample position before
the detector [Fig. 4(a)]. In addition to preventing damage to the detector, the beamstop is also crucial
for maximizing the quality of the diffraction data. The design reduces unwanted background
while still allowing the collection of good quality data at low resolution. The current
beamstop is a set of interlinked tubes as first described by Meents et al. (2017
). In the VMXi configuration, the beamstop is made of three interlocked platinum tubes
(400, 600 and 950 µm outer diameter) with the large tube plugged with gold wire and
lead. It can be positioned 15 mm behind the sample, and at this distance the beamstop
allows low-resolution reflections of approximately 93, 71 and 37 Å at energies of
10, 13 and 25 keV, respectively, to be recorded.
2.4. Detector
At the end of the beam path is an EigerX 4M detector (Dectris) (Johnson et al., 2012; Casanas et al., 2016
; Tinti et al., 2017
) [Table 2
and Fig. 4(a)
]. This detector has an active area of 155.2 mm × 162.5 mm (W × H) with a pixel size
of 75 µm × 75 µm. It is able to collect data continuously at 500 Hz and in short bursts
of up to 30 s at 750 Hz. When operating at full the limiting factor is the photon count rate of 2.4 MHz per pixel as well as the
bit depth of 12 bits. The detector performance will improve when VMXi starts operation
with a new Eiger2X 4M detector at the beginning of 2019. This detector will have a
significantly improved photon count rate, counter bit depth and effectively have no
readout time. Further improvements will await the availability of a suitable charge
integrating detector, which promises a tenfold increase in photon count rate.
|
2.5. Beam monitoring and feedback
For VMXi, all aspects of beam delivery and diagnosis are automated and three elements along the beam path provide feedback to maintain stable beam at the sample position. Firstly, drain current on the primary slits (located upstream from the monochromators) is used to monitor changes to the incoming beam from the storage ring. Secondly, changes in drain current on the dissector blades before the microfocus mirrors are used to adjust the pitch of the pre-focusing HFM. Finally, an X-ray beam-position monitor (CIVIDEC) upstream from the sample shutter is used to ensure that the beam is stable at the sample position by adjusting the horizontal and vertical pitch of the microfocus HMFM and VMFM. Monitoring currently runs at 10 Hz and feedback at 0.2 Hz but is disabled during data collection.
3. Sample path
To make unattended operations possible, VMXi has a fully automated sample path that
allows for the transfer of sample plates from storage outside the experimental hutch
to the goniometer inside the hutch, and back [Fig. 4(b)]. By storing the samples outside the radiation-shielded enclosure, we have maintained
easy access to stored samples even while the beamline is operating. Furthermore, this
set-up makes future upgrades to increase sample storage capacity straightforward,
without the need of modifications to beamline radiation shielding.
The beamline is currently set up to handle SBS-format crystallization plates (ANSI/SLAS 1-2004 through ANSI/SLAS 4-2004), and with appropriate adapters the beamline can handle smaller-sized plates. The SBS format has proved longevity and our assessment is that any future formats are likely to have either the same footprint with higher density or be smaller in which case adapters to mimic the SBS footprint can be used during a transition phase while upgrading the beamline to handle a new format.
3.1. Sample storage
User plates are stored on the beamline in one of two modified Rock Imager 1000 units
(Formulatrix, USA) operating at 277 K and 293 K, respectively [Fig. 4(b)]. These units store and automatically image up to 750 crystallization plates each.
Additional features have been added to the VMXi Rock Imagers in collaboration with
Formulatrix to allow full beamline integration.
The imaging modules in the Rock Imagers have been inverted to image crystallization
plates through the bottom of the plates (Fig. 5). This means that crystallization
drops are imaged from the same direction on and off the beamline enabling a more robust
sample alignment. Furthermore, the Rock Imagers have been fitted with an automation
load port (ALP) at the back of the units used for automatic transfer of plates between
storage and the beamline for diffraction experiments [Fig. 4(b)].
3.2. Sample transfer
Sample transfer and data collection have been implemented, both at the software and
hardware level, as separate concurrent processes so that sample loading and unloading
does not affect the beamline output and vice versa. To achieve this, a radiation-safe transfer system (load lock) shown in Figs. 4(b) and 4(c) allows samples to be loaded in an out through the radiation enclosure while data
are being collected. Furthermore, sample storage located inside the hutch allows twelve
plates to be kept next to the goniometer (six at 277 K and six at 293 K), thus allowing
quick exchange to the goniometer to maximize data collection time [Fig. 4(c)
].
A sample transfer starts with the crystallization plate being delivered to the ALP
in the Rock Imager. Once ejected via the ALP, the plate is picked up by a robot arm
(RV-2FL MELFA, Mitsubishi Electric) mounted on a track running perpendicular to the
beam path and alongside the Rock Imager storage units [Fig. 4(b)]. The robot arm delivers the plate to the load lock.
Once inside the shielding, the plate is picked up by a gantry robot (Sysmac Automation
Platform, Omron) and transferred to the local storage area. Holding plates in adjustable
high-precision plate holders [Figs. 3(d), 4(a) and 4(c)
] ensures repeatable positioning on the goniometer improving accuracy when collecting
data. Using individual holders reduces the time required to swap between data collection
at 277 K and 293 K as it prevents waiting for a common holder on the goniometer to
change temperature.
The waiting plate and holder are then transferred onto the goniometer [Figs. 3(d) and 4(a)
]. This procedure allows an exchange time of plates of less than 20 s. To maintain
the temperature of the 277 K plates and holders during data collection, the gantry
robot mounts an additional cold cover over the plate, while in cold storage, before
transferring the holder to the goniometer. This cold cover maintains the temperature
of a plate at 277 K for up to 15 min on the goniometer.
All steps in the transfer are monitored to capture any anomalies and prevent damage to the plates or holders. Gripper sensors, barcode scanner and a proximity laser have been integrated to give the system the ability to detect and identify the status of transfer at every step of the process.
3.3. Goniometry
The crucial challenge for the goniometer design has been to achieve speed and precision
to enable rapid translocation to the desired drop position within the SBS format while
aligning and rotating micrometre-sized crystals in the beam (Table 2). The goniometer design enables data collection while oscillating the sample (omega
scans) and data collection while moving the sample through the beam (area scans),
and combinations of the two. The novel goniometer design [Fig. 3(d)
] has a rotation axis (RT300L, Nelson Air) at the base aligned to the focal point
of the beam. On this air bearing, we have placed the sample translation axes where
a scissor-like design with two horizontal translations at the base (EC-type, Maxon
Motors) actuate on two arms creating virtual horizontal and vertical sample axes as
seen in Figs. 3(d)
and 4(a)
. This motor configuration allows for very fast motions up to 100 mm s−1 without bulky translation stages. Given the distance from the motor encoders to the
sample and the dynamic nature of the motions we are using interferometers (Attocube)
mounted at the base of the sample holder to account for any parasitic moves during
data collection and make on-the-fly adjustments to correct them [Fig. 3(d)
].
3.4. Sample imaging
To improve the success of matching the images marked by the users to those collected
at the beamline, thus ensuring a good hit rate, the beamline is equipped with a Mag.x
125 vision system (Qioptiq) and a 6 MP Manta G609-B monochrome camera (Allied Vision)
[Fig. 4(a)]. This system allows high-resolution images (>1 µm resolution) of entire drops (2 mm
by 2 mm field of view) to be captured as shown in Fig. 5(a). The system also includes a second Optem FUSION lens (Qioptiq) with a 0.6 mm hole
drilled through the centre, allowing the X-ray beam to pass through the vision system.
This second lens is used for beam commissioning (Fig. 2
). The lenses, which are co-axial to the beam, can be brought into position independently,
and are replaced by a helium-filled tube to reduce air scatter when X-ray data are
being collected (Fig. 4
). Samples are illuminated using a LED RGB backlight (PHLOX).
4. Control software
The beamline control software operates at three levels. An EPICS interface controls
beamline hardware (EPICS, 1994) at the lowest level, and provides an interface that the higher-level software (GDA; GDA, 2011
) has access to. GDA synchronizes all individual actions required to operate the beamline. Finally, users
interact with the VMXi beamline solely through a bespoke GUI in SynchWeb (Fisher et al., 2015
) that provides the third level of software control. The key difference in the way
VMXi operates, compared with other DLS beamlines, is that users never directly control
the beamline. The user input is written as configuration settings to the ISPyB database
(Delageniere et al., 2011
) and these parameters are used by GDA to action data collection.
Beamline autonomy is provided by GDA running two separate control loops. One, is solely dedicated to loading and unloading samples to and from the beamline. The
second control loop, data collection, is responsible for all of the routines needed
from the point a sample is loaded on to the goniometer to the point where all data
are collected and the plate is ready for unloading. To provide robustness to the system,
both processes are separate and only linked via the status of the sample on the goniometer
(Sharpe, 2018).
Complex routines, like image matching and sample prioritizing, are plugged in as external resources. This allows for each of the elements in the process to be optimized separately with minimal dependencies and permits expanding functionality as required with minimal risk to operations.
Robustness and error detection are critical for a fully automated beamline. To prevent clashes during operation, a range of hardware such as limit switches, cameras, sensors and lasers are used to confirm that hardware and samples are in the correct location prior to any actions. Error analysis and management is controlled by the GDA software coordinating all aspects of beam delivery, data collections and sample handling.
5. User workflow
5.1. General process
As described previously, the beamline operates automatically from data input parameters defined by the users. Users set up their crystallization experiments and review progress. Then, they mark regions or points to which data collection parameters can be assigned. Once these parameters are set up and the plate data collection has been requested, there is no further user involvement in the diffraction experiment until it comes to reviewing results and data processing.
The beamline is charged with loading and unloading the correct samples, locating the points or regions once the samples are on the beamline, preparing the beamline with the correct experimental settings, collecting the datasets and presenting the processing results.
5.2. User input via SynchWeb
An overview of the user interface in SynchWeb can be seen in Fig. 5. The interface currently captures all the required sample information for safe beamline
operation prior to the crystallization plate arriving at the beamline. The information
gathered also includes barcode references and storage temperatures that permit the
beamline staff to load the samples in their correct location. Once sample barcodes
are scanned in the storage units, the barcode links the plate to the stored information
in the database. The crystallization plate is then imaged automatically according
to a predefined schedule and users are notified via email whenever new imaging has
been completed.
![]() |
Figure 5 (a) The GUI tools in SynchWeb that allow users to review crystallization results, annotate drops, mark points and select regions for data collection. (b) SynchWeb view for setting data collection parameters and requesting collection of data. |
As the users review their samples, they can mark points or regions on the sample images.
These markers act as collection identifiers [Figs. 5(a) and 6(a)
]. Once the user has marked one or more points or regions, diffraction data collection
can be set up. The SynchWeb interface allows the user to assign a set of experimental
data collection parameters to each point or region [Fig. 5(b)
]. Once the users have supplied the required parameters the plate can be submitted
for data collection. At this point, the plate joins a cohort of samples ready to be
processed by the beamline for data collection.
![]() |
Figure 6 Examples of data collection outputs in SynchWeb. (a, b) Images before and after data collection. Note the extreme radiation damage observed in the areas marked for data collection. (c, d) Area scan over groups of crystals. The overlaid heat-maps show where the highest number of diffraction spots were recorded. Similar overlay for (e) an area with crystalline material and long needles and (f) precipitated protein obscuring a crystal. |
When the beamline is ready for a new plate to be transferred to a free sample holder, the sample loading routine queries the database for the next plate to load. A selection filter is employed to determine the next plate to be selected. The selection criteria can be optimized to improve data output and to make best use of beam time available. Once a plate has been selected, it is conveyed to the beamline for data collection.
5.3. Sample alignment
The alignment of a drop for data collection is a fully automated multi-step process. The first step is to position the drop by scanning it through the focal plane and look for in focus features. The second step is to create an extended-focus image by merging twelve images taken every 20 µm as the drop is moved through the focal plane. The third step is to align this new image and the original image to determine any displacement and thereby convert marked points and regions to the goniometer position.
For oscillation data collection we include an additional analysis for in focus features in a narrow region around the marked point to ensure that the marked point is on the rotation axis and stays in the beam during oscillation. Finally, we do also have to shift the drop position before starting data collection to correct for the optical distortion caused by the plastic and liquid. This is a plate-specific parameter and varies between 30 and 180 µm for the plates tested on the beamline so far.
5.4. Data processing and outputs via SynchWeb
When the requested diffraction data collections for a plate have been completed and
are available for review and processing, the user is notified by email. At the moment,
automatic data processing relies on existing pipelines used by other MX beamlines
at DLS. For example, Xia2 (Winter et al., 2013) image analysis is used to analyse grid scans and produce heat maps that can be displayed
in SynchWeb [Figs. 6(c)–6(f)
]. Xia2 is also used to index, integrate and scale the individual oscillation datasets
using DIALS (Winter et al., 2018
) (Table 3
).
|
Due to the high volume of data and the complexity of the decisions needed to arrive at a final dataset, further developments in software are ongoing. They will eventually allow users to easily review hundreds of partial datasets across multiple plates. The outcome can either feed back into the crystallization process or piece together all the partial information to a complete dataset and structure determination.
6. Results
The beamline user programme is still in its infancy. During the first two runs with limited user access, five user groups have used VMXi and around 30 plates have been loaded onto the beamline producing around 1500 datasets. The beamline is proving useful at both screening through crystallization conditions and for oscillation data collections.
As shown in Fig. 6(a), users are able to mark points of interest for the beamline to collect and, as seen
in Fig. 6(b)
, once these data collections are executed, samples are usually destroyed. Nevertheless,
as illustrated in Table 3
, each individual data collection (typically spanning 60°) produces good statistics
and these data collections can be easily merged in order to produce a complete dataset.
Users have also been able to screen through their samples and, by assessing the resulting
heat maps in SynchWeb [Figs. 6(c) and 6(d)], have found suitable conditions for data collection that are currently being tested
further. One user group has been able to discard certain conditions due to the presence
of salt crystals and others have been able to separate between two different crystal
forms within the same condition as seen in Figs. 6(e) and 6(f)
.
7. Discussion
The VMXi beamline is now providing dedicated in situ capabilities to the MX community. The improved microfocus optics with two monochromators options, a unique setup and 750 Hz data collection give this beamline unique capabilities that will enable cutting-edge science for some of the most challenging projects in structural biology. The automated and remote operation will improve the link between the work taking place in the laboratory and the resulting data quality, thereby speeding up the process from target selection to structural information. The high throughput and automated processing will make multi-crystal data collection routine and enable users to undertake new kinds of experiments on their samples that are not currently possible or are too complex.
With the increased availability of in situ beam time, the crystallization plate will now also serve as the sample holder. The
current available plates and holders are likely to evolve. Improving the precision
of drop location and the X-ray transparency are key developments required. Setting
up crystallization between X-ray transparent sheets has already proven to greatly
reduce optical artefacts and improve sample localization (Axford et al., 2016) and will be available to users soon. This format is also well suited for data collection
from membrane protein crystals grown in the lipidic cubic phase. We also suggest revisiting
the free interface diffusion approach to crystallization, now that in situ data collection means crystals do not have to be recovered or subsequently be reproduced
in a vapour diffusion setup.
The importance of structure-based drug design is clearly recognized in the commitment of all major pharmaceutical companies as a fully embedded process in the early stage of their drug discovery programs. The XChem facility based at DLS dedicated to fragment screening has been hugely successful operating with a cryo-crystallography approach, but is likely to benefit from an in situ approach for at least initial screening, something we will explore further in the coming year. The potential advantage would be to increase the chances of finding bound fragments by collecting diffraction data from more crystals in each drop in situ than are currently harvested for cryo-cooling. Sufficient high-quality data from multiple samples would help to assess fragment binding without the need for additional sample handling.
Further to in situ data collection, the unique properties of VMXi provide a platform for exploring synchrotron-based
serial crystallography (Diederichs & Wang, 2017; Owen et al., 2017
). In collaboration with UK XFEL Hub, we are testing the most suitable types of experiments
that can be added to the VMXi portfolio. For some projects, VMXi will provide the
speed and required to generate serial crystallography data, while for other projects it can
provide the required beam time to optimize and delivery in preparation for XFEL beam time. Once the requirements and scope are
better defined, the beamline user program can be adapted to suit these requirements
helping the user community make serial crystallography data collection more accessible.
Acknowledgements
The authors are grateful for the tremendous support received from groups across the DLS organization during this work. We would in particular acknowledge expert contribution from Lucia Alianelli, Trevor Bates, Dave Butler, Nick Dawkins, Stuart Fisher, Lee Hudson, Karl Levik, Andrew Male, Charles Mita, James O'Hea, Mike Smith, Chris Sharpe and the technical staff of the MX village. We also want to thank Dave Brown (Chair) and the rest of our User Working Group for guidance and encouragement.
References
Aishima, J., Owen, R. L., Axford, D., Shepherd, E., Winter, G., Levik, K., Gibbons,
P., Ashton, A. & Evans, G. (2010). Acta Cryst. D66, 1032–1035. Web of Science CrossRef CAS IUCr Journals Google Scholar
Alcock, S. G., Nistea, I., Sutter, J. P., Sawhney, K., Fermé, J.-J., Thellièr, C.
& Peverini, L. (2015). J. Synchrotron Rad. 22, 10–15. Web of Science CrossRef CAS IUCr Journals Google Scholar
Allan, D. R., Collins, S. P., Evans, G., Hall, D., McAuley, K., Owen, R. L., Sorensen,
T., Tang, C. C., von Delft, F., Wagner, A. & Wilhelm, H. (2015). Eur. Phys. J. Plus, 130, 56. Web of Science CrossRef Google Scholar
Aller, P., Sanchez-Weatherby, J., Foadi, J., Winter, G., Lobley, C. M., Axford, D.,
Ashton, A. W., Bellini, D., Brandao-Neto, J., Culurgioni, S., Douangamath, A., Duman,
R., Evans, G., Fisher, S., Flaig, R., Hall, D. R., Lukacik, P., Mazzorana, M., McAuley,
K. E., Mykhaylyk, V., Owen, R. L., Paterson, N. G., Romano, P., Sandy, J., Sorensen,
T., von Delft, F., Wagner, A., Warren, A., Williams, M., Stuart, D. I. & Walsh, M.
A. (2015). Methods Mol. Biol. 1261, 233–253. CrossRef CAS Google Scholar
Axford, D., Aller, P., Sanchez-Weatherby, J. & Sandy, J. (2016). Acta Cryst. F72, 313–319. Web of Science CrossRef IUCr Journals Google Scholar
Axford, D., Owen, R. L., Aishima, J., Foadi, J., Morgan, A. W., Robinson, J. I., Nettleship,
J. E., Owens, R. J., Moraes, I., Fry, E. E., Grimes, J. M., Harlos, K., Kotecha, A.,
Ren, J., Sutton, G., Walter, T. S., Stuart, D. I. & Evans, G. (2012). Acta Cryst. D68, 592–600. Web of Science CrossRef CAS IUCr Journals Google Scholar
Bingel-Erlenmeyer, R., Olieric, V., Grimshaw, J. P. A., Gabadinho, J., Wang, X., Ebner,
S. G., Isenegger, A., Schneider, R., Schneider, J., Glettig, W., Pradervand, C., Panepucci,
E. H., Tomizaki, T., Wang, M. & Schulze-Briese, C. (2011). Cryst. Growth Des. 11, 916–923. CAS Google Scholar
Broecker, J., Klingel, V., Ou, W. L., Balo, A. R., Kissick, D. J., Ogata, C. M., Kuo,
A. & Ernst, O. P. (2016). Cryst. Growth Des. 16, 6318–6326. CrossRef CAS Google Scholar
Broecker, J., Morizumi, T., Ou, W. L., Klingel, V., Kuo, A., Kissick, D. J., Ishchenko,
A., Lee, M. Y., Xu, S., Makarov, O., Cherezov, V., Ogata, C. M. & Ernst, O. P. (2018).
Nat. Protoc. 13, 260–292. CrossRef CAS Google Scholar
Caffrey, M. (2003). J. Struct. Biol. 142, 108–132. Web of Science CrossRef PubMed CAS Google Scholar
Casanas, A., Warshamanage, R., Finke, A. D., Panepucci, E., Olieric, V., Nöll, A.,
Tampé, R., Brandstetter, S., Förster, A., Mueller, M., Schulze-Briese, C., Bunk, O.
& Wang, M. (2016). Acta Cryst. D72, 1036–1048. Web of Science CrossRef IUCr Journals Google Scholar
Chapman, H. N., Caleman, C. & Timneanu, N. (2014). Philos. Trans. R. Soc. London B Biol. Sci. 369, 20130313. CrossRef Google Scholar
Delagenière, S., Brenchereau, P., Launer, L., Ashton, A. W., Leal, R., Veyrier, S.,
Gabadinho, J., Gordon, E. J., Jones, S. D., Levik, K. E., McSweeney, S. M., Monaco,
S., Nanao, M., Spruce, D., Svensson, O., Walsh, M. A. & Leonard, G. A. (2011). Bioinformatics, 27, 3186–3192. Web of Science PubMed Google Scholar
Diederichs, K. & Wang, M. (2017). Methods Mol. Biol. 1607, 239–272. CrossRef CAS PubMed Google Scholar
EPICS (1994). Experimental Physics and Industrial Control System, https://www.aps.anl.gov/epics. Google Scholar
Fisher, S. J., Levik, K. E., Williams, M. A., Ashton, A. W. & McAuley, K. E. (2015).
J. Appl. Cryst. 48, 927–932. Web of Science CrossRef CAS IUCr Journals Google Scholar
Foadi, J., Aller, P., Alguel, Y., Cameron, A., Axford, D., Owen, R. L., Armour, W.,
Waterman, D. G., Iwata, S. & Evans, G. (2013). Acta Cryst. D69, 1617–1632. Web of Science CrossRef CAS IUCr Journals Google Scholar
GDA (2011). Generic Data Acquisition (GDA), https://www.opengda.org. Google Scholar
Grimes, J. M., Hall, D. R., Ashton, A. W., Evans, G., Owen, R. L., Wagner, A., McAuley,
K. E., von Delft, F., Orville, A. M., Sorensen, T., Walsh, M. A., Ginn, H. M. & Stuart,
D. I. (2018). Acta Cryst. D74, 152–166. CrossRef IUCr Journals Google Scholar
Hargreaves, D. (2012). J. Appl. Cryst. 45, 138–140. Web of Science CrossRef CAS IUCr Journals Google Scholar
Johnson, I., Bergamaschi, A., Buitenhuis, J., Dinapoli, R., Greiffenberg, D., Henrich,
B., Ikonen, T., Meier, G., Menzel, A., Mozzanica, A., Radicci, V., Satapathy, D. K.,
Schmitt, B. & Shi, X. (2012). J. Synchrotron Rad. 19, 1001–1005. Web of Science CrossRef CAS IUCr Journals Google Scholar
Maire, A. le, Gelin, M., Pochet, S., Hoh, F., Pirocchi, M., Guichou, J.-F., Ferrer,
J.-L. & Labesse, G. (2011). Acta Cryst. D67, 747–755. Web of Science CrossRef IUCr Journals Google Scholar
Materlik, G., Rayment, T. & Stuart, D. I. (2015). Philos. Trans. A Math. Phys. Eng. Sci. 373, 20130161. CrossRef Google Scholar
Meents, A., Wiedorn, M. O., Srajer, V., Henning, R., Sarrou, I., Bergtholdt, J., Barthelmess,
M., Reinke, P. Y. A., Dierksmeyer, D., Tolstikova, A., Schaible, S., Messerschmidt,
M., Ogata, C. M., Kissick, D. J., Taft, M. H., Manstein, D. J., Lieske, J., Oberthuer,
D., Fischetti, R. F. & Chapman, H. N. (2017). Nat. Commun. 8, 1281. Web of Science CrossRef PubMed Google Scholar
Nave, C. (2014). J. Synchrotron Rad. 21, 537–546. Web of Science CrossRef CAS IUCr Journals Google Scholar
Owen, R. L., Axford, D., Nettleship, J. E., Owens, R. J., Robinson, J. I., Morgan,
A. W., Doré, A. S., Lebon, G., Tate, C. G., Fry, E. E., Ren, J., Stuart, D. I. & Evans,
G. (2012). Acta Cryst. D68, 810–818. Web of Science CrossRef CAS IUCr Journals Google Scholar
Owen, R. L., Axford, D., Sherrell, D. A., Kuo, A., Ernst, O. P., Schulz, E. C., Miller,
R. J. D. & Mueller-Werkmeister, H. M. (2017). Acta Cryst. D73, 373–378. Web of Science CrossRef IUCr Journals Google Scholar
Rajendran, C., Dworkowski, F. S. N., Wang, M. & Schulze-Briese, C. (2011). J. Synchrotron Rad. 18, 318–328. Web of Science CrossRef CAS IUCr Journals Google Scholar
Santoni, G., Zander, U., Mueller-Dieckmann, C., Leonard, G. & Popov, A. (2017). J. Appl. Cryst. 50, 1844–1851. Web of Science CrossRef CAS IUCr Journals Google Scholar
Schubert, R., Kapis, S., Gicquel, Y., Bourenkov, G., Schneider, T. R., Heymann, M.,
Betzel, C. & Perbandt, M. (2016). IUCrJ, 3, 393–401. Web of Science CrossRef CAS PubMed IUCr Journals Google Scholar
Sharpe, C. J. (2018). Proceedings of the 16th International Conference on Accelerator and Large Experimental
Control Systems (ICALEPCS'17), 8–13 October 2017, Barcelona, Spain, pp. 1054-1059. WEBPL04 (https://doi.org/10.18429/JACoW-ICALEPCS2017-WEBPL04). Google Scholar
Stellato, F., Oberthür, D., Liang, M., Bean, R., Gati, C., Yefanov, O., Barty, A.,
Burkhardt, A., Fischer, P., Galli, L., Kirian, R. A., Meyer, J., Panneerselvam, S.,
Yoon, C. H., Chervinskii, F., Speller, E., White, T. A., Betzel, C., Meents, A. &
Chapman, H. N. (2014). IUCrJ, 1, 204–212. Web of Science CrossRef CAS PubMed IUCr Journals Google Scholar
Sutter, J., Alcock, S. & Sawhney, K. (2012). J. Synchrotron Rad. 19, 960–968. Web of Science CrossRef IUCr Journals Google Scholar
Tinti, G., Marchetto, H., Vaz, C. A. F., Kleibert, A., Andrä, M., Barten, R., Bergamaschi,
A., Brückner, M., Cartier, S., Dinapoli, R., Franz, T., Fröjdh, E., Greiffenberg,
D., Lopez-Cuenca, C., Mezza, D., Mozzanica, A., Nolting, F., Ramilli, M., Redford,
S., Ruat, M., Ruder, Ch., Schädler, L., Schmidt, Th., Schmitt, B., Schütz, F., Shi,
X., Thattil, D., Vetter, S. & Zhang, J. (2017). J. Synchrotron Rad. 24, 963–974. CrossRef CAS IUCr Journals Google Scholar
Winter, G., Lobley, C. M. C. & Prince, S. M. (2013). Acta Cryst. D69, 1260–1273. Web of Science CrossRef CAS IUCr Journals Google Scholar
Winter, G., Waterman, D. G., Parkhurst, J. M., Brewster, A. S., Gildea, R. J., Gerstel,
M., Fuentes-Montero, L., Vollmar, M., Michels-Clark, T., Young, I. D., Sauter, N.
K. & Evans, G. (2018). Acta Cryst. D74, 85–97. Web of Science CrossRef IUCr Journals Google Scholar
Zander, U., Bourenkov, G., Popov, A. N., de Sanctis, D., Svensson, O., McCarthy, A.
A., Round, E., Gordeliy, V., Mueller-Dieckmann, C. & Leonard, G. A. (2015). Acta Cryst. D71, 2328–2343. Web of Science CrossRef IUCr Journals Google Scholar
This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.
