We present the use of the MeshAndCollect protocol to obtain a complete diffraction data set, for use in subsequent structure determination, composed of partial diffraction data sets collected from many small crystals of the fluorescent protein Cerulean.
X-ray crystallography is the major technique used to obtain high resolution information concerning the 3-dimensional structures of biological macromolecules. Until recently, a major requirement has been the availability of relatively large, well diffracting crystals, which are often challenging to obtain. However, the advent of serial crystallography and a renaissance in multi-crystal data collection methods has meant that the availability of large crystals need no longer be a limiting factor. Here, we illustrate the use of the automated MeshAndCollect protocol, which first identifies the positions of many small crystals mounted on the same sample holder and then directs the collection from the crystals of a series of partial diffraction data sets for subsequent merging and use in structure determination. MeshAndCollect can be applied to any type of micro-crystals, even if weakly diffracting. As an example, we present here the use of the technique to solve the crystal structure of the Cyan Fluorescent Protein (CFP) Cerulean.
Macromolecular X-ray crystallography (MX) is, by far, the most used method for gaining atomic resolution insight into the three-dimensional structures of biological macromolecules. However, a major bottle necks is the requirement for relatively large, well diffracting crystals.
Often, and particularly when crystallizing membrane proteins, only very small crystals of a few microns in the largest dimension can be obtained. Radiation damage effects limit the resolution of a complete diffraction data set that can be collected from a single micro crystal2, and very often, it is necessary to improve the signal to noise ratio and hence data set resolution, by merging several partial diffraction data sets from different, but isomorphic crystals. The increases in flux density of X-ray beams at synchrotron sources and elsewhere (e.g. X-ray free-electron lasers (X-FELs)), have meant that useful partial diffraction data sets can be collected from even very small crystals of biological macromolecules. This, in turn, has led to the development of new techniques for the collection and merging of partial diffraction data sets collected from many different crystals in order to produce a complete data set for structure solution. Such techniques are commonly referred to as serial crystallography (SX)3,4,5,6,7,8. A prototypical example of SX is the use of injector devices to introduce a narrow stream of a crystal slurry into the X-ray beam3,4,5. A diffraction pattern is recorded every time a crystal is exposed to X-rays leading to the collection, from many thousands of individual crystals, of 'still' diffraction images, information which is then merged to produce a complete data set. However, a considerable disadvantage of this type of serial data collection is that the processing of still images can be problematic. The data quality is considerably improved if crystals can be rotated and/or several diffraction images are collected from the same crystal during serial crystallography experiments6.
MeshAndCollect1 was developed with the aim of combining SX with 'standard' MX rotation data collection and allows, in an automatic fashion, experimenters to collect partial diffraction data sets from numerous crystals of the same macromolecular target mounted on the same or different sample holders. A complete diffraction data set is then obtained by merging the most isomorphous of the partial data sets collected. MeshAndCollect is compatible with any state-of-the-art synchrotron X-ray beamline for MX (ideally an insertion device facility with a relatively small (20 µm or less) beam size at the sample position). In addition to the compilation of complete data sets from a series of small, well-diffracting crystals, the method is also very suitable for the initial experimental assessment of the diffraction quality of micro-crystals and for the processing of opaque samples, e.g., in meso grown microcrystals of membrane proteins9.
At the start of a MeshAndCollect experiment, the positions, in two dimensions, of each of the many crystal contained in a single sample holder are determined using a low dose X-ray scan. The diffraction images collected during this scan are automatically analyzed by the program DOZOR1, which sorts the positions of the crystals on the sample holder according to their respective diffraction strength. Positions for the collection of partial data sets are assigned automatically based on a diffraction strength cut-off and, in the last step, small wedges of diffraction data, typically ±5° of rotation, are collected from each chosen position. Experience has shown that this rotation range provides a sufficient amount of reflections per crystal for partial data set scaling purposes, while at the same time, reducing possible crystal centering issues and the chance of exposing multiple crystals in a particularly crowded support1. The individual diffraction data wedges (partial data sets) are then processed either manually or using automated data processing pipelines10,11,12,13. For downstream structure determination it is then necessary to find the best combination of partial data sets to be merged14,15,16 after which the resulting complete data set can be treated in the same way as one originating from a single crystal experiment.
As an example of MeshAndCollect in practice, we present here the solution of the crystal structure of the Cyan Fluorescent Protein (CFP) Cerulean, using a diffraction data set constructed from the combination of partial data sets collected from a series of microcrystals mounted on the same sample support. Cerulean has been engineered from the Green Fluorescent Protein (GFP) from the jellyfish Aequorea victoria17, whose fluorescent chromophore is autocatalytically formed from the cyclisation of three consecutive amino acid residues. Cerulean is obtained from GFP by mutating the first and second residues of the chromophore, a serine and a tyrosine, to threonine (S65T) and tryptophan (Y66W) respectively and adapting the chromophore environment with further mutations (Y145A, N146I, H148D, M153T and V163A) to produce a significant, yet suboptimal fluorescence level of QY = 0.4918,19,20. The suboptimal fluorescent properties of Cerulean have been proposed to be linked to complex protein dynamics involving the imperfect stabilization of one of the eleven β-strands of the protein21 and to the accommodation of two different chromophore isomers depending on the pH and irradiation conditions22. We chose to work with Cerulean as a model protein illustrating the use of the MeshAndCollect protocol due to the relatively ease of tuning crystal size depending on the crystallization. The structure of Cerulean is very similar to that of its parent protein GFP, as it is constituted of a β-barrel formed of eleven β-strands surrounding an α-helix, which bears the chromophore.
1. Expression and Purification of Cerulean
Note: This is based on the protocol published by Lelimousin et al.21
2. Crystallization
3. Crystal Mounting
4. Offline preparation of the synchrotron experiment
Note: Request synchrotron beam time as early as possible and follow the online guidelines for available access types and on how to submit an application for a given synchrotron. The ESRF guidelines can be found at http://www.esrf.eu/UsersAndScience/UserGuide/Applying. If a member of an ESRF Block Allocation Group (BAG), an application for each specific project is not required. In this case experimenters should approach their BAG Responsible concerning the scheduling of beam time.
5. Loading of the Sample onto a Beamline
6. Prepare and Execute the MeshAndCollect Workflow
7. Data Processing
Note: The partial data sets are integrated with a suitable program (XDS10). For this a Python script will be used that recognizes each individual data set, integrates it and makes sure that indexing between the different partial data sets is consistent.
8. Merging of Data Sets
Note: After all partial data sets are integrated the best combination of them are merged to produce the final data set for use in structure determination and refinement. Different aims of this merging process can be to obtain full completeness (highly recommended), high multiplicity or the best data statistics (high <I/σ(I)>, low R-factors, etc.). The latter can sometimes be at the expense of completeness and/or multiplicity so this option should be chosen with care.
MeshAndCollect, as implemented in MXCuBE2 (see Figure 1A), was used for the collection of partial diffraction data sets from small crystals of Cerulean located on the same sample holder in which visual identification of crystals was difficult. To screen the sample holder, we drew a grid over the center of the meshloop (see Figure 1B) and based on the DOZOR score heat map (see Figures 1C, 1D) 85 partial diffraction data sets were automatically collected. These were individually integrated then merged (see above) to produce a data set with 99.8% completeness at dmin = 1.7Å (see Table 1). Half-set correlation (CC1/2)34 in the highest resolution shell was 60% ( = 4.7). As expected, the crystal structure of Cerulean could be straightforwardly solved by molecular replacement33 using the data set generated. After refinement, we obtained an Rwork of 22.8% and an Rfree of 25.4%. Superposition with the previously determined structure (PDB entry 2WSO21) shows a global rmsd on Cα positions of 0.1 Å.
Statistics of the merged data set | |
Clustering Threshold | 0.35 |
Number of partial datasets | 25 |
Space Group | P212121 |
Unit Cell (a, b, c) | 50.98, 62.76, 69.50 |
Resolution Range | 46.58-1.70 (1.73-1.70) |
Rmerge (all I+ and I-) | 0.133 (0.743) |
Rmeas (all I+ & I-) | 0.142 (0.813) |
Rpim (all I+ & I-) | 0.047 (0.318) |
Observations total/unique | 220693/25129 |
Mean((I)/sd(I)) | 13.8 (4.7) |
Mn(I) half-set correlation CC(1/2) | 0.994 (0.602) |
Completeness | 99.8 (99.5) |
Multiplicity | 8.8 (6.5) |
Final Rcryst | 22.8 |
Final Rfree | 25.4 |
Table 1: Statistics of the merged data set indicating the high quality of the data collected.
Figure 1: Using MeshAndCollect to collect a series of partial data sets from a series of small crystals contained in the same sample holder. A) User-interface of MXCuBE2. The green oval over the on-axis viewer field indicates the grid tool. B) With it a grid is drawn onto the image of sample holder in the life image field. C) Heat map of the DOZOR scores. D) Example of a diffraction image. E) Dendrogram after hierarchical cluster analysis. Data sets in red were used for merging. F) Overall structure of Cerulean. Please click here to view a larger version of this figure.
The success of an MX experiment usually depends on the existence of relatively large, well diffracting crystals. For projects where optimization from small crystal showers to larger crystals fails, MeshAndCollect provides a possibility to obtain a complete diffraction dataset for structure solution via the combination of isomorphous partial data sets collected from a series of small crystals. The method is compatible with synchrotron beamlines for MX, ideally with a high photon flux and a small beam diameter, equipped with a state of the art diffractometer device and a fast-readout detector. On such an end station, the data collection part of such an experiment will take about 20 minutes, depending on the number of partial data sets to be collected and the number of crystal-containing sample holders to be analyzed.
The most important prerequisite for the success of a MeshAndCollect experiment is the existence of a sufficient number (at least 50, 100 ideally) of diffracting positions on the sample holder. From experience, the minimum size of the crystals to be analyzed should be about 5 µm in the smallest dimension. The method is compatible with any kind of standard cryo-cooling compatible sample holders with the best results being achieved using mesh mounts that are rigid and straight.
At the ESRF, MeshAndCollect is implemented in a user-friendly manner in a Passerelle (http://isencia.be/passerelle-edm-en) workflow30 available from the MXCuBE2 beamline control software. A major advantage of MeshAndCollect compared to other SX methods is that the data collected can be processed by standard programs and automated pipelines used for single crystal MX.
As our example shows, MeshAndCollect is very easy to apply and leads to a series of partial diffraction data sets, usually collected from small crystals, which can be merged to produce a complete data set for use in structure solution. Moreover, MeshAndCollect has the potential to open up the sampling space of protein crystallography as it provides a way to collect usable data from crystallization trials where the last optimization step, the production of large crystals, is unsuccessful.
In the light of the current developments towards brighter X-ray sources (e.g., Extremely Brilliant Source (EBS) project/ESRF35) it is foreseeable that due to increased radiation damage, the type of multi-crystal data collection facilitated by MeshAndCollect will become the standard method of data collection, rather than an exception – as is currently the case – at synchrotron-based MX beamlines.
The authors have nothing to disclose.
We thank the ESRF for providing beam time through its in-house research program.
Beamline | ESRF ID 23-1 | ||
Concentrators: Amicon Ultra-4 Ultracel -30K | Merck Millipore | UFC803024 | |
Crystallization plates XDXm with sealant | Hampton Research | HR3-306 | |
EDTA- free protease inhibitors | Roche | 4,693,159,001 | |
Escherichia coli BL21 (DE3) | Life Technologies Thermo Fisher Scientific | C600003 | |
glycerol | VWR Chemicals Prolabo | 14388.29T | |
HEPES | Euromedex | 10-110-C | |
His-trap HP | GE healthcare | 17-5247-01 | |
imidazole | Sigma-Aldrich | 56750-500G | |
MgCl2 | Sigma-Aldrich | 13452-1KG | |
MicroMeshes 700/25 | MiTeGen | SKU: M3-L18SP-25L | |
NaCl | Fisher Chemical | S/3160/60 | |
PEG8000 | Sigma-Aldrich | P5413-500G | |
Sonicator vibra cell 75/15 | SONICS | ||
Superdex 75 10/300 -GL | GE healthcare | 17-5174-01 | |
Tris base | Euromedex | 26-128-3094-B | |
Trypsin | Sigma-Aldrich | T9201-1G | |
Unipuck | Molecular Dimensions | MD7-601 | |
Name | Company | Catalog Number | Comments |
Programs | |||
ISPyB | ESRF | Solange Delagenière, Patrice Brenchereau, Ludovic Launer, Alun W. Ashton, Ricardo Leal, Stéphanie Veyrier, José Gabadinho, Elspeth J. Gordon, Samuel D. Jones, Karl Erik Levik, Seán M. McSweeney, Stéphanie Monaco, Max Nanao, Darren Spruce, Olof Svensson, Martin A. Walsh, Gordon A. Leonard; ISPyB: an information management system for synchrotron macromolecular crystallography, Bioinformatics, Volume 27, Issue 22, 15 November 2011, Pages 3186–3192, https://doi.org/10.1093/bioinformatics/btr535 | local development |
aimless | MRC Laboratory of Molecular Biology | Evans, P.R., Murshudov, G.N. How good are my data and what is the resolution? Acta Crystallographica Section D Biological Crystallography. 69 (7), 1204–1214, doi: 10.1107/S0907444913000061 (2013). | |
ccCluster | ESRF | Santoni, G., Zander, U., Mueller-Dieckmann, C., Leonard, G., Popov, A. Hierarchical clustering for multiple-crystal macromolecular crystallography experiments: the ccCluster program. Journal of Applied Crystallography. 50 (6), 1844–1851, doi: 10.1107/S1600576717015229 (2017). | local development |
DOZOR | ESRF | Bourenkov and Popov, unpublished | local development |
MeshAndCollect workflow | ESRF | Zander, U. et al. MeshAndCollect: an automated multi-crystal data-collection workflow for synchrotron macromolecular crystallography beamlines. Acta Crystallographica Section D Biological Crystallography. 71 (11), 2328–2343, doi: 10.1107/S1399004715017927 (2015). | local development |
MXCuBE2 | ESRF | Gabadinho, J. et al. MxCuBE: a synchrotron beamline control environment customized for macromolecular crystallography experiments. Journal of Synchrotron Radiation. 17 (5), 700–707, doi: 10.1107/S0909049510020005 (2010). De Santis, D., Leonard, G. Notiziario Neutroni e Luce di Sincrotrone,Consiglio Nazionale delle Ricerche. (19), 24–226 (2014). | local development |
XDS | Max-Planck-Institut für Medizinische Forschung | Kabsch, W. XDS. Acta Crystallographica Section D Biological Crystallography. 66 (2), 125–132, doi: 10.1107/S0907444909047337 (2010) |