automateD collectioN of datA (DNA) Software
Package

A
quick tutorial for version 1.1

23.05.2007

Evangelia
Kapetaniou1, Kristian Koski2, Kyriakos Petratos1,
Rikkert Wierenga2

1 IMBB, FORTH, Heraklion, Crete, EU-BIOXHIT-TID centre, Greece

2 Biocenter Oulu and Department of
Biochemistry, University of Oulu, EU-BIOXHIT-TID centre, Finland

DNA
developers

Karen Ackroyd (a)

Alun Ashton (b)

Gleb Bourenkov (c)

Sandor Brockhauser (d)

Steve Kinder (a)

Pierre Legrand (e)

Karl Levik
(b)

Romeu Pieritz (f)

Harry Powell (g)

Darren Spruce (f)

Olof
Svensson (f)

Graeme Winter (a)

DNA
Exec. Committee:

Gérard Bricogne (h)

Andrew Leslie (g)

Sean
McSweeney (f)

Colin Nave (a)

Alexander Popov (c)

Raimond Ravelli (d)

Andrew Thompson (e)

(a) CLRC
Daresbury, UK

(b) Diamond light source, UK

(c) EMBL Hamburg, Germany

(d) EMBL Grenoble, France

(e) Synchrotron Soleil, France

(f) ESRF, France

(g) MRC LMB, Cambridge, UK

(h) Global Phasing, Cambridge, UK

---------------------------------------------------------------------------------------------------------------------

This manual was written by a
collaboration of the EU-BIOXHIT-TID centres in Oulu and Crete and the program developers of DNA at the ESRF.

Figure 1. The DNA flow
diagram (http://www.dna.ac.uk/).

In current version (1.1) only
BEST strategy is used.

Short Overview

The DNA software package (Leslie at al, 2002) has been developed for the
control of the automatic collection and the processing of x-ray diffraction data
from crystals of macromolecules. It consists of several independent software
modules that communicate with each other (Fig. 1 and 2). Input and output data are
passed to data base (for example ISPyB - Information System for Protein CrystallographY Beamlines) and the Graphical
User Interface (GUI), from which experiments are launched and monitored. The
remainder of data handling and processing is carried out by underlying layers
of software:

MOSFLM (Leslie, 2005): data processing program.

BEST (Bourenkov and Popov, 2006): data collection
strategy calculations.

SCALA (Evans, 2006): data reduction.

POINTLESS (Evans, 2006): determination of point
group/space group.

ISPyB
(https://wwws.esrf.fr/ispyb/ispyb/security/logon.do).

Figure 2: The DNA system contains a number of modules, where each module
is specialised in a particular task (http://www.dna.ac.uk/).

DNA GUI

1.
Getting started

The DNA GUI
(Fig. 3) consists of three separate windows:

¾
Top Main window exhibits the main
options needed for the high-throughput synchrotron data collection experiment: Sample Screening, Sample Ranking, Collect Reference
Images, Auto Index, Strategy and Results.

¾
Middle Main window states the status of
the experiment. Help, Submit feedback and Abort options are available.

¾
Lowest Main window shows on the fly the
log files from DNA (Executive Output)
or from MOSFLM (MOSFLM Output).

When a new
experiment is started at ESRF MX beamlines, the DNA interactive window with the
experimenter's MX code is on display (Fig. 3).

¾
click on OK.

Figure 3. Starting window.

In the following, a number of
scenarios, corresponding to the typical applications of DNA will be presented:

List of
Scenarios:

¾
Screening crystals (2) and ranking them (2.1)

o
User has multiple crystals of the same protein in the
sample changer.

¾
Characterize a single crystal (2.2)

o
User just wants to collect a dataset from a crystal
already mounted on the beamline.

¾
Strategy calculation (3).

¾
Data collection and integration (4).

¾
Quick scaling (5).

2.
Screening Crystals

Once crystals have been transferred into the baskets and placed in the
sample changer and the correct shipment has been selected for experiment in the
beamline LIMS (e.g. ISPyB) interface and activated, the next step is to
automatically characterize and rank them for data collection. Within the DNA
system sample screening procedure consists of the collection of two reference
diffraction images, collected 90o apart for each sample. At ESRF
beamlines, the sample changer can take up to 50 crystals (in five baskets),
which all can be selected for one screening experiment (Select All Samples button).

¾     Select Screening → Screening/Ranking from
top menu and press Sample screening
option. A Screening window will appear (Fig. 4).

Figure 4: Screening window.

¾
Fill up
mandatory information: directory, exposure time, oscillation and resolution.
The resolution for screening the crystals can be provided by the diffraction
plan (2.8 Å for 2nd and 3rd crystal in Figure 5).
If no resolution is available in the diffraction plan, DNA either uses the
default resolution (2 Å in Figure 5) or the user can enter an override
resolution for each crystal individually.

¾
Select
Bravais lattice, if known, and click on Anomalous
Enabled, if you perform SAD/MAD experiments.

¾
Click on
the Get Sample Changer Contents
option (Screening window, middle). Sample changer starts to read the bar codes
from the top of each sample holder and compares them with the corresponding
information in the data base. Crystal
data will appear in the Screening window (Fig. 5).

¾
Select the
samples for screening (press Select All Samples
option, Screening window middle, if you wish to screen all the samples).

¾
Click on Screen option (Screening window, middle).

¾
The program will prompt
you for rank file input (Fig. 5). If similar crystals have not been screened
previously click on Create a New Rank Project
File. The program will then automatically produce a .pdrp file containing
all the information about the screened crystals. If the user wants to compare
screening results to previous screening, a Load
Existing Rank Project File option should be pressed and then the proper
rank file (.pdrp) ashould be selected.

Figure 5. Screening window with rank project question.

2.1.
Crystal
ranking

In principle, the information gathered by
DNA from the two reference diffraction images is sufficient to allow the
automatic ranking of samples. Criteria to be used in a system of crystal
ranking are currently under discussion and include: total exposure time,
ranking resolution, crystal mosaic spread, number of images and spot deviation.
New ranking schemes are easy to implement thanks to the flexible ranking module
and will vary according to the experiment goals and user personal style.

¾     Click on the
Sample Ranking menu option (starting
window, top left; Fig. 2). A Sample Ranking window will appear (Fig. 6) with
space group and unit cell parameters information for each crystal.

¾     The
crystals are ranked as a default by the total exposure time needed for collecting
a full data set as calculated by BEST. The user can select an alternative
ranking criterion from the Sample Ranking window, middle and click on Redo Rank (Fig. 7).

Figure 6. Crystal ranking window.

Figure 7. Redo ranking.

¾     To display
the table containing the more detailed statistics for all screened crystal (as
shown in Fig. 6), select the crystals with the left mouse button and then click
the right mouse button to see the table.

¾     Click on View Rank Result and observe the
diffraction images (Fig. 8), with or without predictions.

Figure 8. Index results.

¾     After
selecting the best crystal press Collect
data (allowing change in strategy).
A Strategy window will appear showing the data collection strategy
proposed by BEST. See sections 3 and 4 (below) for details on how to proceed to
data collection (and processing).

¾     Collect Automatically button
allows the user to collect the data automatically from all selected crystals
using the strategy calculated by BEST (However, it is recommended to use the
option Collect data (allowing change in
strategy), because strategy calculated by BEST is not always the most
convenient one (may have very small oscillation angle, etc.).

2.2.
Characterization of a single
crystal

If the user wants to collect a
data set from a single crystal which is already mounted on the beam:

¾     Click on the
Collect Reference Images menu option.

¾
Fill up
mandatory information: directory, exposure time, oscillation, expected
resolution.

¾
Select
Bravais lattice, if known, and click on Anomalous
Enabled, if you perform SAD/MAD experiments.

¾
Press Collect and Characterize.

Two reference images are collected and processed. If both have been
indexed in the same space group and with comparable unit cell parameters, the Auto index window will appear (Fig. 7).
From Auto Indexing window, DNA will continue automatically to Strategy window, which is described in
next chapter.

The Collect Only button is only
collecting two reference images without starting the data processing. This
option can be used to test the data collecting hardware or just to check the
diffraction images.

Figure 9. Auto index window.

3.
Calculating
strategy

After auto indexing the best data collection strategy is calculated (by
BEST) and the Strategy window will appear automatically. The reference strategy
is seen on the left of the Strategy window (Fig. 10.). The actual
data collection strategy on the right side of the window can be freely edited by
the user by simply clicking the parameters that user wants to change.

However, the user has to keep in mind that changing
the parameter may cause changes in the optimal data collection strategy. So, if
the data collection parameters have been changed the user may have to
recalculate the strategy by pressing the Calculate
Strategy button in the middle left. A new strategy will be then calculated.

Figure 10. Strategy window.

4.
Data
Collection and Integration

After the Strategy Calculation there are two options:

¾
Click on Collect
Data (Strategy window, middle; Fig. 10).

Data collection will be carried out using the given strategy.

¾     Click on Collect and Integrate Data (Strategy window,
middle; Fig. 10).

Data collection will be carried out using the given strategy and the data
set is also integrated by MOSFLM, while it is collected.

DNA will first collect three images starting from at a
phi value 90° away from the starting phi for data collection. These 3
images, together with the first 3 images of the data collection, are used for
unit cell refinement (requirement of MOSFLM).

During integration, DNA will use POINTLESS to
determine the point group of the crystal (Fig. 11).

Figure 11.
Pointless results from
Executive output window (Lowest
window of the DNA GUI).

5.    Quick Scaling

This option is only possible if the Collect and Integrate method is used
during data collection. The quick scaling is meant ONLY for rapid data analysis.
The data is scaled only quickly to save more time for actual data collection
(during scaling the data collection is stopped).

¾     Click on Quick Scaling Statistics (Strategy window,
middle; Fig. 10).

The following statistics are shown after a quick
scaling run: resolution, R merge, I/sigma, completeness,
multiplicity, number of reflections, unique reflections. The values in the
highest resolution shells are shown in brackets (Fig. 12).

Figure 12. Quick scaling results from Executive output window (Lowest window of the DNA GUI).

6.    Results

¾     Click on the
Results menu option (Starting window,
top right).

The
following information is displayed in the Results window

¾     Indexing
results with symmetry information and unit cell parameters (Fig. 13).

¾     Diffraction
images of the two reference images with and without predictions (Figs. 8 and 14).

¾     MOSFLM
log file.

¾     Integration
results shown as graphics.

¾     Strategy
results.

Figure 13.

Figure 14.

All the results files are also written to the working directory. Also
input files for integrating the images using XDS and MOSFLM are generated by
DNA.

The indexing results and the diffraction patterns of the reference
images (with and without predictions) are also written to the database.

7.    References

Evans, P. (2006) Scaling and assessment of data
quality, Acta Cryst. D62:72-82.

Leslie, A. (2002) Automation of the collection
and processing of X-ray diffraction data – a generic approach, Acta Cryst. D58:1924-1928.

Leslie, A. (2005) The integration of
macromolecular diffraction data, Acta
Cryst. D62:48-57.

Bourenkov, G. and Popov, A. (2006) A quantitative
approach to data-collection strategies, Acta Cryst. D62:58-64.