Yu Wai Chen (ed.), Structural Genomics: General Applications, Methods in Molecular Biology,
vol. 1091, DOI 10.1007/978-1-62703-691-7_18, © Springer Science+Business Media, LLC 2014
High-Throughput SAXS for the Characterization
of Biomolecules in Solution: A Practical Approach
Kevin N. Dyer , Michal Hammel , Robert P. Rambo , Susan E. Tsutakawa ,
Ivan Rodic , Scott Classen , John A. Tainer , and Greg L. Hura
The recent innovation of collecting X-ray scattering from solutions containing purifi ed macromolecules in
high-throughput has yet to be truly exploited by the biological community. Yet, this capability is becoming
critical given that the growth of sequence and genomics data is signifi cantly outpacing structural biology
results. Given the huge mismatch in information growth rates between sequence and structural methods,
their combined high-throughput and high success rate make high-throughput small angle X-ray scattering
(HT-SAXS) analyses increasingly valuable. HT-SAXS connects sequence as well as NMR and crystallo-
graphic results to biological outcomes by defi ning the fl exible and dynamic complexes controlling cell biol-
ogy. Commonly falling under the umbrella of bio-SAXS, HT-SAXS data collection pipelines have or are
being developed at most synchrotrons. How investigators practically get their biomolecules of interest into
these pipelines, balance sample requirements and manage HT-SAXS data output format varies from facility
to facility. While these features are unlikely to be standardized across synchrotron beamlines, a detailed
description of HT-SAXS issues for one pipeline provides investigators with a practical guide to the general
procedures they will encounter. One of the longest running and generally accessible HT-SAXS endstations
is the SIBYLS beamline at the Advanced Light Source in Berkeley CA. Here we describe the current state
of the SIBYLS HT-SAXS pipeline, what is necessary for investigators to integrate into it, the output format
and a summary of results from 2 years of operation. Assessment of accumulated data informs issues of con-
centration, background, buffers, sample handling, sample shipping, homogeneity requirements, error
sources, aggregation, radiation sensitivity, interpretation, and fl ags for concern. By quantitatively examining
success and failures as a function of sample and data characteristics, we defi ne practical concerns, consider-
ations, and concepts for optimally applying HT-SAXS techniques to biological samples.
Key words High-throughput , SAXS , Conformation , Structure , Structural genomics , Macromolecules
Small angle X-ray scattering (SAXS) has reemerged in its application
to the study of biological macromolecules. SAXS from biomole-
cules was an early application of synchrotron radiation [ 1 ] in part
because of its simplicity in terms of sample preparation. However
with the realization of degree to which biomolecules could be
crystallized yielding atomic resolution structures, macromolecu-
lar crystallography (MX) quickly became a focus of structural
biologists. Relatively speaking, the application of SAXS and the
development of analytical tools languished. Over the course of
the last 10 years, SAXS has reemerged as a powerful complimen-
tary tool to MX.
Three factors have contributed to the emerging power of SAXS.
First, not all macromolecules of interest are amenable to crystalliza-
tion. Even when a macromolecule has been crystallized and mod-
eled to atomic resolution, biologically relevant alternate
conformations can, at best, be inferred. Through a genomic analy-
sis, 35–48 % of human gene products are predicted to have signifi -
cant fl exible regions when isolated [ 2 ]. SAXS provides an avenue to
capture critical structural information from biomolecules even after
an atomic resolution model is available. SAXS results suggest con-
formational variation is a general functional feature of macromole-
cules, so biologically relevant structural analyses will require a
comprehensive approach that assesses both fl exibility, as seen by
SAXS, and detail, as determined by X-ray crystallography and NMR
[ 3 ]. Indeed, SAXS also provides three-dimensional arrangements
and oligomeric state for full-length proteins in solution, which is
typically the functional assembly state, as seen for DNA break
response framework proteins [ 4 , 5 ], thermophilic superoxide dis-
mutase [ 6 ], ATPase motors [ 7 ], and abscisic acid receptor [ 8 ].
Second, analysis tools have been developed and made accessible for
the extraction of structural information. Shapes of macromolecule
may be determined to ~15 Å resolution. Higher resolution infor-
mation may be probed by complimenting SAXS with information
from an atomic resolution model. Building upon the promise of
early tools [ 9 ], the EMBL ATSAS [ 10 ] package has been transfor-
mative. Others have further contributed to the expanding suite of
software available for analysis [ 11 – 14 ]. Additionally, the practical
implementation of the Porod-Debye law in SAXS experiments of
biopolymers provides a tool for assessing fl exibility and for valida-
tion of SAXS models [ 15 ]. Flexible regions of macromolecules are
often involved in interactions, as seen for antibody–protein binding
[ 16 , 17 ], and SAXS provides a means to defi ne solution conforma-
tions with fl exible regions. As generally appreciated, crystal contacts
and constructs with missing regions may cause structural changes in
the crystal structure relative to the SAXS solution results [ 18 ].
SAXS has recently been used to provide similarity maps of the func-
tional conformational states of macromolecules independent of
shape reconstructions [ 19 ]. Third, high signal to noise SAXS pro-
fi les are routinely collected from small quantities of sample with
short exposure times. High-quality SAXS profi les are the result of
Kevin N. Dyer et al.
advances in X-ray detectors and high brilliance synchrotron light
with beam dimensions that match sample dimensions. Thus the
motivation to move beyond the limits of MX, improved analysis
tools and collection capabilities have all contributed to the increase
in structural reports utilizing SAXS.
The advent and wide spread availability of high-throughput
SAXS is relatively new. Pipelines for high-throughput SAXS have
been reported at SSRL [ 20 ], SOLEIL [ 21 ], PETRA3 [ 22 ], and
CHESS [ 23 ]. Several additional beamlines have developed these
capabilities and are yet to be reported. SAXS at SIBYLS has been
dedicated to HT-SAXS for the last 3 years with the initial applica-
tion to structural genomics pipelines [ 24 ]. SIBYLS has leveraged
tools developed for crystallography such as data control software
and optimized features for SAXS [ 25 ].
A distinction of the SAXS at SIBYLS is that a signifi cant fraction
of samples are collected via mail-in/hand-in. Once an investigator’s
samples have been delivered to the beamline their samples are
placed into a queue and collected by beamline staff. The data out-
put is a SAXS profi le which tabulates the q value (X-ray momentum
transfer) versus X-ray intensity with an error bar. This three- column
format is electronically delivered post collection. One advantage to
the mail-in/hand-in approach is an increase in fl exibly arranging
data collection times. Optimal sample preparation is often challeng-
ing and diffi cult to coordinate for a specifi c time. A second advan-
tage is that “beamtime” is spent collecting data rather than training;
thus increasing throughput. The disadvantage is that the investiga-
tors themselves are not there to guarantee every sample. Thus the
guiding principle for development of the mail-in/hand-in program
has been to enable data collection at as high qualities as if the inves-
tigator was present themselves. Over 160 laboratories have since
taken advantage of this opportunity. Several results have been
included in high profi le reports [ 8 , 26 – 29 ]. Our goal here is not to
review post-processing analysis tools used to determine structural
details. We suggest other sources for this purpose [ 10 , 30 – 32 ].
We’ve also recently described more technical aspects of the control
system and hardware elsewhere [ 25 , 33 ]. Here we focus on optimal
input and a detailed description of the output to improve coordina-
tion between investigators and synchrotron beamlines as required
for true high-throughput. HT-SAXS appears rigid given the reduced
interaction between the beamline and the investigator. In reality
both data collection and data processing are fl exible. Investigators
are empowered to reprocess data by varying from the automated
processing steps. By optimally taking advantage of HT-SAXS, new
opportunities continue to be developed for the investigation of bio-
molecules, such as comprehensive mapping of conformational states
without requiring shape reconstructions [ 19 ].
HT-SAXS opportunities extend beyond experiments preformed at
lower throughput. Optimal samples and procedures depend on the
type of experiment being performed. Here we will provide general
requirements for low signal samples acknowledging that at high
concentrations, requirements may be relaxed.
Concentration is an important parameter that impacts signal, prob-
lems from aggregation, and data collection requirements.
For organic macromolecules in an aqueous solvent, a useful
rule of thumb for determining the required concentration for
high-quality signal is concentration in mg/ml multiplied by molec-
ular weight in kDa must be greater than 100 (mg/ml × kDa > 100).
With HT-SAXS the required concentration can be experimen-
tally evaluated, as the desired signal to noise will vary from facility
to facility and by the scattering power of the solvent.
The proper subtraction of background signal is often critical.
Background includes the halo of the primary X-ray beam, scatter-
ing from windows in the beam path and scattering from solvent.
To focus analysis on a solute (the macromolecule of interest), the
SAXS from a solution containing all but the macromolecule of
interest (referred to from here forward as the buffer) may be sub-
tracted from the SAXS profi le of the solution containing the mac-
romolecule. This subtraction removes all three background
components mentioned above.
Everything in solution scatters X-rays so having the appropriate
matching buffers is critical.
Adequately matched buffers can be prepared by dialysis, size
exclusion chromatography (SEC) or from a spin concentrator.
However, these procedures must be carefully attended to, for
example, fi lters in concentrators are typically covered in preserva-
tives which must be washed at least three times before the fl ow
through can be used as a proper buffer. Dialysis requires more time
with viscous solvents. Some SEC fractions contain small amounts
of column matrix so are not appropriate for use as a buffer.
Pipetting of cofactors into both the buffer and the sample, as a
modifi cation, is also possible provided the added volumes are equal
to high accuracy (usually requires a minimum of 4 μL).
Added signal from improper buffer subtraction will typically
reduce the apparent rate of intensity decay as a function of angle;
giving the appearance of an unfolded polymer. Over subtracted
signal often results in negative intensities at high values of q .
Because of the importance of proper buffer subtraction and
because buffer is typically inexpensive, we recommend preparing
larger buffer volumes than required for samples and collecting
identical buffers both before and after the sample.
2.2 Isolating the
2.3 Matching Buffers
Kevin N. Dyer et al.
Robotic sample loading from 96-well plates requires decisions
regarding shipping, seal against evaporation, and safe volumes for
loading the sample cell. If frozen, the plate should be transported in
sub-freezing conditions. If unfrozen, care must be taken so that
samples do not slow freeze during transport but remain cool.
A kilogram of Blue Ice at 5° packed on both sides of the sample plate
in a well-sealed (taped) Styrofoam box is a reasonable option.
HT-SAXS facilities have specifi c sample formats as precise sam-
ple locations in three dimensions are required for robotic loading.
The sample format at SIBYLS is a specifi c, commercially available,
full-skirt 96 conical well plate. Samples sent in alternate plate types
cause delay as samples must be transferred to the proper plate type.
A safe volume for fi lling the sample cell above the incident
beam path is 24 μL.
Plates must also be covered with an appropriate seal for trans-
port to prevent mixing between wells, evaporation and contamina-
tion from the sealing material. Plates are typically covered with a
commercially available silicone mat.
Once samples are sealed they are ready for shipment or deliv-
ery. Flash freezing of samples is possible but usually unnecessary
with 24 h shipping times and a maximum of two additional days
between delivery and collection. Flash freezing may be accom-
plished by placing the plate over a shallow bath of liquid nitrogen.
Practice with plates containing water is recommended.
Shape reconstruction requires homogeneous samples and removal
of concentration-dependent signals.
A signifi cant fraction of investigators use SAXS data for shape
determination. Strategies for data collection for this purpose have
been reported [ 34 ]. Important procedures include collecting a
concentration series to identify and possibly remove concentration-
dependent signals contaminating the signal characterizing macro-
SAXS by itself cannot determine heterogeneity so supporting data
such as elution profi les from chromatographic purifi cation, native gels
or multi-angle light scattering are required for quality assessment of
homogeneity. Many problems with SAXS experiments on RNA sam-
ples derive from heterogeneity of the folded RNA so separation by
sizing chromatography or other means is important [ 35 ]. The report-
ing of a single shape representing an entire population of macromol-
ecules that contribute to the SAXS signal assumes homogeneity.
An organized plan for sample and washing steps impacts effi ciency.
The SIBYLS HT-SAXS pipeline utilizes formatted spread-
sheets, fi lled out by investigators, for organizing data collection.
The spreadsheet describes the order of data collection, the desired
naming of output experimental fi les from each sample, which wells
contain buffers and at which points in the data collection washes
2.4 Sample Format
2.6 Organizing Data
Washing is not required between every well, if sample collec-
tion order is strategically chosen. For example a concentration
series collected in the order of lowest to highest does not need
washing steps. Washing is a signifi cant bottleneck in data collection
so the fewer washes the higher the throughput.
Signifi cant calibration of the SAXS instrumentation is applied prior
to data collection. Investigators should be aware of four important
calibration procedures which will affect all data sets.
The incident beam orientation, sample position, and detector
orientation must all be accurately defi ned in order to calculate scat-
tering plots of Intensity versus q . This is typically done through the
collection and analysis of a crystalline powder pattern. Inaccuracy
in this calibration will result in blurred SAXS curves where sharp
peaks are broadened and the small q scattering may have larger
The incident X-ray wavelength is calibrated typically by mea-
suring absorbance from metal fi lters with fl uorescence near an elec-
tron orbital edge. Inaccuracy in wavelength leads to shifted and
stretched SAXS profi les with peaks occurring at an alternate appar-
ent q value.
The beamstop and other shadows blocking scattering from the
beamline to the detector are masked out. Inaccuracy in defi ning
these regions will lead to large drops in intensity at small q near the
beamstop. If the mask is too large, valuable low q data may be
A solute of known molecular weight and concentration is col-
lected to enable plotting data on an absolute scale. This calibration
can be valuable for calculating molecular weight when the concen-
tration of the macromolecule is known. However the scattering
contrast between buffer and solute must be considered relative to
the calibrant. Including a calibrant on the sample plate is an alter-
native. These calibration fi les are readily available if desired.
Communicating sample handling procedures is important as the
assumption is that samples are to be stored in cool conditions and
centrifuged prior to data collection.
Once samples have been delivered to the facility they are stored
at an appropriate temperature (−80 °C for frozen and 4 °C for
Just prior to data collection they are spun in a centrifuge to
condense the sample and sediment large aggregates. Once centri-
fuged, the sealing mat is replaced with a thinner pierceable seal for
better sample delivery by the sample loading needle.
3.2 Sample Handling
Kevin N. Dyer et al.
Temperature is an important and underutilized parameter.
The plate deck and the sample cell are cooled to 15 °C during
data collection using a water chiller. The temperature can be
decreased, but the dew point must be considered as condensation
on the sample cell windows can negatively affect buffer
Helium can be added to the sample cell environment to mini-
mize the surrounding humidity, effectively lowering the dew point.
The sample cell can also be heated up to 70 °C using a Peltier;
however, the temperature is typically kept at 15 °C.
Strategic data collection and guarding against interfering bubbles
is key for effi ciency and data quality.
Three plates may be held on the SAXS instrument at one time.
At a rate of 4 h/plate this conveniently enables unsupervised over-
Procedures are in place to automatically stop data collection
and alert the beamline scientists when problems occur. If the X-ray
source is shutdown for example, the system stops and sends a text
message alert. Sample loading and data collection can be moni-
tored by beamline staff remotely.
A snapshot of every loaded sample is taken so that samples
with bubbles can be diagnosed after data collection. Often, suffi -
cient volume remains in the plate to recollect these samples.
Samples are pipetted one at a time from the plate into the
sample cell, exposed, then pipetted back into the plate.
Typically, the aspiration rate for sample delivery is set at 4 μl/s
but can be decreased for viscous, low volume, or bubble-prone
Samples are exposed with a 10 11 photon/s, 12 keV monochro-
matic beam in a series of exposures: 0.5, 1.0, 2.0, and 4.0 s in that
order. A range of exposure times are collected to identify radiation
damage and overcome the limited dynamic range of the detector.
Images from the sample are named using a prefi x designated in
the investigator prepared spreadsheet followed by the well loca-
tion, followed by the exposure number. Results from these images
are later merged together by the investigator to maximize quality.
Once the images are collected from each sample, data processing
Automated scripts subtract the images of the closest collected
buffer before the sample and the closest collected buffer collected
after the sample. The two profi les are averaged creating a total of
three scattering profi les for each sample exposure.
The subtraction process requires normalization for the num-
ber of X-rays during the exposure of the buffer and the sample.
X-ray fl ux is monitored by a diode within the beamstop. Extracting
3.4 Data Collection
3.5 From Images
to SAXS Profi les
an accurate value for the fl ux during the exposure to the high accu-
racy required is not a trivial procedure and is a source of error.
Once a subtracted image is created a mask is applied blocking
out unwanted pixels for integration.
Subtracted and masked images are then integrated utilizing
geometric and wavelength parameters determined from pre-
The calculation of error bars and examination of the buffer sub-
traction impacts quality of data analysis.
Since SAXS images contain many observations at equivalent q ,
an error bar may be calculated using the standard deviation and
A second error of the subtraction process involves slight but
random variations in detector background between sample and
buffer. In some cases these can be signifi cant.
Mechanisms are in place to enable investigators to repeat the
subtraction and integration process using alternate pairings of sam-
ple and buffer.
Raw images are rarely desired, thus investigators typically
receive the one dimensional SAXS profi le of X-ray intensity as a
function of q with error bars.
4 Preliminary Visualization and Interpretation of Results
A sample report and assessment of scattering profi les provides the
basis for appropriate data processing.
Besides receiving scatting data fi les, investigators also receive
an html formatted sample report. The report is viewable utilizing
web browser software and enables mouse click based zooming for
visualization of individual profi les. A partial example is shown in
Fig. 1 .
Using this comprehensive view of the data, beamline staff pro-
vides guidance on which of the three profi les from each sample to
use for further processing.
Data redundancy and consistency of buffer subtraction guide fur-
ther data processing.
If the SAXS profi le from the sample analyzed with a buffer col-
lected before the sample agrees to within noise to that analyzed
with a buffer collected after then the average is used. If the two do
not agree then a judgment is made.
Above we described errors that may occur during data collec-
tion and may cause this disagreement between buffer subtraction
(improperly matched buffer, incorrect measure of the incident
X-ray fl ux, and detector background oscillations). These errors cre-
ate obvious features in the data.
3.6 Sources of Error
and Error Bars
4.1 Sample Report
4.2 Judging Buffer
Kevin N. Dyer et al.
Signifi cant redundancy often exists in collected data. For
example, in concentration series, the q dependent intensity decay
rate of high q data is nearly always consistent. Thus outliers can
often be identifi ed and eliminated.
When an obvious choice is not possible, the average is taken.
Fig. 1 Exemplary SIBYLS output format of data sets collected from a sample
plate. Scattering profi les are grouped by concentration series and graphed on
log plots. In the web-enabled version, individual plots can be enlarged for easier
viewing. ( a ) A concentration series of a well-behaved sample. ( b ) A sample
fl agged as radiation sensitive. Aggregation induced through damage has
occurred during the highest exposure shown in green. ( c ) The extrapolation of
X-ray intensity at q = 0 is impossible for the curves shown assuming a particle
size smaller than 600 Å. Particles of larger size are considered aggregates at
SIBYLS. ( d ) Profi les are over subtracted indicating an error in buffer subtraction
(either an inappropriate buffer or instrumental error). ( e ) A slight concentration
dependence can be observed as the low q region that increases with concen-
tration (SAXS curves from higher intensity plots). This effect can also be seen in
plot. ( f ) The low signal to noise indicates low concentration or insuffi cient expo-
sure times. ( g ) A sharp drop to negative intensity at low q is characteristic of
bubbles or insuffi cient volume in the sample cell. Images of the sample cell
during these exposures may be referenced for further diagnosis. ( h ) The red and
black curves show a smooth downturn in intensity approaching Izero, indicating
the presence of inter-particle repulsive forces. The effect is masked by detector
saturation in the long exposures ( green and blue curves ). ( i ) Aside from major
detector saturation, the curve shows the rare presence of micro-crystals as
indicated by sharp peaks of intensity
Once all scattering profi les are selected and plotted, further com-
ments are added. Comments are based on a visual inspection of the
data. These comments are meant to serve as fl ags of concern rather
than a defi nitive judgment on further processing of data. The fol-
lowing lists typical comments and examples are shown in Fig. 1 .
The intensity at zero scattering angle ( I (0)) cannot be extrapolated
from aggregated data. Similarly particles of size greater than 600 Å
cannot be fully characterized with the available q range at SIBYLS.
The scattering angles required for Guineir analysis are smaller than
can be measured. Further analysis of data without a Guineir region
is limited from a shape restoration perspective as the Guineir region
is valued for quality control.
X-ray radiation damages samples, but the damage rate cannot be
determined a priori. Some samples show no noticeable differences
in SAXS for all exposure lengths. Others are damaged by the fi rst
exposure. Radiation damage is identifi ed as increase in I (0) with
exposure toward features of aggregation. Use of the low exposure
data in this q region is thus critical for further analysis.
Extremely high concentration samples will scatter with intensities
that saturate the detector in some regions of q . Data in these
regions cannot be analyzed and must be compensated by utilizing
shorter exposures or more dilute concentrations.
At low concentration the difference between sample and buffer
approaches zero. The small q region may have suffi cient intensity
to identify the radius of gyration R g . However scattering features
quickly blend in to fl at, near zero values.
Bubbles, low volume, and empty sample cells often resemble pro-
fi les with over subtracted buffers. Radial streaks near the detector
beamstop indicate that the incident X-ray beam is hitting a liquid/
air surface. High q is the most clearly affected region.
See Subheadings 3.5 , 3.6 , and 4.2 above for identifi cation and
causes of this error.
Repulsion is indicated by a gradual dip at low q and is caused by
inter-particle interference. This effect most often occurs at high
concentration. Unless the additional structure factor is of experi-
mental interest, an extrapolation to zero concentration using a
concentration series is often necessary.
Concentration dependence includes multimerization, aggregation,
or inter-particle interference, all of which contribute to characteristic
changes in the scattering profi les from different concentrations.
4.3 Red Flags for
4.3.1 Aggregation or
Undefi ned Guineir Region
4.3.3 Detector Saturation
4.3.4 Low Concentration
4.3.5 Bubble, Low
Volume, or Empty Sample
4.3.6 Bad Buffer
Kevin N. Dyer et al.
Sharp peaks along the scattering curve indicate micro-crystal for-
mation in the sample solution (Fig. 1d ).
5 Conclusions and Perspectives
By compiling statistics over the course of 2 years (2011 and 2012),
below we provide a picture of data collection using the mail-in/
hand-in system. SIBYLS collected 267 plates from 106 different
labs. Of these labs, 73 % requested subsequent data collection.
While most plates were shipped at 4 C, 10 % were shipped frozen.
Figure 2 also breaks down the frequency at which each comment
was made. The scattering from the samples was suffi cient to cause
detector saturation in 39 % of samples, usually during the longest
exposure. 45 % of samples were sensitive to radiation after 8 s of
exposure, while 16 % showed signifi cant radiation damage after
only 3 s. 10 % of samples had an undefi ned Guineir region due to
aggregation or molecular dimensions too large for our SAXS con-
fi guration. 7 % of samples had poorly matching buffer blanks.
Concentration dependence affected 6 % of samples. Another 6 %
were below the required concentration. Approximately 1 % of sam-
ples were lost by bubbles in the beam path or because of insuffi -
cient volume. Repulsion and micro-crystal formation were
observed in less than 1 % of samples. Through visual inspection of
each scattering curve by the SIBYLS staff, it was estimated that
78 % of all data could be used for further processing after a merg-
ing of different exposures and concentrations.
4.3.9 Micro Crystals
Fig. 2 SIBYLS SAXS sample quality statistics for 2 years of data collection.
Each SAXS profi le generated through the mail-in/hand-in system is visually
inspected by beamline staff and commented upon for sample quality. Though
many samples receive comments, when further merged and processed with
other exposures and concentrations 78 % are estimated to be suitable for
further analysis ( pie chart inset )
HT-SAXS systems enable wide spread use of SAXS for structural
characterization. The introduction of HT-SAXS data collection has
been accompanied with criticism for being metric driven rather
than science driven. Looking forward, we’d like to connect
HT-SAXS efforts with problems being addressed in biology.
Biological macromolecules are increasingly appreciated as parts of
larger networks. Frequently, even components of these networks
are challenging to work with and require specifi c laboratory exper-
tise. Few single laboratories can successfully purify, characterize,
and study many interacting components within a network.
HT-SAXS facilities complement efforts to compose more compre-
hensive pictures of networks by drawing upon samples from many
laboratories and enabling facile structural characterization.
SAXS is a solution-based technique so components may be
examined individually, in the presence of partners or under a host
of chemical conditions. Besides providing access to SAXS,
HT-SAXS facilities continue to develop tools to aid in the analysis
and integration of information collected; the staff at these facilities
thus play a key part of the broader effort of post-genomic science.
Further, new opportunities have been enabled with HT-SAXS [ 19 ]
and by analysis of HT-SAXS data [ 36 ]. We anticipate more high
impact results in the near future from HT-SAXS as well as from the
combination of HT-SAXS with crystallography, NMR, and other
This work and the operation of the SIBYLS beamline has been
supported by the Integrated Diffraction Analysis Technologies
(IDAT) program, the DOE Offi ce of Biological and Environmental
Research plus the National Institutes of Health grant MINOS
(Macromolecular Insights on Nucleic Acids Optimized by
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