Publishing SAXS data

Publishing SAXS data

Acknowledging the Beamline in your Publications and Outputs

The beamline team are always happy to support users through to the publication of their work. Please consider the form you would like this acknowledgement to take given the contribution of your beamline scientist. Please note:

  • Beamline staff are Scientists. When they make an intellectual and/or experimental contribution to a publication they deserve to be recognised and acknowledged, just as any other co-author would be.

  • National facilities are not just instruments provided in a room; they are populated by highly-skilled and experienced individuals who make complex experiments possible, and provide essential support in very specialised technologies, often with an intellectual contribution to the project. Proper acknowledgment of facilities enables them to obtain financial support.

  • Beamline staff should have the opportunity to participate in drafting the pertinent part of the paper, and give final approval to the wording and conclusions drawn before publication, as any other contributing Scientist would. This will also ensure the data is interpreted correctly, avoids data misinterpretation, and more information on your samples through advanced analysis may be obtained.

We risk widening the gap between academic and beamline staff if prior practices and non-acknowledgement are allowed to continue.

The research community as a whole, academic and technical alike, should work towards the mutual goal of research excellence across the sector.

To acknowledge the beamline without an authorship please use the words:

Part (or all), of this work was carried out on the BioSAXS beamline at the Australian Synchrotron, ANSTO.

Thanks to Natasha Stephen, University of Plymouth, for developing original policy documentation


Publication guidelines for Biomolecular Small-Angle Scattering

There are guidelines for publishing structural biology studies using SAXS (and SANS) to ensure the quality of data and validity of models is presented clearly to readers. These guidelines are published in the following articles:

https://journals.iucr.org/paper?jc5010

https://journals.iucr.org/d/issues/2023/02/00/cb5145/

When you publish data collected on BioSAXS you should include details following these guidelines. If you have complementary SANS data, there is SANS specific details that you should also include (refer to the above guidelines as these are not covered here).

A summary of these guidelines and the template tables are presented below but we encourage you to read through the original articles as well.

The 2023 article provides a template table in the supplementary Table S3 which you can download as a word document. This template is copied below (including footnotes copied from publication) with a guide to BioSAXS specific information in red text or highlighted yellow:

Table S3  SAS sample details, data collection, analysis, and 3D modelling details for biomolecules in solution.

(a) Sample details

Organism

 

 

 

Source (Catalogue No. or reference)

 

 

 

 

Sample 1

Sample 2

Sample 3 etc

Scattering particle composition 

 

 

 

Protein(s)a

 

 

 

DNA/RNA(s)b

 

 

 

Carbohydrates/glycansc

 

 

 

Stoichiometry of components

 

 

 

Sample environment/configuration

 

 

 

Solvent compositiond

 

 

 

Sample temperature (°C)

 

 

 

In beam sample celle

E.g. 1 mm quartz capillary, coflow

 

 

Batch measurements

 If batch mode was not used, delete these rows

 

 

Sample concentration(s), mg/ml or g/cm3

 

 

 

Size Exclusion Chromatography SEC-SAS

 If SEC-SAXS was not used, delete these rows

 

 

Sample injection concentration, mg/ml or g/cm3

 

 

 

Sample injection volume, mL

 

 

 

SEC column type

 

 

 

SEC flowrate, mL/min

 

 

 

(b) SAS data collection

Data acquisition/reduction software

 BioSAXS Data Reduction algorithm using pyFAI

Source/instrument description or reference

 BioSAXS beamline Australian Synchrotron, ANSTO

Measured q-range (qminqmax; Å-1, nm-1)

 This can be determined from your reduced scattering profiles - open in a text editor and these values are given in the header. See snapshot below table.

BioSAXS uses Angstroms

Method for scaling intensitiesf

 Absolute scaling (cm-1) referenced to water**

**If using coflow, the effective sample path length is <1 cm, so the intensity is not automatically absolutely scaled. You will need to calculate the actual sample pathlength using a sample to sheath fluid ratio of 0.4 (Kirby et al., 2016)

Or, report the intensity as arbitrary units (a.u.)

Exposure time(s), number of exposures. For SEC-SAS, final number of sample frames used for averaging.

The exposure time is recorded in the HDF file for each sample. BioSAXS typically uses an exposure time of 1 s.

SEC-SAXS number of sample frames will be recorded in the .dat file you generated from the LC series analysis using CHROMIXS or RAW LC Analysis.

Additional relevant detailsg

 

(c) SAS-derived structural parameters

Methods/Software

 

 

 

Guinier Analysis

Sample 1

Sample 2

Sample 3

I(0) ± s (cm-1; a.u)

 

 

 

Rg   ± s (Å, nm)

 

 

 

min < qRg < max limit (or data point range)

 

 

 

Linear fit assessment (definition)h

 

 

 

PDDF/P(r) analysis

Sample 1

Sample 2

Sample 3

I(0) ± s (cm-1; a.u.)

 

 

 

Rg   ± s (Å, nm)

 

 

 

dmax (Å, nm)

 

 

 

q-range (Å-1, nm-1)

 

 

 

P(r) fit assessment (definition)i

 

 

 

(d) Scattering particle size

Methods/Software

 

 

 

 

Sample 1

Sample 2

Sample 3

Volume estimates

 

 

 

Porod volume, Vp 3, nm3)

 

 

 

Molecular weight (M) estimates (kDa)

 

 

 

From chemical composition

 

 

 

From SAS, concentration independent methodj

 

 

 

From I(0)/concentrationk

 

 

 

Partial specific volume, n (cm3/g)

 

 

 

Contrast, Δρ (cm-2)

 

 

 

From SAS-independent measurel (method)

 

 

 

(e) Modelling (a complete sub-panel for each method)

Shape modelling method(s) (if used)

 

 

 

 

Sample 1

Sample 2

Sample 3

Software

 

 

 

q-range for fit (qminqmax; Å-1, nm-1)

 

 

 

Symmetry/anisotropy assumptions

 

 

 

Number of individual model reconstructions

 

 

 

c2, CorMap P-values for fit

 

 

 

For multiple phase models: Rg values (Å, nm) and relative phase volumes (Å3, nm3)

 

 

 

Atomistic modelling methods (if used)

 

 

 

 

Sample 1

Sample 2

Sample 3.

Software

 

 

 

q-range for fit (qminqmax; Å-1, nm-1)

 

 

 

Symmetry/anisotropy assumptions

 

 

 

Number of individual model reconstructions

 

 

 

c2, CorMap P-values for fit

 

 

 

(f) Data and model deposition