Partners: Institut Laue-Langevin, European Synchrotron Radiation Facility, EGI Foundation
Project description
Small-angle scattering techniques are used to determine the shape, distribution, and uniformity of particles in solution, with a large domain of applications concerning biological macromolecules. New developments and faster acquisition also allow for tracking the dynamics of the particles themselves. Small-Angle X-ray or Neutron Scattering (SAXS or SANS, respectively) can be very effective tools for studying, for example, the time dependence of genome release from phages, investigating entire viral life cycles, or the assembly of macromolecular complexes, providing deep insights into infection pathways. Furthermore, neutrons and X-rays can be applied in a complementary mode, resulting in a much more accurate and detailed characterization of biological systems.
However, this approach is still rare though, due to a lack of appropriate platforms, infrastructures, and FAIR data. This project aims to advance medical research by providing an EOSC-based platform that enables FAIR data and software, leading-edge processing pipelines. This will support reproducibility and automated validation, and will allow integration with other relevant structural databases.
Societal challenge
Neutron and synchrotron experiments are expensive. However, the collected data are usually exploited only by a small experimental team performing a particular experiment. In addition, the analysis of the data requires often sophisticated tools together with a large domain-specific knowledge, restricting the utility to a restricted community of scattering experts. This should be improved by providing a platform allowing the easy reuse of expensive data sets collected at large scale neutron and synchrotron facilities to explore the conformations of proteins, enzymes and other large macromolecular complexes.
Technical challenge
The analysis of neutron and x-ray small angle scattering data for biological macromolecules require a large degree of domain-specific knowledge and the use of several specialized software tools, not always easy to install and use, combined in a complex workflow. The project aimed to provide a series of simple to use Jupyter notebooks, with the needed software already installed, and default parameters and easy to follow instructions to facilitate such analysis. Additionally, the databases of the two partners, ESRF (https://data.esrf.fr) an ILL (https://data.ill.fr), will provide access to the experimental data collected in both facilities.
The EOSC Future added value
- Provision of resources through EGI
- Visibility through the EOSC marketplace
- Accessibility to new scientific communities
Main results
- ILL and ESRF data portals have been integrated into EOSC as part of EOSC Future activities
- VISA (Virtual Infrastructure for Data Analysis) of ILL and ESRF provide resources for the analysis of the open data available at both facilities
- A prototype to reanalyze SANS/SAXS data and several Jupyter notebooks demonstrating its use have been developed and are available as a service
Other resources
Demo:
Service: http://replay.notebooks.egi.eu + https://github.com/isafiulina/sas_helper
Publications:
- Gonzalez MA, Safiulina I, D`Angelo A, Mutti P, Bodera J, Santoni G, Dimper R, Wagh J, Fuhrmann P, Millar P, Pozsa K, Sala L, Ashton A, La Rocca G (2023) Following biological processes combining small angle neutron and x-ray scattering and modelling techniques. ARPHA Preprints. https://doi.org/10.3897/arphapreprints.e116670
- Safiulina I, Gonzalez MA, Mutti P, La Rocca G, Fernández E (2023) A Jupyter notebook to explore protein conformations: An output of PaNOSC SP8 case. ARPHA Preprints. https://doi.org/10.3897/arphapreprints.e116668
Presentations/Posters:
- EOSC Symposium 2023, Madrid, 20th September 2023: https://symposium23.eoscfuture.eu/wp-content/uploads/2023/09/EOSC-Use-Cases_PanOSC_Miguel-Gonzalez.pdf
- Poster at canSAS (Collective action for nomadic Small Angle Scatterers) 2023 meeting, ILL/ESRF, Grenoble, 16-18 October 2023: https://cloud.ill.fr/index.php/s/apFDzZmZxifWYKp