17-18 January 2018
Medicon Village
Europe/Stockholm timezone

High throughput biological solution SAXS instrumentation for state-of-the-art structural biology research and validation.

17 Jan 2018, 16:15
Auditorium (Medicon Village)


Medicon Village

Scheelevägen 2 223 63 Lund Sweden


Soren Skou (Xenocs)


Low volume samples, high throughput capabilities and easily reconfigurable instrument parameters for biological small angle x-ray scattering have previously been reserved for measurements at state-of-the-art synchrotron beamlines. With the introduction of the dedicated solution SAXS instrument, the BioXolver, Xenocs is not only moving the sample handling technology previously only seen at synchrotrons into the standard laboratory, but also providing it and the instrument itself with a level of automation that empower users at any skill level to obtain the best data for their particular sample without compromise. The instrument has been developed to be a truly easy to use and stable workhorse for samples in solution. By integrating computer vision technology, sample volumes down to 5 uL are possible and the in-line UV/VIS absorption measurements facilitate concentration estimation on the exposed sample. Automated sample loading, sample cell cleaning and drying is done with a high precision pipetting robot that also ensures gentle transport from the 2x96 well tray sample containers to the sample cell. No compromise is made on data quality as the detector is fully in vacuum, ensuring the lowest possible background. Furthermore, using a motorized detector stage and motorized scatterless slits, the sample to detector distance and flux can be automatically optimized to fit a large variety of protein complex sizes. Data reduction and analysis can also be automated and done using the open source software RAW that also includes integration and compatibility with the advanced software suite ATSAS from the EMBL. Built on the platform of an already successful instrument design, the BioXolver is an excellent choice for stability and data quality.

Primary author

Soren Skou (Xenocs)

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