TranSPHIRE: automated and feedback-optimized on-the-fly processing for cryo-EM

Stabrin M, Schoenfeld F, Wagner T, Pospich S, Gatsogiannis C, Raunser S

Forschungsartikel (Zeitschrift) | Peer reviewed

Zusammenfassung

Single particle cryo-EM requires full automation to allow high-throughput structure determination. Although software packages exist where parts of the cryo-EM pipeline are automated, a complete solution that offers reliable on-the-fly processing, resulting in high-resolution structures, does not exist. Here we present TranSPHIRE: A software package for fully-automated processing of cryo-EM datasets during data acquisition. TranSPHIRE transfers data from the microscope, automatically applies the common pre-processing steps, picks particles, performs 2D clustering, and 3D refinement parallel to image recording. Importantly, TranSPHIRE introduces a machine learning-based feedback loop to re-train its picking model to adapt to any given data set live during processing. This elegant approach enables TranSPHIRE to process data more effectively, producing high-quality particle stacks. TranSPHIRE collects and displays all metrics and microscope settings to allow users to quickly evaluate data during acquisition. TranSPHIRE can run on a single work station and also includes the automated processing of filaments.

Details zur Publikation

FachzeitschriftNature Communications
Jahrgang / Bandnr. / Volume11
Ausgabe / Heftnr. / Issue1
StatusVeröffentlicht
Veröffentlichungsjahr2020
Sprache, in der die Publikation verfasst istEnglisch
DOI10.1038/s41467-020-19513-2

Autor*innen der Universität Münster

Gatsogiannis, Christos
Institut für Medizinische Physik und Biophysik
Center for Soft Nanoscience (SoN)