Streamlined Workflow from Instrument to HPC
Mr Lev Lafayette1
1University Of Melbourne
The complexity of many contemporary scientific workflows is well-known, both in the laboratory setting and the computational processes. One discipline where this is particularly true is biochemistry, and in 2017 the Nobel Prize in Chemistry was awarded for the development of cryo-electron microscopy (cryo-EM), aiding researchers in understanding the function and interaction of biomolecules. However, cryo-EM produces vast quantities of data which, when combined with the storage capabilities and processing capabilities available from High Performance Computing simulations, produces challenges.
Optimising the cyro-EM workflow requires image acquisition with transmission electron microscopes and direct electron detectors, through to the preprocessing tasks of motion correction, selection and extraction, CTF estimation, then image classification and curation, image sharpening and refinement, and finally structure modelling. On the computational side, the right selection and balance of storage, network, GPU-enabled and optimised software is requisite.
Following previous presentations at eResearchAustralasia that have mapped the innovations of the University of Melbourne’s HPC system, Spartan, an exploration is provided here on how a combination of Spectrum Scale storage, a significant LIEF-funded GPU partition, and the use of cryoSPARC contributes to rapid solutions and workflow simplification for cryo-EM structures, including SARS-CoV-2. The process involved may be of use and interest to other institutions.
Lev Lafayette is a Senior HPC DevOps Engineer at the University of Melbourne, where he has worked for the past six years. Prior to that, he had a similar role at the Victorian Partnership for Advanced Computing for eight years. For fun and profit, he likes to collect degrees