Designing and Operating an In-House Cryogenic Electron Microscopy Facility with IT Infrastructure and On-the-Fly Data Processing Pipelines.

Abstract

Cryo-EM has become a dominant method for high-resolution structural determination of biological macromolecules. As the number of institutional cryo-EM facilities grows worldwide, a persistent challenge has emerged: the data infrastructure required to support these facilities is routinely underplanned. Modern cryo-EM instruments paired with direct electron detectors (DEDs) generate between 2 and 5 TB of raw data per day, and a 20-user facility can accumulate approximately 2 PB of data within a single operational year. Processing this data demands dedicated GPU computing nodes, high-speed internal networking, and robust long-term archival strategies-all of which must be in place before data collection begins. This protocol presents an integrated framework for the IT and computational design of an in-house cryo-EM facility. We cover physical facility requirements (room design, power, cooling, and vibration isolation), equipment selection (microscopes, DEDs, and supporting instruments), and the full computational stack: network switch configuration, storage server selection and sizing, GPU compute node provisioning, and remote access architecture. We then provide a detailed protocol for implementing on-the-fly data processing pipelines-covering motion correction, contrast transfer function (CTF) estimation, particle picking, and 2D classification in real time during data collection-using industry-standard tools. Data transfer strategies for external users are also addressed. This guide fills a critical gap in the literature and will enable researchers and administrators to build cryo-EM facilities that are computationally ready from day one.