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

Eric Shell; Vitor Hugo Balasco Serrão

doi:10.3791/71837

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Method Article

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

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DOI:

10.3791/71837

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September 1st, 2026

Eric Shell¹^,² , Vitor Hugo Balasco Serrão²^,³

¹ITS-Technology Engineering, Information Technology Services, Physical & Biological Sciences Division, University of California-Santa Cruz, ²Biomolecular Cryo-Electron Microscopy Facility, University of California-Santa Cruz, ³Chemistry and Biochemistry Department, University of California-Santa Cruz

Summary

This protocol provides a practical framework for designing and operating the IT infrastructure of an in-house Cryogenic electron microscopy (cryo-EM) facility. It covers facility planning, network architecture, storage, GPU computing, remote access, and real-time data processing, enabling efficient management of multi-terabyte datasets while ensuring scalable, sustainable, and high-performance cryo-EM operations.

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.

Introduction

The cryo-EM resolution revolution has transformed structural biology, enabling atomic-resolution visualization of proteins, nucleic acids, and macromolecular complexes without the need for crystallization¹^,². Three technical advances drove this transformation: the development of DEDs with high frame rates, improvements in electron optics and microscope mechanics, and the optimization of GPU-accelerated image processing software³^,⁴^,⁵^,⁶. Together, these advances have made cryo-EM the m....