Biology subjects

Kirmse, R.

Publications and source records attributed to Kirmse, R..

2 recordsLinked to original sources

bioRxiv2026

Workflow and instrumentation for multiscale correlative imaging in voluminous cryogenic specimens

Cryo-electron tomography (cryo-ET) enables molecular-resolution imaging of intracellular environments, but is constrained by the need to generate electron-transparent sections of the biological specimen and thus a limited imaging volume. To alleviate such limitations, we present a multiscale correlative workflow that links cryo-confocal fluorescence microscopy (cryo-FLM), cryo-focused ion beam-scanning electron microscopy (cryo-FIB-SEM) volume imaging (cryo-vEM), and cryo-FIB serial lamellae lift-out for cryo-ET in high-pressure frozen voluminous specimens. An integral part of this workflow is a sample holder that preserves specimen orientation across instruments, reduces manual handling, and overcomes stage-tilt limitations in cryo-FIB-SEM hardware. Applied to vitrified colorectal cancer organoids, we demonstrate that this workflow enables fluorescence-guided site preparation for cryo-vEM, which provides biological context beyond the limited field of view of cryo-ET, and targeted lift-out for fabrication of multiple lamellae from defined regions of interest. The reconstructed tomograms reveal subcellular architecture and cell-cell interfaces. This workflow establishes a modular methodological framework for continuum-resolution cryogenic imaging of complex 3D biological specimens.

cell biology↗

bioRxiv2021

CLEMSite, a software for automated phenotypic screens using light microscopy and FIB-SEM

Correlative light and electron microscopy (CLEM) combines two imaging modalities, balancing out the limits of one technique with the other. In recent years, Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) has emerged as a flexible method that enables semi-automated volume acquisition at the ultrastructural level. We present a toolset for adherent cultured cells that enables tracking and finding cell regions previously identified in light microscopy, in the FIB-SEM along with automatic acquisition of high-resolution volume datasets. We detect a grid pattern in both modalities (LM and EM), which identifies common reference points. The novel combination of these techniques enables complete automation of the workflow. This includes setting the coincidence point of both ion and electron beams, automated evaluation of the image quality and constantly tracking the sample position with the microscopes field of view reducing or even eliminating operator supervision. We show the ability to target the regions of interest in EM within 5 {micro}m accuracy, while iterating between different targets and implementing unattended data acquisition. Our results demonstrate that executing high throughput volume acquisition in electron microscopy is possible.

cell biology↗