Biology subjects

Egebjerg, J. M.

Publications and source records attributed to Egebjerg, J. M..

3 recordsLinked to original sources

bioRxiv2026

A semantic segmentation model to predict subcellular glycogen localization using transmission electron microscopy images

Transmission electron microscopy (TEM) is the gold standard for assessing subcellular glycogen localization in skeletal muscle fibres, but conventional manual analysis is extremely time-consuming and limits large-scale studies. Here, we developed and validated a deep learning-based semantic segmentation approach to automate quantification of glycogen particles across defined subcellular compartments in human skeletal muscle. Skeletal muscle biopsies were obtained from seven healthy men under conditions of normal, depleted, and supercompensated glycogen content. TEM images were acquired from myofibrillar and subsarcolemmal regions and manually annotated to train two complementary attention U-Net models: a region model identifying subcellular structures (intermyofibrillar space, intramyofibrillar regions including A-band, I-band and Z-disc, and mitochondria) and a glycogen model detecting individual glycogen particles. Combining the two models enabled estimation of compartment-specific glycogen areal densities. Model performance was evaluated against manual point-counting. At the fibre level, estimates based on 10-12 images per region achieved biases below 15% and coefficient of variation below 26% for all compartments. Importantly, model-derived total glycogen volume density showed strong concordance with biochemically determined muscle glycogen content across biopsies. In conclusion, this validated semantic segmentation workflow provides a robust, objective, and highly time-efficient tool for quantifying subcellular glycogen distribution in skeletal muscle. The model substantially reduces analysis time and enables high-throughput investigations of compartmentalized glycogen metabolism, with model weights and code made openly available.

physiology↗

bioRxiv2024

Demonstrating Soft X-Ray Tomography in the lab for correlative cryogenic biological imaging using X-rays and light microscopy

Soft X-ray tomography (SXT) enables native-contrast three-dimensional (3D) imaging of fully hydrated, cryogenically preserved biological samples, revealing ultrastructural details without the need for staining, embedding, or sectioning. Traditionally available only at synchrotron facilities, recent advances in laser-driven plasma sources have led to the development of compact soft X-ray microscopes, such as the SXT-100. The SXT-100 achieves imaging resolutions down to 54 nm full-pitch, with tomograms acquired in 30 minutes to two hours. Integrated with an epifluorescence microscope, the SXT-100 facilitates correlative workflows by bridging fluorescence and electron microscopy while preserving the structural integrity of vitrified samples. We demonstrate the capabilities of the SXT-100 through various use cases, including imaging Euglena gracilis, Saccharomyces cerevisiae yeast cells, and nanoparticles in mammalian cells. The relatively short tomogram acquisition times, the virtually non-destructive nature of soft X-ray tomography, and its quantitative imaging capabilities underscore its potential as a powerful tool for advanced biological imaging. Future developments promise enhanced throughput and deeper integration with emerging correlative imaging modalities, and a wider variety of sample types including tissue.

biophysics↗

bioRxiv2023

Ergosterol mediates aggregation of natamycin in the yeast plasma membrane

Polyene macrolides are antifungal substances, which interact with cells in a sterol-dependent manner. While being widely used, their mode of action is poorly understood. Here, we employ ultraviolet-sensitive (UV) microscopy to show that the antifungal polyene natamycin binds to the yeast plasma membrane (PM) and causes permeation of propidium iodide into cells. Right before membrane permeability becomes compromised, we observed clustering of natamycin in the PM that was independent of PM protein domains. Aggregation of natamycin was paralleled by cell deformation and membrane blebbing as revealed by soft X-ray microscopy. Substituting ergosterol for cholesterol decreased natamycin binding and resulted in reduced clustering of natamycin in the PM. Blocking of ergosterol synthesis necessitates sterol import via the ABC transporters Aus1/Pdr11 to ensure natamycin binding. Quantitative imaging of dehydroergosterol (DHE) and cholestatrienol (CTL), two analogs of ergosterol and cholesterol, respectively, revealed a largely homogeneous lateral sterol distribution in the PM, ruling out that natamycin binds to pre-assembled sterol domains. Depletion of sphingolipids using myriocin increased natamycin binding to yeast cells, likely by increasing the ergosterol fraction in the outer PM leaflet. We conclude that ergosterol-specific aggregation of natamycin in the yeast PM underlies its antifungal activity, which can be synergistically enhanced by inhibitors of sphingolipid synthesis. SignificanceErgosterol is the major sterol in the membranes of fungi and a major target for antifungal treatments. Polyene macrolides, such as natamycin, are known to target ergosterol but the underlying mechanisms for their preference for this yeast sterol compared to mammalian cholesterol is not understood. This study shows that natamycin forms aggregates when associated with yeast S. cerevisiae in an ergosterol-dependent manner. Cholesterol can only partially substitute for ergosterol with respect to natamycin binding and aggregation. Membrane-associated aggregation of natamycin is not the result of pre-formed sterol domains in the cell membrane, as we show by direct visualization of minimally modified ergosterol and cholesterol analogs. Inhibiting sphingolipid synthesis increased membrane association and antifungal activity of natamycin, suggesting that targeting sphingolipids in combination with polyene macrolides could lead to novel drug treatment approaches against fungal infections.

biophysics↗