Biology subjects

Thaysen, K.

Publications and source records attributed to Thaysen, K..

5 recordsLinked to original sources

bioRxiv2025

Dynamic mode decomposition for analysis and prediction of metabolic oscillations from time-lapse imaging of cellular autofluorescence

Metabolic oscillations are a common phenomenon in cell biology. They are based on non-linear coupling of biochemical reactions and can show rich dynamic behavior including sustained and damped oscillations, as found, for example, in glycolysis of yeast and other eukaryotic cells. Metabolic oscillations are often studied by time-lapse imaging of cellular autofluorescence based on the changing abundance of NAD(P)H, but the analysis of such experimental data is challenging. Here, we show that dynamic mode decomposition (DMD), a numerical algorithm for linear approximation and spectral analysis of non-linear dynamics, allows for dissecting glycolytic oscillations in simulations and experiments in a fully data-driven manner. By combining DMD with time-delay embedding the spatiotemporal dynamics of sustained and damped glycolytic oscillations can be learned. Together with a rigorous assessment of spurious eigenvalues, via residual DMD, this provides a unique spectrum for each scenario, allowing for high-fidelity time-series and image reconstruction as well as for phenotyping different starvation conditions. The ability of DMD to predict future time points depends on the delay embedding dimension and is comparable to that of long short-term memory (LSTM) neural networks. Together, our results demonstrate the potential of DMD for analysis of time-lapse microscopy of metabolic oscillations in living cells.

bioinformatics↗

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↗

bioRxiv2024

Structural and biochemical analysis of ligand binding in yeast Niemann-Pick type C1-related protein

In eukaryotes, integration of sterols into the vacuolar/lysosomal membrane is critically dependent on the Niemann-Pick type C (NPC) system. The system consists of an integral membrane protein, called NCR1 in yeast, and NPC2, a luminal soluble protein that transfers sterols to the N-terminal domain (NTD) of NCR1 before membrane integration. Both proteins have been implicated in sterol homeostasis of yeast and humans. Here, we investigate sterol and lipid binding of the NCR1/NPC2 transport system and determine crystal structures of the sterol-binding NTD. The NTD binds both ergosterol and cholesterol, with nearly identical conformations of the binding pocket. Apart from sterols, the NTD can also bind fluorescent analogs of phosphatidylinositol, phosphatidylcholine and phosphatidylserine as well as sphingosine and ceramide. We confirm the multi-lipid scope of the NCR1/NPC2 system using photo-crosslinkable and clickable lipid analogs, namely pac-cholesterol, pac-sphingosine and pac-ceramide. Finally, we reconstitute the transfer of pac-sphingosine from NPC2 to the NTD in vitro. Collectively, our results support that the yeast NPC system can work as versatile machinery for vacuolar homeostasis of structurally diverse lipids, besides ergosterol. Summary blurbResults of X-ray crystallography and binding assays with different lipids expand our knowledge of the substrate scope of the Niemann-Pick type C1-related proteins NCR1 and NPC2 in yeast. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/598172v2_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@102579borg.highwire.dtl.DTLVardef@c5be27org.highwire.dtl.DTLVardef@471096org.highwire.dtl.DTLVardef@191ee26_HPS_FORMAT_FIGEXP M_FIG C_FIG

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↗

bioRxiv2023

Automated quantification of lipophagy in Saccharomyces cerevisiae from fluorescence and cryo-soft X-ray microscopy data using deep learning

Lipophagy is a form of autophagy by which lipid droplets (LDs) become digested to provide nutrients as a cellular response to starvation. Lipophagy is often studied in yeast, Saccharomyces cerevisiae, in which LDs become internalized into the vacuole. There is a lack of tools to quantitatively assess lipophagy in intact cells with high resolution and throughput. Here, we combine soft X-ray tomography (SXT) with fluorescence microscopy and use a deep learning computational approach to visualize and quantify lipophagy in yeast. We focus on yeast homologs of mammalian Niemann Pick type C proteins, whose dysfunction leads to Niemann Pick type C disease in humans, i.e., NPC1 (named NCR1 in yeast) and NPC2. We developed a convolutional neural network (CNN) model which classifies ring-shaped versus lipid-filled or fragmented vacuoles containing ingested LDs in fluorescence images from wild-type yeast and from cells lacking NCR1 ({Delta}ncr1 cells) or NPC2 ({Delta}npc2 cells). Using a second CNN model, which performs automated segmentation of LDs and vacuoles from high-resolution reconstructions of X-ray tomograms, we can obtain 3D renderings of LDs inside and outside of the vacuole in a fully automated manner and additionally measure droplet volume, number, and distribution. We find that cells lacking functional NPC proteins can ingest LDs into vacuoles normally but show compromised degradation of LDs and accumulation of lipid vesicles inside vacuoles. This phenotype is most severe in{Delta} npc2 cells. Our new method is versatile and allows for automated high-throughput 3D visualization and quantification of lipophagy in intact cells.

bioinformatics↗