Ca2＋ signaling in astrocytes is a central mechanism of intercellular communication in the brain and plays a key role in regulating neuronal excitability, synaptic plasticity, and energy metabolism. Disruption of astrocytic Ca2＋ dynamics is a characteristic of neurodegenerative diseases, as are deviations in cholesterol trafficking and metabolism, which are essential for maintaining membrane structure and function. Although recent studies have begun to explore links between Ca2＋ signaling and sterol homeostasis in astrocytes, unbiased analytical workflows and mechanistic insight into how cholesterol and related sterols regulate astrocytic Ca2＋ dynamics remain limited.Here, we apply dynamic mode decomposition to dissect and classify Ca2＋ signals obtained from time-lapse imaging of human astrocytes. Using both synthetic and experimental datasets, we show that delay-embedded dynamic mode decomposition combined with clustering separates heterogeneous Ca2＋ activity into distinct dynamical states. This analysis reveals that increasing cholesterol levels shift astrocytes toward more active oscillatory states, whereas acute cholesterol depletion suppresses Ca2＋ activity. In addition, pretreatment with the oxysterols 24-, 25-, and 27-hydroxycholesterol impaired cholesterol-induced Ca2＋ oscillations.Together, this work presents a general computational framework for decomposing and analyzing complex spatiotemporal Ca2＋ signals, with broad applicability to quantitative imaging in cell biology.

Abstract Sterol molecules play indispensable roles in the biology of cells and organisms. Yet, arthropods, including ticks, lack the capacity for de novo sterol biosynthesis and must rely on exogenous sources. How these organisms sense and utilise exogenous lipids at the cellular level remains poorly understood. Here, we show that host cholesterol and linoleic acid act as essential external signals that license proliferation of Ixodes ricinus tick cells. In lipid-depleted conditions, cells fail to proliferate despite retaining intracellular cholesterol, indicating that exogenous lipids function as regulatory cues rather than merely structural components. We further demonstrate that tick cells exhibit a non-canonical intracellular distribution of cholesterol, with predominant accumulation in lysosome-associated compartments, and that lipid availability induces a coordinated transcriptional program involving lipid uptake and trafficking machinery. Importantly, we find that limiting host lipid availability significantly reduces extracellular RNA output of tick-borne encephalitis virus (TBEV) from infected tick cells, indicating that viral production is affected by the metabolic state of the host cell. Together, our findings establish host-derived lipids as key regulators of cellular state in a sterol-auxotrophic organism and identify lipid availability as a determinant of flavivirus output. This work provides a conceptual framework linking nutrient sensing, cell proliferation, and vector-pathogen interactions.

Low-density lipoprotein (LDL) delivers cholesterol to mammalian cells in the form of cholesteryl esters (CEs), but due to the lack of suitable tools, our understanding of the intracellular transport and hydrolysis of CEs is limited. We present a novel approach for studying LDL-derived CEs in cells using fatty acyl chain conjugates of the intrinsically fluorescent cholestatrienol (CTL). We demonstrate that CTL esters reconstituted into LDL particles are hydrolyzed in late endosomes and lysosomes (LE/LYSs) by acid lipase, while an LDL-derived CTL ether analogue cannot leave LE/LYSs. Using live-cell imaging, lipidomics, and multimodal Bayesian modeling, we discover a sequential biphasic transport of LDL-derived CTL to LE/LYSs with a half-time of 3.0 h. Hydrolyzed CTL derived from LDL-associated CTL esters is rapidly re-esterified with a similar half-time and stored in lipid droplets, demonstrating efficient sterol transport to the endoplasmic reticulum. Lack of functional Niemann-Pick C1 or C2 protein caused lysosomal accumulation of LDL-derived sterol. Using lipidomics and kinetic modeling, we also track LDL-derived CEs and triacylglycerols in cells and determine the uptake kinetics for each lipid species individually. Our novel approach allows for precise measurement of postendocytic trafficking and metabolism of LDL-derived cholesterol and other lipids in living cells.

Ergosterol is the main sterol in yeast and an important lipid constituent of the yeast plasma membrane (PM). Methods for analysis of ergosterol trafficking between PM and subcellular compartments often rely on fluorescence microscopy, but existing sterol probes either mimic ergosterol poorly or have inconvenient fluorescence properties. Here, we present a novel intrinsically fluorescent probe that differs from ergosterol only by having a 3'-keto group and two additional conjugated double bonds in the ring system. We show that this analog, named Erg-Tetraene, can order fatty acyl chains of phospholipids and partitions partially into the liquid-ordered phase in model membranes containing cholesterol. The Erg-Tetraene has a red-shifted emission and a much stronger two-photon absorption than the widely used analog dehydroergosterol, allowing for its convenient imaging on commercial microscope systems. Using multi-color confocal and two-photon microscopy, we show that uptake of Erg-Tetraene into yeast depends on the sterol transporters Aus1/Pdr11 and is followed by rapid transport to the vacuole and to lipid droplets. Together, we present a novel analogue of ergosterol with improved fluorescence properties for sterol trafficking studies in yeast and other model organisms.

The brain, though less than 10% of body mass, contains about 25% of total cholesterol (CHL), emphasizing CHL's key role in neuronal function. Many CHL actions are stereospecific, as shown by differences from its 3α-hydroxy epimer, epicholesterol (epiCHL). How this minor structural change alters membrane properties and sterol transport remains unclear. Here, we compare fluorescent analogs of CHL (cholestatrienol, CTL) and epiCHL (epicholestatrienol, epiCTL), which closely mimic their natural counterparts. Biophysical membrane properties, such as flip-flop, acyl-chain ordering, and interbilayer transfer, depend on the orientation of the 3-hydroxy group. Similarly, transport by sterol transport proteins (STPs) and intracellular trafficking of the sterols in human astrocytes are stereospecific. Treatment with 25-hydroxycholesterol increases uptake of both epimers, but only CTL shows enhanced esterification and lipid droplet storage. These findings demonstrate that subtle cholesterol structural changes affect cellular homeostasis and establish epiCTL as a useful probe of sterol stereospecificity and trafficking.

ABSTRACT Kinesin-3 motor proteins are increasingly recognized for their important roles in cilia. The mammalian kinesin-3 motor KIF13B moves bidirectionally in primary cilia and regulates ciliary content, but its relationship to the intraflagellar transport (IFT) machinery is unclear. Here, we combine quantitative live-cell imaging with a new kymograph analysis based on dynamic mode decomposition (DMD) to separate mobile from immobile protein populations in primary cilia. This approach simplifies extraction of molecular velocities from kymographs and reveals that a KIF13B deletion mutant retaining only the motor domain and part of the forkhead-associated domain does not alter steady-state IFT velocity or frequency. However, when retrograde dynein-2 function is inhibited by Ciliobrevin D, both anterograde and retrograde IFT velocities decrease in parental cells, as expected, but remain unchanged in KIF13B mutant cells. Structured illumination, confocal, and STED microscopy further show that KIF13B localizes to the ciliary membrane and concentrates at the periciliary membrane region and the centriolar subdistal appendages, below the distal appendage marker FBF1. Our improved kymograph approach provides new insight into KIF13B ciliary function and simplifies the quantitative analysis of ciliary protein transport.

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. The model's outcome 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 an 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.

ABSTRACT Background Statins have gained increasing interest for their potential therapeutic effect in Parkinson’s disease (PD). Beyond their cholesterol-lowering effect, statins decrease synthesis of isoprenoids, which is believed to account for their pleiotropic effects. Isoprenylation is important for proper membrane localization and function of the Rho GTPases, including RhoA. RhoA signalling has emerged as a possible underlying signalling pathway involved in the pathogenesis of PD and other neurodegenerative diseases. Methods In the present study, we investigated the effects of simvastatin on neurodegeneration-associated phenotypes using human induced pluripotent stem cell-derived dopaminergic (DA) neurons from both PD patients and isogenic PARK2 -/- cell lines. The dependence on RhoA was confirmed using direct RhoA inhibition using rhosin. Assessed phenotypes included structural integrity, mitochondrial and lysosomal characteristics, cytokine secretion, and cell viability. To understand the relevance of RhoA in PD, RhoA activity was measured in 32 PD patient iPSC-derived lines with different familial PD-related mutations and in healthy controls. Results Simvastatin rescued multiple PD-associated phenotypes, including impaired DA neurite outgrowth, mitochondrial and lysosomal alterations, cytokine release, and cell death. RhoA inhibition was associated with changes in mitophagy- and autophagy-related markers, suggesting improved autophagic and mitophagic turnover. Furthermore, we performed the first systematic screen of RhoA activity across 32 iPSC-derived DA neuron lines representing multiple genetic forms of PD (PINK1 loss of function, parkin loss of function, LRRK2 (G2019S), LRRK2 (R1441C), GBA (L44P), GBA (N370S), A53T, and SNCA triplication) and healthy controls. RhoA activity was perturbated across several genetic forms of PD subtypes and was significantly increased in many, although not all, patient lines compared with healthy controls, highlighting disease heterogeneity and supporting RhoA dysregulation as a shared pathogenic mechanism in a subset of PD. Conclusions Our findings identify aberrant RhoA signalling as a convergent pathogenic mechanism across multiple forms of genetic PD and demonstrate that simvastatin ameliorates PD-associated phenotypes through RhoA inhibition. These results support RhoA as a promising therapeutic target while emphasizing the importance of patient stratification based on RhoA activity.

Soft X-ray tomography (SXT) provides detailed structural insight into whole cells but is hindered by experimental artifacts such as the missing wedge and by limited availability of annotated datasets. We present , a simulation pipeline that generates realistic cellular phantoms and applies synthetic artifacts to produce paired noisy volumes, sinograms, and reconstructions. We validate our approach by training a neural network primarily on synthetic data and demonstrate effective few-shot and zero-shot transfer learning on real SXT tomograms. Our model delivers accurate segmentations, enabling quantitative analysis of noisy tomograms without relying on large labeled datasets or complex reconstruction methods.

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. Achieving a resolution of 54 nm full-pitch and tomogram acquisition times of 30 min to two hours, we validate the system across a range of biologically relevant contexts, including protists, yeast, and mammalian cells containing polymeric and inorganic nanoparticles. These use cases establish the robustness of the laboratory based system for studying cell architecture, organelle interactions, and nanoparticle trafficking. By showing that a compact SXT system can achieve reliable high-resolution imaging across various cell types, this study highlights a major step toward making correlative cryogenic X-ray imaging broadly accessible in laboratory settings. Future developments will aim at enhanced throughput, deeper integration with correlative imaging modalities, and extension to more complex specimen types, including tissue.

Background Patients with the genetic disorder Niemann-Pick type C2 disease (NP-C2) suffer from lysosomal accumulation of cholesterol causing both systemic and severe neurological symptoms. In a murine NP-C2 model, otherwise successful intravenous Niemann-Pick C2 protein (NPC2) replacement therapy fails to alleviate progressive neurodegeneration as infused NPC2 is unable to cross the blood-brain barrier (BBB). Genetic modification of brain endothelial cells (BECs) is thought to enable secretion of recombinant proteins thereby overcoming the restrictions of the BBB. We hypothesized that BBB-directed gene therapy using the AAV-BR1-NPC2 vector would transduce both BECs and neurons in a mouse model of NP-C2 ( Npc2 -/-). Methods Six weeks old Npc2 -/- mice were intravenously injected with the AAV-BR1-NPC2 vector. Post-mortem analyses included gene expression analyses, determination of NPC2 transduction in the CNS, and co-detection of cholesterol with NPC2 in neurons. Results The vector exerted tropism for BECs and neurons resulting in a widespread NPC2 distribution in the brain with a concomitant reduction of cholesterol in adjacent neurons, presumably not transduced by the vector. Conclusion The data suggests cross-correcting gene therapy to the brain via delivery of NPC2 from BECs and neurons.

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. ### Competing Interest Statement The authors have declared no competing interest.

Oscillations are a common phenomenon in cell biology. They are based on non-linear coupling of biochemical reactions and can show rich dynamic behavior as found in, for example, glycolysis of yeast cells. Here, we show that dynamic mode decomposition (DMD), a numerical algorithm for linear approximation of non-linear dynamics, can be combined with time-delay embedding (TDE) to dissect damped and sustained glycolytic oscillations in simulations and experiments in a fully data-driven manner. Together with an assessment of spurious eigenvalues via residual DMD, this provides a unique spectrum for each scenario, allowing for high-fidelity time-series and image reconstruction. By machine-learning-based clustering of identified DMD modes, we are able to classify NADH oscillations, thereby discovering subtle phenotypes and accounting for cell-to-cell heterogeneity in metabolic activity. This is demonstrated for varying glucose influx and for yeast cells lacking the sterol transporters Ncr1 and Npc2, a model for Niemann Pick type C disease in humans. DMD with TDE can also discern other types of oscillations, as demonstrated for simulated calcium traces, and its forecasting ability is on par with that of Long Short-Term Memory (LSTM) neural networks. Our results demonstrate the potential of DMD for analysis of oscillatory dynamics at the single-cell level.

Allopregnanolone (AlloP) is an example of neuroactive steroids (NAS), which is a potent allosteric activator of the γ-aminobutyric acid A (GABAA) receptor. The mechanisms underlying the biological activity of AlloP and other NAS are only partially understood. Here, we present intrinsically fluorescent analogs of AlloP (MQ-323) and its 3β-epimer, epi-allopregnanolone (E-AlloP) (YX-11), and show, by a combination of spectroscopic and computational studies, that these analogs mimic the membrane properties of AlloP and E-AlloP very well. We found stereospecific differences in the orientation and dynamics of the NAS as well as in their impact on membrane permeability. However, all NAS are unable to condense the lipid bilayer, in stark contrast to cholesterol. Using Förster resonance energy transfer (FRET) and electrophysiological measurements, we show that MQ-323 but not YX-11 binds at the intersubunit site of the ELICα1GABAA receptor and potentiates GABA-induced receptor currents. In aqueous solvents, YX-11 forms aggregates at much lower concentrations than MQ-323, and loading both analogs onto cyclodextrin allows for their uptake by human astrocytes, where they become enriched in lipid droplets (LDs), as shown by quantitative fluorescence microscopy. Trafficking of the NAS analogs is stereospecific, as uptake and lipid droplet targeting is more pronounced for YX-11 compared to MQ-323. In summary, we present novel minimally modified analogs of AlloP and E-AlloP, which enable us to reveal stereospecific membrane properties, allosteric receptor activation, and intracellular transport of these neurosteroids. Our fluorescence design strategy will be very useful for the analysis of other NAS in the future.

Acyl-coenzyme A: cholesterol acyltransferases are enzymes which are involved in the homeostasis of cholesterol. Impaired enzyme activity is associated with the occurrence of various diseases like Alzheimer's disease, atherosclerosis, and cancers. At present, mitotane is the only inhibitor of this class of enzymes in clinical use for the treatment of adrenocortical carcinoma but associated with common and severe adverse effects. The therapeutic effect of mitotane depends on its interaction with cellular membranes. The search for less toxic but equally effective compounds is hampered by an incomplete understanding of these biophysical properties. In the present study, the interaction of the three ACAT inhibitors nevanimibe, Sandoz 58-035, and AZD 3988 with membranes has been investigated using lipid model membranes in conjunction with biophysical experimental (NMR, ESR, fluorescence) and theoretical (MD simulations) approaches. The data show, that the drugs (i) incorporate into lipid membranes, (ii) differently influence the structure of lipid membranes; (iii) affect membrane structure depending on the lipid composition; and (iv) do not cause hemolysis of red blood cells. The results are discussed with regard to the use of the drugs, in particular to better understand their efficacy and possible side effects.

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 became 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 caused a 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 analogues 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. Importantly, binding and membrane aggregation of natamycin was paralleled by a decrease of the dipole potential in the PM, and this effect was enhanced in the presence of myriocin. We conclude that ergosterol promotes binding and aggregation of natamycin in the yeast PM, which can be synergistically enhanced by inhibitors of sphingolipid synthesis.

Subcellular membranes have complex lipid and protein compositions, which give rise to organelle-specific membrane packing, fluidity, and permeability. Due to its exquisite solvent sensitivity, the lipophilic fluorescence dye Nile Red has been used extensively to study membrane packing and polarity. Further improvement of Nile Red can be achieved by introducing electron donating or withdrawing functional groups. Here, we compare the potential of derivatives of Nile Red with such functional substitutions for super-resolution fluorescence microscopy of lipid packing in model membranes and living cells. All studied Nile Red derivatives exhibit cholesterol-dependent fluorescence changes in model membranes, as shown by spectrally resolved stimulated emission depletion (STED) microscopy. STED imaging of Nile Red probes in cells reveals lower membrane packing in fibroblasts from healthy subjects compared to those from patients suffering from Niemann Pick type C1 (NPC1) disease, a lysosomal storage disorder with accumulation of cholesterol and sphingolipids in late endosomes and lysosomes. We also find small but consistent changes in the fluorescence lifetime of the Nile Red derivatives in NPC1 cells, suggesting altered hydrogen-bonding capacity in their membranes. All Nile Red derivatives are essentially non-fluorescent in water but increase their brightness in membranes, allowing for their use in MINFLUX single molecule tracking experiments. Our study uncovers the potential of Nile Red probes with functional substitutions for nanoscopic membrane imaging.

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.

Live-cell imaging of cholesterol trafficking depends on suitable cholesterol analogs. However, existing fluorescent analogs of cholesterol either show very different physicochemical properties compared to cholesterol or demand excitation in the ultraviolet spectral region. We present a strategy to synthesize two novel intrinsically fluorescent sterol probes with a close resemblance of cholesterol. The analogs contain four conjugated double bonds in the ring system and either a keto group (probe 5) or a hydroxy group (probe 6) in the C3 position. The emission of 5 is in the visible range of the spectrum, i.e., red-shifted by 150 nm compared to the widely used dehydroergosterol. Together with its high multiphoton absorption, this allows for imaging of 5 on conventional microscopes, including multicolor 3D and time-lapse microscopy. Molecular dynamics simulations and nuclear magnetic resonance spectroscopy reveal that 5 can condense the fatty acyl chains of phospholipids in model membranes. In giant unilamellar vesicles, 5 partitions equally into the liquid-ordered and disordered phases. In contrast, 6 emits in the ultraviolet range and is unstable in solution, preventing its use in live-cell imaging applications. The good photophysical properties of 5 make it a suitable analogue for improved live-cell imaging of sterol transport.

CRISPR-mediated endogenous tagging of genes provides unique possibilities to explore the function and dynamic subcellular localization of proteins in living cells. Here, we describe experimental strategies for endogenous PCR-tagging of ciliary genes in human RPE1 cells and how image acquisition and analysis of the expressed fluorescently tagged proteins can be utilized to study the dynamic ciliary processes of intraflagellar transport and vesicular trafficking.