Biology subjects

Martin, C.

Publications and source records attributed to Martin, C..

At least 19 recordsLinked to original sources

bioRxiv2026

A robust and scalable image analysis framework for phenotyping human thoracic aorta

Large-scale phenotyping of the thoracic aorta requires a workflow in which every step, from segmentation to phenotype extraction, runs without manual intervention. We present a robust and scalable framework that converts contrast-enhanced CT into anatomical landmarks, a patient-specific quadrilateral mesh, a wall-stress field and regional phenotypes of the thoracic aorta. Four nnU-Net segmentation tasks delineate the aorta, its anatomical regions and two partitions of the aortic root. A surface-curve-point procedure derives the annulus, the sinotubular junction, the ostia of the supra-aortic branches, the cusp nadirs and the commissures from the interfaces between segmented regions. We fit a structured template of 24,882 quadrilateral elements to the segmented aortic surface by staged, differentiable mesh deformation and compute the transmural mean wall stress with PyTorch-FEA. The structured mesh provides node-to-node correspondence across patients, anchored to the anatomy by the landmarks, from which the framework extracts regional morphological and biomechanical phenotypes.

bioengineering↗

bioRxiv2026

CheckAMG: Accurate Identification of Auxiliary Viral Genes with Genome-Language Models

Viruses shape microbial metabolism through auxiliary viral genes (AVGs) that reprogram host metabolism, physiology, and gene regulation during infection. Identifying AVGs is complicated by ambiguous viral versus cellular assignment, inconsistent curation, and reliance on sequence homology that misses divergent functions. Here we present CheckAMG, which pairs annotation-based AVG prediction, curated with a per-gene viral scoring system and ontological mapping of metabolic function, with a finetuned genome-language model for annotation-independent discovery. Benchmarked against DRAM-V and VIBRANT across three ecosystems, CheckAMG produced more strongly supported auxiliary metabolic gene (AMG) calls, and uniquely among AMG tools reports auxiliary physiological (APGs) and regulatory (AReGs) genes. Applied to 1,005,980 fragmented or complete soil and human-gut viral genomes, CheckAMG identified 541,199 AVGs tracking biome-specific protein clusters and functions, including 109,107 proteins with no detectable sequence similarity to any reference database. CheckAMG thus provides a reproducible, scalable framework for identifying the genes through which viruses reprogram host biology.

bioinformatics↗

bioRxiv2026

Beyond harm: synthesising meta-analytical and mechanistic evidence on animal responses to microplastics

A central question in ecology and evolution is determining when environmental challenges translate into stress and biological harm. Human-derived pollutants are often assumed to be inherently damaging; however, their effects may depend strongly on ecological and physiological context. Microplastics exemplify this complexity, eliciting heterogeneous responses across taxa rather than uniform toxicity. Here, we synthesise evidence from 14 meta-analyses encompassing 9,101 effect sizes to identify the conditions under which microplastic exposure leads to damage, neutrality, compensation, or stimulation. These syntheses reveal clear negative effects alongside frequent neutral outcomes and occasional stimulatory responses. Microplastic effects vary with particle characteristics and exposure conditions and are strongly moderated by species-specific traits and life stage. We further argue that plasticity in the gut and in behavioural and physiological traits may buffer microplastic effects. Emerging evidence also indicates that biofilm colonisation alters the physicochemical and biological properties of microplastics, potentially modifying their ecological interactions and toxicity profiles. By reframing microplastics as context-dependent challenges rather than universally toxic agents, we provide a conceptual framework for understanding animal responses under realistic ecological conditions and identifying the biological and environmental contexts in which microplastic exposure is most likely to result in harm.

ecology↗

bioRxiv2026

Syndecan-4 exerts canonical heparan sulfate-dependent and noncanonical heparan sulfate-independent functions that regulate Aβ amyloid homeostasis

Background Heparan sulfate (HS) and heparan sulfate proteoglycans (HSPGs) are components of the amyloid deposits in Alzheimers disease (AD) and other amyloidoses. HS and HSPGs are canonically thought to facilitate amyloid deposition by accelerating the aggregation of amyloidogenic proteins and impairing their clearance in a HS-dependent manner. Methods Leveraging insights from large-scale proteomic data, we focused on Syndecan-4 (Sdc4), the most increased transmembrane HSPG in the AD brain and in the brain of A{beta} amyloid depositing mice. We used proximity ligation assays (PLA) to evaluate the association of Sdc4 with A{beta} in situ and assessed the impacts of the Sdc4 ectodomain on A{beta} aggregation in vitro. Overexpression studies in cells, hiPSC-derived neurons, and mouse organotypic brain slice cultures (OBSCs) coupled with structure-function studies were used to investigate impacts on A{beta} production and APP processing. Finally, effects of overexpression of Sdc4 in vivo in the CRND8 amyloid deposition model were evaluated. Results Consistent with canonical roles, PLA demonstrated a spatial association of Sdc4 with amyloid deposits, and in vitro, the Sdc4 ectodomain accelerated A{beta} fibril formation in a HS-dependent manner. Unexpectedly, Sdc4 overexpression reduced A{beta} production in CHO cells, hiPSC-derived neurons, and OBSCs. These effects were accompanied by dramatic decreases in the levels of sAPP and C83 and increased immature APP in the cell. Sdc4 promoted altered APP localization into detergent resistant membrane domains and increased APP association with ATG5+/LC3+/Cathepsin D+ vesicles. Structure-function studies revealed that the transmembrane region mediates these effects in a glycosaminoglycan-independent manner. Sdc4 overexpression in the brain of APP mice significantly reduced amyloid deposition at an early age. Conclusions Sdc4 exerts paradoxical and mechanistically distinct effects that could impact AD pathogenesis differentially, potentially promoting A{beta} fibrillization extracellularly while suppressing APP processing and A{beta} production. Such data challenge the prevailing view that increased levels of HSPGs in AD are always pro-amyloidogenic and identify Sdc4 as a previously unrecognized regulator of amyloid homeostasis in AD.

neuroscience↗

bioRxiv2026

Semisynthesis of Oxalyl-Coenzyme A for Enzymatic Assays

Oxalyl-coenzyme A (oxalyl-CoA) is a key intermediate in oxalate metabolism in plants, fungi and oxalate-degrading bacteria, but its limited availability has restricted biochemical investigations of oxalyl-CoA-dependent enzymes. Here, we describe a practical semisynthetic procedure for the preparation of oxalyl-CoA based on rapid oxalyl transfer from S-oxalyl p-thiocresol to coenzyme A. The reaction was monitored directly by 1H NMR spectroscopy, allowing optimisation of pD and reaction conditions. Following removal of thiocresol and purification by reversed-phase HPLC, oxalyl-CoA was obtained in 39% yield as determined by quantitative 1H NMR. The product was characterised by high-resolution electrospray mass spectrometry and comprehensive 1H, 13C and 31P NMR spectroscopy, confirming its structure unequivocally. During the study, the limited stability of oxalyl-CoA in aqueous solution was documented, leading to recommendations for its purification and storage. The semisynthetic protocol provides a convenient source of analytically pure oxalyl-CoA suitable for biochemical assays and supplies reference spectroscopic data for its unambiguous identification. The biological utility of the semisynthetic oxalyl-CoA was demonstrated by its application as an acyl donor substrate in assays of PnBAHD15, enabling quantitative kinetic characterisation of the enzyme and illustrating its suitability for biochemical studies of oxalyl-CoA-dependent enzymes.

biochemistry↗

bioRxiv2026

SPARC: A Graph-based Optimization Framework for Directional Trajectory Reconstruction Across Ordered Single-Cell Conditions

Single-cell transcriptomics has enabled systematic profiling of cellular states across ordered biological contexts, including developmental stages, treatment phases, disease progression, and anatomical compartments. A central challenge is to reconstruct trajectories that respect the directionality imposed by biology or experimental design. Existing trajectory inference methods reconstruct cell-state progressions from latent-space geometry but do not enforce external biological ordering during graph construction, yielding biologically inadmissible transitions. An emerging paradigm of optimal-transport (OT) approaches partially addresses this limitation by incorporating experimental ordering into probabilistic state-to-state correspondences, yet their pairwise formulation cannot resolve whether a given state is an intermediate state or a terminal state along a multi-step progression. In multi-timepoint settings, OT typically estimates couplings only betweenadjacent timepoints and then chains these locally solved couplings to approximate long-range trajectories without a global optimization across all conditions simultaneously. Here we present SPARC, a graph-based optimization framework that quantifies similarity in a shared high-dimensional latent space and reconstruct directional trajectories under biological constraints. Global shortest-path optimization over this graph yields progression routes, from which SPARC derives path-based pseudotime identifies bottlenecks clusters, and detects gene temporal behavior. SPARC was evaluated across three complementary settings representing distinct trajectory-inference challenges. Its application to paired primary and lung metastatic osteosarcoma samples allows us to be the first to propose a "cross-organ bone-like microenvironment" hypothesis, in which osteoclastogenic signaling establishes a bone-like remodeling niche within the pulmonary metastatic lesion that promotes osteoclast differentiation and activity. The findings are independently recoverable in human osteosarcoma Visium HD spatial transcriptomics.

bioinformatics↗

bioRxiv2026

Semi-quantitative Classification of HIV-1 Nucleic Acids Using ResNet Image Analysis of Discretized Isothermal Amplification Reactions in a Microfluidic Chip

Isothermal nucleic acid amplification tests enable rapid and decentralized molecular diagnostics but often lack robust quantitative readouts compared to quantitative PCR. Here, we present a semi-quantitative nucleic acid measurement approach using machine learning to extract spatiotemporal features from real-time fluorescence imaging of rapid isothermal amplification reactions in microfluidic chips. A convolutional neural network was trained on multiple images sampled throughout a chip-based recombinase polymerase amplification reaction to classify samples into clinically relevant or logarithmically spaced concentration ranges spanning five orders of magnitude. The clinical classification model achieved 94.6% accuracy, and the logarithmic model achieved 92.7% accuracy, with most errors occurring between adjacent concentration categories. By learning spatiotemporal patterns of fluorescence development rather than relying on explicit feature extraction, the model remained accurate at both high and low nucleic acid concentration regimes where other quantitative isothermal molecular tests struggle. This approach enables automated interpretation of amplification reactions and extends the usable dynamic range of the assay. These results demonstrate that integrating machine learning with image-based amplification methods can support rapid semi-quantitative molecular testing and may facilitate broader deployment of nucleic acid diagnostics outside centralized laboratory settings. Author summaryMany rapid nucleic acid testing methods for infectious diseases are simple to run but struggle to measure how much genetic material is present, which limits their usefulness in clinical decision-making. In our work, we study a technique that produces visible fluorescent patterns during nucleic acid amplification reactions. Traditionally, the amount of nucleic acids present are measured by counting individual bright spots, but this becomes difficult when the target nucleic acid concentration is high and the spots merge together. We developed a machine learning approach that models how the fluorescence pattern changes over time. By analyzing a sequence of images from each reaction, our model can assign samples to concentration ranges across a wide span. This allows us to extract meaningful information even when traditional analysis methods break down. Because this approach works with simple imaging systems and does not require complex equipment, it could help support more informative and accessible diagnostic testing in point-of-care and low-resource settings.

bioengineering↗

bioRxiv2026

Single-Cell Isolation and Patient-Derived Organoid Generation Using the Pala™ Single Cell Dispenser with Cancer Cell Lines Spiked into Blood as a Circulating Tumour Cell Model: A Platform for Precision Oncology and Drug Discovery

The isolation of cancer cells and rare circulating tumour cells (CTCs) and the initiation of patient-derived organoids (PDOs) represent two critical new approach methodologies (NAMs) for advancing precision oncology and drug discovery. However, current technologies encounter significant limitations, including high system pressures that compromise cell viability, sample loss, and reliance on marker-dependent enrichment strategies. Here, we performed a technical validation of the Pala Single Cell Sorter/Dispenser (Bio-Techne) using cancer cell lines spiked into healthy donor blood as a model for CTCs, alongside cells isolated from ovarian cancer (OC) patients and cervical cancer cell lines. The platform achieved up to 80% single-cell dispensing efficiency under gentle sorting conditions (<2 psi), successfully dispensing single cancer cells, cell clusters, and cancer cells spiked into blood (mimicking CTCs). Concurrently, three-dimensional organoid structures generated from dissociated OC samples and cervical cancer cell lines showed viable growth and cluster formation within one week. Compared to literature values for fluorescence-activated cell sorting (FACS), the Pala maintained higher post-sort viability (88% vs. 55-70%) and organoid initiation efficiency (68% vs. 42%). This work establishes the Pala as a flexible tool for patient cancer cell dispensing, CTC-mimic isolation, and PDO generation within drug discovery workflows. Clinical validation using authentic patient CTCs remains necessary prior to clinical implementation.

Cancer Biology↗

bioRxiv2026

Lipid-Gated Vesicular Trafficking Directs HSPA1A to the Plasma Membrane Through the Endo-Lysosomal Network

HSPA1A is a stress-inducible molecular chaperone that localizes to the plasma membrane (PM) of heat-shocked and cancer cells, where its membrane-associated form contributes to therapeutic resistance, membrane stabilization, and immune modulation. Because HSPA1A lacks a signal peptide, it does not follow the classical secretory pathway; instead, it reaches the PM through unconventional routes whose vesicular intermediates and intracellular lipid requirements remain largely undefined. Here, we show that following heat shock, HSPA1A undergoes coordinated redistribution across the endo-lysosomal network. It transiently associates with PI(3)P-enriched early endosomes, progresses through Rab4A- and Rab4B-positive recycling endosomes, and accumulates in LAMP1-positive lysosomes, while avoiding degradative and slow-recycling routes. Pharmacological inhibition of the ER-Golgi pathway did not affect HSPA1As PM localization, while disruption of endosomal maturation and lysosomal function resulted in significant reductions. Heat shock drives a progressive increase in lysosomal BMP immunoreactivity, and pharmacological BMP accumulation increased PM-HSPA1A, whereas intracellular antibody-mediated BMP blockade reduced it, identifying BMP-enriched lysosomes as regulatory hubs that govern HSPA1A PM competence. Using a rapamycin-inducible compartment-specific phosphatase system, we further demonstrate that PI(4)P is required not only at the PM for final docking but within early endosomes, late endosomes, and lysosomes, establishing a distributed PI(4)P requirement across the endosomal network. Together, these findings define a lipid-gated vesicular trafficking mechanism for HSPA1A PM localization and identify lysosomal BMP and endosomal PI(4)P as additional regulatory layers relevant to cancer cells in which constitutive lipid remodeling may sustain membrane-associated HSPA1A and its pro-survival functions.

Cell Biology↗

bioRxiv2026

Nanoparticle mediated delivery of PD-L1 inhibitor enhances γδ T cell immunotherapy against metastatic ovarian cancer cells

IntroductionImmune checkpoint inhibitors (ICIs) have only shown limited efficacy for patients with ovarian cancer (OC), partly due to the immune suppressive tumour microenvironment (TME) and platelet cloaking of the cancer cells. We tested a nanomedicine strategy to enhance {gamma}{delta} T cell immunotherapy by conjugating the PD-L1 inhibitor (BMS202) to nanodiamonds (NDs). MethodsPatient-derived ascites cells were exposed to activated platelets to model platelet cloaking and the immunosuppressive phenotype in metastatic OC. ND/BMS202 nanocomplexes were then applied to platelet-conditioned OC cells and co-cultured with expanded {gamma}{delta} T cells. Cytotoxicity and immune activation were assessed by quantifying Granzyme B, CD107a, {gamma}-H2AX, cleaved caspase-3, and cleaved caspase-8. ResultsND-mediated delivery of BMS202 significantly enhanced {gamma}{delta} T cell-mediated killing of platelet cloaked OC cells in a dose-dependent manner, with greater efficacy than free BMS202 This enhanced cytotoxicity was supported by increased degranulation (CD107a), Granzyme B release, tumour cell apoptosis (caspase cleavage) and DNA damage ({gamma}-H2AX staining). ConclusionsND-based delivery of the PD-L1 inhibitor (BMS202) enhances {gamma}{delta} T cell-mediated killing of platelet-cloaked metastatic OC cells. While our data support enhanced {gamma}{delta} T cell cytotoxicity following BMS202 delivery, direct evidence of PD-L1 target engagement or PD-1/PD-L1 binding inhibition was not demonstrated in this study. These findings nonetheless justify further validation in patient-derived organoid models to optimize this {gamma}{delta} T cell-based combination immunotherapy and advance its development as a precision therapeutic strategy for metastatic OC.

immunology↗

bioRxiv2026

The pseudoproteinase iRhom2 critically promotes acute lung inflammation

ADAM17 sheds cell surface molecules such as TNF-, IL-6R and L-selectin. This activity requires either iRhom1 or iRhom2 as adapter molecules. Since iRhom2 is predominantly expressed in leukocytes and upregulated in tissue cells during inflammation, it represents a potential anti-inflammatory target. We therefore investigated the effects of iRhom2 deficiency in mice using in vivo, ex vivo, and in vitro models of acute inflammation. In an in vivo model of LPS-induced lung inflammation, iRhom2 knockout mice showed reduced neutrophil recruitment into the bronchoalveolar space. Notably, the few recruited neutrophils remained L-selectin positive, whereas most neutrophils in wildtype mice were L-selectin negative, confirming that L-selectin shedding depends on the iRhom2/ADAM17 axis. Furthermore, it suggests that impaired shedding is associated with decreased neutrophil recruitment. Additionally, ADAM17-dependent release of TNF- and IL-6R into the alveolar space was diminished in the absence of iRhom2, accompanied by reduced expression of inflammatory mediators. In isolated perfused lungs challenged with LPS, iRhom2 deficiency similarly reduced inflammatory mediator production, indicating a role for iRhom2 in resident lung tissue cells during the initiation of inflammation. To specifically assess immune cell responses, we further examined macrophages, the sole resident immune cells in the lung. In vitro, LPS-stimulated bone marrow derived macrophages lacking iRhom2 showed decreased shedding of TNF- and IL-6R and reduced induction of secondary inflammatory mediators. Thus, targeting iRhom2 effectively suppresses ADAM17-mediated inflammatory responses in the lung, while preserving basal ADAM17 activity through iRhom1, offering a more selective therapeutic strategy with fewer side effects. HighlightsO_LIThe ADAM17 adapter molecule iRhom2 is required for the acute lung inflammation of mice in vivo including cytokine response and neutrophil recruitment. C_LIO_LIIn resident lung tissue cells iRhom2 promotes the LPS induced inflammatory response at the alveolar interface. C_LIO_LIIn macrophages iRhom2 is required for an effective ADAM17 dependent inflammatory response to LPS. C_LIO_LIThus, iRhom2 targeting can serve to suppress inflammatory activities of ADAM17 in the lung. C_LI Graphical AbstractSchematic overview depicting the role of the iRhom2-ADAM17 axis in mediating neutrophil infiltration and cytokine release during induced pulmonary inflammation, serving as a model for acute lung injury (ALI). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/730404v1_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@d7edc9org.highwire.dtl.DTLVardef@3c4654org.highwire.dtl.DTLVardef@12d36f8org.highwire.dtl.DTLVardef@173dc97_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2026

Whole genome sequencing and variant discovery in 344 global grasspea (Lathyrus sativus L.) lines

The rapid expansion of genomic data resources for major crops is opening new options for crop improvement, while resources for most underutilised crops lag behind, risking a widening gap in crop improvement. One of these underutilised crops is grasspea (Lathyrus sativus), an ancient crop with modern cultivation centred on South Asia and Ethiopia. We conducted whole genome shotgun sequencing on a global collection of 344 grasspea lines, producing over 152 billion reads. Following variant discovery and filtering we created a single nucleotide polymorphism (SNP) marker set of over 1.5 million SNPs. This is a resource of major significance for this crop which can help unlock its breeding potential through marker development and the identification of genes controlling agronomically important traits.

genomics↗

bioRxiv2026

Inter- and Intra-individual Variability in Oral Food Processing and Its Impact on Aroma Release

Aroma perception during food consumption results from the combined effects of food composition, oral processing (such as chewing and saliva action), the release and transport of volatile compounds toward the olfactory epithelium, followed by cognitive integration in the brain. Recent advances in real-time analytical techniques, particularly Proton Transfer Reaction-Time-of-Flight Mass Spectrometry (PTR-ToF-MS), enable in vivo monitoring of aroma release with high temporal resolution and have become widely used for analyzing the composition of exhaled air. However, the interpretation of aroma release kinetics remains challenging due to substantial intra- and inter-individual variability caused by differences in physiology, anatomy, oral behavior, and respiratory patterns. In this context, the present study was designed to quantify aroma release associated with different food oral processing (FOP) mechanisms, such as chewing and swallowing, using simple model matrices containing a single aroma compound, and to document inter- and intra-individual variability among subjects. Real-time PTR-MS measurements were combined with self-reported oral events and simultaneous respiratory monitoring to analyze aroma release from aqueous solutions and gummy discs flavored with isoamyl acetate. The results showed that inter-individual variability was higher than intra-individual variability and allowed its quantification in aroma release. Significant differences in aroma release kinetics were observed depending on FOP protocols. The importance of considering swallowing events when analyzing aroma release data was also highlighted.

systems biology↗

bioRxiv2026

Semi supervised GAN for smart microscopy, fast and data efficient cell cycle classification

Modern optical microscopes are fully motorised; however, transforming them into truly smart systems requires real-time adjustment of acquisition settings in response to detected objects and dynamic biological events. At the core are classification algorithms that commonly depend on customised softwares and are generally designed for narrowly-defined biological applications. In addition, they often require substantial annotated datasets for effective training. We introduce a semi-supervised generative adversarial network (SGAN) for robust cell-cycle stage classification under low-resource conditions, adaptable to diverse cellular structures. The framework combines unlabelled microscopy images with synthetically generated samples to mitigate limited annotation, while preserving stable performance even when the unlabelled subset is class-imbalanced. Tested on the Mitocheck dataset, which features five mitosis classes, the model achieved 93{+/-}2% accuracy using only 80 labelled per class and 600 unlabelled images. The proposed algorithm is generic and can be readily adapted to new labeling schemes, classification targets, cell lines, or microscopy modalities through transfer learning. SGAN is well suited for integration into automated microscopes, enabling efficient and adaptable image analysis across diverse biological and microscopy applications.

bioinformatics↗

bioRxiv2026

Arousal state alters brain network switching and moderates cognitive task performance

Arousal relates to cognitive performance, but the neural underpinnings of this relationship remain unclear. One candidate marker is switching rate, a dynamic measure that has been linked to cognition and has been speculated to be sensitive to arousal. However, whether switching rate is altered across arousal states has not been directly tested. Here, using fMRI together with concurrent eye monitoring and EEG, we examined how the switching rates of the default mode, salience, and central executive networks are altered across arousal states. Default mode and anterior salience networks exhibited significant differences in switching rates across arousal states determined with eye tracking. Notably, thalamic subregions showed arousal-dependent changes in switching rate that were replicated across independent datasets and arousal measures. Additionally, arousal moderated the relationship between average network switching and performance on a relational processing task. Together, these findings suggest that switching rate may index neural underpinnings of arousal-dependent cognition.

neuroscience↗

bioRxiv2026

A Universal, AI-based Design Framework for Efficient Manufacturing of mRNA Therapeutics

The growth of mRNA therapeutics is limited by bespoke manufacturing processes. To overcome this barrier to access and innovation, we introduce an AI-driven framework that decouples sequence design from manufacturing, analogous to the universal design principles that revolutionized the semiconductor industry. We performed a large-scale screen, quantifying the in vitro transcription (IVT) efficiency of one million diverse sequences. We then trained an interpretable deep learning model that accurately predicts manufacturability from sequences alone and learned underlying molecular mechanisms. An algorithm using this model prospectively improved the IVT yield of a vaccine and a gene-editing therapeutic by over 7.5-fold. Co-optimization for manufacturability and translation efficiency provided improvements over state-of-the-art commercial mRNA products. Our AI-driven framework establishes a universal design paradigm with the promise to democratize and accelerate the development of mRNA medicines, potentially unlocking a new era in biotechnology.

bioengineering↗

bioRxiv2026

Serum modulates the aggregation - toxicity landscape of the staphylococcal toxin PSMα3

The pathogenicity of Staphylococcus aureus relies on the secretion of various toxins, including phenol-soluble modulins 3 (PSM3), which play key roles in invasion and infection through its cytolytic activities. Recent controversies have focused on whether PSM3 propensity to self-assemble into unique amyloid-like cross- structures would underlie its high cytotoxicity. Here, by integrating Thioflavin T fluorescence, electron microscopy, and cell-based assays, we demonstrate that early soluble entities formed upon fibrillation - rather than mature fibrils - drive PSM3 cytotoxicity under near-physiological conditions. This mirrors the behavior of neurodegenerative disease related peptides, thus pointing towards a general mechanism of toxicity by amyloid forming peptides. Importantly, we elucidate the critical role of serum in this process: lipoproteins inhibit the formation of oligomeric and fibrillar entities, both in a time- and concentration-dependent manner, thereby drastically reducing cytotoxicity. We further reveal the uptake of such soluble entities in cells, where membrane interactions likely initiate and trigger cell death. These findings reconcile conflicting interpretations of PSM3 toxicity, highlighting the importance of the cellular environment in shaping peptide aggregation and biological function. By targeting such key virulence determinants, e.g. though the rational design of aggregation inhibitors, this study could open novel avenues in the quest for novel drugs against S. aureus infections.

biophysics↗

bioRxiv2026

Clove Aqueous Extract Triggers a Multi-Organellar Stress Crisis through Lysosomal Destabilisation and Mitochondrial Hyperpolarisation to Suppress Patient-Derived Ovarian Cancer Cells

Ovarian cancer (OC) remains a lethal malignancy with limited therapeutic options, underscoring the need for the identification of novel agents. Natural products like clove (Syzygium aromaticum) have shown promising anti-cancer activity, but their mechanism in OC is poorly understood. This study investigates the anti-tumour effects and underlying mechanisms of a clove aqueous extract (CAE) on a panel of patient-derived OC cells. We found that CAE significantly inhibited cellular proliferation and induced cell death in a time-and dose-dependent manner. Mechanistically, CAE induced profound cellular stress, activating the transcription factor ATF-2. This was accompanied by a significantly increased lysosomal stress response, as evidenced by increased lysosomal mass/acidity, and a pathogenic hyperpolarisation of the mitochondrial membrane potential ({Delta}{Psi}m). The bioenergetic crisis induced as a consequence resulted in a sharp reduction in cellular oxygen consumption rate (OCR). Notably, the sensitivity to CAE-induced lysosomal and mitochondrial dysfunction varied across cell lines, revealing distinct phenotypic responses. Our results demonstrate that clove extract exerts its anti-tumour effects by orchestrating a multi-organellar stress response, positioning lysosomal disruption as a central event in its mechanism of action. This study provides a strong rationale for the further development of clove-based interventions for OC.

cancer biology↗