Biology subjects

Malle, M. G.

Publications and source records attributed to Malle, M. G..

10 recordsLinked to original sources

bioRxiv2026

Recipient cell identity governs intracellular transport and membrane interactions of extracellular vesicles across species

Extracellular vesicles (EVs) function as a natural communication system, enabling transfer of biomolecules between cells. Although EVs are produced by nearly all cell types and have shown promise as therapeutic agents, our understanding of how EVs from different cellular origins recognize recipient cells, are taken up, and processed intracellularly remains limited. In particular, it remains unclear whether intracellular EV behavior is primarily governed by EV-intrinsic properties or by the recipient-cell environment. Here, we systematically investigate the relative contributions of EV origin and recipient-cell identity to intracellular EV trafficking. By combining single-vesicle tracking with machine learning-based diffusion-state classification, we analyzed EVs derived from four distinct sources across three recipient cell types over three different time spans. This approach enabled characterization of dynamic transport behaviors, overcoming limitations of traditional ensemble-averaging methods. We observed recipient cell-dependent differences in intracellular trafficking patterns, ranging from relatively uniform and dynamic motion to more heterogeneous and confined behaviors, reflecting variability in intracellular transport environments. Despite these differences, EV origin had only a modest influence on intracellular dynamics following uptake. These findings suggest a model in which intracellular transport arises from an interplay between general EV-associated properties and cell-specific environment.

biophysics↗

bioRxiv2025

Single-Particle Tracking and Positional Phenotyping Reveals Variant-Specific Early Checkpoints in SARS-CoV-2 Cell Entry

SARS-CoV-2 entry is governed by Spike (S) protein-mediated engagement of ACE2 and subsequent activation of either plasma membrane fusion mediated by TMPRSS2 or endocytic uptake. Currently, most insights into these pathways come from bulk assays that obscure the fate of individual virions, thereby concealing intricate mechanistic details that can inform on therapeutic intervention strategies. Here, we applied single-particle fluorescence imaging to directly observe the early checkpoints of SARS-CoV-2 cell entry pathways and separate binding from internalization. Fluorescent virus-like particles (VLPs) pseudotyped with either G614 or Omicron BA.5 S protein variants were imaged on HEK293T-ACE2 (TMPRSS2-negative) and classified at the single-particle level as surface-interacting, crossing, or internal. At baseline, G614 VLPs show higher binding and a larger internalized share than BA.5 VLPs, revealing general divergence in early entry behavior between variants. A trivalent anti-S receptor-binding domain aptamer reduces G614 binding and lowers its internalization. Conversely, the aptamer does not block BA.5 VLP cell binding but increases its internalization efficiency. Pitstop 2, an inhibitor of clathrin-mediated endocytosis, causes no significant change in this observation window, consistent with early clathrin-sensitive events having already progressed. Quantification of trajectories reveals variant-specific mobility: BA.5 displays higher step length than G614, consistent with greater lateral scanning and surface retention. Together, these compact single-particle readouts expose variant-resolved early checkpoints in entry and provide a simple platform to test how ligands and pathway probes shift binding and internalization.

biophysics↗

bioRxiv2025

Native extracellular vesicles display surface bound RNAs that are co-delivered to cells

Extracellular vesicles (EVs) can transport functional RNA between cells and therefore hold great potential for diagnostics and RNA-based therapeutics. Classically, RNA is believed to be encapsulated in the EV lumen. However, it has recently been demonstrated that cells present RNA on their surface. This RNA was found to be glycosylated, and although glycosylated tRNA was also found in EVs, its exact location remained elusive. Here, we demonstrate the presence of RNA on the surface of mesenchymal stem cell (MSC) derived EVs. By combining single-vesicle measurements with direct and selective visualization of RNA, we introduce surface RNA (surfRNA) as a new inherent component of EVs. RNA sequencing supports the surface localization of this RNA and further identifies tRNA fragments as primary constituent of surfRNA. Importantly, surfRNA is co-delivered to target cells together with EVs, suggesting a yet unrecognized uptake route of extracellular RNA. A deeper understanding of the surface-associated RNA may have significant implications for EV biogenesis, targeting, and downstream functional effects. We further envision that these findings are transferable to other nanoparticles and will thereby advance the field of therapeutic RNA delivery.

molecular biology↗

bioRxiv2025

Dedicated nanoparticle flow cytometry for single extracellular vesicle phenotyping: Performance of the CytoFLEX Nano

Accurate discrimination of extracellular vesicles (EVs) from non-vesicular nanoparticles and robust phenotyping of individual EVs directly within complex biofluids are essential to advance understanding of EV biology and to realize their potential as biomarkers and therapeutic agents. Conventional flow cytometers, originally designed for cellular analysis, lack the scatter and fluorescence sensitivity, dynamic range, and event-rate control required for quantitative characterization of nanoscale vesicles and are particularly susceptible to coincident (swarm) detection. Dedicated nanoparticle flow cytometers have been developed to address these limitations, and here we systematically evaluate the suitability of the CytoFLEX Nano (Beckman Coulter) for EV analysis. Using a series of calibration beads of different materials, fluorescent liposomes, and EVs isolated from peritoneal fluid and cell culture medium, we assess size-detection thresholds, scatter and fluorescence sensitivity, dynamic range, and volumetric counting accuracy. These data provide practical guidance for implementing nanoscale flow cytometry in EV research and support the informed adoption of dedicated nanoparticle cytometers in studies adhering to current EV reporting standards.

cell biology↗

bioRxiv2025

Bacteriophage-Mimetic DNA Origami Needle for Targeted Membrane Penetration and Cytosolic Cargo Delivery

Inspired by the natural ability of bacteriophages to deliver genetic material directly into host cells, we employed a bottom-up approach to construct a multifunctional synthetic DNA origami needle-like structure. This origami is functionalized with trastuzumab antibodies, cholesterol, protective polymers, and two dyes, which together enable selective targeting and insertion into SKBR3 cancer cells. A disulfide-linked dye payload was attached to the apex of the needle, allowing controlled release in the cytoplasm triggered by the high intracellular glutathione concentration. Real-time tracking of the payload confirmed both successful targeting of the origami structure and subsequent direct cytosolic delivery. By mimicking fundamental mechanisms of bacteriophages, we propose that this artificial needle structure can serve as a prototypical device for the targeted delivery of small-molecule drugs directly into the cytosol.

biochemistry↗

bioRxiv2025

Targeting Langerhans cells using a modular mannosylated nucleic acid-based vaccine platform

The skin is a diverse reservoir of immune cells with strong potential for immunotherapeutic delivery. Langerhans cells (LCs) in the epidermis are antigen-presenting cells, accessible for vaccination using carbohydrate-conjugated therapeutics targeting their endocytic lectin receptor, Langerin. As carbohydrate-lectin binding is highly dependent on valency, scaffolds that enable control over ligand spacing and stoichiometry are instrumental in enhancing receptor binding and selectivity. Here we utilized a self-assembled nucleic acid-based Holliday Junction scaffold, fully modified for nuclease protection and with a well-defined carbohydrate arrangement to optimize drug delivery to LCs. In vitro screening with Langerin-expressing cells revealed that mannosylated Holliday Junctions showed the strongest binding. This was confirmed in human epidermal cell suspensions, demonstrating specificity and valency-driven interactions. Topical administration of mannosylated scaffolds on skin explants enabled effective targeting of epidermal LCs. Finally, in an antigen-presentation assay, in vitro differentiated LCs loaded with mannosylated and peptide-conjugated scaffolds significantly enhanced T cell activation. Overall, our study presents a promising nucleic acid-based platform for precise LC targeting and drug delivery, with broad potential for skin-directed immunotherapies.

molecular biology↗

bioRxiv2025

Nanoscale precise stamping of biomolecule patterns using DNA origami

Understanding the importance of ligand patterning in biological processes requires precise control over molecular positioning and spacing. While DNA origami structures offer nanoscale precision in biomolecule arrangement, their biological applications are limited by challenges related to their structural stability, scalability, and surface area. Here, we present a straightforward and rapid DNA origami stamping technique for transferring nanoscale oligonucleotide patterns onto surfaces, visualized using DNA-PAINT super-resolution microscopy to quantitatively assess the stamping efficiency and precision across different stamp types. Unlike traditional top-down methods that require specialized equipment, our technique provides an accessible, self-assembled platform for surface patterning, with versatility across various substrates via modifiable pattern-transfer oligonucleotides. We demonstrate reliable, efficient, and precise pattern transfer at single-molecule resolution, enabling new opportunities to study distance-dependent biological processes, including receptor activation, multivalent binding, and enzymatic cascades across broader spatial scales and different detection techniques. The use of the passivated surface limits non-specific interactions with unpatterned areas and enables control over the interaction between the biological target and the patterned biomolecules. Our method advances surface patterning by combining DNA nanotechnology with single-molecule imaging techniques, expanding access to cost-effective analytical approaches and potentially enabling multiplexed detection and live measurements.

bioengineering↗

bioRxiv2025

Single-vesicle tracking of α-synuclein oligomers reveals pore formation by a three-stage model modulated by charge, curvature, lipids and ligands

Neurodegenerative disorders like Parkinsons disease (PD) pose significant health challenges. A major hallmark is the aggregation of -synuclein into toxic oligomers (SO) and fibrils. While many efforts focus on slowing disease progression, the molecular origins and mechanisms of SO toxicity remain poorly understood, particularly its proposed link to membrane disruption. To address this, we have developed a single-vesicle analysis platform for direct and real-time measurements of SO and membrane interaction. This allows us to show real-time translocation of dyes through SO pores with single-particle resolution and single-channel electrical recordings for analyzing pore formation in planar lipid bilayers. Across methods, our data reveal evidence for a three-stage model for SO and membrane interactions with initial membrane recruitment followed by partial pore insertion and subsequent full pore formation. Strikingly, while SO recruitment was found to favor curved membranes, pore formation occurred more efficiently in less curved membranes, hence recruitment is divorced from a membrane charge-promoted reorientation and pore integration. Single SO pore formations are undergoing multiple translocation steps hence pore formation is highly dynamic cycling back and forth from partial insertion to full pore formation. The dynamic nature of pore formation can be modulated by lipid charge, lipid headgroup class, and ligand binding. Our findings suggest that increased dynamic pore formation could implies increased membrane toxicity. Evidence for the three-stage model is important for future targeting strategies for blocking SO mitigated PD-related cellular dysfunction and we envision the single-vesicle assay enables screening for ligands modulating the pore formation.

biophysics↗

bioRxiv2021

Single particle combinatorial multiplexed liposome fusion mediated by DNA

Combinatorial high throughput methodologies are central for both screening and discovery in synthetic biochemistry and biomedical sciences. They are, however, often reliant on large scale analyses and thus limited by long running time and excessive materials cost. We herein present Single PARticle Combinatorial multiplexed Liposome fusion mediated by DNA (SPARCLD), for the parallelized, multi-step and non-deterministic fusion of individual zeptoliter nanocontainers. We observed directly the efficient (>93%), and leakage free stochastic fusion sequences for arrays of surface tethered target liposomes with six freely diffusing populations of cargo liposomes, each functionalized with individual lipidated ssDNA (LiNA) and fluorescent barcoded by distinct ratio of chromophores. The stochastic fusion results in distinct permutation of fusion sequences for each autonomous nanocontainer. Real-time TIRF imaging allowed the direct observation of >16000 fusions and 566 distinct fusion sequences accurately classified using machine learning. The high-density arrays of surface tethered target nanocontainers [~]42,000 containers per mm2 offers entire combinatorial multiplex screens using only picograms of material.

biophysics↗

bioRxiv2020

DeepFRET: Rapid and automated single molecule FRET data classification using deep learning

Single molecule Forster Resonance energy transfer (smFRET) is a mature and adaptable method for studying the structure of biomolecules and integrating their dynamics into structural biology. The development of high throughput methodologies and the growth of commercial instrumentation have outpaced the development of rapid, standardized, and fully automated methodologies to objectively analyze the wealth of produced data. Here we present DeepFRET, an automated standalone solution based on deep learning, where the only crucial human intervention in transiting from raw microscope images to histogram of biomolecule behavior, is a user-adjustable quality threshold. Integrating all standard features of smFRET analysis, DeepFRET will consequently output common kinetic information metrics for biomolecules. We validated the utility of DeepFRET by performing quantitative analysis on simulated, ground truth, data and real smFRET data. The accuracy of classification by DeepFRET outperformed human operators and current commonly used hard threshold and reached >95% precision accuracy only requiring a fraction of the time (<1% as compared to human operators) on ground truth data. Its flawless and rapid operation on real data demonstrates its wide applicability. This level of classification was achieved without any preprocessing or parameter setting by human operators, demonstrating DeepFRETs capacity to objectively quantify biomolecular dynamics. The provided a standalone executable based on open source code capitalises on the widespread adaptation of machine learning and may contribute to the effort of benchmarking smFRET for structural biology insights.

biophysics↗