2025/05/21 by Maximilian Kloppe, Stefan J. Maurer, Kloppe, Maximilian +7
Biochemistry, Genetics and Molecular Biology · Physics and Astronomy · #Biological Physics (physics.bio-ph) #Cellular Mechanics and Interactions #FOS: Physical sciences #Force Microscopy Techniques and Applications #Lipid Membrane Structure and Behavior #Soft Condensed Matter (cond-mat.soft)
paper · pdf · doi:10.48550/arxiv.2505.15341
openalex publication_date 2025/05/21 · openalex created_date 2025/10/19 · openalex updated_date 2026/07/28
Real-time deformability cytometry (RT-DC) enables high-throughput, contact-free mechanical characterization of soft microscopic objects. Here we apply this technique to giant unilamellar vesicles (GUVs). To interpret vesicle deformation in RT-DC, we present a simulation-based model taking into account the area expansion modulus as the dominant mechanical parameter. Using phase-field simulations over a wide parameter space, we find GUV deformation to depend linearly on GUV area. Based on these results, we derive two complementary fitting strategies for extracting the area expansion modulus K from RT-DC data: a direct model-based fit for single-vesicle characterization and a noise-resistant collective approach that enables robust population-level estimates. Furthermore, we introduce a combined fitting method that integrates both approaches to filter outliers and improve accuracy in heterogeneous or noisy datasets. All methods scale across varying flow rates, channel geometries and buffer viscosities, and produce predictions of K consistent with literature values for different lipid compositions. Compared to traditional techniques such as micropipette aspiration, our approach offers orders of magnitude higher throughput without mechanical contact, making it particularly suitable for GUV population studies. Beyond mechanical phenotyping, this framework opens new avenues for sorting vesicle populations based on membrane mechanics, a capability of growing interest in synthetic biology and soft matter research.