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Brauburger, S.

Publications and source records attributed to Brauburger, S..

2 recordsLinked to original sources

Volume and surface methods for microparticle traction force microscopy: a computational and experimental comparison

It is an essential element of mechanobiology to measure the forces of biological cells. In microparticle traction force microscopy, they are inferred from the deformation of elastic microparticles. Two complementary variants have been introduced before: the volume method, which reconstructs surface stresses from the displacements of fiducial markers embedded inside the particles, and the surface method, which infers stresses directly from the deformation of the particle surface. However, a systematic comparison of the two methods has been lacking. Here, we quantitatively compare both approaches using simulated traction fields representing biologically relevant loading scenarios. We find that the surface method consistently reconstructs traction profiles with substantially lower errors than the volume method, which suffers from displacement tracking and stress calculation at the surface. At high noise levels, however, the performance gap becomes smaller. To compare the performance of the two methods in a realistic experimental setting, we developed DNA-based hydrogel microparticles equipped with both fluorescent surface labels and embedded fluorescent nanoparticles, enabling the direct comparison of the two methods within the same system. Compression experiments produced traction profiles consistent with Hertzian contact mechanics and confirmed the trends observed in the simulations. We also show that despite large experimental deformations and strains (both up to 20 percent), linear elasticity theory should still be valid. While our computational workflow establishes a framework to apply both methods, our experimental workflow establishes DNA microparticles as versatile and biocompatible probes for measuring cellular forces.

biophysics↗

One pot RNA:DNA assembly for ribosomal RNA detection of pathogenic bacteria with single-molecule sensitivity

Ribosomal RNAs (rRNAs) serve as species-defining markers and undergo processing steps such as excision of intervening sequences (IVSs). Direct analysis of native rRNAs is hampered by amplification-induced biases and by the high conservation of rRNA sequences, which complicates discrimination of closely related variants. Here, we present modular RNA:DNA nanostructures that enable direct, amplification-free identification of rRNAs and their variants. The approach employs rationally designed RNA:DNA duplexes, named RNA identifiers (IDs), assembled onto native rRNAs via short complementary oligonucleotides bearing programmable coding motifs. We demonstrate that native bacterial 16S rRNAs can be directly converted into RNA IDs and detected with solid-state nanopores. Having established direct rRNA readout, we next show that biologically encoded rRNA processing states, including serovar-specific 23S rRNA fragmentation patterns arising from IVS excision, are resolved using RNA IDs. Finally, to extend discrimination beyond processing-level differences, we incorporate catalytically inactive Cas9 ribonucleoprotein complexes to enable single-nucleotide discrimination of rRNA variants. Our modular RNA ID-nanopore system facilitates studying rRNA processing and rRNA diversity.

biophysics↗