Biology subjects

Helmerich, D.

Publications and source records attributed to Helmerich, D..

5 recordsLinked to original sources

bioRxiv2026

Programmable protein reference standards for benchmarking sub-10-nm fluorescence microscopy

Fluorescence microscopy is increasingly used to measure molecular organization at length scales where labeling, photophysics and sample preparation can dominate quantitative accuracy. Reference standards are therefore needed that combine defined nanoscale geometry with a protein-like environment and compatibility with biological imaging. Here we introduce circular tandem repeat protein as programmable protein standards for benchmarking sub-10-nm fluorescence microscopy. Using genetic code expansion and bioorthogonal labeling, we generated compact protein rings carrying up to six labeling sites. Photoswitching fingerprint analysis revealed geometry-dependent localization accumulation and blinking kinetics, demonstrating that short-range fluorophore interactions can be assessed as measurable benchmark parameters. DNA-PAINT confirmed accessible docking sites and programmed valency at the single-particle level. We further established recombinant tethering and genetically encoded membrane display, extending the standards to cellular environments. cTRP PicoRulers were also compatible with expansion microscopy. Together, cTRPs provide a modular protein-based platform for evaluating molecular-scale imaging performance in purified and cellular environments.

biophysics↗

bioRxiv2025

Towards improved particle averaging for single-molecule localization microscopy using geometric deep learning

Single-molecule localization microscopy (SMLM) can resolve intracellular structures down to the nanoscale, but often produces sparse and incomplete data. Particle averaging (PA) can aid with the reconstruction of complete structures, but traditional PA methods can suffer from template bias or the high computational costs of geometric alignment. To address these limitations, we developed a geometric deep learning (GDL) framework for enhanced, template-free 3D particle averaging. Our pipeline uses a GDL autoencoder, trained on realistic simulated data, to map incomplete point clouds into a robust latent space. By averaging feature vectors directly within this space, our method bypasses the need for explicit 3D alignment. We validated our approach on simulated DNA origami and experimental nuclear pore complex (NPC) data. The latent space averaging successfully reconstructed NPC structures with key metrics (ring radius {approx} 46 nm, ring distance {approx} 52 nm) that are comparable to state-of-the-art methods. This work establishes a viable GDL pipeline for SMLM analysis, offering an efficient alternative to traditional PA. While the current model requires structure-specific training, our results highlight the significant potential of GDL for quantitative structural biology.

bioinformatics↗

bioRxiv2024

Traction Force Microscopy with DNA FluoroCubes

Mechanical forces at the cell-substrate interface govern processes from migration to differentiation, yet mapping these forces at high spatial resolution remains challenging. Traction force microscopy (TFM) addresses this by quantifying substrate deformations using fiducial markers, which are conventionally fluorescent beads. Here, we introduce fluorescently labeled DNA nanostructures (FluoroCubes) as alternative fiducials grafted onto polydimethylsiloxane (PDMS) substrates. Co-anchored with RGD peptides, FluoroCubes remain stably tethered, resist internalization, and enable dense, minimally perturbing labeling. This surface-functionalized platform is compatible with TIRF microscopy and leverages tunable biotin-NeutrAvidin chemistry for precise control of fiducial density. Using a modified multi-channel optical flow algorithm, we achieve improved displacement sensitivity and force reconstruction resolution compared to conventional algorithms. FluoroCube-functionalized substrates provide a reproducible, high-resolution method for traction force mapping and offer a versatile foundation for future integration with DNA-based molecular sensors to probe interfacial forces at biointerfaces.

biophysics↗

bioRxiv2020

Confocal Laser-Scanning Fluorescence-Lifetime Single-Molecule Localisation Microscopy

Fluorescence lifetime imaging microscopy (FLIM) is an important technique that adds another dimension to the intensity and colour information of conventional microscopy. In particular, it allows for multiplexing fluorescent labels that have otherwise similar spectral properties. Currently, the only super-resolution technique that is capable of recording super-resolved images with lifetime information is STimulated Emission Depletion (STED) microscopy. In contrast, all Single-Molecule Localisation Microscopy (SMLM) techniques that employ wide-field cameras completely lack the lifetime dimension. Here, we combine Fluorescence-Lifetime Confocal Laser-Scanning Microscopy (FL-CLSM) with SMLM for realising single-molecule localisation-based fluorescence-lifetime super-resolution imaging (FL-SMLM). Besides yielding images with a spatial resolution much beyond the diffraction limit, it determines the fluorescence lifetime of all localised molecules. We validate our technique by applying it to direct STochastic Optical Reconstruction Microscopy (dSTORM) and Points Accumulation for Imaging in Nanoscale Topography (PAINT) imaging of fixed cells, and we demonstrate its multiplexing capability on samples with two different labels that differ only by fluorescence lifetime but not by their spectral properties.

biophysics↗

bioRxiv2019

Unraveling nanotopography of cell surface receptors

Cells communicate with their environment via surface receptors, but nanoscopic receptor organization with respect to complex cell surface morphology remains unclear. This is mainly due to a lack of accessible, robust and high-resolution methods. Here, we present an approach for mapping the topography of receptors at the cell surface with nanometer precision. The method involves coating glass coverslips with glycine, which preserves the fine membrane morphology while allowing immobilized cells to be positioned close to the optical surface. We developed an advanced and simplified algorithm for the analysis of single-molecule localization data acquired in a biplane detection scheme. These advancements enable direct and quantitative mapping of protein distribution on ruffled plasma membranes with near isotropic 3D nanometer resolution. As demonstrated successfully for CD4 and CD45 receptors, the described workflow is a straightforward quantitative technique to study molecules and their interactions at the complex surface nanomorphology of differentiated metazoan cells.

cell biology↗