Biology subjects

Rahm, J. V.

Publications and source records attributed to Rahm, J. V..

6 recordsLinked to original sources

bioRxiv2024

Localization of Albumin with Correlative Super Resolution Light- and Electron Microscopy in the Kidney

The functioning of vertebrate life relies on renal filtration of surplus fluid and elimination of low-molecular-weight waste products, while keeping serum proteins in the blood. In disease, however, there is leak of serum proteins and tracing them to identify the leaking position within tissue with a nanometer resolution poses a significant challenge. Correlative microscopy integrates the specificity of fluorescent protein labeling into high-resolution electron micrographs. Using chemical tagging of albumin with synthetic fluorophores we achieve protein-specific labeling that preserve their post-embedding fluorescence after high-pressure freezing and freeze-substitution of murine kidney tissue. Using advanced registration techniques for super-resolution correlative light and electron microscopy, we can localize the labeled albumin with a high precision in the x-y plane of electron micrographs and cartograph its distribution. Thereby we can quantify the albumin concentration and measure a linear reduction gradient across the kidney filtration barrier. Our study shows the feasibility of combining different microscopy contrasts for tracing fluorescently labeled protein markers with super resolution in various tissue samples and opens new perspectives for correlative imaging in volume electron microscopy.

biophysics↗

bioRxiv2024

Fast and long-term super-resolution imaging of ER nano-structural dynamics in living cells using a neural network

Stimulated emission depletion (STED) microscopy is a super-resolution technique that surpasses the diffraction limit and has contributed to the study of dynamic processes in living cells. However, high laser intensities induce fluorophore photobleaching and sample phototoxicity, limiting the number of fluorescence images obtainable from a living cell. Here, we address these challenges by using ultra-low irradiation intensities and a neural network for image restoration, enabling extensive imaging of single living cells. The endoplasmic reticulum (ER) was chosen as the target structure due to its dynamic nature over short and long timescales. The reduced irradiation intensity combined with denoising permitted continuous ER dynamics observation in living cells for up to 7 hours with a temporal resolution of seconds. This allowed for quantitative analysis of ER structural features over short (seconds) and long (hours) timescales within the same cell, and enabled fast 3D live-cell STED microscopy. Overall, the combination of ultra-low irradiation with image restoration enables comprehensive analysis of organelle dynamics over extended periods in living cells.

biophysics↗

bioRxiv2024

Robust virtual staining of landmark organelles

Correlative dynamic imaging of cellular landmarks, such as nuclei and nucleoli, cell membranes, nuclear envelope and lipid droplets is critical for systems cell biology and drug discovery, but challenging to achieve with molecular labels. Virtual staining of label-free images with deep neural networks is an emerging solution for correlative dynamic imaging. Multiplexed imaging of cellular landmarks from scattered light and subsequent demultiplexing with virtual staining leaves the light spectrum for imaging additional molecular reporters, photomanipulation, or other tasks. Current approaches for virtual staining of landmark organelles are fragile in the presence of nuisance variations in imaging, culture conditions, and cell types. We report training protocols for virtual staining of nuclei and membranes robust to variations in imaging parameters, cell states, and cell types. We describe a flexible and scalable convolutional architecture, UNeXt2, for supervised training and self-supervised pre-training. The strategies we report here enable robust virtual staining of nuclei and cell membranes in multiple cell types, including human cell lines, neuromasts of zebrafish and stem cell (iPSC)-derived neurons, across a range of imaging conditions. We assess the models by comparing the intensity, segmentations, and application-specific measurements obtained from virtually stained and experimentally stained nuclei and cell membranes. The models rescue missing labels, non-uniform expression of labels, and photobleaching. We share three pre-trained models (VSCyto3D, VSNeuromast, and VSCyto2D) and a PyTorch-based pipeline (VisCy) for training, inference, and deployment that leverages current community standards for image data and metadata.

bioinformatics↗

bioRxiv2023

The molecular architecture of the kidney slit diaphragm

Vertebrate life depends on renal function to filter excess fluid and remove low-molecular-weight waste products. An essential component of the kidney filtration barrier is the slit diaphragm (SD), a specialized cell-cell junction between podocytes. Although the constituents of the SD are largely known, its molecular organization remains elusive. Here, we use super-resolution correlative light and electron microscopy to quantify a linear rate of reduction in albumin concentration across the filtration barrier. Next, we use cryo-electron tomography of vitreous lamellae from high-pressure frozen native glomeruli to analyze the molecular architecture of the SD. The resulting densities resemble a fishnet pattern. Fitting of Nephrin and Neph1, the main constituents of the SD, results in a complex interaction pattern with multiple contact sites between the molecules. Using molecular dynamics flexible fitting, we construct a blueprint of the SD, where we describe all interactions. Our architectural understanding of the SD reconciles previous findings and provides a mechanistic framework for the development of novel therapies to treat kidney dysfunction.

cell biology↗

bioRxiv2022

Biased activation of the receptor tyrosine kinase HER2

HER2 belongs to the ErbB sub-family of receptor tyrosine kinases and regulates cellular proliferation and growth. Different from other ErbB receptors, HER2 has no known ligand. Activation occurs through heterodimerization with other ErbB receptors and their cognate ligands. This suggests several possible activation paths of HER2 with ligand-specific, differential response, which so far remained unexplored. Using single-molecule tracking and the diffusion profile of HER2 as a proxy for activity, we measured the activation strength and temporal profile in live cells. We found that HER2 is strongly activated by EGFR-targeting ligands EGF and TGF, yet with a distinguishable temporal fingerprint. The HER4-targeting ligands EREG and NRG{beta}1 showed weaker activation of HER2, a preference for EREG, and a delayed response to NRG{beta}1. Our results indicate a selective ligand response of HER2 that may serve as a regulatory element. Our experimental approach is easily transferable to other membrane receptors targeted by multiple ligands. HighlightsO_LIHER2 exhibits heterogeneous motion in the plasma membrane C_LIO_LIThe fraction of immobile HER2 correlates with phosphorylation levels C_LIO_LIDiffusion properties serve as proxies for HER2 activation C_LIO_LIHER2 exhibits ligand-specific activation strength and temporal profiles C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/519064v2_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@172415eorg.highwire.dtl.DTLVardef@21bf95org.highwire.dtl.DTLVardef@1a907aforg.highwire.dtl.DTLVardef@37a85a_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2021

Fast DNA-PAINT imaging using a deep neural network

DNA points accumulation for imaging in nanoscale topography (DNA-PAINT) is a super-resolution technique with relatively easy-to-implement multi-target imaging. However, image acquisition is slow as sufficient statistical data has to be generated from spatio-temporally isolated single emitters. Here, we trained the neural network (NN) DeepSTORM to predict fluorophore positions from high emitter density DNA-PAINT data. This achieves image acquisition in one minute. We demonstrate multi-color super-resolution imaging of structure-conserved semi-thin neuronal tissue and imaging of large samples. This improvement can be integrated into any single-molecule microscope and enables fast single-molecule super-resolution microscopy.

biophysics↗