Biology subjects

Kaminer, A.

Publications and source records attributed to Kaminer, A..

3 recordsLinked to original sources

bioRxiv2026

Quantitative mapping of nanoscale EGFR-Grb2 assemblies by DNA-PAINT

Receptor tyrosine kinase signaling is initiated by extracellular ligand binding, which drives the formation of membrane-protein assemblies that activate intracellular signal transduction. Accurately resolving the molecular composition of these assemblies in situ remains challenging due to their nanoscale dimensions and intrinsic heterogeneity. Here, we introduce a single-molecule super-resolution imaging and analysis workflow designed to resolve and quantitatively characterize individual membrane-protein assembly sites in cells. We apply this approach to the nanoscale organization of the epidermal growth factor receptor (EGFR) and its adaptor protein Grb2 following stimulation with the native ligand epidermal growth factor (EGF). As activation progresses, we observe a reduction in EGFR density at the plasma membrane, a progressive accumulation of Grb2 at EGFR assembly sites, and an increase in both dimeric and higher-order oligomeric EGFR. The experimental and analytical framework presented here is broadly applicable to the study of diverse membrane-protein assemblies.

biophysics↗

bioRxiv2025

Nanoscale spatial-omics via contrastive embedding of single-molecule localisation data

Omics approaches have revolutionised biology, and cells can now be routinely characterised on the genomic, transcriptomic and proteomic levels. However, there is an additional pillar; the (nanoscale) spatial organisation of molecules in the cell - information now accessible through super-resolution microscopy. We present a contrastive learning framework for nanoscale spatial-omics that embeds single-molecule localisation microscopy data into a latent space representing protein architecture directly to enabling comparative analysis. Using simulated and experimental data, we demonstrate its ability to enable new bioanalysis capabilities including assessing changes to cellular nanoscale architecture arising from pharmacological treatments, cell type, fluorophore selection or data-processing workflows. The approach supports downstream tasks such as clustering proteins by nanoscale organisation, mapping dose-response trajectories and identifying batch effects in replicate datasets, establishing contrastive learning as a scalable foundation for nanoscale spatial-omics and providing a platform for comparative phenotyping, quality control, and hypothesis generation.

bioinformatics↗

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↗