Mike Heilemann

The paper identifies cell-envelope conduits in Acinetobacter baumannii that enable direct transfer of large chromosomal DNA segments between cells.

This study uses DNA-PAINT to quantitatively map nanoscale EGFR-Grb2 assemblies in cells after EGF stimulation, revealing changes in EGFR density and Grb2 accumulation.

This paper introduces a wash-free method for multi-target super-resolution microscopy using photocaged DNA labels, demonstrating improved imaging accuracy without sample manipulation.

The paper uses single-molecule FRET and tracking to study MET receptor activation by InlB in living cells, finding a dimeric complex lifetime of ~1 second and slower diffusion for dimers.

This paper introduces a method for quantitative STED microscopy using DNA-fluorophore labels to enable molecule counting in biological samples.

The paper uses smart 3D super-resolution microscopy to study the RNA scaffold structure in paraspeckles, revealing new insights into their 3D organization and growth.

Glyco-STORM maps nanoscale glycosylation patterns in cells, revealing subcellular glycan domains and a spatial glycosylation code.

This paper introduces a contrastive learning framework for nanoscale spatial-omics, enabling analysis of single-molecule localisation data to study protein architecture and its changes under various conditions.

This study shows SRSF5 is critical for paraspeckle assembly and dynamics, with stress-induced changes and compensatory effects on TDP-43 and NEAT1.

This paper introduces Rho-tag and SiR-tag, fast, reversible, and fluorogenic protein tags for live-cell imaging, compatible with super-resolution techniques and demonstrated in zebrafish larvae.

The paper introduces AutoDS and AutoDS3D, deep learning tools for single-molecule super-resolution microscopy that reduce manual intervention and computation time.

This paper introduces a labeling method for long-term single-molecule tracking in living cells and demonstrates its application to study EGFR dynamics.

This paper enables long-term super-resolution imaging of ER dynamics in living cells using low irradiation and neural network-based image restoration.

This study localizes albumin in kidney tissue using correlative super-resolution light and electron microscopy to map its distribution and quantify concentration gradients across the filtration barrier.

The paper introduces self-quenched fluorophore-DNA labels to reduce background signal in super-resolution microscopy, improving imaging performance in STED and SMLM.

This paper introduces an unbiased clustering algorithm for single-molecule localization microscopy that reduces false positives and negatives compared to existing methods.

The paper quantifies the spatial scale of synaptic protein allocation during homeostatic plasticity and finds that proteins are distributed at the level of synaptic neighborhoods.

ZeroCostDL4Mic provides a platform to use deep learning in microscopy, enabling tasks like segmentation and denoising through Google Colab.

The paper introduces maS3TORM, a method for highly multiplexed 3D super-resolution imaging of proteins in cells and tissues, achieving sub-10 nm localization precision for up to 16 targets.