Reinhardt, S. C. | Search bioRxiv

bioRxiv2026

Combinatorial DNA-PAINT

State-of-the-art super-resolution microscopy enables nanometer-resolution imaging of proteins, but its multiplexing capacity has been fundamentally constrained. Here, we present Combi-PAINT, a combinatorial DNA barcoding strategy based on DNA-PAINT, that facilitates superlinear scaling of multiplexing with the number of imaging rounds. Instead of assigning one unique docking strand per target, Combi-PAINT encodes targets as combinations of orthogonal sequences, allowing nonlinear scaling of target number with imaging rounds. Using just six imaging rounds, we resolve 41 targets in a field-of-view of 100 x 100 m2 with [~]2.5 nm localization precision and [~]90% decoding accuracy in under 30 minutes, representing the fastest sub-10 nm super-resolution microscopy acquisition to date. We benchmark decoding fidelity and demonstrate robust in situ performance in mammalian cells, achieving 97% decoding accuracy. Combi-PAINT is compatible with existing DNA-PAINT workflows and speed-enhancing techniques, offering a scalable, accessible platform for high-content, single-molecule spatial proteomics.

biophysics↗

bioRxiv2023

Spatial proteomics in neurons at single-protein resolution

To fully understand biological processes and functions, it is necessary to reveal the molecular heterogeneity of cells and even subcellular assemblies by gaining access to the location and interaction of all biomolecules. The study of protein arrangements has seen significant advancements through super-resolution microscopy, but such methods are still far from reaching the multiplexing capacity of spatial proteomics. Here, we introduce Secondary label-based Unlimited Multiplexed DNA-PAINT (SUM-PAINT), a high-throughput imaging method capable of achieving virtually unlimited multiplexing at better than 15 nm spatial resolution. Using SUM-PAINT, we generated the most extensive multiprotein dataset to date at single-protein spatial resolution, comprising up to 30 distinct protein targets in parallel and adapted omics-inspired analysis workflows to explore these feature-rich datasets. Remarkably, by examining the multiplexed protein content of almost 900 individual synapses at single-protein resolution, we revealed the complexity of synaptic heterogeneity, ultimately leading to the discovery of a new synapse type. This work provides not only a feature-rich resource for researchers, but also an integrated data acquisition and analysis workflow for comprehensive spatial proteomics at single-protein resolution, paving the way for Localizomics.

neuroscience↗