Philipp Steen

Excellent work, check it out!

Here’s their paper: biorxiv.org/content/10.64898/2026.01.23.701081v1
And our work: biorxiv.org/content/10.64898/2026.01.23.701249v1
Many thanks to @jungmannlab.bsky.social, all the co-authors and everyone who partook in this project!
5/5

Bonus:
We’re not the only ones to come up with an idea like this – @fbzt.bsky.social has developed a closely related technique, so we’re extra confident about applicability and reproducibility!
4/5

Key achievements:
• 41 targets in just 6 rounds.
• <30 min total acquisition time for FOVs over 100×100 µm².
• ~2.5 nm localization precision.
• ~up to 97% decoding accuracy in intact cells.
Dive into nanoscale spatial proteomics with standard DNA-PAINT reagents!
3/5

Core Idea:
Targets are not labeled with one unique docking strand.
Instead, each target is encoded by a combination of orthogonal docking motifs.
Each imaging round reads out one motif → identities are decoded combinatorially.
Thus: non-linear scaling of target number with imaging rounds!
2/5

How do you scale super-resolution microscopy to dozens of proteins without linearly scaling imaging time?
We introduce Combi-PAINT: a combinatorial DNA-PAINT strategy that breaks the 1-target-per-round bottleneck of Exchange-PAINT: www.biorxiv.org/content/10.6...
1/5

Pretty images are one thing, but quantitative analysis of your super-resolution data is key! Check out our new paper where we introduce a method to investigate protein oligomerization and spatial patterns!