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Researchers developed a screening platform to optimize DNA-PAINT super-resolution imaging for use in Gram-negative bacteria, addressing the technique's limited adoption in bacterial studies. Using an RNA-FISH-based approach targeting 16S rRNA in E. coli, they systematically tested 12 different DNA sequences to identify optimal imager-docking pairs for imaging inside intact bacterial cells. The optimized sequences enabled four-target 3D multiplexed imaging in E. coli and successful visualization and quantification of three mRNA species in the pathogen Yersinia enterocolitica.
Why it matters
This work removes a major technical barrier to studying nanoscale structures in bacteria by providing practical protocols for DNA-PAINT imaging in organisms with challenging cellular environments. The method enables researchers to visualize multiple molecular targets simultaneously at super-resolution in bacterial pathogens, which could advance understanding of bacterial gene expression, cellular organization, and infection mechanisms.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
DNA-PAINT enables super-resolution imaging with high multiplexing capacity, yet it is rarely used in nanoscale bacteriology. A likely reason is the lack of straightforward protocols and of systematic characterization of imager-docking strand pairs inside intact bacterial cells, whose envelope and dense cytoplasm differ markedly from both the DNA origami in vitro systems used to develop them, and eukaryotic cells. In this work, we establish a screening platform based on RNA-FISH, in which we extend the 16S rRNA-directed EUB338 probe with docking sequences of choice. This allows imager-docking pairs to be benchmarked directly inside Escherichia coli cells and characterized for parameters such as specificity, binding kinetics, and localization precision. We screened 12 different DNA-PAINT sequences and used an optimized set to perform four-target 3D Exchange-PAINT in single E. coli cells. We further applied our strategy to image three effector mRNAs in the Gram-negative pathogen Yersinia enterocolitica and quantified RNA clusters and their 3D distribution. Our work provides a framework and practical guidelines for high-quality 3D DNA-PAINT imaging in Gram-negative bacteria and should facilitate its broader adoption in nanoscale bacteriology.