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Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment
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Fluorogenic speed-optimized DNA-PAINT probes enable super-resolution imaging of whole cells.

Sylvi Stoller1,2,3, Asmita Jha1, Joerg Bewersdorf1,2,3,4,5,6

  • 1Department of Cell Biology, Yale School of Medicine, New Haven, CT, USA.

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Summary

We developed a new DNA-PAINT probe architecture to overcome limitations in super-resolution microscopy. This modular design improves imaging speed and signal quality, enabling detailed molecular imaging in cells.

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Area of Science:

  • Biophysics
  • Molecular Imaging
  • Nanotechnology

Background:

  • DNA-PAINT super-resolution microscopy offers molecular-scale, multiplexed, and quantitative imaging.
  • Current limitations include slow probe binding kinetics and high background noise, hindering throughput.
  • Existing speed-optimized probes face design constraints due to a binding-quenching tradeoff.

Purpose of the Study:

  • To introduce a novel modular probe architecture for DNA-PAINT.
  • To decouple probe binding kinetics from fluorophore-quencher interactions.
  • To enhance imaging speed, signal-to-background ratio, and overall efficiency.

Main Methods:

  • Designed a modular probe architecture integrating speed-optimized DNA motifs with PEG spacers.
  • Utilized DNA origami nanostructures for probe assembly and characterization.
  • Validated probe performance in cellular imaging of nuclear targets and endoplasmic reticulum.

Main Results:

  • Demonstrated enhanced localization rates and signal-to-background ratios compared to existing probes.
  • Achieved improved imaging efficiency using the new modular probe architecture.
  • Successfully applied the probes for 3D imaging of cellular structures with standard widefield illumination.

Conclusions:

  • The modular probe architecture effectively overcomes key limitations in DNA-PAINT super-resolution microscopy.
  • This approach enables faster, more efficient, and lower-background molecular imaging.
  • The developed framework supports advanced multiplexed and 3D super-resolution imaging applications.