Deep learning-based spectroscopic single-molecule localization microscopy

Sunil Kumar Gaire*, Ali Daneshkhah, Ethan Flowerday, Ruyi Gong, Jane Frederick, Vadim Backman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Significance: Spectroscopic single-molecule localization microscopy (sSMLM) takes advantage of nanoscopy and spectroscopy, enabling sub-10 nm resolution as well as simultaneous multicolor imaging of multi-labeled samples. Reconstruction of raw sSMLM data using deep learning is a promising approach for visualizing the subcellular structures at the nanoscale. Aim: Develop a novel computational approach leveraging deep learning to reconstruct both label-free and fluorescence-labeled sSMLM imaging data. Approach: We developed a two-network-model based deep learning algorithm, termed DsSMLM, to reconstruct sSMLM data. The effectiveness of DsSMLM was assessed by conducting imaging experiments on diverse samples, including label-free single-stranded DNA (ssDNA) fiber, fluorescence-labeled histone markers on COS-7 and U2OS cells, and simultaneous multicolor imaging of synthetic DNA origami nanoruler. Results: For label-free imaging, a spatial resolution of 6.22 nm was achieved on ssDNA fiber; for fluorescence-labeled imaging, DsSMLM revealed the distribution of chromatin-rich and chromatin-poor regions defined by histone markers on the cell nucleus and also offered simultaneous multicolor imaging of nanoruler samples, distinguishing two dyes labeled in three emitting points with a separation distance of 40 nm. With DsSMLM, we observed enhanced spectral profiles with 8.8% higher localization detection for single-color imaging and up to 5.05% higher localization detection for simultaneous two-color imaging. Conclusions: We demonstrate the feasibility of deep learning-based reconstruction for sSMLM imaging applicable to label-free and fluorescence-labeled sSMLM imaging data. We anticipate our technique will be a valuable tool for high-quality superresolution imaging for a deeper understanding of DNA molecules’ photophysics and will facilitate the investigation of multiple nanoscopic cellular structures and their interactions.

Original languageEnglish (US)
Article number066501
JournalJournal of Biomedical Optics
Volume29
Issue number6
DOIs
StatePublished - Jun 1 2024
Externally publishedYes

Keywords

  • deep-learning
  • label-free
  • nanoscopy
  • simultaneous multicolor imaging
  • single-molecule localization microscopy
  • spectroscopic single-molecule localization microscopy
  • spectroscopy
  • super-resolution microscopy

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Biomedical Engineering

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