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Structured Illumination Microscopy Improves Spot Detection Performance in Spatial Transcriptomics.

Alejandro Linares1, Carlo Brighi2, Sergio Espinola1

  • 1Epigenetics and Neurobiology Unit, European Molecular Biology Laboratory, 00015 Rome, Italy.

Cells
|May 13, 2023
PubMed
Summary

Structured illumination microscopy (SIM) enhances gene transcript spot detection in spatial transcriptomics. This super-resolution technique improves data quality by increasing the efficiency of visualizing single-gene transcripts within tissues.

Keywords:
deconvolution microscopygene expressionin situ sequencingspatial transcriptomicsstructured illuminationsuper-resolution

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Area of Science:

  • Molecular Biology
  • Microscopy
  • Genomics

Background:

  • Spatial biology analyzes cellular and molecular data within tissue context.
  • Imaging-based spatial transcriptomics uses microscopy for in situ gene expression analysis.
  • Light diffraction limits the resolution and detection of genes in traditional microscopy.

Purpose of the Study:

  • To evaluate the impact of structured illumination microscopy (SIM) on single-gene transcript detection in spatial transcriptomics.
  • To compare SIM performance against widefield and confocal microscopy for transcript localization.
  • To determine how objective magnification and spot density influence SIM's effectiveness.

Main Methods:

  • Direct mRNA-targeted hybridization in situ sequencing was employed.
  • Experiments were conducted on mouse coronal brain tissue sections.
  • Spot detection was assessed using widefield, confocal, and SIM imaging with 20×, 25×, and 60× objectives.

Main Results:

  • SIM generally increased the detection efficiency of gene transcript spots compared to widefield and confocal modes.
  • The fold increase in detected spots varied with gene transcript density and objective numerical aperture.
  • Higher numerical apertures were particularly beneficial for resolving densely clustered transcripts.

Conclusions:

  • Structured illumination microscopy significantly improves spot detection in spatial transcriptomics.
  • SIM enhances the overall data quality for transcriptomic profiling in situ.
  • SIM offers a valuable approach to overcome resolution limitations in spatial transcriptomics.