Preprint Communication Version 1 Preserved in Portico This version is not peer-reviewed

Structured Illumination Microscopy Improves Spot Detection Performance in Spatial Transcriptomics

Version 1 : Received: 28 February 2023 / Approved: 2 March 2023 / Online: 2 March 2023 (10:42:14 CET)

A peer-reviewed article of this Preprint also exists.

Linares, A.; Brighi, C.; Espinola, S.; Bacchi, F.; Crevenna, Á.H. Structured Illumination Microscopy Improves Spot Detection Performance in Spatial Transcriptomics. Cells 2023, 12, 1310. Linares, A.; Brighi, C.; Espinola, S.; Bacchi, F.; Crevenna, Á.H. Structured Illumination Microscopy Improves Spot Detection Performance in Spatial Transcriptomics. Cells 2023, 12, 1310.

Abstract

Spatial biology is a rapidly growing research field which focuses on the transcriptomic or proteomic profiling of single cells within tissues with preserved spatial information. Imaging-based spatial transcriptomics uses epifluorescence microscopy, which has shown remarkable results for identification of multiple targets in situ. Nonetheless, the number of genes that can be reliably visualized is limited by the diffraction of light. Here, we investigate the effect of structured illumination (SIM), a super-resolution microscopy approach, over the performance of single gene transcript detection in spatial transcriptomics experiments. We performed direct mRNA-targeted hybridization in situ sequencing for multiple genes in mouse coronal brain tissue sections. We evaluated spot detection performance in widefield and confocal images versus those with SIM in combination with 20X, 25X and 60X objectives. In general, SIM increases the detection efficiency of gene transcripts spots compared to widefield and confocal modes. For each case, the specific fold increase in localizations is dependent on gene transcripts density and the numerical aperture of the objective used, which showed to play an important role especially for densely clustered spots. Taken together, our results suggest that SIM has the capacity to improve spot detection and overall data quality in spatial transcriptomics.

Keywords

Structured illumination; Spatial transcriptomics; Super-resolution; Gene expression; In situ sequencing; Deconvolution microscopy

Subject

Biology and Life Sciences, Biophysics

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