Protocol for open-source automated universal high-content multiplex fluorescence for RNA in situ analysis

Jean Descarpentrie; Florian Bernard; Wilfried Souleyreau; Lucie Brisson; Thomas Mathivet; Ioannis S Pateras; Océane C B Martin; Maria Lopez Chiloeches; Teresa Frisan

doi:10.1016/j.xpro.2024.103508

Protocol for open-source automated universal high-content multiplex fluorescence for RNA in situ analysis

STAR Protoc. 2024 Dec 20;5(4):103508. doi: 10.1016/j.xpro.2024.103508. Epub 2024 Dec 6.

Authors

Jean Descarpentrie¹, Florian Bernard², Wilfried Souleyreau³, Lucie Brisson³, Thomas Mathivet³, Ioannis S Pateras⁴, Océane C B Martin⁵, Maria Lopez Chiloeches⁶, Teresa Frisan⁷

Affiliations

¹ Department of Molecular Biology, 90187 Umeå, Sweden; Umeå Centre for Microbial Research (UCMR), Umeå University, 90187 Umeå, Sweden. Electronic address: [email protected].
² University of Bordeaux, INSERM, U1212, Nucleic Acids: Natural and Artificial Regulations Laboratory, 33000 Bordeaux, France.
³ University of Bordeaux, INSERM, U1312 BRIC, Tumor and Vascular Biology Laboratory, 33000 Bordeaux, France.
⁴ 2nd Department of Pathology, "Attikon" University Hospital, Medical School, National and Kapodistrian University of Athens, 124 62 Athens, Greece.
⁵ University of Bordeaux, CNRS, IBGC, UMR 5095, 33000 Bordeaux, France.
⁶ Department of Molecular Biology, 90187 Umeå, Sweden; Umeå Centre for Microbial Research (UCMR), Umeå University, 90187 Umeå, Sweden.
⁷ Department of Molecular Biology, 90187 Umeå, Sweden; Umeå Centre for Microbial Research (UCMR), Umeå University, 90187 Umeå, Sweden. Electronic address: [email protected].

Abstract

In situ hybridization visualizes RNA in cells, but image analysis is complex. We present a protocol based on open-source software for automated high-content multiplex fluorescence in situ transcriptomics analysis. Steps include nuclei segmentation with a Fiji macro and quantification of up to 14 mRNA probes per image. We describe procedures for storing raw data, quality control images, and the use of a Python app to summarize all the results in one spreadsheet detailing the number of single or co-positive cells.

Keywords: cell biology; health sciences; in situ hybridization.

MeSH terms

Humans
Image Processing, Computer-Assisted / methods
In Situ Hybridization, Fluorescence* / methods
RNA* / analysis
RNA* / genetics
Software*

Substances

RNA