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Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics

Authors :
François Rivest
Deniz Eroglu
Benjamin Pelz
Joanna Kowal
Alexandre Kehren
Vytautas Navikas
Maria Giuseppina Procopio
Pino Bordignon
Emilie Pérès
Marco Ammann
Emmanuel Dorel
Sylvain Scalmazzi
Lorenzo Bruno
Matthieu Ruegg
Gabriel Campargue
Gilles Casqueiro
Lionel Arn
Jérôme Fischer
Saska Brajkovic
Pierre Joris
Marco Cassano
Diego Dupouy
Source :
Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

Abstract Tissues are complex environments where different cell types are in constant interaction with each other and with non-cellular components. Preserving the spatial context during proteomics analyses of tissue samples has become an important objective for different applications, one of the most important being the investigation of the tumor microenvironment. Here, we describe a multiplexed protein biomarker detection method on the COMET instrument, coined sequential ImmunoFluorescence (seqIF). The fully automated method uses successive applications of antibody incubation and elution, and in-situ imaging enabled by an integrated microscope and a microfluidic chip that provides optimized optical access to the sample. We show seqIF data on different sample types such as tumor and healthy tissue, including 40-plex on a single tissue section that is obtained in less than 24 h, using off-the-shelf antibodies. We also present extensive characterization of the developed method, including elution efficiency, epitope stability, repeatability and reproducibility, signal uniformity, and dynamic range, in addition to marker and panel optimization strategies. The streamlined workflow using off-the-shelf antibodies, data quality enabling downstream analysis, and ease of reaching hyperplex levels make seqIF suitable for immune-oncology research and other disciplines requiring spatial analysis, paving the way for its adoption in clinical settings.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
20452322
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.3a417ff679f42828b038f7ea1871887
Document Type :
article
Full Text :
https://doi.org/10.1038/s41598-023-43435-w