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Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics
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 importan...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562446/ https://www.ncbi.nlm.nih.gov/pubmed/37813886 http://dx.doi.org/10.1038/s41598-023-43435-w |
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author | Rivest, François Eroglu, Deniz Pelz, Benjamin Kowal, Joanna Kehren, Alexandre Navikas, Vytautas Procopio, Maria Giuseppina Bordignon, Pino Pérès, Emilie Ammann, Marco Dorel, Emmanuel Scalmazzi, Sylvain Bruno, Lorenzo Ruegg, Matthieu Campargue, Gabriel Casqueiro, Gilles Arn, Lionel Fischer, Jérôme Brajkovic, Saska Joris, Pierre Cassano, Marco Dupouy, Diego |
author_facet | Rivest, François Eroglu, Deniz Pelz, Benjamin Kowal, Joanna Kehren, Alexandre Navikas, Vytautas Procopio, Maria Giuseppina Bordignon, Pino Pérès, Emilie Ammann, Marco Dorel, Emmanuel Scalmazzi, Sylvain Bruno, Lorenzo Ruegg, Matthieu Campargue, Gabriel Casqueiro, Gilles Arn, Lionel Fischer, Jérôme Brajkovic, Saska Joris, Pierre Cassano, Marco Dupouy, Diego |
author_sort | Rivest, François |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10562446 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105624462023-10-11 Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics Rivest, François Eroglu, Deniz Pelz, Benjamin Kowal, Joanna Kehren, Alexandre Navikas, Vytautas Procopio, Maria Giuseppina Bordignon, Pino Pérès, Emilie Ammann, Marco Dorel, Emmanuel Scalmazzi, Sylvain Bruno, Lorenzo Ruegg, Matthieu Campargue, Gabriel Casqueiro, Gilles Arn, Lionel Fischer, Jérôme Brajkovic, Saska Joris, Pierre Cassano, Marco Dupouy, Diego Sci Rep Article 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. Nature Publishing Group UK 2023-10-09 /pmc/articles/PMC10562446/ /pubmed/37813886 http://dx.doi.org/10.1038/s41598-023-43435-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Rivest, François Eroglu, Deniz Pelz, Benjamin Kowal, Joanna Kehren, Alexandre Navikas, Vytautas Procopio, Maria Giuseppina Bordignon, Pino Pérès, Emilie Ammann, Marco Dorel, Emmanuel Scalmazzi, Sylvain Bruno, Lorenzo Ruegg, Matthieu Campargue, Gabriel Casqueiro, Gilles Arn, Lionel Fischer, Jérôme Brajkovic, Saska Joris, Pierre Cassano, Marco Dupouy, Diego Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics |
title | Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics |
title_full | Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics |
title_fullStr | Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics |
title_full_unstemmed | Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics |
title_short | Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics |
title_sort | fully automated sequential immunofluorescence (seqif) for hyperplex spatial proteomics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562446/ https://www.ncbi.nlm.nih.gov/pubmed/37813886 http://dx.doi.org/10.1038/s41598-023-43435-w |
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