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Single-cell transcriptomic analysis of mIHC images via antigen mapping
Highly multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific mar...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935366/ https://www.ncbi.nlm.nih.gov/pubmed/33674303 http://dx.doi.org/10.1126/sciadv.abc5464 |
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author | Govek, Kiya W. Troisi, Emma C. Miao, Zhen Aubin, Rachael G. Woodhouse, Steven Camara, Pablo G. |
author_facet | Govek, Kiya W. Troisi, Emma C. Miao, Zhen Aubin, Rachael G. Woodhouse, Steven Camara, Pablo G. |
author_sort | Govek, Kiya W. |
collection | PubMed |
description | Highly multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific markers is challenging. To overcome this obstacle, we have developed an approach for enriching mIHC images with single-cell RNA sequencing data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements. Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA) performs transcriptome-guided annotation of highly multiplexed cytometry datasets. It increases the level of detail in histological analyses by enabling the systematic annotation of nuanced cell populations, spatial patterns of transcription, and interactions between cell types. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published cytometry and mIHC data of this organ. |
format | Online Article Text |
id | pubmed-7935366 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-79353662021-03-17 Single-cell transcriptomic analysis of mIHC images via antigen mapping Govek, Kiya W. Troisi, Emma C. Miao, Zhen Aubin, Rachael G. Woodhouse, Steven Camara, Pablo G. Sci Adv Research Articles Highly multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific markers is challenging. To overcome this obstacle, we have developed an approach for enriching mIHC images with single-cell RNA sequencing data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements. Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA) performs transcriptome-guided annotation of highly multiplexed cytometry datasets. It increases the level of detail in histological analyses by enabling the systematic annotation of nuanced cell populations, spatial patterns of transcription, and interactions between cell types. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published cytometry and mIHC data of this organ. American Association for the Advancement of Science 2021-03-05 /pmc/articles/PMC7935366/ /pubmed/33674303 http://dx.doi.org/10.1126/sciadv.abc5464 Text en Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/ https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Govek, Kiya W. Troisi, Emma C. Miao, Zhen Aubin, Rachael G. Woodhouse, Steven Camara, Pablo G. Single-cell transcriptomic analysis of mIHC images via antigen mapping |
title | Single-cell transcriptomic analysis of mIHC images via antigen mapping |
title_full | Single-cell transcriptomic analysis of mIHC images via antigen mapping |
title_fullStr | Single-cell transcriptomic analysis of mIHC images via antigen mapping |
title_full_unstemmed | Single-cell transcriptomic analysis of mIHC images via antigen mapping |
title_short | Single-cell transcriptomic analysis of mIHC images via antigen mapping |
title_sort | single-cell transcriptomic analysis of mihc images via antigen mapping |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935366/ https://www.ncbi.nlm.nih.gov/pubmed/33674303 http://dx.doi.org/10.1126/sciadv.abc5464 |
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