Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Govek, Kiya W., Troisi, Emma C., Miao, Zhen, Aubin, Rachael G., Woodhouse, Steven, Camara, Pablo G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2021
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
_version_ 1783660995034480640
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
work_keys_str_mv AT govekkiyaw singlecelltranscriptomicanalysisofmihcimagesviaantigenmapping
AT troisiemmac singlecelltranscriptomicanalysisofmihcimagesviaantigenmapping
AT miaozhen singlecelltranscriptomicanalysisofmihcimagesviaantigenmapping
AT aubinrachaelg singlecelltranscriptomicanalysisofmihcimagesviaantigenmapping
AT woodhousesteven singlecelltranscriptomicanalysisofmihcimagesviaantigenmapping
AT camarapablog singlecelltranscriptomicanalysisofmihcimagesviaantigenmapping