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Titration of 124 antibodies using CITE-Seq on human PBMCs

Single-cell RNA-sequencing (scRNA-Seq) is widely used to characterize immune cell populations. However, mRNA levels correlate poorly with expression of surface proteins, which are well established to define immune cell types. CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing)...

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Autores principales: Nettersheim, Felix Sebastian, Armstrong, Sujit Silas, Durant, Christopher, Blanco-Dominguez, Rafael, Roy, Payel, Orecchioni, Marco, Suryawanshi, Vasantika, Ley, Klaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718773/
https://www.ncbi.nlm.nih.gov/pubmed/36460735
http://dx.doi.org/10.1038/s41598-022-24371-7
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author Nettersheim, Felix Sebastian
Armstrong, Sujit Silas
Durant, Christopher
Blanco-Dominguez, Rafael
Roy, Payel
Orecchioni, Marco
Suryawanshi, Vasantika
Ley, Klaus
author_facet Nettersheim, Felix Sebastian
Armstrong, Sujit Silas
Durant, Christopher
Blanco-Dominguez, Rafael
Roy, Payel
Orecchioni, Marco
Suryawanshi, Vasantika
Ley, Klaus
author_sort Nettersheim, Felix Sebastian
collection PubMed
description Single-cell RNA-sequencing (scRNA-Seq) is widely used to characterize immune cell populations. However, mRNA levels correlate poorly with expression of surface proteins, which are well established to define immune cell types. CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing) utilizes oligonucleotide-tagged antibodies to simultaneously analyze surface phenotypes and transcriptomes. Considering the high costs of adding surface phenotyping to scRNA-Seq, we aimed to determine which of 188 tested CITE-Seq antibodies can detect their antigens on human peripheral blood mononuclear cells (PBMCs), a commonly interrogated cell population in immunology, and find the optimal concentration for staining. The recommended concentration was optimal for 76 antibodies, whereas staining quality of 7 antibodies improved when the concentration was doubled. 33 and 8 antibodies still worked well when the concentration was reduced to 1/5 or 1/25, respectively. 64 antigens were not detected at any antibody concentration. Optimizing the antibody panel by removing antibodies not able to detect their target antigens and adjusting concentrations of the remaining antibodies will improve the analysis and may reduce costs. In conclusion, our data are a resource for building an informative and cost-effective panel of CITE-Seq antibodies and use them at their optimal concentrations in future CITE-seq experiments on human PBMCs.
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spelling pubmed-97187732022-12-04 Titration of 124 antibodies using CITE-Seq on human PBMCs Nettersheim, Felix Sebastian Armstrong, Sujit Silas Durant, Christopher Blanco-Dominguez, Rafael Roy, Payel Orecchioni, Marco Suryawanshi, Vasantika Ley, Klaus Sci Rep Article Single-cell RNA-sequencing (scRNA-Seq) is widely used to characterize immune cell populations. However, mRNA levels correlate poorly with expression of surface proteins, which are well established to define immune cell types. CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing) utilizes oligonucleotide-tagged antibodies to simultaneously analyze surface phenotypes and transcriptomes. Considering the high costs of adding surface phenotyping to scRNA-Seq, we aimed to determine which of 188 tested CITE-Seq antibodies can detect their antigens on human peripheral blood mononuclear cells (PBMCs), a commonly interrogated cell population in immunology, and find the optimal concentration for staining. The recommended concentration was optimal for 76 antibodies, whereas staining quality of 7 antibodies improved when the concentration was doubled. 33 and 8 antibodies still worked well when the concentration was reduced to 1/5 or 1/25, respectively. 64 antigens were not detected at any antibody concentration. Optimizing the antibody panel by removing antibodies not able to detect their target antigens and adjusting concentrations of the remaining antibodies will improve the analysis and may reduce costs. In conclusion, our data are a resource for building an informative and cost-effective panel of CITE-Seq antibodies and use them at their optimal concentrations in future CITE-seq experiments on human PBMCs. Nature Publishing Group UK 2022-12-02 /pmc/articles/PMC9718773/ /pubmed/36460735 http://dx.doi.org/10.1038/s41598-022-24371-7 Text en © The Author(s) 2022 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
Nettersheim, Felix Sebastian
Armstrong, Sujit Silas
Durant, Christopher
Blanco-Dominguez, Rafael
Roy, Payel
Orecchioni, Marco
Suryawanshi, Vasantika
Ley, Klaus
Titration of 124 antibodies using CITE-Seq on human PBMCs
title Titration of 124 antibodies using CITE-Seq on human PBMCs
title_full Titration of 124 antibodies using CITE-Seq on human PBMCs
title_fullStr Titration of 124 antibodies using CITE-Seq on human PBMCs
title_full_unstemmed Titration of 124 antibodies using CITE-Seq on human PBMCs
title_short Titration of 124 antibodies using CITE-Seq on human PBMCs
title_sort titration of 124 antibodies using cite-seq on human pbmcs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718773/
https://www.ncbi.nlm.nih.gov/pubmed/36460735
http://dx.doi.org/10.1038/s41598-022-24371-7
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