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Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications

Proteins play critical roles across all facets of biology, with their abundance frequently used as markers of cell identity and state. The most popular method for detecting proteins on single cells, flow cytometry, is limited by considerations of fluorescent spectral overlap. While mass cytometry (C...

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Detalles Bibliográficos
Autores principales: Sheng, Jenny, Hod, Eldad A., Vlad, George, Chavez, Alejandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766443/
https://www.ncbi.nlm.nih.gov/pubmed/35042926
http://dx.doi.org/10.1038/s41598-022-04842-7
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author Sheng, Jenny
Hod, Eldad A.
Vlad, George
Chavez, Alejandro
author_facet Sheng, Jenny
Hod, Eldad A.
Vlad, George
Chavez, Alejandro
author_sort Sheng, Jenny
collection PubMed
description Proteins play critical roles across all facets of biology, with their abundance frequently used as markers of cell identity and state. The most popular method for detecting proteins on single cells, flow cytometry, is limited by considerations of fluorescent spectral overlap. While mass cytometry (CyTOF) allows for the detection of upwards of 40 epitopes simultaneously, it requires local access to specialized instrumentation not commonly accessible to many laboratories. To overcome these limitations, we independently developed a method to quantify multiple protein targets on single cells without the need for specialty equipment other than access to widely available next generation sequencing (NGS) services. We demonstrate that this combinatorial indexing method compares favorably to traditional flow-cytometry, and allows over two dozen target proteins to be assayed at a time on single cells. To showcase the potential of the technique, we analyzed peripheral blood and bone marrow aspirates from human clinical samples, and identified pathogenic cellular subsets with high fidelity. The ease of use of this technique makes it a promising technology for high-throughput proteomics and for interrogating complex samples such as those from patients with leukemia.
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spelling pubmed-87664432022-01-20 Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications Sheng, Jenny Hod, Eldad A. Vlad, George Chavez, Alejandro Sci Rep Article Proteins play critical roles across all facets of biology, with their abundance frequently used as markers of cell identity and state. The most popular method for detecting proteins on single cells, flow cytometry, is limited by considerations of fluorescent spectral overlap. While mass cytometry (CyTOF) allows for the detection of upwards of 40 epitopes simultaneously, it requires local access to specialized instrumentation not commonly accessible to many laboratories. To overcome these limitations, we independently developed a method to quantify multiple protein targets on single cells without the need for specialty equipment other than access to widely available next generation sequencing (NGS) services. We demonstrate that this combinatorial indexing method compares favorably to traditional flow-cytometry, and allows over two dozen target proteins to be assayed at a time on single cells. To showcase the potential of the technique, we analyzed peripheral blood and bone marrow aspirates from human clinical samples, and identified pathogenic cellular subsets with high fidelity. The ease of use of this technique makes it a promising technology for high-throughput proteomics and for interrogating complex samples such as those from patients with leukemia. Nature Publishing Group UK 2022-01-18 /pmc/articles/PMC8766443/ /pubmed/35042926 http://dx.doi.org/10.1038/s41598-022-04842-7 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
Sheng, Jenny
Hod, Eldad A.
Vlad, George
Chavez, Alejandro
Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications
title Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications
title_full Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications
title_fullStr Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications
title_full_unstemmed Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications
title_short Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications
title_sort quantifying protein abundance on single cells using split-pool sequencing on dna-barcoded antibodies for diagnostic applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766443/
https://www.ncbi.nlm.nih.gov/pubmed/35042926
http://dx.doi.org/10.1038/s41598-022-04842-7
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