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A unique human cord blood CD8+CD45RA+CD27+CD161+ T-cell subset identified by flow cytometric data analysis using Seurat
JGA. Reyes, D. Ni, B. Santner-Nanan, GV. Pinget, L. Kraftova, TM. Ashhurst, F. Marsh-Wakefield, CL. Wishart, J. Tan, P. Hsu, NJC. King, L. Macia, R. Nanan
Language English Country England, Great Britain
Document type Journal Article
Grant support
APP1104134
National Health and Medical Research Council
Norman Ernest Cummings Bequest
NLK
Free Medical Journals
from 1958 to 1 year ago
Medline Complete (EBSCOhost)
from 1958-01-01 to 1 year ago
Wiley Free Content
from 1996 to 1 year ago
PubMed
38798051
DOI
10.1111/imm.13803
Knihovny.cz E-resources
- MeSH
- Single-Cell Analysis methods MeSH
- Tumor Necrosis Factor Receptor Superfamily, Member 7 metabolism immunology MeSH
- Leukocyte Common Antigens * metabolism immunology MeSH
- CD8-Positive T-Lymphocytes * immunology MeSH
- Adult MeSH
- Fetal Blood * immunology cytology MeSH
- Immunophenotyping methods MeSH
- NK Cell Lectin-Like Receptor Subfamily B immunology metabolism MeSH
- Humans MeSH
- Flow Cytometry * methods MeSH
- Software MeSH
- T-Lymphocyte Subsets immunology metabolism MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
Advances in single-cell level analytical techniques, especially cytometric approaches, have led to profound innovation in biomedical research, particularly in the field of clinical immunology. This has resulted in an expansion of high-dimensional data, posing great challenges for comprehensive and unbiased analysis. Conventional manual analysis is thus becoming untenable to handle these challenges. Furthermore, most newly developed computational methods lack flexibility and interoperability, hampering their accessibility and usability. Here, we adapted Seurat, an R package originally developed for single-cell RNA sequencing (scRNA-seq) analysis, for high-dimensional flow cytometric data analysis. Based on a 20-marker antibody panel and analyses of T-cell profiles in both adult blood and cord blood (CB), we showcased the robust capacity of Seurat in flow cytometric data analysis, which was further validated by Spectre, another high-dimensional cytometric data analysis package, and conventional manual analysis. Importantly, we identified a unique CD8+ T-cell population defined as CD8+CD45RA+CD27+CD161+ T cell that was predominantly present in CB. We characterised its IFN-γ-producing and potential cytotoxic properties using flow cytometry experiments and scRNA-seq analysis from a published dataset. Collectively, we identified a unique human CB CD8+CD45RA+CD27+CD161+ T-cell subset and demonstrated that Seurat, a widely used package for scRNA-seq analysis, possesses great potential to be repurposed for cytometric data analysis. This facilitates an unbiased and thorough interpretation of complicated high-dimensional data using a single analytical pipeline and opens a novel avenue for data-driven investigation in clinical immunology.
Biomedical Center Faculty of Medicine Charles University Pilsen Czech Republic
Charles Perkins Centre The University of Sydney Sydney New South Wales Australia
Discipline of Child and Adolescent Health The University of Sydney Sydney New South Wales Australia
Kids Research The Children's Hospital at Westmead Sydney New South Wales Australia
Liver Injury and Cancer Program Centenary Institute Sydney New South Wales Australia
Nepean Clinical School The University of Sydney Sydney New South Wales Australia
Nepean Hospital Nepean Blue Mountains Local Health District Penrith New South Wales Australia
Sydney Nano The University of Sydney Sydney New South Wales Australia
References provided by Crossref.org
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