A unique human cord blood CD8 + CD45RA + CD27 + CD161 + T cell subset
identified by flow cytometric data analysis using Seurat
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, 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 cord blood. We characterized 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 cord blood CD8
+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.