Phenotypic Landscape of Immune Cells in Sepsis: Insights from High-Dimensional Mass Cytometry.
Sehee ParkHaribalan PerumalsamyZayakhuu GerelkhuuSneha SunderrajYangsoon LeeTae Hyun YoonPublished in: ACS infectious diseases (2024)
Understanding the sepsis-induced immunological response can be facilitated by identifying phenotypic changes in immune cells at the single-cell level. Mass cytometry, a novel multiparametric single-cell analysis technique, offers considerable benefits in characterizing sepsis-induced phenotypic changes in peripheral blood mononuclear cells. Here, we analyzed peripheral blood mononuclear cells from 20 sepsis patients and 10 healthy donors using mass cytometry and employing 23 markers. Both manual gating and automated clustering approaches (PhenoGraph) were used for cell identification, complemented by uniform manifold approximation and projection (UMAP) for dimensionality reduction and visualization. Our study revealed that patients with sepsis exhibited a unique immune cell profile, marked by an increased presence of monocytes, B cells, and dendritic cells, alongside a reduction in natural killer (NK) cells and CD4/CD8 T cells. Notably, significant changes in the distributions of monocytes and B and CD4 T cells were observed. Clustering with PhenoGraph unveiled the subsets of each cell type and identified elevated CCR6 expression in sepsis patients' monocyte subset (PG#5), while further PhenoGraph clustering on manually gated T and B cells discovered sepsis-specific CD4 T cell subsets (CCR4 low CD20 low CD38 low ) and B cell subsets (HLA-DR low CCR7 low CCR6 high ), which could potentially serve as novel diagnostic markers for sepsis.
Keyphrases
- single cell
- dendritic cells
- rna seq
- septic shock
- acute kidney injury
- intensive care unit
- nk cells
- high throughput
- end stage renal disease
- peripheral blood
- regulatory t cells
- newly diagnosed
- ejection fraction
- immune response
- chronic kidney disease
- machine learning
- magnetic resonance imaging
- poor prognosis
- prognostic factors
- peritoneal dialysis
- computed tomography
- magnetic resonance
- deep learning
- cell therapy
- mesenchymal stem cells
- long non coding rna