Dataset Information

Marking the difference in acutely responding human CD8 T cells

ABSTRACT: The CD8 T cell response features functions that are fundamental for long-lasting immune protection, including antigen-specific cytolysis and memory. Accordingly, a range of differentiation subsets have been described with diverse functionalities and corresponding profiles of expression of markers. In both mouse and human systems, a major distinction has been “memory” versus “effector” terms. On the one hand, these terms may relate to temporality within the immune response : “effector” indicates the acute phase, “memory” refers to the post-contraction, resting phase. On the other hand, the terms also assign prototypic differentiation phenotypes that may be found at the same time-point : memory or effector subsets, based on characteristic markers. In this study, we analyse the human CD8 T cell response to YF-17D vaccination as the best-known model of acute immune response in humans. We study 21 characteristic markers conventionally used in mice and in humans to analyse and describe differentiation, activation, cycling, and so-called effector functions such as cytokine production and degranulation. We find clearly distinct ‘acute traits’ at the peak of the response that are shared amongst all non-naïve antigen-specific subsets, including in memory phenotype cells. These acute traits were low BCL-2 and high Ki67, CD38, HLA- DR, as well as increased Granzyme B and Perforin, which have been previously attributed only to effector cells at the peak of the response. Altogether, we evidenced ‘acute traits’ independent of differentiation phenotypes, supporting the semantic and marker distinction between “effector” and “acute” terms in the human CD8 T cell response.

ORGANISM(S): Homo sapiens

PROVIDER: GSE148223 | GEO | 2022/05/05

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Using killer cell lectin-like receptor G1 as a marker to distinguish terminal effector cells from memory precursors, we found that despite their diverse cell fates both subsets possessed remarkably similar gene expression profiles and functioned as equally potent killer cells. However, only the memory precursors were capable of making IL-2 thus defining a novel effector cell that was cytotoxic, expressed granzyme B, and produced inflammatory cytokines in addition to IL-2. This effector population then differentiated into long-lived protective memory T cells capable of self-renewal and rapid re-call responses. Mechanistic studies showed that cells that continued to receive antigenic stimulation during the later stages of infection were more likely to become terminal effectors. Importantly, curtailing antigenic stimulation towards the tail-end of the acute infection enhanced the generation of memory cells. These studies support the decreasing potential model of memory differentiation and show that the duration of antigenic stimulation is a critical regulator of memory formation Experiment Overall Design: An important question in memory development is understanding the differences between effector CD8 T cells that die versus effector cells that survive and give rise to memory cells. In this study we provide a comprehensive phenotypic, functional and genomic profiling of terminal effectors and memory precursors, towards better understanding the generation of these subsets. The two effector subsets were FACS purified during the early expansion phase (Days 4-5 post-infection) and extensively analyzed for their phenotypic (eg. CD127, CD62L, CD27, Bcl-2, Granzyme B, etc.) and functional properties (cytokine production, cytotoxicity, homeostatic proliferation, recall proliferation), and gene expression profiles (by genome-wide microarray analyses). Mechanistic studies involving the extent of proliferation and duration of antigen stimulation on memory differentiation potential of effectors were also performed using adoptive transfer techniques.

Dataset Information

Marking the difference in acutely responding human CD8 T cells

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure