Differential Requirements for Tcf1 Long Isoforms in CD8+ and CD4+ T Cell Responses to Acute Viral Infection.
Jodi A GullicksrudFengyin LiShaojun XingZhouhao ZengWeiqun PengVladimir P BadovinacJohn T HartyHai-Hui XuePublished in: Journal of immunology (Baltimore, Md. : 1950) (2017)
In response to acute viral infection, activated naive T cells give rise to effector T cells that clear the pathogen and memory T cells that persist long-term and provide heightened protection. T cell factor 1 (Tcf1) is essential for several of these differentiation processes. Tcf1 is expressed in multiple isoforms, with all isoforms sharing the same HDAC and DNA-binding domains and the long isoforms containing a unique N-terminal β-catenin-interacting domain. In this study, we specifically ablated Tcf1 long isoforms in mice, while retaining expression of Tcf1 short isoforms. During CD8+ T cell responses, Tcf1 long isoforms were dispensable for generating cytotoxic CD8+ effector T cells and maintaining memory CD8+ T cell pool size, but they contributed to optimal maturation of central memory CD8+ T cells and their optimal secondary expansion in a recall response. In contrast, Tcf1 long isoforms were required for differentiation of T follicular helper (TFH) cells, but not TH1 effectors, elicited by viral infection. Although Tcf1 short isoforms adequately supported Bcl6 and ICOS expression in TFH cells, Tcf1 long isoforms remained important for suppressing the expression of Blimp1 and TH1-associated genes and for positively regulating Id3 to restrain germinal center TFH cell differentiation. Furthermore, formation of memory TH1 and memory TFH cells strongly depended on Tcf1 long isoforms. These data reveal that Tcf1 long and short isoforms have distinct, yet complementary, functions and may represent an evolutionarily conserved means to ensure proper programming of CD8+ and CD4+ T cell responses to viral infection.
Keyphrases
- induced apoptosis
- poor prognosis
- dna binding
- working memory
- cell cycle arrest
- magnetic resonance
- dendritic cells
- machine learning
- type diabetes
- genome wide
- metabolic syndrome
- hiv infected
- cell death
- social media
- endoplasmic reticulum stress
- binding protein
- deep learning
- epithelial mesenchymal transition
- dna methylation
- big data
- intensive care unit
- health information
- data analysis
- high fat diet induced