TCF1-LEF1 co-expression identifies a multipotent progenitor cell (T H 2-MPP) across human allergic diseases.
Radomir KratchmarovSarah DjeddiGarrett S DunlapWenqin HeXiaojiong JiaCaitlin M BurkTessa RyanAlanna McGillJessica R AllegrettiRaghu P KataruBabak J MehraraErin M TaylorShailesh AgarwalNeil BhattacharyyaRegan W BergmarkAlice Z MaxfieldStella E LeeRachel RoditiDaniel F DwyerJoshua A BoyceKathleen M BuchheitTanya M LaidlawWayne G ShrefflerDeepak A RaoMaria Gutierrez-ArcelusPatrick J BrennanPublished in: Nature immunology (2024)
Repetitive exposure to antigen in chronic infection and cancer drives T cell exhaustion, limiting adaptive immunity. In contrast, aberrant, sustained T cell responses can persist over decades in human allergic disease. To understand these divergent outcomes, we employed bioinformatic, immunophenotyping and functional approaches with human diseased tissues, identifying an abundant population of type 2 helper T (T H 2) cells with co-expression of TCF7 and LEF1, and features of chronic activation. These cells, which we termed T H 2-multipotent progenitors (T H 2-MPP) could self-renew and differentiate into cytokine-producing effector cells, regulatory T (T reg ) cells and follicular helper T (T FH ) cells. Single-cell T-cell-receptor lineage tracing confirmed lineage relationships between T H 2-MPP, T H 2 effectors, T reg cells and T FH cells. T H 2-MPP persisted despite in vivo IL-4 receptor blockade, while thymic stromal lymphopoietin (TSLP) drove selective expansion of progenitor cells and rendered them insensitive to glucocorticoid-induced apoptosis in vitro. Together, our data identify T H 2-MPP as an aberrant T cell population with the potential to sustain type 2 inflammation and support the paradigm that chronic T cell responses can be coordinated over time by progenitor cells.
Keyphrases
- induced apoptosis
- endoplasmic reticulum stress
- oxidative stress
- cell cycle arrest
- signaling pathway
- single cell
- endothelial cells
- machine learning
- type diabetes
- magnetic resonance imaging
- metabolic syndrome
- young adults
- skeletal muscle
- big data
- rna seq
- climate change
- weight loss
- binding protein
- insulin resistance
- artificial intelligence
- childhood cancer
- data analysis