SMAD4 and TGFβ are architects of inverse genetic programs during fate determination of antiviral CTLs.
Karthik ChandiranJenny E Suarez-RamirezYinghong HuEvan R JellisonZeynep UgurJun Siong LowBryan McDonaldSusan M KaechLinda S CauleyPublished in: eLife (2022)
Transforming growth factor β (TGFβ) is an important differentiation factor for cytotoxic T lymphocytes (CTLs) and alters the expression levels of several of homing receptors during infection. SMAD4 is part of the canonical signaling network used by members of the transforming growth factor family. For this study, genetically modified mice were used to determine how SMAD4 and TGFβ receptor II (TGFβRII) participate in transcriptional programming of pathogen-specific CTLs. We show that these molecules are essential components of opposing signaling mechanisms, and cooperatively regulate a collection of genes that determine whether specialized populations of pathogen-specific CTLs circulate around the body, or settle in peripheral tissues. TGFβ uses a canonical SMAD-dependent signaling pathway to downregulate Eomesodermin (EOMES), KLRG1, and CD62L, while CD103 is induced. Conversely, in vivo and in vitro data show that EOMES, KLRG1, CX 3 CR1, and CD62L are positively regulated via SMAD4, while CD103 and Hobit are downregulated. Intravascular staining also shows that signaling via SMAD4 promotes formation of long-lived terminally differentiated CTLs that localize in the vasculature. Our data show that inflammatory molecules play a key role in lineage determination of pathogen-specific CTLs, and use SMAD-dependent signaling to alter the expression levels of multiple homing receptors and transcription factors with known functions during memory formation.
Keyphrases
- transforming growth factor
- epithelial mesenchymal transition
- signaling pathway
- transcription factor
- poor prognosis
- gene expression
- oxidative stress
- public health
- big data
- machine learning
- palliative care
- binding protein
- molecularly imprinted
- working memory
- electronic health record
- metabolic syndrome
- mass spectrometry
- nk cells
- pi k akt
- type diabetes
- dna methylation
- adipose tissue
- insulin resistance
- long non coding rna
- solid phase extraction
- cell proliferation
- drug induced
- flow cytometry
- deep learning
- high glucose
- genetic diversity
- liquid chromatography