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CD4+ T Cell Subset Differentiation and Avidity Setpoint Are Dictated by the Interplay of Cytokine and Antigen Mediated Signals

Overview of attention for article published in PLOS ONE, June 2014
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Title
CD4+ T Cell Subset Differentiation and Avidity Setpoint Are Dictated by the Interplay of Cytokine and Antigen Mediated Signals
Published in
PLOS ONE, June 2014
DOI 10.1371/journal.pone.0100175
Pubmed ID
Authors

Erin K. Shiner, Beth C. Holbrook, Martha A. Alexander-Miller

Abstract

CD4+ T cell differentiation has been shown to be regulated by the cytokine milieu present during activation as well as peptide MHC levels. However, the extent to which these two important regulatory signals work in concert to shape CD4+ T cell function has not been investigated. Using a murine OT-II transgenic TCR model of in vitro differentiation, we demonstrate that the ability of CD4+ T cells to commit to a distinct lineage, i.e. Th1 vs. Th2 vs. Th17, is restricted by the amount of peptide antigen present in the stimulating environment. In addition, whether cells succumb to inhibitory effects associated with high dose antigen is dependent on the array of cytokine signals encountered. Specifically, stimulation with high dose antigen in Th1 or Th17 conditions promoted efficient generation of functional cells, while Th2 polarizing conditions did not. Finally, we found that the peptide sensitivity of an effector cell was determined by the combined actions of cytokine and peptide level, with Th1 cells exhibiting the highest avidity, followed by Th17 and Th2 cells. Together, these data show that the interplay of antigen and cytokine signals shape both the differentiation fate and avidity setpoint of CD4+ T cells.

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The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 42%
Researcher 4 11%
Student > Bachelor 4 11%
Other 2 6%
Student > Doctoral Student 2 6%
Other 4 11%
Unknown 5 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 36%
Immunology and Microbiology 6 17%
Biochemistry, Genetics and Molecular Biology 5 14%
Medicine and Dentistry 5 14%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 1 3%
Unknown 5 14%