Image_2_Identification of Two Subsets of Murine DC1 Dendritic Cells That Differ by Surface Phenotype, Gene Expression, and Function.jpeg
Classical dendritic cells (cDCs) in mice have been divided into 2 major subsets based on the expression of nuclear transcription factors: a CD8+Irf8+Batf3 dependent (DC1) subset, and a CD8-Irf4+ (DC2) subset. We found that the CD8+DC1 subset can be further divided into CD8+DC1a and CD8+DC1b subsets by differences in surface receptors, gene expression, and function. Whereas all 3 DC subsets can act alone to induce potent Th1 cytokine responses to class I and II MHC restricted peptides derived from ovalbumin (OVA) by OT-I and OT-II transgenic T cells, only the DC1b subset could effectively present glycolipid antigens to natural killer T (NKT) cells. Vaccination with OVA protein pulsed DC1b and DC2 cells were more effective in reducing the growth of the B16-OVA melanoma as compared to pulsed DC1a cells in wild type mice. In conclusion, the Batf3-/- dependent DC1 cells can be further divided into two subsets with different immune functional profiles in vitro and in vivo.
History
References
- https://doi.org//10.1126/science.1164206
- https://doi.org//10.1084/jem.20091627
- https://doi.org//10.1182/blood-2002-04-1088
- https://doi.org//10.1038/ni.3197
- https://doi.org//10.1146/annurev-immunol-032713-120204
- https://doi.org//10.1038/ni.2467
- https://doi.org//10.1016/j.celrep.2016.05.025
- https://doi.org//10.1016/j.ccell.2014.09.007
- https://doi.org//10.1016/j.ccr.2012.01.008
- https://doi.org//10.4049/jimmunol.1402622
- https://doi.org//10.1016/j.ccell.2016.06.003
- https://doi.org//10.4049/jimmunol.181.2.1345
- https://doi.org//10.1038/mi.2016.79
- https://doi.org//10.1128/JVI.00495-18
- https://doi.org//10.1084/jem.20071365
- https://doi.org//10.1101/cshperspect.a028613
- https://doi.org//10.1038/gt.2011.187
- https://doi.org//10.1002/eji.200838958
- https://doi.org//10.4049/jimmunol.1001205
- https://doi.org//10.3389/fimmu.2015.00035
- https://doi.org//10.1016/j.jri.2014.09.051
- https://doi.org//10.1038/ni.2679
- https://doi.org//10.1016/j.immuni.2015.04.017
- https://doi.org//10.3389/fimmu.2012.00214
- https://doi.org//10.1158/2326-6066.CIR-18-0291
- https://doi.org//10.4049/jimmunol.1101717
- https://doi.org//10.1084/jem.20080414
- https://doi.org//10.1038/srep06030
- https://doi.org//10.1002/eji.201041075
- https://doi.org//10.1080/2162402X.2018.1445457
- https://doi.org//10.1016/j.cellimm.2004.03.010
- https://doi.org//10.4049/jimmunol.166.9.5327
- https://doi.org//10.1182/bloodadvances.2018023119
- https://doi.org//10.1158/1078-0432.CCR-14-2824
- https://doi.org//10.4049/jimmunol.1300975
- https://doi.org//10.1016/j.immuni.2013.12.004
- https://doi.org//10.1016/j.smim.2009.10.003
- https://doi.org//10.1126/science.275.5302.977
- https://doi.org//10.1126/science.278.5343.1623
- https://doi.org//10.1038/nature05907
- https://doi.org//10.1016/0092-8674%2894%2990169-4
- https://doi.org//10.4049/jimmunol.164.9.4706
- https://doi.org//10.1182/blood-2011-08-371948
- https://doi.org//10.1016/j.jaut.2014.01.002
- https://doi.org//10.1186/gb-2013-14-4-r36
- https://doi.org//10.1111/j.1399-0004.2011.01713.x
- https://doi.org//10.1093/bioinformatics/btu638
- https://doi.org//10.1038/srep12599
- https://doi.org//10.1111/ajt.12606
Usage metrics
Read the peer-reviewed publication
Categories
- Transplantation Immunology
- Tumour Immunology
- Immunology not elsewhere classified
- Immunology
- Veterinary Immunology
- Animal Immunology
- Genetic Immunology
- Applied Immunology (incl. Antibody Engineering, Xenotransplantation and T-cell Therapies)
- Autoimmunity
- Cellular Immunology
- Humoural Immunology and Immunochemistry
- Immunogenetics (incl. Genetic Immunology)
- Innate Immunity
CC BY 4.0