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Proceedings of the National Academy of Sciences
Article . 2007 . Peer-reviewed
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Human β-defensin-3 activates professional antigen-presenting cells via Toll-like receptors 1 and 2

Authors: Nicholas, Funderburg; Michael M, Lederman; Zhimin, Feng; Michael G, Drage; Julie, Jadlowsky; Clifford V, Harding; Aaron, Weinberg; +1 Authors

Human β-defensin-3 activates professional antigen-presenting cells via Toll-like receptors 1 and 2

Abstract

There is increasing evidence that innate and adaptive immune responses are intimately linked. This linkage is in part mediated through the recognition of conserved microbial products by Toll-like receptors (TLRs). Detection of microbial products by TLRs can result in induction of inflammatory cytokines and activation of professional antigen-presenting cells, thereby enhancing adaptive immune responses. Here, we show that human β-defensin-3 (hBD-3), an innate antimicrobial peptide, can induce expression of the costimulatory molecules CD80, CD86, and CD40, on monocytes and myeloid dendritic cells in a TLR-dependent manner. Activation of monocytes by hBD-3 is mediated by interaction with TLRs 1 and 2, resulting in signaling that requires myeloid differentiating factor 88 and results in IL-1 receptor-associated kinase-1 phosphorylation. In studies with HEK cells engineered to express various TLRs, we show that activation of NF-κB by hBD-3 depends on the expression of both TLR1 and TLR2. Thus, human TLR signaling is not restricted to recognition of microbial patterns but also can be initiated by host-derived peptides such as hBD-3.

Related Organizations
Keywords

beta-Defensins, Antigen-Presenting Cells, Toll-Like Receptor 1, Monocytes, Toll-Like Receptor 2, Interleukin-1 Receptor-Associated Kinases, Antigens, CD, Myeloid Differentiation Factor 88, Humans, Phosphorylation, Cells, Cultured, Signal Transduction

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    350
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
350
Top 1%
Top 1%
Top 1%
bronze