Science Inventory

Modulation of TLR2 protein expression by a miR-105 in human oral keratinocytes

Citation:

Benakanakere, M. R., Q. Li, M. A. Eskan, A. V. SINGH, J. Zhao, J. C. Galicia, P. Stathopoulou, T. B. KNUDSEN, AND D. F. Kinane. Modulation of TLR2 protein expression by a miR-105 in human oral keratinocytes. JOURNAL OF BIOLOGICAL CHEMISTRY. JBC Papers in Press, 284(34):23107-15, (2009).

Impact/Purpose:

Further understanding of miRNA’s role in host responses may elucidate disease susceptibility and suggest new anti-inflammatory therapeutics.

Description:

Mammalian biological processes such as inflammation, involve regulation of hundreds of genes controlling onset and termination. MicroRNAs (miRNAs) can translationally repress target mRNAs and can regulate innate immune responses. Our model system comprised primary human keratinocytes which exhibited robust differences in inflammatory cytokine production (IL-6) following specific TLR-2/TLR-4 agonist challenge. We challenged these primary cells with Porphyromonas gingivalis (a Gram-negative bacterium that triggers TLR-2 and TLR-4) and performed micro-RNA expression profiling. We identified micro-RNA (miR)-105 as a modulator of TLR-2 protein translation in human gingival keratinocytes. There was a strong inverse correlation between cells which had high cytokine responses following TLR-2 agonist challenge and miR-105 levels. Knock-in and knock-down of miR-105 confirmed this inverse relationship. In silico analysis predicted that miR-105 had complementarity for TLR-2 mRNA and the luciferase reporter assay verified this. Further understanding of miRNA’s role in host responses may elucidate disease susceptibility and suggest new anti-inflammatory therapeutics.

URLs/Downloads:

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Record Details:

Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Product Published Date: 08/21/2009
Record Last Revised: 08/19/2010
OMB Category: Other
Record ID: 209900

Organization:

U.S. ENVIRONMENTAL PROTECTION AGENCY

OFFICE OF RESEARCH AND DEVELOPMENT

NATIONAL CENTER FOR COMPUTATIONAL TOXICOLOGY