Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 16410796

TLR signaling.

T Kawai·S Akira
View original source ↗Export metadata ↓

Abstract

The Toll-like receptor (TLR) family plays an instructive role in innate immune responses against microbial pathogens, as well as the subsequent induction of adaptive immune responses. TLRs recognize specific molecular patterns found in a broad range of microbial pathogens such as bacteria and viruses, triggering inflammatory and antiviral responses and dendritic cell maturation, which result in the eradication of invading pathogens. Individual TLRs interact with different combinations of adapter proteins and activate various transcription factors such as nuclear factor (NF)-kappaB, activating protein-1 and interferon regulatory factors, driving a specific immune response. This review outlines the recent advances in our understanding of TLR-signaling pathways and their roles in immune responses. Further, we also discuss a new concept of TLR-independent mechanisms for recognition of microbial pathogens.

Explore related subjects

Adaptor Proteins, Signal TransducingAdaptor Proteins, Vesicular TransportAnimalsDEAD-box RNA HelicasesDrosophilaGene Expression RegulationHumansImmunity, InnateInterferon Regulatory FactorsInterferon-Induced Helicase, IFIH1Membrane ProteinsMiceModels, BiologicalMyeloid Differentiation Factor 88NF-kappa BNerve Tissue ProteinsRNA HelicasesReceptors, Cell SurfaceSignal TransductionToll-Like ReceptorsTranscription Factor AP-1Roundabout ProteinsJournal ArticleReview

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

T Kawai, S Akira. 2006. TLR signaling.. https://doi.org/10.1038/sj.cdd.4401850

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2022

Epigenome-wide meta-analysis of PTSD symptom severity in three military cohorts implicates DNA methylation changes in genes involved in immune system and oxidative stress.

Epigenetic factors modify the effects of environmental factors on biological outcomes. Identification of epigenetic changes that associate with PTSD is therefore a crucial step in deciphering mechanisms of risk and resilience. In this study, our goal is to identify epigenetic signatures associated with PTSD symptom severity (PTSS) and changes in PTSS over time, using whole blood DNA methylation (DNAm) data (MethylationEPIC BeadChip) of military personnel prior to and following combat deployment. A total of 429 subjects (858 samples across 2 time points) from three male military cohorts were included in the analyses. We conducted two different meta-analyses to answer two different scientific questions: one to identify a DNAm profile of PTSS using a random effects model including both time points for each subject, and the other to identify a DNAm profile of change in PTSS conditioned on pre-deployment DNAm. Four CpGs near four genes (F2R, CNPY2, BAIAP2L1, and TBXAS1) and 88 differentially methylated regions (DMRs) were associated with PTSS. Change in PTSS after deployment was associated with 15 DMRs, of those 2 DMRs near OTUD5 and ELF4 were also associated with PTSS. Notably, three PTSS-associated CpGs near F2R, BAIAP2L1 and TBXAS1 also showed nominal evidence of association with change in PTSS. This study, which identifies PTSD-associated changes in genes involved in oxidative stress and immune system, provides novel evidence that epigenetic differences are associated with PTSS.

Adaptor Proteins, Signal Transducing↗
PubMed2020

LINC00922 regulates epithelial-mesenchymal transition, invasive and migratory capacities in breast cancer through promoting NKD2 methylation.

Breast cancer ranks as the major reason for mortality in women populations, accounting for 23% of all cancer deaths. One in every three Asian women encounters the risk of this cancer in their lifetime. Long intergenic non-coding RNAs (lincRNAs) have emerged as tumor promoters and suppressors. The molecular mechanism of breast cancer remains elusive. Therefore, the current study aimed to explore the role lincRNA LINC00922 plays in the development of breast cancer. Breast cancer tissues and adjacent tissues were obtained from 109 patients with breast cancer. The RNA extraction and quantification and immunohistochemical staining characterized the high expression of LINC00922 and low expression of NKD2 in breast cancer tissues in comparison to its adjacent counterparts. Furthermore, the ectopic expression and knockdown experiments were conducted to figure out the in vivo and in vitro effects of LINC00922 on breast cancer progression. The ectopically expressed LINC00922 activated the Wnt signaling pathway, promoted epithelial-mesenchymal transition, cell proliferative, invasive and migratory capacities, tumor growth and metastasis. Additionally, the RIP and ChIP assay identified that LINC00922 recruited DNMT1, DNMT3A and DNMT3B proteins in the promoter region of NKD2 to promote NKD2 promoter methylation, thus reducing the NKD2 expression. Moreover, the Wnt signaling pathway was activated subsequent to NKD2 silencing, which was reversed by LINC00922 silencing. Lastly, the anti-oncogenic effects of LINC00922 inhibition was antagonized after NKD2 knocked down. The current study provides evidence that LINC00922 acts as a tumor promoter by promoting NKD2 methylation. Hopefully, it provides a novel potential gene target for the treatment of breast cancer.

Adaptor Proteins, Signal Transducing↗
PubMed2011

Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease.

The Alzheimer Disease Genetics Consortium (ADGC) performed a genome-wide association study of late-onset Alzheimer disease using a three-stage design consisting of a discovery stage (stage 1) and two replication stages (stages 2 and 3). Both joint analysis and meta-analysis approaches were used. We obtained genome-wide significant results at MS4A4A (rs4938933; stages 1 and 2, meta-analysis P (P(M)) = 1.7 × 10(-9), joint analysis P (P(J)) = 1.7 × 10(-9); stages 1, 2 and 3, P(M) = 8.2 × 10(-12)), CD2AP (rs9349407; stages 1, 2 and 3, P(M) = 8.6 × 10(-9)), EPHA1 (rs11767557; stages 1, 2 and 3, P(M) = 6.0 × 10(-10)) and CD33 (rs3865444; stages 1, 2 and 3, P(M) = 1.6 × 10(-9)). We also replicated previous associations at CR1 (rs6701713; P(M) = 4.6 × 10(-10), P(J) = 5.2 × 10(-11)), CLU (rs1532278; P(M) = 8.3 × 10(-8), P(J) = 1.9 × 10(-8)), BIN1 (rs7561528; P(M) = 4.0 × 10(-14), P(J) = 5.2 × 10(-14)) and PICALM (rs561655; P(M) = 7.0 × 10(-11), P(J) = 1.0 × 10(-10)), but not at EXOC3L2, to late-onset Alzheimer's disease susceptibility.

Adaptor Proteins, Signal Transducing↗