• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of jbcAbout JBCASBMBSubmissionsSubscriptionsContactJBCThis Article
J Biol Chem. Aug 21, 2009; 284(34): 23107–23115.
Published online Jun 9, 2009. doi:  10.1074/jbc.M109.013862
PMCID: PMC2755716

Modulation of TLR2 Protein Expression by miR-105 in Human Oral Keratinocytes*


Mammalian biological processes such as inflammation, involve regulation of hundreds of genes controlling onset and termination. MicroRNAs (miRNAs) can translationally repress target mRNAs and regulate innate immune responses. Our model system comprised primary human keratinocytes, which exhibited robust differences in inflammatory cytokine production (interleukin-6 and tumor necrosis factor-α) following specific Toll-like receptor 2 and 4 (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 miRNA expression profiling. We identified miRNA (miR)-105 as a modulator of TLR-2 protein translation in human gingival keratinocytes. There was a strong inverse correlation between cells that 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 the role of miRNA in host responses may elucidate disease susceptibility and suggest new anti-inflammatory therapeutics.

The innate immune response is a crucial first line of defense against pathogens. Host detection of microbes occurs through pattern recognition receptors, including Toll-like receptors (TLRs)2 that are expressed on many cells, including macrophages, monocytes (1), and keratinocytes (2). To date, 11 TLRs have been identified in humans, recognizing a range of distinct and conserved microbial molecules (3). TLRs responding to particular pathogens may activate complex networks of pathways and interactions, positive and negative feedback loops, and multifunctional transcriptional responses (4). Among the key downstream targets of these networks are NF-κB, mitogen-activated protein kinases, and members of the IRF family (5). Proper regulation of the gene products comprising these networks by transcriptional and post-transcriptional processing is not only important for selective pathogen elimination but also for preventing excessive accumulation of cytokines such as interferon-β, interferon-γ, IL-6, and TNF-α that initiate the host defense against microbial attack (6). Deregulated expression of these cytokines has been implicated in cancer, autoimmunity, and hyper-inflammatory states (79).

MicroRNAs (miRNAs) have been implicated in pathway-level regulation of complex biological processes (10). The role of miRNA-based regulation of the innate immune responses is a current topic of investigation (11). Mammalian miRNAs are a class of conserved, small noncoding RNA oligonucleotides that function as negative regulators of translation for multiple target transcripts (12). As many as 5000 distinct miRNAs may be transcribed and processed in mammalian cells (1317). Mature miRNAs bind to specific cognate sequences in the 3′-UTRs of target transcripts, resulting in either mRNA degradation or inhibition of translation (12).

In mammalian cells, the miRNAs provide a key level of biological regulation in developmental and differentiation pathways (18). Deregulation of specific miRNA abundance has been associated with malignancies in the colon, breast, and lung (19, 20). Recently, miRNAs have been shown to modulate the NF-κB pathway (miR-146a) (21) and negatively regulate TRAF6, IRAK1 (miR-155) (22), or SOCS3 (miR-203) (23). It is presently unclear how miRNAs regulate cellular pathways in innate and inflammatory processes, where precise control of complex networks is needed to engage an appropriate response to microbes that avoids a cytokine storm.

Periodontitis is a common chronic inflammatory condition affecting 50% of humans that results in loss of bone and teeth (24). This disease is initiated by dental plaque, a microbial biofilm composed mainly of Gram-negative anaerobic bacilli (25, 26), including the pathogen Porphyromonas gingivalis. Individual human variability in susceptibility to periodontitis is recognized (27) and may involve individual variation in the immune response (25, 26). We identified innate immune variations within a bank of over 30 primary human gingival cell cultures (25) based on variations in cytokine response following TLR agonist challenge.

The present study tested the hypothesis that differential expression of miRNAs may account for some of the variability in innate immunity. To test this hypothesis, we selected three “normal” and three “diminished” cytokine-response phenotypes. We subjected the corresponding primary human gingival cell cultures to TLR agonist challenge and profiled the expression of 600 miRNAs. We found strong up-regulation of hsa-miR-105 specifically in the diminished cytokine-response phenotype and furthermore showed that TLR-2 protein levels were depressed. This implies a concordant logic circuit in which miR-105 inversely regulates TLR-2 function. A computational (in silico) search of the miRNA database revealed that TLR-2 transcript is a potential target for miR-105 regulation at the 3′-UTR. This binding was confirmed using a linked luciferase reporter gene, and through small interference RNA and inhibitor (antagomir) studies a functional association with cell surface TLR-2 expression. We also confirmed this complementarity. We conclude that cell surface TLR-2 expression is inversely regulated by miR-105 expression in human gingival epithelial cells. This mechanism may reduce inflammatory cytokine production and provide a novel target for therapeutic intervention.


Cell Culture and Challenge Assays

A total of 13 human gingival epithelial cells (keratinocytes), with University of Louisville IRB approval, were obtained from healthy patients after third molar extraction. They were grown as previously described (28) to sub-confluence, sub-cultured, and challenged as described (2, 29, 30). At confluence, they were challenged with heat-inactivated P. gingivalis (strain 33277) or 1 μg/ml FSL-1 (Pam2CGDPKHPKSF, a synthetic diacylated lipoprotein and a specific ligand for TLR-2) (InvivoGen, CA). Cells were challenged for 24 h, and culture supernatants were subjected to IL-6 and TNF-α cytokine levels were measured by enzyme-linked immunosorbent assay (BD Biosciences). The transcription factor NF-κB assay was performed using a modified electrophoretic mobility shift assay technique with TransAMTM NF-κB enzyme-linked immunosorbent assay kit from ActiveMotif (Carlsbad, CA) according to the manufacturer's instructions. HEK-293 (ATCC number: CRL-1573) cells were cultured following ATCC protocol. Briefly, the cell monolayer was washed and incubated with 2–3 ml of trypsin-EDTA solution to the flask and neutralized with trypsin inhibitor after 5 min. The cells were centrifuged and suspended in ATCC-formulated Eagle's minimum essential medium (catalogue no. 30-2003) with 10% fetal bovine serum (complete medium). The cells were propagated in complete medium until they were ready for transfection.

miRNA Array Profiling/Analysis

Total RNA was collected by the TRIzol method and purified with a Qiagen purification kit (Qiagen), and total RNA quality was analyzed using a Bioanalyzer 2100 (Agilent). Equal amounts of each sample were used to generate a reference pool. For each array to be hybridized, 2 μg of total RNA from each sample, and the reference pool were labeled with Hy3TM and Hy5TM fluorescent label, respectively, using the miRCURYTM LNA Array labeling kit (Exiqon, Denmark) following the manufacturer's instructions. The Hy3TM-labeled sample and the Hy5TM-labeled reference pool RNA were mixed and hybridized to the miRCURYTM LNA array version 8.1 (Exiqon). The hybridization was performed according to the miRCURYTM LNA array manual using a Tecan HS4800 hybridization station (Tecan, Austria). The miRCURYTM LNA array microarray slides were scanned by a ScanArray 4000 XL scanner (Packard Biochip Technologies), and the image analysis was carried out using the ImaGene 7.0 software (BioDiscovery, Inc.). Expression ratios were determined for microarray data by computing the background-corrected fluorescent signal from the query sample (Q)/reference sample (R). Ratiometric data were transformed to log 2 to produce a continuous spectrum of up- and down-regulated values. Data were normalized by plotting the difference, log 2(Q/R), against the average, (1/2) log 2(Q*R) followed by the application of locally weighted regression (lowness) to smooth intensity-dependent ratios. The log 2(Hy3/Hy5) intensity data were uploaded into GeneSpring v7.3 for two-way analysis of variance (factors = cell-line and second treatment), using a parametric test with variances assumed equal, α cutoff (p = 0.05) to generate a heat-map through bi-directional hierarchical clustering (31, 32).

TLR-2 mRNA and miR-105 Real-time PCR

Total RNA was extracted from cultured cells using TRIzol reagent (Invitrogen). The isolated total RNA samples were used for first strand cDNA synthesis with specific miR-105 hairpin loop primers (Applied Biosystems, Foster City, CA). Real-time PCR was performed by using 1 ng of cDNA with an miR-105-specific primer and probe on an ABI 7500 system (Applied Biosystems) in the presence of TaqMan DNA polymerase. The data were analyzed by normalizing miRNA level to miRNA RNU48 (small nucleolar RNA used as internal control, which has least variability across the cell types and challenges). For TLR-2 mRNA quantification, the total RNA was converted to single-stranded cDNA using a cDNA archive kit (Applied Biosystems) and 100 ng of cDNA to quantify TLR-2 mRNA using the TaqMan method (Applied Biosystems). Glyceraldehyde-3-phosphate dehydrogenase was the internal control, and –fold increase was calculated as described (33).

Transfection of miRNA

Epithelial cells were transfected with 100 pmol of miR-105 mimic (UCAAAUGCUCAGACUCCUGUGGU) and miR-105 inhibitor (AGTTTACGAGTCTGAGGACACCA) (Dharmacon, CA) and co-transfected with 100 pmol of small interference RNA control, labeled with 6-carboxyfluorescein to monitor transfection efficiency. The transfection reaction was performed using FuGENE 6 reagent (Roche Applied Science). Cells were challenged with P. gingivalis/FSL-1 for 24 h following transfection.


The cells were seeded onto collagen-coated chamber glass slides (Lab-TekTM II Chamber Slide®, Nalgene Nunc International, Rochester, NY). At 50–60% confluence, the cells were transfected either with miR-105 mimic or miR-105 inhibitor or with scrambled small interference RNA using FuGENE 6 transfection reagent as described above. The transfection reaction was performed for up to 24 h and replaced with fresh medium. The challenge assay was performed after 48 h of transfection with FSL-1 (0.5 μg/ml, InvitroGen), they were fixed in 4% paraformaldehyde, permeabilized, and stained with anti-human TLR-2 antibody overnight at 4 °C followed by Alexa Fluor® 488 anti-mouse IgG in 3% bovine serum albumin (1/500, InvitroGen) for 1 h at room temperature and SYTO® 83-orange for 15 min. The stained cultures were photographed using a Confocal Laser Scanning Microscope (FV500, Olympus, Melville, NY).

Western Blotting

Total protein was extracted from cells using radioimmune precipitation assay buffer after 24 h of challenge. The Western blot was performed by loading 25 μg of total proteins on to each lane. Blotted membranes were blocked using 5% nonfat milk and incubated at 4 °C overnight in anti-TLR-2 antibody (Cell Signaling Technology, Danvers, MA). The membranes were washed and incubated in anti-mouse IgG conjugated with horseradish peroxidase (Cell Signaling Technology) secondary antibody and signal was developed using ECL plusTM Western blotting detection reagent (Amersham Biosciences). The ratiometric analysis of band intensity was calculated using FluorChem HD software (Alpha Innotech).

Luciferase Reporter Assay

The putative miRNA-105 target site of 52 bp within the 3′-UTR region of human TLR-2 mRNA (Ensembl transcript ID: ENST 00000260010) were synthesized with flanking SpeI and HindIII restriction enzyme sites. In addition, the primers with their putative binding site mutated, were also synthesized from Integrated DNA Technologies Inc. (sense primers: 5′-gctgactagtCATAGATGATCAAGTCCCTTATAAGAGTGGCATAGTATTTGCATATAACaagcttggac-3′; antisense primer: 5′-gtccaagcttGTTATATGCAAATACTATGCCACTCTTATAAGGGACTTGATCATCTATGactagtcagc-3′; mutated sense primer: 5′-gctgactagtCATAGATGATCAAGTCCCTTATAAGAGTGGCATAGTCATATAACaagcttggac-3′; and mutated antisense primer: 5′-gtccaagcttGTTATATGACTATGCCACTCTTATAAGGGACTTGATCATCTATGactagtcagc-3′). The sense and antisense strands of the oligonucleotides were annealed (34). The annealed oligonucleotides were digested with SpeI and HindIII and ligated into the multiple cloning site of the pMIRREPORT Luciferase vector (Ambion, Inc.). The post-transcriptional regulation of pMIRREPORT luciferase vector was potentially regulated by miRNA interactions with the TLR-2 3′-UTR. We then transfected cultured HEK293 cells with each of these reporter constructs (pMIR-TLR2 or pMIR-mutTLR-2), as well as co-transfecting them with pMIF-cGFP-Zeo-miR-105 (pMIF-miR-105) plasmid (System Biosciences) following transfection with FuGENE 6 as noted above. Luciferase expression was assessed by confocal microscopy 24 h after transfection by use of anti-Luciferase antibody (Abcam). The protein extract from the transfected cells was collected using radioimmune precipitation assay buffer and equal amounts of protein were tested by a Luciferase activity assay kit following the manufacturer's instructions (Stratagene).

Statistical Analysis

The microarray statistical analysis is detailed under “miRNA Array Profiling/Analysis” above. The mRNA -fold increase data were calculated according to the ΔΔCT method (33). Cytokine data were evaluated by analysis of variance using the InStat program (GraphPad, San Diego, CA) with Bonferroni corrections applied. Statistical differences were declared significant at p < 0.05 level. Statistically significant data are indicated by asterisks (p < 0.05 (*), p < 0.01 (**), and p < 0.001 (***)).


MiR-105 Is Up-regulated in Human Gingival Keratinocytes with a Diminished Inflammatory Response

We hypothesized that miRNAs may play a role in innate immune response variation (25) and could differentiate periodontitis disease-susceptible and disease-resistant subjects. From a bank of over 30 primary cell cultures of human gingival epithelial cells (HGECs) (2) we selected cultures having a diminished cytokine response type and “normal” response type as reported previously. Briefly, the rule specification for the latter selected cells that up-regulated IL-6 and TNF-α production by at least 2-fold after 4-h challenge with TLR agonists, and the rule for the former (diminished) phenotype was no significant increase in pro-inflammatory cytokine production after challenge. We thus tested in depth the 3 diminished cytokine response primary cultures against 3 representatives of the normal HGEC type chosen from the median of the range of the 13 available cultures (2).

We performed chip-based miRNA profiling from normal and diminished cytokine response cells challenged with heat-inactivated P. gingivalis, a TLR-2 and TLR-4 agonist. The data were deposited in the Gene Expression Omnibus data base under the platform GPL7423 and series GSE13042 (www.ncbi.nlm.nih.gov/geo). In the preliminary statistical analysis, the normalized miRNA data were analyzed by two-way analysis of variance (phenotype, treatment, and interaction) for all miRNA chips. Of the 600 miRNA species tested on the platform, 95 miRNAs were significantly different between phenotypes and 45 between treatments. Among the 109 miRNAs that were differentially expressed only 26 were well annotated. These 26 were significantly altered by challenge with heat-inactivated P. gingivalis when compared with unstimulated cells (p = 0.0038). The miR-105 signal was markedly down-regulated in normal versus diminished cells after TLR agonist challenge (Fig. 1A) (p = 0.0017).

Normal and diminished cytokine response cells were challenged with heat-inactivated P. gingivalis (strain 33277) at 100 multiplicity of infection for 24 h, and RNA was miRNA microarray profiled using the miRCURY LNA Array (Exiqon). The heat map shows ...

In silico analyses revealed 1060 hits for miR-105 targets and predicted complimentarity to TLR-2 (Fig. 1C). Because we noted miR-105 up-regulation in the diminished cytokine response cells, we constructed a computational matrix for miR-105 targets, which revealed 37 potential mRNA targets across species. In matrix, hsa-miR-577 and hsa-miR-19b were also differentially expressed between normal and diminished cells but to a lesser degree than miR-105 (see dotted box in Fig. 1A). Numerical expression values were plotted to show the difference between normal and diminished cell types (Fig. 1B). For this reason, we focused on miR-105.

TLR-2 mRNA Up-regulation Correlates with Pro-inflammatory Cytokines in Gingival Keratinocytes

Because P. gingivalis signals through both TLR-2 and TLR-4 (2, 35) we evaluated TLR-2 mRNA by quantitative real-time PCR after challenging both cell types with FSL-1, a specific agonist to TLR-2. Analysis of TLR-2 mRNA abundance between phenotypes revealed a 2.5-fold up-regulation with P. gingivalis challenge and a 4.5-fold up-regulation with FSL-1 challenge relative to the unstimulated control (p = 0.001) (Fig. 2A). In striking contrast, diminished cytokine response cells did not show this up-regulation (Fig. 2A). TLR-2 induction upon P. gingivalis or FSL-1 stimulation is consistent with TLR-2 recognition of P. gingivalis (36, 37). Furthermore, IL-6 cytokine protein levels corresponded to corresponding mRNA levels. Normal response cells up-regulated their IL-6 (Fig. 2B) and TNF-α (Fig. 2C) production following P. gingivalis or FSL-1 challenge, and again this response was not evident in diminished response cells (Fig. 2, B and C). We also explored IL-12p40 secretion in the gingival epithelial cells after P. gingivalis and FSL-1 challenge. The primary gingival epithelial cells do not secret IL-12p40.3 This has to be further verified and hence not included in the present study.

TLR-2 gene, IL-6, and TNF-α cytokine expression in both normal type and diminished cytokine response cells. Human gingival keratinocytes were challenged with heat-inactivated P. gingivalis (100 MOI) or FSL-1 (1 μg/ml) for 24 h. Total RNA ...

Modulation of TLR-2 Protein Expression by miR-105

Confirmation of the differential expression of miR-105 was sought by a non-array method. The real-time PCR data indicated an 8-fold up-regulation of miR-105 following P. gingivalis challenge, and an 11-fold increase following FSL-1 challenge, in diminished-response cells relative to an internal benchmark, miRNA RNU48 (Fig. 3, A and B). Consistent with the microarray data, the normal response cells did not show significant up-regulation of miR-105 (Fig. 3).

miR-105 and TLR2 expression in normal and diminished cytokine response cells. The cells were subjected to P. gingivalis and FSL-1 treatment for 24 h and quantitated the miR-105 expression and Western blot for TLR-2. Total RNA was amplified with specific ...

Search of the open miRNA data base revealed over 1060 potential target transcripts for miR-105. These potential target genes were loaded onto Ingenuity pathway analysis (Ingenuity Systems Inc.) software to discover the most significant pathways associated with the global miR-105 target genes. This analysis revealed a preponderance of immune diseases (data not shown) and identified TLR-2 as one of the important targets. Because microarray profiling revealed miR-105 as the most significant miRNA discriminating between normal and diminished HGEP phenotypes, we tested for evidence that miR-105 expression would down-regulate TLR-2 as well as pro-inflammatory cytokines in the 3 selected cell types, as well as across the broader panel of 13 HGECs available. This analysis revealed a generalized, strong inverse correlation between TLR2 protein and miR-105 gene expression (Fig. 3, B and C).

We next sought to determine whether miR-105 directly modulated TLR-2 mRNA and/or protein expression in HGECs. To test this, we transfected miR-105 mimic (same sequence as mature miR-105) and miR-105 antagomir (sequence complementary to miR-105, which blocks its effect) to diminished cytokine cell phenotypes. After miR-105 transfection, the cells were challenged for 24 h with either heat-inactivated P. gingivalis or FSL-1. The diminished cytokine response cells transfected with miR-105 antagomir up-regulated the TLR-2 protein levels in either challenge (Fig. 4A) compared with mock transfected cells. This indicates a role for miR-105 in modulating TLR-2 protein expression and implies a post-transcriptional repression of TLR-2 translation. However, the miR-105 antagomir control cells expressed higher TLR-2 protein versus non-transfected cells. This implies a role for miR-105 in modulating basal receptor expression, an inference supported by the correlation of TLR-2 and miR-105 (Fig. 3, B and C). Evidence for a functional relationship was sought by transfecting miR-105 antagomir into diminished cytokine response cells challenged with P. gingivalis and FSL-1. This scenario induced significantly higher IL-6 and TNF-α compared with mock control, confirming that miR-105 overexpression is biologically relevant (Fig. 4, C and D). Because we previously showed that P. gingivalis activates NF-κB (38) and induces cytokines (39), the induction of IL-6 in miR-105 mimic and antagomir-transfected cells was further verified by measuring NF-κB activity by modified electrophoretic mobility shift assay technique (FACE kit, ActifMotif). The miR-105 inhibitor-transfected cells exhibited increased NF-κB activity upon P. gingivalis and FSL-1 ligand challenge (data not shown). The normal cell phenotype transfected with miR-105 mimic down-regulated NF-κB activation after P. gingivalis or FSL-1 challenge suggesting that miR-105 induction is dependant on NF-κB.

The level of TLR-2 protein by Western blot after transfecting miR-105 antagomir. The diminished type cells transfected with miR-105 antagomir up-regulated TLR-2 protein expression upon TLR-2 agonist challenge (A). The ratio metric analysis (β-Actin/TLR-2) ...

MiR-105 Modulated Surface TLR-2 Expression

The functional relationship was further confirmed by Western blot for TLR-2 and immunohistochemistry after inhibiting miR-105. Overexpression of miR-105 mimic in normal cells challenged with FSL-1 suppressed TLR-2 protein levels compared with scrambled miRNA target or mock transfection (Fig. 5A). We then sought to determine the effect of reducing the miR-105 levels by transfecting miR-105 antagomir into the cell type with miR-105 up-regulation. Lysates of cells challenged with FSL-1 had increased TLR-2 protein (Fig. 5B). The antagomir control had increased TLR-2 protein level confirming our TLR-2 mRNA observations (Fig. 3A), which correlated with the expression of miR-105.

The expression of TLR-2in epithelial cells following miR-105 mimic and antagomir transfection. The normal cells were transfected with miR-105 mimic, and diminished cells were transfected with miR-105 antagomir and challenged with FSL-1 (1 μg/ml) ...

Surface expression of TLR-2 immunoreactivity was confirmed by confocal microscopy. TLR-2 expression was down-regulated in cells transfected with miR-105 mimic and challenged with FSL-1 (Fig. 6D). In contrast, TLR-2 expression was retained in cells transfected with miR-105 antagomir (Fig. 6C). This confirmed that miR-105 up-regulation suppressed TLR-2 protein expression on the cell surface. These data are consistent with observations of another miRNA, let-7i, and the link between surface TLR-4 expression, NF-κB activation, and cytokine modulation.

Surface expression of TLR-2 in gingival keratinocytes. Normal cells transfected with either miR-105 mimic or antagomir and stained with antiTLR-2 antibody-clone TL2.3 (eBiosciences) with proper Isotype control (Mouse IgG2a). TLR-2 was detected by immunohistochemistry ...

To test if we had predicted correctly the binding site for miR-105 on TLR-2, miR-105 binding to the 3′-UTR of TLR-2 was assessed by cloning a putative cognate 22-bp fragment from 332 bp away from the stop codon (Ensembl transcript ID: ENST00000260010) to the multiple cloning site located at the 3′-UTR of the Luciferase reporter gene in pMIRREPORTER. A mutant vector was also constructed by deleting the predicted AGTTTA binding site of miR-105 and cloning the fragment into a multiple cloning site located in the 3′-UTR of the Luciferase reporter gene. Co-transfection of HEK293 cells with Luciferase construct (pMIR-TLR2) and a vector overexpressing miR-105 precursor (pMIF-miR-105) inhibited Luciferase activity (Fig. 7A, panel C). The mutant Luciferase vector (pMIR-mutTLR2) co-transfected with pMIF-miR-105 retained luciferase activity (Fig. 7A, panel D). Cell lysates had significantly less luciferase from samples co-transfected with pMIR-TLR2 and pMIF-miR-105 (Fig. 7B). This confirms our in silico prediction of the binding site. We may conclude that modulation of TLR-2 expression by miR-105 occurs through binding to the 3′-UTR of TLR-2 mRNA, thus inhibiting TLR-2 translation.

The putative miRNA-105 target site within the 3[prime]-UTR of human TLR-2 mRNA (Ensembl transcript ID: ENST00000260010) and a predicted binding site mutated primers were synthesized, annealed, digested with SpeI and HindIII, and ligated into the multiple ...


This study identified miR-105 as a modulator of TLR-2 protein translation in human gingival keratinocytes. There was a strong inverse correlation between cells that naturally 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.

Recently, miRNAs have been shown to fine-tune innate immune responses (40). For example, miR-146a/b was up-regulated in an NF-κB-dependent manner (21). In another study, IL-6 induced let-7a-modulated apoptosis in cholangiocytes (41) and up-regulated miR-19a and -19b while down-regulating SOCS1 (suppressor of cytokine signaling 1), a gene important in negative regulation of TLR signaling (42). The present study adds miR-105 to the panel of miRNA species known to influence innate immune function.

Human miR-105 is located on the intronic region of GABRA3A (γ-aminobutyric acid receptor 3α), which resides on the X chromosome. Certain types of tumor cells have been shown to transcribe miR-105 but lack processing machinery in the nucleus to form mature miRNA (43). It is still unclear how miR-105 is processed and exported out of the nucleus in gingival epithelial cells. Perhaps it is analogous to miR-155, which is present on the B-cell integration cluster transcript up-regulated with polyriboinosinic:polyribocytidylic acid or the cytokine interferon-β challenge. The up-regulated B-cell integration cluster transcript with miR-155 precursor undergoes processing to export mature miR-155 out of the nucleus, which suppresses the macrophage inflammatory response via c-Jun NH2-terminal kinase pathway (21).

High basal secretion of IL-6 seen in deficient cell types may be explained by multiple factors such as activation of NF-κB at the basal level or cAMP signaling. IL-6 production is not solely dependent on NF-κB, and the IL-6 gene in epithelial cells contains cAMP-responsive elements on the promoter that are important for its transcriptional regulation (35, 44).

Agonist availability and receptor compartmentalization are pivotal in regulating TLR signaling (45). TLR itself may be degraded, preventing ligand activation, or its protein expression may be inhibited (45). It has been shown that expression of TLR-4 is necessary for intestinal homeostasis (46), increases in TLR-4 are pathogenic in lupus-like autoimmune disease (47), and increased TLR-2 levels are associated with the response to vaccinia virus (48). Taken together, the receptor surface levels regulate pathogen recognition and inflammatory responses.

Up-regulation of miR-203 has been shown to inhibit the suppressor of cytokine signaling 3 (SOCS3) involved in inflammatory responses and keratinocyte function (23), repress the expression of p63-promoting differentiation of epithelium (49), and repress stemness by targeting DeltaNp63 (50). In contrast to miR-105, the TLR ligands tested did not up-regulate miR-155 in our epithelial cell model, although both miR-146 a/b were up-regulated (data not shown). This suggests that miR-155 is not involved in the down-regulation of epithelial cell cytokines, but miR-146 a/b might have a role in inhibiting IRAK1 and TRAF6 protein expression as previously observed (21).

It is unclear how miRNA-105 itself is regulated in gingival epithelial cells, because its precursor resides on intron I of the GABRA3A gene within the X chromosome and has a neurotransmitter function (51). Lithium has been used as a potent drug against affective neurological disorders (52). By inhibiting glycogen synthase kinase 3 (53), lithium invokes an anti-inflammatory response (54). The γ-aminobutyric acid receptor has been shown to inhibit immune responses of T cells, and modulation of this receptor influences T-cell responses and autoimmune diseases (55). These data also suggest that intronic regions are involved in regulating cell function.

Our diminished cytokine response cell findings reflect the observation made with TLR-2 knock-out mice (37) in that the low inflammatory response correlates with the low level of TLR-2 expression in these cells. These data also confirm other studies (21, 22, 34) showing that miRNAs may play a crucial role in modulating immune function. Although miR-105 targets TLR-2 and can induce down-regulation of cytokine production in primary epithelial cell cultures, it is unlikely that low cytokine response is solely explained by miR-105 regulation. Instead, miR-105 may play an important role in fine-tuning TLR-2 response to control excessive inflammation. Further understanding of the mechanism of miR-105 and other targets may lead to a better understanding of variations in inflammatory responses within the oral mucosa and to new anti-inflammatory therapeutics.

*This work was supported, in whole or in part, by National Institutes of Health Grant DE017384 (to D. F. K.) from the United States Public Health Service, NIDCR.

3M. R. Benakanakere, Q. Li, M. A. Eskan, A. V. Singh, J. Zhao, J. C. Galicia, P. Stathopoulou, T. B. Knudsen, and D. F. Kinane, unpublished data.

2The abbreviations used are:

Toll-like receptor
human gingival epithelial cell
interleukin 6
tumor necrosis factor α
Homo sapiens microRNA
precursor microRNA
untranslated region
suppressor of cytokine signaling 3
Pam2CGDPKHPKSF (a synthetic diacylated lipoprotein and a specific ligand for TLR-2).


1. Akira S., Uematsu S., Takeuchi O. (2006) Cell 124,783–801. [PubMed]
2. Kinane D. F., Shiba H., Stathopoulou P. G., Zhao H., Lappin D. F., Singh A., Eskan M. A., Beckers S., Waigel S., Alpert B., Knudsen T. B. (2006) Genes Immun. 7,190–200. [PubMed]
3. Akira S., Takeda K. (2004) Nat. Rev. Immunol. 4,499–511. [PubMed]
4. Bartel D. P. (2004) Cell 116,281–297. [PubMed]
5. Liew F. Y., Xu D., Brint E. K., O'Neill L. A. (2005) Nat. Rev. Immunol. 5,446–458. [PubMed]
6. Lynn D. J., Winsor G. L., Chan C., Richard N., Laird M. R., Barsky A., Gardy J. L., Roche F. M., Chan T. H., Shah N., Lo R., Naseer M., Que J., Yau M., Acab M., Tulpan D., Whiteside M. D., Chikatamarla A., Mah B., Munzner T., Hokamp K., Hancock R. E., Brinkman F. S. (2008) Mol. Syst. Biol. 4,218. [PMC free article] [PubMed]
7. Farh K. K., Grimson A., Jan C., Lewis B. P., Johnston W. K., Lim L. P., Burge C. B., Bartel D. P. (2005) Science 310,1817–1821. [PubMed]
8. Gregory R. I., Yan K. P., Amuthan G., Chendrimada T., Doratotaj B., Cooch N., Shiekhattar R. (2004) Nature 432,235–240. [PubMed]
9. Chendrimada T. P., Gregory R. I., Kumaraswamy E., Norman J., Cooch N., Nishikura K., Shiekhattar R. (2005) Nature 436,740–744. [PMC free article] [PubMed]
10. Ambros V. (2004) Nature 431,350–355. [PubMed]
11. Fritz J. H., Girardin S. E., Philpott D. J. (2006) Sci STKE 2006, pe27. [PubMed]
12. Lee Y., Kim M., Han J., Yeom K. H., Lee S., Baek S. H., Kim V. N. (2004) EMBO J. 23,4051–4060. [PMC free article] [PubMed]
13. Fazi F., Rosa A., Fatica A., Gelmetti V., De Marchis M. L., Nervi C., Bozzoni I. (2005) Cell 123,819–831. [PubMed]
14. O'Donnell K. A., Wentzel E. A., Zeller K. I., Dang C. V., Mendell J. T. (2005) Nature 435,839–843. [PubMed]
15. Pasquinelli A. E., Hunter S., Bracht J. (2005) Curr. Opin. Genet. Dev. 15,200–205. [PubMed]
16. Chen C. Z., Li L., Lodish H. F., Bartel D. P. (2004) Science 303,83–86. [PubMed]
17. Monticelli S., Ansel K. M., Xiao C., Socci N. D., Krichevsky A. M., Thai T. H., Rajewsky N., Marks D. S., Sander C., Rajewsky K., Rao A., Kosik K. S. (2005) Genome Biol. 6,R71. [PMC free article] [PubMed]
18. Esau C., Kang X., Peralta E., Hanson E., Marcusson E. G., Ravichandran L. V., Sun Y., Koo S., Perera R. J., Jain R., Dean N. M., Freier S. M., Bennett C. F., Lollo B., Griffey R. (2004) J. Biol. Chem. 279,52361–52365. [PubMed]
19. Calin G. A., Sevignani C., Dumitru C. D., Hyslop T., Noch E., Yendamuri S., Shimizu M., Rattan S., Bullrich F., Negrini M., Croce C. M. (2004) Proc. Natl. Acad. Sci. U.S.A. 101,2999–3004. [PMC free article] [PubMed]
20. Lu J., Getz G., Miska E. A., Alvarez-Saavedra E., Lamb J., Peck D., Sweet-Cordero A., Ebert B. L., Mak R. H., Ferrando A. A., Downing J. R., Jacks T., Horvitz H. R., Golub T. R. (2005) Nature 435,834–838. [PubMed]
21. Taganov K. D., Boldin M. P., Chang K. J., Baltimore D. (2006) Proc. Natl. Acad. Sci. U.S.A. 103,12481–12486. [PMC free article] [PubMed]
22. O'Connell R. M., Taganov K. D., Boldin M. P., Cheng G., Baltimore D. (2007) Proc. Natl. Acad. Sci. U.S.A. 104,1604–1609. [PMC free article] [PubMed]
23. Sonkoly E., Wei T., Janson P. C., Sääf A., Lundeberg L., Tengvall-Linder M., Norstedt G., Alenius H., Homey B., Scheynius A., Ståhle M., Pivarcsi A. (2007) PLoS ONE 2,e610. [PMC free article] [PubMed]
24. Kinane D. F. (2000) Ann. R. Australas Coll. Dent. Surg. 15,42–50. [PubMed]
25. Kinane D. F., Galicia J. C., Gorr S. U., Stathopoulou P. G., Benakanakere M. (2008) Front. Biosci. 13,966–984. [PubMed]
26. Spratt D. (2003) in Medical Biofilms: Detection, Prevention, and Control ( Jass J., Surman S., Walker J., editors. eds) pp. 175–198, Wiley and Sons, Ltd., London.
27. Kinane D. F., Hart T. C. (2003) Crit. Rev. Oral Biol. Med. 14,430–449. [PubMed]
28. Shiba H., Venkatesh S. G., Gorr S. U., Barbieri G., Kurihara H., Kinane D. F. (2005) J. Periodontal Res. 40,153–157. [PubMed]
29. Eskan M. A., Rose B. G., Benakanakere M. R., Zeng Q., Fujioka D., Martin M. H., Lee M. J., Kinane D. F. (2008) Eur. J. Immunol. 38,1138–1147. [PMC free article] [PubMed]
30. Eskan M. A., Benakanakere M. R., Rose B. G., Zhang P., Zhao J., Stathopoulou P., Fujioka D., Kinane D. F. (2008) Infect. Immun. 76,2080–2089. [PMC free article] [PubMed]
31. Eisen M. B., Spellman P. T., Brown P. O., Botstein D. (1998) Proc. Natl. Acad. Sci. U.S.A. 95,14863–14868. [PMC free article] [PubMed]
32. Singh A. V., Green M., States J. C., Knudsen T. B. (2007) Birth Defects Res. Part A. Clin. Mol. Teratol. 79,319–350.
33. Livak K. J., Schmittgen T. D. (2001) Methods 25,402–408. [PubMed]
34. Chen X. M., Splinter P. L., O'Hara S. P., LaRusso N. F. (2007) J. Biol. Chem. 282,28929–28938. [PMC free article] [PubMed]
35. Eskan M. A., Hajishengallis G., Kinane D. F. (2007) Infect Immun 75,892–898. [PMC free article] [PubMed]
36. Darveau R. P., Pham T. T., Lemley K., Reife R. A., Bainbridge B. W., Coats S. R., Howald W. N., Way S. S., Hajjar A. M. (2004) Infect. Immun. 72,5041–5051. [PMC free article] [PubMed]
37. Burns E., Bachrach G., Shapira L., Nussbaum G. (2006) J. Immunol. 177,8296–8300. [PubMed]
38. Brozovic S., Sahoo R., Barve S., Shiba H., Uriarte S., Blumberg R. S., Kinane D. F. (2006) Microbiology 152,797–806. [PubMed]
39. Sandros J., Karlsson C., Lappin D. F., Madianos P. N., Kinane D. F., Papapanou P. N. (2000) J. Dent. Res. 79,1808–1814. [PubMed]
40. Gantier M. P., Sadler A. J., Williams B. R. (2007) Immunol. Cell Biol. 85,458–462. [PubMed]
41. Meng F., Henson R., Wehbe-Janek H., Smith H., Ueno Y., Patel T. (2007) J. Biol. Chem. 282,8256–8264. [PubMed]
42. Pichiorri F., Suh S. S., Ladetto M., Kuehl M., Palumbo T., Drandi D., Taccioli C., Zanesi N., Alder H., Hagan J. P., Munker R., Volinia S., Boccadoro M., Garzon R., Palumbo A., Aqeilan R. I., Croce C. M. (2008) Proc. Natl. Acad. Sci. U.S.A. 105,12885–12890. [PMC free article] [PubMed]
43. Lee E. J., Baek M., Gusev Y., Brackett D. J., Nuovo G. J., Schmittgen T. D. (2008) RNA 14,35–42. [PMC free article] [PubMed]
44. Krueger J., Ray A., Tamm I., Sehgal P. B. (1991) J. Cell. Biochem. 45,327–334. [PubMed]
45. Miggin S. M., O'Neill L. A. (2006) J. Leukoc. Biol. 80,220–226. [PubMed]
46. Rakoff-Nahoum S., Paglino J., Eslami-Varzaneh F., Edberg S., Medzhitov R. (2004) Cell 118,229–241. [PubMed]
47. Liu B., Yang Y., Dai J., Medzhitov R., Freudenberg M. A., Zhang P. L., Li Z. (2006) J. Immunol. 177,6880–6888. [PubMed]
48. Zhu J., Martinez J., Huang X., Yang Y. (2007) Blood 109,619–625. [PMC free article] [PubMed]
49. Yi R., Poy M. N., Stoffel M., Fuchs E. (2008) Nature 452,225–229. [PubMed]
50. Lena A. M., Shalom-Feuerstein R., di Val Cervo P., Aberdam D., Knight R. A., Melino G., Candi E. (2008) Cell Death Differ. 15,1187–1195. [PubMed]
51. Bell M. V., Bloomfield J., McKinley M., Patterson M. N., Darlison M. G., Barnard E. A., Davies K. E. (1989) Am. J. Hum. Genet. 45,883–888. [PMC free article] [PubMed]
52. Rowe M. K., Chuang D. M. (2004) Expert Rev. Mol Med. 6,1–18. [PubMed]
53. Phiel C. J., Klein P. S. (2001) Annu. Rev. Pharmacol. Toxicol. 41,789–813. [PubMed]
54. Martin M., Rehani K., Jope R. S., Michalek S. M. (2005) Nat. Immunol. 6,777–784. [PMC free article] [PubMed]
55. Tian J., Chau C., Hales T. G., Kaufman D. L. (1999) J. Neuroimmunol. 96,21–28. [PubMed]

Articles from The Journal of Biological Chemistry are provided here courtesy of American Society for Biochemistry and Molecular Biology


Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...


Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...