T-helper (Th)17 cell responses are important for the development of neutrophilic inflammatory disease. Recently, we found that acetyl salicylic acid (ASA) inhibited Th17 airway inflammation in an asthma mouse model induced by sensitization with lipopolysaccharide (LPS)-containing allergens. To investigate the mechanism(s) of the inhibitory effect of ASA on the development of Th17 airway inflammation, a neutrophilic asthma mouse model was generated by intranasal sensitization with LPS plus ovalbumin (OVA) and then challenged with OVA alone. Immunologic parameters and airway inflammation were evaluated 6 and 48 h after the last OVA challenge. ASA inhibited the production of interleukin (IL)-17 from lung T cells as well as in vitro Th17 polarization induced by IL-6. Additionally, ASA, but not salicylic acid, suppressed Th17 airway inflammation, which was associated with decreased expression of acetyl-STAT3 (downstream signaling of IL-6) in the lung. Moreover, the production of IL-6 from inflammatory cells, induced by IL-17, was abolished by treatment with ASA, whereas that induced by LPS was not. Altogether, ASA, likely via its acetyl moiety, inhibits Th17 airway inflammation by blockade of IL-6 and IL-17 positive feedback.

Accurate prediction of transcription factor binding sites (TFBSs) is a prerequisite for identifying cis-regulatory modules that underlie transcriptional regulatory circuits encoded in the genome. Here, we present a computational framework for detecting TFBSs, when multiple position weight matrices (PWMs) for a transcription factor are available. Grouping multiple PWMs of a transcription factor (TF) based on their sequence similarity improves the specificity of TFBS prediction, which was evaluated using multiple genome-wide ChIP-Seq data sets from 26 TFs. The Z-scores of the area under a receiver operating characteristic curve (AUC) values of 368 TFs were calculated and used to statistically identify co-occurring regulatory motifs in the TF bound ChIP loci. Motifs that are co-occurring along with the empirical bindings of E2F, JUN or MYC have been evaluated, in the basal or stimulated condition. Results prove our method can be useful to systematically identify the co-occurring motifs of the TF for the given conditions.

RIG-I is a cytosolic receptor for non-self RNA that mediates immune responses against viral infections through IFNα/β production. In an attempt to identify novel tools that modulate IFNα/β production, we used SELEX technology to screen RNA aptamers that specifically target RIG-I protein. Most of the selected RIG-I aptamers contained polyU motifs in the second half regions that played critical roles in the activation of RIG-I-mediated IFNβ production. Unlike other known ligands, RIG-I aptamer bound and activated RIG-I in a 5′-triphosphate-independent manner. The helicase and RD domain of RIG-I were used for aptamer binding, but intact RIG-I protein was required to exert aptamer-mediated signaling activation. Furthermore, replication of NDV, VSV and influenza virus in infected host cells was efficiently blocked by pre- or post-treatment with RIG-I aptamer. Based on these data, we propose that RIG-I aptamer has strong potential to be an antiviral agent that specifically boosts the RIG-I-dependent signaling cascade.

The comprehensive identification of functional transcription factor binding sites (TFBSs) is an important step in understanding complex transcriptional regulatory networks. This study presents a motif-based comparative approach, STAT-Finder, for identifying functional DNA binding sites of STAT3 transcription factor. STAT-Finder combines STAT-Scanner, which was designed to predict functional STAT TFBSs with improved sensitivity, and a motif-based alignment to minimize false positive prediction rates. Using two reference sets containing promoter sequences of known STAT3 target genes, STAT-Finder identified functional STAT3 TFBSs with enhanced prediction efficiency and sensitivity relative to other conventional TFBS prediction tools. In addition, STAT-Finder identified novel STAT3 target genes among a group of genes that are over-expressed in human cancer cells. The binding of STAT3 to the predicted TFBSs was also experimentally confirmed through chromatin immunoprecipitation. Our proposed method provides a systematic approach to the prediction of functional TFBSs that can be applied to other TFs.

RIG-I senses intracellular virus-specific nucleic acid structures and initiates an antiviral response that induces interferon (IFN) production, which, in turn, activates the transcription of RIG-I to increase RIG-I protein levels. Upon intracellular poly(I:C) stimulation, however, the levels of RIG-I protein did not correlate with the expression patterns of RIG-I transcripts. When the ISG15 conjugation system was overexpressed, ISG15 was conjugated to RIG-I and cellular levels of the unconjugated form of RIG-I decreased. The ISGylation of RIG-I reduced levels of both basal and virus-induced IFN promoter activity. Levels of unconjugated RIG-I also decreased when 26S proteasome activity was blocked by treatment with MG132, ALLN, or Lactacystin. In the presence of MG132, ISG15 conjugation to RIG-I increased, and hence, the unconjugated form of RIG-I was reduced. In Ube1L−/− cells, which lack the ability to conjugate ISG15, basal levels of both RIG-I protein and transcripts were increased compared to those in wild-type cells. As a result, enhanced production of ISGs and enhanced IFN promoter activity in Ube1L−/− cells were observed, and the phenotype was restored to that of wild-type cells by the overexpression of Ube1L. Based on these results, we propose a novel negative feedback loop which adjusts the strength of the RIG-I-mediated antiviral response and IFN production through the regulation of RIG-I protein by IFN-induced ISG15 conjugation.