[Frontiers in Bioscience E4, 1478-1495, January 1, 2012]
MicroRNAs and other mechanisms regulate interleukin-17 cytokines and receptors
Jietang Mai1, Anthony Virtue1, Erin Maley1, Tran Tran1, Ying Yin1, Shu Meng1, Meghana Pansuria1, Xiaohua Jiang1,
Hong Wang1, Xiao-Feng Yang1
1
TABLE OF CONTENTS
1. ABSTRACT
Interleukin-17 cytokines are a family of pro-inflammatory cytokines. Our current studies found: i) IL-17 cytokines are not ubiquitously expressed, but several receptors and TRAF3IP2 are ubiquitously expressed in tissues with a few exceptions; ii) heart and vascular tissue are in the second tier of readiness to respond to IL-17 cytokine stimulation; iii) alternative transcription starting sites and alternative spliced isoforms are found in IL-17 cytokine and receptor transcripts; iv) higher hypomethylation status is associated with higher expressions of IL-17 receptors; v) the binding sites of several RNA binding proteins are found in the 3'UTRs of the mRNAs of IL-17 cytokines and receptors; and vi) numerous microRNA binding sites are statistically equivalent to that of experimentally verified microRNAs-mRNA interactions in the 3'UTRs of IL-17 cytokine and receptor mRNAs. These results suggest that mechanisms including alternative promoters, alternative splicing, RNA binding proteins, and microRNAs regulate the structures and expressions of IL-17 cytokines and receptors. These results provide an insight into the roles of IL-17 in mediating inflammation and immunity.
2. INTRODUCTION
Cardiovascular disease (CVD) remains a leading cause of fatality in well-developed countries. Despite a long held understanding and strong characterization of the traditional and non-traditional risk factors for CVD, some mechanisms of CVD onset have only recently been elucidated. As a chronic inflammatory disease, atherosclerosis and its progression involve both the adaptive and innate immune systems(1). For example, we and others reported that CD4+CD25high regulatory T cells(2-4) (a type of adaptive immune cells) and Ly6Cmid/high monocytes (a type of innate immune cells) play suppressive and promoting roles respectively, in the pathogenesis of atherosclerosis and vascular inflammation(5). Since 2003, a new lineage of CD4+RORgammat+ (retinoid-related orphan receptor gamma) T cells has been defined by its production of pro-inflammatory cytokine interleukin-17 (IL-17) and hence named T-helper 17 (Th17) cells. These cells have been found to play an essential role in promoting autoimmune diseases, inflammation(6, 7), and potentially atherosclerosis(8-11) (see our invited review(12)). Increased Th17, rather than Th1 response is associated with some vasculopathy(13), suggesting an important role for IL-17 cytokines in cardiovascular diseases. However, detailed tissue expression and regulation mechanisms of IL-17 cytokines and receptors remain poorly defined in cardiovascular and other tissues.
IL-17 cytokine family consists of six members designated IL-17A-F. IL-17 cytokine family members are highly conserved between human and mouse with homology of 62% to 88%(14) among the six members across species. The first cytokine of this family studied was IL-17A (also known as IL-17)(15, 16). Sequentially, the other five members were cloned and categorized into the IL-17 cytokine family(17-20). IL-17 cytokines are a family of pro-inflammatory cytokines implicated in numerous autoimmune and inflammatory diseases. IL-17 cytokines have found to induce expression of pro-inflammatory cytokines and chemokines including CXCL1, CXCL2, IL-6, and G-CSF(21, 22) via the activation of nuclear factor - kappaB (NF-κB) and mitogen-activated protein (MAP) kinase pathways(23, 24). It has been shown that IL-17 and IL-17F have the ability to form dimers, and the main functions of IL-17, IL-17F, and IL-17A/F are in autoimmune pathology, extracellular pathogen immunity, and neutrophil recruitment(7, 25). However, the issue of which tissues express both dimer-forming cytokines remains poorly defined.
The IL-17 receptor family is made up of five unique cytokine receptor members: IL-17RA, IL-17RB, IL-17RC, IL-17RD, and IL-17RE(26). Similar to the cytokines, IL-17 receptors between human and mouse also show a great degree of homology (68% to 90%)(14). IL-17RA and IL-17RC are the receptors for IL-17 and IL-17F, and they are the best characterized receptors among this family of cytokine receptors(27-29). IL-17RB has affinity for IL-17B and IL-17E, IL-17RE binds IL-17C, and the ligands for IL-17RD remain to be elucidated(18, 30). IL-17RA has been shown to be ubiquitously expressed but at higher levels in hematopoietic tissues(27). IL-17 has been shown to activate some of its pro-inflammatory effects via NF-κB and MAPK pathways. A component of the IL-17 receptors that is crucial for IL-17 signaling is an adaptor termed ACT1 (also known as TRAF3IP2; TRAF3 interacting protein 2), which is needed to mediate various downstream event of the IL-17 receptors(31-34). However, the issue of which tissues express receptor complexes remains poorly defined.
Despite significant progress, several important knowledge gaps exist which prevent investigators from defining the detailed roles of these molecules in inflammation and immune responses. First, how IL-17 cytokines and receptors are expressed in cardiovascular and other tissues; second, whether alternative splicing and alternative promoters regulate the structures of IL-17 cytokines and receptors; and third, whether mRNA decay proteins (AU-rich element binding proteins)(35, 36) and microRNAs(37) regulate the mRNA stability and translation of IL-17 cytokines and receptors. Using database mining techniques and statistical analysis similar to that we reported previously(38, 39), we examined the expressions of IL-17 cytokines and receptors in cardiovascular and other tissues from a panoramic viewpoint. In addition, we also examined the potential molecular mechanisms regulating the expression of these IL-17 cytokines and receptors. In depth analysis of the expression patterns of these important cytokines and receptors could prove vital in further understanding the underlying mechanism for immune responses and inflammation. This insight may provide novel avenues for innovative therapeutic treatments for pro-atherogenic inflammation and other cardiovascular diseases.
3. METHODS
3.1. Tissue expression profiles of genes encoding IL-17 cytokines, IL-17 receptors, RORC, and TRAF3IP2
Experimental data mining strategy, as we previously described(38-40) (Figure 1), was used to analyze the expression profiles of mRNA transcripts of IL-17 cytokines, IL-17 receptors, RORC, and TRAF3IP2 in cardiovascular and other tissues in humans and mice by mining experimentally verified human and mouse mRNA transcript expressions in the sequence tag (EST) databases of the National Institutes of Health (NIH)/National Center of Biotechnology Information (NCBI) Unigene (http://www.ncbi.nlm.nih.gov/sites/entrez?db=unigene)(41). Transcripts per million of genes of interest were normalized with that of house-keeping beta-actin in any given tissue to calculate the arbitrary units of the gene expression. The confidence interval of the expression variation of house-keeping genes was generated by calculating the mean and 2 times the standard deviation of the arbitrary units of three randomly selected house-keeping genes (RPS27A, GADPH, and ARHGDIA in human; Ldha, Nono, and Rpl32 in mouse) normalized by beta-actin in given tissues. If the expression variation of a given gene in the tissues was larger than the upper limit of the confidence interval (the mean plus 2 times the standard deviation) of the house-keeping genes, the high expression levels of genes in the tissues were statistically significant. Any given gene transcript, if lower than one per million, was technically presented as no expression.
3.2. Alternative spliced isoforms of IL-17 cytokines and IL-17 receptors
The presence and features of alternative promoters and alternatively spliced isoforms of each gene were examined with the AceView database of the National Institutes of Health (NIH)/National Center of Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html).
3.3. Presence of AU-rich elements and functional motifs in 3' untranslated regions of IL-17 cytokines and IL-17 receptors
The gene of interest was searched in the UTRdb (http://utrdb.ba.itb.cnr.it/search) at the Institute for Biomedical Technologies, University of Bari for the existence of functional motifs and signals in the 3' untranslated regions (3'UTR) of each mRNA. The presence of AU-rich elements in the 3'UTRs of IL-17 cytokines and receptors was searched using the AU-rich Element Containing mRNA Database (ARED 3.0) (http://brp.kfshrc.edu.sa/ARED/). AU-rich elements or AREs have been classified into three classes based on the presence and distribution of AUUUA sequence (42).
3.4. Correlation of the ratios of tissue SAH versus SAM concentrations with the expression levels of IL-17 cytokine and receptor mRNA transcripts
The concentrations of S-adenosylmethionine (SAM) levels over S-adenosylhomocysteine (SAH) levels were determined previously by Ueland's group (43-45) in tissues from adult male mice under physiological condition. The SAM and SAH levels were measured in perchloric acid extracts by high performance liquid chromatography. The SAM/SAH ratios were calculated for the current analysis based on Ueland's results (43-45). Tissue SAH and SAM concentrations and SAM/SAH ratios were used for further comparison and regression analyses. Simple linear regression analyses were performed using Sigma Plot 9.0 (Systat Software, Inc, San Jose, CA, USA) by plotting mRNA levels of individual gene against SAM/SAH ratios in seven mouse tissues including the brain, kidney, liver, spleen, heart, lung, and thymus. Multivariable regression analyses were performed to evaluate the effect of SAM/SAH ratios on the expressions of IL-17 cytokines and receptors.
3.5. MicroRNA interaction with the mRNAs of IL-17 cytokines and IL-17 receptors
The interactions of the mRNAs of genes of interest with microRNAs were examined using the Bioinformatics and Research Computing software TargetScan Release 5.1. (http://www.targetscan.org/) from the Whitehead Institute for Biomedical Research of Massachusetts Institute of Technology (MIT). The significance of microRNAs binding to the genes of interest was determined using the confidence intervals generated from the microRNAs within the Tarbase, an experimentally verified microRNA online database (http://diana.cslab.ece.ntua.gr/tarbase/)(46, 47). Briefly, human microRNAs, which were single site effective and confirmed with luciferase reporter assays, were used for establishing the intervals. Using single site effective and luciferase assay confirmed microRNAs ensures that the interactions between the microRNAs and their respective mRNA targets are specific. 27 microRNAs that met the criteria were selected and evaluated in TargetScan to construct the intervals and set the lower limit for the context values and score percentile. MicroRNAs with the context score of 70% or higher and context value of -0.22 or lower were determined to be significant.
4. RESULTS
4.1. Most of IL-17 cytokines are not constitutively expressed in the tissues examined, but several IL-17 receptors and TRAF3IP2 are ubiquitously expressed
We hypothesized that in order to keep inflammation in check, IL-17 cytokines and receptors are differentially expressed in cardiovascular and other tissues. To examine this hypothesis, a database mining method as we reported(40) was used to examined experimentally verified expression profiles of mRNA transcripts of IL-17 cytokines and receptors (Table 1). The copy number per million transcripts was calculated based on the experimental data of expression sequence tag (EST) cDNA cloning and sequencing in the NCBI UniGene database. The gene expression data were normalized by beta-actin expression data in the same tissue, thus the arbitrary units of gene expression were comparable among genes (Figure 2). Statistical significance is defined when gene expression is larger than the upper limit of the confidence interval (the mean plus 2 times the standard deviation) of the housekeeping genes. As shown in Table 2A and 2B, the expressions of six IL-17 cytokines, IL-17A-F, five IL-17 receptors, IL-17RA-E, RORC, and TRAF3IP2 (ACT1) gene transcripts were examined in 16 tissues: adrenal gland, blood, bone marrow, brain, eye, heart, intestine, kidney, lung, lymph node, pancreas, placenta, spleen, thymus, trachea, and vascular. The EST profiles for human IL-17A, human IL-17E, mouse IL-17c, and mouse IL-17e were not found in the EST NCBI UniGene database, suggesting lower abundance of these molecules than other IL-17 cytokines expressed in tissues. Of the 16 tissues examined, only a few tissues expressed IL-17 cytokines, which correlate with previous reports(15). But our analysis examined more cardiovascular inflammation-related human and mouse tissues for expression of IL-17 cytokines than previous reported. These expression patterns suggest that the non-detected IL-17 cytokines are not required for physiological functions of these tissues; and that the expressions of these non-detected IL-17 cytokines are not beneficial for physiological functions of these tissues.
Among the IL-17 cytokines that had expression (Table 2A), human IL-17D was most widely expressed, and it was found in vascular, placenta, heart, brain, pancreas, eye, and lung. IL-17D has been shown to have an important role in endothelial cell pathology; in HUVECs (Human Umbilical Vein Endothelial Cells) IL-17D upregulates pro-inflammatory cytokines IL-6 and IL-8 production and induces GM-CSF(48). Human IL-17B was expressed in placenta, heart, eye, and lung. IL-17B and IL-17D were expressed significantly in the heart. Human IL-17F and IL-17C were expressed in blood and lung, respectively. In addition, we found that Th17 cell-specific transcription factor RORC (RORgamma) was expressed in trachea, adrenal gland, brain, pancreas, thymus, kidney, lung, and intestine. The tissue expression pattern of RORC was broader than that of Th17 cytokines IL-17A and IL-17F, which was conserved evolutionally in mouse and humans. These results suggest that other factors may also be involved in the development of IL-17A- and IL-17F-secreting Th17 cells. Mouse IL-17 cytokines expressed in tissues differently from that in human tissues but the mouse tissue expression of IL-17d was similar to that in human tissues (Table 2B). In mouse, expressions of IL-17b in intestine and IL-17d in eye were statistically significant.
IL-17 receptor A (IL-17RA), IL-17RC, and TRAF3IP2 were expressed in all human tissues examined except in trachea, heart, and thymus for IL-17RA, and in lymph nodes for IL-17RC, which correlate with others findings that IL-17RA was found in human epithelial cells, fibroblast, B and T lymphocytes, stromal cells(49), and vascular endothelial cells(26). IL-17RA expressions in human bone marrow and placenta were statistically significant. IL-17RB in human kidney was expressed significantly. IL-17RC expressions in human pancreas and trachea were statistically significant. In addition, IL-17RB was expressed in 10 out of 16 tissues; IL-17E was also expressed in 9 out of 16 tissues; IL-17RD was expressed in 8 out of 16 tissues. The tissue expression patterns of IL-17 receptors and TRAF3IP2 were most conserved among mouse and human tissues. Also, in mouse statistically significant expression were found in lymph node and thymus for IL-17ra, in blood and thymus for IL-17rb, in pancreas for IL-17rc, and in pancreas and eye for IL-17rd. Expression of TRAF3IP2 was significant in human trachea while the expression of this gene in mouse was found to be significant in blood, lymph node, thymus, and lung.
4.2. Heart and vascular tissues are in the second tier of readiness to respond to IL-17 cytokine stimulation, which requires the upregulation of IL-17 receptor complex components
IL-17 and IL-17F define a new lineage of IL-17-producing CD4+ T helper (Th17) cells(50, 51). We hypothesized that functional status of IL-17 receptor complex can be different among tissues based on the expression status of IL-17 receptor complex and TRAF3IP2. Since the complex of IL-17RA and IL-17RC is required for IL-17 and IL-17F signaling(29), and TRAF3IP2 is essential for IL-17 signaling(52, 53), we divided the tissues examined into two tiers based on their expression of IL-17 receptor complexes and TRAF3IP2 (Table 3). IL-17RA/B is required for IL-17E signaling(54, 55). Tissues that express IL-17 receptor complexes (A/C or A/B) and TRAF3IP2 are placed in the first tier of "ready to go" status. Tissues that do not express TRAF3IP2 or all the receptors are placed in the second tier of "inducible" status with induction/upregulation of one or more components needed for a complete complex of IL-17 signaling (Figure 3).
Of note, in term of expressions of both IL-17RA/C complex and IL-17RA/B complex, heart was in the second tier. IL-17 signaling may participate in chronic inflammation in heart in response to stimulation by pro-inflammatory risk factors. For the expression of IL-17RA/B complex, vascular tissue was also in the second tier, suggesting that IL-17RA/B complex may be involved in acute and chronic inflammation in vascular tissue, and that IL-17RA/C complex and IL-17RA/B complex may participate in chronic inflammation in heart in response to pro-inflammatory stimuli of risk factors. Moreover, more human tissues were in the first tier than mouse tissues, suggesting that the complexes of IL-17RA/C and IL-17RA/B are more involved in the inflammation of these human tissues than in those tissues of mouse. In the most of the first tier tissues in human including placenta, adrenal gland, brain, pancreas, eye, kidney, lung, and intestine, the expressions of IL-17RA/C and IL-17RA/B signaling pathways were overlapped, which may suggest the assurance of function of IL-17 signaling in these tissues.
4.3. Alternative promoter and alternative splicing regulate the structures and expressions of IL-17 cytokines and receptors
Recent findings justify a renewed interest in alternative splicing, which affects the expression of 60% of human genes. Alternative splicing explains how a vast mammalian proteomic complexity is achieved with a limited number of genes(56). Alternative splicing regulation not only depends on the interaction of splicing factors with splicing enhancers and silencers in the pre-mRNA, but also on the coupling between transcription and splicing. This coupling is possible because splicing is often co-transcriptional, and promoter identity and occupation may affect alternative splicing(57). Due to the lack of expression data for each of the alternatively spliced isoforms of IL-17 cytokines and IL-17 receptors in the database, we focused on the roles of alternative splicing in regulating the structure of IL-17 cytokines and IL-17 receptors. We hypothesized that alternative promoter and alternative splicing regulate the structure of IL-17 cytokines and the receptors. To test this hypothesis, we examined the AceView-NCBI database, the NIH-supported, most comprehensive database of alternative promoters and alternatively spliced isoforms of genes based on experimental data of cDNA cloning and DNA sequencing analysis of tissue mRNA transcriptomes(58). As shown in Table 4A and 4B, human IL-17 and mouse IL-17 had no alternatively spliced isoform, suggesting the functional intolerance for structural variations of these molecules. In contrast, other human IL-17 cytokines and mouse IL-17 cytokines had numerous isoforms. Human IL-17B, IL-17D, and IL-17F had alternative promoters, suggesting that the importance of alternative promoters of IL-17 cytokines in response to tissue-specific and/or stimulation-specific transcriptional regulation(Figure 4). Human IL-17RA (18 isoforms), IL-17RC (26 isoforms), and IL-17RD (4 isoforms) had more than three open reading frames (ORFs). These results suggest that alternative splicing plays more important roles in regulating the structures of IL-17 receptors than regulating the structures of IL-17 cytokines, which may serve as a compensatory mechanism since IL-17 receptors were more widely expressed than IL-17 cytokines in the tissues examined. Future work is needed to determine whether pro-atherogenic risk factors regulate alternative splicing and alternative promoters.
4.4. Higher hypomethylation status is positively associated with higher expressions of IL-17 receptors and lower expression of IL-17d in mouse tissues
Previously, it has been shown that epigenetic changes at the IL-17A/F locus are associated with Th17 differentiation(59). To demonstrate the possibility that the expressions of IL-17 cytokines and receptors are regulated by intracellular metabolic stimuli, we hypothesized that the expressions of IL-17 cytokines and receptors are under the regulation of methylation/demethylation, a major metabolic stress-related epigenetic modification(60). As we discussed in our invited review(61), the ratio of S-adenosylmethionine (SAM) levels over S-adenosylhomocysteine (SAH) levels is an important metabolic indicator of cellular methylation status (Figure 5A)(62, 63). To test this hypothesis, we summarized tissue concentrations of SAH and SAM and the ratio of SAM over SAH in seven mouse tissues including brain, heart, kidney, liver, lung, and thymus(39), which were reported previously by Ueland's group(43-45) (Table 5). In this study, we used SAH and SAM data generated by this group for the consideration of methodology consistency as we reported(39). We performed multivariable regression analyses to determine the effect of cellular methylation indicated by the SAM/SAH ratio on the expressions of IL-17 cytokines and receptors. As shown in Figure 5B, the SAM/SAH ratios negatively correlated with the expression levels of five IL-17 receptors and traf3ip2, especially with those of IL-17rc and IL-17re (p<0.05). The SAM/SAH ratios did not correlate with the expressions of cytokines IL-17a, IL-17e (IL-25), IL-17f, and RORgamma (RORC). However, the SAM/SAH ratios were somehow either positively or negatively correlated with the expressions of cytokines IL-17d (p<0.7196) and IL-17b (p<0.2739), respectively. These results suggest that higher cellular hypomethylation status as judged by the lower methylation status (SAM/SAH ratios) is positively associated with higher expressions of IL-17 receptors and lower expression of IL-17d.
4.5. RNA binding proteins may regulate the mRNA stability and translation of IL-17 cytokines and receptors
The results from tristetraprolin (TTP) knock-out mice and other studies suggest that TTP targets pro-inflammatory cytokine tumor necrosis factor (TNF)-alpha for decay in the exosome complex(54) via specific binding to AU-rich element(42) in the 3'UTR of TNF-alpha(35, 64). Since both TNF-alpha and IL-17 are pro-inflammatory cytokines, we hypothesized that mRNA stability mechanisms may regulate the mRNA stability of IL-17 cytokines and receptors. Using web-based AU-rich element mRNA database(65), we analyzed all the mRNA 3'UTRs of IL-17 cytokines and IL-17 receptors in the most comprehensive UTR database UTRdb (http://utrdb.ba.itb.cnr.it/search) (Table 6). As shown in Table 6, human IL-17A was the only molecule that contains an AU-rich element in the 3'UTR. In addition, other binding motifs for RNA binding proteins were found in some 3'UTRs of IL-17 cytokines and receptors. For example, Mos-PRE (Musashi Binding Element), which regulates the temporal order of mRNA translation(66), was found in the 3'UTR of human IL-17A mRNA. The GY-BOX (GTCTTCC)(67) was found in the 3'UTRs of human IL-17RB, IL-17RD, IL-17RE, and mouse IL-17rd mRNAs, respectively. Bearded (BRD)-BOX (AGCTTTA)(68) was found in the 3'UTRs of mouse IL-17a and IL-17d. BRD boxes and GY box confer negative regulatory activity on heterologous transcripts in vivo. UNR-bs (Upstream of N-ras Binding Site)(68) was found in the 3'UTR of mouse IL-17f and K-BOX (cTGTGATa)(69) was found in mouse IL-17rd. These results suggest that various RNA binding proteins may participate in regulating mRNA stability of IL-17 cytokines and receptors(36).
4.6. MicroRNAs may regulate the mRNA stability and translation of IL-17 cytokines and receptors independently or via interaction with RNA binding protein-mediated mechanism
MicroRNAs (miRNAs or miRs) is a newly characterized class of short (18-24 nucleotide long)(70), endogenous and non-coding RNAs, which contribute to the development of particular disease states through the regulation of diverse biological processes such as cell growth, differentiation, proliferation, and apoptosis(37). This regulation occurs through base-pairing predominately with messenger RNAs (mRNAs) at the 3'UTR (71, 72), and leads to target mRNA cleavage and degradation or inhibition of mRNA translation(73). Sequence analysis identified miR-16 as possessing complementary sequence to the canonical AUUUA and demonstrated a role for this microRNA in interaction with the AU-rich element(74). Since we found an AU-rich element in the 3'UTR of human IL-17A, we hypothesized that mRNAs of IL-17 cytokines and receptors contain the structures in their 3'UTR for microRNA binding and regulation (Table 6). To examine this hypothesis, we used the online microRNA target prediction software, TargetScan (http://www.targetscan.org/) developed in MIT. The rationale for the use of this prediction database is presented in the discussion. To ensure that the predicted microRNAs have the binding quality equivalent to that of the experimentally verified microRNAs, we hypothesized that experimentally verified microRNAs have certain shared binding features between microRNAs and targeted 3'UTRs of mRNAs that are reflected in the context value and context percentage. To test this hypothesis, the confidence intervals for context value (the mean � 2 x SD = -0.25 � 0.12) and that for context percentage (76.07 � 19.07) were generated, respectively, from the 45 interaction between 27 experimentally verified human microRNAs and 36 different genes (not shown) within the Tarbase, an online database of experimentally verified microRNAs (http://diana.cslab.ece.ntua.gr/tarbase/)(46, 47). These human microRNAs were confirmed using luciferase reporter assays and had effectively targeted a single unique mRNA sequence.
Using the microRNA target prediction software TargetScan, 909 microRNA binding sites were found in the 3'UTRs of the mRNAs of IL-17 cytokines and receptors. Using the confidence intervals of context value and context percentage, 125 microRNAs out of total predicted 909 microRNAs (125/909=13.75%) were selected to target the mRNAs of IL-17 cytokines and IL-17 receptors except IL-17RC (Table 7 and 8) with the binding quality equivalent to that of the experimentally verified microRNA-mRNA binding sites. The results suggest that the statistical confidence intervals are highly selective for the qualified microRNA-mRNA bindings. Among 125 high quality microRNAs, 39 selected microRNAs were found to target human IL-17A. Eight human IL-17A-targeting microRNAs, including miR-129-3p, miR-30b, miR-30c, miR-548a-5p, miR-548i, miR-548n and miR-938, targeted the same/nearby sequence region, bases 234-253 of the 3'UTR of human IL-17A. Similarly, three out of eight microRNAs targeted to the same sequence region (bases 216-225) in the 3'UTR of human IL-17C, and six out of nine microRNAs targeted to the same sequence region (bases 167-175) in 3'UTR of human IL-17F. These results suggest that the same sequence region in the 3'UTR of the mRNAs of IL-17 cytokines and receptors can be targeted by several different microRNAs, and that these "hot spots" in the 3'UTRs of mRNAs may be important for microRNA-mediated post-transcriptional regulation of IL-17 cytokine and receptor expression. In addition, some microRNAs were found to target more than one mRNA. For example, miR-129 targeted human IL-17A, IL-17D, and IL-17RB; miR-383 targeted human IL-17A and IL-17RD; and miR-1248 targeted human IL-17A and IL-17RD. This finding correlated well with others' report that some microRNAs have numerous mRNA targets(75, 76). Furthermore, our analysis on experimental reports showed that 10 microRNAs, that target IL-17 cytokines and receptors, also targeted the mRNAs involved in cardiovascular disease, inflammatory molecule mRNAs, and cancer-related mRNAs (Table 9). The results suggest that signaling pathways regulating the expression and translation of IL-17 cytokines and receptors may be related to pathogenic processes of cardiovascular disease, inflammation, and cancer.
5. DISCUSSION
IL-17 cytokines are a family of pro-inflammatory autoimmune cytokines(also see our invited review(12)). Despite significant progress, several important knowledge gaps exist which prevent investigators from defining the detailed roles of these molecules in inflammation and immune responses. Our current studies have made the following findings: i) most IL-17 cytokines are not constitutively expressed in the 16 tissues examined, but several IL-17 receptors and TRAF3IP2 are ubiquitously expressed with a few exceptions, suggesting the upregulation of IL-17 cytokines in response to pro-inflammatory stimuli is one of the major mechanisms for IL-17 signaling; ii) heart and vascular tissue are in the second tier of readiness to respond to IL-17 cytokine stimulation, which require the upregulation of IL-17 receptor components; iii) alternative promoters and alternative spliced isoforms are found in the transcripts of IL-17 cytokines and receptors, suggesting that tissue-specific and stimulation-specific alternative promoters and alternative splicing regulate the structures and expressions of IL-17 cytokines and receptors; iv) Higher hypomethylation status as judged by the lower SAM/SAH ratios is positively associated with higher expressions of several IL-17 receptors and lower expression of IL-17d in mouse tissues, suggesting that the expression of these molecules is also regulated by epigenetic methylation mechanism; v) An AU-rich element is found in the 3'UTR of human IL-17A and the binding sites of several RNA binding proteins are found in the 3'UTR of IL-17 cytokines and receptors, suggesting that RNA binding proteins may regulate the mRNA stability and translation of IL-17 cytokines and receptors; and vi) using the statistical confidence intervals generated with experimentally verified microRNA-mRNA binding sites, 125 binding sites in the mRNAs of IL-17 cytokines and receptors for qualified microRNAs to target were selected out of the 909 total predicted binding sites. The finding of microRNA binding sites in the 3'UTR of IL-17 cytokines and receptors statistically equivalent to that of experimentally verified microRNAs-mRNA interaction suggests that microRNAs may regulate the mRNA stability and translation of IL-17 cytokines and receptors. Of note, the microRNA-mediated regulations of mRNA stability of IL-17 cytokines and receptors are realized independently or via interaction with RNA binding protein-mediated mechanism.
It is worth to point out that the expression data retrieved from the expression sequence tag (EST) database analyzed in this study are more precise than that detected with traditional approaches including Northern blot analysis and PCR analysis due to the un-biased cDNA cloning and DNA sequencing procedures of EST database deposits(77). Thus, the expression patterns of IL-17 cytokines and receptors are experimentally based and precise.
Alternative promoters play an important role for gene transcription in response to tissue/cell-specific, and/or stimulation-specific transcription signaling(78). One of the best examples about multiple promoter usage is fibroblast growth factor-1 (FGF1) transcription, which is controlled by at least four distinct promoters in a tissue-specific manner. The 1.A and 1.B promoters of FGF1 are constitutively active in their respective cell types. In contrast, different biological response modifiers, including serum and transforming growth factor-beta, can induce the 1.C and 1.D promoters of FGF1(78). Identification of alternative promoters in human IL-17B, IL-17D, and IL-17F genes suggests that the transcription of these three human IL-17 cytokines may be under regulation of tissue-specific and/or stimulation-specific transcription signaling.
Post-transcriptional regulation controls the abundance, turnover, and translation of mRNA and offers the capacity to integrate signal transduction events with very rapid changes in gene expression during cellular differentiation, which can be realized via different mechanisms including RNA binding proteins such as Tristetraprolin family proteins and microRNAs(79). Previous report showed that mitogen-activated protein kinase (MAPK) stabilizes mRNAs through the inhibition of stabilizing proteins such as tristetraprolin. Tristetraprolin binds to AU-rich elements in mRNA transcripts and delivers them to the exosome complex, where they are degraded(54). Identification of AU-rich element in the 3'UTR of human IL-17A mRNA suggest that the mRNA stability of human IL-17A may be under regulation of tristetraprolin-activated MAPK pathway.
RNA binding proteins may also interact with microRNAs through mechanisms that are not fully understood, and there is evidence that both mechanisms can target the same mRNA(80). MicroRNAs are a newly characterized class of short (18-24 nucleotide long)(70), endogenous, and non-coding RNAs, which are processed by nuclear RNase Drosha and cytosolic RNase Dicer. MicroRNAs are capable of controlling complex biological functions through post-transcriptional gene silencing(73). A recent report showed that miRNA-326 promotes Th-17 cell differentiation by targeting Ets-1, a negative regulator of Th-17 cell differentiation(81), suggesting a possibility that IL-17 cytokines and receptors are under regulation of microRNAs. However, the issue of whether microRNAs regulate the expression of IL-17 cytokines and receptors remains unknown. Using the most widely used target prediction program TargetScan (http://www.targetscan.org/) (82-84), we predicted a list of microRNAs that could target the 3'UTRs of IL-17 cytokines and receptors mRNAs. We hypothesized that experimentally verified microRNAs have certain shared binding features between the microRNAs and the targeted 3'UTRs of mRNAs that are reflected in the context value and context percentage, which can further be analyzed with statistical methods. By examining this hypothesis, the confidence intervals were generated, which allowed us to identify the microRNAs with the binding features statistically equivalent to that of experimentally verified microRNA-mRNA interaction. In our study, introduction of statistical method to generate the confidence intervals of experimentally verified microRNA-mRNA binding features sort out a small portion of high quality microRNAs among total predicted ones and significantly improves our prediction. Our result suggest that microRNAs as a new mechanism may regulate the mRNA stability and translation of IL-17 cytokines and receptors. This software was used in this study based on the following rationales: first, this software includes conserved and poorly conserved miRNAs; second, it individually ranks microRNA-target mRNA binding efficacy; and third, this software is the most widely used target prediction program(82-84). Of note, some microRNAs that we predicted for targeting the mRNAs of IL-17 cytokines and receptors are well-characterized. Our data showed that miRNA-21 is found to target human IL-17RD. Previous reports showed that miRNA-21 has been validated as a bona fide oncogene, which decreases apoptosis, promotes survival and proliferation. In addition, one of the potential targets of miRNA-21 is IL-12p35, a subunit of IL-12, suggesting that miRNA-21 may regulate inflammation and type 1 T helper cell (Th1) polarization(85). Previous report also showed that miRNA-221/222 inhibits angiogenesis(86). Our results showed that miRNA-221/222 may inhibit human IL-17RB expression, implying that IL-17RB promotes angiogenesis. Moreover, previous report showed that miRNA-146 regulates several inflammatory pathways as part of a negative feedback(85). Our results suggest that miRNA-146 may inhibit human IL-17A expression, which correlated well with the previous studies. Finally, previous report showed that miRNA-155 promotes regulatory T cell development and suppresses excessive inflammation(85). Our results suggest that miRNA-155 may inhibit human IL-17RB expression, which correlated well with the previous studies. Taken together, our results correlated well with the previous reports for some well-characterized microRNAs with the function in regulating inflammation. In addition, eight human microRNAs, that target IL-17 cytokines and receptors, also targeted cardiovascular disease molecule mRNAs, inflammatory molecule mRNAs, and cancer-related mRNAs. In conclusion, as shown in our working model (Figure 6), our results suggest that microRNAs and other mechanisms regulate the expression, structure, and translation of IL-17 cytokines and receptors. These findings provide an insight into pathogenic processes of cardiovascular disease, inflammation, and cancers.
7. ACKNOWLEDGEMENTS
Anthony Virtue, Erin Maley, and Tran Tran made equal contributions to this work. This work was partially supported by the National Institutes of Health Grants HL094451 (XFY), HL67033, HL82774, and HL77288 (HW).
8. REFERFENCES
1. Packard, R. R., A. H. Lichtman & P. Libby: Innate and adaptive immunity in atherosclerosis. Semin Immunopathol, 31, 5-22 (2009)
doi:10.1007/s00281-009-0153-8
PMid:19449008 PMCid:2823132
2. Ait-Oufella, H., B. L. Salomon, S. Potteaux, A. K. Robertson, P. Gourdy, J. Zoll, R. Merval, B. Esposito, J. L. Cohen, S. Fisson, R. A. Flavell, G. K. Hansson, D. Klatzmann, A. Tedgui & Z. Mallat: Natural regulatory T cells control the development of atherosclerosis in mice. Nat Med, 12, 178-80 (2006)
doi:10.1038/nm1343
PMid:16462800
3. Xiong, Z., J. Song, Y. Yan, Y. Huang, A. Cowan, H. Wang & X. F. Yang: Higher expression of Bax in regulatory T cells increases vascular inflammation. Front Biosci, 13, 7143-55 (2008)
doi:10.2741/3217
PMid:18508723 PMCid:2915779
4. Xiong, Z., Y. Yan, J. Song, P. Fang, Y. Yin, Y. Yang, A. Cowan, H. Wang & X. F. Yang: Expression of TCTP antisense in CD25 (high) regulatory T cells aggravates cuff-injured vascular inflammation. Atherosclerosis, 203, 401-8 (2009)
doi:10.1016/j.atherosclerosis.2008.07.041
PMid:18789801 PMCid:2695670
5. Zhang, D., X. Jiang, P. Fang, Y. Yan, J. Song, S. Gupta, A. I. Schafer, W. Durante, W. D. Kruger, X. Yang & H. Wang: Hyperhomocysteinemia promotes inflammatory monocyte generation and accelerates atherosclerosis in transgenic cystathionine beta-synthase-deficient mice. Circulation, 120, 1893-902 (2009)
doi:10.1161/CIRCULATIONAHA.109.866889
PMid:19858416 PMCid:2783582
6. Fouser, L. A., J. F. Wright, K. Dunussi-Joannopoulos & M. Collins: Th17 cytokines and their emerging roles in inflammation and autoimmunity. Immunol Rev, 226, 87-102 (2008)
doi:10.1111/j.1600-065X.2008.00712.x
PMid:19161418
7. Korn, T., E. Bettelli, M. Oukka & V. K. Kuchroo: IL-17 and Th17 Cells. Annu Rev Immunol, 27, 485-517 (2009)
doi:10.1146/annurev.immunol.021908.132710
PMid:19132915
8. van Es, T., G. H. van Puijvelde, O. H. Ramos, F. M. Segers, L. A. Joosten, W. B. van den Berg, I. M. Michon, P. de Vos, T. J. van Berkel & J. Kuiper: Attenuated atherosclerosis upon IL-17R signaling disruption in LDLr deficient mice. Biochem Biophys Res Commun, 388, 261-5 (2009)
doi:10.1016/j.bbrc.2009.07.152
PMid:19660432
9. Xie, J. J., J. Wang, T. T. Tang, J. Chen, X. L. Gao, J. Yuan, Z. H. Zhou, M. Y. Liao, R. Yao, X. Yu, D. Wang, Y. Cheng, Y. H. Liao & X. Cheng: The Th17/Treg functional imbalance during atherogenesis in ApoE (-/-) mice Th17/Treg imbalance in atherogenesis. Cytokine (2009)
10. Taleb, S., M. Romain, B. Ramkhelawon, C. Uyttenhove, G. Pasterkamp, O. Herbin, B. Esposito, N. Perez, H. Yasukawa, J. Van Snick, A. Yoshimura, A. Tedgui & Z. Mallat: Loss of SOCS3 expression in T cells reveals a regulatory role for interleukin-17 in atherosclerosis. J Exp Med, 206, 2067-77 (2009)
doi:10.1084/jem.20090545
PMid:19737863 PMCid:2757872
11. Erbel, C., Klingenberg, R, Celik, S, Wambsganss, N, Funke, B, Boeckler, D, Dengler, T.: Abstract 759: Inhibition of proinflammatory cytokine IL-17 reduces atherosclerotic lesion development in ApoE-/- mice. Circulation, 116, 145-146 (2007)
12. Mai, J., H Wang, X-F Yang T Helper 17 Cells Interplay with CD4+CD25highFoxp3+ Tregs in Regulation of Inflammations and Autoimmune Diseases Frontiers in Bioscience, in press, (2010)
13. Syrjala, S. O., M. A. Keranen, R. Tuuminen, A. I. Nykanen, M. Tammi, R. Krebs & K. B. Lemstrom: Increased Th17 rather than Th1 alloimmune response is associated with cardiac allograft vasculopathy after hypothermic preservation in the rat. J Heart Lung Transplant (2010)
14. Kolls, J. K. & A. Linden: Interleukin-17 family members and inflammation. Immunity, 21, 467-76 (2004)
doi:10.1016/j.immuni.2004.08.018
PMid:15485625
15. Rouvier, E., M. F. Luciani, M. G. Mattei, F. Denizot & P. Golstein: CTLA-8, cloned from an activated T cell, bearing AU-rich messenger RNA instability sequences, and homologous to a herpesvirus saimiri gene. J Immunol, 150, 5445-56 (1993)
PMid:8390535
16. Yao, Z., S. L. Painter, W. C. Fanslow, D. Ulrich, B. M. Macduff, M. K. Spriggs & R. J. Armitage: Human IL-17: a novel cytokine derived from T cells. J Immunol, 155, 5483-6 (1995)
PMid:7499828
17. Li, H., J. Chen, A. Huang, J. Stinson, S. Heldens, J. Foster, P. Dowd, A. L. Gurney & W. I. Wood: Cloning and characterization of IL-17B and IL-17C, two new members of the IL-17 cytokine family. Proc Natl Acad Sci U S A, 97, 773-8 (2000)
doi:10.1073/pnas.97.2.773
18. Lee, J., W. H. Ho, M. Maruoka, R. T. Corpuz, D. T. Baldwin, J. S. Foster, A. D. Goddard, D. G. Yansura, R. L. Vandlen, W. I. Wood & A. L. Gurney: IL-17E, a novel proinflammatory ligand for the IL-17 receptor homolog IL-17Rh1. J Biol Chem, 276, 1660-4 (2001)
doi:10.1074/jbc.M008289200
PMid:11058597
19. Hymowitz, S. G., E. H. Filvaroff, J. P. Yin, J. Lee, L. Cai, P. Risser, M. Maruoka, W. Mao, J. Foster, R. F. Kelley, G. Pan, A. L. Gurney, A. M. de Vos & M. A. Starovasnik: IL-17s adopt a cystine knot fold: structure and activity of a novel cytokine, IL-17F, and implications for receptor binding. Embo J, 20, 5332-41 (2001)
doi:10.1093/emboj/20.19.5332
PMid:11574464 PMCid:125646
20. Starnes, T., M. J. Robertson, G. Sledge, S. Kelich, H. Nakshatri, H. E. Broxmeyer & R. Hromas: Cutting edge: IL-17F, a novel cytokine selectively expressed in activated T cells and monocytes, regulates angiogenesis and endothelial cell cytokine production. J Immunol, 167, 4137-40 (2001)
PMid:11591732
21. Park, H., Z. Li, X. O. Yang, S. H. Chang, R. Nurieva, Y. H. Wang, Y. Wang, L. Hood, Z. Zhu, Q. Tian & C. Dong: A distinct lineage of CD4 T cells regulates tissue inflammation by producing interleukin 17. Nat Immunol, 6, 1133-41 (2005)
doi:10.1038/ni1261
PMid:16200068 PMCid:1618871
22. Kawaguchi, M., F. Kokubu, M. Odaka, S. Watanabe, S. Suzuki, K. Ieki, S. Matsukura, M. Kurokawa, M. Adachi & S. K. Huang: Induction of granulocyte-macrophage colony-stimulating factor by a new cytokine, ML-1 (IL-17F), via Raf I-MEK-ERK pathway. J Allergy Clin Immunol, 114, 444-50 (2004)
doi:10.1016/j.jaci.2004.03.047
PMid:15316530
23. Awane, M., P. G. Andres, D. J. Li & H. C. Reinecker: NF-kappa B-inducing kinase is a common mediator of IL-17-, TNF-alpha-, and IL-1 beta-induced chemokine promoter activation in intestinal epithelial cells. J Immunol, 162, 5337-44 (1999)
PMid:10228009
24. Shalom-Barak, T., J. Quach & M. Lotz: Interleukin-17-induced gene expression in articular chondrocytes is associated with activation of mitogen-activated protein kinases and NF-kappaB. J Biol Chem, 273, 27467-73 (1998)
doi:10.1074/jbc.273.42.27467
PMid:9765276
25. Chang, S. H. & C. Dong: A novel heterodimeric cytokine consisting of IL-17 and IL-17F regulates inflammatory responses. Cell Res, 17, 435-40 (2007)
PMid:17452998
26. Moseley, T. A., D. R. Haudenschild, L. Rose & A. H. Reddi: Interleukin-17 family and IL-17 receptors. Cytokine Growth Factor Rev, 14, 155-74 (2003)
doi:10.1016/S1359-6101(03)00002-9
27. Yao, Z., W. C. Fanslow, M. F. Seldin, A. M. Rousseau, S. L. Painter, M. R. Comeau, J. I. Cohen & M. K. Spriggs: Herpesvirus Saimiri encodes a new cytokine, IL-17, which binds to a novel cytokine receptor. Immunity, 3, 811-21 (1995)
doi:10.1016/1074-7613(95)90070-5
28. Kuestner, R. E., D. W. Taft, A. Haran, C. S. Brandt, T. Brender, K. Lum, B. Harder, S. Okada, C. D. Ostrander, J. L. Kreindler, S. J. Aujla, B. Reardon, M. Moore, P. Shea, R. Schreckhise, T. R. Bukowski, S. Presnell, P. Guerra-Lewis, J. Parrish-Novak, J. L. Ellsworth, S. Jaspers, K. E. Lewis, M. Appleby, J. K. Kolls, M. Rixon, J. W. West, Z. Gao & S. D. Levin: Identification of the IL-17 receptor related molecule IL-17RC as the receptor for IL-17F. J Immunol, 179, 5462-73 (2007)
PMid:17911633 PMCid:2849293
29. Toy, D., D. Kugler, M. Wolfson, T. Vanden Bos, J. Gurgel, J. Derry, J. Tocker & J. Peschon: Cutting edge: interleukin 17 signals through a heteromeric receptor complex. J Immunol, 177, 36-9 (2006)
PMid:16785495
30. Gratchev, A., J. Kzhyshkowska, K. Duperrier, J. Utikal, F. W. Velten & S. Goerdt: The receptor for interleukin-17E is induced by Th2 cytokines in antigen-presenting cells. Scand J Immunol, 60, 233-7 (2004)
doi:10.1111/j.0300-9475.2004.01443.x
PMid:15320879
31. Novatchkova, M., A. Leibbrandt, J. Werzowa, A. Neubuser & F. Eisenhaber: The STIR-domain superfamily in signal transduction, development and immunity. Trends Biochem Sci, 28, 226-9 (2003)
doi:10.1016/S0968-0004(03)00067-7
32. Dong, C.: Regulation and pro-inflammatory function of interleukin-17 family cytokines. Immunol Rev, 226, 80-6 (2008)
doi:10.1111/j.1600-065X.2008.00709.x
PMid:19161417 PMCid:2631160
33. Linden, A.: A role for the cytoplasmic adaptor protein Act1 in mediating IL-17 signaling. Sci STKE, 2007, re4 (2007)
doi:10.1126/stke.3982007re4
PMid:17684298
34. Qian, Y., C. Liu, J. Hartupee, C. Z. Altuntas, M. F. Gulen, D. Jane-Wit, J. Xiao, Y. Lu, N. Giltiay, J. Liu, T. Kordula, Q. W. Zhang, B. Vallance, S. Swaidani, M. Aronica, V. K. Tuohy, T. Hamilton & X. Li: The adaptor Act1 is required for interleukin 17-dependent signaling associated with autoimmune and inflammatory disease. Nat Immunol, 8, 247-56 (2007)
doi:10.1038/nrg2096
doi:10.1038/ni1439
PMid:17277779
35. Sandler, H. & G. Stoecklin: Control of mRNA decay by phosphorylation of tristetraprolin. Biochem Soc Trans, 36, 491-6 (2008)
doi:10.1042/BST0360491
PMid:18481987
36. Anderson, P.: Post-transcriptional control of cytokine production. Nat Immunol, 9, 353-9 (2008)
doi:10.1038/ni1584
PMid:18349815
37. Zhang, C.: MicroRNAs: role in cardiovascular biology and disease. Clin Sci (Lond), 114, 699-706 (2008)
doi:10.1042/CS20070211
PMid:18474027
38. Ng, B., F. Yang, D. P. Huston, Y. Yan, Y. Yang, Z. Xiong, L. E. Peterson, H. Wang & X. F. Yang: Increased noncanonical splicing of autoantigen transcripts provides the structural basis for expression of untolerized epitopes. J Allergy Clin Immunol, 114, 1463-70 (2004)
doi:10.1016/j.jaci.2004.09.006
PMid:15577853
39. Chen, N. C., F. Yang, L. M. Capecci, Z. Gu, A. I. Schafer, W. Durante, X. F. Yang & H. Wang: Regulation of homocysteine metabolism and methylation in human and mouse tissues. Faseb J, 24, 2804-17 (2010)
doi:10.1096/fj.09-143651
PMid:20305127
40. Yin, Y., Y. Yan, X. Jiang, J. Mai, N. C. Chen, H. Wang & X. F. Yang: Inflammasomes are differentially expressed in cardiovascular and other tissues. Int J Immunopathol Pharmacol, 22, 311-22 (2009)
PMid:19505385 PMCid:2847797
41. Pires Martins, R., R. E. Leach & S. A. Krawetz: Whole-body gene expression by data mining. Genomics, 72, 34-42 (2001)
doi:10.1006/geno.2000.6437
PMid:11247664
42. Chen, C. Y. & A. B. Shyu: AU-rich elements: characterization and importance in mRNA degradation. Trends Biochem Sci, 20, 465-70 (1995)
doi:10.1016/S0968-0004(00)89102-1
43. Ueland, P. M., S. Helland, O. J. Broch & J. S. Schanche: Homocysteine in tissues of the mouse and rat. J Biol Chem, 259, 2360-4 (1984)
PMid:6698970
44. Helland, S. & P. M. Ueland: S-adenosylhomocysteine and S-adenosylhomocysteine hydrolase in various tissues of mice given injections of 9-beta-D-arabinofuranosyladenine. Cancer Res, 43, 1847-50 (1983)
PMid:6831422
45. Helland, S. & P. M. Ueland: Effect of 2'-deoxycoformycin infusion on S-adenosylhomocysteine hydrolase and the amount of S-adenosylhomocysteine and related compounds in tissues of mice. Cancer Res, 43, 4142-7 (1983)
PMid:6603264
46. Sethupathy, P., B. Corda & A. G. Hatzigeorgiou: TarBase: A comprehensive database of experimentally supported animal microRNA targets. Rna, 12, 192-7 (2006)
doi:10.1261/rna.2239606
PMid:16373484 PMCid:1370898
47. Papadopoulos, G. L., M. Reczko, V. A. Simossis, P. Sethupathy & A. G. Hatzigeorgiou: The database of experimentally supported targets: a functional update of TarBase. Nucleic Acids Res, 37, D155-8 (2009)
doi:10.1093/nar/gkn809
PMid:18957447 PMCid:2686456
48. Starnes, T., H. E. Broxmeyer, M. J. Robertson & R. Hromas: Cutting edge: IL-17D, a novel member of the IL-17 family, stimulates cytokine production and inhibits hemopoiesis. J Immunol, 169, 642-6 (2002)
PMid:12097364
49. Silva, W. A., Jr., D. T. Covas, R. A. Panepucci, R. Proto-Siqueira, J. L. Siufi, D. L. Zanette, A. R. Santos & M. A. Zago: The profile of gene expression of human marrow mesenchymal stem cells. Stem Cells, 21, 661-9 (2003)
doi:10.1634/stemcells.21-6-661
PMid:14595126
50. Harrington, L. E., R. D. Hatton, P. R. Mangan, H. Turner, T. L. Murphy, K. M. Murphy & C. T. Weaver: Interleukin 17-producing CD4+ effector T cells develop via a lineage distinct from the T helper type 1 and 2 lineages. Nat Immunol, 6, 1123-32 (2005)
doi:10.1038/ni1254
PMid:16200070
51. Weaver, C. T., L. E. Harrington, P. R. Mangan, M. Gavrieli & K. M. Murphy: Th17: an effector CD4 T cell lineage with regulatory T cell ties. Immunity, 24, 677-88 (2006)
doi:10.1016/j.immuni.2006.06.002
PMid:16782025
52. Claudio, E., S. U. Sonder, S. Saret, G. Carvalho, T. R. Ramalingam, T. A. Wynn, A. Chariot, A. Garcia-Perganeda, A. Leonardi, A. Paun, A. Chen, N. Y. Ren, H. Wang & U. Siebenlist: The adaptor protein CIKS/Act1 is essential for IL-25-mediated allergic airway inflammation. J Immunol, 182, 1617-30 (2009)
PMid:19155511 PMCid:2630122
53. Chang, S. H., H. Park & C. Dong: Act1 adaptor protein is an immediate and essential signaling component of interleukin-17 receptor. J Biol Chem, 281, 35603-7 (2006)
doi:10.1074/jbc.C600256200
PMid:17035243
54. Gaffen, S. L.: Structure and signalling in the IL-17 receptor family. Nat Rev Immunol, 9, 556-67 (2009)
doi:10.1038/nri2586
PMid:19575028 PMCid:2821718
55. Letuve, S., S. Lajoie-Kadoch, S. Audusseau, M. E. Rothenberg, P. O. Fiset, M. S. Ludwig & Q. Hamid: IL-17E upregulates the expression of proinflammatory cytokines in lung fibroblasts. J Allergy Clin Immunol, 117, 590-6 (2006)
doi:10.1016/j.jaci.2005.10.025
PMid:16522458
56. Kornblihtt, A. R.: Promoter usage and alternative splicing. Curr Opin Cell Biol, 17, 262-8 (2005)
doi:10.1016/j.ceb.2005.04.014
PMid:15901495
57. Kornblihtt, A. R.: Coupling transcription and alternative splicing. Adv Exp Med Biol, 623, 175-89 (2007)
doi:10.1007/978-0-387-77374-2_11
58. Thierry-Mieg, D. & J. Thierry-Mieg: AceView: a comprehensive cDNA-supported gene and transcripts annotation. Genome Biol, 7 Suppl 1, S12 1-14 (2006)
59. Akimzhanov, A. M., X. O. Yang & C. Dong: Chromatin remodeling of interleukin-17 (IL-17)-IL-17F cytokine gene locus during inflammatory helper T cell differentiation. J Biol Chem, 282, 5969-72 (2007)
doi:10.1074/jbc.C600322200
PMid:17218320
60. Ordovas, J. M. & C. E. Smith: Epigenetics and cardiovascular disease. Nat Rev Cardiol (2010)
61. Jamaluddin, M. S., X. Yang & H. Wang: Hyperhomocysteinemia, DNA methylation and vascular disease. Clin Chem Lab Med, 45, 1660-6 (2007)
doi:10.1515/CCLM.2007.350
PMid:18067449
62. James, S. J., S. Melnyk, M. Pogribna, I. P. Pogribny & M. A. Caudill: Elevation in S-adenosylhomocysteine and DNA hypomethylation: potential epigenetic mechanism for homocysteine-related pathology. J Nutr, 132, 2361S-2366S (2002)
PMid:12163693
63. Caudill, M. A., J. C. Wang, S. Melnyk, I. P. Pogribny, S. Jernigan, M. D. Collins, J. Santos-Guzman, M. E. Swendseid, E. A. Cogger & S. J. James: Intracellular S-adenosylhomocysteine concentrations predict global DNA hypomethylation in tissues of methyl-deficient cystathionine beta-synthase heterozygous mice. J Nutr, 131, 2811-8 (2001)
PMid:11694601
64. Taylor, G. A., E. Carballo, D. M. Lee, W. S. Lai, M. J. Thompson, D. D. Patel, D. I. Schenkman, G. S. Gilkeson, H. E. Broxmeyer, B. F. Haynes & P. J. Blackshear: A pathogenetic role for TNF alpha in the syndrome of cachexia, arthritis, and autoimmunity resulting from tristetraprolin (TTP) deficiency. Immunity, 4, 445-54 (1996)
doi:10.1016/S1074-7613(00)80411-2
65. Bakheet, T., B. R. Williams & K. S. Khabar: ARED 2.0: an update of AU-rich element mRNA database. Nucleic Acids Res, 31, 421-3 (2003)
doi:10.1093/nar/gkg023
PMid:12520039 PMCid:165470
66. Charlesworth, A., A. Wilczynska, P. Thampi, L. L. Cox & A. M. MacNicol: Musashi regulates the temporal order of mRNA translation during Xenopus oocyte maturation. Embo J, 25, 2792-801 (2006)
doi:10.1038/sj.emboj.7601159
PMid:16763568 PMCid:1500856
67. Lai, E. C. & J. W. Posakony: The Bearded box, a novel 3' UTR sequence motif, mediates negative post-transcriptional regulation of Bearded and Enhancer of split Complex gene expression. Development, 124, 4847-56 (1997)
PMid:9428421
68. Dinur, M., R. Kilav, A. Sela-Brown, H. Jacquemin-Sablon & T. Naveh-Many: In vitro evidence that upstream of N-ras participates in the regulation of parathyroid hormone messenger ribonucleic acid stability. Mol Endocrinol, 20, 1652-60 (2006)
doi:10.1210/me.2005-0333
PMid:16469771
69. Lai, E. C., C. Burks & J. W. Posakony: The K box, a conserved 3' UTR sequence motif, negatively regulates accumulation of enhancer of split complex transcripts. Development, 125, 4077-88 (1998)
PMid:9735368
70. Bartel, D. P.: MicroRNAs: target recognition and regulatory functions. Cell, 136, 215-33 (2009)
doi:10.1016/j.cell.2009.01.002
PMid:19167326
71. Rasmussen, K. D., S. Simmini, C. Abreu-Goodger, N. Bartonicek, M. Di Giacomo, D. Bilbao-Cortes, R. Horos, M. Von Lindern, A. J. Enright & D. O'Carroll: The miR-144/451 locus is required for erythroid homeostasis. J Exp Med, 207, 1351-8 (2010)
doi:10.1084/jem.20100458
PMid:20513743 PMCid:2901075
72. Cordes, K. R., N. T. Sheehy, M. P. White, E. C. Berry, S. U. Morton, A. N. Muth, T. H. Lee, J. M. Miano, K. N. Ivey & D. Srivastava: miR-145 and miR-143 regulate smooth muscle cell fate and plasticity. Nature, 460, 705-10 (2009)
PMid:19578358 PMCid:2769203
73. Naeem, H., R. Kuffner, G. Csaba & R. Zimmer: miRSel: automated extraction of associations between microRNAs and genes from the biomedical literature. BMC Bioinformatics, 11, 135 (2010)
doi:10.1186/1471-2105-11-135
PMid:20233441 PMCid:2845581
74. Jing, Q., S. Huang, S. Guth, T. Zarubin, A. Motoyama, J. Chen, F. Di Padova, S. C. Lin, H. Gram & J. Han: Involvement of microRNA in AU-rich element-mediated mRNA instability. Cell, 120, 623-34 (2005)
doi:10.1016/j.cell.2004.12.038
PMid:15766526
75. Asirvatham, A. J., C. J. Gregorie, Z. Hu, W. J. Magner & T. B. Tomasi: MicroRNA targets in immune genes and the Dicer/Argonaute and ARE machinery components. Mol Immunol, 45, 1995-2006 (2008)
doi:10.1016/j.molimm.2007.10.035
PMid:18061676 PMCid:2678893
76. Asirvatham, A. J., W. J. Magner & T. B. Tomasi: miRNA regulation of cytokine genes. Cytokine, 45, 58-69 (2009)
doi:10.1016/j.cyto.2008.11.010
PMid:19121586
77. Yin, Y., Y. Yan, X. Jiang, J. Mai, N. C. Chen, H. Wang & X. F. Yang: Inflammasomes are differentially expressed in cardiovascular and other tissues. Int J Immunopathol Pharmacol, 22, 311-322 (2009)
PMid:19505385 PMCid:2847797
78. Chiu, I. M., K. Touhalisky & C. Baran: Multiple controlling mechanisms of FGF1 gene expression through multiple tissue-specific promoters. Prog Nucleic Acid Res Mol Biol, 70, 155-74 (2001)
doi:10.1016/S0079-6603(01)70016-5
79. Ademokun, A. & M. Turner: Regulation of B-cell differentiation by microRNAs and RNA-binding proteins. Biochem Soc Trans, 36, 1191-3 (2008)
doi:10.1042/BST0361191
PMid:19021522
80. Kedde, M. & R. Agami: Interplay between microRNAs and RNA-binding proteins determines developmental processes. Cell Cycle, 7, 899-903 (2008)
doi:10.4161/cc.7.7.5644
PMid:18414021
81. Du, C., C. Liu, J. Kang, G. Zhao, Z. Ye, S. Huang, Z. Li, Z. Wu & G. Pei: MicroRNA miR-326 regulates TH-17 differentiation and is associated with the pathogenesis of multiple sclerosis. Nat Immunol, 10, 1252-9 (2009)
doi:10.1038/ni.1798
PMid:19838199
82. Vickers, K. C. & A. T. Remaley: MicroRNAs in atherosclerosis and lipoprotein metabolism. Curr Opin Endocrinol Diabetes Obes, 17, 150-5 (2010)
doi:10.1097/MED.0b013e32833727a1
PMid:20150807 PMCid:2897736
83. Rosero, S., V. Bravo-Egana, Z. Jiang, S. Khuri, N. Tsinoremas, D. Klein, E. Sabates, M. Correa-Medina, C. Ricordi, J. Dominguez-Bendala, J. Diez & R. L. Pastori: MicroRNA signature of the human developing pancreas. BMC Genomics, 11, 509 (2010)
doi:10.1186/1471-2164-11-509
PMid:20860821 PMCid:2997005
84. Dong, H., M. Paquette, A. Williams, R. T. Zoeller, M. Wade & C. Yauk: Thyroid hormone may regulate mRNA abundance in liver by acting on microRNAs. PLoS One, 5, (2010)
85. Sonkoly, E. & A. Pivarcsi: microRNAs in inflammation. Int Rev Immunol, 28, 535-61 (2009)
doi:10.3109/08830180903208303
PMid:19954362
86. Haver, V. G., R. H. Slart, C. J. Zeebregts, M. P. Peppelenbosch & R. A. Tio: Rupture of vulnerable atherosclerotic plaques: microRNAs conducting the orchestra? Trends Cardiovasc Med, 20, 65-71 (2010)
doi:10.1016/j.tcm.2010.04.002
PMid:20656218
87. Nakasa, T., S. Miyaki, A. Okubo, M. Hashimoto, K. Nishida, M. Ochi & H. Asahara: Expression of microRNA-146 in rheumatoid arthritis synovial tissue. Arthritis Rheum, 58, 1284-92(2008)
doi:10.1002/art.23429
88. Tang, Y., X. Luo, H. Cui, X. Ni, M. Yuan, Y. Guo, X. Huang, H. Zhou, N. de Vries, P. P. Tak, S. Chen & N. Shen: MicroRNA-146A contributes to abnormal activation of the type I interferon pathway in human lupus by targeting the key signaling proteins. Arthritis Rheum, 60, 1065-75(2009)
doi:10.1002/art.24436
89. Doebele, C., A. Bonauer, A. Fischer, A. Scholz, Y. Reiss, C. Urbich, W. K. Hofmann, A. M. Zeiher & S. Dimmeler: Members of the microRNA-17-92 cluster exhibit a cell-intrinsic antiangiogenic function in endothelial cells. Blood, 115, 4944-50(2010)
doi:10.1182/blood-2010-01-264812
PMid:20299512
90. Fontana, L., E. Pelosi, P. Greco, S. Racanicchi, U. Testa, F. Liuzzi, C. M. Croce, E. Brunetti, F. Grignani & C. Peschle: MicroRNAs 17-5p-20a-106a control monocytopoiesis through AML1 targeting and M-CSF receptor upregulation. Nat Cell Biol, 9, 775-87(2007)
doi:10.1038/ncb1613
PMid:17589498
91. Volinia, S., G. A. Calin, C. G. Liu, S. Ambs, A. Cimmino, F. Petrocca, R. Visone, M. Iorio, C. Roldo, M. Ferracin, R. L. Prueitt, N. Yanaihara, G. Lanza, A. Scarpa, A. Vecchione, M. Negrini, C. C. Harris & C. M. Croce: A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci U S A, 103, 2257-61(2006)
doi:10.1073/pnas.0510565103
PMid:16461460 PMCid:1413718
92. Hua, Z., Q. Lv, W. Ye, C. K. Wong, G. Cai, D. Gu, Y. Ji, C. Zhao, J. Wang, B. B. Yang & Y. Zhang: MiRNA-directed regulation of VEGF and other angiogenic factors under hypoxia. PLoS One, 1, e116(2006)
doi:10.1371/journal.pone.0000116
PMid:17205120 PMCid:1762435
93. Pauley, K.M., M. Satoh, A. L. Chan, M. R. Bubb, W. H. Reeves & E. K. Chan: Upregulated miR-146a expression in peripheral blood mononuclear cells from rheumatoid arthritis patients. Arthritis Res Ther, 10, R101(2008)
PMid:18759964 PMCid:2575615
94. Martinez-Nunez, R.T., F. Louafi, P. S. Friedmann & T. Sanchez-Elsner: MicroRNA-155 modulates the pathogen binding ability of dendritic cells (DCs) by down-regulation of DC-specific intercellular adhesion molecule-3 grabbing non-integrin (DC-SIGN). J Biol Chem, 284, 16334-42(2009)
doi:10.1074/jbc.M109.011601
PMid:19386588 PMCid:2713543
95. Ceppi, M., P. M. Pereira, I. Dunand-Sauthier, E. Barras, W. Reith, M. A. Santos & P. Pierre: MicroRNA-155 modulates the interleukin-1 signaling pathway in activated human monocyte-derived dendritic cells. Proc Natl Acad Sci U S A, 106, 2735-40(2009)
doi:10.1073/pnas.0811073106
PMid:19193853 PMCid:2650335
96. Martin, M. M., E. J. Lee, J. A. Buckenberger, T. D. Schmittgen & T. S. Elton: MicroRNA-155 regulates human angiotensin II type 1 receptor expression in fibroblasts. J Biol Chem, 281, 18277-84(2006)
doi:10.1074/jbc.M601496200
PMid:16675453
97. Poliseno, L., A. Tuccoli, L. Mariani, M. Evangelista, L. Citti, K. Woods, A. Mercatanti, S. Hammond & G. Rainaldi: MicroRNAs modulate the angiogenic properties of HUVECs. Blood, 108, 3068-71(2006)
doi:10.1182/blood-2006-01-012369
PMid:16849646
98. Suarez, Y., C. Fernandez-Hernando, J. S. Pober & W. C. Sessa: Dicer dependent microRNAs regulate gene expression and functions in human endothelial cells. Circ Res, 100, 1164-73(2007)
doi:10.1161/01.RES.0000265065.26744.17
PMid:17379831
99. Gabriely, G., T. Wurdinger, S. Kesari, C. C. Esau, J. Burchard, P. S. Linsley & A. M. Krichevsky: MicroRNA 21 promotes glioma invasion by targeting matrix metalloproteinase regulators. Mol Cell Biol, 28, 5369-80(2008)
doi:10.1128/MCB.00479-08
PMid:18591254 PMCid:2519720
100. Zhu, S., M. L. Si, H. Wu & Y. Y. Mo: MicroRNA-21 targets the tumor suppressor gene tropomyosin 1 (TPM1). J Biol Chem, 282, 14328-36(2007)
doi:10.1074/jbc.M611393200
PMid:17363372
101. Meng, F., R. Henson, M. Lang, H. Wehbe, S. Maheshwari, J. T. Mendell, J. Jiang, T. D. Schmittgen & T. Patel: Involvement of human micro-RNA in growth and response to chemotherapy in human cholangiocarcinoma cell lines. Gastroenterology, 130, 2113-29(2006)
doi:10.1053/j.gastro.2006.02.057
PMid:16762633
102. Asangani, I. A., S. A. Rasheed, D. A. Nikolova, J. H. Leupold, N. H. Colburn, S. Post & H. Allgayer: MicroRNA-21 (miR-21) post-transcriptionally downregulates tumor suppressor Pdcd4 and stimulates invasion, intravasation and metastasis in colorectal cancer. Oncogene, 27, 2128-36(2008)
doi:10.1038/sj.onc.1210856
PMid:17968323
Key Words: interleukin-17 Cytokines, Interleukin-17 Receptors, Gene Expression, mRNA Stability, Vascular Inflammation, Review
Send correspondence to: Xiao-Feng Yang, Department of Pharmacology, Temple University School of Medicine, 3420 North Broad Street, MRB 325, Philadelphia, PA 19140, U.S.A., Tel: 215-707-5985, Fax: 215-707-7068, E-mail:xfyang@temple.edu