New Perspectives in MicroRNA Regulation of Innate Immunity

Abstract

The fine-tuning of the innate immune response by microRNAs (miRNAs) is a concept now supported by a rapidly growing body of evidence. Target prediction analyses indicate that up to a half of innate immune genes could be under the direct regulation of miRNAs. However, the extent to which miRNAs regulate innate immunity remains poorly defined and is currently limited to a handful of target genes. This review highlights several important parameters of miRNA regulation, mostly neglected in the field, which underpin the relevance of miRNAs in the regulation of innate immunity.

Introduction

S ince their first observation in Caenorhabditis elegans in 1993 (Lee and others 1993), there is now overwhelming evidence that microRNAs (miRNAs) are master regulators of gene expression in most cellular processes (Du and Zamore 2007). miRNAs constitute an additional level of gene expression regulation between messenger RNA (mRNA) and protein translation. Mature miRNAs are short, averaging 21 nucleotides long, and result from a multistep processing of longer RNA transcripts [see Winter and others (2009) for a detailed review]. miRNAs recruited to the RNA-induced silencing complex affect translation of partially complementary mRNA sequences. Although their short length theoretically allows for binding to a specific target motif, recognition by miRNAs of a target mRNA mostly relies on the complementary pairing of a 6–8-nt seed region (Brennecke and others 2005). Consequently, a single miRNA may directly affect the expression of hundreds of proteins at once (Selbach and others 2008). Nevertheless, the negative regulation of protein translation by miRNA is limited and rarely exceeds 4-fold in proteomic studies (Selbach and others 2008). Several miRNAs can target the same mRNA and result in enhanced translational inhibition (Selbach and others 2008). This fine-tuning of multiple protein expression by multiple miRNAs is crucial for tight control of cellular function, and mice lacking miRNAs are simply not viable (Harfe and others 2005).

miRNA Regulation of Gene Expression

A key challenge of miRNA research is the prediction of valid miRNA–mRNA interactions. Novel miRNAs are still being discovered (currently 721 and 579 for human and mouse, respectively) (Griffiths-Jones and others 2008), and it has been proposed that at least 30% of human genes could be directly regulated by miRNAs (Lewis and others 2005). Several computational methods relying on seed regions of miRNAs have been established to help the identification of functionally relevant miRNA targets (Creighton and others 2008). Predictions relying on interspecies conservation of target sites in the 3′ untranslated region (UTR) are the most accurate (averaging 60% of reliability in large proteomics studies) (Selbach and others 2008), but omit at least half of the valid targets (Wu and others 2010). In a systematic screen of 266 miRNAs predicted to target p21Cip1/Waf1 by an aggregation of four different algorithms, Wu and others (2010) identified only 28 miRNAs that significantly suppressed luciferase expression of a p21 3′ UTR reporter. This finding underlines the fact that miRNA regulation of gene expression should be focusing on the interactions between multiple miRNAs and one target. The variation of basal miRNA levels between different tissues/cell types (Landgraf and others 2007) is therefore expected to have a large impact on the regulation of a given target, independent of any stimuli-related miRNA induction. Further, given that only ∼10% of the interactions predicted in silico were significant, the work of Wu and others (2010) underlines the enormous task at hand to validate miRNA–mRNA interactions of biological relevance.

Current studies of miRNA regulation of gene expression have so far predominantly relied on single miRNA–mRNA interactions. First, miRNAs that are differentially expressed between samples following a treatment are identified through the use of miRNA profiling. Second, in silico predicted targets of the identified miRNA(s) that have been previously involved with the treatment used are searched for. Third, evidence is provided that one of these miRNAs directly interacts with the predicted target and that disruption of this interaction affects the translation of the target. Finally, it is shown that inhibition of the miRNA regulation has similar biological function to that associated with alteration of expression of its target. Although indicative of the role for a given miRNA in a biological process, this convoluted way of resolving miRNA regulation of gene function actually reduces miRNA significance to the function of its target. It does not take into account variations of basal miRNA expression between tissues/cell types, which is also expected to contribute to the regulation of a given target. In addition, because one miRNA only dampens the expression of a single target (Selbach and others 2008), the actual relevance of these target-specific miRNA regulations is questionable. Such an approach limits our understanding of miRNA regulation of biological processes to a small number of genes, whose function in these processes is already known.

miRNA Regulation of Gene Networks

An important aspect of miRNA regulation that remains poorly characterized is the simultaneous regulation of several genes from the same functional network by 1 miRNA. In this case, the postulate is that weak regulation of multiple targets by a given miRNA concurrently results in a biological function that may not necessarily be observed through regulating each individual target alone. This can in turn inform on novel roles for proteins that were not previously associated with the function studied.

In this respect, the field of innate immunity presents many unique opportunities. Signal transduction following pathogen-induced activation of immune sensors such as toll-like receptors (TLRs) promotes the rapid induction of hundreds of genes that help in clearance of the pathogen. Only a few miRNAs (including miR-155, miR-146a, miR-21, miR-9) have been consistently found to be rapidly induced by innate immune activation (Taganov and others 2006; O'Connell and others 2007; Bazzoni and others 2009; Sheedy and others 2010), and only a few targets have been directly identified for these miRNAs [see O'Connell and others (2010)]. However, because these miRNAs are rapidly induced, it is reasonable to assume that they may play an important role in the modulation of the innate immune response. Consequently, identification of novel gene networks regulated by these miRNAs could have significant impact on our current understanding of the regulation of innate immune signaling.

miR-155 is one of the most studied miRNAs, which is induced by innate immune activation. First reported by Taganov and others (2006) to be upregulated in human monocytic THP-1 cells following lipopolysaccharide (LPS) stimulation, it was further characterized in mouse bone marrow macrophages (BMMs) (O'Connell and others 2007). Mature miR-155 accumulates very rapidly following TLR (TLR2, 3, 4, and 9) and tumor necrosis factor α (TNF-α) stimulation (Taganov and others 2006; O'Connell and others 2007). miR-155 expression is restricted to hematopoietic cells (B and T cells, macrophages, and dendritic cells) (Landgraf and others 2007), and it is overexpressed in cancers of B-cell origin (Eis and others 2005). However, the basal level of miR-155 in immune cells is very low compared with other miRNAs such as miR-21 (Landgraf and others 2007; O'Connell and others 2009). miR-155 has been shown to directly target several innate immune genes including Tab2, Peli-1, CEBPβ, and SHIP-1 (Selbach and others 2008; Yin and others 2008; Ceppi and others 2009; Costinean and others 2009; O'Connell and others 2009; Pedersen and others 2009; Yamanaka and others 2009). In addition, blockage of miR-155 induction using synthetic antagomirs resulted in the derepression of genes involved in TLR/interleukin-1 (IL-1) signaling (Ceppi and others 2009). Functionally, miR-155 has been implicated in the positive regulation of TNF-α production (Thai and others 2007; Tili and others 2007), the modulation of the IL-6 signaling pathway in B-cell lineage differentiation (Costinean and others 2009), and the inhibition of interferon γ (IFN-γ) signaling in CD4+ T cells (Banerjee and others 2010). Eμ-miR-155 transgenic mice produced more TNF-α when challenged with LPS (Tili and others 2007). These functions of miR-155 on cytokine production and function point toward a combined action of complex gene networks.

A recent study revealed that 100 proteins were significantly downregulated in HeLa cells, upon transfection of an miR-155 mimic (Selbach and others 2008). Among them, 28 have been involved in innate immunity [according to the innate immune database (Korb and others 2008) or the interferome database (Samarajiwa and others 2009)] and have a matching seed region for miR-155 (Table 1). The fact that these 28 innate immune genes are directly impacted on by miR-155 suggests that they could belong to similar gene networks, regulating TLR signaling and TNF-α production. In this respect, several of these miR-155 targets are involved in phagocytosis (Myo10, Myo1e), autophagy (Atg3), endocytosis (Arl5b, Rab5c, Ankfy1, Wdfy1), or cytokine secretion (VAMP3), all of key importance for macrophage function (Murray and others 2005; Groves and others 2008; Orvedahl and Levine 2009). Targeting of syntenin, a previously suggested negative regulator of TLR signaling (Chen and others 2008), is also of particular interest and could represent opportunities in the therapeutic regulation of aberrant TLR/IL-1 recruitment. The finding that 74 proteins downregulated by miR-155 were not previously linked to innate immunity could also allow for the identification of novel genes involved in some aspects of innate immune regulation (Selbach and others 2008).

Table 1.

Validated miR-155 Innate Immune Targets (Adapted from Selbach and Others 2008)

Gene name	Full name	Innate immune function	PubMed ID reference(s)	Seeds
Ankfy1	Ankyrin repeat and FYVE domain containing 1 (alias ANKHZN and Rabankyrin-5)	PI(3)P-binding Rab5 effector, reported as Rabankyrin-5, which localizes to early endosomes and stimulates their fusion activity	15328530	2
Arl5b	ADP-ribosylation factor-like 5B	Member of GTPases, regulating cell growth and signal transduction, organization of the cytoskeleton and regulating membrane trafficking and exocytic and endocytic pathways		2
Atg3	ATG3 autophagy related 3 homolog	ATG3 displays the same enzymatic characteristics in vitro as yeast Apg3, a protein-conjugating enzyme essential for autophagy	11825910	1
Cbfb	Core-binding factor, beta subunit	Enhances DNA binding by alpha subunit as the complex binds to the core site of various enhancers and promoters, such as the GM-CSF promoter		1
Cebpb	CCAAT/enhancer-binding protein (C/EBP), beta	Regulation of genes involved in immune and inflammatory responses and has been shown to bind to the IL-1 response element in the IL-6 gene		1
Cldn1	Claudin 1	Component of tight junction strands; elevated levels in inflammatory bowel disease		1
Dnajb1	DnaJ (Hsp40) homolog, subfamily B, member 1	Involved in thermotolerance in the early phase after mild heat treatment	17050614	1
Gna13	Guanine nucleotide-binding protein (G protein), alpha 13	Regulates cell growth and differentiation through the monomeric Rho GTPase		1
Kras	v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog	Oncogene		2
Mlstd2	Fatty acyl CoA reductase 1	Fatty alcohol synthesis		3
Myo10	Myosin X	Myo10 provides a molecular link between PI(3)K and pseudopod extension during phagocytosis	12055636	1
Myo1e	Myosin IE	Contains a myosin motor domain, type I myosins; myosin I generates movement at the leading edge in cell motility, and class I myosins have been implicated in phagocytosis and vesicle transport		1
Nars	Asparaginyl-tRNA synthetase	Induced survival signaling in osteoblasts through the activation of PI3K/Akt survival pathway		1 (TargetScan 5.1)
Pdlim5	PDZ and LIM domain 5	Proteins of this family are involved in protein–protein interactions		1
Phc2	Polyhomeotic-like 2	Unknown		1
Picalm	Phosphatidylinositol-binding clathrin assembly protein	Regulates expression of cell surface VAMP2	18182011	3
Pkn2	Protein kinase N2	Unknown		1
Prkci	Protein kinase C, iota	Activates transcription of the IL-6 gene through NFkappaB and AP-1	19805306	2
Ptprj	Protein tyrosine phosphatase, receptor type, J	Potent negative regulator of Akt and K-ras	19922411	1 (TargetScan 5.1)
Rab5c	RAB5C, member RAS oncogene family	Regulates endocytic trafficking in macrophages and is induced by IL-6	16763563	2
Rheb	Ras homolog enriched in brain	Member of the small GTPase superfamily		1
Sdcbp	Syndecan-binding protein (syntenin)	Syntenin negatively regulates TRAF6-mediated IL-1R/TLR4 signaling	18234474	1
Smad1	MAD homolog 1 (Drosophila)	Smad1 has a role in regulating p38 MAPK	14718543	1
Txnrd1	Thioredoxin reductase 1	TrxR1 upregulates transcriptional activity of NF-kappaB	19555664	1 (TargetScan 5.1)
VAMP3	Vesicle-associated membrane protein 3 (cellubrevin)	Required for phagocytosis and cytokine secretion in macrophages	12101283, 16282525	2
Vezf1	Vascular endothelial zinc finger 1	Transcriptional regulation		2
Wdfy1	WD repeat and FYVE domain containing 1	Contains a FYVE domain, which mediates the recruitment of proteins involved in membrane trafficking and cell signaling to phosphatidylinositol 3-phosphate (PtdIns[3]P)-containing membranes		2
Wdr68 (DCAF7)	DDB1 and CUL4 associated factor 7	Unknown		1 (TargetScan 5.1)

Pulsed stable isotope labeling by amino acids in cell culture (pSILAC) was used to determine proteins affected by miR-155 transfection into HeLa cells (Selbach and others 2008). The 100 proteins significantly down-regulated (Selbach and others 2008) were compared to the innate immune database and the interferome database (Korb and others 2008; Samarajiwa and others 2009) and are presented here. Gene function related to innate immunity is presented, when available (with PubMed ID reference). miR-155 seed targeting of human mRNAs (and the number of seeds) was confirmed using DIANA-microT v3 (with a threshold of 2) (Maragkakis and others 2009) or TargetScan (Grimson and others 2007).

IL-1, interleukin 1; PI(3)P, phosphatidylinositol 3-phosphate; GM-CSF, granulocyte-macrophage colony-stimulating factor; IL-6, interleukin 6; PI(3)K, phosphoinositide 3-kinases; VAMP2, vesicle-associated membrane protien 2; NFkappaB, nuclear factor kappa-light-chain-enhancer of activated B cells; AP-1, activator protein 1; IL-1R, IL-1 receptor; TRAF6, tumor necrosis factor receptor-associated factor 6; MAPK, mitogen-activated protein kinase.

A relatively straightforward method for the identification of novel gene networks regulated by a given miRNA is to search for genes with a similar gene ontology annotation/reported function, within in silico predicted miRNA targets. Using a 2,361-gene list annotated as innate immune genes (Korb and others 2008) together with an miRNA target prediction software relying on TargetScan (Grimson and others 2007; Creighton and others 2008), we found that up to 52% of genes involved in innate immunity had conserved miRNAs' target sites (Gantier and Williams, unpublished data). Given that half these target predictions are probably accurate (Landgraf and others 2007), but that they omit nonconserved target sites accounting for up to 50% of all true target sites (Wu and others 2010), the speculation that about half of the innate immune genes would be targeted by miRNAs appears to be the right order of prediction. This is in agreement with previous analyses of a smaller dataset (Asirvatham and others 2008).

Looking specifically at miR-155 and its predicted conserved targets, it was observed that several SNARE proteins (soluble N-ethylmaleimide-sensitive factor accessory protein receptor) or SNARE-interacting proteins, are predicted to be concurrently regulated by miR-155 (Stx6, VTI1A, Stx16, StxBP5L, and RAB11FIP2). Together with the finding that VAMP3 is a valid target for miR-155 (Table 1), these in silico predictions suggest the involvement of these genes in a network concurrently regulating membrane fusion proteins and macrophage detection of pathogens (Stow and others 2006).

The Relevance of miRNA Induction

As with some innate immune genes, transcriptional induction of miRNAs is directly dependent on certain transcription factors and varies greatly between cell types. A key issue that the field of miRNA research in innate immunity currently faces relates to the conservation of miRNA inducibility or expression in different cells. This in turn can be very informative about the putative functional role of an miRNA.

Although most studies have so far measured the levels of miRNA following induction relative to nontreated cells, this does not reflect the actual amounts of miRNAs in the cells. High-throughput cloning of miRNAs from B cells following LPS stimulation shows that miR-155 is induced to a similar level to that of miR-146a or miR-21, indicating a similar contribution of all 3 miRNAs to the regulation of LPS signaling in these cells. However, by limiting the analysis of miRNA induction relative to that of basal levels, miR-155 induction would have been favored and the importance of miR-146a and miR-21 could have been overlooked (Fig. 1A). In addition, important variations of miRNA induction can be seen between different cell types because of differences in basal levels of miRNAs. In bone marrow-derived mouse dendritic cells (BMDCs) treated with LPS, miR-146a is induced to a much lower level than miR-155 (Fig. 1B). miR-21 is not inducible in BMDCs and the most strongly upregulated miRNA is miR-147 (12-fold increase relative to basal level), but it remains at much lower levels than miR-155/miR-21 (Fig. 1B). These differences in basal miRNA levels and inducibility between murine B cells and BMDCs may therefore highlight the potential different regulatory roles for these miRNAs in specific cells.

FIG. 1.

Induction of miRNA following LPS treatment of immune cells. Graphs (A), (B), and (C) present data formatted from the supplementary tables in the work of Landgraf and others (2007). miRNAs from different cells/treatments were cloned into small RNA libraries and sequenced. The cloning occurrence of a given miRNA is directly correlated with its abundance in the cells (Landgraf and others 2007). (A) miRNA cloning occurrence from mouse splenic B cells, stimulated for the indicated duration with IL-4 (5 ng/mL) and LPS (25 μg/mL). miR-15a, which is not affected by LPS stimulation, controls for experimental variations. (B, C) miRNA cloning occurrence from mouse splenic B cells stimulated for 24 h with IL-4 (5 ng/mL) and LPS (25 μg/mL), from mouse BMDCs at day 7 following granulocyte-macrophage colony stimulating factor (GM-CSF) treatment and stimulated or not with 1 μg/mL LPS for 24 h, and from hDCs generated from purified monocytes incubated with GM-CSF and IL-4 for 7 days and stimulated or not with 1 μg/mL LPS for 24 h. (B) Important variations of basal and induced miRNA levels can be seen between cell types (eg, for miR-155 between B cells and BMDCs). (C) Several abundant miRNAs appear to be consistently induced following LPS stimulation (eg, miR-22 and miR-142-3p). miRNAs, microRNAs; LPS, lipopolysaccharide; IL-4, interleukin 4; BMDCs, bone marrow-derived mouse dendritic cells; hDCs, human myeloid dendritic cells; NC, not cloned.

Given that only 18.4% of the innate immune genes predicted to be targets of miRNAs by Targetscan are targets of “inducible” miRNAs (ie, miR-146a, miR-155, miR-21, miR-147, and miR-9) (Gantier and Williams, unpublished data), the variation of basal miRNAs between different cell types is likely to have a key role in the fine-tuning of innate immune function, probably even greater than that of inducible miRNAs. To illustrate this point, miR-122 represents 70% of all miRNAs present in liver cells (Landgraf and others 2007), it is crucial for hepatitis C virus (HCV) replication in liver (Jopling and others 2005), and it can be downregulated following IFN treatment (Pedersen and others 2007; Sarasin-Filipowicz and others 2009). miR-1 and miR-351 have been shown to be inducible (∼5-fold) following IFN-β treatment of human hepatoma Huh7 cells (Pedersen and others 2007; Sarasin-Filipowicz and others 2009) and have been proposed to participate in the restriction of HCV replication by IFN-β (Pedersen and others 2007). However, these miRNAs were present at very low levels (fewer than 10 molecules per cell) even after IFN treatment, making it very unlikely that they play a biological role (Sarasin-Filipowicz and others 2009). Indeed, it is currently proposed that a minimum of 100 molecules of miRNA per pg of small RNAs (ie, more or less, per cell) is required for functional repression of a target mRNA (Brown and others 2007; Sarasin-Filipowicz and others 2009). Rather, 20%–40% downregulation of highly expressed miR-122 levels by IFN is probably more relevant to HCV restriction in Huh7 cells (Pedersen and others 2007; Sarasin-Filipowicz and others 2009).

Another area of concern regarding miRNA induction following innate immune activation is that of the sensitivity of miRNA profiling using microarrays. Initial screens of miRNA profiles following innate immune activation were mostly performed on miRNA microarrays (Taganov and others 2006; O'Connell and others 2007; Androulidaki and others 2009). The short length of miRNAs together with the very variable, different melting temperatures and the similarity of sequences between miRNA family members render the design of traditional DNA probes particularly challenging. The probes do not allow for the discrimination between pre-miRNA precursors and mature miRNAs, which can be of importance given that some pre-miRNAs are degraded before being processed into mature miRNAs (such as let-7 family members, miR-107, miR-143, and miR-200) (Heo and others 2009). Important discrepancies of sensitivity and specificity between the use of more sensitive polymerase chain reaction (PCR)-based miRNA quantification and that of DNA microarrays have recently been highlighted (Chen and others 2009). In-depth analysis of the cloning data from murine LPS-treated B cells/BMDCs or human dendritic cells suggests that other miRNAs could be induced by innate immune activation (such as miR-22, miR-142-5p/3p, and miR-29b) (Fig. 1C). With more sensitive techniques such as lock nucleic acid (LNA™)-based microarray, PCR-based miRNA profiling assays, and deep sequencing of small RNAs becoming widely available, it can be anticipated that more miRNAs will be shown to be regulated following innate immune recruitment in the near future.

Kinetics of miRNA Regulation

The key factors associated with mature miRNA levels are transcription, processing, and turnover. Over the last decade, much work has concentrated on the synthesis of miRNAs, which is now relatively well understood (Winter and others 2009). However, the factors regulating the stability and turnover of mature miRNAs are only now beginning to be investigated (Kai and Pasquinelli 2010). The rapid induction of several miRNAs by innate immune activation raises important questions regarding mature miRNA stability.

The miR-155 precursor (BIC) has been shown to be rapidly induced by stimulation in murine BMMs, returning to initial levels within 24 h of treatment (O'Connell and others 2009). However, the levels of mature miR-155 plateau at 24 h and decrease by only 40% between 24 and 48 h (O'Connell and others 2009). Accurate determination of miR-155 levels in the absence of its precursor is indicative of the decay rate of this miRNA in BMMs. The results from O'Connell and others (2009) indicate a high level of stability of mature miR-155 following processing of its precursor and propose that miR-155 half-life is >24 h. Although this concurs with reports using transient downregulation of the miRNA synthesis machinery (Lee and others 2003; Gregory and others 2004), a precise determination of the half-life of mature miRNAs following Dicer processing has not been attempted and remains poorly characterized as being some “days long” (Winter and others 2009; Kai and Pasquinelli 2010).

The kinetics of miRNA degradation are crucial in the characterization of their regulation. The concept that miR-155, miR-146, and miR-21 levels remain very high for up to 72 h in B cells following LPS stimulation (Fig. 1A) is strongly suggestive of a role for these inducible miRNAs in the stabilization of certain gene networks. This sustained miRNA presence indicates that they help maintain cells in their differentiated state, rather than simply contributing to cellular differentiation. The unusual persistence of mature miRNAs over several days, given the rapid kinetics of gene induction or repression following LPS stimulation, is independent of a transcriptional event and suggests a sustained regulation of hundreds of proteins involved in pathogen clearance.

On the other hand, rapid decrease of select mature miRNAs following innate immune activation has also been reported. The levels of miR-125b and let-7i have been shown to rapidly decline (within 4 h) in LPS-stimulated murine macrophages (Tili and others 2007; Androulidaki and others 2009) and cholangiocytes (Chen and others 2007), respectively. miR-122 level also diminishes rapidly (within 4 h) in Huh7 cells treated with IFN-β (Pedersen and others 2007; Sarasin-Filipowicz and others 2009). Although transcriptional regulation of these miRNAs can indeed be very rapid—as seen with miR-155 BIC induction within 1 h of treatment with LPS (O'Connell and others 2009)—rapid decrease of mature miRNA levels would imply that the turnover of these specific miRNAs following maturation by Dicer is very rapid. Given the concept that mature miRNAs would be long lived, this rapid miRNA decrease implies a targeted degradation of these miRNAs following stimulation. Recently, the nuclease XRN-2 was implicated in the degradation of miRNAs in C. elegans (Chatterjee and Grosshans 2009). However, XRN-2-mediated degradation was not miRNA specific, indicating that the mechanism underlying the differences of miRNA half-life is independent of XRN-2 activity.

The selective modification of the mature miRNA 3′ terminus is likely to play a key role in the stability of miRNAs. In their analysis of 330,000 miRNA sequences from 256 small RNA libraries from different tissues/cell types, Landgraf and others (2007) found significant sequence variation in 143 and 109 human and mouse miRNA sequences, respectively. The most frequent modifications were caused by A to I editing of miRNAs and 3′ terminal A and U additions. In mouse, 20% of all let-7i sequences cloned contained a 3′ terminal A, and 20% of miR-122 cloned from liver also had a 3′ terminal A (Landgraf and others 2007). The cytoplasmic poly(A) polymerase GLD-2 has recently been involved in the specific 3′ adenylation of miR-122 (Katoh and others 2009). The finding that GLD-2-deficient mice have lower levels of mature miR-122 in liver, but unaffected levels of the pre-miR-122 precursor, strongly suggests a protective role for GLD-2-mediated 3′-terminal adenylation in the stabilization of miR-122 (Katoh and others 2009; Kai and Pasquinelli 2010). One could infer that the rapid degradation of mature miR-122, let-7i, and miR-125b reported upon stimulation could therefore relate to an inducible regulation of the stability of these miRNAs through regulation of their 3′ termini.

Concluding Remarks

The discovery that miRNAs have altered expression patterns in cancer cells has created new opportunities in cancer research (Croce 2009) and is directly related to the explosion of the field of miRNA research. Not too surprisingly, miR-21, miR-155, and miR-146a, the prevalent innate immune miRNAs, have all been implicated in cancer and are considered as Onco-miRs (Cho 2007). This further underlines their key role in the fine-tuning of innate immune signaling pathways. Additionally, translation of miRNA research into the clinic holds great potential, as recently demonstrated with HCV inhibition with miR-122 antisense treatment in chimpanzees (Lanford and others 2010). However, miRNA-regulation of gene expression should be seen as a novel opportunity to further our understanding of gene networks and uncover novel gene functions. Type I IFN production following viral recognition is able to promote gene induction of >300 genes (Der and others 1998). Nevertheless, the direct contribution in the antiviral effect of most of these IFN-stimulated genes (ISGs) is unknown (Sadler and Williams 2008). As many ISGs are predicted targets of miRNAs, it can be envisioned that concurrent targeting of several ISGs by the same miRNA will help better define and delineate the roles of these ISGs in the antiviral response.

Footnotes

Acknowledgments

The author thanks Bryan R.G. Williams, Claire E. McCoy, Frederick J. Sheedy, and Frances Cribbin for their useful comments and their help with the redaction of this review. The author was supported by funding from the Australian NHMRC 491106.

Author Disclosure Statement

No competing financial interests exist.

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