The human genome encodes for over 1800 microRNAs, which are short noncoding RNA molecules that function to regulate gene expression post-transcriptionally. Due to the potential for one microRNA to target multiple gene transcripts, microRNAs are recognized as a major mechanism to regulate gene expression and mRNA translation. Computational prediction of microRNA targets is a critical initial step in identifying microRNA:mRNA target interactions for experimental validation. The available tools for microRNA target prediction encompass a range of different computational approaches, from the modeling of physical interactions to the incorporation of machine learning. This review provides an overview of the major computational approaches to microRNA target prediction. Our discussion highlights three tools for their ease of use, reliance on relatively updated versions of miRBase, and range of capabilities, and these are DIANA-microT-CDS, miRanda-mirSVR, and TargetScan. In comparison across all microRNA target prediction tools, four main aspects of the microRNA:mRNA target interaction emerge as common features on which most target prediction is based: seed match, conservation, free energy, and site accessibility. This review explains these features and identifies how they are incorporated into currently available target prediction tools. MicroRNA target prediction is a dynamic field with increasing attention on development of new analysis tools. This review attempts to provide a comprehensive assessment of these tools in a manner that is accessible across disciplines. Understanding the basis of these prediction methodologies will aid in user selection of the appropriate tools and interpretation of the tool output.

Notch and transforming growth factor-beta (TGFbeta) play pivotal roles during vascular development and the pathogenesis of vascular disease. The interaction of these two pathways is not fully understood. The present study utilized primary human smooth muscle cells (SMC) to examine molecular cross-talk between TGFbeta1 and Notch signaling on contractile gene expression. Activation of Notch signaling using Notch intracellular domain or Jagged1 ligand induced smooth muscle alpha-actin (SM actin), smooth muscle myosin heavy chain, and calponin1, and the expression of Notch downstream effectors hairy-related transcription factors. Similarly, TGFbeta1 treatment of human aortic smooth muscle cells induced SM actin, calponin1, and smooth muscle protein 22-alpha (SM22alpha) in a dose- and time-dependent manner. Hairy-related transcription factor proteins, which antagonize Notch activity, also suppressed the TGFbeta1-induced increase in SMC markers, suggesting a general mechanism of inhibition. We found that Notch and TGFbeta1 cooperatively activate SMC marker transcripts and protein through parallel signaling axes. Although the intracellular domain of Notch4 interacted with phosphoSmad2/3 in SMC, this interaction was not observed with Notch1 or Notch2. However, we found that CBF1 co-immunoprecipitated with phosphoSmad2/3, suggesting a mechanism to link canonical Notch signaling to phosphoSmad activity. Indeed, the combination of Notch activation and TGFbeta1 treatment led to synergistic activation of a TGFbeta-responsive promoter. This increase corresponded to increased levels of phosphoSmad2/3 interaction at Smad consensus binding sites within the SM actin, calponin1, and SM22alpha promoters. Thus, Notch and TGFbeta coordinately induce a molecular and functional contractile phenotype by co-regulation of Smad activity at SMC promoters.

Activation of Notch signaling by Jagged-1 (Jag-1) in vascular smooth muscle cells (VSMC) promotes a differentiated phenotype characterized by increased expression of contractile proteins. Recent studies show that microRNAs (miR)-143/145 regulates VSMC phenotype. The serum response factor (SRF)/myocardin complex binds to CArG sequences to activate miR-143/145 transcription, but no other regulators are known in VSMC. Using miR arrays, we found miR-143/145 induced following expression of a constitutively active Notch1 intracellular domain (N1ICD). We hypothesized that miR-143/145 is required for Jag-1/Notch-induced VSMC differentiation. Activation of Notch receptors by Jag-1 caused CBF1-dependent up-regulation of miR-143/145, increased differentiation, and decreased proliferation. Conversely, inhibiting basal Notch signaling decreased steady state levels of miR-143/145. Using SRF knockdown, we found that Jag-1/Notch induction of miR-143/145 is SRF independent, although full acquisition of contractile markers requires SRF. Using miR-143/145 promoter reporter constructs we show Jag-1/Notch increases promoter activity, and this is dependent on intact CBF1 consensus sites within the promoter. Chromatin immunoprecipitation (ChIP) assays revealed that N1ICD-containing complexes bind to CBF1 sites in the miR-143/145 promoter. We also identified N1ICD complex binding to CBF1 sites within the endogenous human miR-143/145 promoter. Using miR-143/145-interfering oligonucleotides, we demonstrate that Jag-1/Notch signaling requires induction of both miR-143 and miR-145 to promote the VSMC contractile phenotype. Thus, miR-143/145 is a novel transcriptional target of Jag-1/Notch signaling in VSMC. We propose miR-143/145 as activated independently by Jag-1/Notch and SRF in parallel pathways. Multiple pathways converging on miR-143/145 provides potential for fine-tuning or amplification of VSMC differentiation signals.

Notch signaling in the cardiovascular system is important during embryonic development, vascular repair of injury, and vascular pathology in humans. The vascular smooth muscle cell (VSMC) expresses multiple Notch receptors throughout its life cycle, and responds to Notch ligands as a regulatory mechanism of differentiation, recruitment to growing vessels, and maturation. The goal of this review is to provide an overview of the current understanding of the molecular basis for Notch regulation of VSMC phenotype. Further, we will explore Notch interaction with other signaling pathways important in VSMC.

Notch signaling regulates smooth muscle cell phenotype and is critical for vascular development. One Notch target is smooth muscle α-actin (SMA), a differentiated smooth muscle cell marker. The Notch intracellular domain (NotchICD) forms a complex with CBF-1 (C-promoter–binding factor-1) and directly induces SMA expression. Using primary human smooth muscle cells, we show that expression of the constitutive active ICD of human Notch1, Notch2, or Notch4 receptors increase SMA levels. NotchICD also induce expression of the transcriptional repressors HRT1 (Hairy-related transcription factor 1) and HRT2, in a CBF-1–dependent manner. However, unlike the activating effects of NotchICD, HRT1 or HRT2 represses basal SMA expression, and both are strong antagonists of NotchICD-induced SMA upregulation. This antagonism does not depend on histone deacetylase activity and occurs at the transcriptional level. Competitive coimmunoprecipitation experiments demonstrate that HRT does not disrupt the association of NotchICD and CBF-1, which form a complex in the presence or absence of HRTs. However, HRT suppresses NotchICD/CBF-1 binding to the SMA promoter, as measured by chromatin immunoprecipitation, and transactivation of an SMA promoter reporter spanning sequences −124/+32. SMA expression was regulated similarly following endogenous Notch activation in smooth muscle cells by coculture with endothelial cells, and this effect was also sensitive to HRT inhibition. Temporally defined HRT activity may constitute a negative feedback mechanism of Notch signaling. Our study presents a novel mechanism by which a balance between Notch signaling and HRT activity determines the expression of smooth muscle differentiation markers including SMA.