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PubMed2006

MicroRNA responses to cellular stress.

Recent work has begun to explore the instrumental role that small noncoding RNA species, particularly microRNAs (miRNA), have both in classifying human tumors and in directing embryonic development. These studies suggest that developmental programs in essentially all organisms studied are set, in part, by varied expressions of miRNAs and that neoplasia is characterized by altered expression of miRNAs. Reasoning that these observations are linked, we examined whether cellular exposures that induce both developmental anomalies and cancer alter miRNAs. Using microarrays of 385 known human miRNAs, we studied human lymphoblastoid cells grown under various conditions or treatments. Folate deficiency induced a pronounced global increase in miRNA expression. We observed no significant alteration in miRNA expression in cells treated with gamma-irradiation, whereas exposure to sodium arsenite led to global increases in miRNA expression. The miRNA hsa-miR-222 was identified from these arrays as significantly overexpressed under folate-deficient conditions, and this finding was confirmed in vivo in human peripheral blood from individuals with low folate intake. Alterations to cellular miRNA expression profiles represent a novel mode of action of folate deprivation and arsenic exposure, and specific alterations in miRNA expression may be a powerful biomarker for these and other toxins with serious effects on human health.

Arsenites↗
PubMed2006

Synthetic microRNA designed to target glioma-associated antigen 1 transcription factor inhibits division and induces late apoptosis in pancreatic tumor cells.

PURPOSE: To determine whether the synthetic microRNAs (miRNA) could effectively target tumor cells we designed several miRNA complementary to glioma-associated antigen-1 (Gli-1) mRNA and investigated their ability to inhibit tumor cell proliferation. The sonic hedgehog pathway is an early and late mediator of tumorigenesis in epithelial cancers. Activation of sonic hedgehog signaling seems to precede transformation of tissue stem cells to cancerous stem cells, with the Gli-1 transcription factor functioning as a mediator of environmental signals. Inhibiting cancer cell proliferation by targeting the Gli-1 effector pathway is difficult to achieve by chemotherapeutic agents or short interfering RNA. EXPERIMENTAL DESIGN: We hypothesized that targeting the 3'-untranslated region of Gli-1 mRNA would effectively inhibit tumor cell proliferation. To test this hypothesis, we used synthetic miRNAs of our own design and corresponding duplex/small temporal RNAs by introducing three-nucleotide loops in the 3'-untranslated region Gli-1 sequence of high GU content. RESULTS: We found that miRNA (Gli-1-miRNA-3548) and its corresponding duplex (Duplex-3548) significantly inhibited proliferation of Gli-1+ ovarian (SK-OV-3) and pancreatic (MiaPaCa-2) tumor cells. The miRNAs mediated delayed cell division and activation of late apoptosis in MiaPaCa-2 cells. This is the first demonstration of inhibition of pancreatic tumor cell division by designed miRNA. CONCLUSIONS: Gli-1 miRNAs should significantly add to the general understanding of the mechanisms of metastasis and contribute toward the design of better treatments for epithelial cancers.

3' Untranslated Regions↗
PubMed2026

Suppression of AAV-Delivered Transgene Expression Using Artificial MicroRNAs Delivered by an Alternative AAV Serotype.

Adeno-associated virus (AAV) gene transfer vectors mediate long-term expression in nondividing cells, an advantage for treating chronic disorders. However, current platforms lack a way to selectively shut down transgene expression if adverse effects arise. To create an "off switch," we hypothesized that incorporating unique artificial microRNA (amiRNA) target sequences into an AAV expression cassette would allow subsequent suppression of transgene expression using a second AAV vector encoding the cognate amiRNA. We introduced 22-nt sequences absent from human and mouse transcriptomes into the 3' untranslated region (UTR) of a therapeutic AAV cassette. To identify optimal amiRNAs, two tandem copies of each amiRNA were cloned into the 3'UTR of an mCherry reporter gene. In vitro assessment of six amiRNA/target pairs using a dual luciferase assay identified four amiRNAs that efficiently suppressed reporter expression. Cells cotransfected with target site 3 (TS3) and amiRNA-T3B showed the greatest reduction in luciferase activity (80%, p < 0.0001) and were selected for further study. The "off-switch" system was then evaluated using an AAV5 therapeutic vector expressing a recombinant humanized anti-IgE monoclonal antibody (AAV5-TBG-anti-IgE-TS3), designed for long-term suppression of allergen-induced reactions. Co-transfection of HEK293T cells with anti-IgE-TS3 and amiRNA-T3B significantly reduced anti-IgE mRNA and protein levels relative to a control amiRNA (p < 0.0001). In vivo testing in Balb/c mice (n = 5) involved intravenous administration of AAV5-anti-IgE-TS3 (3.2 &#xd7; 1010 gc), followed 4 weeks later by an AAVrh.10 amiRNA vector (AAVrh.10-TBG-amiRNA-T3B; 1 &#xd7; 1011 gc). Control mice receiving only the therapeutic vector expressed 18.4 &#xb1; 13.8 &#xb5;g/mL serum anti-IgE at 10 weeks. In contrast, mice receiving the amiRNA "off" vector showed marked suppression of anti-IgE (0.3 &#xb1; 0.15 &#xb5;g/mL, p < 0.0001). These findings provide proof-of-concept that AAV-delivered amiRNAs can selectively switch off transgene expression, offering a strategy to improve the safety of AAV-mediated gene therapies.

Dependovirus↗
PubMed2006

MicroRNAs modulate the angiogenic properties of HUVECs.

MicroRNAs (miRNAs) have recently come into focus as key posttranscriptional modulators of gene expression. In this work, we addressed whether in vitro angiogenesis is an miRNA-regulated process. We performed large-scale analysis of miRNA expression in human umbilical vein endothelial cells (HUVECs) and found that 15 highly expressed miRNAs have the receptors of angiogenic factors as putative targets. In particular, we demonstrated that miR-221 and miR-222 affect c-Kit expression and, as a consequence, the angiogenic properties of its ligand stem cell factor. Interaction between miR-222 and c-Kit is likely to be part of a complex circuit that controls the ability of endothelial cells to form new capillaries.

Endothelium, Vascular↗
PubMed2005

Identification of clustered microRNAs using an ab initio prediction method.

BACKGROUND: MicroRNAs (miRNAs) are endogenous 21 to 23-nucleotide RNA molecules that regulate protein-coding gene expression in plants and animals via the RNA interference pathway. Hundreds of them have been identified in the last five years and very recent works indicate that their total number is still larger. Therefore miRNAs gene discovery remains an important aspect of understanding this new and still widely unknown regulation mechanism. Bioinformatics approaches have proved to be very useful toward this goal by guiding the experimental investigations. RESULTS: In this work we describe our computational method for miRNA prediction and the results of its application to the discovery of novel mammalian miRNAs. We focus on genomic regions around already known miRNAs, in order to exploit the property that miRNAs are occasionally found in clusters. Starting with the known human, mouse and rat miRNAs we analyze 20 kb of flanking genomic regions for the presence of putative precursor miRNAs (pre-miRNAs). Each genome is analyzed separately, allowing us to study the species-specific identity and genome organization of miRNA loci. We only use cross-species comparisons to make conservative estimates of the number of novel miRNAs. Our ab initio method predicts between fifty and hundred novel pre-miRNAs for each of the considered species. Around 30% of these already have experimental support in a large set of cloned mammalian small RNAs. The validation rate among predicted cases that are conserved in at least one other species is higher, about 60%, and many of them have not been detected by prediction methods that used cross-species comparisons. A large fraction of the experimentally confirmed predictions correspond to an imprinted locus residing on chromosome 14 in human, 12 in mouse and 6 in rat. Our computational tool can be accessed on the world-wide-web. CONCLUSION: Our results show that the assumption that many miRNAs occur in clusters is fruitful for the discovery of novel miRNAs. Additionally we show that although the overall miRNA content in the observed clusters is very similar across the three considered species, the internal organization of the clusters changes in evolution.

Algorithms↗
PubMed2005

Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine.

BACKGROUND: MicroRNAs (miRNAs) are a group of short (approximately 22 nt) non-coding RNAs that play important regulatory roles. MiRNA precursors (pre-miRNAs) are characterized by their hairpin structures. However, a large amount of similar hairpins can be folded in many genomes. Almost all current methods for computational prediction of miRNAs use comparative genomic approaches to identify putative pre-miRNAs from candidate hairpins. Ab initio method for distinguishing pre-miRNAs from sequence segments with pre-miRNA-like hairpin structures is lacking. Being able to classify real vs. pseudo pre-miRNAs is important both for understanding of the nature of miRNAs and for developing ab initio prediction methods that can discovery new miRNAs without known homology. RESULTS: A set of novel features of local contiguous structure-sequence information is proposed for distinguishing the hairpins of real pre-miRNAs and pseudo pre-miRNAs. Support vector machine (SVM) is applied on these features to classify real vs. pseudo pre-miRNAs, achieving about 90% accuracy on human data. Remarkably, the SVM classifier built on human data can correctly identify up to 90% of the pre-miRNAs from other species, including plants and virus, without utilizing any comparative genomics information. CONCLUSION: The local structure-sequence features reflect discriminative and conserved characteristics of miRNAs, and the successful ab initio classification of real and pseudo pre-miRNAs opens a new approach for discovering new miRNAs.

Animals↗
PubMed2006

Lower expression of genes near microRNA in C. elegans germline.

BACKGROUND: MicroRNAs (miRNAs) are recently discovered short non-protein-coding RNA molecules. miRNAs are increasingly implicated in tissue-specific transcriptional control and particularly in development. Because there is mounting evidence for the localized component of transcriptional control, we investigated if there is a distance-dependent effect of miRNA. RESULTS: We analyzed gene expression levels around the 84 of 113 know miRNAs for which there are nearby gene that were measured in the data in two independent C. elegans expression data sets. The expression levels are lower for genes in the vicinity of 59 of 84 (71%) miRNAs as compared to genes far from such miRNAs. Analysis of the genes with lower expression in proximity to the miRNAs reveals increased frequency matching of the 7 nucleotide "seed"s of these miRNAs. CONCLUSION: We found decreased messenger RNA (mRNA) abundance, localized within a 10 kb of chromosomal distance of some miRNAs, in C. elegans germline. The increased frequency of seed matching near miRNA can explain, in part, the localized effects.

Animals↗
PubMed2006

miTarget: microRNA target gene prediction using a support vector machine.

BACKGROUND: MicroRNAs (miRNAs) are small noncoding RNAs, which play significant roles as posttranscriptional regulators. The functions of animal miRNAs are generally based on complementarity for their 5' components. Although several computational miRNA target-gene prediction methods have been proposed, they still have limitations in revealing actual target genes. RESULTS: We implemented miTarget, a support vector machine (SVM) classifier for miRNA target gene prediction. It uses a radial basis function kernel as a similarity measure for SVM features, categorized by structural, thermodynamic, and position-based features. The latter features are introduced in this study for the first time and reflect the mechanism of miRNA binding. The SVM classifier produces high performance with a biologically relevant data set obtained from the literature, compared with previous tools. We predicted significant functions for human miR-1, miR-124a, and miR-373 using Gene Ontology (GO) analysis and revealed the importance of pairing at positions 4, 5, and 6 in the 5' region of a miRNA from a feature selection experiment. We also provide a web interface for the program. CONCLUSION: miTarget is a reliable miRNA target gene prediction tool and is a successful application of an SVM classifier. Compared with previous tools, its predictions are meaningful by GO analysis and its performance can be improved given more training examples.

Algorithms↗
PubMed2006

Molecular phylogenetics and comparative modeling of HEN1, a methyltransferase involved in plant microRNA biogenesis.

BACKGROUND: Recently, HEN1 protein from Arabidopsis thaliana was discovered as an essential enzyme in plant microRNA (miRNA) biogenesis. HEN1 transfers a methyl group from S-adenosylmethionine to the 2'-OH or 3'-OH group of the last nucleotide of miRNA/miRNA* duplexes produced by the nuclease Dicer. Previously it was found that HEN1 possesses a Rossmann-fold methyltransferase (RFM) domain and a long N-terminal extension including a putative double-stranded RNA-binding motif (DSRM). However, little is known about the details of the structure and the mechanism of action of this enzyme, and about its phylogenetic origin. RESULTS: Extensive database searches were carried out to identify orthologs and close paralogs of HEN1. Based on the multiple sequence alignment a phylogenetic tree of the HEN1 family was constructed. The fold-recognition approach was used to identify related methyltransferases with experimentally solved structures and to guide the homology modeling of the HEN1 catalytic domain. Additionally, we identified a La-like predicted RNA binding domain located C-terminally to the DSRM domain and a domain with a peptide prolyl cis/trans isomerase (PPIase) fold, but without the conserved PPIase active site, located N-terminally to the catalytic domain. CONCLUSION: The bioinformatics analysis revealed that the catalytic domain of HEN1 is not closely related to any known RNA:2'-OH methyltransferases (e.g. to the RrmJ/fibrillarin superfamily), but rather to small-molecule methyltransferases. The structural model was used as a platform to identify the putative active site and substrate-binding residues of HEN and to propose its mechanism of action.

Amino Acid Sequence↗
PubMed2005

Computational evidence for hundreds of non-conserved plant microRNAs.

BACKGROUND: MicroRNAs (miRNA) are small (20-25 nt) non-coding RNA molecules that regulate gene expression through interaction with mRNA in plants and metazoans. A few hundred miRNAs are known or predicted, and most of those are evolutionarily conserved. In general plant miRNA are different from their animal counterpart: most plant miRNAs show near perfect complementarity to their targets. Exploiting this complementarity we have developed a method for identification plant miRNAs that does not rely on phylogenetic conservation. RESULTS: Using the presumed targets for the known miRNA as positive controls, we list and filter all segments of the genome of length approximately 20 that are complementary to a target mRNA-transcript. From the positive control we recover 41 (of 92 possible) of the already known miRNA-genes (representing 14 of 16 families) with only four false positives. Applying the procedure to find possible new miRNAs targeting any annotated mRNA, we predict of 592 new miRNA genes, many of which are not conserved in other plant genomes. A subset of our predicted miRNAs is additionally supported by having more than one target that are not homologues. CONCLUSION: These results indicate that it is possible to reliably predict miRNA-genes without using genome comparisons. Furthermore it suggests that the number of plant miRNAs have been underestimated and points to the existence of recently evolved miRNAs in Arabidopsis.

Animals↗
PubMed2005

Prediction and verification of microRNA targets by MovingTargets, a highly adaptable prediction method.

BACKGROUND: MicroRNAs (miRNAs) mediate a form of translational regulation in animals. Hundreds of animal miRNAs have been identified, but only a few of their targets are known. Prediction of miRNA targets for translational regulation is challenging, since the interaction with the target mRNA usually occurs via incomplete and interrupted base pairing. Moreover, the rules that govern such interactions are incompletely defined. RESULTS: MovingTargets is a software program that allows a researcher to predict a set of miRNA targets that satisfy an adjustable set of biological constraints. We used MovingTargets to identify a high-likelihood set of 83 miRNA targets in Drosophila, all of which adhere to strict biological constraints. We tested and verified 3 of these predictions in cultured cells, including a target for the Drosophila let-7 homolog. In addition, we utilized the flexibility of MovingTargets by relaxing the biological constraints to identify and validate miRNAs targeting tramtrack, a gene also known to be subject to translational control dependent on the RNA binding protein Musashi. CONCLUSION: MovingTargets is a flexible tool for the accurate prediction of miRNA targets in Drosophila. MovingTargets can be used to conduct a genome-wide search of miRNA targets using all Drosophila miRNAs and potential targets, or it can be used to conduct a focused search for miRNAs targeting a specific gene. In addition, the values for a set of biological constraints used to define a miRNA target are adjustable, allowing the software to incorporate the rules used to characterize a miRNA target as these rules are experimentally determined and interpreted.

3' Untranslated Regions↗
PubMed2006

Bioinformatic discovery of microRNA precursors from human ESTs and introns.

BACKGROUND: MicroRNAs (miRNAs) function in many physiological processes, and their discovery is beneficial for further studying their physiological functions. However, many of the miRNAs predicted from genomic sequences have not been experimentally validated to be authentic expressed RNA transcripts, thereby decreasing the reliability of miRNA discovery. To overcome this problem, we examined expressed transcripts - ESTs and intronic sequences - to identify novel miRNAs as well as their target genes. RESULTS: To facilitate our approach, we developed our scanning method using criteria based on the features of 207 known human pre-miRNAs to discriminate miRNAs from random sequences. We identified 208 candidate hairpins in human ESTs and human reference gene intronic sequences, 52 of which are known pre-miRNAs. The discovery pipeline performance was further assessed using 130 newly updated pre-miRNA and randomly selected sequences. We achieved sensitivity of 85% (110/130) and overall specificity of 49.7% using this method. Because miRNAs are evolutionarily conserved regulators of gene expression, it is expected that their host genes and target genes should have respective phylogenetic orthologs. Our results confirmed that, in certain mammals, the host genes carrying the same miRNAs are orthologs, as previously reported. Moreover, this observation is also the case for some of the miRNA target genes. CONCLUSION: We have predicted 208 human pre-miRNA candidates and over 10,000 putative human target genes. Using sequence information from ESTs and introns ensures that the predicted pre-miRNA candidates are expressed and the combined expression transcription information from ESTs and introns makes our prediction results more decisive with regard to expressed pre-miRNAs.

3' Untranslated Regions↗
PubMed2006

SAGE detects microRNA precursors.

BACKGROUND: MicroRNAs (miRNAs) have been shown to play important roles in regulating gene expression. Since miRNAs are often evolutionarily conserved and their precursors can be folded into stem-loop hairpins, many miRNAs have been predicted. Yet experimental confirmation is difficult since miRNA expression is often specific to particular tissues and developmental stages. RESULTS: Analysis of 29 human and 230 mouse longSAGE libraries revealed the expression of 22 known and 10 predicted mammalian miRNAs. Most were detected in embryonic tissues. Four SAGE tags detected in human embryonic stem cells specifically match a cluster of four human miRNAs (mir-302a, b, c&d) known to be expressed in embryonic stem cells. LongSAGE data also suggest the existence of a mouse homolog of human and rat mir-493. CONCLUSION: The observation that some orphan longSAGE tags uniquely match miRNA precursors provides information about the expression of some known and predicted miRNAs.

Animals↗
PubMed2006

Identification by Real-time PCR of 13 mature microRNAs differentially expressed in colorectal cancer and non-tumoral tissues.

MicroRNAs (miRNAs) are short non-coding RNA molecules playing regulatory roles by repressing translation or cleaving RNA transcripts. Although the number of verified human miRNA is still expanding, only few have been functionally described. However, emerging evidences suggest the potential involvement of altered regulation of miRNA in pathogenesis of cancers and these genes are thought to function as both tumours suppressor and oncogenes. In our study, we examined by Real-Time PCR the expression of 156 mature miRNA in colorectal cancer. The analysis by several bioinformatics algorithms of colorectal tumours and adjacent non-neoplastic tissues from patients and colorectal cancer cell lines allowed identifying a group of 13 miRNA whose expression is significantly altered in this tumor. The most significantly deregulated miRNA being miR-31, miR-96, miR-133b, miR-135b, miR-145, and miR-183. In addition, the expression level of miR-31 was correlated with the stage of CRC tumor. Our results suggest that miRNA expression profile could have relevance to the biological and clinical behavior of colorectal neoplasia.

Cluster Analysis↗
PubMed2004

HIV-1 nef suppression by virally encoded microRNA.

BACKGROUND: MicroRNAs (miRNAs) are 21 to approximately 25-nucleotides (nt) long and interact with mRNAs to trigger either translational repression or RNA cleavage through RNA interference (RNAi), depending on the degree of complementarity with the target mRNAs. Our recent study has shown that HIV-1 nef dsRNA from AIDS patients who are long-term non-progressors (LTNPs) inhibited the transcription of HIV-1. RESULTS: Here, we show the possibility that nef-derived miRNAs are produced in HIV-1 persistently infected cells. Furthermore, nef short hairpin RNA (shRNA) that corresponded to a predicted nef miRNA (approximately 25 nt, miR-N367) can block HIV-1 Nef expression in vitro and the suppression by shRNA/miR-N367 would be related with low viremia in an LTNP (15-2-2). In the 15-2-2 model mice, the weight loss, which may be rendered by nef was also inhibited by shRNA/miR-N367 corresponding to suppression of nef expression in vivo. CONCLUSIONS: These data suggest that nef/U3 miRNAs produced in HIV-1-infected cells may suppress both Nef function and HIV-1 virulence through the RNAi pathway.

Acquired Immunodeficiency Syndrome↗
PubMed2005

Changes in microRNA expression profiles in HIV-1-transfected human cells.

MicroRNAs (miRNAs) are small RNAs of 18-25 nucleotides (nt) in length that play important roles in regulating a variety of biological processes. Recent studies suggest that cellular miRNAs may serve to control the replication of viruses in cells. If such is the case, viruses might be expected to evolve the ability to modulate the expression of cellular miRNAs. To ask if expression of HIV-1 genes changes the miRNA profiles in human cells, we employed a high throughput microarray method, termed the RNA-primed Array-based Klenow Enzyme (RAKE) assay. Here, we describe the optimization of this assay to quantify the expression of miRNAs in HIV-1 transfected human cells. We report distinct differences in miRNA profiles in mock-transfected HeLa cells versus HeLa cells transfected with an infectious HIV-1 molecular clone, pNL4-3.

Gene Expression Profiling↗
PubMed2003

Computational identification of Drosophila microRNA genes.

BACKGROUND: MicroRNAs (miRNAs) are a large family of 21-22 nucleotide non-coding RNAs with presumed post-transcriptional regulatory activity. Most miRNAs were identified by direct cloning of small RNAs, an approach that favors detection of abundant miRNAs. Three observations suggested that miRNA genes might be identified using a computational approach. First, miRNAs generally derive from precursor transcripts of 70-100 nucleotides with extended stem-loop structure. Second, miRNAs are usually highly conserved between the genomes of related species. Third, miRNAs display a characteristic pattern of evolutionary divergence. RESULTS: We developed an informatic procedure called 'miRseeker', which analyzed the completed euchromatic sequences of Drosophila melanogaster and D. pseudoobscura for conserved sequences that adopt an extended stem-loop structure and display a pattern of nucleotide divergence characteristic of known miRNAs. The sensitivity of this computational procedure was demonstrated by the presence of 75% (18/24) of previously identified Drosophila miRNAs within the top 124 candidates. In total, we identified 48 novel miRNA candidates that were strongly conserved in more distant insect, nematode, or vertebrate genomes. We verified expression for a total of 24 novel miRNA genes, including 20 of 27 candidates conserved in a third species and 4 of 11 high-scoring, Drosophila-specific candidates. Our analyses lead us to estimate that drosophilid genomes contain around 110 miRNA genes. CONCLUSIONS: Our computational strategy succeeded in identifying bona fide miRNA genes and suggests that miRNAs constitute nearly 1% of predicted protein-coding genes in Drosophila, a percentage similar to the percentage of miRNAs recently attributed to other metazoan genomes.

Animals↗