Lost in translation: an assessment and perspective for computational microRNA target identification

Regulation of NF-κB signaling by oxidized glycerophospholipid and IL-1β induced miRs-21-3p and -27a-5p in human aortic endothelial cells

Exposure of endothelial cells (ECs) to agents such as oxidized glycerophospholipids (oxGPs) and cytokines, known to accumulate in atherosclerotic lesions, perturbs the expression of hundreds of genes in ECs involved in inflammatory and other biological processes. We hypothesized that microRNAs (miRNAs) are involved in regulating the inflammatory response in human aortic endothelial cells (HAECs) in response to oxGPs and interleukin 1β (IL-1β). Using next-generation sequencing and RT-quantitative PCR, we characterized the profile of expressed miRNAs in HAECs pre- and postexposure to oxGPs. Using this data, we identified miR-21-3p and miR-27a-5p to be induced 3- to 4-fold in response to oxGP and IL-1β treatment compared with control treatment. Transient overexpression of miR-21-3p and miR-27a-5p resulted in the downregulation of 1,253 genes with 922 genes overlapping between the two miRNAs. Gene Ontology functional enrichment analysis predicted that the two miRNAs were involved in the regulation of nuclear factor κB (NF-κB) signaling. Overexpression of these two miRNAs leads to changes in p65 nuclear translocation. Using 3' untranslated region luciferase assay, we identified 20 genes within the NF-κB signaling cascade as putative targets of miRs-21-3p and -27a-5p, implicating these two miRNAs as modulators of NF-κB signaling in ECs.

Regulation of cytochrome b5 expression by miR-223 in human liver: effects on cytochrome P450 activities

PURPOSE

Cytochrome b5 (b5) is a hemoprotein that transfers electrons to several enzymes to fulfill functions in fatty acid desaturation, methemoglobin reduction, steroidogenesis, and drug metabolism. Despite the importance of b5, the regulation of b5 expression in human liver remains largely unknown. We investigated whether microRNA (miRNA) might be involved in the regulation of human b5.

METHODS

Twenty-four human liver specimens were used for correlation analysis. In silico analysis and luciferase assay were performed to determine whether the predicted miRNAs functionally target to b5. The miR-223 was overexpressed into HepG2 cells infected with adenovirus expressing human cytochrome P450.

RESULTS

In human livers, the b5 protein levels were not positively correlated with the b5 mRNA levels, and miR-223 levels were inversely correlated with the b5 mRNA levels or the translational efficiencies. The luciferase assay showed that miR-223 functionally binds to the element in the 3′-untranslated region of b5 mRNA. The overexpression of miR-223 significantly reduced the endogenous b5 protein level and the mRNA stability in HepG2 cells. Moreover, the overexpression of miR-223 significantly reduced CYP3A4-catalyzed testosterone 6β-hydroxylation activity and CYP2E1-catalyzed chlorzoxazone 6-hydroxylase activity but not CYP1A2-catalyzed 7-ethoxyresorufin O-deethylase activity.

CONCLUSIONS

miR-223 down-regulates b5 expression in the human liver, modulating P450 activities.

Large-scale modeling of condition-specific gene regulatory networks by information integration and inference

Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η² (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research.

miRror2.0: a platform for assessing the joint action of microRNAs in cell regulation

microRNAs (miRNAs) are short, noncoding RNAs that negatively regulate the levels of mRNA post-transcriptionally. Recent experiments revealed thousands of mRNA-miRNA pairs in which multiple miRNAs may bind the same transcript. These results raised the notion of miRNAs teamwork for a wide range of cellular context. miRror2.0 utilizes the miRNA-target predictions from over a dozen programs and resources and unifies them under a common statistical basis. The platform, called miRror2.0, considers the combinatorial regulation by miRNAs in different tissues, cell lines and under a broad range of conditions. A flexible setting permits the selection of the preferred combination of miRNA-target prediction resources as well as the statistical parameters for the analysis. miRror2.0 covers six major model organisms including human and mouse. Importantly, the system is capable of analyzing hundreds of genes that were subjected to miRNAs' regulation. Activating miRror2.0 by introducing thousands of genes from miRNA overexpression experiments successfully identified the objective miRNAs. The output from miRror2.0 is a list of genes that is optimally regulated by a defined set of miRNAs. A symmetric application of miRror2.0 starts with a set of miRNAs, and the system then seeks the preferred set of genes that are regulated by that miRNA composition. The results from miRror2.0 are empowered by an iterative procedure called PSI-miRror. PSI-miRror tests the robustness of miRror2.0 prediction. It allows a refinement of the initial list of genes in view of the miRNAs that optimally regulate this list. We present miRror2.0 as a valuable resource for supporting cellular experimentalists that seek recovery of combinatorial regulation by miRNAs from noisy experimental data. miRror2.0 is available at http://www.mirrorsuite.cs.huji.ac.il .

MicroRNA target identification: lessons from hypoxamiRs

SIGNIFICANCE

MicroRNAs (miRNAs) are small noncoding RNAs that have emerged as key regulators of many physiological and pathological processes, including those relevant to hypoxia such as cancer, neurological dysfunctions, myocardial infarction, and lung diseases.

RECENT ADVANCES

During the last 5 years, miRNAs have been shown to play a role in the regulation of the cellular response to hypoxia. The identification of several bona fide targets of these hypoxamiRs has underlined their pleiotropic functions and the complexity of the molecular rules directing miRNA::target transcript pairing.

CRITICAL ISSUES

This review outlines the main in silico and experimental approaches used to identify the targetome of hypoxamiRs and presents new recent relevant methodologies for future studies.

FUTURE DIRECTIONS

Since hypoxia plays key roles in many pathophysiological conditions, the precise characterization of regulatory hypoxamiRs networks will be instrumental both at a fundamental level and for their future potential therapeutic applications.

A systems biology approach identified different regulatory networks targeted by KSHV miR-K12-11 in B cells and endothelial cells

Background

Kaposi’s sarcoma associated herpes virus (KSHV) is associated with tumors of endothelial and lymphoid origin. During latent infection, KSHV expresses miR-K12-11, an ortholog of the human tumor gene hsa-miR-155. Both gene products are microRNAs (miRNAs), which are important post-transcriptional regulators that contribute to tissue specific gene expression. Advances in target identification technologies and molecular interaction databases have allowed a systems biology approach to unravel the gene regulatory networks (GRNs) triggered by miR-K12-11 in endothelial and lymphoid cells. Understanding the tissue specific function of miR-K12-11 will help to elucidate underlying mechanisms of KSHV pathogenesis.

Results

Ectopic expression of miR-K12-11 differentially affected gene expression in BJAB cells of lymphoid origin and TIVE cells of endothelial origin. Direct miRNA targeting accounted for a small fraction of the observed transcriptome changes: only 29 genes were identified as putative direct targets of miR-K12-11 in both cell types. However, a number of commonly affected biological pathways, such as carbohydrate metabolism and interferon response related signaling, were revealed by gene ontology analysis. Integration of transcriptome profiling, bioinformatic algorithms, and databases of protein-protein interactome from the ENCODE project identified different nodes of GRNs utilized by miR-K12-11 in a tissue-specific fashion. These effector genes, including cancer associated transcription factors and signaling proteins, amplified the regulatory potential of a single miRNA, from a small set of putative direct targets to a larger set of genes.

Conclusions

This is the first comparative analysis of miRNA-K12-11’s effects in endothelial and B cells, from tissues infected with KSHV in vivo. MiR-K12-11 was able to broadly modulate gene expression in both cell types. Using a systems biology approach, we inferred that miR-K12-11 establishes its GRN by both repressing master TFs and influencing signaling pathways, to counter the host anti-viral response and to promote proliferation and survival of infected cells. The targeted GRNs are more reproducible and informative than target gene identification, and our approach can be applied to other regulatory factors of interest.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-668) contains supplementary material, which is available to authorized users.

Molecular interaction networks for the analysis of human disease: utility, limitations, and considerations

High-throughput '-omics' data can be combined with large-scale molecular interaction networks, for example, protein-protein interaction networks, to provide a unique framework for the investigation of human molecular biology. Interest in these integrative '-omics' methods is growing rapidly because of their potential to understand complexity and association with disease; such approaches have a focus on associations between phenotype and "network-type." The potential of this research is enticing, yet there remain a series of important considerations. Here, we discuss interaction data selection, data quality, the relative merits of using data from large high-throughput studies versus a meta-database of smaller literature-curated studies, and possible issues of sociological or inspection bias in interaction data. Other work underway, especially international consortia to establish data formats, quality standards and address data redundancy, and the improvements these efforts are making to the field, is also evaluated. We present options for researchers intending to use large-scale molecular interaction networks as a functional context for protein or gene expression data, including microRNAs, especially in the context of human disease.

The multiMiR R package and database: integration of microRNA-target interactions along with their disease and drug associations

microRNAs (miRNAs) regulate expression by promoting degradation or repressing translation of target transcripts. miRNA target sites have been catalogued in databases based on experimental validation and computational prediction using various algorithms. Several online resources provide collections of multiple databases but need to be imported into other software, such as R, for processing, tabulation, graphing and computation. Currently available miRNA target site packages in R are limited in the number of databases, types of databases and flexibility. We present multiMiR, a new miRNA-target interaction R package and database, which includes several novel features not available in existing R packages: (i) compilation of nearly 50 million records in human and mouse from 14 different databases, more than any other collection; (ii) expansion of databases to those based on disease annotation and drug microRNAresponse, in addition to many experimental and computational databases; and (iii) user-defined cutoffs for predicted binding strength to provide the most confident selection. Case studies are reported on various biomedical applications including mouse models of alcohol consumption, studies of chronic obstructive pulmonary disease in human subjects, and human cell line models of bladder cancer metastasis. We also demonstrate how multiMiR was used to generate testable hypotheses that were pursued experimentally.

Identification and consequences of miRNA-target interactions--beyond repression of gene expression

Comparative genomics analyses and high-throughput experimental studies indicate that a microRNA (miRNA) binds to hundreds of sites across the transcriptome. Although the knockout of components of the miRNA biogenesis pathway has profound phenotypic consequences, most predicted miRNA targets undergo small changes at the mRNA and protein levels when the expression of the miRNA is perturbed. Alternatively, miRNAs can establish thresholds in and increase the coherence of the expression of their target genes, as well as reduce the cell-to-cell variability in target gene expression. Here, we review the recent progress in identifying miRNA targets and the emerging paradigms of how miRNAs shape the dynamics of target gene expression.

The new world of RNAs

One of the major developments that resulted from the human genome sequencing projects was a better understanding of the role of non-coding RNAs (ncRNAs). NcRNAs are divided into several different categories according to size and function; however, one shared feature is that they are not translated into proteins. In this review, we will discuss relevant aspects of ncRNAs, focusing on two main types: i) microRNAs, which negatively regulate gene expression either by translational repression or target mRNA degradation, and ii) small interfering RNAs (siRNAs), which are involved in the biological process of RNA interference (RNAi). Our knowledge regarding these two types of ncRNAs has increased dramatically over the past decade, and they have a great potential to become therapeutic alternatives for a variety of human conditions.

Integration analysis of microRNA and mRNA expression profiles in human peripheral blood lymphocytes cultured in modeled microgravity

We analyzed miRNA and mRNA expression profiles in human peripheral blood lymphocytes (PBLs) incubated in microgravity condition, simulated by a ground-based rotating wall vessel (RWV) bioreactor. Our results show that 42 miRNAs were differentially expressed in MMG-incubated PBLs compared with 1 g incubated ones. Among these, miR-9-5p, miR-9-3p, miR-155-5p, miR-150-3p, and miR-378-3p were the most dysregulated. To improve the detection of functional miRNA-mRNA pairs, we performed gene expression profiles on the same samples assayed for miRNA profiling and we integrated miRNA and mRNA expression data. The functional classification of miRNA-correlated genes evidenced significant enrichment in the biological processes of immune/inflammatory response, signal transduction, regulation of response to stress, regulation of programmed cell death, and regulation of cell proliferation. We identified the correlation of miR-9-3p, miR-155-5p, miR-150-3p, and miR-378-3p expression with that of genes involved in immune/inflammatory response (e.g., IFNG and IL17F), apoptosis (e.g., PDCD4 and PTEN), and cell proliferation (e.g., NKX3-1 and GADD45A). Experimental assays of cell viability and apoptosis induction validated the results obtained by bioinformatics analyses demonstrating that in human PBLs the exposure to reduced gravitational force increases the frequency of apoptosis and decreases cell proliferation.

Exposing synonymous mutations

Synonymous codon changes, which do not alter protein sequence, were previously thought to have no functional consequence. Although this concept has been overturned in recent years, there is no unique mechanism by which these changes exert biological effects. A large repertoire of both experimental and bioinformatic methods has been developed to understand the effects of synonymous variants. Results from this body of work have provided global insights into how biological systems exploit the degeneracy of the genetic code to control gene expression, protein folding efficiency, and the coordinated expression of functionally related gene families. Although it is now clear that synonymous variants are important in a variety of contexts, from human disease to the safety and efficacy of therapeutic proteins, there is no clear consensus on the approaches to identify and validate these changes. Here, we review the diverse methods to understand the effects of synonymous mutations.

In silico identification of plant miRNAs in mammalian breast milk exosomes--a small step forward?

MicroRNAs (miRNAs) are a class of small RNA molecules that regulate gene expression by inhibiting the protein translation or targeting the mRNA cleavage. They play many important roles in living organism cells; however, the knowledge on miRNAs functions has become more extensive upon their identification in biological fluids and recent reports on plant-origin miRNAs abundance in human plasma and serum. Considering these findings, we performed a rigorous bioinformatics analysis of publicly available, raw data from high-throughput sequencing studies on miRNAs composition in human and porcine breast milk exosomes to identify the fraction of food-derived miRNAs. Several processing and filtering steps were applied to increase the accuracy, and to avoid false positives. Through aforementioned analysis, 35 and 17 miRNA species, belonging to 25 and 11 MIR families, were identified, respectively. In the human samples the highest abundance levels yielded the ath-miR166a, pab-miR951, ptc-miR472a and bdi-miR168, while in the porcine breast milk exosomes, the zma-miR168a, zma-miR156a and ath-miR166a have been identified in the largest amounts. The consensus prediction and annotation of potential human targets for select plant miRNAs suggest that the aforementioned molecules may interact with mRNAs coding several transcription factors, protein receptors, transporters and immune-related proteins, thus potentially influencing human organism. Taken together, the presented analysis shows proof of abundant plant miRNAs in mammal breast milk exosomes, pointing at the same time to the new possibilities arising from this discovery.

A rapid genome-wide microRNA screen identifies miR-14 as a modulator of Hedgehog signaling

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression by binding to sequences within the 3' UTR of mRNAs. Because miRNAs bind to short sequences with partial complementarity, target identification is challenging. To complement the existing target prediction algorithms, we devised a systematic "reverse approach" screening platform that allows the empirical prediction of miRNA-target interactions. Using Drosophila cells, we screened the 3' untranslated regions (3' UTRs) of the Hedgehog pathway genes against a genome-wide miRNA library and identified both predicted and many nonpredicted miRNA-target interactions. We demonstrate that miR-14 is essential for maintaining the proper level of Hedgehog signaling activity by regulating its physiological target, hedgehog. Furthermore, elevated levels of miR-14 suppress Hedgehog signaling activity by cotargeting its apparent nonphysiological targets, patched and smoothened. Altogether, our systematic screening platform is a powerful approach to identifying both physiological and apparent nonphysiological targets of miRNAs, which are relevant in both normal and diseased tissues.

miRror-Suite: decoding coordinated regulation by microRNAs

MicroRNAs (miRNAs) are short, non-coding RNAs that negatively regulate post-transcriptional mRNA levels. Recent data from cross-linking and immunoprecipitation technologies confirmed the combinatorial nature of the miRNA regulation. We present the miRror-Suite platform, developed to yield a robust and concise explanation for miRNA regulation from a large collection of differentially expressed transcripts and miRNAs. The miRror-Suite platform includes the miRror2.0 and Probability Supported Iterative miRror (PSI-miRror) tools. Researchers who performed large-scale transcriptomics or miRNA profiling experiments from cells and tissues will benefit from miRror-Suite. Our platform provides a concise, plausible explanation for the regulation of miRNAs in such complex settings. The input for miRror2.0 may include hundreds of differentially expressed genes or miRNAs. In the case of miRNAs as input, the algorithm seeks the statistically most likely set of genes regulated by this input. Alternatively, for a set of genes, the miRror algorithm seeks a collection of miRNAs that best explains their regulation. The miRror-Suite algorithm designates statistical criteria that were uniformly applied to a dozen miRNA-target prediction databases. Users select the preferred databases for predictions and numerous optional filters/parameters that restrict the search to the desired tissues, cell lines, level of expression and predictor scores. PSI-miRror is an advanced application for refining the input set by gradually enhancing the degree of pairing of the sets of miRNAs with the sets of targets. The iterations of PSI-miRror probe the interlinked nature of miRNAs and targets within cells. miRror-Suite serves experimentalists in facilitating the understanding of miRNA regulation through combinatorial– cooperative activity. The platform applies to human, mouse, rat, fly, worm and zebrafish.

Database URL:http://www.mirrorsuite.cs.huji.ac.il.

The potential clinical applications and prospects of microRNAs in lung cancer

Lung cancer is the major cause of cancer deaths worldwide due to its late diagnosis and poor outcome. Understanding genomic medicine may widen our vision into the oncogenesis of lung cancer and may open the door to improvements in the clinical management of lung cancer. It is well known that almost half of all genes are regulated by microRNAs (miRNAs). This review focuses on the role of miRNAs in lung cancer and also touches on the value of miRNA-based novel therapies for lung cancers.

Mining the 3'UTR of autism-implicated genes for SNPs perturbing microRNA regulation

Autism spectrum disorder (ASD) refers to a group of childhood neurodevelopmental disorders with polygenic etiology. The expression of many genes implicated in ASD is tightly regulated by various factors including microRNAs (miRNAs), a class of noncoding RNAs ~22 nucleotides in length that function to suppress translation by pairing with 'miRNA recognition elements' (MREs) present in the 3'untranslated region (3'UTR) of target mRNAs. This emphasizes the role played by miRNAs in regulating neurogenesis, brain development and differentiation and hence any perturbations in this regulatory mechanism might affect these processes as well. Recently, single nucleotide polymorphisms (SNPs) present within 3'UTRs of mRNAs have been shown to modulate existing MREs or even create new MREs. Therefore, we hypothesized that SNPs perturbing miRNA-mediated gene regulation might lead to aberrant expression of autism-implicated genes, thus resulting in disease predisposition or pathogenesis in at least a subpopulation of ASD individuals. We developed a systematic computational pipeline that integrates data from well-established databases. By following a stringent selection criterion, we identified 9 MRE-modulating SNPs and another 12 MRE-creating SNPs in the 3'UTR of autism-implicated genes. These high-confidence candidate SNPs may play roles in ASD and hence would be valuable for further functional validation.

MicroRNA binding sites in the coding region of mRNAs: extending the repertoire of post-transcriptional gene regulation

It is well established that microRNAs (miRNAs) induce mRNA degradation by binding to 3' untranslated regions (UTRs). The functionality of sites in the coding domain sequence (CDS), on the other hand, remains under discussion. Such sites have limited impact on target mRNA abundance and recent work suggests that miRNAs bind in the CDS to inhibit translation. What then could be the regulatory benefits of translation inhibition through CDS targeting compared to mRNA degradation following 3' UTR binding? We propose that these domain-dependent effects serve to diversify the functional repertoire of post-transcriptional gene expression control. Possible regulatory benefits may include tuning the time-scale and magnitude of post-transcriptional regulation, regulating protein abundance depending on or independently of the cellular state, and regulation of the protein abundance of alternative splice variants. Finally, we review emerging evidence that these ideas may generalize to RNA-binding proteins beyond miRNAs and Argonaute proteins.

Tissue-specific expression and regulatory networks of pig microRNAome

Background

Despite the economic and medical importance of the pig, knowledge about its genome organization, gene expression regulation, and molecular mechanisms involved in physiological processes is far from that achieved for mouse and rat, the two most used model organisms in biomedical research. MicroRNAs (miRNAs) are a wide class of molecules that exert a recognized role in gene expression modulation, but only 280 miRNAs in pig have been characterized to date.

Results

We applied a novel computational approach to predict species-specific and conserved miRNAs in the pig genome, which were then subjected to experimental validation. We experimentally identified candidate miRNAs sequences grouped in high-confidence (424) and medium-confidence (353) miRNAs according to RNA-seq results. A group of miRNAs was also validated by PCR experiments. We established the subtle variability in expression of isomiRs and miRNA-miRNA star couples supporting a biological function for these molecules. Finally, miRNA and mRNA expression profiles produced from the same sample of 20 different tissue of the animal were combined, using a correlation threshold to filter miRNA-target predictions, to identify tissue-specific regulatory networks.

Conclusions

Our data represent a significant progress in the current understanding of miRNAome in pig. The identification of miRNAs, their target mRNAs, and the construction of regulatory circuits will provide new insights into the complex biological networks in several tissues of this important animal model.

Macros in microRNA target identification: a comparative analysis of in silico, in vitro, and in vivo approaches to microRNA target identification

MicroRNAs (miRNAs) are short RNA molecules that modulate post-transcriptional gene expression by partial or incomplete base-pairing to the complementary sequences on their target genes. Sequence-based miRNA target gene recognition enables the utilization of computational methods, which are highly informative in identifying a subset of putative miRNA targets from the genome. Subsequently, single miRNA-target gene binding is evaluated experimentally by in vitro assays to validate and quantify the transcriptional or post-transcriptional effects of miRNA-target gene interaction. Although ex vivo approaches are instructive in providing a basis for further analyses, in vivo genetic studies are critical to determine the occurrence and biological relevance of miRNA targets under physiological conditions. In the present review, we summarize the important features of each of the experimental approaches, their technical and biological limitations, and future challenges in light of the complexity of miRNA target gene recognition.

Insights into miRNA regulation of the human glycome

Glycosylation is an intricate process requiring the coordinated action of multiple proteins, including glycosyltransferases, glycosidases, sugar nucleotide transporters and trafficking proteins. Work by several groups points to a role for microRNA (miRNA) in controlling the levels of specific glycosyltransferases involved in cancer, neural migration and osteoblast formation. Recent work in our laboratory suggests that miRNA are a principal regulator of the glycome, translating genomic information into the glycocode through tuning of enzyme levels. Herein we overlay predicted miRNA regulation of glycosylation related genes (glycogenes) onto maps of the common N-linked and O-linked glycan biosynthetic pathways to identify key regulatory nodes of the glycome. Our analysis provides insights into glycan regulation and suggests that at the regulatory level, glycogenes are non-redundant.

Area under precision-recall curves for weighted and unweighted data

Precision-recall curves are highly informative about the performance of binary classifiers, and the area under these curves is a popular scalar performance measure for comparing different classifiers. However, for many applications class labels are not provided with absolute certainty, but with some degree of confidence, often reflected by weights or soft labels assigned to data points. Computing the area under the precision-recall curve requires interpolating between adjacent supporting points, but previous interpolation schemes are not directly applicable to weighted data. Hence, even in cases where weights were available, they had to be neglected for assessing classifiers using precision-recall curves. Here, we propose an interpolation for precision-recall curves that can also be used for weighted data, and we derive conditions for classification scores yielding the maximum and minimum area under the precision-recall curve. We investigate accordances and differences of the proposed interpolation and previous ones, and we demonstrate that taking into account existing weights of test data is important for the comparison of classifiers.

Mapping posttranscriptional regulation of the human glycome uncovers microRNA defining the glycocode

Cell surface glycans form a critical interface with the biological milieu, informing diverse processes from the inflammatory cascade to cellular migration. Assembly of discrete carbohydrate structures requires the coordinated activity of a repertoire of proteins, including glycosyltransferases and glycosidases. Little is known about the regulatory networks controlling this complex biosynthetic process. Recent work points to a role for microRNA (miRNA) in the regulation of specific glycan biosynthetic enzymes. Herein we take a unique systems-based approach to identify connections between miRNA and the glycome. By using our glycomic analysis platform, lectin microarrays, we identify glycosylation signatures in the NCI-60 cell panel that point to the glycome as a direct output of genomic information flow. Integrating our glycomic dataset with miRNA data, we map miRNA regulators onto genes in glycan biosynthetic pathways (glycogenes) that generate the observed glycan structures. We validate three of these predicted miRNA/glycogene regulatory networks: high mannose, fucose, and terminal β-GalNAc, identifying miRNA regulation that would not have been observed by traditional bioinformatic methods. Overall, our work reveals critical nodes in the global glycosylation network accessible to miRNA regulation, providing a bridge between miRNA-mediated control of cell phenotype and the glycome.

Refining microRNA target predictions: sorting the wheat from the chaff

microRNAs are short RNAs that reduce gene expression by binding to their targets. The accurate prediction of microRNA targets is essential to understanding the function of microRNAs. Computational predictions indicate that all human genes may be regulated by microRNAs, with each microRNA possibly targeting thousands of genes. Here we discuss computational methods for identifying mammalian microRNA targets and refining them for further experimental validation. We describe microRNA target prediction resources and procedures and how they integrate with various types of experimental techniques that aim to validate them or further explore their function. We also provide a list of target prediction databases and explain how these are curated.

Understanding principles of miRNA target recognition and function through integrated biological and bioinformatics approaches

In recent times, microRNA (miRNA) have emerged as primary regulators of fundamental biological processes including cellular differentiation, proliferation, apoptosis, as well as synaptic plasticity. However, miRNAs bind their targets with only partial complementarity, making it very challenging to determine exactly how a miRNA is functioning in specific biological environments. This review discusses key principles of miRNA target recognition and function which have emerged through the progressive advancement of biological and bioinformatics approaches. Ultimately, the integration of gene expression and biochemical methods with sequence- and systems-based bioinformatics approaches will reveal profound insights regarding the importance of target contextual features in determining miRNA target recognition and regulatory outcome, as well as the importance of RNA interaction networks in enabling miRNA to regulate different target genes and functions in specific biological contexts. There is therefore a demand for the elegant design of future experiments such that principles of context-specific miRNA target recognition and regulatory outcome can be accurately modeled in normal developmental and disease states.

Translational repression of SLC26A3 by miR-494 in intestinal epithelial cells

SLC26A3 [downregulated in adenoma (DRA)] is a Cl(-)/HCO3(-) exchanger involved in electroneutral NaCl absorption in the mammalian intestine. Altered DRA expression levels are associated with infectious and inflammatory diarrheal diseases. Therefore, it is critical to understand the regulation of DRA expression. MicroRNAs (miRNAs) are endogenous, small RNAs that regulate protein expression via blocking the translation and/or promoting mRNA degradation. To investigate potential modulation of DRA expression by miRNA, five different in silico algorithms were used to predict the miRNAs that target DRA. Of these miRNAs, miR-494 was shown to have a highly conserved putative binding site in the DRA 3'-untranslated region (3'-UTR) compared with other DRA-targeting miRNAs in vertebrates. Transfection with pmirGLO dual luciferase vector containing DRA 3'-UTR (pmirGLO-3'-UTR DRA) resulted in a significant decrease in relative luciferase activity compared with empty vector. Cotransfection of the DRA 3'-UTR luciferase vector with a miR-494 mimic further decreased luciferase activity compared with cells transfected with negative control. The transfection of a miR-494 mimic into Caco-2 and T-84 cells significantly increased the expression of miR-494 and concomitantly decreased the DRA protein expression. Mutation of the seed sequences for miR-494 in 3'-UTR of DRA abrogated the effect of miR-494 on 3'-UTR. These data demonstrate a novel regulatory mechanism of DRA expression via miR-494 and indicate that targeting this microRNA may serve to be a potential therapeutic strategy for diarrheal diseases.

Identification of distinct miRNA target regulation between breast cancer molecular subtypes using AGO2-PAR-CLIP and patient datasets

BACKGROUND

Various microRNAs (miRNAs) are up- or downregulated in tumors. However, the repression of cognate miRNA targets responsible for the phenotypic effects of this dysregulation in patients remains largely unexplored. To define miRNA targets and associated pathways, together with their relationship to outcome in breast cancer, we integrated patient-paired miRNA-mRNA expression data with a set of validated miRNA targets and pathway inference.

RESULTS

To generate a biochemically-validated set of miRNA-binding sites, we performed argonaute-2 photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (AGO2-PAR-CLIP) in MCF7 cells. We then defined putative miRNA-target interactions using a computational model, which ranked and selected additional TargetScan-predicted interactions based on features of our AGO2-PAR-CLIP binding-site data. We subselected modeled interactions according to the abundance of their constituent miRNA and mRNA transcripts in tumors, and we took advantage of the variability of miRNA expression within molecular subtypes to detect miRNA repression. Interestingly, our data suggest that miRNA families control subtype-specific pathways; for example, miR-17, miR-19a, miR-25, and miR-200b show high miRNA regulatory activity in the triple-negative, basal-like subtype, whereas miR-22 and miR-24 do so in the HER2 subtype. An independent dataset validated our findings for miR-17 and miR-25, and showed a correlation between the expression levels of miR-182 targets and overall patient survival. Pathway analysis associated miR-17, miR-19a, and miR-200b with leukocyte transendothelial migration.

CONCLUSIONS

We combined PAR-CLIP data with patient expression data to predict regulatory miRNAs, revealing potential therapeutic targets and prognostic markers in breast cancer.

MicroRNA-148a is downregulated in gastric cancer, targets MMP7, and indicates tumor invasiveness and poor prognosis

Gastric cancer (GC) develops through deregulation of gene expression and accumulation of epigenetic abnormalities, leading to tumor cell acquisition of malignant features. MicroRNAs (miRNAs) play a critical role in cancer development where they can act as oncogenes or oncosuppressors. To identify miRNAs that are associated with some clinicopathologic features of GC and/or participate in tumor progression, miRNA expression in 20 GC tissues and five corresponding non-neoplastic gastric mucosa was examined by miRNA microarray. Oligonucleotide array analysis was carried out for miRNA target prediction. The functions of candidate miRNAs and their target genes were also analyzed by quantitative RT-PCR, Western blotting, reporter gene assay, and cell invasion assay. Comparison of miRNA expression profiles revealed that downregulation of miR-148a was identified in most of the GC tissues. Downregulation of miR-148a was significantly correlated with an advanced clinical stage, lymph node metastasis, and poor clinical outcome. Custom oligonucleotide array analysis revealed that MMP7 expression was markedly downregulated in miR-148a-overexpressing GC cells; MMP7 was found to be a direct and functional target of miR-148a, participating in cell invasion. These results suggest that miR-148a contributes to the maintenance of homeostasis in normal stomach tissue and plays an important role in GC invasion by regulating MMP7 expression.

The miRNA-mediated cross-talk between transcripts provides a novel layer of posttranscriptional regulation

Endogenously expressed transcripts that are posttranscriptionally regulated by the same microRNAs (miRNAs) will, in principle, compete for the binding of their shared small noncoding RNA regulators and modulate each other's abundance. Recently, the levels of some coding as well as noncoding transcripts have indeed been found to be regulated in this way. Transcripts that engage in such regulatory interactions are referred to as competitive endogenous RNAs (ceRNAs). This novel layer of posttranscriptional regulation has been shown to contribute to diverse aspects of organismal and cellular biology, despite the number of functionally characterized ceRNAs being as yet relatively low. Importantly, increasing evidence suggests that the dysregulation of some ceRNA interactions is associated with disease etiology, most preeminently with cancer. Here we review how posttranscriptional regulation by miRNAs contributes to the cross-talk between transcripts and review examples of known ceRNAs by highlighting the features underlying their interactions and what might be their biological relevance.

Identification of microRNA targets by pulsed SILAC

Pulsed stable isotope labeling by amino acids in cell culture (pulsed SILAC or pSILAC) allows to monitor and quantify the de novo synthesis of proteins in an unbiased fashion on a proteome-wide scale. The high applicability of this metabolic labeling technique has been demonstrated for the identification of posttranscriptional changes in gene expression on the proteome level, in particular those caused by microRNAs. The application of pSILAC allows the selective quantification of newly synthesized proteins and thus the detection of differences in protein translation. This is of particular interest in the case of microRNA-mediated regulations, which characteristically cause rather modest decreases in protein amounts that may be difficult to detect by other proteomic methods. Here, we describe a detailed protocol for using pSILAC to track miRNA-mediated changes in protein expression, using the p53-induced miR-34a microRNA as a prototypic example of microRNA-mediated regulations.

Computational prediction of microRNA function and activity

Inferring microRNA (miRNA) functions and activities has been extremely important to understand their system-level roles and the mechanisms behind the cellular behaviors of their target genes. This chapter first details methodologies necessary for prediction of function and activity. It then introduces the computational methods available for investigation of sequence and experimental data and for analysis of the information flow mediated through miRNAs.

Regulation of ABCA1 protein expression and function in hepatic and pancreatic islet cells by miR-145

OBJECTIVE

The ATP-binding cassette transporter A1 (ABCA1) protein maintains cellular cholesterol homeostasis in several different tissues. In the liver, ABCA1 is crucial for high-density lipoprotein biogenesis, and in the pancreas ABCA1 can regulate insulin secretion. In this study, our aim was to identify novel microRNAs that regulate ABCA1 expression in these tissues.

APPROACH AND RESULTS

We combined multiple microRNA prediction programs to identify 8 microRNAs that potentially regulate ABCA1. A luciferase reporter assay demonstrated that 5 of these microRNAs (miR-148, miR-27, miR-144, miR-145, and miR-33a/33b) significantly repressed ABCA1 3'-untranslated region activity with miR-145 resulting in one of the larger decreases. In hepatic HepG2 cells, miR-145 can regulate both ABCA1 protein expression levels and cholesterol efflux function. In murine islets, an increase in miR-145 expression decreased ABCA1 protein expression, increased total islet cholesterol levels, and decreased glucose-stimulated insulin secretion. Inhibiting miR-145 produced the opposite effect of increasing ABCA1 protein levels and improving glucose-stimulated insulin secretion. Finally, increased glucose levels in media significantly decreased miR-145 levels in cultured pancreatic beta cells. These findings suggest that miR-145 is involved in glucose homeostasis and is regulated by glucose concentration.

CONCLUSIONS

Our studies demonstrate that miR-145 regulates ABCA1 expression and function, and inhibiting this microRNA represents a novel strategy for increasing ABCA1 expression, promoting high-density lipoprotein biogenesis in the liver, and improving glucose-stimulated insulin secretion in islets.

Single nucleotide polymorphisms in microRNA binding sites of oncogenes: implications in cancer and pharmacogenomics

Cancer, a complex genetic disease involving uncontrolled cell proliferation, is caused by inactivation of tumor suppressor genes and activation of oncogenes. A vast majority of these cancer causing genes are known targets of microRNAs (miRNAs) that bind to complementary sequences in 3' untranslated regions (UTR) of messenger RNAs and repress them from translation. Single Nucleotide Polymorphisms (SNPs) occurring naturally in such miRNA binding regions can alter the miRNA:mRNA interaction and can significantly affect gene expression. We hypothesized that 3'UTR SNPs in miRNA binding sites of proto-oncogenes could abrogate their post-transcriptional regulation, resulting in overexpression of oncogenic proteins, tumor initiation, progression, and modulation of drug response in cancer patients. Therefore, we developed a systematic computational pipeline that integrates data from well-established databases, followed stringent selection criteria and identified a panel of 30 high-confidence SNPs that may impair miRNA target sites in the 3' UTR of 54 mRNA transcripts of 24 proto-oncogenes. Further, 8 SNPs amidst them had the potential to determine therapeutic outcome in cancer patients. Functional annotation suggested that altogether these SNPs occur in proto-oncogenes enriched for kinase activities. We provide detailed in silico evidence for the functional effect of these candidate SNPs in various types of cancer.

Structural analysis of microRNA-target interaction by sequential seed mutagenesis and stem-loop 3' RACE

Background

As a consequence of recent RNAseq efforts, miRNAomes of diverse tissues and species are available. However, most interactions between microRNAs and regulated mRNAs are still to be deciphered. While in silico analysis of microRNAs results in prediction of hundreds of potential targets, bona-fide interactions have to be verified e.g. by luciferase reporter assays using fused target sites as well as controls incorporating mutated seed sequences. The aim of this study was the development of a straightforward approach for sequential mutation of multiple target sites within a given 3’ UTR.

Methodology/Principal Findings

The established protocol is based on Seed Mutagenesis Assembly PCR (SMAP) allowing for rapid identification of microRNA target sites. Based on the presented approach, we were able to determine the transcription factor NKX3.1 as a genuine target of miR-155. The sequential mutagenesis of multiple microRNA target sites was examined by miR-29a mediated CASP7 regulation, which revealed one of two predicted target sites as the predominant site of interaction. Since 3’ UTR sequences of non-model organisms are either lacking in databases or computationally predicted, we developed a Stem-Loop 3’ UTR RACE PCR (SLURP) for efficient generation of required 3’ UTR sequence data. The stem-loop primer allows for first strand cDNA synthesis by nested PCR amplification of the 3’ UTR. Besides other applications, the SLURP method was used to gain data on porcine CASP7 3’UTR evaluating evolutionary conservation of the studied interaction.

Conclusions/Significance

Sequential seed mutation of microRNA targets based on the SMAP approach allows for rapid structural analysis of several target sites within a given 3’ UTR. The combination of both methods (SMAP and SLURP) enables targeted analysis of microRNA binding sites in hitherto unknown mRNA 3’ UTRs within a few days.

Dynamic modelling of microRNA regulation during mesenchymal stem cell differentiation

Background

Network inference from gene expression data is a typical approach to reconstruct gene regulatory networks. During chondrogenic differentiation of human mesenchymal stem cells (hMSCs), a complex transcriptional network is active and regulates the temporal differentiation progress. As modulators of transcriptional regulation, microRNAs (miRNAs) play a critical role in stem cell differentiation. Integrated network inference aimes at determining interrelations between miRNAs and mRNAs on the basis of expression data as well as miRNA target predictions. We applied the NetGenerator tool in order to infer an integrated gene regulatory network.

Results

Time series experiments were performed to measure mRNA and miRNA abundances of TGF-beta1+BMP2 stimulated hMSCs. Network nodes were identified by analysing temporal expression changes, miRNA target gene predictions, time series correlation and literature knowledge. Network inference was performed using NetGenerator to reconstruct a dynamical regulatory model based on the measured data and prior knowledge. The resulting model is robust against noise and shows an optimal trade-off between fitting precision and inclusion of prior knowledge. It predicts the influence of miRNAs on the expression of chondrogenic marker genes and therefore proposes novel regulatory relations in differentiation control. By analysing the inferred network, we identified a previously unknown regulatory effect of miR-524-5p on the expression of the transcription factor SOX9 and the chondrogenic marker genes COL2A1, ACAN and COL10A1.

Conclusions

Genome-wide exploration of miRNA-mRNA regulatory relationships is a reasonable approach to identify miRNAs which have so far not been associated with the investigated differentiation process. The NetGenerator tool is able to identify valid gene regulatory networks on the basis of miRNA and mRNA time series data.

A probabilistic approach to explore human miRNA targetome by integrating miRNA-overexpression data and sequence information

MOTIVATION

Systematic identification of microRNA (miRNA) targets remains a challenge. The miRNA overexpression coupled with genome-wide expression profiling is a promising new approach and calls for a new method that integrates expression and sequence information.

RESULTS

We developed a probabilistic scoring method called targetScore. TargetScore infers miRNA targets as the transformed fold-changes weighted by the Bayesian posteriors given observed target features. To this end, we compiled 84 datasets from Gene Expression Omnibus corresponding to 77 human tissue or cells and 113 distinct transfected miRNAs. Comparing with other methods, targetScore achieves significantly higher accuracy in identifying known targets in most tests. Moreover, the confidence targets from targetScore exhibit comparable protein downregulation and are more significantly enriched for Gene Ontology terms. Using targetScore, we explored oncomir-oncogenes network and predicted several potential cancer-related miRNA-messenger RNA interactions.

AVAILABILITY AND IMPLEMENTATION

TargetScore is available at Bioconductor: http://www.bioconductor.org/packages/devel/bioc/html/TargetScore.html.

Extracellular matrix secretion by cardiac fibroblasts: role of microRNA-29b and microRNA-30c

RATIONALE

MicroRNAs (miRNAs), in particular miR-29b and miR-30c, have been implicated as important regulators of cardiac fibrosis.

OBJECTIVE

To perform a proteomics comparison of miRNA effects on extracellular matrix secretion by cardiac fibroblasts.

METHODS AND RESULTS

Mouse cardiac fibroblasts were transfected with pre-/anti-miR of miR-29b and miR-30c, and their conditioned medium was analyzed by mass spectrometry. miR-29b targeted a cadre of proteins involved in fibrosis, including multiple collagens, matrix metalloproteinases, and leukemia inhibitory factor, insulin-like growth factor 1, and pentraxin 3, 3 predicted targets of miR-29b. miR-29b also attenuated the cardiac fibroblast response to transforming growth factor-β. In contrast, miR-30c had little effect on extracellular matrix production but opposite effects regarding leukemia inhibitory factor and insulin-like growth factor 1. Both miRNAs indirectly affected cardiac myocytes. On transfection with pre-miR-29b, the conditioned medium of cardiac fibroblasts lost its ability to support adhesion of rat ventricular myocytes and led to a significant reduction of cardiac myocyte proteins (α-actinin, cardiac myosin-binding protein C, and cardiac troponin I). Similarly, cardiomyocytes derived from mouse embryonic stem cells atrophied under pre-miR-29 conditioned medium, whereas pre-miR-30c conditioned medium had a prohypertrophic effect. Levels of miR-29a, miR-29c, and miR-30c, but not miR-29b, were significantly reduced in a mouse model of pathological but not physiological hypertrophy. Treatment with antagomiRs to miR-29b induced excess fibrosis after aortic constriction without overt deterioration in cardiac function.

CONCLUSIONS

Our proteomic analysis revealed novel molecular targets of miRNAs that are linked to a fibrogenic cardiac phenotype. Such comprehensive screening methods are essential to define the concerted actions of miRNAs in cardiovascular disease.

Comparative evaluation of miRNA expression between in vitro and in vivo airway epithelium demonstrates widespread differences

Airway epithelial cells cultured at an air-liquid interface bear many hallmarks of in vivo cells and are used extensively to study the biology of the lung epithelium. Because miRNAs regulate many cellular functions, we postulated that miRNA profiling would provide an unbiased assessment of the effects of in vitro culturing. RNA was extracted from primary airway epithelial cells either immediately after cell procurement (in vivo condition) or after air-liquid interface culture was established (in vitro condition). We assessed 742 miRNAs and determined differential expression between in vivo and in vitro conditions. Air-liquid interface culturing of airway epithelial cells caused widespread changes in miRNA expression. A similarly extensive alteration in gene expression was observed in an independent set of publicly available microarray data. We integrated miRNA and gene expression results to identify culture-induced differences in transcriptional programs (including several involved in epithelial injury and repair). Air-liquid interface cultures are useful models for studying airway biology, but the present findings indicate that, despite phenotypic similarities with primary cells, these culture systems profoundly perturb miRNA and gene expression. Studies of lung epithelium based on in vitro culture should therefore be designed and interpreted with an appreciation of the limitations of air-liquid interface culture systems.

BayMiR: inferring evidence for endogenous miRNA-induced gene repression from mRNA expression profiles

Background

Popular miRNA target prediction techniques use sequence features to determine the functional miRNA target sites. These techniques commonly ignore the cellular conditions in which miRNAs interact with their targets in vivo. Gene expression data are rich resources that can complement sequence features to take into account the context dependency of miRNAs.

Results

We introduce BayMiR, a new computational method, that predicts the functionality of potential miRNA target sites using the activity level of the miRNAs inferred from genome-wide mRNA expression profiles. We also found that mRNA expression variation can be used as another predictor of functional miRNA targets. We benchmarked BayMiR, the expression variation, Cometa, and the TargetScan “context scores” on two tasks: predicting independently validated miRNA targets and predicting the decrease in mRNA abundance in miRNA overexpression assays. BayMiR performed better than all other methods in both benchmarks and, surprisingly, the variation index performed better than Cometa and some individual determinants of the TargetScan context scores. Furthermore, BayMiR predicted miRNA target sets are more consistently annotated with GO and KEGG terms than similar sized random subsets of genes with conserved miRNA seed regions. BayMiR gives higher scores to target sites residing near the poly(A) tail which strongly favors mRNA degradation using poly(A) shortening. Our work also suggests that modeling multiplicative interactions among miRNAs is important to predict endogenous mRNA targets.

Conclusions

We develop a new computational method for predicting the target mRNAs of miRNAs. BayMiR applies a large number of mRNA expression profiles and successfully identifies the mRNA targets and miRNA activities without using miRNA expression data. The BayMiR package is publicly available and can be readily applied to any mRNA expression data sets.

Developing microRNA screening as a functional genomics tool for disease research

Originally discovered as regulators of developmental timing in C. elegans, microRNAs (miRNAs) have emerged as modulators of nearly every cellular process, from normal development to pathogenesis. With the advent of whole genome libraries of miRNA mimics suitable for high throughput screening, it is possible to comprehensively evaluate the function of each member of the miRNAome in cell-based assays. Since the relatively few microRNAs in the genome are thought to directly regulate a large portion of the proteome, miRNAome screening, coupled with the identification of the regulated proteins, might be a powerful new approach to gaining insight into complex biological processes.

Large-scale screens of miRNA-mRNA interactions unveiled that the 3'UTR of a gene is targeted by multiple miRNAs

Animal microRNA (miRNA) target prediction is still a challenge, although many prediction programs have been exploited. MiRNAs exert their function through partially binding the messenger RNAs (mRNAs; likely at 3′ untranslated regions [3′UTRs]), which makes it possible to detect the miRNA-mRNA interactions in vitro by co-transfection of miRNA and a luciferase reporter gene containing the target mRNA fragment into mammalian cells under a dual-luciferase assay system. Here, we constructed a human miRNA expression library and used a dual-luciferase assay system to perform large-scale screens of interactions between miRNAs and the 3′UTRs of seven genes, which included more than 3,000 interactions with triplicate experiments for each interaction. The screening results showed that the 3′UTR of one gene can be targeted by multiple miRNAs. Among the prediction algorithms, a Bayesian phylogenetic miRNA target identification algorithm and a support vector machine (SVM) presented a relatively better performance (27% for EIMMo and 24.7% for miRDB) against the average precision (17.3%) of the nine prediction programs used here. Additionally, we noticed that a relatively high conservation level was shown at the miRNA 3′ end targeted regions, as well as the 5′ end (seed region) binding sites.

miRTCat: a comprehensive map of human and mouse microRNA target sites including non-canonical nucleation bulges

SUMMARY

MicroRNAs (miRNAs) regulate various biological functions by binding hundreds of transcripts to impart post-transcriptional repression. Recently, by applying a transcriptome-wide experimental method for identifying miRNA target sites (Ago HITS-CLIP), a novel non-canonical target site, named 'nucleation bulge', was discovered as widespread, functional and evolutionally conserved. Although such non-canonical nucleation bulges have been proven to be predictive by using 'pivot pairing rule' and sequence conservation, this approach has not been applied yet. To facilitate the functional studies of non-canonical miRNA targets, we implement miRTCat: a comprehensive searchable map of miRNA target sites, including non-canonical nucleation bulges, not only mapped in experimentally verified miRNA-bound regions but also predicted in all 3'-untranslated regions (3'-UTRs) derived from human and mouse (∼15.6% as expected false-positive results).

AVAILABILITY

http://ion.skku.edu/mirtcat.

CONTACT

swchi@skku.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Quantitative proteomic strategies for the identification of microRNA targets

MicroRNAs (miRNAs) are small noncoding RNAs, approximately 22 nucleotides in length, found in diverse organisms. They have emerged in recent years as key regulators of a broad spectrum of cellular functions. miRNAs regulate biological processes by inducing translational inhibition and degradation of their target mRNAs through base pairing to partially or fully complementary sites. In the field of miRNA research, the identification of the targets of individual miRNAs is of utmost importance. Our understanding of the molecular mechanisms by which individual miRNAs modulate cellular functions will remain incomplete until a full set of miRNA targets is identified and validated. Since a miRNA may regulate many of its targets at the translational level without affecting mRNA abundance, proteomic methods are best suited for revealing the full spectrum of miRNA targets. Quantitative proteomics is emerging as a powerful toolbox for identifying miRNA targets and for quantifying the contribution of translational repression by miRNAs. In this review, the authors summarize the quantitative proteomic approaches that have been employed for identification of miRNA targets and discuss current challenges as well as possible ways of overcoming them.

DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows

MicroRNAs (miRNAs) are small endogenous RNA molecules that regulate gene expression through mRNA degradation and/or translation repression, affecting many biological processes. DIANA-microT web server (http://www.microrna.gr/webServer) is dedicated to miRNA target prediction/functional analysis, and it is being widely used from the scientific community, since its initial launch in 2009. DIANA-microT v5.0, the new version of the microT server, has been significantly enhanced with an improved target prediction algorithm, DIANA-microT-CDS. It has been updated to incorporate miRBase version 18 and Ensembl version 69. The in silico-predicted miRNA–gene interactions in Homo sapiens, Mus musculus, Drosophila melanogaster and Caenorhabditis elegans exceed 11 million in total. The web server was completely redesigned, to host a series of sophisticated workflows, which can be used directly from the on-line web interface, enabling users without the necessary bioinformatics infrastructure to perform advanced multi-step functional miRNA analyses. For instance, one available pipeline performs miRNA target prediction using different thresholds and meta-analysis statistics, followed by pathway enrichment analysis. DIANA-microT web server v5.0 also supports a complete integration with the Taverna Workflow Management System (WMS), using the in-house developed DIANA-Taverna Plug-in. This plug-in provides ready-to-use modules for miRNA target prediction and functional analysis, which can be used to form advanced high-throughput analysis pipelines.

miR-135b coordinates progression of ErbB2-driven mammary carcinomas through suppression of MID1 and MTCH2

In an attempt to reveal deregulated miRNAs associated with the progression of carcinomas developed in BALB-neuT transgenic mice, we found increased expression of miR-135b during malignancy. Relevantly, we observed that miR-135b is up-regulated in basal or normal-like human breast cancers, and it correlates with patient survival and early metastatization. Therefore, we investigated its biological functions by modulating its expression (up- or down-regulation) in mammary tumor cells. Although no effect was observed on proliferation in cell culture and in orthotopically injected mice, miR-135b was able to control cancer cell stemness in a mammosphere assay, anchorage-independent growth in vitro, and lung cancer cell dissemination in mice after tail vein injections. Focusing on the miR-135b molecular mechanism, we observed that miR-135b controls malignancy via its direct targets, midline 1 (MID1) and mitochondrial carrier homolog 2 (MTCH2), as proved by biochemical and functional rescuing/phenocopying experiments. Consistently, an anti-correlation between miR-135b and MID1 or MTCH2 was found in human primary tumor samples. In conclusion, our research led us to the identification of miR-135b and its targets, MID1 and MTCH2, as relevant coordinators of mammary gland tumor progression.

Simultaneous miRNA and mRNA transcriptome profiling of human myoblasts reveals a novel set of myogenic differentiation-associated miRNAs and their target genes

Background

miRNA profiling performed in myogenic cells and biopsies from skeletal muscles has previously identified miRNAs involved in myogenesis.

Results

Here, we have performed miRNA transcriptome profiling in human affinity-purified CD56+ myoblasts induced to differentiate in vitro. In total, we have identified 60 miRNAs differentially expressed during myogenic differentiation. Many were not known for being differentially expressed during myogenic differentiation. Of these, 14 (miR-23b, miR-28, miR-98, miR-103, miR-107, miR-193a, miR-210, miR-324-5p, miR-324-3p, miR-331, miR-374, miR-432, miR-502, and miR-660) were upregulated and 6 (miR-31, miR-451, miR-452, miR-565, miR-594 and miR-659) were downregulated. mRNA transcriptome profiling performed in parallel resulted in identification of 6,616 genes differentially expressed during myogenic differentiation.

Conclusions

This simultaneous miRNA/mRNA transcriptome profiling allowed us to predict with high accuracy target genes of myogenesis-related microRNAs and to deduce their functions.