Deep-sequencing of endothelial cells exposed to hypoxia reveals the complexity of known and novel microRNAs

In order to understand the role of microRNAs (miRNAs) in vascular physiopathology, we took advantage of deep-sequencing techniques to accurately and comprehensively profile the entire miRNA population expressed by endothelial cells exposed to hypoxia. SOLiD sequencing of small RNAs derived from human umbilical vein endothelial cells (HUVECs) exposed to 1% O₂ or normoxia for 24 h yielded more than 22 million reads per library. A customized bioinformatic pipeline identified more than 400 annotated microRNA/microRNA* species with a broad abundance range: miR-21 and miR-126 totaled almost 40% of all miRNAs. A complex repertoire of isomiRs was found, displaying also 5′ variations, potentially affecting target recognition. High-stringency bioinformatic analysis identified microRNA candidates, whose predicted pre-miRNAs folded into a stable hairpin. Validation of a subset by qPCR identified 18 high-confidence novel miRNAs as detectable in independent HUVEC cultures and associated to the RISC complex. The expression of two novel miRNAs was significantly down-modulated by hypoxia, while miR-210 was significantly induced. Gene ontology analysis of their predicted targets revealed a significant association to hypoxia-inducible factor signaling, cardiovascular diseases, and cancer. Overexpression of the novel miRNAs in hypoxic endothelial cells affected cell growth and confirmed the biological relevance of their down-modulation. In conclusion, deep-sequencing accurately profiled known, variant, and novel microRNAs expressed by endothelial cells in normoxia and hypoxia.     

Expanding roles for miRNAs and siRNAs in cell regulation

The role of small RNAs as key regulators of mRNA turnover and translation has been well established. Recent advances indicate that the small RNAs termed microRNAs play important roles in cell proliferation, apoptosis and differentiation. Moreover, the microRNA mechanism is an efficient means to regulate production of a diverse range of proteins. As new microRNAs and their mRNA targets rapidly emerge, it is becoming apparent that RNA-based regulation of mRNAs may rival ubiquitination as a mechanism to control protein levels.     

MicroRNA在肿瘤发生发展和诊断中作用的研究进展

microRNA是一类由内源基因编码的长度约为18-25个核苷酸的非编码单链RNA分子,可以与靶基因mRNA的3'非编码区结合,通过降解靶m RNA或(和)抑制靶m RNA转录后翻译调节靶蛋白的生成,从而发挥其生物学作用。目前,在人体基因组内发现的microRNA已经超过2500多个,可能调节着人类1/3的基因,在维持正常干细胞功能、调控细胞增殖分化及恶性肿瘤发生过程中均起重要作用。既往的研究表明microRNA与基因之间相互调控的失衡导致肿瘤的发生。从分子水平上研究microRNA与肿瘤发生的关系,检测microRNA与肿瘤相关基因表达情况的改变,分析肿瘤组织和血清中microRNA表达量与肿瘤分型的关系,将有利于肿瘤的病因学研究,早期发现和肿瘤治疗及预后判断。本文主要就microRNA在肿瘤发生发展和诊断中作用的研究进展进行了综述。     

Paradoxical microRNAs

In mammalian cells, microRNAs regulate the expression of target mRNAs generally by reducing their stability and/or translation, and thereby control diverse cellular processes such as senescence. We recently reported the differential abundance of microRNAs in young (early-passage, proliferating) relative to senescent (late-passage, non-proliferating) WI-38 human diploid fibroblasts. Here we report that the levels of the vast majority of mRNAs were unaltered in senescent compared to young WI-38 cells, while overall mRNA translation was potently reduced in senescent cells. Downregulation of Dicer or Drosha, two major enzymes in microRNA biogenesis, lowered microRNA levels, but, unexpectedly, it also reduced global translation. While a reduction in Dicer levels markedly enhanced cellular senescence, reduction of Drosha levels did not, suggesting that the Drosha/Dicer effects on translation may be independent of senescence, and further suggesting that microRNAs may directly or indirectly enhance mRNA translation in WI-38 cells. We discuss possible scenarios through which Dicer/Drosha/microRNAs could enhance translation.     

Repression of protein synthesis by miRNAs: how many mechanisms?

MicroRNAs are approximately 21-nucleotide-long regulators of gene expression that gain access to their target mRNAs by complementary base pairing. Recent studies have revealed that animal microRNAs might take diverse routes to repress gene expression, affecting both target mRNA levels and translation. Mechanistic details of microRNA-mediated repression are starting to emerge but a comprehensive picture of the inhibition, and particularly the effects on mRNA translation, is still lacking. Recent data support different microRNA mechanisms and a role for cytoplasmic processing bodies in the degradation and storage of mRNAs targeted by microRNA regulators.     

Prediction of personalized microRNA activity

MicroRNAs have been known to regulate almost all physiological and pathological processes by suppressing their target genes. In humans, more than 1000 microRNAs have been identified, each of which targets dozens or even hundreds of genes. Facing this huge repertoire of microRNA targeting, it is important to identify which microRNAs are active, i.e., down-regulating their targets, in specific physiological or pathological conditions. Predicting active microRNAs is different from predicting microRNA targets because the authentic target genes of a microRNA are often not directly and solely regulated by that microRNA, leading to inconsistent expression changes between the microRNA and its true targets. Several computational programs have been proposed to predict the activity of a microRNA from the expressions of its target genes. These programs performed well when being applied on the expression data obtained from distinct tissue types or from experiments that transfect a microRNA into cells (i.e., non-physiological). But the performance of microRNA activity prediction is not clear on the expression data from the same tissue type in two physiological conditions, e.g., liver tissues from cancer patients and healthy people. In this work, we evaluate the performance of two microRNA activity prediction programs using seven expression data sets, all of which compare samples in two physiological conditions, as well as propose a new approach that predicts microRNA activity with an accuracy of over 80%. Unlike current methods, which predict active microRNAs by comparing two groups of samples, e.g., tumor versus normal, our new approach compares each diseased sample with all the samples in the control group. In other words, it can predict the microRNA activity of a person. In this work, this new application is named to predict “personalized microRNA activity”.     

Regulation of p27Kip1 by miRNA 221/222 in Glioblastoma

Levels of p27Kip1, a key negative regulator of the cell cycle, are often decreased in cancer. In most cancers, levels of p27Kip1 mRNA are unchanged and increased proteolysis of the p27Kip1 protein is thought to be the primary mechanism for its down-regulation. Here we show that p27Kip1 protein levels are also down-regulated by microRNAs in cancer cells. We used RNA interference to reduce Dicer levels in human glioblastoma cell lines and found that this caused an increase in p27Kip1 levels and a decrease in cell proliferation. When the coding sequence for the 3'UTR of the p27Kip1 mRNA was inserted downstream of a luciferase reporter gene, Dicer depletion also enhanced expression of the reporter gene product. The microRNA target site software TargetScan predicts that the 3'UTR of p27Kip1 mRNA contains multiple sites for microRNAs. These include two sites for microRNA 221 and 222, which have been shown to be upregulated in glioblastoma relative to adjacent normal brain tissue. The genes for microRNA 221 and microRNA 222 occupy adjacent sites on the X chromosome; their expression appears to be coregulated and they also appear to have the same target specificity. Antagonism of either microRNA 221 or 222 in glioblastoma cells also caused an increase in p27Kip1 levels and enhanced expression of the luciferase reporter gene fused to the p27Kip1 3'UTR. These data show that p27Kip1 is a direct target for microRNAs 221 and 222, and suggest a role for these microRNAs in promoting the aggressive growth of human glioblastoma.     

Droplet digital PCR,a prospective technological approach to quantitative profiling of microRNA

MicroRNA is a special type of regulatory molecules modulating gene expression. Circulating microRNAs found in blood and other biological body fluids are now considered as potential biomarkers of human pathology. Quantitative changes of particular microRNAs have been recognized in many oncological diseases and other disorders. A recently developed method of droplet digital PCR (ddPCR) possesses a number of advantages making this method the most suitable for verification and validation of perspective microRNA markers of various human pathologies. These advantages include high accuracy and reproducibility of microRNA quantification as well as possibility of direct high-throughput determination of the absolute number of microRNA copies within a wide dynamic range. The present review considers microRNA biogenesis, the origin of circulating microRNAs, and methods used for their quantification. The special technical features of ddPCR, which make this method especially attractive for studying microRNAs as biomarkers of human pathologies and for basic research devoted to aspects of gene regulation by microRNA molecules, are also discussed.     

Platelet function and ageing

There are clear age-related changes in platelet count and function, driven by changes in hematopoietic tissue, the composition of the blood and vascular health. Platelet count remains relatively stable during middle age (25–60 years old) but falls in older people. The effect of age on platelet function is slightly less clear. The longstanding view is that platelet reactivity increases with age in an almost linear fashion. There are, however, serious limitations to the data supporting this dogma. We can conclude that platelet function increases during middle age, but little evidence exists on the changes in platelet responsiveness in old age (>75 years old). This change in platelet function is driven by differential mRNA and microRNA expression, an increase in oxidative stress and changes in platelet receptors. These age-related changes in platelets are particularly pertinent given that thrombotic disease and use of anti-platelet drugs is much more prevalent in the elderly population, yet the majority of platelet research is carried out in young to middle-aged (20–50 years old) human volunteers and young mice (2–6 months old). We know relatively little about exactly how platelets from people over 75 years old differ from those of middle-aged subjects, and we know even less about the mechanisms that drive these changes. Addressing these gaps in our knowledge will provide substantial understanding in how cell signalling changes during ageing and will enable the development of more precise anti-platelet therapies.     

Distinctive Profile of IsomiR Expression and Novel MicroRNAs in Rat Heart Left Ventricle

MicroRNAs (miRNAs) are single-stranded non-coding RNAs that negatively regulate target gene expression through mRNA cleavage or translational repression. There is mounting evidence that they play critical roles in heart disease. The expression of known miRNAs in the heart has been studied at length by microarray and quantitative PCR but it is becoming evident that microRNA isoforms (isomiRs) are potentially physiologically important. It is well known that left ventricular (patho)physiology is influenced by transmural heterogeneity of cardiomyocyte phenotype, and this likely reflects underlying heterogeneity of gene expression. Given the significant role of miRNAs in regulating gene expression, knowledge of how the miRNA profile varies across the ventricular wall will be crucial to better understand the mechanisms governing transmural physiological heterogeneity. To determinine miRNA/isomiR expression profiles in the rat heart we investigated tissue from different locations across the left ventricular wall using deep sequencing. We detected significant quantities of 145 known rat miRNAs and 68 potential novel orthologs of known miRNAs, in mature, mature* and isomiR formation. Many isomiRs were detected at a higher frequency than their canonical sequence in miRBase and have different predicted targets. The most common miR-133a isomiR was more effective at targeting a construct containing a sequence from the gelsolin gene than was canonical miR-133a, as determined by dual-fluorescence assay. We identified a novel rat miR-1 homolog from a second miR-1 gene; and a novel rat miRNA similar to miR-676. We also cloned and sequenced the rat miR-486 gene which is not in miRBase (v18). Signalling pathways predicted to be targeted by the most highly detected miRNAs include Ubiquitin-mediated Proteolysis, Mitogen-Activated Protein Kinase, Regulation of Actin Cytoskeleton, Wnt signalling, Calcium Signalling, Gap junctions and Arrhythmogenic Right Ventricular Cardiomyopathy. Most miRNAs are not expressed in a gradient across the ventricular wall, with exceptions including miR-10b, miR-21, miR-99b and miR-486.     

Age‐associated microRNA expression in human peripheral blood is associated with all‐cause mortality and age‐related traits

Recent studies provide evidence of correlations of DNA methylation and expression of protein‐coding genes with human aging. The relations of microRNA expression with age and age‐related clinical outcomes have not been characterized thoroughly. We explored associations of age with whole‐blood microRNA expression in 5221 adults and identified 127 microRNAs that were differentially expressed by age at P < 3.3 × 10^?4 (Bonferroni‐corrected). Most microRNAs were underexpressed in older individuals. Integrative analysis of microRNA and mRNA expression revealed changes in age‐associated mRNA expression possibly driven by age‐associated microRNAs in pathways that involve RNA processing, translation, and immune function. We fitted a linear model to predict ‘microRNA age’ that incorporated expression levels of 80 microRNAs. MicroRNA age correlated modestly with predicted age from DNA methylation (r = 0.3) and mRNA expression (r = 0.2), suggesting that microRNA age may complement mRNA and epigenetic age prediction models. We used the difference between microRNA age and chronological age as a biomarker of accelerated aging (Δage) and found that Δage was associated with all‐cause mortality (hazards ratio 1.1 per year difference, P = 4.2 × 10^?5 adjusted for sex and chronological age). Additionally, Δage was associated with coronary heart disease, hypertension, blood pressure, and glucose levels. In conclusion, we constructed a microRNA age prediction model based on whole‐blood microRNA expression profiling. Age‐associated microRNAs and their targets have potential utility to detect accelerated aging and to predict risks for age‐related diseases.