The discovery approaches and detection methods of microRNAs

Metal-organic framework (MOF)-based biosensors for miRNA detection

MicroRNAs (miRNAs) play several crucial roles in the physiological and pathological processes of the human body. They are considered as important biomarkers for the diagnosis of various disorders. Thus, rapid, sensitive, selective, and affordable detection of miRNAs is of great importance. However, the small size, low abundance, and highly similar sequences of miRNAs impose major challenges to their accurate detection in biological samples. In recent years, metal-organic frameworks (MOFs) have been applied as promising sensing materials for the fabrication of different biosensors due to their distinctive characteristics, such as high porosity and surface area, tunable pores, outstanding adsorption affinities, and ease of functionalization. In this review, the applications of MOFs and MOF-derived materials in the fabrication of fluorescence, electrochemical, chemiluminescence, electrochemiluminescent, and photoelectrochemical biosensors for the detection of miRNAs and their detection principle and analytical performance are discussed. This paper attempts to provide readers with a comprehensive knowledge of the fabrication and sensing mechanisms of miRNA detection platforms.

Isothermal amplification methods in cancer-related miRNA detection; a new paradigm in study of cancer pathology

MicroRNAs (miRNAs) are short, non-coding RNA molecules that regulate gene expression. They are involved in a wide range of biological processes, including development, differentiation, cell cycle regulation, and response to stress. Numerous studies have demonstrated that miRNAs are present in different bodily fluids, which could serve as an important biomarker. The advancement of techniques and strategies for the identification of cancer-associated miRNAs in human specimens offers a novel opportunity to diagnose cancer in early stages, predict patient prognosis and evaluate response to treatment. Isothermal techniques including loop-mediated isothermal amplification (LAMP), rolling circle amplification (RCA), or recombinase polymerase amplification (RPA) offer simplicity, efficiency, and rapidity in miRNA detection processes. In contrast to traditional PCR (polymerase chain reaction), these techniques analysis and quantify miRNA molecules in specimens using a single constant temperature. In this comprehensive review, we summarized the recent advances in cancer-related miRNA detection via highly sensitive isothermal amplification methods by more focusing on the involved mechanism.

Mechanism and Therapeutic Prospect of miRNAs in Neurodegenerative Diseases

MicroRNAs (miRNAs) are the smallest class of noncoding RNAs, which widely exist in animals and plants. They can inhibit translation or overexpression by combining with mRNA and participate in posttranscriptional regulation of genes, resulting in reduced expression of target proteins, affecting the development, growth, aging, metabolism, and other physiological and pathological processes of animals and plants. It is a powerful negative regulator of gene expression. It mediates the information exchange between different cellular pathways in cellular homeostasis and stress response and regulates the differentiation, plasticity, and neurotransmission of neurons. In neurodegenerative diseases, in addition to the complex interactions between genetic susceptibility and environmental factors, miRNAs can serve as a promising diagnostic tool for diseases. They can also increase or reduce neuronal damage by regulating the body's signaling pathways, immune system, stem cells, gut microbiota, etc. They can not only affect the occurrence of diseases and exacerbate disease progression but also promote neuronal repair and reduce apoptosis, to prevent and slow down the development of diseases. This article reviews the research progress of miRNAs on the mechanism and treatment of neurodegenerative diseases in the nervous system. This trial is registered with NCT01819545, NCT02129452, NCT04120493, NCT04840823, NCT02253732, NCT02045056, NCT03388242, NCT01992029, NCT04961450, NCT03088839, NCT04137926, NCT02283073, NCT04509271, NCT02859428, and NCT05243017.

Hypoadiponectinemia-induced upregulation of microRNA449b downregulating Nrf-1 aggravates cardiac ischemia-reperfusion injury in diabetic mice

Diabetes enhances myocardial ischemic/reperfusion (MI/R) injury via an incompletely understood mechanism. Adiponectin (APN) is a cardioprotective adipokine suppressed by diabetes. However, how hypoadiponectinemia exacerbates cardiac injury remains incompletely understood. Dysregulation of miRNAs plays a significant role in disease development. However, whether hypoadiponectinemia alters cardiac miRNA profile, contributing to diabetic heart injury, remains unclear. Methods and Results: Wild-type (WT) and APN knockout (APN-KO) mice were subjected to MI/R. A cardiac microRNA profile was determined. Among 23 miRNAs increased in APN-KO mice following MI/R, miR-449b was most significantly upregulated (3.98-fold over WT mice). Administrating miR-449b mimic increased apoptosis, enlarged infarct size, and impaired cardiac function in WT mice. In contrast, anti-miR-449b decreased apoptosis, reduced infarct size, and improved cardiac function in APN-KO mice. Bioinformatic analysis predicted 73 miR-449b targeting genes, and GO analysis revealed oxidative stress as the top pathway regulated by these genes. Venn analysis followed by luciferase assay identified Nrf-1 and Ucp3 as the two most important miR-449b targets. In vivo administration of anti-miR-449b in APN-KO mice attenuated MI/R-stimulated superoxide overproduction. In vitro experiments demonstrated that high glucose/high lipid and simulated ischemia/reperfusion upregulated miR-449b and inhibited Nrf-1 and Ucp3 expression. These pathological effects were attenuated by anti-miR-449b or Nrf-1 overexpression. In a final attempt to validate our finding in a clinically relevant model, high-fat diet (HFD)-induced diabetic mice were subjected to MI/R and treated with anti-miR-449b or APN. Diabetes significantly increased miR-449b expression and downregulated Nrf-1 and Ucp3 expression. Administration of anti-miR-449b or APN preserved cardiac Nrf-1 expression, reduced cardiac oxidative stress, decreased apoptosis and infarct size, and improved cardiac function. Conclusion: We demonstrated for the first time that hypoadiponectinemia upregulates miR-449b and suppresses Nrf-1/Ucp3 expression, promoting oxidative stress and exacerbating MI/R injury in this population. Dysregulated APN/miR-449b/oxidative stress pathway is a potential therapeutic target against diabetic MI/R injury.

Insights into Online microRNA Bioinformatics Tools

MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the importance of miRNA regulation. As a result of the vast data and information available regarding miRNAs, numerous online tools have emerged to address various biological questions related to their function and influence across essential cellular processes. This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAs.

Detection of miRNAs

MicroRNAs (miRNAs) are small, noncoding RNAs that regulate gene expression. They play an important role in many biological processes including human diseases. However, miRNAs are challenging to detect due to their short sequence length and low copy number. A number of conventional (e.g., Northern blot, microarray, and RT-qPCR) and emerging (e.g., nanostructured materials and electrochemical methods) techniques have been developed to detect miRNA, each with their own strengths and weaknesses. Some of these techniques have been combined to detect miRNAs as disease biomarkers in point-of-care (POC) settings. Nonetheless, there is still potential for further innovation to facilitate the detection of miRNAs.

Single-Molecule Sensor for High-Confidence Detection of miRNA

MicroRNAs (miRNAs) play a crucial role in regulating gene expression and have been linked to many diseases. Therefore, sensitive and accurate detection of disease-linked miRNAs is vital to the emerging revolution in early diagnosis of diseases. While the detection of miRNAs is a challenge due to their intrinsic properties such as small size, high sequence similarity among miRNAs and low abundance in biological fluids, the majority of miRNA-detection strategies involve either target/signal amplification or involve complex sensing designs. In this study, we have developed and tested a DNA-based fluorescence resonance energy transfer (FRET) sensor that enables ultrasensitive detection of a miRNA biomarker (miRNA-342-3p) expressed by triple-negative breast cancer (TNBC) cells. The sensor shows a relatively low FRET state in the absence of a target but it undergoes continuous FRET transitions between low- and high-FRET states in the presence of the target. The sensor is highly specific, has a detection limit down to low femtomolar (fM) without having to amplify the target, and has a large dynamic range (3 orders of magnitude) extending to 300 000 fM. Using this strategy, we demonstrated that the sensor allows detection of miRNA-342-3p in the miRNA-extracts from cancer cell lines and TNBC patient-derived xenografts. Given the simple-to-design hybridization-based detection, the sensing platform developed here can be used to detect a wide range of miRNAs enabling early diagnosis and screening of other genetic disorders.

Rolling Circle and Loop Mediated Isothermal Amplification Strategy for Ultrasensitive miRNA Detection

Rolling circle amplification (RCA) and loop mediated isothermal amplification (LAMP) were combined to establish the rolling circle and loop mediated isothermal amplification (RC-LAMP) method for miRNA detection. With the participation of Bst 2.0 DNA Polymerase, the method enabled RCA and LAMP amplification to occur simultaneously without thermal cycling. The limit of detection of RC-LAMP was 500 amol/L, which is comparable to previously reported amplification strategies. Moreover, its upper limit of quantitation was higher and showed a stronger resistance to matrix interference. Therefore, it is possible to detect low concentrations of miRNA in samples by increasing the total RNA added. Owing to its facile detection mode and simple operation, this method has great potential in clinical sample detection.

Highly Potent GalNAc-Conjugated Tiny LNA Anti-miRNA-122 Antisense Oligonucleotides

The development of clinically relevant anti-microRNA antisense oligonucleotides (anti-miRNA ASOs) remains a major challenge. One promising configuration of anti-miRNA ASOs called "tiny LNA (tiny Locked Nucleic Acid)" is an unusually small (~8-mer), highly chemically modified anti-miRNA ASO with high activity and specificity. Within this platform, we achieved a great enhancement of the in vivo activity of miRNA-122-targeting tiny LNA by developing a series of N-acetylgalactosamine (GalNAc)-conjugated tiny LNAs. Specifically, the median effective dose (ED50) of the most potent construct, tL-5G3, was estimated to be ~12 nmol/kg, which is ~300-500 times more potent than the original unconjugated tiny LNA. Through in vivo/ex vivo imaging studies, we have confirmed that the major advantage of GalNAc over tiny LNAs can be ascribed to the improvement of their originally poor pharmacokinetics. We also showed that the GalNAc ligand should be introduced into its 5' terminus rather than its 3' end via a biolabile phosphodiester bond. This result suggests that tiny LNA can unexpectedly be recognized by endogenous nucleases and is required to be digested to liberate the parent tiny LNA at an appropriate time in the body. We believe that our strategy will pave the way for the clinical application of miRNA-targeting small ASO therapy.

Versatile Multiplex Endogenous RNA Detection with Simultaneous Signal Normalization Using Mesoporous Silica Nanoquenchers

Detection of endogenous tumor-related RNA is vital for cancer diagnostics. Despite advancements made, live-cell RNA detection still faces numerous problems, such as low signal output and cell-to-cell variations arising from differences in probe uptake. To address these issues, we designed a versatile and highly sensitive mRNA/miRNA nanosensor featuring, for the first time, signal amplification and in-built signal normalization. Using dye-loaded mesoporous silica nanoquenchers (qMSNs) capped with target-corresponding antisense oligos (ASOs), direct fluorescence "Turn-ON" with signal amplification was achieved upon target binding. By readily varying the capping ASOs as well as cargo dyes, a suite of RNA nanosensors for multiplex target detection could be easily prepared. Further modification of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNA-responsive molecular beacons (MBs) onto our nanosensor enabled dual detection of target RNA and GAPDH mRNA, allowing for target signal normalization using GAPDH as a reference. We demonstrated that this newly developed nanosensor could successfully differentiate between noncancer and cancer cells, as well as accurately monitor the relative expression levels of multiple tumor-related RNAs simultaneously in different cancer cell lines, with a high degree of specificity and sensitivity, functioning as a noninvasive "qPCR mimic" imaging tool in live cells.

Reverse transcription-based loop-mediated isothermal amplification strategy for real-time miRNA detection with phosphorothioated probes

A novel reverse transcription-based loop-mediated isothermal amplification (LAMP) strategy for miRNA detection has been developed. This method consists of two stem-loop probes inspired by the dumbbell-shaped amplicons and inner primers used in conventional LAMP reactions. Termed "terminal hairpin formation and self-priming" (THSP), this reaction incorporates phosphorothioated (PS) modifications to achieve DNA folding and extension without primers. The final signal is monitored by a sequence-specific detection probe, which minimizes the background noise. We suggest that our rapid, facile, and reliable LAMP method will be a promising candidate for detecting miRNA in biomedical applications.

Autophagy regulation by microRNAs: Novel insights into osteosarcoma therapy

Osteosarcoma (OS) is a kind of primary bone cancer that is considered as the leading cause of children death. Surgery and chemotherapy are considered as common treatment approaches for OS; the rate of survival for patients is almost 60-70%. Besides the used therapeutic approaches, it seems that there is a crucial need to launch new treatments for OS. In this regard, more understanding about cellular and molecular pathways involved in OS can contribute to recovery and develop new therapeutic platforms. Autophagy is a cellular machinery that digests and degrades dysfunctional proteins and organelles, so it can regulate the cell proliferation and survival. Most of the time, OS cells use autophagy to increase their survival and proliferation and to gain the ability to resist chemotherapy. Although, there are several controversial evidences on how OS cells use autophagy. A variety of cellular and molecular pathways, that is, microRNAs (miRNAs) can modulate autophagy. MiRNAs are some endogenous, approximately 22 nucleotide RNAs that have an important role in posttranscriptional regulation of mRNAs by targeting them. There are many evidences that the various miRNA expressions in OS cells are dysregulated, so it can propel a normal cell to cancerous one by influencing the cell survival, apoptosis, and autophagy, and eventually increased chemoresitance. Hence, miRNAs can be considered as new biomarkers for OS diagnosis, and according to the role of autophagy in OS progression, miRNAs can use inhibiting or promoting autophagy agents. The present review summarizes the effects of aberrant expression of miRNAs in OS diagnosis and treatment with focus on their roles in autophagy.

Bioinformatics prediction and experimental validation of a novel microRNA: hsa-miR-B43 within human CDH4 gene with a potential metastasis-related function in breast cancer

As a class of short noncoding RNAs, microRNAs (miRNAs) play a key role in the modulation of gene expression. Although, the regulatory roles of currently identified miRNAs in various cancer types including breast cancer have been well documented, there are many as yet undiscovered miRNAs. The aim of the current study was to bioinformatically reanalyze a list of 189 potentially new miRNAs introduced in a previously published paper (PMID: 21346806) and experimentally explore the existence and function of a candidate one: hsa-miR-B43 in breast cancer cells. The sequences of 189 potential miRNAs were re-checked in the miRbase database. Genomic location and conservation of them were assessed with the University of California Santa Cruz (UCSC) genome browser. SSC profiler, RNAfold, miRNAFold, MiPred, and FOMmiR bioinformatics tools were furthermore utilized to explore potential hairpin structures and differentiate real miRNA precursors from pseudo ones. hsa-miR-B43 was finally selected as one of the best candidates for laboratory verification. The expression and function of hsa-miR-B43 were examined by real-time polymerase chain reaction, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, and wound-healing assays. DIANA-microT, RNAhybrid and Enrichr tools were used to predict the miRNA target genes and for further enrichment analysis. We could detect the exogenous and endogenous expression of hsa-miR-B43, as a real novel miRNA, in cancer cell lines. Gene Ontology enrichment, pathway analysis and wound-healing assay results furthermore confirmed that a metastasis-related function may be assigned to hsa-miR-B43. Our results introduced hsa-miR-B43, as a novel functional miRNA, which might play a role in the metastatic process. Further studies will be necessary to completely survey the existence and function of hsa-miR-B43 in other cancer types.

Research advances in the detection of miRNA

MicroRNAs (miRNAs) are a family of endogenous, small (approximately 22 nucleotides in length), noncoding, functional RNAs. With the development of molecular biology, the research of miRNA biological function has attracted significant interest, as abnormal miRNA expression is identified to contribute to serious human diseases such as cancers. Traditional methods for miRNA detection do not meet current demands. In particular, nanomaterial-based methods, nucleic acid amplification-based methods such as rolling circle amplification (RCA), loop-mediated isothermal amplification (LAMP), strand-displacement amplification (SDA) and some enzyme-free amplifications have been employed widely for the highly sensitive detection of miRNA. MiRNA functional research and clinical diagnostics have been accelerated by these new techniques. Herein, we summarize and discuss the recent progress in the development of miRNA detection methods and new applications. This review will provide guidelines for the development of follow-up miRNA detection methods with high sensitivity and specificity, and applicability to disease diagnosis and therapy.

New insights into tomato microRNAs

Cultivated tomato, Solanum lycopersicum, is one of the most common fruits in the global food industry. Together with the wild tomato Solanum pennellii, it is widely used for developing better cultivars. MicroRNAs affect mRNA regulation, inhibiting its translation and/or promoting its degradation. Important proteins involved in these processes are ARGONAUTE and DICER. This study aimed to identify and characterize the genes involved in the miRNA processing pathway, miRNA molecules and target genes in both species. We validated the presence of pathway genes and miRNA in different NGS libraries and 6 miRNA families using quantitative RT-PCR. We identified 71 putative proteins in S. lycopersicum and 108 in S. pennellii likely involved in small RNAs processing. Of these, 29 and 32 participate in miRNA processing pathways, respectively. We identified 343 mature miRNAs, 226 pre-miRNAs in 87 families, including 192 miRNAs, which were not previously identified, belonging to 38 new families in S. lycopersicum. In S. pennellii, we found 388 mature miRNAs and 234 pre-miRNAs contained in 85 families. All miRNAs found in S. pennellii were unpublished, being identified for the first time in our study. Furthermore, we identified 2471 and 3462 different miRNA target in S. lycopersicum and S. pennellii, respectively.

Antitumor effect of a new nano-vector with miRNA-135a on malignant glioma

Introduction

MiR-135a is found to selectively induce apoptosis in glioma cell but not in normal neurons and glial cells. However, low transfection efficacy limits its application in vivo as other miRNAs. We prepared a new kind of nano-vector based on polyethylene glycol methyl ether (mPEG) and hyper-branched polyethylenimine (hy-PEI) in order to improve the miRNA delivery system into the glioma cells.

Methods

The mPEG-g-PEI/miR-135a was constructed and detected by 1H NMR and FTIR analyses. Transmission electron microscope was utilized for its characteristics. Stability and release efficiency was assessed by electrophoresis. Biocompatibility was observed and analyzed through co-culture with astrocytes and malignant glioma cells (C6). Transfection rate was monitored by laser confocal microscopy and flow cytometry. The antitumor effect of mPEG-g-PEI/miR-135a to C6 was confirmed in vivo by MR scanning, pathology and survival curve. RT-PCR was used to assay transfection efficiency of mPEG-g-PEI/miR-135a in vitro and in vivo. And Western blotting was used to assess the expressions of the targeted proteins of miR-135a.

Results

In this experiment, we found the optimal N/P ratio of mPEG-g-PEI/miR-135a was about 6 judged by Zeta potential, particle size and encapsulation ability. The stability of mPEG-g-PEI/miR-135a in serum and the release efficiency in acid(pH=5.0) of mPEG-g-PEI/miR-135a were simulated the environment in vivo and in tumor. The mPEG-g-PEI nano-vector was co-cultured with malignant glioma cell C6 and normal astrocytes in vitro and showed good biocompatibility evaluated by CCK8 assay. The cell experiments in vitro indicated that mPEG-g-PEI could significantly improve miR-135a transfection by enhancing uptake effect of both normal glial and glioma cells. Given the C6 implanted in situ model, we discovered that the mPEG-g-PEI/miR-135a could obviously increase the survival period and inhibit the growth of glioma confirmed by MRI and histochemistry. In addition, the transfection efficiency of mPEG-g-PEI was better than that of other transfection agents either in vitro or in vivo confirmed by RT-PCR. Moreover, the expressions of the targeted proteins of miR-135a were consistent with the in vitro results.

Conclusion

These results suggest that mPEG-g-PEI is expected to provide a new effective intracellular miRNA delivery system with low toxicity for glioma therapy.

Computational identification and characterization of novel microRNA in the mammary gland of dairy goat (Capra hircus)

Many studies have indicated that microRNAs (miRNAs) influence the development of the mammary gland by posttranscriptionally affecting their target genes. The objective of this research was to identify novel miRNAs in the mammary gland of dairy goats with a bioinformatics approach that was based on expressed sequence tag (EST) and genome survey sequence (GSS) analyses. We applied all known major mammals, miRNAs to search against the goat EST and GSS databases for the first time to identify new miRNAs. We, then, validated these newly predicted miRNAs with stem-loop reverse transcription followed by a SYBR Green polymerase chain reaction assay. Finally, 29 mature miRNAs were identified and verified, and of these, 14 were grouped into 13 families based on seed sequence identity and 85 potential target genes of newly verified miRNAs were subsequently predicted, most of which seemed to encode the proteins participating in regulation of metabolism, signal transduction, growth and development. The predicting accuracy of the new miRNAs was 70.37%, which confirmed that the methods used in this study were efficient and reliable. Detailed analyses of the sequence characteristics of the novel miRNAs of the goat mammary gland were performed. In conclusion, these results provide a reference for further identification of miRNAs in animals without a complete genome and thus improve the understanding of miRNAs in the caprine mammary gland.

WITHDRAWN: Identification of microRNA precursor based on gapped n-tuple structure status composition kernel

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Bioinformatic tools for microRNA dissection

Recently, microRNAs (miRNAs) have emerged as important elements of gene regulatory networks. MiRNAs are endogenous single-stranded non-coding RNAs (~22-nt long) that regulate gene expression at the post-transcriptional level. Through pairing with mRNA, miRNAs can down-regulate gene expression by inhibiting translation or stimulating mRNA degradation. In some cases they can also up-regulate the expression of a target gene. MiRNAs influence a variety of cellular pathways that range from development to carcinogenesis. The involvement of miRNAs in several human diseases, particularly cancer, makes them potential diagnostic and prognostic biomarkers. Recent technological advances, especially high-throughput sequencing, have led to an exponential growth in the generation of miRNA-related data. A number of bioinformatic tools and databases have been devised to manage this growing body of data. We analyze 129 miRNA tools that are being used in diverse areas of miRNA research, to assist investigators in choosing the most appropriate tools for their needs.

Small RNA Detection by in Situ Hybridization Methods

Small noncoding RNAs perform multiple regulatory functions in cells, and their exogenous mimics are widely used in research and experimental therapies to interfere with target gene expression. MicroRNAs (miRNAs) are the most thoroughly investigated representatives of the small RNA family, which includes short interfering RNAs (siRNAs), PIWI-associated RNA (piRNAs), and others. Numerous methods have been adopted for the detection and characterization of small RNAs, which is challenging due to their short length and low level of expression. These include molecular biology methods such as real-time RT-PCR, northern blotting, hybridization to microarrays, cloning and sequencing, as well as single cell miRNA detection by microscopy with in situ hybridization (ISH). In this review, we focus on the ISH method, including its fluorescent version (FISH), and we present recent methodological advances that facilitated its successful adaptation for small RNA detection. We discuss relevant technical aspects as well as the advantages and limitations of ISH. We also refer to numerous applications of small RNA ISH in basic research and molecular diagnostics.

Amplification-based method for microRNA detection

Over the last two decades, the study of miRNAs has attracted tremendous attention since they regulate gene expression post-transcriptionally and have been demonstrated to be dysregulated in many diseases. Detection methods with higher sensitivity, specificity and selectivity between precursors and mature microRNAs are urgently needed and widely studied. This review gave an overview of the amplification-based technologies including traditional methods, current modified methods and the cross-platforms of them combined with other techniques. Many progresses were found in the modified amplification-based microRNA detection methods, while traditional platforms could not be replaced until now. Several sample-specific normalizers had been validated, suggesting that the different normalizers should be established for different sample types and the combination of several normalizers might be more appropriate than a single universal normalizer. This systematic overview would be useful to provide comprehensive information for subsequent related studies and could reduce the un-necessary repetition in the future.

Nanotechnology-based strategies for the detection and quantification of microRNA

MicroRNAs (miRNAs) are important regulators of gene expression, and many pathological conditions, including cancer, are characterized by altered miRNA expression levels. Therefore, accurate and sensitive quantification of miRNAs may result in correct disease diagnosis establishing these small noncoding RNA transcripts as valuable biomarkers. Aiming at overcoming some limitations of conventional quantification strategies, nanotechnology is currently providing numerous significant alternatives to miRNA sensing. In this review an up-to-date account of nanotechnology-based strategies for miRNA detection and quantification is given. The topics covered are: nanoparticle-based approaches in solution, sensing based on nanostructured surfaces, combined nanoparticle/surface sensing approaches, and single-molecule approaches.

Novel insights into miRNA in lung and heart inflammatory diseases

MicroRNAs (miRNAs) are noncoding regulatory sequences that govern posttranscriptional inhibition of genes through binding mainly at regulatory regions. The regulatory mechanism of miRNAs are influenced by complex crosstalk among single nucleotide polymorphisms (SNPs) within miRNA seed region and epigenetic modifications. Circulating miRNAs exhibit potential characteristics as stable biomarker. Functionally, miRNAs are involved in basic regulatory mechanisms of cells including inflammation. Thus, miRNA dysregulation, resulting in aberrant expression of a gene, is suggested to play an important role in disease susceptibility. This review focuses on the role of miRNA as diagnostic marker in pathogenesis of lung inflammatory diseases and in cardiac remodelling events during inflammation. From recent reports, In this context, the information about the models in which miRNAs expression were investigated including types of biological samples, as well as on the methods for miRNA validation and prediction/definition of their gene targets are emphasized in the review. Besides disease pathogenesis, promising role of miRNAs in early disease diagnosis and prognostication is also discussed. However, some miRNAs are also indicated with protective role. Thus, identifications and usage of such potential miRNAs as well as disruption of disease susceptible miRNAs using antagonists, antagomirs, are imperative and may provide a novel therapeutic approach towards combating the disease progression.

Microarray technology for analysis of microRNA expression in renal biopsies of lupus nephritis patients

Systemic lupus erythematosus (SLE) is a complex autoimmune disease, which predominantly occurs in females and is characterized by autoantibody production against a host of nuclear self-antigens and deposition of proinflammatory immune complexes in the organs including kidney glomeruli. MicroRNAs are small noncoding intracellular RNAs that modulate gene expression at the posttranslational level. Microarray technology is in widespread use for analysis of microRNA (miRNA) gene expression because of its flexibility and accurate high throughput. RNA microarray technology is based on nucleic acid hybridization between a mixture of labeled RNA targets and their corresponding complementary probes. This article offers a technological overview of microarray technology for analysis of microRNA gene expression in kidney biopsies from SLE patients.

Improved and Promising Identification of Human MicroRNAs by Incorporating a High-Quality Negative Set

MicroRNA (miRNA) plays an important role as a regulator in biological processes. Identification of (pre-) miRNAs helps in understanding regulatory processes. Machine learning methods have been designed for pre-miRNA identification. However, most of them cannot provide reliable predictive performances on independent testing data sets. We assumed this is because the training sets, especially the negative training sets, are not sufficiently representative. To generate a representative negative set, we proposed a novel negative sample selection technique, and successfully collected negative samples with improved quality. Two recent classifiers rebuilt with the proposed negative set achieved an improvement of ~6 percent in their predictive performance, which confirmed this assumption. Based on the proposed negative set, we constructed a training set, and developed an online system called miRNApre specifically for human pre-miRNA identification. We showed that miRNApre achieved accuracies on updated human and non-human data sets that were 34.3 and 7.6 percent higher than those achieved by current methods. The results suggest that miRNApre is an effective tool for pre-miRNA identification. Additionally, by integrating miRNApre, we developed a miRNA mining tool, mirnaDetect, which can be applied to find potential miRNAs in genome-scale data. MirnaDetect achieved a comparable mining performance on human chromosome 19 data as other existing methods.

MicroRNA-22 targeting CBP protects against myocardial ischemia-reperfusion injury through anti-apoptosis in rats

MicroRNAs are extensively involved in the pathogenesis of major cardiovascular diseases by suppressing target gene expression. Recent studies have reported that microRNA-22 (miR-22) may be implicated in ischemia-reperfusion (I/R) induced myocardial injury. However, the specific function of miR-22 in myocardial I/R injury is far from clear nowadays. The present study was designed to determine the role of miR-22 in myocardial I/R injury and investigate the underlying cardio-protective mechanism. The rat myocardial I/R injury model was induced by occluding the left anterior descending coronary artery for 30 min followed by 12 h reperfusion. As predicted, adenovirus-mediated miR-22 overexpression markedly reduced the release of creatine kinase and lactate dehydrogenase, infarct size and cardiomyocytes apoptosis. Moreover, CREB binding protein (CBP) as a potential miR-22 target by bioinformatics was significantly inhibited after miR-22 transfection. We also found that p53 acetylation activity, pro-apoptotic related genes Bax and p21 levels were all decreased associated with the down-regulation of CBP. In conclusion, our data demonstrate that miR-22 could inhibit apoptosis of cardiomyocytes through one of its targets, CBP. Thus, miR-22 may constitute a new therapeutic target for the prevention of myocardial I/R injury.

Meeting the methodological challenges in molecular mapping of the embryonic epigenome

The past decade of life sciences research has been driven by progress in genomics. Many voices are already proclaiming the post-genomics era, in which phenomena other than sequence polymorphism influence gene expression and also explain complex phenotypes. One of these burgeoning fields is the study of the epigenome. Although the mechanisms by which chromatin structure and reorganization as well as cytosine methylation influence gene expression are not fully understood, they are being invoked to explain the now-accepted long-term impact of the environment on gene expression, which appears to be a factor in the development of numerous diseases. Such studies are particularly relevant in early embryonic development, during which waves of epigenetic reprogramming are known to have profound impacts. Since gametes and zygotes are in the process of resetting the genome in order to create embryonic stem cells that will each differentiate to create one of many specific tissue types, this phase of life is now viewed as a window of susceptibility to epigenetic reprogramming errors. Epigenetics could explain the influence of factors such as the nutritional/metabolic status of the mother or the artificial environment of assisted reproductive technologies. However, the peculiar nature of early embryos in addition to their scarcity poses numerous technological challenges that are slowly being overcome. The principal subject of this article is to review the suitability of various current and emerging technological platforms to study oocytes and early embryonic epigenome with more emphasis on studying DNA methylation. Furthermore, the constraint of samples size, inherent to the study of preimplantation embryo development, was put in perspective with the various molecular platforms described.

Computational identification and evolutionary relationships of the microRNA gene cluster miR-71/2 in protostomes

MicroRNAs (miRNAs) are small noncoding RNA molecules which are processed into ~20-24 nt molecules that can regulate the gene expression post-transcriptionally. MiRNA gene clusters have been identified in a range of species, where in miRNAs are often processed from polycistronic transcripts. In this study, a computational approach is used to investigate the extent of evolutionary conservation of the miR-71/2 cluster in animals, and to identify novel miRNAs in the miRNA cluster miR-71/2. The miR-71/2 cluster, consisting of copies of the miR-71 and miR-2 (including miR-13) families, was found to be Protostome-specific. Although, this cluster is highly conserved across the Protostomia, the miR-2 family is completely absent from the Deuterostomia species, while miR-71 is absent from the Vertebrata and Urochordata. The evolutionary conservation and clustering propensity of the miR-71/2 family across the Protostomes could indicate the common functional roles across the member species of the Protostomia.

A Review of Computational Tools in microRNA Discovery

Since microRNAs (miRNAs) were discovered, their impact on regulating various biological activities has been a surprising and exciting field. Knowing the entire repertoire of these small molecules is the first step to gain a better understanding of their function. High throughput discovery tools such as next-generation sequencing significantly increased the number of known miRNAs in different organisms in recent years. However, the process of being able to accurately identify miRNAs is still a complex and difficult task, requiring the integration of experimental approaches with computational methods. A number of prediction algorithms based on characteristics of miRNA molecules have been developed to identify new miRNA species. Different approaches have certain strengths and weaknesses and in this review, we aim to summarize several commonly used tools in metazoan miRNA discovery.

The regulation of silkworm fibroin L chain production by miRNA-965 and miRNA-1926 in insect cells

MicroRNAs (miRNAs) are an abundant class of approximately 22-nucleotide (nt)-short noncoding RNA molecules present in the genomes of all multicellular organisms that act through base pairing to partially complementary sequences of the 3'untranslated region (UTR) of targeted mRNAs. Using bioinformatic approach, we found that the 3'UTR of the Fibroin L chain (Fib-L) mRNA matches perfectly the nucleotides 2-8 at the 5' end of the miRNA-965 and miRNA-1926. These two miRNAs might act as regulators of Fib-L gene expression at the post-transcriptional level. To examine whether Fib-L is directly targeted by miRNA-965 and miRNA-1926 in vitro, miRNA expression vectors and target reporter vector with 3'UTR of Fib-L were constructed respectively. Two vectors were co-transfected into Sf21cells. The luciferase assay showed that miRNA-965 and miRNA-1926 may down regulate the expression of Fib-L via complementary interaction with the target sites in 3'UTR.

Multiclass relevance units machine: benchmark evaluation and application to small ncRNA discovery

BACKGROUND

Classification is the problem of assigning each input object to one of a finite number of classes. This problem has been extensively studied in machine learning and statistics, and there are numerous applications to bioinformatics as well as many other fields. Building a multiclass classifier has been a challenge, where the direct approach of altering the binary classification algorithm to accommodate more than two classes can be computationally too expensive. Hence the indirect approach of using binary decomposition has been commonly used, in which retrieving the class posterior probabilities from the set of binary posterior probabilities given by the individual binary classifiers has been a major issue.

METHODS

In this work, we present an extension of a recently introduced probabilistic kernel-based learning algorithm called the Classification Relevance Units Machine (CRUM) to the multiclass setting to increase its applicability. The extension is achieved under the error correcting output codes framework. The probabilistic outputs of the binary CRUMs are preserved using a proposed linear-time decoding algorithm, an alternative to the generalized Bradley-Terry (GBT) algorithm whose application to large-scale prediction settings is prohibited by its computational complexity. The resulting classifier is called the Multiclass Relevance Units Machine (McRUM).

RESULTS

The evaluation of McRUM on a variety of real small-scale benchmark datasets shows that our proposed Naïve decoding algorithm is computationally more efficient than the GBT algorithm while maintaining a similar level of predictive accuracy. Then a set of experiments on a larger scale dataset for small ncRNA classification have been conducted with Naïve McRUM and compared with the Gaussian and linear SVM. Although McRUM's predictive performance is slightly lower than the Gaussian SVM, the results show that the similar level of true positive rate can be achieved by sacrificing false positive rate slightly. Furthermore, McRUM is computationally more efficient than the SVM, which is an important factor for large-scale analysis.

CONCLUSIONS

We have proposed McRUM, a multiclass extension of binary CRUM. McRUM with Naïve decoding algorithm is computationally efficient in run-time and its predictive performance is comparable to the well-known SVM, showing its potential in solving large-scale multiclass problems in bioinformatics and other fields of study.

Human hepatocellular carcinoma cell-specific miRNAs reveal the differential expression of miR-24 and miR-27a in cirrhotic/non-cirrhotic HCC

microRNAs (miRs) are 18–25 nucleotide non-coding RNAs that regulate gene expression in several physiological and pathological conditions. To gather more knowledge on microRNAs in human hepatocellular carcinoma (HCC) we generated a small RNA library in the human HCC cell line HA22T/VGH by cloning and sequencing the cDNA obtained following the size selection of 18–24 nucleotide RNAs. We determined the expression levels of the most frequently cloned microRNAs by qPCR in HCC tissues and in their peritumoral counterparts from biopsy specimens of 41 HCC patients. The most frequently cloned miRs were miR-24, miR-27a and miR-21, and their expression levels in human HCC tissues indicate that these miRs were dysregulated in HCC. We showed that miR-24 and miR-27a were significantly downregulated in HCCs from cirrhotic liver tissues in comparison to those from non-cirrhotic liver tissues. In cirrhotic HCCs the downregulation of miR-24 was correlated with poorer prognosis in patients with HBV and HCV virus infections. miR-21 was generally upregulated in HCC tissues versus the corresponding peritu-moral tissues, particularly in non-cirrhotic HCC. Furthermore, by sequence alignment we identified the human miR orthologue of Mus musculus miR-1199 not yet annotated. Our results outline the differential expression of miRs in cirrhotic and non-cirrhotic HCCs, thereby contributing to advances in the discovery and validation of novel molecular biomarkers of HCC progression.

Identifying miRNAs, targets and functions

microRNAs (miRNAs) are small endogenous non-coding RNAs that function as the universal specificity factors in post-transcriptional gene silencing. Discovering miRNAs, identifying their targets and further inferring miRNA functions have been a critical strategy for understanding normal biological processes of miRNAs and their roles in the development of disease. In this review, we focus on computational methods of inferring miRNA functions, including miRNA functional annotation and inferring miRNA regulatory modules, by integrating heterogeneous data sources. We also briefly introduce the research in miRNA discovery and miRNA-target identification with an emphasis on the challenges to computational biology.