miRMaid: a unified programming interface for microRNA data resources

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are endogenous small RNAs that play a key role in post-transcriptional regulation of gene expression in animals and plants. The number of known miRNAs has increased rapidly over the years. The current release (version 14.0) of miRBase, the central online repository for miRNA annotation, comprises over 10.000 miRNA precursors from 115 different species. Furthermore, a large number of decentralized online resources are now available, each contributing with important miRNA annotation and information.</p> <p>Results</p> <p>We have developed a software framework, designated here as miRMaid, with the goal of integrating miRNA data resources in a uniform web service interface that can be accessed and queried by researchers and, most importantly, by computers. miRMaid is built around data from miRBase and is designed to follow the official miRBase data releases. It exposes miRBase data as inter-connected web services. Third-party miRNA data resources can be modularly integrated as miRMaid plugins or they can loosely couple with miRMaid as individual entities in the World Wide Web. miRMaid is available as a public web service but is also easily installed as a local application. The software framework is freely available under the LGPL open source license for academic and commercial use.</p> <p>Conclusion</p> <p>miRMaid is an intuitive and modular software platform designed to unify miRBase and independent miRNA data resources. It enables miRNA researchers to computationally address complex questions involving the multitude of miRNA data resources. Furthermore, miRMaid constitutes a basic framework for further programming in which microRNA-interested bioinformaticians can readily develop their own tools and data sources.</p

Characteristic Evolution and Matching

I review the development of numerical evolution codes for general relativity based upon the characteristic initial value problem. Progress in characteristic evolution is traced from the early stage of 1D feasibility studies to 2D axisymmetric codes that accurately simulate the oscillations and gravitational collapse of relativistic stars and to current 3D codes that provide pieces of a binary black hole spacetime. Cauchy codes have now been successful at simulating all aspects of the binary black hole problem inside an artificially constructed outer boundary. A prime application of characteristic evolution is to extend such simulations to null infinity where the waveform from the binary inspiral and merger can be unambiguously computed. This has now been accomplished by Cauchy-characteristic extraction, where data for the characteristic evolution is supplied by Cauchy data on an extraction worldtube inside the artificial outer boundary. The ultimate application of characteristic evolution is to eliminate the role of this outer boundary by constructing a global solution via Cauchy-characteristic matching. Progress in this direction is discussed.Comment: New version to appear in Living Reviews 2012. arXiv admin note: updated version of arXiv:gr-qc/050809

MultiMiTar: A Novel Multi Objective Optimization based miRNA-Target Prediction Method

BACKGROUND: Machine learning based miRNA-target prediction algorithms often fail to obtain a balanced prediction accuracy in terms of both sensitivity and specificity due to lack of the gold standard of negative examples, miRNA-targeting site context specific relevant features and efficient feature selection process. Moreover, all the sequence, structure and machine learning based algorithms are unable to distribute the true positive predictions preferentially at the top of the ranked list; hence the algorithms become unreliable to the biologists. In addition, these algorithms fail to obtain considerable combination of precision and recall for the target transcripts that are translationally repressed at protein level. METHODOLOGY/PRINCIPAL FINDING: In the proposed article, we introduce an efficient miRNA-target prediction system MultiMiTar, a Support Vector Machine (SVM) based classifier integrated with a multiobjective metaheuristic based feature selection technique. The robust performance of the proposed method is mainly the result of using high quality negative examples and selection of biologically relevant miRNA-targeting site context specific features. The features are selected by using a novel feature selection technique AMOSA-SVM, that integrates the multi objective optimization technique Archived Multi-Objective Simulated Annealing (AMOSA) and SVM. CONCLUSIONS/SIGNIFICANCE: MultiMiTar is found to achieve much higher Matthew's correlation coefficient (MCC) of 0.583 and average class-wise accuracy (ACA) of 0.8 compared to the others target prediction methods for a completely independent test data set. The obtained MCC and ACA values of these algorithms range from -0.269 to 0.155 and 0.321 to 0.582, respectively. Moreover, it shows a more balanced result in terms of precision and sensitivity (recall) for the translationally repressed data set as compared to all the other existing methods. An important aspect is that the true positive predictions are distributed preferentially at the top of the ranked list that makes MultiMiTar reliable for the biologists. MultiMiTar is now available as an online tool at www.isical.ac.in/~bioinfo_miu/multimitar.htm. MultiMiTar software can be downloaded from www.isical.ac.in/~bioinfo_miu/multimitar-download.htm

Downregulation of miR-92a Is Associated with Aggressive Breast Cancer Features and Increased Tumour Macrophage Infiltration

BACKGROUND: MicroRNAs are small non-coding RNAs involved in the regulation of gene expression on a posttranscriptional level. These regulatory RNAs have been implicated in numerous cellular processes and are further deregulated in different cancer types, including breast cancer. MiR-92a is part of the miR-17∼92 cluster, which was first reported to be linked to tumourigenesis. However, little is known about the expression of miR-92a in breast cancer and potential associations to tumour properties. The expression of miR-92a was therefore characterized in 144 invasive breast cancer samples using in situ hybridization and related to clinico-pathological data as well as to selected key properties of the tumour stroma, including the presence of macrophages (CD68) and cancer activated fibroblasts (alpha-SMA). METHODOLOGY/PRINCIPAL FINDINGS: To measure miR-92a levels, an in situ hybridisation protocol was developed and validated using cell lines and miR-92a inhibitors. The expression in the tumour samples was objectively evaluated using digital image analysis program subtracting background activities. We found that the miR-92a expression varied between tumours and was inversely correlated to tumour grade (r = -0.276, p = 0.003) and recurrence-free survival (p = 0.008) and provided independent prognostic information in multivariate Cox analysis (HR: 0.375, CI: 0.145-0.972, p = 0.043). MiR-92a was moreover inversely correlated to the number of infiltrating macrophages in the tumour stroma (r = -0.357, p<0.001), and downregulation of miR-92a promoted cell migration (p<0.01). CONCLUSIONS/SIGNIFICANCE: This study demonstrates that downregulation of miR-92a in breast cancer is linked to key epithelial and stromal properties as well as clinical outcome

Study protocol: a mixed methods feasibility study for a loaded self-managed exercise programme for patellofemoral pain

Background: Patellofemoral pain (PFP) is one of the most common forms of knee pain in adults under the age of 40, with a prevalence of 23% in the general population. The long-term prognosis is poor, with only one third of people pain-free 1 year after diagnosis. The biomedical model of pain in relation to persistent PFP has recently been called into question. It has been suggested that interventions for chronic musculoskeletal conditions should consider alternative mechanisms of action, beyond muscles and joints. Modern treatment therapies should consider desensitising strategies, with exercises that target movements and activities patients find fearful and painful. High-quality research on exercise prescription in relation to pain mechanisms, not directed at specific tissue pathology, and dose response clearly warrants further investigation. Our primary aim is to establish the feasibility and acceptability of conducting a definitive RCT which will evaluate the clinical and cost-effectiveness of a loaded self-managed exercise programme for people with patellofemoral pain. Method: This is a single-centred, multiphase, sequential, mixed-methods trial that will evaluate the feasibility of running a definitive large-scale randomised controlled trial of a loaded self-managed exercise programme versus usual physiotherapy. Initially, 8–10 participants with a minimum 3-month history of PFP will be recruited from an NHS physiotherapy waiting list and interviewed. Participants will be invited to discuss perceived barriers and facilitators to exercise engagement, and the meaning and impact of PFP. Then, 60 participants will be recruited in the same manner for the main phase of the feasibility trial. A web-based service will randomise patients to a loaded self-managed exercise programme or usual physiotherapy. The loaded self-managed exercise programme is aimed at addressing lower limb knee and hip weakness and is positioned within a framework of reducing fear/avoidance with an emphasis on self-management. Baseline assessment will include demographic data, average pain within the last week (VAS), fear avoidance behaviours, catastrophising, self-efficacy, sport and leisure activity participation, and general quality of life. Follow-up will be 3 and 6 months. The analysis will focus on descriptive statistics and confidence intervals. The qualitative components will follow a thematic analysis approach. Discussion: This study will evaluate the feasibility of running a definitive large-scale trial on patients with patellofemoral pain, within the NHS in the UK. We will identify strengths and weaknesses of the proposed protocol and the utility and characteristics of the outcome measures. The results from this study will inform the design of a multicentre trial

Expression profile of microRNAs in young stroke patients

10.1371/journal.pone.0007689PLoS ONE41

The Characterisation of Three Types of Genes that Overlie Copy Number Variable Regions

Background: Due to the increased accuracy of Copy Number Variable region (CNV) break point mapping, it is now possible to say with a reasonable degree of confidence whether a gene (i) falls entirely within a CNV; (ii) overlaps the CNV or (iii) actually contains the CNV. We classify these as type I, II and III CNV genes respectively. Principal Findings: Here we show that although type I genes vary in copy number along with the CNV, most of these type I genes have the same expression levels as wild type copy numbers of the gene. These genes must, therefore, be under homeostatic dosage compensation control. Looking into possible mechanisms for the regulation of gene expression we found that type I genes have a significant paucity of genes regulated by miRNAs and are not significantly enriched for monoallelically expressed genes. Type III genes, on the other hand, have a significant excess of genes regulated by miRNAs and are enriched for genes that are monoallelically expressed. Significance: Many diseases and genomic disorders are associated with CNVs so a better understanding of the different ways genes are associated with normal CNVs will help focus on candidate genes in genome wide association studies

Identification of Trypanosome Proteins in Plasma from African Sleeping Sickness Patients Infected with T. b. rhodesiense

Control of human African sleeping sickness, caused by subspecies of the protozoan parasite Trypanosoma brucei, is based on preventing transmission by elimination of the tsetse vector and by active diagnostic screening and treatment of infected patients. To identify trypanosome proteins that have potential as biomarkers for detection and monitoring of African sleeping sickness, we have used a ‘deep-mining” proteomics approach to identify trypanosome proteins in human plasma. Abundant human plasma proteins were removed by immunodepletion. Depleted plasma samples were then digested to peptides with trypsin, fractionated by basic reversed phase and each fraction analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This sample processing and analysis method enabled identification of low levels of trypanosome proteins in pooled plasma from late stage sleeping sickness patients infected with Trypanosoma brucei rhodesiense. A total of 254 trypanosome proteins were confidently identified. Many of the parasite proteins identified were of unknown function, although metabolic enzymes, chaperones, proteases and ubiquitin-related/acting proteins were found. This approach to the identification of conserved, soluble trypanosome proteins in human plasma offers a possible route to improved disease diagnosis and monitoring, since these molecules are potential biomarkers for the development of a new generation of antigen-detection assays. The combined immuno-depletion/mass spectrometric approach can be applied to a variety of infectious diseases for unbiased biomarker identification

A Curated Database of miRNA Mediated Feed-Forward Loops Involving MYC as Master Regulator

BACKGROUND: The MYC transcription factors are known to be involved in the biology of many human cancer types. But little is known about the Myc/microRNAs cooperation in the regulation of genes at the transcriptional and post-transcriptional level. METHODOLOGY/PRINCIPAL FINDINGS: Employing independent databases with experimentally validated data, we identified several mixed microRNA/Transcription Factor Feed-Forward Loops regulated by Myc and characterized completely by experimentally supported regulatory interactions, in human. We then studied the statistical and functional properties of these circuits and discussed in more detail a few interesting examples involving E2F1, PTEN, RB1 and VEGF. CONCLUSIONS/SIGNIFICANCE: We have assembled and characterized a catalogue of human mixed Transcription Factor/microRNA Feed-Forward Loops, having Myc as master regulator and completely defined by experimentally verified regulatory interactions

Functional and Transcriptional Induction of Aquaporin-1 Gene by Hypoxia; Analysis of Promoter and Role of Hif-1α

Aquaporin-1 (AQP1) is a water channel that is highly expressed in tissues with rapid O2 transport. It has been reported that this protein contributes to gas permeation (CO2, NO and O2) through the plasma membrane. We show that hypoxia increases Aqp1 mRNA and protein levels in tissues, namely mouse brain and lung, and in cultured cells, the 9L glioma cell line. Stopped-flow light-scattering experiments confirmed an increase in the water permeability of 9L cells exposed to hypoxia, supporting the view that hypoxic Aqp1 up-regulation has a functional role. To investigate the molecular mechanisms underlying this regulatory process, transcriptional regulation was studied by transient transfections of mouse endothelial cells with a 1297 bp 5′ proximal Aqp1 promoter-luciferase construct. Incubation in hypoxia produced a dose- and time-dependent induction of luciferase activity that was also obtained after treatments with hypoxia mimetics (DMOG and CoCl2) and by overexpressing stabilized mutated forms of HIF-1α. Single mutations or full deletions of the three putative HIF binding domains present in the Aqp1 promoter partially reduced its responsiveness to hypoxia, and transfection with Hif-1α siRNA decreased the in vitro hypoxia induction of Aqp1 mRNA and protein levels. Our results indicate that HIF-1α participates in the hypoxic induction of AQP1. However, we also demonstrate that the activation of Aqp1 promoter by hypoxia is complex and multifactorial and suggest that besides HIF-1α other transcription factors might contribute to this regulatory process. These data provide a conceptual framework to support future research on the involvement of AQP1 in a range of pathophysiological conditions, including edema, tumor growth, and respiratory diseases