miR-34a-5p as molecular hub of pathomechanisms in Huntington's disease.

BACKGROUND: Although a pivotal role of microRNA (miRNA, miR) in the pathogenesis of Huntington's disease (HD) is increasingly recognized, the molecular functions of miRNAs in the pathomechanisms of HD await further elucidation. One of the miRNAs that have been associated with HD is miR-34a-5p, which was deregulated in the mouse R6/2 model and in human HD brain tissues. METHODS: The aim of our study was to demonstrate interactions between miR-34a-5p and HD associated genes. By computational means we predicted 12 801 potential target genes of miR-34a-5p. An in-silico pathway analysis revealed 22 potential miR-34a-5p target genes in the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway "Huntington's disease". RESULTS: Using our high-throughput miRNA interaction reporter assay (HiTmIR) we identified NDUFA9, TAF4B, NRF1, POLR2J2, DNALI1, HIP1, TGM2 and POLR2G as direct miR-34a-5p target genes. Direct binding of miR-34a-5p to target sites in the 3'UTRs of TAF4B, NDUFA9, HIP1 and NRF1 was verified by a mutagenesis HiTmIR assay and by determining endogenous protein levels for HIP1 and NDUFA9. STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) analysis identified protein-protein interaction networks associated with HD like "Glutamine Receptor Signaling Pathway" and "Calcium Ion Transmembrane Import Into Cytosol". CONCLUSION: Our study demonstrates multiple interactions between miR-34a-5p and HD associated target genes and thereby lays the ground for future therapeutic interventions using this miRNA.

Outside the limit: questioning the distance restrictions for cooperative miRNA binding sites.

Among the concepts in biology that are widely taken granted is a potentiated cooperative effect of multiple miRNAs on the same target. This strong hypothesis contrasts insufficient experimental evidence. The quantity as well as the quality of required side constraints of cooperative binding remain largely hidden. For miR-21-5p and miR-155-5p, two commonly investigated regulators across diseases, we selected 15 joint target genes. These were chosen to represent various neighboring 3'UTR binding site constellations, partially exceeding the distance rules that have been established for over a decade. We identified different cooperative scenarios with the binding of one miRNA enhancing the binding effects of the other miRNA and vice versa. Using both, reporter assays and whole proteome analyses, we observed these cooperative miRNA effects for genes that bear 3'UTR binding sites at distances greater than the previously defined limits. Astonishingly, the experiments provide even stronger evidence for cooperative miRNA effects than originally postulated. In the light of these findings the definition of targetomes specified for single miRNAs need to be refined by a concept that acknowledges the cooperative effects of miRNAs.

Validation of human microRNA target pathways enables evaluation of target prediction tools.

MicroRNAs are regulators of gene expression. A wide-spread, yet not validated, assumption is that the targetome of miRNAs is non-randomly distributed across the transcriptome and that targets share functional pathways. We developed a computational and experimental strategy termed high-throughput miRNA interaction reporter assay (HiTmIR) to facilitate the validation of target pathways. First, targets and target pathways are predicted and prioritized by computational means to increase the specificity and positive predictive value. Second, the novel webtool miRTaH facilitates guided designs of reporter assay constructs at scale. Third, automated and standardized reporter assays are performed. We evaluated HiTmIR using miR-34a-5p, for which TNF- and TGFB-signaling, and Parkinson's Disease (PD)-related categories were identified and repeated the pipeline for miR-7-5p. HiTmIR validated 58.9% of the target genes for miR-34a-5p and 46.7% for miR-7-5p. We confirmed the targeting by measuring the endogenous protein levels of targets in a neuronal cell model. The standardized positive and negative targets are collected in the new miRATBase database, representing a resource for training, or benchmarking new target predictors. Applied to 88 target predictors with different confidence scores, TargetScan 7.2 and miRanda outperformed other tools. Our experiments demonstrate the efficiency of HiTmIR and provide evidence for an orchestrated miRNA-gene targeting.

What's the target: understanding two decades of in silico microRNA-target prediction.

MOTIVATION: Since the initial discovery of microRNAs as post-transcriptional, regulatory key players in the 1990s, a total number of $2656$ mature microRNAs have been publicly described for Homo sapiens. As discovery of new miRNAs is still on-going, target identification remains to be an essential and challenging step preceding functional annotation analysis. One key challenge for researchers seems to be the selection of the most appropriate tool out of the larger multiverse of published solutions for a given research study set-up. RESULTS: In this review we collectively describe the field of in silico target prediction in the course of time and point out long withstanding principles as well as recent developments. By compiling a catalog of characteristics about the 98 prediction methods and identifying common and exclusive traits, we signpost a simplified mechanism to address the problem of application selection. Going further we devised interpretation strategies for common types of output as generated by frequently used computational methods. To this end, our work specifically aims to make prospective users aware of common mistakes and practical questions that arise during the application of target prediction tools. AVAILABILITY: An interactive implementation of our recommendations including materials shown in the manuscript is freely available at https://www.ccb.uni-saarland.de/mtguide.

Quantitative and time-resolved miRNA pattern of early human T cell activation.

T cells are central to the immune response against various pathogens and cancer cells. Complex networks of transcriptional and post-transcriptional regulators, including microRNAs (miRNAs), coordinate the T cell activation process. Available miRNA datasets, however, do not sufficiently dissolve the dynamic changes of miRNA controlled networks upon T cell activation. Here, we established a quantitative and time-resolved expression pattern for the entire miRNome over a period of 24 h upon human T-cell activation. Based on our time-resolved datasets, we identified central miRNAs and specified common miRNA expression profiles. We found the most prominent quantitative expression changes for miR-155-5p with a range from initially 40 molecules/cell to 1600 molecules/cell upon T-cell activation. We established a comprehensive dynamic regulatory network of both the up- and downstream regulation of miR-155. Upstream, we highlight IRF4 and its complexes with SPI1 and BATF as central for the transcriptional regulation of miR-155. Downstream of miR-155-5p, we verified 17 of its target genes by the time-resolved data recorded after T cell activation. Our data provide comprehensive insights into the range of stimulus induced miRNA abundance changes and lay the ground to identify efficient points of intervention for modifying the T cell response.

GeneTrail 3: advanced high-throughput enrichment analysis.

We present GeneTrail 3, a major extension of our web service GeneTrail that offers rich functionality for the identification, analysis, and visualization of deregulated biological processes. Our web service provides a comprehensive collection of biological processes and signaling pathways for 12 model organisms that can be analyzed with a powerful framework for enrichment and network analysis of transcriptomic, miRNomic, proteomic, and genomic data sets. Moreover, GeneTrail offers novel workflows for the analysis of epigenetic marks, time series experiments, and single cell data. We demonstrate the capabilities of our web service in two case-studies, which highlight that GeneTrail is well equipped for uncovering complex molecular mechanisms. GeneTrail is freely accessible at: http://genetrail.bioinf.uni-sb.de.

Evaluation of a Three-Dimensional Primary Human Hepatocyte Spheroid Model: Adoption and Industrialization for the Enhanced Detection of Drug-Induced Liver Injury.

Drug-induced liver injury is a leading cause of compound attrition during both preclinical and clinical drug development, and early strategies are in place to tackle this recurring problem. Human-relevant in vitro models that are more predictive of hepatotoxicity hazard identification, and that could be employed earlier in the drug discovery process, would improve the quality of drug candidate selection and help reduce attrition. We present an evaluation of four human hepatocyte in vitro models of increasing culture complexity (i.e., two-dimensional (2D) HepG2 monolayers, hepatocyte sandwich cultures, three-dimensional (3D) hepatocyte spheroids, and precision-cut liver slices), using the same tool compounds, viability end points, and culture time points. Having established the improved prediction potential of the 3D hepatocyte spheroid model, we describe implementing this model into an industrial screening setting, where the challenge was matching the complexity of the culture system with the scale and throughput required. Following further qualification and miniaturization into a 384-well, high-throughput screening format, data was generated on 199 compounds. This clearly demonstrated the ability to capture a greater number of severe hepatotoxins versus the current routine 2D HepG2 monolayer assay while continuing to flag no false-positive compounds. The industrialization and miniaturization of the 3D hepatocyte spheroid complex in vitro model demonstrates a significant step toward reducing drug attrition and improving the quality and safety of drugs, while retaining the flexibility for future improvements, and has replaced the routine use of the 2D HepG2 monolayer assay at GlaxoSmithKline.

Effect of ammonium fluoride doping on the ice III to ice IX phase transition.

Ice III is a hydrogen-disordered phase of ice that is stable between about 0.2 and 0.35 GPa. Upon cooling, it transforms to its hydrogen-ordered counterpart ice IX within the stability region of ice II. Here, the effect of ammonium fluoride doping on this phase transition is investigated, which is followed for the first time with in situ neutron diffraction. The a and c lattice constants are found to expand and contract, respectively, upon hydrogen ordering, yielding an overall negative volume change. Interestingly, the anisotropy in the lattice constants persists when ice IX is fully formed, and negative thermal expansion is observed. Analogous to the isostructural keatite and ß-spodumenes, the negative thermal expansion can be explained through the buildup of torsional strain within the a-b plane as the helical "springs" within the structure expand upon heating. The reversibility of the phase transition was demonstrated upon heating. As seen in diffraction and Raman spectroscopy, the ammonium fluoride doping induces additional residual hydrogen disorder in ice IX and is suggested to be a chemical way for the "excitation" of the configurational ice-rules manifold. Compared to ice VIII, the dopant-induced hydrogen disorder in ice IX is smaller, which suggests a higher density of accessible configurational states close to the ground state in ice IX. This study highlights the importance of dopants for exploring the water's phase diagram and underpins the highly complex solid-state chemistry of ice.

An estimate of the total number of true human miRNAs.

While the number of human miRNA candidates continuously increases, only a few of them are completely characterized and experimentally validated. Toward determining the total number of true miRNAs, we employed a combined in silico high- and experimental low-throughput validation strategy. We collected 28 866 human small RNA sequencing data sets containing 363.7 billion sequencing reads and excluded falsely annotated and low quality data. Our high-throughput analysis identified 65% of 24 127 mature miRNA candidates as likely false-positives. Using northern blotting, we experimentally validated miRBase entries and novel miRNA candidates. By exogenous overexpression of 108 precursors that encode 205 mature miRNAs, we confirmed 68.5% of the miRBase entries with the confirmation rate going up to 94.4% for the high-confidence entries and 18.3% of the novel miRNA candidates. Analyzing endogenous miRNAs, we verified the expression of 8 miRNAs in 12 different human cell lines. In total, we extrapolated 2300 true human mature miRNAs, 1115 of which are currently annotated in miRBase V22. The experimentally validated miRNAs will contribute to revising targetomes hypothesized by utilizing falsely annotated miRNAs.

A high-resolution map of the human small non-coding transcriptome.

Motivation: Although the amount of small non-coding RNA-sequencing data is continuously increasing, it is still unclear to which extent small RNAs are represented in the human genome. Results: In this study we analyzed 303 billion sequencing reads from nearly 25 000 datasets to answer this question. We determined that 0.8% of the human genome are reliably covered by 874 123 regions with an average length of 31 nt. On the basis of these regions, we found that among the known small non-coding RNA classes, microRNAs were the most prevalent. In subsequent steps, we characterized variations of miRNAs and performed a staged validation of 11 877 candidate miRNAs. Of these, many were actually expressed and significantly dysregulated in lung cancer. Selected candidates were finally validated by northern blots. Although isolated miRNAs could still be present in the human genome, our presented set likely contains the largest fraction of human miRNAs. Contact: c.backes@mx.uni-saarland.de or andreas.keller@ccb.uni-saarland.de. Supplementary information: Supplementary data are available at Bioinformatics online.

One-Dimensional Pnictogen Allotropes inside Single-Wall Carbon Nanotubes.

The discovery of phosphorene, a single layer of black phosphorus, has accelerated the investigation of pnictogen nanomaterials, leading to the recent identification of arsenene and antimonene. These two-dimensional nanomaterials display physical properties superior to those of graphene for some applications. Recently, single-wall carbon nanotubes (SWCNTs) have been filled with P4 molecules from the melt and As4 molecules from the vapor phase. Confined within SWCNTs, polymerization reactions yielded new one-dimensional pnictogen allotropes. Here, we show using high-resolution electron microscopy that such nanostructures can also be observed upon filling SWCNTs from the vapor phase using red phosphorus as the source material. Using larger-diameter SWCNTs, the vapor phase favors the formation of double-stranded phosphorus zigzag ladders observed here for the first time. Overall, however, SWCNTs were generally found to fill more efficiently with liquid phosphorus; substantial decreases in the filling yields were observed for both phosphorus and arsenic filling of narrow SWCNTs using the vapor route. Attempts to extend the pnitogen series using molten antimony gave very low filling yields. However, the antimony zigzag ladder was observed on two occasions, suggesting that this structural motif dominates across the pnictogens. Computational predictions of the encapsulation energies of the various pnictogen nanostructures are consistent with the observed experimental trends, and band gap calculations predict that the single-stranded zigzag chains of all investigated pnictogens are fully metallic. Using SWCNTs with diameters of >1.5 nm revealed a plethora of complex new phosphorus nanostructures, which highlights an exciting new avenue for future work in this area.

Do TRPV1 antagonists increase the risk for skin tumourigenesis? A collaborative in vitro and in vivo assessment.

A recent hypothesis suggesting that the pharmacological target TRPV1 (transient receptor potential vanilloid subfamily, member 1) may function as a tumour suppressor, which potentially impacts the development of TRPV1 antagonist therapeutics for a range of conditions. However, little is known about the long-term physiologic effects of TRPV1 blockade in the skin. In vitro and in vivo studies suggested that the potent TRPV1 competitive antagonist AMG-9810 promoted proliferation in N/TERT1 cells (telomerase-immortalised primary human keratinocytes 1) and tumour development in mouse skin that was mediated through EGFR/Akt/mTOR signalling. We attempted to reproduce the reported in vitro and in vivo findings to further explore this hypothesis to understand the underlying mechanism and the risk associated with TRPV1 antagonism in the skin. In vitro proliferation studies using multiple methods and topical application with AMG-9810 and structurally similar TRPV1 antagonists such as SB-705498 and PAC-14028 were performed. Although we confirmed expression of TRPV1 in primary human epidermal keratinocytes (HEKn) and spontaneously immortalised human keratinocytes (HaCaT), we were unable to demonstrate cell proliferation in either cell type or any clear evidence of increased expression of proteins in the EGFR/Akt/mTOR signalling pathway with these molecules. We were also unable to demonstrate skin tumour promotion or underlying molecular mechanisms involved in the EGFR/Akt/mTOR signalling pathway in a single-dose and two-stage carcinogenesis mouse study treated with TRPV1 antagonists. In conclusion, our data suggest that inhibiting the pharmacological function of TRPV1 in skin by specific antagonists has not been considered to be indicative of skin tumour development.

The deterministic role of 5-mers in microRNA-gene targeting.

MiRNAs play a central role in physiological and pathological processes. Both for the biological understanding and for their clinical application, it is essential to understand the interaction of miRNAs and their targets. Target identification largely hinges on in-silico prediction, which requires a complete consideration of miRNA binding sites within the UTRs of target genes. Here, we show that 5-mer sites might also play an essential role for human miRNA-target binding. We implemented and employed an algorithm to all pairs of 2,588 human miRNAs annotated in miRBase and the 3' UTRs of 16725 genes (>43 million combinations). Our in-silico analysis showed a highly significant enrichment (p = 1.4 × 10-69) of 5-mer binding sites in 3' UTRs across all experimentally validated miRNA-target gene pairs. We next confirmed the central role of 5-mer binding sites by reporter assays and demonstrated that two non-canonical 5-mer sites of miR-34a in the 3' UTR of T-cell receptor alpha (TCRA) have a significantly stronger influence on its posttranscriptional regulation than the canonical binding sites. These observations indicate an essential role of 5-mer binding sites for the miRNA targeting in human cells.

Prioritizing and selecting likely novel miRNAs from NGS data.

Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent releases (v20 and v21) are influenced by next-generation sequencing based miRNA predictions and show significant deviation from miRNAs discovered prior to the high-throughput profiling period. From the analysis of miRBase, we derived a set of key characteristics to predict new miRNAs and applied the implemented algorithm to evaluate novel blood-borne miRNA candidates. We carried out 705 individual whole miRNA sequencings of blood cells and collected a total of 9.7 billion reads. Using miRDeep2 we initially predicted 1452 potentially novel miRNAs. After excluding false positives, 518 candidates remained. These novel candidates were ranked according to their distance to the features in the early miRBase versions allowing for an easier selection of a subset of putative miRNAs for validation. Selected candidates were successfully validated by qRT-PCR and northern blotting. In addition, we implemented a web-server for ranking potential miRNA candidates, which is available at:www.ccb.uni-saarland.de/novomirank.

One-Dimensional Arsenic Allotropes: Polymerization of Yellow Arsenic Inside Single-Wall Carbon Nanotubes.

The pnictogen nanomaterials, including phosphorene and arsenene, display remarkable electronic and chemical properties. Yet, the structural diversity of these main group elements is still poorly explored. Here we fill single-wall carbon nanotubes with elemental arsenic from the vapor phase. Using electron microscopy, we find chains of highly reactive As4 molecules as well as two new one-dimensional allotropes of arsenic: a single-stranded zig-zag chain and a double-stranded zig-zag ladder. These linear structures are important intermediates between the gas-phase clusters of arsenic and the extended sheets of arsenene. Raman spectroscopy indicates weak electronic interaction between the arsenic and the nanotubes which implies that the formation of the new allotropes is driven primarily by the geometry of the confinement. The relative stabilities of the new arsenic structures are estimated computationally. Band-gap calculations predict that the insulating As4 chains become semiconducting, once converted to the zig-zag ladder, and form a fully metallic allotrope of arsenic as the zig-zag chain.

Deep characterization of blood cell miRNomes by NGS.

A systematic understanding of different factors influencing cell type specific microRNA profiles is essential for state-of-the art biomarker research. We carried out a comprehensive analysis of the biological variability and changes in cell type pattern over time for different cell types and different isolation approaches in technical replicates. All combinations of the parameters mentioned above have been measured, resulting in 108 miRNA profiles that were evaluated by next-generation-sequencing. The largest miRNA variability was due to inter-individual differences (34 %), followed by the cell types (23.4 %) and the isolation technique (17.2 %). The change over time in cell miRNA composition was moderate (<3 %) being close to the technical variations (<1 %). Largest variability (including technical and biological variance) was observed for CD8 cells while CD3 and CD4 cells showed significantly lower variations. ANOVA highlighted that 51.5 % of all miRNAs were significantly influenced by the purification technique. While CD4 cells were least affected, especially miRNA profiles of CD8 cells were fluctuating depending on the cell purification approach. To provide researchers access to the profiles and to allow further analyses of the tested conditions we implemented a dynamic web resource.

Encapsulation and Polymerization of White Phosphorus Inside Single-Wall Carbon Nanotubes.

Elemental phosphorus displays an impressive number of allotropes with highly diverse chemical and physical properties. White phosphorus has now been filled into single-wall carbon nanotubes (SWCNTs) from the liquid and thereby stabilized against the highly exothermic reaction with atmospheric oxygen. The encapsulated tetraphosphorus molecules were visualized with transmission electron microscopy, but found to convert readily into chain structures inside the SWCNT "nanoreactors". The energies of the possible chain structures were determined computationally, highlighting a delicate balance between the extent of polymerization and the SWCNT diameter. Experimentally, a single-stranded zig-zag chain of phosphorus atoms was observed, which is the lowest energy structure at small confinement diameters. These one-dimensional chains provide a glimpse into the very first steps of the transformation from white to red phosphorus.

Bias in High-Throughput Analysis of miRNAs and Implications for Biomarker Studies.

A certain degree of bias in high-throughput molecular technologies including microarrays and next-generation sequencing (NGS) is known. To quantify the actual impact of the biomarker discovery platform on miRNA profiles, we first performed a meta-analysis: raw data of 1 539 microarrays and 705 NGS blood-borne miRNomes were statistically evaluated, suggesting a substantial influence of the technology on biomarker profiles. We observed highly significant dependency of the miRNA nucleotide composition on the expression level. Higher expression in NGS was discovered for uracil-rich miRNAs (p = 7 × 10(-37)), while high expression in microarrays was found predominantly for guanine-rich miRNAs (p = 3 × 10(-33)). To verify the findings, 10 identical replicates of one individual were measured using NGS and microarrays (2 525 miRNAs from miRBase version 21). Overall, we calculated a correlation coefficient of 0.414 for both technologies. Detailed analysis however revealed that the correlation was observed only for miRNAs in the early miRBase versions (<8). The majority of miRNAs (2 013 from miRBase version 8 onward) was not correlated between microarray and NGS. Specifically, we observed 67 miRNAs with a median read count above 10 in NGS, while they were not detected in any of the 10 replicated array experiments. In contrast, 234 miRNAs were discovered in all 10 replicated array measurements but were not found in any of the NGS experiments of the same individual. While the first group had average guanine content of 22%, the latter group consisted of 41% of this nucleotide. Selected concordant and discordant miRNAs were tested in quantitative real-time-polymerase chain reaction (RT-qPCR) experiments again of the same individual, providing further evidence for the substantial bias depending on the base composition. As a consequence, biomarkers that have been discovered by specific high-throughout technologies have to be carefully considered. Especially for validation of the platform, the selection of reasonable candidates is essential.

Differential blood-based diagnosis between benign prostatic hyperplasia and prostate cancer: miRNA as source for biomarkers independent of PSA level, Gleason score, or TNM status.

Since the benefit of prostate-specific antigen (PSA) screening remains controversial, new non-invasive biomarkers for prostate carcinoma (PCa) are still required. There is evidence that microRNAs (miRNAs) in whole peripheral blood can separate patients with localized prostate cancer from healthy individuals. However, the potential of blood-based miRNAs for the differential diagnosis of PCa and benign prostatic hyperplasia (BPH) has not been tested. We compared the miRNome from blood of PCa and BPH patients and further investigated the influence of the tumor volume, tumor-node-metastasis (TNM) classification, Gleason score, pretreatment risk status, and the pretreatment PSA value on the miRNA pattern. By microarray approach, we identified seven miRNAs that were significantly deregulated in PCa patients compared to BPH patients. Using quantitative real time PCR (qRT-PCR), we confirmed downregulation of hsa-miR-221* (now hsa-miR-221-5p) and hsa-miR-708* (now hsa-miR-708-3p) in PCa compared to BPH. Clinical parameters like PSA level, Gleason score, or TNM status seem to have only limited impact on the overall abundance of miRNAs in patients' blood, suggesting a no influence of these factors on the expression of deregulated miRNAs.

MiRTargetLink--miRNAs, Genes and Interaction Networks.

Information on miRNA targeting genes is growing rapidly. For high-throughput experiments, but also for targeted analyses of few genes or miRNAs, easy analysis with concise representation of results facilitates the work of life scientists. We developed miRTargetLink, a tool for automating respective analysis procedures that are frequently applied. Input of the web-based solution is either a single gene or single miRNA, but also sets of genes or miRNAs, can be entered. Validated and predicted targets are extracted from databases and an interaction network is presented. Users can select whether predicted targets, experimentally validated targets with strong or weak evidence, or combinations of those are considered. Central genes or miRNAs are highlighted and users can navigate through the network interactively. To discover the most relevant biochemical processes influenced by the target network, gene set analysis and miRNA set analysis are integrated. As a showcase for miRTargetLink, we analyze targets of five cardiac miRNAs. miRTargetLink is freely available without restrictions at www.ccb.uni-saarland.de/mirtargetlink.