Artemis G. Hatzigeorgiou

DIANA-LncBase v2: indexing microRNA targets on non-coding transcripts

microRNAs (miRNAs) are short non-coding RNAs (ncRNAs) that act as post-transcriptional regulators of coding gene expression. Long non-coding RNAs (lncRNAs) have been recently reported to interact with miRNAs. The sponge-like function of lncRNAs introduces an extra layer of complexity in the miRNA interactome. DIANA-LncBase v1 provided a database of experimentally supported and in silico predicted miRNA Recognition Elements (MREs) on lncRNAs. The second version of LncBase (www.microrna.gr/LncBase) presents an extensive collection of miRNA:lncRNA interactions. The significantly enhanced database includes more than 70 000 low and high-throughput, (in)direct miRNA:lncRNA experimentally supported interactions, derived from manually curated publications and the analysis of 153 AGO CLIP-Seq libraries. The new experimental module presents a 14-fold increase compared to the previous release. LncBase v2 hosts in silico predicted miRNA targets on lncRNAs, identified with the DIANA-microT algorithm. The relevant module provides millions of predicted miRNA binding sites, accompanied with detailed metadata and MRE conservation metrics. LncBase v2 caters information regarding cell type specific miRNA:lncRNA regulation and enables users to easily identify interactions in 66 different cell types, spanning 36 tissues for human and mouse. Database entries are also supported by accurate lncRNA expression information, derived from the analysis of more than 6 billion RNA-Seq reads.

DIANA-miRGen v3.0: accurate characterization of microRNA promoters and their regulators

microRNAs (miRNAs) are small non-coding RNAs that actively fine-tune gene expression. The accurate characterization of the mechanisms underlying miRNA transcription regulation will further expand our knowledge regarding their implication in homeostatic and pathobiological networks. Aim of DIANA-miRGen v3.0 (http://www.microrna.gr/mirgen) is to provide for the first time accurate cell-line-specific miRNA gene transcription start sites (TSSs), coupled with genome-wide maps of transcription factor (TF) binding sites in order to unveil the mechanisms of miRNA transcription regulation. To this end, more than 7.3 billion RNA-, ChIP- and DNase-Seq next generation sequencing reads were analyzed/assembled and combined with state-of-the-art miRNA TSS prediction and TF binding site identification algorithms. The new database schema and web interface facilitates user interaction, provides advanced queries and innate connection with other DIANA resources for miRNA target identification and pathway analysis. The database currently supports 276 miRNA TSSs that correspond to 428 precursors and >19M binding sites of 202 TFs on a genome-wide scale in nine cell-lines and six tissues of Homo sapiens and Mus musculus.

DIANA-TarBase v8: a decade-long collection of experimentally supported miRNA–gene interactions

Abstract DIANA-TarBase v8 (http://www.microrna.gr/tarbase) is a reference database devoted to the indexing of experimentally supported microRNA (miRNA) targets. Its eighth version is the first database indexing >1 million entries, corresponding to ∼670 000 unique miRNA-target pairs. The interactions are supported by >33 experimental methodologies, applied to ∼600 cell types/tissues under ∼451 experimental conditions. It integrates information on cell-type specific miRNA–gene regulation, while hundreds of thousands of miRNA-binding locations are reported. TarBase is coming of age, with more than a decade of continuous support in the non-coding RNA field. A new module has been implemented that enables the browsing of interactions through different filtering combinations. It permits easy retrieval of positive and negative miRNA targets per species, methodology, cell type and tissue. An incorporated ranking system is utilized for the display of interactions based on the robustness of their supporting methodologies. Statistics, pie-charts and interactive bar-plots depicting the database content are available through a dedicated result page. An intuitive interface is introduced, providing a user-friendly application with flexible options to different queries.

DIANA-mirExTra v2.0: Uncovering microRNAs and transcription factors with crucial roles in NGS expression data

Differential expression analysis (DEA) is one of the main instruments utilized for revealing molecular mechanisms in pathological and physiological conditions. DIANA-mirExTra v2.0 (http://www.microrna.gr/mirextrav2) performs a combined DEA of mRNAs and microRNAs (miRNAs) to uncover miRNAs and transcription factors (TFs) playing important regulatory roles between two investigated states. The web server uses as input miRNA/RNA-Seq read count data sets that can be uploaded for analysis. Users can combine their data with 350 small-RNA-Seq and 65 RNA-Seq in-house analyzed libraries which are provided by DIANA-mirExTra v2.0. The web server utilizes miRNA:mRNA, TF:mRNA and TF:miRNA interactions derived from extensive experimental data sets. More than 450 000 miRNA interactions and 2 000 000 TF binding sites from specific or high-throughput techniques have been incorporated, while accurate miRNA TSS annotation is obtained from microTSS experimental/in silico framework. These comprehensive data sets enable users to perform analyses based solely on experimentally supported information and to uncover central regulators within sequencing data: miRNAs controlling mRNAs and TFs regulating mRNA or miRNA expression. The server also supports predicted miRNA:gene interactions from DIANA-microT-CDS for 4 species (human, mouse, nematode and fruit fly). DIANA-mirExTra v2.0 has an intuitive user interface and is freely available to all users without any login requirement.

Defective synaptic connectivity and axonal neuropathology in a human iPSC-based model of familial Parkinson’s disease

Significance Parkinson’s disease (PD) is an incurable neurodegenerative disorder characterized by motor and nonmotor deficits, including cognitive decline and dementia. The protein αSyn is strongly associated with PD pathogenesis, whereas αSyn mutations, such as p.A53T, cause familial forms of PD. Animal models are crucial for understanding PD pathogenesis, but there are limitations in the extent to which these models reproduce faithfully the human disease. Cell-reprogramming technologies allow the generation of human neurons from patients with PD, but it has proven difficult to identify cellular pathologies in induced pluripotent stem cell–derived neurons. In this study, we created a robust p.A53T patient–derived model of PD that captures disease-related phenotypes under basal conditions, thus providing a unique system for studies of disease mechanisms and development of therapeutics. α-Synuclein (αSyn) is the major gene linked to sporadic Parkinson’s disease (PD), whereas the G209A (p.A53T) αSyn mutation causes a familial form of PD characterized by early onset and a generally severe phenotype, including nonmotor manifestations. Here we generated de novo induced pluripotent stem cells (iPSCs) from patients harboring the p.A53T mutation and developed a robust model that captures PD pathogenic processes under basal conditions. iPSC-derived mutant neurons displayed novel disease-relevant phenotypes, including protein aggregation, compromised neuritic outgrowth, and contorted or fragmented axons with swollen varicosities containing αSyn and Tau. The identified neuropathological features closely resembled those in brains of p.A53T patients. Small molecules targeting αSyn reverted the degenerative phenotype under both basal and induced stress conditions, indicating a treatment strategy for PD and other synucleinopathies. Furthermore, mutant neurons showed disrupted synaptic connectivity and widespread transcriptional alterations in genes involved in synaptic signaling, a number of which have been previously linked to mental disorders, raising intriguing implications for potentially converging disease mechanisms.

Functional Analysis of miRNAs Using the DIANA Tools Online Suite

microRNAs (miRNAs) are central regulators of gene expression. They are actively studied for their involvement in numerous physiological and pathological conditions but also as diagnostic biomarkers or promising therapeutic targets. The increased complexity of the miRNA interactomes hinders straightforward interpretation of miRNA expression differences between states and conditions. To this end, functional analysis web servers process and combine experimental and in silico data, enabling researchers to uncover targeted pathways and transcriptional mechanisms that are hidden within numerous interactions and vast expression datasets. DIANA-tools ( www.microrna.gr ) is a web server hosting state-of-the-art utilities and databases for miRNA functional investigation. Available utilities cover a wide scope of different needs and research scenarios, rendering DIANA website a one-stop-shop for miRNA analyses. The most commonly utilized databases and algorithms include DIANA-microT-CDS, DIANA-TarBase v7.0, DIANA-lncBase v2.0, DIANA-miRGen v3.0, DIANA-miRPath v3.0, and DIANA-mirExTra v2.0.In the presented protocol, we will utilize different online tools in order to explore miRNA functions and to identify probable targets of interest for downstream analyses and wet lab experiments. The combined use of different applications from the DIANA suite can shed light to numerous different aspects of miRNA regulation and regulatory function, without the necessity for extensive bioinformatics expertise or computational infrastructure.

DIANA‐TarBase and DIANA Suite Tools: Studying Experimentally Supported microRNA Targets

microRNAs (miRNAs) are short non‐coding RNAs (∼22 nts) present in animals, plants, and viruses. They are considered central post‐transcriptional regulators of gene expression and are key components in a great number of physiological and pathological conditions. The accurate characterization of their targets is considered essential to a series of applications and basic or applied research settings. DIANA‐TarBase (http://www.microrna.gr/tarbase) was initially launched in 2006. It is a reference repository indexing experimentally derived miRNA‐gene interactions in different cell types, tissues, and conditions across numerous species. This unit focuses on the study of experimentally supported miRNA‐gene interactions, as well as their functional interpretation through the use of available tools in the DIANA suite (http://www.microrna.gr). The proposed use‐case scenarios are presented in protocols, describing how to utilize the DIANA‐TarBase database and DIANA‐microT‐CDS server and perform miRNA‐targeted pathway analysis with DIANA‐miRPath‐v3. All analyses are directly invoked or initiated from DIANA‐TarBase.

A Poly(Lactic-co-Glycolic) Acid Nanovaccine Based on Chimeric Peptides from Different Leishmania infantum Proteins Induces Dendritic Cells Maturation and Promotes Peptide-Specific IFNγ-Producing CD8+ T Cells Essential for the Protection against Experimental Visceral Leishmaniasis

Visceral leishmaniasis, caused by Leishmania (L.) donovani and L. infantum protozoan parasites, can provoke overwhelming and protracted epidemics, with high case-fatality rates. An effective vaccine against the disease must rely on the generation of a strong and long-lasting T cell immunity, mediated by CD4+ TH1 and CD8+ T cells. Multi-epitope peptide-based vaccine development is manifesting as the new era of vaccination strategies against Leishmania infection. In this study, we designed chimeric peptides containing HLA-restricted epitopes from three immunogenic L. infantum proteins (cysteine peptidase A, histone H1, and kinetoplastid membrane protein 11), in order to be encapsulated in poly(lactic-co-glycolic) acid nanoparticles with or without the adjuvant monophosphoryl lipid A (MPLA) or surface modification with an octapeptide targeting the tumor necrosis factor receptor II. We aimed to construct differentially functionalized peptide-based nanovaccine candidates and investigate their capacity to stimulate the immunomodulatory properties of dendritic cells (DCs), which are critical regulators of adaptive immunity generated upon vaccination. According to our results, DCs stimulation with the peptide-based nanovaccine candidates with MPLA incorporation or surface modification induced an enhanced maturation profile with prominent IL-12 production, promoting allogeneic T cell proliferation and intracellular production of IFNγ by CD4+ and CD8+ T cell subsets. In addition, DCs stimulated with the peptide-based nanovaccine candidate with MPLA incorporation exhibited a robust transcriptional activation, characterized by upregulated genes indicative of vaccine-driven DCs differentiation toward type 1 phenotype. Immunization of HLA A2.1 transgenic mice with this peptide-based nanovaccine candidate induced peptide-specific IFNγ-producing CD8+ T cells and conferred significant protection against L. infantum infection. Concluding, our findings supported that encapsulation of more than one chimeric multi-epitope peptides from different immunogenic L. infantum proteins in a proper biocompatible delivery system with the right adjuvant is considered as an improved promising approach for the development of a vaccine against VL.

Computational Challenges and -omics Approaches for the Identification of microRNAs and Targets

From very early on, computational methods have been deemed as key players in microRNA (miRNA) research. Currently, there are numerous implemented approaches that can be used to support miRNA-related studies by identifying their coding and noncoding targets, their expression, their regulators, as well as by inferring their underlying regulatory networks. This chapter aims to provide an overview of the available state-of-the-art tools, web servers, and databases utilized in miRNA research. The selected tools cover an extensive scope ranging from miRNA annotation, promoter identification, and transcription to the identification of miRNA-controlled pathways. Significant attention has been paid to present and explain standard and novel -omics approaches that can be used to support, complement, or even substitute their in silico counterparts. Importantly, current open challenges, limitations, and good experimental practices followed in the field are comprehensively explored.

microCLIP super learning framework uncovers functional transcriptome-wide miRNA interactions

Argonaute crosslinking and immunoprecipitation (CLIP) experiments are the most widely used high-throughput methodologies for miRNA targetome characterization. The analysis of Photoactivatable Ribonucleoside-Enhanced (PAR) CLIP methodology focuses on sequence clusters containing T-to-C conversions. Here, we demonstrate for the first time that the non-T-to-C clusters, frequently observed in PAR-CLIP experiments, exhibit functional miRNA-binding events and strong RNA accessibility. This discovery is based on the analysis of an extensive compendium of bona fide miRNA-binding events, and is further supported by numerous miRNA perturbation experiments and structural sequencing data. The incorporation of these previously neglected clusters yields an average of 14% increase in miRNA-target interactions per PAR-CLIP library. Our findings are integrated in microCLIP (www.microrna.gr/microCLIP), a cutting-edge framework that combines deep learning classifiers under a super learning scheme. The increased performance of microCLIP in CLIP-Seq-guided detection of miRNA interactions, uncovers previously elusive regulatory events and miRNA-controlled pathways.AGO-PAR-CLIP is widely used for high-throughput miRNA target characterization. Here, the authors show that the previously neglected non-T-to-C clusters denote functional miRNA binding events, and develop microCLIP, a super learning framework that accurately detects miRNA interactions.