Circular RNA regulatory role in pathological cardiac remodelling.

Cardiac remodelling involves structural, cellular and molecular alterations in the heart after injury, resulting in progressive loss of heart function and ultimately leading to heart failure. Circular RNAs (circRNAs) are a recently rediscovered class of non-coding RNAs that play regulatory roles in the pathogenesis of cardiovascular diseases, including heart failure. Thus, a more comprehensive understanding of the role of circRNAs in the processes governing cardiac remodelling may set the ground for the development of circRNA-based diagnostic and therapeutic strategies. In this review, the current knowledge about circRNA origin, conservation, characteristics and function is summarized. Bioinformatics and wet-lab methods used in circRNA research are discussed. The regulatory function of circRNAs in cardiac remodelling mechanisms such as cell death, cardiomyocyte hypertrophy, inflammation, fibrosis and metabolism is highlighted. Finally, key challenges and opportunities in circRNA research are discussed, and orientations for future work to address the pharmacological potential of circRNAs in heart failure are proposed.

Agnodice: indexing experimentally supported bacterial sRNA-RNA interactions.

In the last decade, the immense growth in the field of bacterial small RNAs (sRNAs), along with the biotechnological breakthroughs in Deep Sequencing permitted the deeper understanding of sRNA-RNA interactions. However, microbiology is currently lacking a thoroughly curated collection of this rapidly expanding universe. We present Agnodice (https://dianalab.e-ce.uth.gr/agnodice), our effort to systematically catalog and annotate experimentally supported bacterial sRNA-RNA interactions. Agnodice, for the first time, incorporates thousands of bacterial sRNA-RNA interactions derived from a diverse set of experimental methodologies including state-of-the-art Deep Sequencing interactome identification techniques. It comprises 39,600 entries which are annotated at strain-level resolution and pertain to 399 sRNAs and 12,137 target RNAs identified in 71 bacterial strains. The database content is exclusively experimentally supported, incorporating interactions derived via low yield as well as state-of-the-art high-throughput methods. The entire content of the database is freely accessible and can be directly downloaded for further analysis. Agnodice will serve as a valuable source, enabling microbiologists to form novel hypotheses, design/identify novel sRNA-based drug targets, and explore the therapeutic potential of microbiomes from the perspective of small regulatory RNAs.IMPORTANCEAgnodice (https://dianalab.e-ce.uth.gr/agnodice) is an effort to systematically catalog and annotate experimentally supported bacterial small RNA (sRNA)-RNA interactions. Agnodice, for the first time, incorporates thousands of bacterial sRNA-RNA interactions derived from a diverse set of experimental methodologies including state-of-the-art Next Generation Sequencing interactome identification techniques.

TarBase-v9.0 extends experimentally supported miRNA-gene interactions to cell-types and virally encoded miRNAs.

TarBase is a reference database dedicated to produce, curate and deliver high quality experimentally-supported microRNA (miRNA) targets on protein-coding transcripts. In its latest version (v9.0, https://dianalab.e-ce.uth.gr/tarbasev9), it pushes the envelope by introducing virally-encoded miRNAs, interactions leading to target-directed miRNA degradation (TDMD) events and the largest collection of miRNA-gene interactions to date in a plethora of experimental settings, tissues and cell-types. It catalogues ∼6 million entries, comprising ∼2 million unique miRNA-gene pairs, supported by 37 experimental (high- and low-yield) protocols in 172 tissues and cell-types. Interactions are annotated with rich metadata including information on genes/transcripts, miRNAs, samples, experimental contexts and publications, while millions of miRNA-binding locations are also provided at cell-type resolution. A completely re-designed interface with state-of-the-art web technologies, incorporates more features, and allows flexible and ingenious use. The new interface provides the capability to design sophisticated queries with numerous filtering criteria including cell lines, experimental conditions, cell types, experimental methods, species and/or tissues of interest. Additionally, a plethora of fine-tuning capacities have been integrated to the platform, offering the refinement of the returned interactions based on miRNA confidence and expression levels, while boundless local retrieval of the offered interactions and metadata is enabled.

Long non-coding RNAs regulate Aedes aegypti vector competence for Zika virus and reproduction.

Long non-coding RNAs (lncRNAs) play critical regulatory roles in various cellular and metabolic processes in mosquitoes and all other organisms studied thus far. In particular, their involvement in essential processes such as reproduction makes them potential targets for the development of novel pest control approaches. However, their function in mosquito biology remains largely unexplored. To elucidate the role of lncRNAs in mosquitoes' reproduction and vector competence for arboviruses, we have implemented a computational and experimental pipeline to mine, screen, and characterize lncRNAs related to these two biological processes. Through analysis of publicly available Zika virus (ZIKV) infection-regulated Aedes aegypti transcriptomes, at least six lncRNAs were identified as being significantly upregulated in response to infection in various mosquito tissues. The roles of these ZIKV-regulated lncRNAs (designated Zinc1, Zinc2, Zinc3, Zinc9, Zinc10 and Zinc22), were further investigated by dsRNA-mediated silencing studies. Our results show that silencing of Zinc1, Zinc2, and Zinc22 renders mosquitoes significantly less permissive to ZIKV infection, while silencing of Zinc22 also reduces fecundity, indicating a potential role for Zinc22 in trade-offs between vector competence and reproduction. We also found that silencing of Zinc9 significantly increases fecundity but has no effect on ZIKV infection, suggesting that Zinc9 may be a negative regulator of oviposition. Our work demonstrates that some lncRNAs play host factor roles by facilitating viral infection in mosquitoes. We also show that lncRNAs can influence both mosquito reproduction and permissiveness to virus infection, two biological systems with important roles in mosquito vectorial capacity.

DIANA-miRPath v4.0: expanding target-based miRNA functional analysis in cell-type and tissue contexts.

DIANA-miRPath is an online miRNA analysis platform harnessing predicted or experimentally supported miRNA interactions towards the exploration of combined miRNA effects. In its latest version (v4.0, http://www.microrna.gr/miRPathv4), DIANA-miRPath breaks new ground by introducing the capacity to tailor its target-based miRNA functional analysis engine to specific biological and/or experimental contexts. Via a redesigned modular interface with rich interaction, annotation and parameterization options, users can now perform enrichment analysis on Gene Ontology (GO) terms, KEGG and REACTOME pathways, sets from Molecular Signatures Database (MSigDB) and PFAM. Included miRNA interaction sets are derived from state-of-the-art resources of experimentally supported (DIANA-TarBase v8.0, miRTarBase and microCLIP cell-type-specific interactions) or from in silico miRNA-target interactions (updated DIANA-microT-CDS and TargetScan predictions). Bulk and single-cell expression datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression project (GTEx) and adult/fetal single-cell atlases are integrated and can be used to assess the expression of enriched term components across a wide range of states. A discrete module enabling enrichment analyses using CRISPR knock-out screen datasets enables the detection of selected miRNAs with potentially crucial roles within conditions under study. Notably, the option to upload custom interaction, term, expression and screen sets further expands the versatility of miRPath webserver.

Virus-Derived Small RNAs and microRNAs in Health and Disease.

MicroRNAs (miRNAs) are short noncoding RNAs that can regulate all steps of gene expression (induction, transcription, and translation). Several virus families, primarily double-stranded DNA viruses, encode small RNAs (sRNAs), including miRNAs. These virus-derived miRNAs (v-miRNAs) help the virus evade the host's innate and adaptive immune system and maintain an environment of chronic latent infection. In this review, the functions of the sRNA-mediated virus-host interactions are highlighted, delineating their implication in chronic stress, inflammation, immunopathology, and disease. We provide insights into the latest viral RNA-based research-in silico approaches for functional characterization of v-miRNAs and other RNA types. The latest research can assist toward the identification of therapeutic targets to combat viral infections.

DIANA-microT 2023: including predicted targets of virally encoded miRNAs.

DIANA-microT-CDS is a state-of-the-art miRNA target prediction algorithm catering the scientific community since 2009. It is one of the first algorithms to predict miRNA binding sites in both the 3' Untranslated Region (3'-UTR) and the coding sequence (CDS) of transcripts, with increased performance. Its current version, DIANA-microT 2023 (www.microrna.gr/microt_webserver/), brings forward a significantly updated set of interactions. DIANA-microT-CDS has been executed utilizing annotation information from Ensembl v102, miRBase 22.1 and, for the first time, MirGeneDB 2.1, yielding more than 83 million interactions in human, mouse, rat, chicken, fly and worm species. Additionally, this version delivers predicted interactions of miRNAs encoded from 20 viruses against host transcripts from human, mouse and chicken species. Numerous resources have been interconnected into DIANA-microT, including DIANA-TarBase, plasmiR, HMDD, UCSC, dbSNP, ClinVar, as well as miRNA/gene abundance values for 369 distinct cell-lines/tissues. The server interface has been redesigned allowing users to use smart filtering options, identify abundance patterns of interest, pinpoint known SNPs residing on binding sites and obtain miRNA-disease information. The contents of DIANA-microT webserver are freely accessible and can also be locally downloaded without any login requirements.

Radiomic tumor phenotypes augment molecular profiling in predicting recurrence free survival after breast neoadjuvant chemotherapy.

BACKGROUND: Early changes in breast intratumor heterogeneity during neoadjuvant chemotherapy may reflect the tumor's ability to adapt and evade treatment. We investigated the combination of precision medicine predictors of genomic and MRI data towards improved prediction of recurrence free survival (RFS). METHODS: A total of 100 women from the ACRIN 6657/I-SPY 1 trial were retrospectively analyzed. We estimated MammaPrint, PAM50 ROR-S, and p53 mutation scores from publicly available gene expression data and generated four, voxel-wise 3-D radiomic kinetic maps from DCE-MR images at both pre- and early-treatment time points. Within the primary lesion from each kinetic map, features of change in radiomic heterogeneity were summarized into 6 principal components. RESULTS: We identify two imaging phenotypes of change in intratumor heterogeneity (p < 0.01) demonstrating significant Kaplan-Meier curve separation (p < 0.001). Adding phenotypes to established prognostic factors, functional tumor volume (FTV), MammaPrint, PAM50, and p53 scores in a Cox regression model improves the concordance statistic for predicting RFS from 0.73 to 0.79 (p = 0.002). CONCLUSIONS: These results demonstrate an important step in combining personalized molecular signatures and longitudinal imaging data towards improved prognosis.

Early changes in tumor properties during treatment may tell us whether or not a patient's tumor is responding to treatment. Such changes may be seen on imaging. Here, changes in breast cancer properties are identified on imaging and are used in combination with gene markers to investigate whether response to treatment can be predicted using mathematical models. We demonstrate that tumor properties seen on imaging early on in treatment can help to predict patient outcomes. Our approach may allow clinicians to better inform patients about their prognosis and choose appropriate and effective therapies.

Association of miR-144 levels in the peripheral blood with COVID-19 severity and mortality.

Coronavirus disease-2019 (COVID-19) can be asymptomatic or lead to a wide symptom spectrum, including multi-organ damage and death. Here, we explored the potential of microRNAs in delineating patient condition and predicting clinical outcome. Plasma microRNA profiling of hospitalized COVID-19 patients showed that miR-144-3p was dynamically regulated in response to COVID-19. Thus, we further investigated the biomarker potential of miR-144-3p measured at admission in 179 COVID-19 patients and 29 healthy controls recruited in three centers. In hospitalized patients, circulating miR-144-3p levels discriminated between non-critical and critical illness (AUCmiR-144-3p = 0.71; p = 0.0006), acting also as mortality predictor (AUCmiR-144-3p = 0.67; p = 0.004). In non-hospitalized patients, plasma miR-144-3p levels discriminated mild from moderate disease (AUCmiR-144-3p = 0.67; p = 0.03). Uncontrolled release of pro-inflammatory cytokines can lead to clinical deterioration. Thus, we explored the added value of a miR-144/cytokine combined analysis in the assessment of hospitalized COVID-19 patients. A miR-144-3p/Epidermal Growth Factor (EGF) combined score discriminated between non-critical and critical hospitalized patients (AUCmiR-144-3p/EGF = 0.81; p < 0.0001); moreover, a miR-144-3p/Interleukin-10 (IL-10) score discriminated survivors from nonsurvivors (AUCmiR-144-3p/IL-10 = 0.83; p < 0.0001). In conclusion, circulating miR-144-3p, possibly in combination with IL-10 or EGF, emerges as a noninvasive tool for early risk-based stratification and mortality prediction in COVID-19.

A species-specific lncRNA modulates the reproductive ability of the asian tiger mosquito.

Long non-coding RNA (lncRNA) research has emerged as an independent scientific field in recent years. Despite their association with critical cellular and metabolic processes in plenty of organisms, lncRNAs are still a largely unexplored area in mosquito research. We propose that they could serve as exceptional tools for pest management due to unique features they possess. These include low inter-species sequence conservation and high tissue specificity. In the present study, we investigated the role of ovary-specific lncRNAs in the reproductive ability of the Asian tiger mosquito, Aedes albopictus. Through the analysis of transcriptomic data, we identified several lncRNAs that were differentially expressed upon blood feeding; we called these genes Norma (NOn-coding RNA in Mosquito ovAries). We observed that silencing some of these Normas resulted in significant impact on mosquito fecundity and fertility. We further focused on Norma3 whose silencing resulted in 43% oviposition reduction, in smaller ovaries and 53% hatching reduction of the laid eggs, compared to anti-GFP controls. Moreover, a significant downregulation of 2 mucins withing a neighboring (∼100 Kb) mucin cluster was observed in smaller anti-Norma3 ovaries, indicating a potential mechanism of in-cis regulation between Norma3 and the mucins. Our work constitutes the first experimental proof-of-evidence connecting lncRNAs with mosquito reproduction and opens a novel path for pest management.

DIANA-miTED: a microRNA tissue expression database.

microRNAs (miRNAs) are short (∼23nt) single-stranded non-coding RNAs that act as potent post-transcriptional gene expression regulators. Information about miRNA expression and distribution across cell types and tissues is crucial to the understanding of their function and for their translational use as biomarkers or therapeutic targets. DIANA-miTED is the most comprehensive and systematic collection of miRNA expression values derived from the analysis of 15 183 raw human small RNA-Seq (sRNA-Seq) datasets from the Sequence Read Archive (SRA) and The Cancer Genome Atlas (TCGA). Metadata quality maximizes the utility of expression atlases, therefore we manually curated SRA and TCGA-derived information to deliver a comprehensive and standardized set, incorporating in total 199 tissues, 82 anatomical sublocations, 267 cell lines and 261 diseases. miTED offers rich instant visualizations of the expression and sample distributions of requested data across variables, as well as study-wide diagrams and graphs enabling efficient content exploration. Queries also generate links towards state-of-the-art miRNA functional resources, deeming miTED an ideal starting point for expression retrieval, exploration, comparison, and downstream analysis, without requiring bioinformatics support or expertise. DIANA-miTED is freely available at http://www.microrna.gr/mited.

PlasmiR: A Manual Collection of Circulating microRNAs of Prognostic and Diagnostic Value.

Only recently, microRNAs (miRNAs) were found to exist in traceable and distinctive amounts in the human circulatory system, bringing forth the intriguing possibility of using them as minimally invasive biomarkers. miRNAs are short non-coding RNAs that act as potent post-transcriptional regulators of gene expression. Extensive studies in cancer and other disease landscapes investigate the protective/pathogenic functions of dysregulated miRNAs, as well as their biomarker potential. A specialized resource amassing experimentally verified, circulating miRNA biomarkers does not exist. We queried the existing literature to identify articles assessing diagnostic/prognostic roles of miRNAs in blood, serum, or plasma samples. Articles were scrutinized in order to exclude instances lacking sufficient experimental documentation or employing no biomarker assessment methods. We incorporated information from more than 200 biomedical articles, annotating crucial meta-information including cohort sizes, inclusion-exclusion criteria, disease/healthy confirmation methods and quantification details. miRNAs and diseases were systematically characterized using reference resources. Our circulating miRNA biomarker collection is provided as an online database, plasmiR. It consists of 1021 entries regarding 251 miRNAs and 112 diseases. More than half of plasmiR's entries refer to cancerous and neoplastic conditions, 183 of them (32%) describing prognostic associations. plasmiR facilitates smart queries, emphasizing visualization and exploratory modes for all researchers.

Peryton: a manual collection of experimentally supported microbe-disease associations.

We present Peryton (https://dianalab.e-ce.uth.gr/peryton/), a database of experimentally supported microbe-disease associations. Its first version constitutes a novel resource hosting more than 7900 entries linking 43 diseases with 1396 microorganisms. Peryton's content is exclusively sustained by manual curation of biomedical articles. Diseases and microorganisms are provided in a systematic, standardized manner using reference resources to create database dictionaries. Information about the experimental design, study cohorts and the applied high- or low-throughput techniques is meticulously annotated and catered to users. Several functionalities are provided to enhance user experience and enable ingenious use of Peryton. One or more microorganisms and/or diseases can be queried at the same time. Advanced filtering options and direct text-based filtering of results enable refinement of returned information and the conducting of tailored queries suitable to different research questions. Peryton also provides interactive visualizations to effectively capture different aspects of its content and results can be directly downloaded for local storage and downstream analyses. Peryton will serve as a valuable source, enabling scientists of microbe-related disease fields to form novel hypotheses but, equally importantly, to assist in cross-validation of findings.

Impact of Helicobacter pylori Infection and Its Major Virulence Factor CagA on DNA Damage Repair.

Helicobacter pylori infection induces a plethora of DNA damages. Gastric epithelial cells, in order to maintain genomic integrity, require an integrous DNA damage repair (DDR) machinery, which, however, is reported to be modulated by the infection. CagA is a major H. pylori virulence factor, associated with increased risk for gastric carcinogenesis. Its pathogenic activity is partly regulated by phosphorylation on EPIYA motifs. Our aim was to identify effects of H. pylori infection and CagA on DDR, investigating the transcriptome of AGS cells, infected with wild-type, ΔCagA and EPIYA-phosphorylation-defective strains. Upon RNA-Seq-based transcriptomic analysis, we observed that a notable number of DDR genes were found deregulated during the infection, potentially resulting to base excision repair and mismatch repair compromise and an intricate deregulation of nucleotide excision repair, homologous recombination and non-homologous end-joining. Transcriptome observations were further investigated on the protein expression level, utilizing infections of AGS and GES-1 cells. We observed that CagA contributed to the downregulation of Nth Like DNA Glycosylase 1 (NTHL1), MutY DNA Glycosylase (MUTYH), Flap Structure-Specific Endonuclease 1 (FEN1), RAD51 Recombinase, DNA Polymerase Delta Catalytic Subunit (POLD1), and DNA Ligase 1 (LIG1) and, contrary to transcriptome results, Apurinic/Apyrimidinic Endodeoxyribonuclease 1 (APE1) upregulation. Our study accentuates the role of CagA as a significant contributor of H. pylori infection-mediated DDR modulation, potentially disrupting the balance between DNA damage and repair, thus favoring genomic instability and carcinogenesis.

Manatee: detection and quantification of small non-coding RNAs from next-generation sequencing data.

Small non-coding RNAs (sncRNAs) play important roles in health and disease. Next Generation Sequencing (NGS) technologies are considered as the most powerful and versatile methodologies to explore small RNA (sRNA) transcriptomes in diverse experimental and clinical studies. Small RNA-Seq (sRNA-Seq) data analysis proved to be challenging due to non-unique genomic origin, short length, and abundant post-transcriptional modifications of sRNA species. Here, we present Manatee, an algorithm for the quantification of sRNA classes and the detection of novel expressed non-coding loci. Manatee combines prior annotation of sRNAs with reliable alignment density information and extensive rescue of usually neglected multimapped reads to provide accurate transcriptome-wide sRNA expression quantification. Comparison of Manatee against state-of-the-art implementations using real and simulated data demonstrates its high accuracy across diverse sRNA classes. Manatee also goes beyond common pipelines by identifying and quantifying expression from unannotated loci and microRNA isoforms (isomiRs). It is user-friendly, can be easily incorporated in pipelines, and provides a simplified output suitable for direct usage in downstream analyses and functional studies.

DIANA-LncBase v3: indexing experimentally supported miRNA targets on non-coding transcripts.

DIANA-LncBase v3.0 (www.microrna.gr/LncBase) is a reference repository with experimentally supported miRNA targets on non-coding transcripts. Its third version provides approximately half a million entries, corresponding to ∼240 000 unique tissue and cell type specific miRNA-lncRNA pairs. This compilation of interactions is derived from the manual curation of publications and the analysis of >300 high-throughput datasets. miRNA targets are supported by 14 experimental methodologies, applied to 243 distinct cell types and tissues in human and mouse. The largest part of the database is highly confident, AGO-CLIP-derived miRNA-binding events. LncBase v3.0 is the first relevant database to employ a robust CLIP-Seq-guided algorithm, microCLIP framework, to analyze 236 AGO-CLIP-Seq libraries and catalogue ∼370 000 miRNA binding events. The database was redesigned from the ground up, providing new functionalities. Known short variant information, on >67,000 experimentally supported target sites and lncRNA expression profiles in different cellular compartments are catered to users. Interactive visualization plots, portraying correlations of miRNA-lncRNA pairs, as well as lncRNA expression profiles in a wide range of cell types and tissues, are presented for the first time through a dedicated page. LncBase v3.0 constitutes a valuable asset for ncRNA research, providing new insights to the understanding of the still widely unexplored lncRNA functions.

Transcriptome Analysis Identifies Immune Markers Related to Visceral Leishmaniasis Establishment in the Experimental Model of BALB/c Mice.

Visceral leishmaniasis (VL) caused by Leishmania donovani and L. infantum is a potentially fatal disease. To date there are no registered vaccines for disease prevention despite the fact that several vaccines are in preclinical development. Thus, new strategies are needed to improve vaccine efficacy based on a better understanding of the mechanisms mediating protective immunity and mechanisms of host immune responses subversion by immunopathogenic components of Leishmania. We found that mice vaccinated with CPA162-189-loaded p8-PLGA nanoparticles, an experimental nanovaccine, induced the differentiation of antigen-specific CD8+ T cells in spleen compared to control mice, characterized by increased dynamics of proliferation and high amounts of IFN-γ production after ex vivo re-stimulation with CPA162-189 antigen. Vaccination with CPA162-189-loaded p8-PLGA nanoparticles resulted in about 80% lower parasite load in spleen and liver at 4 weeks after challenge with L. infantum promastigotes as compared to control mice. However, 16 weeks after infection the parasite load in spleen was comparable in both mouse groups. Decreased protection levels in vaccinated mice were followed by up-regulation of the anti-inflammatory IL-10 production although at lower levels in comparison to control mice. Microarray analysis in spleen tissue at 4 weeks post challenge revealed different immune-related profiles among the two groups. Specifically, vaccinated mice were characterized by similar profile to naïve mice. On the other hand, the transcriptome of the non-vaccinated mice was dominated by increased expression of genes related to interferon type I, granulocyte chemotaxis, and immune cells suppression. This profile was significantly enriched at 16 weeks post challenge, a time-point which is relative to disease establishment, and was common for both groups, further suggesting that type I signaling and granulocyte influx has a significant role in disease establishment, pathogenesis and eventually in decreased vaccine efficacy for stimulating long-term protection. Overall, we put a spotlight on host immune networks during active VL as potential targets to improve and design more effective vaccines against disease.

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.

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

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.

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.