Editorial to the special issue “lipidomics and neurodegenerative diseases”

The contribution of dysregulation of lipid signaling and metabolism to neurodegenerative diseases including Alzheimer’s and Parkinson’s is the focus of this special issue. Here, the matter of three reviews and one research article is summarized

miEAA 2023: updates, new functional microRNA sets and improved enrichment visualizations

MicroRNAs (miRNAs) are small non-coding RNAs that play a critical role in regulating diverse biological processes. Extracting functional insights from a list of miRNAs is challenging, as each miRNA can potentially interact with hundreds of genes. To address this challenge, we developed miEAA, a flexible and comprehensive miRNA enrichment analysis tool based on direct and indirect miRNA annotation. The latest release of miEAA includes a data warehouse of 19 miRNA repositories, covering 10 different organisms and 139 399 functional categories. We have added information on the cellular context of miRNAs, isomiRs, and high-confidence miRNAs to improve the accuracy of the results. We have also improved the representation of aggregated results, including interactive Upset plots to aid users in understanding the interaction among enriched terms or categories. Finally, we demonstrate the functionality of miEAA in the context of ageing and highlight the importance of carefully considering the miRNA input list. MiEAA is free to use and publicly available at https://www.ccb.uni-saarland.de/mieaa/

Functional Enrichment Analysis of Regulatory Elements

This work has been partially supported by FEDER/Junta de Andalucia-Consejeria de Economia y Conocimiento/(grant CV20-36723), grant PID2020-119032RB-I00, MCIN/AEI/10.13039/501100011033 and FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades (Grant P20_00335).Statistical methods for enrichment analysis are important tools to extract biological information from omics experiments. Although these methods have been widely used for the analysis of gene and protein lists, the development of high-throughput technologies for regulatory elements demands dedicated statistical and bioinformatics tools. Here, we present a set of enrichment analysis methods for regulatory elements, including CpG sites, miRNAs, and transcription factors. Statistical significance is determined via a power weighting function for target genes and tested by theWallenius noncentral hypergeometric distribution model to avoid selection bias. These new methodologies have been applied to the analysis of a set of miRNAs associated with arrhythmia, showing the potential of this tool to extract biological information from a list of regulatory elements. These new methods are available in GeneCodis 4, a web tool able to perform singular and modular enrichment analysis that allows the integration of heterogeneous information.FEDER/Junta de Andalucia-Consejeria de Economia y Conocimiento CV20-36723MCIN/AEI PID2020-119032RB-I00FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades P20_0033

miEAA 2.0: integrating multi-species microRNA enrichment analysis and workflow management systems

Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from ten frequently investigated organisms. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miRBase miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualizations such as heatmaps and running sum curves with background distributions. We demonstrate the new features with case studies for human kidney cancer, a biomarker study on Parkinson’s disease from the PPMI cohort, and a mouse model for breast cancer. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2

Dynamic and static circulating cancer microRNA biomarkers : a validation study

For cancers and other pathologies, early diagnosis remains the most promising path to survival. Profiling of longitudinal cohorts facilitates insights into trajectories of biomarkers. We measured microRNA expression in 240 serum samples from patients with colon, lung, and breast cancer and from cancerfree controls. Each patient provided at least two serum samples, one prior to diagnosis and one following diagnosis. The median time interval between the samples was 11.6 years. Using computational models, we evaluated the circulating profiles of 21 microRNAs. The analysis yielded two sets of biomarkers, static ones that show an absolute difference between certain cancer types and controls and dynamic ones where the level over time provided higher diagnostic information content. In the first group, miR-99a-5p stands out for all three cancer types. In the second group, miR-155-5p allows to predict lung cancers and colon cancers. Classification in samples from cancer and non-cancer patients using gradient boosted trees reached an average accuracy of 79.9%. The results suggest that individual change over time or an absolute value at one time point may predict a disease with high specificity and sensitivity

A signature of circulating microRNAs predicts the response to treatment with FOLFIRI plus aflibercept in metastatic colorectal cancer patients

Antiangiogenic therapy; Circulating miRNAs; Colorectal cancerTerapia antiangiogénica; MiARN circulantes; Cáncer colorrectalTeràpia antiangiogènica; MiARN circulants; Càncer colorectalThe benefit of adding the antiangiogenic drug aflibercept to FOLFIRI regime in metastatic colorectal cancer (CRC) patients resistant to or progressive on an oxaliplatin-based therapy has been previously demonstrated. However, the absence of validated biomarkers to predict greater outcomes is a major challenge encountered when using antiangiogenic therapies. In this study we investigated profiles of circulating microRNAs (miRNAs) to build predictive models of response to treatment and survival. Plasma was obtained from 98 metastatic CRC patients enrolled in a clinical phase II trial before receiving FOLFIRI plus aflibercept treatment, and the circulating levels of 754 individual miRNAs were quantified using real-time PCR. A distinct signature of circulating miRNAs differentiated responder from non-responder patients. Remarkably, most of these miRNAs were found to target genes that are involved in angiogenic processes. Accordingly, some of these miRNAs had predictive value and entered in predictive models of response to therapy, progression of disease, and survival of patients treated with FOLFIRI plus aflibercept. Among these miRNAs, circulating levels of hsa-miR-33b-5p efficiently discriminated between responder and non-responder patients and predicted the risk of disease progression. Moreover, the combination of circulating VEGF-A and miR-33b-5p levels improved clinical stratification of metastatic CRC patients who were to receive FOLFIRI plus aflibercept treatment. In conclusion, our study supports circulating miRNAs as valuable biomarkers for predicting better outcomes in metastatic CRC patients treated with FOLFIRI plus aflibercept.Funding was provided by Sanofi

Music-listening regulates human microRNA expression

Music-listening and performance have been shown to affect human gene expression. In order to further elucidate the biological basis of the effects of music on the human body, we studied the effects of music-listening on gene regulation by sequencing microRNAs of the listeners (Music Group) and their controls (Control Group) without music exposure. We identified upregulation of six microRNAs (hsa-miR-132-3p, hsa-miR-361-5p, hsa-miR-421, hsa-miR-23a-3p, hsa-miR-23b-3p, hsa-miR-25-3p) and downregulation of two microRNAs (hsa-miR-378a-3p, hsa-miR-16-2-3p) in Music Group with high musical aptitude. Some upregulated microRNAs were reported to be responsive to neuronal activity (miR-132, miR-23a, miR-23b) and modulators of neuronal plasticity, CNS myelination, and cognitive functions like long-term potentiation and memory. miR-132 plays a critical role in regulating TAU protein levels and is important for preventing tau protein aggregation that causes Alzheimer's disease. miR-132 andDICER, upregulated after music-listening, protect dopaminergic neurons and are important for retaining striatal dopamine levels. Some of the transcriptional regulators (FOS, CREB1, JUN, EGR1,andBDNF) of the upregulated microRNAs were immediate early genes and top candidates associated with musical traits.BDNFand SNCA, co-expressed and upregulated in music-listening and music-performance, are both are activated by GATA2, which is associated with musical aptitude. Several miRNAs were associated with song-learning, singing, and seasonal plasticity networks in songbirds. We did not detect any significant changes in microRNA expressions associated with music education or low musical aptitude. Our data thereby show the importance of inherent musical aptitude for music appreciation and for eliciting the human microRNA response to music-listening.Peer reviewe

HumiR: Web Services, Tools and Databases for Exploring Human microRNA Data

For many research aspects on small non-coding RNAs, especially microRNAs, computational tools and databases are developed. This includes quantification of miRNAs, piRNAs, tRNAs and tRNA fragments, circRNAs and others. Furthermore, the prediction of new miRNAs, isomiRs, arm switch events, target and target pathway prediction and miRNA pathway enrichment are common tasks. Additionally, databases and resources containing expression profiles, e.g., from different tissues, organs or cell types, are generated. This information in turn leads to improved miRNA repositories. While most of the respective tools are implemented in a species-independent manner, we focused on tools for human small non-coding RNAs. This includes four aspects: (1) miRNA analysis tools (2) databases on miRNAs and variations thereof (3) databases on expression profiles (4) miRNA helper tools facilitating frequent tasks such as naming conversion or reporter assay design. Although dependencies between the tools exist and several tools are jointly used in studies, the interoperability is limited. We present HumiR, a joint web presence for our tools. HumiR facilitates an entry in the world of miRNA research, supports the selection of the right tool for a research task and represents the very first step towards a fully integrated knowledge-base for human small non-coding RNA research. We demonstrate the utility of HumiR by performing a very comprehensive analysis of Alzheimer’s miRNAs

LnCompare: gene set feature analysis for human long non-coding RNAs.

Interest in the biological roles of long noncoding RNAs (lncRNAs) has resulted in growing numbers of studies that produce large sets of candidate genes, for example, differentially expressed between two conditions. For sets of protein-coding genes, ontology and pathway analyses are powerful tools for generating new insights from statistical enrichment of gene features. Here we present the LnCompare web server, an equivalent resource for studying the properties of lncRNA gene sets. The Gene Set Feature Comparison mode tests for enrichment amongst a panel of quantitative and categorical features, spanning gene structure, evolutionary conservation, expression, subcellular localization, repetitive sequences and disease association. Moreover, in Similar Gene Identification mode, users may identify other lncRNAs by similarity across a defined range of features. Comprehensive results may be downloaded in tabular and graphical formats, in addition to the entire feature resource. LnCompare will empower researchers to extract useful hypotheses and candidates from lncRNA gene sets

In silico interrogation of the miRNAome of infected haematopoietic cells to predict processes important for human cytomegalovirus latent infection

Abstract Human cytomegalovirus (HCMV) latency in CD34+ progenitor cells is the outcome of a complex and continued interaction of virus and host that is initiated during very early stages of infection and reflects pro and anti-viral activity. We hypothesized that a key event during early infection could involve changes to host miRNAs, allowing for rapid modulation of the host proteome. Here, we identify 72 significantly upregulated miRNAs, and 3 that were downregulated by 6hpi of infection of CD34+ cells which were then subject to multiple in silico analyses to identify potential genes and pathways important for viral infection. The analyses focused on the upregulated miRNAs and were used to predict potential gene hubs or common mRNA targets of multiple miRNAs. Constitutive deletion of one target, the transcriptional regulator JDP2, resulted in a defect in latent infection of myeloid cells; interestingly, transient knockdown in differentiated dendritic cells resulted in increased viral lytic IE gene expression, arguing for subtle differences in the role of JDP2 during latency establishment and reactivation of HCMV. Finally, in silico predictions identified clusters of genes with related functions (such as calcium signaling, ubiquitination and chromatin modification), suggesting potential importance in latency and reactivation. Consistent with this hypothesis, we demonstrate that viral IE gene expression is sensitive to calcium channel inhibition in reactivating dendritic cells. In conclusion, we demonstrate HCMV alters the miRNAome rapidly upon infection and that in silico interrogation of these changes reveals new insight into mechanisms controlling viral gene expression during HCMV latency and, intriguingly, reactivation