bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep and accurate detection of m6A RNA modifications using miCLIP2 and m6Aboost machine learning
Authors: Körtel Nadine , Rücklé Cornelia , Zhou You , Busch Anke , Hoch-Kraft Peter , Sutandy FX Reymond , Haase Jacob , Pradhan Mihika , Musheev Michael , Ostareck Dirk , Ostareck-Lederer Antje , Dieterich Christoph , Hüttelmaier Stefan , Niehrs Christof , Rausch Oliver , Dominissini Dan , König Julian , Zarnack Kathi 
Published: December 2020

ABSTRACTN6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present miCLIP2 in combination with machine learning to significantly improve m6A detection. The optimised miCLIP2 results in high-complexity libraries from less input material. Importantly, we established a robust computational pipeline to tackle the inherent issue of false positives in antibody-based m6A detection. The analyses are calibrated withMettl3knockout cells to learn the characteristics of m6A deposition, including m6A sites outside of DRACH motifs. To make our results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP2 data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.HighlightsmiCLIP2 produces complex libraries to map m6A RNA modificationsMettl3KO miCLIP2 allows to identify Mettl3-dependent RNA modification sitesMachine learning predicts genuine m6A sites from human and mouse miCLIP2 data withoutMettl3KOm6A modifications occur outside of DRACH motifs and associate with alternative splicing
A Systematic Review and Network Meta-Analysis for COVID-19 Treatments
Authors: Zhang Chenyang , Jin Huaqing , Wen Yifeng , Yin Guosheng 
Published: December 2020

AbstractBackgroundNumerous interventions for coronavirus disease 2019 (COVID-19) have been investigated by randomized controlled trials (RCTs). This systematic review and Bayesian network meta-analysis (NMA) aim to provide a comprehensive evaluation of efficacy of available treatments for COVID-19.MethodsWe searched for candidate COVID-19 studies in WHO COVID-19 Global Research Database, PubMed, PubMed Central, LitCovid, Proquest Central and Ovid up to December 19, 2020. RCTs for suspected or confirmed COVID-19 patients were included, regardless of publication status or demographic characteristics. Bayesian NMA with fixed effects was conducted to estimate the effect sizes using posterior means and 95% equal-tailed credible intervals (CrIs), while that with random effects was carried out as well for sensitivity analysis. Bayesian hierarchical models were used to estimate effect sizes of treatments grouped by their drug classifications.ResultsWe identified 96 eligible RCTs with a total of 51187 patients. Compared with the standard of care (SOC), this NMA showed that dexamethasone led to lower risk of mortality with an odds ratio (OR) of 0.85 (95% CrI [0.76, 0.95]; moderate certainty) and lower risk of mechanical ventilation (MV) with an OR of 0.68 (95% CrI [0.56, 0.83]; low certainty). For hospital discharge, remdesivir (OR 1.37, 95% CrI [1.15, 1.64]; moderate certainty), dexamethasone (OR 1.20, 95% CrI [1.08, 1.34]; low certainty), interferon beta (OR 2.15, 95% CrI [1.26, 3.74]; moderate certainty), tocilizumab (OR 1.40, 95% CrI [1.05, 1.89]; moderate certainty) and baricitinib plus remdesivir (OR 1.75, 95% CrI [1.28, 2.39]; moderate certainty) could all increase the discharge rate respectively. Recombinant human granulocyte colony-stimulating factor indicated lower risk of MV (OR 0.20, 95% CrI [0.10, 0.40]; moderate certainty); and patients receiving convalescent plasma resulted in better viral clearance (OR 2.28, 95% CrI [1.57, 3.34]; low certainty). About two-thirds of the studies included in this NMA were rated as high risk of bias, and the certainty of evidence was either low or very low for most of the comparisons.ConclusionThe Bayesian NMA identified superiority of several COVID-19 treatments over SOC in terms of mortality, requirement of MV, hospital discharge and viral clearance. These results provide a comprehensive comparison of current COVID-19 treatments and shed new light on further research and discovery of potential COVID-19 treatments.
Iliski, a software for robust calculation of transfer functions
Authors: Aydin Ali-Kemal , Haselden William D. , Dang Julie , Drew Patrick J. , Charpak Serge , Boido Davide 
Published: December 2020

1.AbstractUnderstanding the relationships between biological events is paramount to unravel pathophysiological mechanisms. These relationships can be modeled with Transfer Functions (TFs), with no need of a priori hypotheses as to the shape of the transfer function. Here we present Iliski, a software dedicated to TFs computation between two signals. It includes different pre-treatment routines and TF computation processes: deconvolution, deterministic and non-deterministic optimization algorithms that are adapted to disparate datasets. We apply Iliski to data on neurovascular coupling, an ensemble of biological events that link neuronal activity to local changes of blood flow, highlighting the software benefits and caveats in the computation and evaluation of TFs. We also propose a workflow that will help users to choose the best computation according to the dataset. Iliski is available under the open-source license CC BY 4.0 on GitLab (https://gitlab.com/AliK_A/iliski) and can be used on the most common operating systems, either within the MATLAB environment, or as a standalone application.
EBV miRNAs are potent effectors of tumor cell transcriptome remodeling in promoting immune escape
Authors: Ungerleider Nathan , Bullard Whitney , Kara Mehmet , Wang Xia , Roberts Claire , Renne Rolf , Tibbetts Scott , Flemington Erik 
Published: December 2020

ABSTRACTEpstein Barr virus (EBV) contributes to the tumor phenotype through a limited set of primarily non-coding viral RNAs, including 31 mature miRNAs. Here we investigated the impact of EBV miRNAs on remodeling the tumor cell transcriptome. Strikingly, EBV miRNAs displayed exceptionally abundant expression in primary EBV-associated Burkitt’s Lymphomas (BLs) and Gastric Carcinomas (GCs). To investigate viral miRNA targeting, we used the high-resolution approach, CLASH in GC and a BL cell models. Affinity constant calculations of targeting efficacies for CLASH hits showed that viral miRNAs bind their targets more effectively than their host counterparts, as did Kaposi’s sarcoma-associated herpesvirus (KSHV) and murine gammaherpesvirus 68 (MHV68) miRNAs. Using public BL and GC RNA-seq datasets, we found that high EBV miRNA targeting efficacies translates to enhanced reduction of target expression. Pathway analysis of high efficacy EBV miRNA targets showed enrichment for innate and adaptive immune responses. Inhibition of the immune response by EBV miRNAs was functionally validatedin vivothrough the finding of inverse correlations between EBV miRNAs and immune cell infiltration and T-cell diversity in TCGA GC dataset. Together, this study demonstrates that EBV miRNAs are potent effectors of the tumor transcriptome that play a role in suppressing the host immune response.AUTHOR SUMMARYBurkitt’s Lymphoma and gastric cancer are both associated with EBV, a prolific DNA tumor virus that latently resides in nearly all human beings. Despite mostly restricting viral gene expression to noncoding RNAs, EBV has important influences on the fitness of infected tumor cells. Here, we show that the miRNA class of viral noncoding RNAs are a major viral contributor to remodeling the tumor cell regulatory machinery in patient tumor samples. First, an assessment of miRNA expression in clinical tumor samples showed that EBV miRNAs are expressed at unexpectedly high levels relative to cell miRNAs. Using a highly specific miRNA target identification approach, CLASH, we comprehensively identified both viral and cellular microRNA targets and the relative abundance of each microRNA-mRNA interaction. We also show that viral microRNAs bind to and alter the expression of their mRNA targets more effectively than their cellular microRNA counterparts. Pathway analysis of the most effectively targeted mRNAs revealed enrichment of immune signaling pathways and we show a corresponding inverse correlation between EBV miRNA expression and infiltrating immune cells in EBV positive primary tumors. Altogether, this study shows that EBV miRNAs are key regulators of the tumor cell phenotype and the immune cell microenvironment.
Cetylpyridinium chloride-containing mouthwashes reduce the infectivity of SARS-CoV-2 variantsin vitro
Authors: Muñoz-Basagoiti Jordana , Perez-Zsolt Daniel , León Rubén , Blanc Vanessa , Raïch-Regué Dàlia , Cano-Sarabia Mary , Trinité Benjamin , Pradenas Edwards , Blanco Julià , Gispert Joan , Clotet Bonaventura , Izquierdo-Useros Nuria 
Published: December 2020

ABSTRACTOral mouthwashes decrease the infectivity of several respiratory viruses including SARS-CoV-2. However, the precise agents with antiviral activity present in these oral rinses and their exact mechanism of action remain unknown. Here we show that Cetylpyridinium chloride (CPC), a quaternary ammonium compound present in many oral mouthwashes, reduces SARS-CoV-2 infectivity by inhibiting the viral fusion step with target cells after disrupting the integrity of the viral envelope. We also found that CPC-containing mouth rinses decreased more than a thousand times the infectivity of SARS-CoV-2in vitro, while the corresponding vehicles had no effect. This activity was effective for different SARS-CoV-2 variants, including the B.1.1.7 variant, predominant in UK, also in the presence of sterilized saliva. CPC-containing mouth rinses could therefore represent a cost-effective measure to reduce SARS-CoV-2 infectivity in saliva, aiding to reduce viral transmission from infected individuals regardless of the variants they are infected with.
Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning
Authors: Frazer Jonathan , Notin Pascal , Dias Mafalda , Gomez Aidan , Brock Kelly , Gal Yarin , Marks Debora S. 
Published: December 2020

AbstractQuantifying the pathogenicity of protein variants in human disease-related genes would have a profound impact on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences1–3. In principle, computational methods could support the large-scale interpretation of genetic variants. However, prior methods4–7have relied on training machine learning models on available clinical labels. Since these labels are sparse, biased, and of variable quality, the resulting models have been considered insufficiently reliable8. By contrast, our approach leverages deep generative models to predict the clinical significance of protein variants without relying on labels. The natural distribution of protein sequences we observe across organisms is the result of billions of evolutionary experiments9,10. By modeling that distribution, we implicitly capture constraints on the protein sequences that maintain fitness. Our model EVE (Evolutionary model of Variant Effect) not only outperforms computational approaches that rely on labelled data, but also performs on par, if not better than, high-throughput assays which are increasingly used as strong evidence for variant classification11–23. After thorough validation on clinical labels, we predict the pathogenicity of 11 million variants across 1,081 disease genes, and assign high-confidence reclassification for 72k Variants of Unknown Significance8. Our work suggests that models of evolutionary information can provide a strong source of independent evidence for variant interpretation and that the approach will be widely useful in research and clinical settings.
Identification of Key Genes Potentially Related to Triple Receptor Negative Breast Cancer by Microarray Analysis
Authors: Vastrad Basavaraj , Vastrad Chanabasayya , Kotturshetti Iranna 
Published: December 2020

AbstractTriple receptor negative breast cancer (TNBC) is the type of gynecological cancer in the elderly women. This study is aimed to explore molecular mechanism of TNBC via bioinformatics analysis. The gene expression profiles of GSE88715 (including 38 TNBC and 38 normal control) was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the limma package in R software. Pathway and gene ontology (GO) enrichment analysis were performed based on various pathway dabases and GO database. Then, InnateDb interactome database, Cytoscape and PEWCC1 were applied to construct the protein-protein interaction (PPI) network and screen hub genes. Similarly, miRNet database, NetworkAnalyst database and Cytoscape were applied to construct the target gene - miRNA network and target gene - TF network, and screen targate genes. Pathway and GO enrichment analysis was further performed for hub genes, gene clusters identified via module analysis and targate genes. The expression of hub genes with prognostic values was validated on the UALCAN, cBio Portal, The Human Protein Atlas, receiver operator characteristic (ROC) curve analysis, RT-PCR analysis and immune infiltration analysis. A total of 949 DEGs were identified in TNBC (469 up regulated genes, and 480 down regulated genes), and they were mainly enriched in the terms of phospholipases, toxoplasmosis, immune response, cell surface, glycolysis, biosynthesis of amino acids, carboxylic acid metabolic process and organic substance catabolic process extracellular space. Hub genes including UBD, HLA-B, MYC and HSP90AB1 were identified via PPI network and modules, which were mainly enriched in immune response, antigen processing and presentation, cell cycle and pathways in cancer. Targate genes including CCDC80, PEG10, HOPX and CCNA2 were identified via target gene - miRNA network and target gene - TF network, which were mainly enriched in extracellular structure organization, validated targets of C-MYC transcriptional activation, ensemble of genes encoding core extracellular matrix including ECM glycoproteins and cell cycle. The top five significantly overexpressed mRNA (ADAM15, BATF, NOTCH3, ITGAX and SDC1) and the top five significantly underexpressed mRNA (RPL4, EEF1G, RPL3, RBMX and ABCC2) were selected for further validation in TNBCpatients and healthy controls. Analysis of the expression of genes in the various databases showed that ADAM15, BATF, NOTCH3, ITGAX, SDC1, RPL4, EEF1G, RPL3, RBMX and ABCC2 expressions have a cancer specific pattern in TNBC. Collectively, ADAM15, BATF, NOTCH3, ITGAX, SDC1, RPL4, EEF1G, RPL3, RBMX and ABCC2 may be useful candidate biomarkers for TNBC diagnosis, prognosis and theraputic targates.
Cytopath: Simulation-based inference of differentiation trajectories from RNA velocity fields
Authors: Gupta R. , Cerletti D. , Gut G. , Oxenius A. , Claassen M. 
Published: December 2020

AbstractTrajectory inference from single-cell RNA sequencing data bears the potential to systematically reconstruct complex differentiation processes, however inferring trajectories that accurately model the biological characteristics of varied processes continues to be a challenge, notwithstanding the many available solutions. In general, trajectory and pseudotime inference methods have so far suffered from the ambiguity of static single-cell transcriptome snapshots lacking a concept of directionality and rate of transcriptional activity.We report Cytopath, a method for trajectory inference that takes advantage of transcriptional activity information from RNA velocity of single-cells to perform trajectory inference. Cytopath performs this task by defining a Markov chain model, simulating an ensemble of possible differentiation trajectories and constructs a consensus trajectory. We show that Cytopath can recapitulate the topological and molecular characteristics of the differentiation process under study. In our analysis we include differentiation trajectories with varying bifurcated, circular, convergent and mixed topology studied in single-snapshot as well as time-series single-cell RNA sequencing experiments. We demonstrate superior and enabling capability to reconstruct differentiation trajectories in comparison to state-of-the art trajectory inference approaches.
Hepatitis B virus envelope proteins can serve as therapeutic targets embedded in the host cell plasma membrane
Authors: Zhao Lili , Chen Fuwang , Quitt Oliver , Festag Marvin , Ringelhan Marc , Wisskirchen Karin , Hasreiter Julia , Yakovleva Luidmila , Sureau Camille , Bohne Felix , Aichler Michaela , Bruss Volker , Shevtsov Maxim , van de Klundert Maarten , Momburg Frank , Möhl Britta S. , Protzer Ulrike 
Published: December 2020

AbstractHepatitis B virus (HBV) infection is a major health threat causing 880,000 deaths each year. Available therapies control viral replication, but do not cure HBV leaving patients at risk to develop hepatocellular carcinoma. Here we show that HBV envelope proteins (HBs) - besides their integration into endosomal membranes - become embedded in the plasma membrane where they can be targeted by redirected T-cells. HBs was detected on the surface of HBV-infected cells, in livers of mice replicating HBV and in HBV-induced hepatocellular carcinoma. Staining with HBs-specific recombinant antibody MoMab recognizing a confirmational epitope indicated that membrane-associated HBs remains correctly folded in HBV-replicating cells in cell culture and in livers of HBV-transgenic micein vivo. MoMab coated onto superparamagnetic iron oxide nanoparticles allowed to detect membrane-associated HBs after HBV infection by electron microscopy in distinct stretched of the hepatocyte plasma membrane. Last not least we demonstrate that HBs located to the cell surface allows therapeutic targeting of HBV-positive cells by T-cells either engrafted with a chimeric antigen receptor or redirected by bispecific, T-cell engager antibodies.
Distinct molecular pathways govern presynaptic homeostatic plasticity
Authors: Nair Anu G. , Muttathukunnel Paola , Müller Martin 
Published: December 2020

SummaryPresynaptic homeostatic plasticity (PHP) stabilizes synaptic transmission by counteracting impaired neurotransmitter receptor function through increased presynaptic release. PHP is thought to be triggered by impaired receptor function, and to involve a stereotypic signaling pathway. However, here we demonstrate that different receptor perturbations that similarly reduce synaptic activity result in vastly different responses at theDrosophilaneuromuscular junction. While receptor inhibition by the glutamate receptor (GluR) antagonist γ-DGG is not compensated by PHP, the GluR inhibitors PhTx-433 and Gyki induce compensatory PHP. Intriguingly, PHP triggered by PhTx and Gyki involve separable signaling pathways, including inhibition of distinct GluR subtypes, differential modulation of the active-zone scaffold Bruchpilot, and short-term plasticity. Moreover, while PHP upon Gyki treatment does not require genes promoting PhTx-induced PHP, it involves presynaptic Protein Kinase D. Thus, synapses not only respond differentially to similar activity impairments, but achieve homeostatic compensation via distinct mechanisms, highlighting the diversity of homeostatic signaling.
Assessment and comparison of two different methods to extract nucleic acids from individual honey bees
Authors: Swami Rohan , Ganser Brooke , Tarpy David R. , Strand Micheline K. , Li-Byarlay Hongmei 
Published: December 2020

AbstractThe honey bee is an excellent model system to study behavior ecology, behavioral genetics, and sociogenomics. Nucleic acid based analyses enable a broad scope of research in functional genomics, disease diagnostics, mutant screening, and genetic breeding. Multiple levels of analysis lead to a more comprehensive understanding of the causes of phenotypic variation by integrating genomic variation, transcriptomic profiles, and epigenomic information. One limitation, however, is the sample preparation procedures to obtain high quality DNA and RNA simultaneously, particularly from small amounts of material, such as tissues of individual bees. We demonstrate that it is feasible to perform dual extractions of DNA and RNA from a single individual bee and compare the quality and quantity of the extracted nucleic acids using two different types of methods (column based versus ethanol precipitation). We obtained a higher yield of both DNA and RNA with one of the extraction methods over the other, although the quality of the DNA and RNA was not significantly different between methods. We describe here the first validated method for dual extraction of DNA and RNA specifically from individual honey bees.
How to coordinate vaccination and social distancing to mitigate SARS-CoV-2 outbreaks
Authors: Grundel Sara , Heyder Stefan , Hotz Thomas , Ritschel Tobias K. S. , Sauerteig Philipp , Worthmann Karl 
Published: December 2020

AbstractMost countries have started vaccinating people against COVID-19. However, due to limited production capacities and logistical challenges it will take months/years until herd immunity is achieved. Therefore, vaccination and social distancing have to be coordinated. In this paper, we provide some insight on this topic using optimization-based control on an age-differentiated compartmental model. For real-life decision making, we investigate the impact of the planning horizon on the optimal vaccination/social distancing strategy. We find that in order to reduce social distancing in the long run, without overburdening the healthcare system, it is essential to vaccinate the people with the highest contact rates first. That is also the case if the objective is to minimize fatalities provided that the social distancing measures are sufficiently strict. However, for short-term planning it is optimal to focus on the high-risk group.