An atlas of cells in the human tonsil.

Palatine tonsils are secondary lymphoid organs (SLOs) representing the first line of immunological defense against inhaled or ingested pathogens. We generated an atlas of the human tonsil composed of >556,000 cells profiled across five different data modalities, including single-cell transcriptome, epigenome, proteome, and immune repertoire sequencing, as well as spatial transcriptomics. This census identified 121 cell types and states, defined developmental trajectories, and enabled an understanding of the functional units of the tonsil. Exemplarily, we stratified myeloid slan-like subtypes, established a BCL6 enhancer as locally active in follicle-associated T and B cells, and identified SIX5 as putative transcriptional regulator of plasma cell maturation. Analyses of a validation cohort confirmed the presence, annotation, and markers of tonsillar cell types and provided evidence of age-related compositional shifts. We demonstrate the value of this resource by annotating cells from B cell-derived mantle cell lymphomas, linking transcriptional heterogeneity to normal B cell differentiation states of the human tonsil.

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data.

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, limitations, and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for continuous extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies, while the containers and reproducible workflows could easily be deployed and extended to evaluate new methods or data sets.

pH-degradable, bisphosphonate-loaded nanogels attenuate liver fibrosis by repolarization of M2-type macrophages.

Immune-suppressive (M2-type) macrophages can contribute to the progression of cancer and fibrosis. In chronic liver diseases, M2-type macrophages promote the replacement of functional parenchyma by collagen-rich scar tissue. Here, we aim to prevent liver fibrosis progression by repolarizing liver M2-type macrophages toward a nonfibrotic phenotype by applying a pH-degradable, squaric ester­based nanogel carrier system. This nanotechnology platform enables a selective conjugation of the highly water-soluble bisphosphonate alendronate, a macrophage-repolarizing agent that intrinsically targets bone tissue. The covalent delivery system, however, promotes the drug's safe and efficient delivery to nonparenchymal cells of fibrotic livers after intravenous administration. The bisphosphonate payload does not eliminate but instead reprograms profibrotic M2- toward antifibrotic M1-type macrophages in vitro and potently prevents liver fibrosis progression in vivo, mainly via induction of a fibrolytic phenotype, as demonstrated by transcriptomic and proteomic analyses. Therefore, the alendronate-loaded squaric ester­based nanogels represent an attractive approach for nanotherapeutic interventions in fibrosis and other diseases driven by M2-type macrophages, including cancer.

Plasma metabolomic and lipidomic profiles accurately classify mothers of children with congenital heart disease: an observational study.

INTRODUCTION: Congenital heart disease (CHD) is the most common congenital anomaly, representing a significant global disease burden. Limitations exist in our understanding of aetiology, diagnostic methodology and screening, with metabolomics offering promise in addressing these. OBJECTIVE: To evaluate maternal metabolomics and lipidomics in prediction and risk factor identification for childhood CHD. METHODS: We performed an observational study in mothers of children with CHD following pregnancy, using untargeted plasma metabolomics and lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). 190 cases (157 mothers of children with structural CHD (sCHD); 33 mothers of children with genetic CHD (gCHD)) from the children OMACp cohort and 162 controls from the ALSPAC cohort were analysed. CHD diagnoses were stratified by severity and clinical classifications. Univariate, exploratory and supervised chemometric methods were used to identify metabolites and lipids distinguishing cases and controls, alongside predictive modelling. RESULTS: 499 metabolites and lipids were annotated and used to build PLS-DA and SO-CovSel-LDA predictive models to accurately distinguish sCHD and control groups. The best performing model had an sCHD test set mean accuracy of 94.74% (sCHD test group sensitivity 93.33%; specificity 96.00%) utilising only 11 analytes. Similar test performances were seen for gCHD. Across best performing models, 37 analytes contributed to performance including amino acids, lipids, and nucleotides. CONCLUSIONS: Here, maternal metabolomic and lipidomic analysis has facilitated the development of sensitive risk prediction models classifying mothers of children with CHD. Metabolites and lipids identified offer promise for maternal risk factor profiling, and understanding of CHD pathogenesis in the future.

Biosignatures of defective sebaceous gland activity in sebum-rich and sebum-poor skin areas in adult atopic dermatitis.

Atopic dermatitis (AD) is a composite disease presenting disruption of the skin permeability barrier (SPB) in the stratum corneum (SC). Recent evidence supports derangement of the sebaceous gland (SG) activity in the AD pathomechanisms. The objective of this study was to delineate profiles of both sebaceous and epidermal lipids and of aminoacids from SG-rich (SGR) and SG-poor (SGP) areas in AD. Both sebum and SC were sampled from SGR areas, while SC was sampled also from SGP areas in 54 adult patients with AD, consisting of 34 and 20 subjects, respectively with and without clinical involvement of face, and in 44 age and sex-matched controls. Skin biophysics were assessed in all sampling sites. Disruption of the SBP was found to be associated with dysregulated lipidome. Abundance of sapienate and lignocerate, representing, respectively, sebum and the SC type lipids, were decreased in sebum and SC from both SGR and SGP areas. Analogously, squalene was significantly diminished in AD, regardless the site. Extent of lipid derangement in SGR areas was correlated with the AD severity. The abundance of aminoacids in the SC from SGR areas was altered more than that determined in SGP areas. Several gender-related differences were found in both controls and AD subgroups. In conclusion, the SG activity was differently compromised in adult females and males with AD, in both SGR and SGP areas. In AD, alterations in the aminoacidome profiles were apparent in the SGR areas. Lipid signatures in association with aminoacidome and skin physical properties may serve the definition of phenotype clusters that associate with AD severity and gender.

Genetic Cell Ablation Reveals Clusters of Local Self-Renewing Microglia in the Mammalian Central Nervous System.

During early embryogenesis, microglia arise from yolk sac progenitors that populate the developing central nervous system (CNS), but how the tissue-resident macrophages are maintained throughout the organism's lifespan still remains unclear. Here, we describe a system that allows specific, conditional ablation of microglia in adult mice. We found that the microglial compartment was reconstituted within 1 week of depletion. Microglia repopulation relied on CNS-resident cells, independent from bone-marrow-derived precursors. During repopulation, microglia formed clusters of highly proliferative cells that migrated apart once steady state was achieved. Proliferating microglia expressed high amounts of the interleukin-1 receptor (IL-1R), and treatment with an IL-1R antagonist during the repopulation phase impaired microglia proliferation. Hence, microglia have the potential for efficient self-renewal without the contribution of peripheral myeloid cells, and IL-1R signaling participates in this restorative proliferation process.

Impact of plastic-related compounds on the gene expression signature of HepG2 cells transfected with CYP3A4.

The presence of plastic and microplastic within the oceans as well as in marine flora and fauna have caused a multitude of problems that have been the topic of numerous investigations for many years. However, their impact on human health remains largely unknown. Such plastic and microplastic particles have been detected in blood and placenta, underlining their ability to enter the human body. Plastics also contain other compounds, such as plasticizers, antioxidants, or dyes, whose impact on human health is currently being studied. Critical enzymes within the metabolism of endogenous molecules, especially of xenobiotics, are the cytochrome P450 monooxygenases (CYPs). Although their importance in maintaining cellular balance has been confirmed, their interactions with plastics and related products are poorly understood. In this study, the possible relationship between different plastic-related compounds and CYP3A4 as one of the most important CYPs was analyzed using hepatic cells overexpressing this enzyme. Beginning with virtual compound screening and molecular docking of more than 1000 plastic-related compounds, several candidates were identified to interact with CYP3A4. In a second step, RNA-sequencing was used to study in detail the transcriptome-wide gene expression levels affected by the selected compounds. Three candidate molecules ((2,2'-methylenebis(6-tert-butyl-4-methylphenol), 1,1-bis(3,5-di-tert-butyl-2-hydroxyphenyl)ethane, and 2,2'-methylenebis(6-cyclohexyl-4-methylphenol)) had an excellent binding affinity to CYP3A4 in-silico as well as cytotoxic effects and interactions with several metabolic pathways in-vitro. We identified common pathways influenced by all three selected plastic-related compounds. In particular, the suppression of pathways related to mitosis and 'DNA-templated DNA replication' which were confirmed by cell cycle analysis and single-cell gel electrophoresis. Furthermore, several mis-regulated metabolic and inflammation-related pathways were identified, suggesting the induction of hepatotoxicity at different levels. These findings imply that these compounds may cause liver problems subsequently affecting the entire organism.

Improvement of Qualitative Analyses of Aliphatic Alcohols Using Direct Catalytic Fuel Cell and Chemometric Analysis Format.

Direct catalytic methanol fuel cells (DCMFCs) have been studied for several years for energy conversion. Less extensive is the investigation of their analytical properties. In this paper, we demonstrate that the behavior of both the discharge and charger curves of DCMFCs depends on the chemical composition of the solution injected in the fuel cell. Their discharge and charge curves, analyzed using a chemometric data fusion method named ComDim, enable the identification of various types of aliphatic alcohols diluted in water. The results also show that the identification of alcohols can be obtained from the first portion of the discharge and charge curves. To this end, the curves have been described by a set of features related to the slope and intercept of the initial portion of the curves. The ComDim analysis of this set of features shows that the identification of alcohols can be obtained in a time that is about thirty times shorter than the time taken to achieve steady-state voltage.

Gene expression variability in long-term survivors of childhood cancer and cancer-free controls in response to ionizing irradiation.

BACKGROUND: Differential expression analysis is usually adjusted for variation. However, most studies that examined the expression variability (EV) have used computations affected by low expression levels and did not examine healthy tissue. This study aims to calculate and characterize an unbiased EV in primary fibroblasts of childhood cancer survivors and cancer-free controls (N0) in response to ionizing radiation. METHODS: Human skin fibroblasts of 52 donors with a first primary neoplasm in childhood (N1), 52 donors with at least one second primary neoplasm (N2 +), as well as 52 N0 were obtained from the KiKme case-control study and exposed to a high (2 Gray) and a low dose (0.05 Gray) of X-rays and sham- irradiation (0 Gray). Genes were then classified as hypo-, non-, or hyper-variable per donor group and radiation treatment, and then examined for over-represented functional signatures. RESULTS: We found 22 genes with considerable EV differences between donor groups, of which 11 genes were associated with response to ionizing radiation, stress, and DNA repair. The largest number of genes exclusive to one donor group and variability classification combination were all detected in N0: hypo-variable genes after 0 Gray (n = 49), 0.05 Gray (n = 41), and 2 Gray (n = 38), as well as hyper-variable genes after any dose (n = 43). While after 2 Gray positive regulation of cell cycle was hypo-variable in N0, (regulation of) fibroblast proliferation was over-represented in hyper-variable genes of N1 and N2+. In N2+, 30 genes were uniquely classified as hyper-variable after the low dose and were associated with the ERK1/ERK2 cascade. For N1, no exclusive gene sets with functions related to the radiation response were detected in our data. CONCLUSION: N2+ showed high degrees of variability in pathways for the cell fate decision after genotoxic insults that may lead to the transfer and multiplication of DNA-damage via proliferation, where apoptosis and removal of the damaged genome would have been appropriate. Such a deficiency could potentially lead to a higher vulnerability towards side effects of exposure to high doses of ionizing radiation, but following low-dose applications employed in diagnostics, as well.

Orchestrating single-cell analysis with Bioconductor.

Recent technological advancements have enabled the profiling of a large number of genome-wide features in individual cells. However, single-cell data present unique challenges that require the development of specialized methods and software infrastructure to successfully derive biological insights. The Bioconductor project has rapidly grown to meet these demands, hosting community-developed open-source software distributed as R packages. Featuring state-of-the-art computational methods, standardized data infrastructure and interactive data visualization tools, we present an overview and online book (https://osca.bioconductor.org) of single-cell methods for prospective users.

Publisher Correction: Orchestrating single-cell analysis with Bioconductor.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

SimBu: bias-aware simulation of bulk RNA-seq data with variable cell-type composition.

MOTIVATION: As complex tissues are typically composed of various cell types, deconvolution tools have been developed to computationally infer their cellular composition from bulk RNA sequencing (RNA-seq) data. To comprehensively assess deconvolution performance, gold-standard datasets are indispensable. Gold-standard, experimental techniques like flow cytometry or immunohistochemistry are resource-intensive and cannot be systematically applied to the numerous cell types and tissues profiled with high-throughput transcriptomics. The simulation of 'pseudo-bulk' data, generated by aggregating single-cell RNA-seq expression profiles in pre-defined proportions, offers a scalable and cost-effective alternative. This makes it feasible to create in silico gold standards that allow fine-grained control of cell-type fractions not conceivable in an experimental setup. However, at present, no simulation software for generating pseudo-bulk RNA-seq data exists. RESULTS: We developed SimBu, an R package capable of simulating pseudo-bulk samples based on various simulation scenarios, designed to test specific features of deconvolution methods. A unique feature of SimBu is the modeling of cell-type-specific mRNA bias using experimentally derived or data-driven scaling factors. Here, we show that SimBu can generate realistic pseudo-bulk data, recapitulating the biological and statistical features of real RNA-seq data. Finally, we illustrate the impact of mRNA bias on the evaluation of deconvolution tools and provide recommendations for the selection of suitable methods for estimating mRNA content. SimBu is a user-friendly and flexible tool for simulating realistic pseudo-bulk RNA-seq datasets serving as in silico gold-standard for assessing cell-type deconvolution methods. AVAILABILITY AND IMPLEMENTATION: SimBu is freely available at https://github.com/omnideconv/SimBu as an R package under the GPL-3 license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Ten simple rules to host an inclusive conference.

Conferences are spaces to meet and network within and across academic and technical fields, learn about new advances, and share our work. They can help define career paths and create long-lasting collaborations and opportunities. However, these opportunities are not equal for all. This article introduces 10 simple rules to host an inclusive conference based on the authors' recent experience organizing the 2021 edition of the useR! statistical computing conference, which attracted a broad range of participants from academia, industry, government, and the nonprofit sector. Coming from different backgrounds, career stages, and even continents, we embraced the challenge of organizing a high-quality virtual conference in the context of the Coronavirus Disease 2019 (COVID-19) pandemic and making it a kind, inclusive, and accessible experience for as many people as possible. The rules result from our lessons learned before, during, and after the organization of the conference. They have been written mainly for potential organizers and selection committees of conferences and contain multiple practical tips to help a variety of events become more accessible and inclusive. We see this as a starting point for conversations and efforts towards building more inclusive conferences across the world. * Translated versions of the English abstract and the list of rules are available in 10 languages in S1 Text: Arabic, French, German, Italian, Japanese, Korean, Portuguese, Spanish, Tamil, and Thai.

Discrimination of Robusta Amazônico coffee farmed by indigenous and non-indigenous people in Amazon: comparing benchtop and portable NIR using ComDim and duplex.

Robusta Amazônico is the name given to the Amazonian coffee that has been becoming popular and has recently been registered as a geographical indication in Brazil. It is produced by indigenous and non-indigenous coffee producers in regions that are geographically very close to one another. There is a need to authenticate whether coffee is truly produced by indigenous people and near-infrared (NIR) spectroscopy is an excellent technique for this. To meet the substantial trend towards NIR spectroscopy miniaturization, this work compared benchtop and portable NIR instruments to discriminate Robusta Amazônico samples using partial least squares discriminant analysis (PLS-DA). To ensure the results to be fairly comparable and, at the same time, to guarantee representative selection of both training and test set for the discriminant analysis, a sample selection strategy based on coupling ComDim multi-block analysis and the duplex algorithm was applied. Different pre-processing techniques were tested to create multiple matrices to be used in ComDim, as well as to build the discriminant models. The best PLS-DA model for benchtop NIR provided an accuracy of 96% for the test samples, while for the portable NIR the correct classification rate was 92%. It was demonstrated that portable NIR provides similar results to benchtop NIR for coffee origin classification by performing an unbiased sample selection strategy.

TREND-DB-a transcriptome-wide atlas of the dynamic landscape of alternative polyadenylation.

Alternative polyadenylation (APA) profoundly expands the transcriptome complexity. Perturbations of APA can disrupt biological processes, ultimately resulting in devastating disorders. A major challenge in identifying mechanisms and consequences of APA (and its perturbations) lies in the complexity of RNA 3' end processing, involving poorly conserved RNA motifs and multi-component complexes consisting of far more than 50 proteins. This is further complicated in that RNA 3' end maturation is closely linked to transcription, RNA processing and even epigenetic (histone/DNA/RNA) modifications. Here, we present TREND-DB (http://shiny.imbei.uni-mainz.de:3838/trend-db), a resource cataloging the dynamic landscape of APA after depletion of >170 proteins involved in various facets of transcriptional, co- and post-transcriptional gene regulation, epigenetic modifications and further processes. TREND-DB visualizes the dynamics of transcriptome 3' end diversification (TREND) in a highly interactive manner; it provides a global APA network map and allows interrogating genes affected by specific APA-regulators and vice versa. It also permits condition-specific functional enrichment analyses of APA-affected genes, which suggest wide biological and clinical relevance across all RNAi conditions. The implementation of the UCSC Genome Browser provides additional customizable layers of gene regulation accounting for individual transcript isoforms (e.g. epigenetics, miRNA-binding sites and RNA-binding proteins). TREND-DB thereby fosters disentangling the role of APA for various biological programs, including potential disease mechanisms, and helps identify their diagnostic and therapeutic potential.

Effects of l-Arginine Plus Vitamin C Supplementation on l-Arginine Metabolism in Adults with Long COVID: Secondary Analysis of a Randomized Clinical Trial.

Altered l-arginine metabolism has been described in patients with COVID-19 and has been associated with immune and vascular dysfunction. In the present investigation, we determined the serum concentrations of l-arginine, citrulline, ornithine, monomethyl-l-arginine (MMA), and symmetric and asymmetric dimethylarginine (SDMA, ADMA) in adults with long COVID at baseline and after 28-days of l-arginine plus vitamin C or placebo supplementation enrolled in a randomized clinical trial, compared with a group of adults without previous history of SARS-CoV-2-infection. l-arginine-derived markers of nitric oxide (NO) bioavailability (i.e., l-arginine/ADMA, l-arginine/citrulline+ornithine, and l-arginine/ornithine) were also assayed. Partial least squares discriminant analysis (PLS-DA) models were built to characterize systemic l-arginine metabolism and assess the effects of the supplementation. PLS-DA allowed discrimination of participants with long COVID from healthy controls with 80.2 ± 3.0% accuracy. Lower markers of NO bioavailability were found in participants with long COVID. After 28 days of l-arginine plus vitamin C supplementation, serum l-arginine concentrations and l-arginine/ADMA increased significantly compared with placebo. This supplement may therefore be proposed as a remedy to increase NO bioavailability in people with long COVID.

The Effect of Plastic-Related Compounds on Transcriptome-Wide Gene Expression on CYP2C19-Overexpressing HepG2 Cells.

In recent years, plastic and especially microplastic in the oceans have caused huge problems to marine flora and fauna. Recently, such particles have also been detected in blood, breast milk, and placenta, underlining their ability to enter the human body, presumably via the food chain and other yet-unknown mechanisms. In addition, plastic contains plasticizers, antioxidants, or lubricants, whose impact on human health is also under investigation. At the cellular level, the most important enzymes involved in the metabolism of xenobiotic compounds are the cytochrome P450 monooxygenases (CYPs). Despite their extensive characterization in the maintenance of cellular balance, their interactions with plastic and related products are unexplored. In this study, the possible interactions between several plastic-related compounds and one of the most important cytochromes, CYP2C19, were analyzed. By applying virtual compound screening and molecular docking to more than 1000 commercially available plastic-related compounds, we identified candidates that are likely to interact with this protein. A growth inhibition assay confirmed their cytotoxic activity on a CYP2C19-transfected hepatic cell line. Subsequently, we studied the effect of the selected compounds on the transcriptome-wide gene expression level by conducting RNA sequencing. Three candidate molecules were identified, i.e., 2,2'-methylene bis(6-tert-butyl-4-methylphenol), 1,1-bis(3,5-di-tert-butyl-2-hydroxyphenyl) ethane, and 2,2'-methylene bis(6-cyclohexyl-4-methylphenol)), which bound with a high affinity to CYP2C19 in silico. They exerted a profound cytotoxicity in vitro and interacted with several metabolic pathways, of which the 'cholesterol biosynthesis process' was the most affected. In addition, other affected pathways involved mitosis, DNA replication, and inflammation, suggesting an increase in hepatotoxicity. These results indicate that plastic-related compounds could damage the liver by affecting several molecular pathways.

Multiplexing the Quantitation of MAP Kinase Activities Using Differential Sensing.

Protein kinases are therapeutic targets for many human diseases, but the lack of user-friendly quantitative assays limits the ability to follow the activities of numerous kinases at once (multiplexing). To develop such an assay, we report an array of sulfonamido-oxine (SOX)-labeled peptides showing cross-reactivity to different mitogen-activated protein kinases (MAPKs) for use in a differential sensing scheme. We first verified using linear discriminant analysis that the array could differentiate MAPK isoforms. Then, using principal component analysis, the array was optimized based on the discrimination imparted by each SOX-peptide. Next, the activity of individual MAPK families in ternary mixtures was quantified by support vector machine regression. Finally, we multiplexed the quantification of three MAPK families using partial least squares regression in A549 cell lysates, which has possible interference from other kinase classes. Thus, our method simultaneously quantifies the activity of multiple kinases. The technique could be applied to other protein kinase families and the monitoring of diseases.

Radiation-response in primary fibroblasts of long-term survivors of childhood cancer with and without second primary neoplasms: the KiKme study.

BACKGROUND: The etiology and most risk factors for a sporadic first primary neoplasm in childhood or subsequent second primary neoplasms are still unknown. One established causal factor for therapy-associated second primary neoplasms is the exposure to ionizing radiation during radiation therapy as a mainstay of cancer treatment. Second primary neoplasms occur in 8% of all cancer survivors within 30 years after the first diagnosis in Germany, but the underlying factors for intrinsic susceptibilities have not yet been clarified. Thus, the purpose of this nested case-control study was the investigation and comparison of gene expression and affected pathways in primary fibroblasts of childhood cancer survivors with a first primary neoplasm only or with at least one subsequent second primary neoplasm, and controls without neoplasms after exposure to a low and a high dose of ionizing radiation. METHODS: Primary fibroblasts were obtained from skin biopsies from 52 adult donors with a first primary neoplasm in childhood (N1), 52 with at least one additional primary neoplasm (N2+), as well as 52 without cancer (N0) from the KiKme study. Cultured fibroblasts were exposed to a high [2 Gray (Gy)] and a low dose (0.05 Gy) of X-rays. Messenger ribonucleic acid was extracted 4 h after exposure and Illumina-sequenced. Differentially expressed genes (DEGs) were computed using limma for R, selected at a false discovery rate level of 0.05, and further analyzed for pathway enrichment (right-tailed Fisher's Exact Test) and (in-) activation (z ≥|2|) using Ingenuity Pathway Analysis. RESULTS: After 0.05 Gy, least DEGs were found in N0 (n = 236), compared to N1 (n = 653) and N2+ (n = 694). The top DEGs with regard to the adjusted p-value were upregulated in fibroblasts across all donor groups (SESN1, MDM2, CDKN1A, TIGAR, BTG2, BLOC1S2, PPM1D, PHLDB3, FBXO22, AEN, TRIAP1, and POLH). Here, we observed activation of p53 Signaling in N0 and to a lesser extent in N1, but not in N2+. Only in N0, DNA (excision-) repair (involved genes: CDKN1A, PPM1D, and DDB2) was predicted to be a downstream function, while molecular networks in N2+ were associated with cancer, as well as injury and abnormalities (among others, downregulation of MSH6, CCNE2, and CHUK). After 2 Gy, the number of DEGs was similar in fibroblasts of all donor groups and genes with the highest absolute log2 fold-change were upregulated throughout (CDKN1A, TIGAR, HSPA4L, MDM2, BLOC1SD2, PPM1D, SESN1, BTG2, FBXO22, PCNA, and TRIAP1). Here, the p53 Signaling-Pathway was activated in fibroblasts of all donor groups. The Mitotic Roles of Polo Like Kinase-Pathway was inactivated in N1 and N2+. Molecular Mechanisms of Cancer were affected in fibroblasts of all donor groups. P53 was predicted to be an upstream regulator in fibroblasts of all donor groups and E2F1 in N1 and N2+. Results of the downstream analysis were senescence in N0 and N2+, transformation of cells in N0, and no significant effects in N1. Seven genes were differentially expressed in reaction to 2 Gy dependent on the donor group (LINC00601, COBLL1, SESN2, BIN3, TNFRSF10A, EEF1AKNMT, and BTG2). CONCLUSION: Our results show dose-dependent differences in the radiation response between N1/N2+ and N0. While mechanisms against genotoxic stress were activated to the same extent after a high dose in all groups, the radiation response was impaired after a low dose in N1/N2+, suggesting an increased risk for adverse effects including carcinogenesis, particularly in N2+.

Magnetique: an interactive web application to explore transcriptome signatures of heart failure.

BACKGROUND: Despite a recent increase in the number of RNA-seq datasets investigating heart failure (HF), accessibility and usability remain critical issues for medical researchers. We address the need for an intuitive and interactive web application to explore the transcriptional signatures of heart failure with this work. METHODS: We reanalysed the Myocardial Applied Genomics Network RNA-seq dataset, one of the largest publicly available datasets of left ventricular RNA-seq samples from patients with dilated (DCM) or hypertrophic (HCM) cardiomyopathy, as well as unmatched non-failing hearts (NFD) from organ donors and patient characteristics that allowed us to model confounding factors. We analyse differential gene expression, associated pathway signatures and reconstruct signaling networks based on inferred transcription factor activities through integer linear programming. We additionally focus, for the first time, on differential RNA transcript isoform usage (DTU) changes and predict RNA-binding protein (RBP) to target transcript interactions using a Global test approach. We report results for all pairwise comparisons (DCM, HCM, NFD). RESULTS: Focusing on the DCM versus HCM contrast (DCMvsHCM), we identified 201 differentially expressed genes, some of which can be clearly associated with changes in ERK1 and ERK2 signaling. Interestingly, the signs of the predicted activity for these two kinases have been inferred to be opposite to each other: In the DCMvsHCM contrast, we predict ERK1 to be consistently less activated in DCM while ERK2 was more activated in DCM. In the DCMvsHCM contrast, we identified 149 differently used transcripts. One of the top candidates is the O-linked N-acetylglucosamine (GlcNAc) transferase (OGT), which catalyzes a common post-translational modification known for its role in heart arrhythmias and heart hypertrophy. Moreover, we reconstruct RBP - target interaction networks and showcase the examples of CPEB1, which is differentially expressed in the DCMvsHCM contrast. CONCLUSION: Magnetique ( https://shiny.dieterichlab.org/app/magnetique ) is the first online application to provide an interactive view of the HF transcriptome at the RNA isoform level and to include transcription factor signaling and RBP:RNA interaction networks. The source code for both the analyses ( https://github.com/dieterich-lab/magnetiqueCode2022 ) and the web application ( https://github.com/AnnekathrinSilvia/magnetique ) is available to the public. We hope that our application will help users to uncover the molecular basis of heart failure.