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SUMOylation is a reversible posttranslational modification pathway catalyzing the conjugation of small ubiquitin-related modifier (SUMO) proteins to lysine residues of distinct target proteins. SUMOylation modifies a wide variety of cellular regulators thereby affecting a multitude of key processes in a highly dynamic manner. The SUMOylation pathway displays a hallmark in cellular stress-adaption, such as heat or redox stress. It has been proposed that enhanced cellular SUMOylation protects the brain during ischemia, however, little is known about the specific regulation of the SUMO system and the potential target proteins during cardiac ischemia and reperfusion injury (I/R). By applying left anterior descending (LAD) coronary artery ligation and reperfusion in mice, we detect dynamic changes in the overall cellular SUMOylation pattern correlating with decreased SUMO deconjugase activity during I/R injury. Further, unbiased system-wide quantitative SUMO-proteomics identified a sub-group of SUMO targets exhibiting significant alterations in response to cardiac I/R. Notably, transcription factors that control hypoxia- and angiogenesis-related gene expression programs, exhibit altered SUMOylation during ischemic stress adaptation. Moreover, several components of the ubiquitin proteasome system undergo dynamic changes in SUMO conjugation during cardiac I/R suggesting an involvement of SUMO signaling in protein quality control and proteostasis in the ischemic heart. Altogether, our study reveals regulated candidate SUMO target proteins in the mouse heart, which might be important in coping with hypoxic/proteotoxic stress during cardiac I/R injury.
Individual adult ventricular cardiomyocytes are either mono- or multi-nucleated and undergo morphological changes during cardiac hypertrophy. However, corresponding transcriptional signatures, reflecting potentially different functions or the ability for cell-cycle entry, are not known. The aim of this study was to determine the transcriptional profile of mono- and multi-nucleated adult cardiomyocytes by single-cell RNA-sequencing (scRNA-seq) and to investigate heterogeneity among cardiomyocytes under baseline conditions and in pressure-induced cardiac hypertrophy. We developed an array-based approach for scRNA-seq of rod-shaped multi-nucleated cardiomyocytes from both healthy and hypertrophic hearts. Single-cell transcriptomes of mono- or multi-nucleated cardiomyocytes were highly similar, although a certain degree of variation was noted across both populations. Non-image-based quality control allowing inclusion of damaged cardiomyocytes generated artificial cell clusters demonstrating the need for strict exclusion criteria. In contrast, cardiomyocytes isolated from hypertrophic heart after transverse aortic constriction showed heterogeneous transcriptional signatures, characteristic for hypoxia-induced responses. Immunofluorescence analysis revealed an inverse correlation between HIF1α+ cells and CD31-stained vessels, suggesting that imbalanced vascular growth in the hypertrophied heart induces cellular heterogeneity. Our study demonstrates that individual mono- and multi-nucleated cardiomyocytes express nearly identical sets of genes. Homogeneity among cardiomyocytes was lost after induction of hypertrophy due to differential HIF1α-dependent responses most likely caused by none-homogenous vessel growth.
In the current study we compared the molecular signature of expanded mesenchymal stromal cells (MSCs) derived from selected CD271+ bone marrow mononuclear cells (CD271-MSCs) and MSCs derived from non-selected bone marrow mononuclear cells by plastic adherence (PA-MSCs). Transcriptome analysis demonstrated for the first time the upregulation of 115 and downregulation of 131 genes in CD271-MSCs. Functional enrichment analysis showed that the upregulated genes in CD271-MSCs are significantly enriched for extracellular matrix (tenascin XB, elastin, ABI family, member 3 (NESH) binding protein, carboxypeptidase Z, laminin alpha 2 and nephroblastoma overexpressed) and cell adhesion (CXCR7, GPNMB, MYBPH, SVEP1, ARHGAP6, TSPEAR, PIK3CG, ABL2 and NCAM1). CD271-MSCs expressed higher gene transcript levels that are involved in early osteogenesis/chondrogenesis/adipogenesis (ZNF145, FKBP5). In addition, increased transcript levels for early and late osteogenesis (DPT, OMD, ID4, CRYAB, SORT1), adipogenesis (CTNNB1, ZEB, LPL, FABP4, PDK4, ACDC), and chondrogenesis (CCN3/NOV, CCN4/WISP1, CCN5/WISP2 and ADAMTS-5) were detected. Interestingly, CD271-MSCs expressed increased levels of hematopoiesis associated genes (CXCL12, FLT3L, IL-3, TPO, KITL). Down-regulated genes in CD271-MSCs were associated with WNT and TGF-beta signaling, and cytokine/chemokine signaling pathways. In addition to their capacity to support hematopoiesis, these results suggest that CD271-MSCs may contain more osteo/chondro progenitors and/or feature a greater differentiation potential.
Introns of human transfer RNA precursors (pre-tRNAs) are excised by the tRNA splicing endonuclease TSEN in complex with the RNA kinase CLP1. Mutations in TSEN/CLP1 occur in patients with pontocerebellar hypoplasia (PCH), however, their role in the disease is unclear. Here, we show that intron excision is catalyzed by tetrameric TSEN assembled from inactive heterodimers independently of CLP1. Splice site recognition involves the mature domain and the anticodon-intron base pair of pre-tRNAs. The 2.1-Å resolution X-ray crystal structure of a TSEN15–34 heterodimer and differential scanning fluorimetry analyses show that PCH mutations cause thermal destabilization. While endonuclease activity in recombinant mutant TSEN is unaltered, we observe assembly defects and reduced pre-tRNA cleavage activity resulting in an imbalanced pre-tRNA pool in PCH patient-derived fibroblasts. Our work defines the molecular principles of intron excision in humans and provides evidence that modulation of TSEN stability may contribute to PCH phenotypes.
Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
Aims: Patients with cardiovascular comorbidities have a significantly increased risk for a critical course of COVID-19. As the SARS-CoV2 virus enters cells via the angiotensin-converting enzyme receptor II (ACE2), drugs which interact with the renin angiotensin aldosterone system (RAAS) were suspected to influence disease severity.
Methods and results: We analyzed 1946 consecutive patients with cardiovascular comorbidities or hypertension enrolled in one of the largest European COVID-19 registries, the Lean European Open Survey on SARS-CoV-2 (LEOSS) registry. Here, we show that angiotensin II receptor blocker intake is associated with decreased mortality in patients with COVID-19 [OR 0.75 (95% CI 0,59–0.96; p = 0.013)]. This effect was mainly driven by patients, who presented in an early phase of COVID-19 at baseline [OR 0,64 (95% CI 0,43–0,96; p = 0.029)]. Kaplan-Meier analysis revealed a significantly lower incidence of death in patients on an angiotensin receptor blocker (ARB) (n = 33/318;10,4%) compared to patients using an angiotensin-converting enzyme inhibitor (ACEi) (n = 60/348;17,2%) or patients who received neither an ACE-inhibitor nor an ARB at baseline in the uncomplicated phase (n = 90/466; 19,3%; p<0.034). Patients taking an ARB were significantly less frequently reaching the mortality predicting threshold for leukocytes (p<0.001), neutrophils (p = 0.002) and the inflammatory markers CRP (p = 0.021), procalcitonin (p = 0.001) and IL-6 (p = 0.049). ACE2 expression levels in human lung samples were not altered in patients taking RAAS modulators.
Conclusion: These data suggest a beneficial effect of ARBs on disease severity in patients with cardiovascular comorbidities and COVID-19, which is linked to dampened systemic inflammatory activity.
Formation and segregation of cell lineages forming the heart have been studied extensively but the underlying gene regulatory networks and epigenetic changes driving cell fate transitions during early cardiogenesis are still only partially understood. Here, we comprehensively characterize mouse cardiac progenitor cells (CPCs) marked by Nkx2-5 and Isl1 expression from E7.5 to E9.5 using single-cell RNA sequencing and transposase-accessible chromatin profiling (ATAC-seq). By leveraging on cell-to-cell transcriptome and chromatin accessibility heterogeneity, we identify different previously unknown cardiac subpopulations. Reconstruction of developmental trajectories reveal that multipotent Isl1+ CPC pass through an attractor state before separating into different developmental branches, whereas extended expression of Nkx2-5 commits CPC to an unidirectional cardiomyocyte fate. Furthermore, we show that CPC fate transitions are associated with distinct open chromatin states critically depending on Isl1 and Nkx2-5. Our data provide a model of transcriptional and epigenetic regulations during cardiac progenitor cell fate decisions at single-cell resolution.
Profiles of CFC-11 (CCl3F) and CFC-12 (CCl2F2) of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard the European satellite Envisat have been retrieved from versions MIPAS/4.61 to MIPAS/4.62 and MIPAS/5.02 to MIPAS/5.06 level-1b data using the scientific level-2 processor run by Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK) and Consejo Superior de Investigaciones Científicas (CSIC), Instituto de Astrofísica de Andalucía (IAA). These profiles have been compared to measurements taken by the balloon-borne cryosampler, Mark IV (MkIV) and MIPAS-Balloon (MIPAS-B), the airborne MIPAS-STRatospheric aircraft (MIPAS-STR), the satellite-borne Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) and the High Resolution Dynamic Limb Sounder (HIRDLS), as well as the ground-based Halocarbon and other Atmospheric Trace Species (HATS) network for the reduced spectral resolution period (RR: January 2005–April 2012) of MIPAS. ACE-FTS, MkIV and HATS also provide measurements during the high spectral resolution period (full resolution, FR: July 2002–March 2004) and were used to validate MIPAS CFC-11 and CFC-12 products during that time, as well as profiles from the Improved Limb Atmospheric Spectrometer, ILAS-II. In general, we find that MIPAS shows slightly higher values for CFC-11 at the lower end of the profiles (below ∼ 15 km) and in a comparison of HATS ground-based data and MIPAS measurements at 3 km below the tropopause. Differences range from approximately 10 to 50 pptv ( ∼ 5–20 %) during the RR period. In general, differences are slightly smaller for the FR period. An indication of a slight high bias at the lower end of the profile exists for CFC-12 as well, but this bias is far less pronounced than for CFC-11 and is not as obvious in the relative differences between MIPAS and any of the comparison instruments. Differences at the lower end of the profile (below ∼ 15 km) and in the comparison of HATS and MIPAS measurements taken at 3 km below the tropopause mainly stay within 10–50 pptv (corresponding to ∼ 2–10 % for CFC-12) for the RR and the FR period. Between ∼ 15 and 30 km, most comparisons agree within 10–20 pptv (10–20 %), apart from ILAS-II, which shows large differences above ∼ 17 km. Overall, relative differences are usually smaller for CFC-12 than for CFC-11. For both species – CFC-11 and CFC-12 – we find that differences at the lower end of the profile tend to be larger at higher latitudes than in tropical and subtropical regions. In addition, MIPAS profiles have a maximum in their mixing ratio around the tropopause, which is most obvious in tropical mean profiles. Comparisons of the standard deviation in a quiescent atmosphere (polar summer) show that only the CFC-12 FR error budget can fully explain the observed variability, while for the other products (CFC-11 FR and RR and CFC-12 RR) only two-thirds to three-quarters can be explained. Investigations regarding the temporal stability show very small negative drifts in MIPAS CFC-11 measurements. These instrument drifts vary between ∼ 1 and 3 % decade−1. For CFC-12, the drifts are also negative and close to zero up to ∼ 30 km. Above that altitude, larger drifts of up to ∼ 50 % decade−1 appear which are negative up to ∼ 35 km and positive, but of a similar magnitude, above.
Endocannabinoids are important lipid-signaling mediators. Both protective and deleterious effects of endocannabinoids in the cardiovascular system have been reported but the mechanistic basis for these contradicting observations is unclear. We set out to identify anti-inflammatory mechanisms of endocannabinoids in the murine aorta and in human vascular smooth muscle cells (hVSMC). In response to combined stimulation with cytokines, IL-1β and TNFα, the murine aorta released several endocannabinoids, with anandamide (AEA) levels being the most significantly increased. AEA pretreatment had profound effects on cytokine-induced gene expression in hVSMC and murine aorta. As revealed by RNA-Seq analysis, the induction of a subset of 21 inflammatory target genes, including the important cytokine CCL2 was blocked by AEA. This effect was not mediated through AEA-dependent interference of the AP-1 or NF-κB pathways but rather through an epigenetic mechanism. In the presence of AEA, ATAC-Seq analysis and chromatin-immunoprecipitations revealed that CCL2 induction was blocked due to increased levels of H3K27me3 and a decrease of H3K27ac leading to compacted chromatin structure in the CCL2 promoter. These effects were mediated by recruitment of HDAC4 and the nuclear corepressor NCoR1 to the CCL2 promoter. This study therefore establishes a novel anti-inflammatory mechanism for the endogenous endocannabinoid AEA in vascular smooth muscle cells. Furthermore, this work provides a link between endogenous endocannabinoid signaling and epigenetic regulation.
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.