79 research outputs found

    The Crystal Structure of PPIL1 Bound to Cyclosporine A Suggests a Binding Mode for a Linear Epitope of the SKIP Protein

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    BACKGROUND: The removal of introns from pre-mRNA is carried out by a large macromolecular machine called the spliceosome. The peptidyl-prolyl cis/trans isomerase PPIL1 is a component of the human spliceosome and binds to the spliceosomal SKIP protein via a binding site distinct from its active site. PRINCIPAL FINDINGS: Here, we have studied the PPIL1 protein and its interaction with SKIP biochemically and by X-ray crystallography. A minimal linear binding epitope derived from the SKIP protein could be determined using a peptide array. A 36-residue region of SKIP centred on an eight-residue epitope suffices to bind PPIL1 in pull-down experiments. The crystal structure of PPIL1 in complex with the inhibitor cyclosporine A (CsA) was obtained at a resolution of 1.15 A and exhibited two bound Cd(2+) ions that enabled SAD phasing. PPIL1 residues that have previously been implicated in binding of SKIP are involved in the coordination of Cd(2+) ions in the present crystal structure. Employing the present crystal structure, the determined minimal binding epitope and previously published NMR data, a molecular docking study was performed. In the docked model of the PPIL1.SKIP interaction, a proline residue of SKIP is buried in a hydrophobic pocket of PPIL1. This hydrophobic contact is encircled by several hydrogen bonds between the SKIP peptide and PPIL1. CONCLUSION: We characterized a short, linear epitope of SKIP that is sufficient to bind the PPIL1 protein. Our data indicate that this SKIP peptide could function in recruiting PPIL1 into the core of the spliceosome. We present a molecular model for the binding mode of SKIP to PPIL1 which emphasizes the versatility of cyclophilin-type PPIases to engage in additional interactions with other proteins apart from active site contacts despite their limited surface area

    Transcriptional and Cellular Diversity of the Human Heart

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    Background: The human heart requires a complex ensemble of specialized cell types to perform its essential function. A greater knowledge of the intricate cellular milieu of the heart is critical to increase our understanding of cardiac homeostasis and pathology. As recent advances in low-input RNA sequencing have allowed definitions of cellular transcriptomes at single-cell resolution at scale, we have applied these approaches to assess the cellular and transcriptional diversity of the nonfailing human heart. Methods: Microfluidic encapsulation and barcoding was used to perform single nuclear RNA sequencing with samples from 7 human donors, selected for their absence of overt cardiac disease. Individual nuclear transcriptomes were then clustered based on transcriptional profiles of highly variable genes. These clusters were used as the basis for between-chamber and between-sex differential gene expression analyses and intersection with genetic and pharmacologic data. Results: We sequenced the transcriptomes of 287 269 single cardiac nuclei, revealing 9 major cell types and 20 subclusters of cell types within the human heart. Cellular subclasses include 2 distinct groups of resident macrophages, 4 endothelial subtypes, and 2 fibroblast subsets. Comparisons of cellular transcriptomes by cardiac chamber or sex reveal diversity not only in cardiomyocyte transcriptional programs but also in subtypes involved in extracellular matrix remodeling and vascularization. Using genetic association data, we identified strong enrichment for the role of cell subtypes in cardiac traits and diseases. Intersection of our data set with genes on cardiac clinical testing panels and the druggable genome reveals striking patterns of cellular specificity. Conclusions: Using large-scale single nuclei RNA sequencing, we defined the transcriptional and cellular diversity in the normal human heart. Our identification of discrete cell subtypes and differentially expressed genes within the heart will ultimately facilitate the development of new therapeutics for cardiovascular diseases

    Relations between the milnor and quillen K-theory of fields

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    De novo mutations in specific mTOR pathway genes cause brain overgrowth in the context of intellectual disability (ID). By analyzing 101 mMTOR-related genes in a large ID patient cohort and two independent population cohorts, we show that these genes modulate brain growth in health and disease. We report the mTOR activator gene RHEB as an ID gene that is associated with megalencephaly when mutated. Functional testing of mutant RHEB in vertebrate animal models indicates pathway hyperactivation with a concomitant increase in cell and head size, aberrant neuronal migration, and induction of seizures, concordant with the human phenotype. This study reveals that tight control of brain volume is exerted through a large community of mTOR-related genes. Human brain volume can be altered, by either rare disruptive events causing hyperactivation of the pathway, or through the collective effects of common alleles

    TRAIL receptor I (DR4) polymorphisms C626G and A683C are associated with an increased risk for hepatocellular carcinoma (HCC) in HCV-infected patients

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    <p>Abstract</p> <p>Background</p> <p>Tumour surveillance via induction of TRAIL-mediated apoptosis is a key mechanism, how the immune system prevents malignancy. To determine if gene variants in the TRAIL receptor I (<it>DR4</it>) gene affect the risk of hepatitis C virus (HCV)-induced liver cancer (HCC), we analysed <it>DR4 </it>mutations C626G (rs20575) and A683C (rs20576) in HCV-infected patients with and without HCC.</p> <p>Methods</p> <p>Frequencies of <it>DR4 </it>gene polymorphisms were determined by LightSNiP assays in 159 and 234 HCV-infected patients with HCC and without HCC, respectively. 359 healthy controls served as reference population.</p> <p>Results</p> <p>Distribution of C626G and A683C genotypes were not significantly different between healthy controls and HCV-positive patients without HCC. <it>DR4 </it>variants 626C and 683A occurred at increased frequencies in patients with HCC. The risk of HCC was linked to carriage of the 626C allele and the homozygous 683AA genotype, and the simultaneous presence of the two risk variants was confirmed as independent HCC risk factor by Cox regression analysis (Odds ratio 1.975, 95% CI 1.205-3.236; p = 0.007). Furthermore HCV viral loads were significantly increased in patients who simultaneously carried both genetic risk factors (2.69 ± 0.36 × 10<sup>6</sup> IU/ml vs. 1.81 ± 0.23 × 10<sup>6</sup> IU/ml, p = 0.049).</p> <p>Conclusions</p> <p>The increased prevalence of patients with a 626C allele and the homozygous 683AA genotype in HCV-infected patients with HCC suggests that these genetic variants are a risk factor for HCC in chronic hepatitis C.</p

    Deep learning enables genetic analysis of the human thoracic aorta

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    Genome-wide association analyses identify variants associated with thoracic aortic diameter. A polygenic score for ascending aortic diameter was associated with a diagnosis of thoracic aortic aneurysm in independent samples. Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, identifying 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests and human aortic single nucleus RNA sequencing prioritized genes including SVIL, which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (hazard ratio = 1.43 per s.d., confidence interval 1.32-1.54, P = 3.3 x 10(-20)). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images

    Quantification in cardiac MRI: advances in image acquisition and processing

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    Cardiac magnetic resonance (CMR) imaging enables accurate and reproducible quantification of measurements of global and regional ventricular function, blood flow, perfusion at rest and stress as well as myocardial injury. Recent advances in MR hardware and software have resulted in significant improvements in image quality and a reduction in imaging time. Methods for automated and robust assessment of the parameters of cardiac function, blood flow and morphology are being developed. This article reviews the recent advances in image acquisition and quantitative image analysis in CMR

    The Arabidopsis leucine-rich repeat receptor kinase MIK2/LRR-KISS connects cell wall integrity sensing, root growth and response to abiotic and biotic stresses

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    Plants actively perceive and respond to perturbations in their cell walls which arise during growth, biotic and abiotic stresses. However, few components involved in plant cell wall integrity sensing have been described to date. Using a reverse-genetic approach, we identified the Arabidopsis thaliana leucine-rich repeat receptor kinase MIK2 as an important regulator of cell wall damage responses triggered upon cellulose biosynthesis inhibition. Indeed, loss-of-function mik2 alleles are strongly affected in immune marker gene expression, jasmonic acid production and lignin deposition. MIK2 has both overlapping and distinct functions with THE1, a malectin-like receptor kinase previously proposed as cell wall integrity sensor. In addition, mik2 mutant plants exhibit enhanced leftward root skewing when grown on vertical plates. Notably, natural variation in MIK2 (also named LRR-KISS) has been correlated recently to mild salt stress tolerance, which we could confirm using our insertional alleles. Strikingly, both the increased root skewing and salt stress sensitivity phenotypes observed in the mik2 mutant are dependent on THE1. Finally, we found that MIK2 is required for resistance to the fungal root pathogen Fusarium oxysporum. Together, our data identify MIK2 as a novel component in cell wall integrity sensing and suggest that MIK2 is a nexus linking cell wall integrity sensing to growth and environmental cues

    CERT1 mutations perturb human development by disrupting sphingolipid homeostasis

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    Neural differentiation, synaptic transmission, and action potential propagation depend on membrane sphingolipids, whose metabolism is tightly regulated. Mutations in the ceramide transporter CERT (CERT1), which is involved in sphingolipid biosynthesis, are associated with intellectual disability, but the pathogenic mechanism remains obscure. Here, we characterize 31 individuals with de novo missense variants in CERT1. Several variants fall into a previously uncharacterized dimeric helical domain that enables CERT homeostatic inactivation, without which sphingolipid production goes unchecked. The clinical severity reflects the degree to which CERT autoregulation is disrupted, and inhibiting CERT pharmacologically corrects morphological and motor abnormalities in a Drosophila model of the disease, which we call ceramide transporter (CerTra) syndrome. These findings uncover a central role for CERT autoregulation in the control of sphingolipid biosynthetic flux, provide unexpected insight into the structural organization of CERT, and suggest a possible therapeutic approach for patients with CerTra syndrome.This work was supported by the National Institute of Neurological Disorders and Stroke (NINDS), NIH (R01NS109858, to VAG); the Paul A. Marks Scholar Program at the Columbia University Vagelos College of Physicians and Surgeons (to VAG); a TIGER grant from the TAUB Institute at the Columbia Vagelos College of Physicians and Scientists (to VAG); the Swiss National Science Foundation (SNF 31003A-179371, to TH); the European Joint Program on Rare Diseases (EJP RD+SNF 32ER30-187505, to TH); the Swiss Cancer League (KFS-4999-02-2020, to GD); the EPFL institutional fund (to GD); the Kristian Gerhard Jebsen Foundation (to GD); the Swiss National Science Foundation (SNSF) (310030_184926, to GD); the Swiss Foundation for Research on Muscle Disease (FSRMM, to MAL); the Natural Science and Engineering Research Council of Canada (Discovery Grant 2020-04241, to JEB); the Italian Ministry of Health Young Investigator Grant (GR-2011-02347754, to EL); the Fondazione Istituto di Ricerca Pediatrica – Città della Speranza (18-04, to EL); the Wroclaw Medical University (SUB.E160.21.004, to RS); the National Science Centre, Poland (2017/27/B/NZ5/0222, to RS); Telethon Undiagnosed Diseases Program (TUDP) (GSP15001); the Temple Street Foundation/Children’s Health Foundation Ireland (RPAC 19-02, to IK); the Deutsche Forschungsgemeinschaft (DFG) (PO2366/2–1, to BP); the Instituto de Salud Carlos III, Spain (to ELM, EBS, and BMD); the National Natural Science Foundation of China (81871079 and 81730036, to HG and KX); and the National Institutes of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH (R01 DK115574, to SSC).The DEFIDIAG study is funded by grants from the French Ministry of Health in the framewok of the national French initiative for genomic medicine. The funders were not involved in the study design, data acquisition, analysis, or writing of the manuscript. Funding for the DECIPHER project was provided by Wellcome. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between Wellcome and the Department of Health, and the Wellcome Sanger Institute (grant number WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of Wellcome or the Department of Health. The study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South REC, and GEN/284/12, granted by the Republic of Ireland REC). The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network.S

    Missense variants in ANKRD11 cause KBG syndrome by impairment of stability or transcriptional activity of the encoded protein

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    Purpose Although haploinsufficiency of ANKRD11 is among the most common genetic causes of neurodevelopmental disorders, the role of rare ANKRD11 missense variation remains unclear. We characterized clinical, molecular, and functional spectra of ANKRD11 missense variants. Methods We collected clinical information of individuals with ANKRD11 missense variants and evaluated phenotypic fit to KBG syndrome. We assessed pathogenicity of variants through in silico analyses and cell-based experiments. Results We identified 20 unique, mostly de novo, ANKRD11 missense variants in 29 individuals, presenting with syndromic neurodevelopmental disorders similar to KBG syndrome caused by ANKRD11 protein truncating variants or 16q24.3 microdeletions. Missense variants significantly clustered in repression domain 2 at the ANKRD11 C-terminus. Of the 10 functionally studied missense variants, 6 reduced ANKRD11 stability. One variant caused decreased proteasome degradation and loss of ANKRD11 transcriptional activity. Conclusion Our study indicates that pathogenic heterozygous ANKRD11 missense variants cause the clinically recognizable KBG syndrome. Disrupted transrepression capacity and reduced protein stability each independently lead to ANKRD11 loss-of-function, consistent with haploinsufficiency. This highlights the diagnostic relevance of ANKRD11 missense variants, but also poses diagnostic challenges because the KBG-associated phenotype may be mild and inherited pathogenic ANKRD11 (missense) variants are increasingly observed, warranting stringent variant classification and careful phenotyping
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