Desmosomal Molecules In and Out of Adhering Junctions: Normal and Diseased States of Epidermal, Cardiac and Mesenchymally Derived Cells

Current cell biology textbooks mention only two kinds of cell-to-cell adhering junctions coated with the cytoplasmic plaques: the desmosomes (maculae adhaerentes), anchoring intermediate-sized filaments (IFs), and the actin microfilament-anchoring adherens junctions (AJs), including both punctate (puncta adhaerentia) and elongate (fasciae adhaerentes) structures. In addition, however, a series of other junction types has been identified and characterized which contain desmosomal molecules but do not fit the definition of desmosomes. Of these special cell-cell junctions containing desmosomal glycoproteins or proteins we review the composite junctions (areae compositae) connecting the cardiomyocytes of mature mammalian hearts and their importance in relation to human arrhythmogenic cardiomyopathies. We also emphasize the various plakophilin-2-positive plaques in AJs (coniunctiones adhaerentes) connecting proliferatively active mesenchymally-derived cells, including interstitial cells of the heart and several soft tissue tumor cell types. Moreover, desmoplakin has also been recognized as a constituent of the plaques of the complexus adhaerentes connecting certain lymphatic endothelial cells. Finally, we emphasize the occurrence of the desmosomal transmembrane glycoprotein, desmoglein Dsg2, out of the context of any junction as dispersed cell surface molecules in certain types of melanoma cells and melanocytes. This broadening of our knowledge on the diversity of AJ structures indicates that it may still be too premature to close the textbook chapters on cell-cell junctions

Work-Life-Balance in der IT-Unternehmensberatung: (Fortsetzungsbericht zur Studie WoBaFIT)

Die Untersuchungen zeigen, dass eine gute Work-Life-Balance (WLB) in Unternehmensberatungen für die Mitarbeiter einen hohen Stellenwert hat. Ein signifikanter geschlechtsspezifischer Unterschied ist nicht erkennbar. Sowohl Frauen als auch Männer streben aktiv nach einer ausgewogenen WLB. Die Inanspruchnahme von WLB-Maßnahmen kann jedoch nur erfolgen, wenn das konkrete WLB-Maßnahmenangebot des Arbeitgebers den Mitarbeitern hinlänglich bekannt ist. Insbesondere in der mittelständischen Unternehmensberatung XYZ zeigt die Kommunikation des bestehenden WLB-Maßnahmenangebots erhebliche Schwächen. Mehr als die Hälfte der Befragten wusste nichts über den bestehenden WLB-Maßnahmenkatalog von XYZ. Die übrigen Mitarbeiter nutzen die vorhandenen WLB-Maßnahmen rege. Die meisten der Mitarbeiter von XYZ wünschen sich zudem einen Ausbau des derzeitigen WLB-Maßnahmenangebots und haben zahlreiche Erweiterungsvorschläge eingebracht. Besonders interessant sind dabei WLB-Maßnahmen, die eine zeitbezogene Strategie verfolgen und das Verhältnis von Arbeits- zu Freizeit verändern. Zusätzlich gewonnene Zeit kann von den Mitarbeitern individuell auf private Lebensbereiche verteilt werden und bietet somit für jeden den optimalen Nutzen

Immunopeptidomics toolkit library (IPTK): a python-based modular toolbox for analyzing immunopeptidomics data

Background The human leukocyte antigen (HLA) proteins play a fundamental role in the adaptive immune system as they present peptides to T cells. Mass-spectrometry-based immunopeptidomics is a promising and powerful tool for characterizing the immunopeptidomic landscape of HLA proteins, that is the peptides presented on HLA proteins. Despite the growing interest in the technology, and the recent rise of immunopeptidomics-specific identification pipelines, there is still a gap in data-analysis and software tools that are specialized in analyzing and visualizing immunopeptidomics data. Results We present the IPTK library which is an open-source Python-based library for analyzing, visualizing, comparing, and integrating different omics layers with the identified peptides for an in-depth characterization of the immunopeptidome. Using different datasets, we illustrate the ability of the library to enrich the result of the identified peptidomes. Also, we demonstrate the utility of the library in developing other software and tools by developing an easy-to-use dashboard that can be used for the interactive analysis of the results. Conclusion IPTK provides a modular and extendable framework for analyzing and integrating immunopeptidomes with different omics layers. The library is deployed into PyPI at https://pypi.org/project/IPTKL/ and into Bioconda at https://anaconda.org/bioconda/iptkl , while the source code of the library and the dashboard, along with the online tutorials are available at https://github.com/ikmb/iptoolkit

Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction

Human Leukocyte Antigen class II (HLA-II) molecules present peptides to T lymphocytes and play an important role in adaptive immune responses. Characterizing the binding specificity of single HLA-II molecules has profound impacts for understanding cellular immunity, identifying the cause of autoimmune diseases, for immunotherapeutics, and vaccine development. Here, novel high-density peptide microarray technology combined with machine learning techniques were used to address this task at an unprecedented level of high-throughput. Microarrays with over 200,000 defined peptides were assayed with four exemplary HLA-II molecules. Machine learning was applied to mine the signals. The comparison of identified binding motifs, and power for predicting eluted ligands and CD4+ epitope datasets to that obtained using NetMHCIIpan-3.2, confirmed a high quality of the chip readout. These results suggest that the proposed microarray technology offers a novel and unique platform for large-scale unbiased interrogation of peptide binding preferences of HLA-II molecules

A novel unconventional T cell population enriched in Crohn's disease

Objective One of the current hypotheses to explain the proinflammatory immune response in IBD is a dysregulated T cell reaction to yet unknown intestinal antigens. As such, it may be possible to identify disease-associated T cell clonotypes by analysing the peripheral and intestinal T-cell receptor (TCR) repertoire of patients with IBD and controls. Design We performed bulk TCR repertoire profiling of both the TCR alpha and beta chains using high-throughput sequencing in peripheral blood samples of a total of 244 patients with IBD and healthy controls as well as from matched blood and intestinal tissue of 59 patients with IBD and disease controls. We further characterised specific T cell clonotypes via single-cell RNAseq. Results We identified a group of clonotypes, characterised by semi-invariant TCR alpha chains, to be significantly enriched in the blood of patients with Crohn's disease (CD) and particularly expanded in the CD8+ T cell population. Single-cell RNAseq data showed an innate-like phenotype of these cells, with a comparable gene expression to unconventional T cells such as mucosal associated invariant T and natural killer T (NKT) cells, but with distinct TCRs. Conclusions We identified and characterised a subpopulation of unconventional Crohn-associated invariant T (CAIT) cells. Multiple evidence suggests these cells to be part of the NKT type II population. The potential implications of this population for CD or a subset thereof remain to be elucidated, and the immunophenotype and antigen reactivity of CAIT cells need further investigations in future studies

HLA-DP on Epithelial Cells Enables Tissue Damage by NKp44⁺ Natural Killer Cells in Ulcerative Colitis

Background &amp; Aims: Ulcerative colitis (UC) is characterized by severe inflammation and destruction of the intestinal epithelium, and is associated with specific risk single nucleotide polymorphisms in HLA class II. Given the recently discovered interactions between subsets of HLA-DP molecules and the activating natural killer (NK) cell receptor NKp44, genetic associations of UC and HLA-DP haplotypes and their functional implications were investigated. Methods: HLA-DP haplotype and UC risk association analyses were performed (UC: n = 13,927; control: n = 26,764). Expression levels of HLA-DP on intestinal epithelial cells (IECs) in individuals with and without UC were quantified. Human intestinal 3-dimensional (3D) organoid cocultures with human NK cells were used to determine functional consequences of interactions between HLA-DP and NKp44. Results: These studies identified HLA-DPA1∗01:03-DPB1∗04:01 (HLA-DP401) as a risk haplotype and HLA-DPA1∗01:03-DPB1∗03:01 (HLA-DP301) as a protective haplotype for UC in European populations. HLA-DP expression was significantly higher on IECs of individuals with UC compared with controls. IECs in human intestinal 3D organoids derived from HLA-DP401pos individuals showed significantly stronger binding of NKp44 compared with HLA-DP301pos IECs. HLA-DP401pos IECs in organoids triggered increased degranulation and tumor necrosis factor production by NKp44+ NK cells in cocultures, resulting in enhanced epithelial cell death compared with HLA-DP301pos organoids. Blocking of HLA-DP401–NKp44 interactions (anti-NKp44) abrogated NK cell activity in cocultures. Conclusions: We identified an UC risk HLA-DP haplotype that engages NKp44 and activates NKp44+ NK cells, mediating damage to intestinal epithelial cells in an HLA-DP haplotype–dependent manner. The molecular interaction between NKp44 and HLA-DP401 in UC can be targeted by therapeutic interventions to reduce NKp44+ NK cell–mediated destruction of the intestinal epithelium in UC.</p

HLA-DP on Epithelial Cells Enables Tissue Damage by NKp44⁺ Natural Killer Cells in Ulcerative Colitis

Background &amp; Aims: Ulcerative colitis (UC) is characterized by severe inflammation and destruction of the intestinal epithelium, and is associated with specific risk single nucleotide polymorphisms in HLA class II. Given the recently discovered interactions between subsets of HLA-DP molecules and the activating natural killer (NK) cell receptor NKp44, genetic associations of UC and HLA-DP haplotypes and their functional implications were investigated. Methods: HLA-DP haplotype and UC risk association analyses were performed (UC: n = 13,927; control: n = 26,764). Expression levels of HLA-DP on intestinal epithelial cells (IECs) in individuals with and without UC were quantified. Human intestinal 3-dimensional (3D) organoid cocultures with human NK cells were used to determine functional consequences of interactions between HLA-DP and NKp44. Results: These studies identified HLA-DPA1∗01:03-DPB1∗04:01 (HLA-DP401) as a risk haplotype and HLA-DPA1∗01:03-DPB1∗03:01 (HLA-DP301) as a protective haplotype for UC in European populations. HLA-DP expression was significantly higher on IECs of individuals with UC compared with controls. IECs in human intestinal 3D organoids derived from HLA-DP401pos individuals showed significantly stronger binding of NKp44 compared with HLA-DP301pos IECs. HLA-DP401pos IECs in organoids triggered increased degranulation and tumor necrosis factor production by NKp44+ NK cells in cocultures, resulting in enhanced epithelial cell death compared with HLA-DP301pos organoids. Blocking of HLA-DP401–NKp44 interactions (anti-NKp44) abrogated NK cell activity in cocultures. Conclusions: We identified an UC risk HLA-DP haplotype that engages NKp44 and activates NKp44+ NK cells, mediating damage to intestinal epithelial cells in an HLA-DP haplotype–dependent manner. The molecular interaction between NKp44 and HLA-DP401 in UC can be targeted by therapeutic interventions to reduce NKp44+ NK cell–mediated destruction of the intestinal epithelium in UC.</p

Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ∼0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.publishedVersio

Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.S.E.H. and C.A.S. partially supported genotyping through a philanthropic donation. A.F. and D.E. were supported by a grant from the German Federal Ministry of Education and COVID-19 grant Research (BMBF; ID:01KI20197); A.F., D.E. and F.D. were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). D.E. was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). D.E., K.B. and S.B. acknowledge the Novo Nordisk Foundation (NNF14CC0001 and NNF17OC0027594). T.L.L., A.T. and O.Ö. were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. M.W. and H.E. are supported by the German Research Foundation (DFG) through the Research Training Group 1743, ‘Genes, Environment and Inflammation’. L.V. received funding from: Ricerca Finalizzata Ministero della Salute (RF-2016-02364358), Italian Ministry of Health ‘CV PREVITAL’—strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ‘REVEAL’; Fondazione IRCCS Ca’ Granda ‘Ricerca corrente’, Fondazione Sviluppo Ca’ Granda ‘Liver-BIBLE’ (PR-0391), Fondazione IRCCS Ca’ Granda ‘5permille’ ‘COVID-19 Biobank’ (RC100017A). A.B. was supported by a grant from Fondazione Cariplo to Fondazione Tettamanti: ‘Bio-banking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by an MIUR grant to the Department of Medical Sciences, under the program ‘Dipartimenti di Eccellenza 2018–2022’. This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP (The Institute for Health Science Research Germans Trias i Pujol) IGTP is part of the CERCA Program/Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). M.M. received research funding from grant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (European Regional Development Fund (FEDER)-Una manera de hacer Europa’). B.C. is supported by national grants PI18/01512. X.F. is supported by the VEIS project (001-P-001647) (co-funded by the European Regional Development Fund (ERDF), ‘A way to build Europe’). Additional data included in this study were obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, European Institute of Innovation & Technology (EIT), a body of the European Union, COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. A.J. and S.M. were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). A.J. was also supported by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the European Regional Development Fund (FEDER). The Basque Biobank, a hospital-related platform that also involves all Osakidetza health centres, the Basque government’s Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. M.C. received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). M.R.G., J.A.H., R.G.D. and D.M.M. are supported by the ‘Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III’ (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100) and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón’s team is supported by CIBER of Epidemiology and Public Health (CIBERESP), ‘Instituto de Salud Carlos III’. J.C.H. reports grants from Research Council of Norway grant no 312780 during the conduct of the study. E.S. reports grants from Research Council of Norway grant no. 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). P.K. Bergisch Gladbach, Germany and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF). O.A.C. is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—CECAD, EXC 2030–390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. K.U.L. is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. F.H. was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to A.R. from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme—Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to A.R. P.R. is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). F.T. is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). C.L. and J.H. are supported by the German Center for Infection Research (DZIF). T.B., M.M.B., O.W. und A.H. are supported by the Stiftung Universitätsmedizin Essen. M.A.-H. was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. E.C.S. is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).Peer reviewe