Identification and Characterization of Host Shut-Off Proteins of Mycobacteriophages

Mycobacteriophages are viruses that infect exclusively mycobacteria. In this work I screened mycobacteriophage genomes for host shut-off proteins, proteins that are capable of down-regulating the mycobacterial metabolism early in the infectious cycle. These proteins are of interest in the drug-target discovery process of important pathogens such as Mycobacterium tuberculosis. Several host shut-off proteins were identified and characterized with regard to functional and regulatory aspects. Geneproduct 49, the WhiB-like protein of mycobacteriophage TM4 (WhiBTM4) was shown to be growth inhibitory in the mycobacterial host upon induction of expression. Like its homologue in the host (WhiB2), this viral protein is capable of co-ordinating an iron-sulfur (Fe-S) cluster. The UV-visible absorption spectra obtained from freshly purified and reconstituted WhiBTM4 were consistent with the presence of an oxygen sensitive [2Fe-2S] cluster. The quantification of mRNA-levels during phage infection showed that whiBTM4 is a highly transcribed early phage gene and a dominant negative regulator of WhiB2, an essential mycobacterial protein. Strikingly, both apo-WhiB2 of M. tuberculosis and apo-WhiBTM4 were capable of binding to the conserved promoter region upstream of the whiB2 gene indicating that WhiB2 regulates its own synthesis which is inhibited in the presence of WhiBTM4. Thus, within this work, substantial evidence could be provided, supporting the hypothesis of viral and bacterial WhiB proteins being important Fe-S containing transcriptional regulators with DNA-binding capability. In mycobacteriophage L5 three open reading frames within an early operon were identified as toxic to the host M. smegmatis when expressed from an inducible expression vector. These ORFs coding for gp77, gp78 and gp79 presumably function as shut-off genes during early stages of phage replication. There is evidence, that the cell division is affected by one of the proteins (gp79). The transcription of the cytotoxic polypeptides is directed by a promoter situated in ORF83 and transcription control is achieved through the phage repressor gp71 which was shown by co-expression of this protein. The findings presented here can provide useful tools for the molecular genetics of mycobacteria. The mycobacteriophage L5 early protein gp77 was further characterized with regard to its possible function within the host. I provide data showing that this purified phage protein of unknown function specifically binds to protein MSMEG_3532 when incubated with protein lysates of Mycobacterium smegmatis. This interaction was confirmed by pull-down assays using purified MSMEG_3532 as bait which co-purified with gp77. The amino acid sequence of MSMEG_3532 is nearly identical to that of threonine dehydratases, serine dehydratases and an L-threo-3-hydroxyaspartate dehydratase. An enzymatic assay confirmed this host protein as a pyridoxal-5'-phosphate-dependent L-serine dehydratase (SdhA) which converts L-serine to pyruvate. This is the first biochemical characterization of a serine dehydratase derived from mycobacteria. Though the addition of purified gp77 to the established in vitro assay had no influence on the enzymatic activity of MSMEG_3532, the specific interaction of phage protein and dehydratase in vivo may well have a role in altering the amino acid pool or the products of amino acid metabolism in favour of phage maturation

Acquired Long QT Syndrome and Torsade de Pointes Associated with HIV Infection

Here, we report the case of an HIV infected patient that was treated for pneumonia with a macrolid antibiotic. The patient experienced a prolongation of the already pathologic QTc interval resulting in repeated torsades de pointes necessitating CPR and implantation of an AICD. This case exemplifies that torsades de pointes due to acquired long QT syndrome is a serious and potentially fatal complication in HIV-positive patients

Lansoprazole is an antituberculous prodrug targeting cytochrome bc1

Better antibiotics capable of killing multi-drug-resistant Mycobacterium tuberculosis are urgently needed. Despite extensive drug discovery efforts, only a few promising candidates are on the horizon and alternative screening protocols are required. Here, by testing a panel of FDA-approved drugs in a host cell-based assay, we show that the blockbuster drug lansoprazole (Prevacid), a gastric proton-pump inhibitor, has intracellular activity against M. tuberculosis. Ex vivo pharmacokinetics and target identification studies reveal that lansoprazole kills M. tuberculosis by targeting its cytochrome bc(1) complex through intracellular sulfoxide reduction to lansoprazole sulfide. This novel class of cytochrome bc(1) inhibitors is highly active against drug-resistant clinical isolates and spares the human H+K+-ATPase thus providing excellent opportunities for targeting the major pathogen M. tuberculosis. Our finding provides proof of concept for hit expansion by metabolic activation, a powerful tool for antibiotic screens

Spleen tyrosine kinase mediates innate and adaptive immune crosstalk in SARS-CoV-2 mRNA vaccination

Durable cell-mediated immune responses require efficient innate immune signaling and the release of pro-inflammatory cytokines. How precisely mRNA vaccines trigger innate immune cells for shaping antigen specific adaptive immunity remains unknown. Here, we show that SARS-CoV-2 mRNA vaccination primes human monocyte-derived macrophages for activation of the NLRP3 inflammasome. Spike protein exposed macrophages undergo NLRP3-driven pyroptotic cell death and subsequently secrete mature interleukin-1β. These effects depend on activation of spleen tyrosine kinase (SYK) coupled to C-type lectin receptors. Using autologous cocultures, we show that SYK and NLRP3 orchestrate macrophage-driven activation of effector memory T cells. Furthermore, vaccination-induced macrophage priming can be enhanced with repetitive antigen exposure providing a rationale for prime-boost concepts to augment innate immune signaling in SARS-CoV-2 vaccination. Collectively, these findings identify SYK as a regulatory node capable of differentiating between primed and unprimed macrophages, which modulate spike protein-specific T cell responses

Swarm Learning for decentralized and confidential clinical machine learning

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine

Immunological fingerprint in coronavirus disease-19 convalescents with and without post-COVID syndrome

BackgroundSymptoms lasting longer than 12  weeks after severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection are called post-coronavirus disease (COVID) syndrome (PCS). The identification of new biomarkers that predict the occurrence or course of PCS in terms of a post-viral syndrome is vital. T-cell dysfunction, cytokine imbalance, and impaired autoimmunity have been reported in PCS. Nevertheless, there is still a lack of conclusive information on the underlying mechanisms due to, among other things, a lack of controlled study designs.MethodsHere, we conducted a prospective, controlled study to characterize the humoral and cellular immune response in unvaccinated patients with and without PCS following SARS-CoV-2 infection over 7 months and unexposed donors.ResultsPatients with PCS showed as early as 6 weeks and 7 months after symptom onset significantly increased frequencies of SARS-CoV-2-specific CD4+ and CD8+ T-cells secreting IFNγ, TNF, and expressing CD40L, as well as plasmacytoid dendritic cells (pDC) with an activated phenotype. Remarkably, the immunosuppressive counterparts type 1 regulatory T-cells (TR1: CD49b/LAG-3+) and IL-4 were more abundant in PCS+.ConclusionThis work describes immunological alterations between inflammation and immunosuppression in COVID-19 convalescents with and without PCS, which may provide potential directions for future epidemiological investigations and targeted treatments

The dpsA Gene of Streptomyces coelicolor: Induction of Expression from a Single Promoter in Response to Environmental Stress or during Development

The DpsA protein plays a dual role in Streptomyces coelicolor, both as part of the stress response and contributing to nucleoid condensation during sporulation. Promoter mapping experiments indicated that dpsA is transcribed from a single, sigB-like dependent promoter. Expression studies implicate SigH and SigB as the sigma factors responsible for dpsA expression while the contribution of other SigB-like factors is indirect by means of controlling sigH expression. The promoter is massively induced in response to osmotic stress, in part due to its sensitivity to changes in DNA supercoiling. In addition, we determined that WhiB is required for dpsA expression, particularly during development. Gel retardation experiments revealed direct interaction between apoWhiB and the dpsA promoter region, providing the first evidence for a direct WhiB target in S. coelicolor

Using observational data to emulate a randomized trial of dynamic treatment switching strategies

BACKGROUND: When a clinical treatment fails or shows suboptimal results, the question of when to switch to another treatment arises. Treatment switching strategies are often dynamic because the time of switching depends on the evolution of an individual's time-varying covariates. Dynamic strategies can be directly compared in randomized trials. For example, HIV-infected individuals receiving antiretroviral therapy could be randomized to switching therapy within 90 days of HIV-1 RNA crossing above a threshold of either 400 copies/ml (tight-control strategy) or 1000 copies/ml (loose-control strategy).METHODS: We review an approach to emulate a randomized trial of dynamic switching strategies using observational data from the Antiretroviral Therapy Cohort Collaboration, the Centers for AIDS Research Network of Integrated Clinical Systems and the HIV-CAUSAL Collaboration. We estimated the comparative effect of tight-control vs. loose-control strategies on death and AIDS or death via inverse-probability weighting.RESULTS: Of 43 803 individuals who initiated an eligible antiretroviral therapy regimen in 2002 or later, 2001 met the baseline inclusion criteria for the mortality analysis and 1641 for the AIDS or death analysis. There were 21 deaths and 33 AIDS or death events in the tight-control group, and 28 deaths and 41 AIDS or death events in the loose-control group. Compared with tight control, the adjusted hazard ratios (95% confidence interval) for loose control were 1.10 (0.73, 1.66) for death, and 1.04 (0.86, 1.27) for AIDS or death.CONCLUSIONS: Although our effective sample sizes were small and our estimates imprecise, the described methodological approach can serve as an example for future analyses

Swarm Learning for decentralized and confidential clinical machine learning

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine

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