Biochemical and functional studies have demonstrated major histocompatibility complex (MHC) class II-restricted presentation of peptides derived from cytosolic proteins, but the underlying processing and presentation pathways have remained elusive. Here we show that endogenous presentation of an epitope derived from the cytosolic protein neomycin phosphotransferase II (NeoR) on MHC class II is mediated by autophagy. This presentation pathway involves the sequestration of NeoR into autophagosomes, and subsequent delivery into the lytic compartment. These results identify endosomes/lysosomes as the processing compartment for cytosolic antigens and furthermore link endogenous antigen presentation on MHC class II with the process of cellular protein turnover by autophagy.
ZusammenfassungDie Deutsche Gesellschaft für Pneumologie hat die AWMFS1-Leitlinie Post-COVID/Long-COVID initiiert. In einem breiten interdisziplinären Ansatz wurde diese S1-Leitlinie basierend auf dem aktuellen Wissensstand gestaltet.Die klinische Empfehlung beschreibt die aktuellen Post-COVID/Long-COVID-Symptome, diagnostische Ansätze und Therapien.Neben der allgemeinen und konsentierten Einführung wurde ein fachspezifischer Zugang gewählt, der den aktuellen Wissensstand zusammenfasst.Die Leitlinie hat einen expilzit praktischen Anspruch und wird basierend auf dem aktuellen Wissenszugewinn vom Autorenteam stetig weiterentwickelt und adaptiert.
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.
Epstein-Barr virus (EBV) establishes lifelong persistent infections in humans by latently infecting B cells, with occasional cycles of reactivation, virus production, and reinfection. Protective immunity against EBV is mediated by T cells, but the role of EBV-specific T helper (Th) cells is still poorly defined. Here, we study the Th response to the EBV lytic cycle proteins BLLF1 (gp350/220), BALF4 (gp110), and BZLF1 and show that glycoprotein-specific Th cells recognize EBV-positive cells directly; surprisingly, a much higher percentage of target cells than those expressing lytic cycle proteins were recognized. Antigen is efficiently transferred to bystander B cells by receptor-mediated uptake of released virions, resulting in recognition of target cells incubated with <1 virion/cell. T cell recognition does not require productive infection and occurs early after virus entry before latency is established. Glycoprotein-specific Th cells are cytolytic and inhibit proliferation of lymphoblastoid cell lines (LCL) and the outgrowth of LCL after infection of primary B cells with EBV. These results establish a novel role for glycoprotein-specific Th cells in the control of EBV infection and identify virion proteins as important immune targets. These findings have implications for the treatment of diseases associated with EBV and potentially other coated viruses infecting MHC class II–positive cells.
Influenza virus still poses a major threat to human health. Despite widespread vaccination programmes and the development of drugs targeting essential viral proteins, the extremely high mutation rate of influenza virus still leads to the emergence of new pathogenic virus strains. Therefore, it has been suggested that cellular cofactors that are essential for influenza virus infection might be better targets for antiviral therapy. It has previously been reported that influenza virus efficiently infects Epstein-Barr virus-immortalized B cells, whereas Burkitt's lymphoma cells are virtually resistant to infection. Using this cellular system, it has been shown here that an active NF-kB signalling pathway is a general prerequisite for influenza virus infection of human cells. Cells with low NF-kB activity were resistant to influenza virus infection, but became susceptible upon activation of NF-kB. In addition, blocking of NF-kB activation severely impaired influenza virus infection of otherwise highly susceptible cells, including the human lung carcinoma cell lines A549 and U1752 and primary human cells. On the other hand, infection with vaccinia virus was not dependent on an active NF-kB signalling pathway, demonstrating the specificity of this pathway for influenza virus infection. These results might be of major importance for both the development of new antiviral therapies and the understanding of influenza virus biology.
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