Summary Objectives Patients with acute respiratory distress syndrome (ARDS) due to viral infection are at risk for secondary complications like invasive aspergillosis. Our study evaluates coronavirus disease 19 (COVID‐19) associated invasive aspergillosis at a single centre in Cologne, Germany. Methods A retrospective chart review of all patients with COVID‐19 associated ARDS admitted to the medical or surgical intensive care unit at the University Hospital of Cologne, Cologne, Germany. Results COVID‐19 associated invasive pulmonary aspergillosis was found in five of 19 consecutive critically ill patients with moderate to severe ARDS. Conclusion Clinicians caring for patients with ARDS due to COVID‐19 should consider invasive pulmonary aspergillosis and subject respiratory samples to comprehensive analysis to detect co‐infection.

Highlights d Low avidity and broad cross-reactivities of pre-existing SARS-CoV-2 memory T cells d Strong CCCoV-specific memory CD4 + T cell responses in all analyzed individuals d SARS-CoV-2-specific CD4 + T cells in COVID-19 patients lack cross-reactivity to CCCoVs d Low avidity and clonality of SARS-CoV-2-specific T cell responses in severe COVID-19

Highlights d SARS-CoV2 infection elicits dynamic changes of circulating cells in the blood d Severe COVID-19 is characterized by increased metabolically active plasmablasts d Elevation of IFN-activated megakaryocytes and erythroid cells in severe COVID-19 d Cell-type-specific expression signatures are associated with a fatal COVID-19 outcome

Cytosolic detection of microbial products is essential for the initiation of an innate immune response against intracellular pathogens such as Mycobacterium tuberculosis (Mtb). During Mtb infection of macrophages, activation of cytosolic surveillance pathways is dependent on the mycobacterial ESX-1 secretion system and leads to type I interferon (IFN) and interleukin-1β (IL-1β) production. Whereas the inflammasome regulates IL-1β secretion, the receptor(s) responsible for the activation of type I IFNs has remained elusive. We demonstrate that the cytosolic DNA sensor cyclic GMP-AMP synthase (cGAS) is essential for initiating an IFN response to Mtb infection. cGAS associates with Mtb DNA in the cytosol to stimulate cyclic GAMP (cGAMP) synthesis. Notably, activation of cGAS-dependent cytosolic host responses can be uncoupled from inflammasome activation by modulating the secretion of ESX-1 substrates. Our findings identify cGAS as an innate sensor of Mtb and provide insight into how ESX-1 controls the activation of specific intracellular recognition pathways.

The expectation that genomics would result in new therapeutic interventions for infectious diseases remains unfulfilled. In the post-genomic era, the decade immediately following the availability of the genome sequence of Mycobacterium tuberculosis, tuberculosis (TB) drug discovery relied heavily on the target-based approach but this proved unsuccessful leading to a return to whole cell screening. Genomics underpinned screening by providing knowledge and many enabling technologies, most importantly whole genome resequencing to find resistance mutations and targets, and this resulted in a selection of leads and new TB drug candidates that are reviewed here. Unexpectedly, many new targets were found to be ‘promiscuous’ as they were inhibited by a variety of different compounds. In the post-post-genomics era, more advanced technologies have been implemented and these include high-content screening, screening for inhibitors of latency, the use of conditional knock-down mutants for validated targets and siRNA screens. In addition, immunomodulation and pharmacological manipulation of host functions are being explored in an attempt to widen our therapeutic options.

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 bc1 complex through intracellular sulfoxide reduction to lansoprazole sulfide. This novel class of cytochrome bc1 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.

SUMMARY Patients and physicians worldwide are facing tremendous health care hazards that are caused by the ongoing severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) pandemic. Remdesivir (GS-5734) is the first approved treatment for severe coronavirus disease 2019 (COVID-19). It is a novel nucleoside analog with a broad antiviral activity spectrum among RNA viruses, including ebolavirus (EBOV) and the respiratory pathogens Middle East respiratory syndrome coronavirus (MERS-CoV), SARS-CoV, and SARS-CoV-2. First described in 2016, the drug was derived from an antiviral library of small molecules intended to target emerging pathogenic RNA viruses. In vivo, remdesivir showed therapeutic and prophylactic effects in animal models of EBOV, MERS-CoV, SARS-CoV, and SARS-CoV-2 infection. However, the substance failed in a clinical trial on ebolavirus disease (EVD), where it was inferior to investigational monoclonal antibodies in an interim analysis. As there was no placebo control in this study, no conclusions on its efficacy in EVD can be made. In contrast, data from a placebo-controlled trial show beneficial effects for patients with COVID-19. Remdesivir reduces the time to recovery of hospitalized patients who require supplemental oxygen and may have a positive impact on mortality outcomes while having a favorable safety profile. Although this is an important milestone in the fight against COVID-19, approval of this drug will not be sufficient to solve the public health issues caused by the ongoing pandemic. Further scientific efforts are needed to evaluate the full potential of nucleoside analogs as treatment or prophylaxis of viral respiratory infections and to develop effective antivirals that are orally bioavailable.

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.