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The coronavirus disease 2019 (COVID-19) pandemic has claimed millions of lives and caused a global economic crisis. No effective antiviral drugs are currently available to treat infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The medical need imposed by the pandemic has spurred unprecedented research efforts to study coronavirus biology. Every virus depends on cellular host factors and pathways for successful replication. These proviral host factors represent attractive targets for antiviral therapy as they are genetically more stable than viral targets and may be shared among related viruses. The application of various ‘omics’ technologies has led to the rapid discovery of proviral host factors that are required for the completion of the SARS-CoV-2 life cycle. In this Review, we summarize insights into the proviral host factors that are required for SARS-CoV-2 infection that were mainly obtained using functional genetic and interactome screens. We discuss cellular processes that are important for the SARS-CoV-2 life cycle, as well as parallels with non-coronaviruses. Finally, we highlight host factors that could be targeted by clinically approved molecules and molecules in clinical trials as potential antiviral therapies for COVID-19. Proviral host factors for SARS-CoV-2 infection, cellular processes that are important in SARS-CoV-2 replication and host factors that could be targeted by antiviral therapies for COVID-19 are reviewed.

This study investigated how human locomotion through an obstacle environment is influenced by visual field limitation. Participants were asked to walk at a comfortable pace to a target location while avoiding multiple vertical objects. During this task, they wore goggles restricting their visual field to small (S: 40° × 25°), medium (M: 80° × 60°), large (L: 115° × 90°), or unlimited (U) visual field sizes. Full-body motion capture was used to extract for each trial the mean speed, pathlength, mean step width, magnitude of head rotation and head mean angular speed. The results show that compared with the U condition, the M and L conditions caused participants to select a wider path around the obstacles without slowing down or altering step width. However, the S condition did slow down the participants, and increased both their step width and path length. We conclude that only for the S condition, balancing problems were substantial enough to spend more energy associated with increased step width. In all cases, participants choose to optimize safety (collision avoidance) at the cost of spending more energy.

How the innate and adaptive host immune system miscommunicate to worsen COVID-19 immunopathology has not been fully elucidated. Here, we perform single-cell deep-immune profiling of bronchoalveolar lavage (BAL) samples from 5 patients with mild and 26 with critical COVID-19 in comparison to BALs from non-COVID-19 pneumonia and normal lung. We use pseudotime inference to build T-cell and monocyte-to-macrophage trajectories and model gene expression changes along them. In mild COVID-19, CD8 + resident-memory (T RM ) and CD4 + T-helper-17 (T H17 ) cells undergo active (presumably antigen-driven) expansion towards the end of the trajectory, and are characterized by good effector functions, while in critical COVID-19 they remain more naïve. Vice versa, CD4 + T-cells with T-helper-1 characteristics (T H1 -like) and CD8 + T-cells expressing exhaustion markers (T EX -like) are enriched halfway their trajectories in mild COVID-19, where they also exhibit good effector functions, while in critical COVID-19 they show evidence of inflammation-associated stress at the end of their trajectories. Monocyte-to-macrophage trajectories show that chronic hyperinflammatory monocytes are enriched in critical COVID-19, while alveolar macrophages, otherwise characterized by anti-inflammatory and antigen-presenting characteristics, are depleted. In critical COVID-19, monocytes contribute to an ATP-purinergic signaling-inflammasome footprint that could enable COVID-19 associated fibrosis and worsen disease-severity. Finally, viral RNA-tracking reveals infected lung epithelial cells, and a significant proportion of neutrophils and macrophages that are involved in viral clearance.

Emergence of SARS-CoV-2 causing COVID-19 has resulted in hundreds of thousands of deaths. In search for key targets of effective therapeutics, robust animal models mimicking COVID-19 in humans are urgently needed. Here, we show that Syrian hamsters, in contrast to mice, are highly permissive to SARS-CoV-2 and develop bronchopneumonia and strong inflammatory responses in the lungs with neutrophil infiltration and edema, further confirmed as consolidations visualized by micro-CT alike in clinical practice. Moreover, we identify an exuberant innate immune response as key player in pathogenesis, in which STAT2 signaling plays a dual role, driving severe lung injury on the one hand, yet restricting systemic virus dissemination on the other. Our results reveal the importance of STAT2-dependent interferon responses in the pathogenesis and virus control during SARS-CoV-2 infection and may help rationalizing new strategies for the treatment of COVID-19 patients. SARS-CoV-2 infection can result in severe lung inflammation and pathology, but host response remains incompletely understood. Here the authors show in Syrian hamsters that STAT2 signaling restricts systemic virus dissemination but also drives severe lung injury, playing a dual role in SARS-CoV-2 infection.

In order to acquire information concerning the geometry and material of handheld objects, people tend to execute stereotypical hand movement patterns called haptic Exploratory Procedures (EPs). Manual annotation of haptic exploration trials with these EPs is a laborious task that is affected by subjectivity, attentional lapses, and viewing angle limitations. In this paper we propose an automatic EP annotation method based on position and orientation data from motion tracking sensors placed on both hands and inside a stimulus. A set of kinematic variables is computed from these data and compared to sets of predefined criteria for each of four EPs. Whenever all criteria for a specific EP are met, it is assumed that that particular hand movement pattern was performed. This method is applied to data from an experiment where blindfolded participants haptically discriminated between objects differing in hardness, roughness, volume, and weight. In order to validate the method, its output is compared to manual annotation based on video recordings of the same trials. Although mean pairwise agreement is less between human-automatic pairs than between human-human pairs (55.7% vs 74.5%), the proposed method performs much better than random annotation (2.4%). Furthermore, each EP is linked to a specific object property for which it is optimal (e.g., Lateral Motion for roughness). We found that the percentage of trials where the expected EP was found does not differ between manual and automatic annotation. For now, this method cannot yet completely replace a manual annotation procedure. However, it could be used as a starting point that can be supplemented by manual annotation.

Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the respiratory microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 respiratory microbiome studies by analyzing the upper ( n  = 58) and lower ( n  = 35) respiratory tract microbiome in well-phenotyped COVID-19 patients and controls combining microbiome sequencing, viral load determination, and immunoprofiling. We find that time in the intensive care unit and type of oxygen support, as well as associated treatments such as antibiotic usage, explain the most variation within the upper respiratory tract microbiome, while SARS-CoV-2 viral load has a reduced impact. Specifically, mechanical ventilation is linked to altered community structure and significant shifts in oral taxa previously associated with COVID-19. Single-cell transcriptomics of the lower respiratory tract of COVID-19 patients identifies specific oral bacteria in physical association with proinflammatory immune cells, which show higher levels of inflammatory markers. Overall, our findings suggest confounders are driving contradictory results in current COVID-19 microbiome studies and careful attention needs to be paid to ICU stay and type of oxygen support, as bacteria favored in these conditions may contribute to the inflammatory phenotypes observed in severe COVID-19 patients. Here, the authors profile the respiratory microbiome of COVID-19 patients and link clinical practices, such as mechanical ventilation, with vast changes in the microbiota. In the lungs, oral bacteria are found physically associated with proinflammatory immune cells, thus possibly contributing to exacerbated immune responses in severe disease

The expanding pandemic of coronavirus disease 2019 (COVID-19) requires the development of safe, efficacious and fast-acting vaccines. Several vaccine platforms are being leveraged for a rapid emergency response 1 . Here we describe the development of a candidate vaccine (YF-S0) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that uses live-attenuated yellow fever 17D (YF17D) vaccine as a vector to express a noncleavable prefusion form of the SARS-CoV-2 spike antigen. We assess vaccine safety, immunogenicity and efficacy in several animal models. YF-S0 has an excellent safety profile and induces high levels of SARS-CoV-2 neutralizing antibodies in hamsters ( Mesocricetus auratus ), mice ( Mus musculus ) and cynomolgus macaques ( Macaca fascicularis ), and—concomitantly—protective immunity against yellow fever virus. Humoral immunity is complemented by a cellular immune response with favourable T helper 1 polarization, as profiled in mice. In a hamster model 2 and in macaques, YF-S0 prevents infection with SARS-CoV-2. Moreover, a single dose conferred protection from lung disease in most of the vaccinated hamsters within as little as 10 days. Taken together, the quality of the immune responses triggered and the rapid kinetics by which protective immunity can be attained after a single dose warrant further development of this potent SARS-CoV-2 vaccine candidate. A candidate vaccine against SARS-CoV-2 that uses the yellow fever 17D live-virus vector is highly efficacious and displays a favourable safety profile in Syrian hamster, mouse and cynomolgus macaque models.

The ongoing COVID-19 pandemic has caused a global economic and health crisis. To identify host factors essential for coronavirus infection, we performed genome-wide functional genetic screens with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and human coronavirus 229E. These screens uncovered virus-specific as well as shared host factors, including TMEM41B and PI3K type 3. We discovered that SARS-CoV-2 requires the lysosomal protein TMEM106B to infect human cell lines and primary lung cells. TMEM106B overexpression enhanced SARS-CoV-2 infection as well as pseudovirus infection, suggesting a role in viral entry. Furthermore, single-cell RNA-sequencing of airway cells from patients with COVID-19 demonstrated that TMEM106B expression correlates with SARS-CoV-2 infection. The present study uncovered a collection of coronavirus host factors that may be exploited to develop drugs against SARS-CoV-2 infection or future zoonotic coronavirus outbreaks. Genome-wide CRISPR screens for proviral host factors of SARS-CoV-2 and HCoV-229E human coronaviruses show that the lysosomal protein TMEM106B is required for SARS-CoV-2 infection.

The potential to operate third-party terminals over multi-domain transparent optical networks attracts operators and customers to implement Optical Spectrum as a Service (OSaaS). As infrastructure information cannot always be shared with OSaaS end customers, alternatives to off-line Quality of Transmission (QoT) estimation tools are required to assess the performance of the spectrum slot in order to estimate achievable throughput. In this paper, commercially available sliceable coherent transceivers are used to assess the Generalized Signal To Noise Ratio (GSNR) based QoT of the OSaaS in a live production network for both, narrow-band and wide-band OSaaS configurations. Extended channel probing based on symbol rate variability is combined with spectral sweeping and operation regime detection to characterize OSaaS implementations on 17 links with different underlying infrastructure configurations in order to maximize capacity and increase service margins in a low-margin operation regime. We achieve 0.05 dB estimation accuracy in GSNR for a wide-band spectrum services and 0.32 dB accuracy for narrow-band spectrum services. Based on the GSNR profile, spectral misalignment, spectral ripple, and operation regime are detected and service margin improvements are demonstrated. Finally, we discuss the network optimization perspective based on acquired data from channel probing and propose use-cases for continuous channel probing in transparent optical networks.

We present \\(\\)-OTDR for detecting and localising full spark-gap breakdowns by analysing backscattered light phase and frequency-domain signatures during high-voltage discharges synchronised with oscilloscope-recorded events. Measuring sub-kHz confirms clear discharge signatures and acoustic reconstruction over long links with \\(\\) 10 m spatial resolution.