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The main protease (Mpro) of SARS-CoV-2 is central to its viral lifecycle and is a promising drug target, but little is known concerning structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of classical molecular mechanics and quantum mechanical techniques, including automated docking, molecular dynamics (MD) simulations, linear-scaling DFT, QM/MM, and interactive MD in virtual reality, to investigate the molecular features underlying recognition of the natural Mpro substrates. Analyses of the subsite interactions of modelled 11-residue cleavage site peptides, ligands from high-throughput crystallography, and designed covalently binding inhibitors were performed. Modelling studies reveal remarkable conservation of hydrogen bonding patterns of the natural Mpro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular at the P2/S2 sites. The binding modes of the natural substrates, together with extensive interaction analyses of inhibitor and fragment binding to Mpro, reveal new opportunities for inhibition. Building on our initial Mpro-substrate models, computational mutagenesis scanning was employed to design peptides with improved affinity and which inhibit Mpro competitively. The combined results provide new insight useful for the development of Mpro inhibitors.

Background\ud \ud Mortality rates in hospitalised patients with COVID-19 in the UK appeared to decline during the first wave of the pandemic. We aimed to quantify potential drivers of this change and identify groups of patients who remain at high risk of dying in hospital.\ud \ud \ud Methods\ud \ud In this multicentre prospective observational cohort study, the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK recruited a prospective cohort of patients with COVID-19 admitted to 247 acute hospitals in England, Scotland, and Wales during the first wave of the pandemic (between March 9 and Aug 2, 2020). We included all patients aged 18 years and older with clinical signs and symptoms of COVID-19 or confirmed COVID-19 (by RT-PCR test) from assumed community-acquired infection. We did a three-way decomposition mediation analysis using natural effects models to explore associations between week of admission and in-hospital mortality, adjusting for confounders (demographics, comorbidities, and severity of illness) and quantifying potential mediators (level of respiratory support and steroid treatment). The primary outcome was weekly in-hospital mortality at 28 days, defined as the proportion of patients who had died within 28 days of admission of all patients admitted in the observed week, and it was assessed in all patients with an outcome. This study is registered with the ISRCTN Registry, ISRCTN66726260.\ud \ud \ud Findings\ud \ud Between March 9, and Aug 2, 2020, we recruited 80 713 patients, of whom 63 972 were eligible and included in the study. Unadjusted weekly in-hospital mortality declined from 32·3% (95% CI 31·8–32·7) in March 9 to April 26, 2020, to 16·4% (15·0–17·8) in June 15 to Aug 2, 2020. Reductions in mortality were observed in all age groups, in all ethnic groups, for both sexes, and in patients with and without comorbidities. After adjustment, there was a 32% reduction in the risk of mortality per 7-week period (odds ratio [OR] 0·68 [95% CI 0·65–0·71]). The higher proportions of patients with severe disease and comorbidities earlier in the first wave (March and April) than in June and July accounted for 10·2% of this reduction. The use of respiratory support changed during the first wave, with gradually increased use of non-invasive ventilation over the first wave. Changes in respiratory support and use of steroids accounted for 22·2%, OR 0·95 (0·94–0·95) of the reduction in in-hospital mortality.\ud \ud \ud Interpretation\ud \ud The reduction in in-hospital mortality in patients with COVID-19 during the first wave in the UK was partly accounted for by changes in the case-mix and illness severity. A significant reduction in in-hospital mortality was associated with differences in respiratory support and critical care use, which could partly reflect accrual of clinical knowledge. The remaining improvement in in-hospital mortality is not explained by these factors, and could be associated with changes in community behaviour, inoculum dose, and hospital capacity strain.\ud \ud \ud Funding\ud \ud National Institute for Health Research and the Medical Research Council.

Thermal denaturation assays and size exclusion chromatography with multi-angle light scattering analyses show that Î RBD deletion does not influence the overall shape and multimerization of purified His-TRIM25Î RBD. Figure S2. Generation and characterization of TRIM25 KO HeLa cell line. Figure S3. T7-TRIM25 CLIP-seq and T7-TRIM25 RNA immunoprecipitation results. Figure S4. T7-TRIM25 CLIP-seq experiments are reproducible, based on three independent experiments. Figure S5. No correlation of TRIM25 CLIP-seq cluster intensities with transcript abundance in HeLa cells. Figure S6. Gene Ontology-term annotation of TRIM25-bound transcripts and the ab initio-derived TRIM25-binding binding sequences cluster in three motif clusters. Figure S7. TRIM25 does not influence RNA stability of selected targets. Figure S8. TRIM25 undergoes ubiquitination. (PDF 9873 kb)

Background: In the context of the current coronavirus disease 2019 (COVID-19) pandemic, understanding household transmission of seasonal coronaviruses may inform pandemic control. We aimed to investigate what proportion of seasonal coronavirus transmission occurred within households, measure the risk of transmission in households, and describe the impact of household-related factors of risk of transmission. Methods: Using data from three winter seasons of the UK Flu Watch cohort study, we measured the proportion of symptomatic infections acquired outside and within the home, the household transmission risk and the household secondary attack risk for PCR-confirmed seasonal coronaviruses. We present transmission risk stratified by demographic features of households. Results: We estimated that the proportion of cases acquired outside the home, weighted by age and region, was 90.7% (95% CI 84.6- 94.5, n=173/195) and within the home was 9.3% (5.5-15.4, 22/195). Following a symptomatic coronavirus index case, 14.9% (9.8 - 22.1, 20/134) of households experienced symptomatic transmission to at least one other household member. Onward transmission risk ranged from 11.90% (4.84-26.36, 5/42) to 19.44% (9.21-36.49, 7/36) by strain. The overall household secondary attack risk for symptomatic cases was 8.00% (5.31-11.88, 22/275), ranging across strains from 5.10 (2.11-11.84, 5/98) to 10.14 (4.82- 20.11, 7/69). Median clinical onset serial interval was 7 days (IQR= 6-9.5). Households including older adults, 3+ children, current smokers, contacts with chronic health conditions, and those in relatively deprived areas had the highest transmission risks. Child index cases and male index cases demonstrated the highest transmission risks. Conclusion: Most seasonal coronaviruses appear to be acquired outside the household, with relatively modest risk of onward transmission within households. Transmission risk following an index case appears to vary by demographic household features, with potential overlap between those demonstrating the highest point estimates for seasonal coronavirus transmission risk and COVID-19 susceptibility and poor illness outcomes.

A common overlapping site on the N-terminal IgV-like domain of human carcinoembryonic antigen (CEA)-related cell adhesion molecules (CEACAMs) is targeted by several important human respiratory pathogens. These include Neisseria meningitidis (Nm) and Haemophilus influenzae (Hi) that can cause disseminated or persistent localized infections. To define the precise structural features that determine the binding of distinct pathogens with CEACAMs, we have undertaken molecular modelling and mutation of the receptor molecules at previously implicated key target residues required for bacterial binding. These include Ser-32, Tyr-34, Val-39, Gln-44 and Gln-89, in addition to Ile-91, the primary docking site for the pathogens. Most, but not all, of these residues located adjacent to each other in a previous N-domain model of human CEACAM1, which was based on REI, CD2 and CD4. In the current studies, we have refined this model based on the mouse CEACAM1 crystal structure, and observe that all of the above residues form an exposed continuous binding region on the N-domain. Examination of the model also suggested that substitution of two of these residues 34 and 89 could affect the accessibility of Ile-91 for ligand binding. By introducing selected mutations at the positions 91, 34 and 89, we confirmed the primary importance of Ile-91 in all bacterial binding to CEACAM1 despite the inter- and intraspecies structural differences between the bacterial CEACAM-binding ligands. The studies further indicated that the efficiency of binding was significantly enhanced for specific strains by mutations such as Y34F and Q89N, which also altered the hierarchy of Nm versus Hi strain binding. These studies imply that distinct polymorphisms in human epithelial CEACAMs have the potential to decrease or increase the risk of infection by the receptor-targeting pathogens.

Summary CoV-GLUE is an online web application for the interpretation and analysis of SARS-CoV-2 virus genome sequences, with a focus on amino acid sequence variation. It is based on the GLUE data-centric bioinformatics environment and provides a browsable database of amino acid replacements and coding region indels that have been observed in sequences from the pandemic. Users may also analyse their own SARS-CoV-2 sequences by submitting them to the web application to receive an interactive report containing visualisations of phylogenetic classification and highlighting genomic variation of potentially high impact, for example linked to primer mismatches.Availability and implementation Available at http://cov-glue.cvr.gla.ac.uk. Implemented using GLUE, an open source framework for the development of virus sequence data resources. Contact josh.singer@glasgow.ac.uk

Background: Emerging and epidemic infectious disease outbreaks are a significant public health problem and global health security threat. As an outbreak begins, epidemiological investigations and traditional public health responses are generally mounted very quickly. However, patient-centred research is usually not prioritised when planning and enacting the response. Instead, the clinical research response occurs subsequent to and separate from the public health response, and is inadequate for evidence-based decision-making at the bedside or in the offices of public health policymakers.Discussion: The deficiencies of the clinical research response to severe acute respiratory syndrome, pandemic influenza, Middle East respiratory syndrome coronavirus and Ebola virus demonstrate that current research models do not adequately inform and improve the quality of clinical care or public health response. Three suggestions for improvements are made. First, integrate the data and sample collection needs for clinical and public health decision-making within a unified framework, combined with a risk-based, rather than a discipline-based, approach to ethical review and consent. Second, develop clinical study methods and tools that are specifically designed to meet the epidemiological and contextual challenges of emerging and epidemic infectious diseases. Third, invest in investigator-led clinical research networks that are primed and incentivised to respond to outbreak infections, and which can call on the support and resources of a central centre of excellence.Conclusions: It is crucial that the field of epidemic science matures to place patients at the heart of the response. This can only be achieved when patient-centred research is integrated in the outbreak response from day one and practical steps are taken to reduce the barriers to the generation of reliable and useful evidence.

Importance: Since January 2020, Singapore has implemented comprehensive measures to suppress SARS-CoV-2. Despite this, the country has experienced contrasting epidemics, with limited transmission in the community and explosive outbreaks in migrant worker dormitories. Objective: To estimate SARS-CoV-2 infection incidence among migrant workers and the general population in Singapore. Design: Prospective serological cohort studies. Setting: Two cohort studies — in a migrant worker dormitory and in the general population in Singapore. Participants: 478 residents of a SARS-CoV-2-affected migrant worker dormitory were followed up between May and July 2020, with blood samples collected on recruitment and after 2 and 6 weeks. In addition, 937 community-dwelling adult Singapore residents, for whom pre-pandemic sera were available, were recruited. These individuals also provided a serum sample on recruitment in November/December 2020. Exposure: Exposure to SARS-CoV-2 in a densely populated migrant worker dormitory and in the general population. Main outcomes and measures: The main outcome measures were the incidences of SARS-CoV-2 infection in migrant workers and in the general population, as determined by the detection of neutralizing antibodies against SARS-CoV-2, and adjusting for assay sensitivity and specificity using a Bayesian modeling framework. Results: No evidence of community SARS-CoV-2 exposure was found in Singapore prior to September 2019. It was estimated that < 2 per 1000 adult residents in the community were infected with SARS-CoV-2 in 2020 (cumulative seroprevalence: 0.16%; 95% CrI: 0.008–0.72%). Comparison with comprehensive national case notification data suggested that around 1 in 4 infections in the general population were associated with symptoms. In contrast, in the migrant worker cohort, almost two-thirds had been infected by July 2020 (cumulative seroprevalence: 63.8%; 95% CrI: 57.9–70.3%); no symptoms were reported in almost all of these infections. Conclusions and relevance: Our findings demonstrate that SARS-CoV-2 suppression is possible with strict and rapid implementation of border restrictions, case isolation, contact tracing, quarantining, and social-distancing measures. However, the risk of large-scale epidemics in densely populated environments requires specific consideration in preparedness planning. Prioritization of these settings in vaccination strategies should minimize the risk of future resurgences and potential spillover of transmission to the wider community.