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1.
Preprint | medRxiv | ID: ppmedrxiv-22283069

RESUMO

Epidemiological application of chaos theory methods have uncovered the existence of chaotic markers in SARS-CoV-2's epidemiological data, including low dimensional attractors with positive Lyapunov exponents, and evidence markers of a dynamics that is close to the onset of chaos for different regions. We expand on these previous works, performing a comparative study of United States of America (USA) and Canada's COVID-19 daily hospital occupancy cases, applying a combination of chaos theory, machine learning and topological data analysis methods. Both countries show markers of low dimensional chaos for the COVID-19 hospitalization data, with a high predictability for adaptive artificial intelligence systems exploiting the recurrence structure of these attractors, with more than 95% R2 scores for up to 42 days ahead prediction. The evidence is favorable to the USA's hospitalizations being closer to the onset of chaos and more predictable than Canada, the reasons for this higher predictability are accounted for by using topological data analysis methods.

2.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22283067

RESUMO

RT-qPCR is considered the gold standard for diagnosis of COVID-19; however, it is laborious, time-consuming, and expensive. RADTs have evolved recently as relatively inexpensive methods to address these shortcomings, but their performance for detecting different SARS-COV-2 variants remains limited. RADT test performance could be enhanced using different antibody labeling and signal detection techniques. Here, we aimed to evaluate the performance of two Wondfo antigen RADTs for detecting different SARS-CoV-2 variants: (i) the conventional colorimetric RADT (Ab-conjugated with gold beads); and (ii) the new FinecareTM RADT (Ab-coated fluorescent beads). FinecareTM is a meter used for the detection of a fluorescent signal. 187 frozen nasopharyngeal swabs collected in Universal transport (UTM) that are RT-qPCR positive for different SARS-CoV-2 variants were selected, including 60 Alpha, 59 multiple Delta, and 108 multiple Omicron variants. 60 flu and 60 RSV-positive samples were included as negative controls (total sample number=349). The conventional RADT showed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 62.4% (95%CI: 54-70), 100% (95%CI: 97-100), 100% (95%CI: 100-100), and 58% (95%CI: 49-67) respectively. These measurements were enhanced using the FinecareTM RADT: sensitivity, specificity, PPV, and NPV were 92.6% (95%CI: 89.08-92.3), 96% (95%CI: 96-99.61), 98% (95%CI: 89-92.3), and 85% (95%CI: 96-99.6) respectively. The sensitivity of both RADTs could be greatly underestimated because nasopharyngeal swab samples collected UTM and stored at -80 oC were used. Despite that, our results indicate that the FinecareTM RADT is appropriate for clinical laboratory and community-based surveillance due to its high sensitivity and specificity.

3.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22283006

RESUMO

Background Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection can be asymptomatic in young children. Therefore, the true rate of infection is likely underestimated. Few data are available on the rate of infections in young children, and studies on the SARS-CoV-2 seroprevalence among children during omicron wave are limited. Our study aims to assess the SARS-CoV-2 infection-induced seroprevalence among children and estimated the associated risk factors for seropositivity. Methods A longitudinal serological survey was conducted from January 2021 through November 2022. Samples were tested for anti-nucleocapsid (N) IgG, anti-receptor binding domain (RBD) IgG using a chemiluminescent microparticle immunoassay (CMIA) and detected anti-RBD Immunoglobulin (Ig) using an electrochemiluminescence immunoassay (ECLIA). The vaccination and SARS-CoV-2 infection history were collected. Results A total of 452 serum samples were obtained from 249 children aged 5-7 years old who were annually followed-up in the longitudinal serological survey. Of these, 191 participants provided samples at two serial time points, including during the pre-and omicron dominant wave. Overall, seroprevalence induced by SARS-CoV-2 infection was increased from 9.1% (95%CI: 0.6-12.6%) during the pre-omicron wave to 49.7% (95%CI: 35.9-66.8%) during the omicron wave. Amongst seropositive individuals, the infection-induced seroprevalence was lower in vaccinated participants than those with no vaccination (40.4% vs. 57.4%; risk ratio, 0.71; 95%CI: 0.52-0.95). Nevertheless, the ratio of seropositive cases per recalled infection was 1.56 during the omicron dominant wave. In addition, overall seroprevalence induced by infection, vaccination and hybrid immunity was 76.6% (151/197; 95%CI: 54.6-97.9%) between January and November 2022. Conclusions our study reports an increase in infection-induced seroprevalence among children during the omicron wave. These findings highlight that estimating seroprevalence is crucial to monitor SARS-CoV-2 exposure, particularly in asymptomatic infection, and help to optimize public health policies and determine the effect of immunization in the pediatric population.

4.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22282927

RESUMO

Abstract Background In low- and middle-income countries where SARS-CoV-2 testing is limited, seroprevalence studies can characterise the scale and determinants of the pandemic, as well as elucidate protection conferred by prior exposure. Methods We conducted repeated cross-sectional serosurveys (July 2020 - November 2021) using residual plasma from routine convenient blood samples from patients with non-COVID-19 conditions from Cape Town, South Africa. SARS-CoV-2 anti-nucleocapsid antibodies and linked clinical information were used to investigate: (1) seroprevalence over time and risk factors associated with seropositivity, (2) ecological comparison of seroprevalence between subdistricts, (3) case ascertainment rates, and (4) the relative protection against COVID-19 associated with seropositivity and vaccination statuses, to estimate variant disease severity. Findings Among the subset sampled, seroprevalence of SARS-CoV-2 in Cape Town increased from 39.2% in July 2020 to 67.8% in November 2021. Poorer communities had both higher seroprevalence and COVID-19 mortality. Only 10% of seropositive individuals had a recorded positive SARS-CoV-2 test. Antibody positivity before the start of the Omicron BA.1 wave (28 November 2021) was strongly protective for severe disease (adjusted odds ratio [aOR] 0.15; 95%CI 0.05-0.46), with additional benefit in those who were also vaccinated (aOR 0.07, 95%CI 0.01-0.35). Interpretation The high population seroprevalence in Cape Town was attained at the cost of substantial COVID-19 mortality. At the individual level, seropositivity was highly protective against subsequent infections and severe COVID-19.

5.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22282902

RESUMO

Age is a significant risk factor for the coronavirus disease 2019 (COVID-19) outcomes due to immunosenescence and certain age-dependent medical conditions (e.g., obesity, cardiovascular disorder, diabetes, chronic respiratory disease). However, despite the well-known influence of age on autoantibody biology in health & disease, its impact on the risk of developing severe COVID-19 remains poorly explored. Here, we performed a cross-sectional study of autoantibodies directed against 58 targets associated with autoimmune diseases in 159 individuals with different COVID-19 outcomes (with 71 mild, 61 moderate, and 27 severe patients) and 73 healthy controls. We found that the natural production of autoantibodies increases with age and is exacerbated by SARS-CoV-2 infection, mostly in severe COVID-19 patients. Multivariate regression analysis showed that severe COVID-19 patients have a significant age-associated increase of autoantibody levels against 16 targets (e.g., amyloid beta peptide, beta catenin, cardiolipin, claudin, enteric nerve, fibulin, insulin receptor a, and platelet glycoprotein). Principal component analysis with spectrum decomposition based on these autoantibodies indicated an age-dependent stratification of severe COVID-19 patients. Random forest analysis ranked autoantibodies targeting cardiolipin, claudin, and platelet glycoprotein as the three most crucial autoantibodies for the stratification of severe elderly COVID-19 patients. Follow-up analysis using binomial regression found that anti-cardiolipin and anti-platelet glycoprotein autoantibodies indicated a significantly increased likelihood of developing a severe COVID-19 phenotype, presenting a synergistic effect on worsening COVID-19 outcomes. These findings provide new key insights to explain why elderly patients less favorable outcomes have than young individuals, suggesting new associations of distinct autoantibody levels with disease severity.

6.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22282932

RESUMO

In July 2022, a cohort of 28 staff members were recruited from a UK primary school setting. The prevalent variants at the time were Omicron BA.1.159, BA.4/5 and BA.2: 61% of the cohort reported a lateral flow confirmed positive test for SARS-CoV-2 infection in late 2021 or 2022. A fully quantitative antibody screen for concentration and affinity was performed for spike protein variants Wuhan, Alpha, Beta, Gamma, Delta and Omicron BA.1, BA.2.75, BA.2.12.1, BA.4 and BA.5 and a pH dependent affinity was derived from disruption of the epitope-paratope complex at pH 3.2. The cohort showed a Universal positive immunity endotype, U(+), incidence of 78% (95% CI 60% - 88%) with good antibody concentrations to all ten variants; the incidence drops to 25% (95% CI 13% - 43%) when the affinity spectrum is measured. The antibody affinity profiles for each Omicron variant were all significantly better than Alpha, Beta, Gamma and Delta reflecting exposure to the antigens; we surmise either from the booster vaccines or continual contact with the virus, presenting in the school children either asymptomatically or symptomatically. Significant antibody affinity maturation was seen to the spike protein in all prevalent variants of SARS-CoV-2. Antibody concentrations were waning compared to the post-booster vaccine response. Using our hypothesised 3.4 mg/L nasal mucosal protection threshold, we postulate 46% of the cohort required boosting within 60 days and 66% within 120 days. We propose a smart boosting programme around the constant-exposure teacher cohort and parents of children could reduce community transmission.

7.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22283089

RESUMO

Objective It has been hypothesized that SARS-CoV-2 infection in children can increase risk of developing type 1 diabetes. Research Design and Methods We undertook a prospective analysis based on all children in Denmark where we investigated the association between SARS-CoV-2 infection and subsequent risk of type 1 diabetes, using information from several different national Danish registers. Denmark had one of the highest test-rates per capita in the world during the pandemic. Results We did not observe a higher risk of a first time diagnosis of type 1 diabetes in children 30 days or more after a positive SARS-CoV-2 test, compared to children with a history of only negative SARS-CoV-2 tests (Hazard ratio 0.85, 95% CI 0.70, 1.04). Conclusions Our data do not support that SARS-CoV-2 infection is associated with type 1 diabetes, or that type 1 diabetes should be a special focus after a SARS-CoV-2 infection in children.

8.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22283074

RESUMO

Colleges and universities in the US struggled to provide safe in-person education throughout the COVID-19 pandemic. Testing coupled with isolation is a nimble intervention strategy that can be tailored to mitigate health and economic costs, as the virus and our arsenal of medical countermeasures continue to evolve. We developed a decision-support tool to aid in the design of university-based testing strategies using a mathematical model of SARS-CoV-2 transmission. Applying this framework to a large public university reopening in the fall of 2021 with a 60% student vaccination rate, we find that the optimal strategy, in terms of health and economic costs, is twice weekly antigen testing of all students. This strategy provides a 95% guarantee that, throughout the fall semester, case counts would not exceed the CDCs original high transmission threshold of 100 cases per 100k persons over 7 days. As the virus and our medical armament continue to evolve, testing will remain a flexible tool for managing risks and keeping campuses open. We have implemented this model as an online tool to facilitate the design of testing strategies that adjust for COVID-19 conditions, university-specific parameters, and institutional goals.

9.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22282938

RESUMO

The spatio-temporal course of an epidemic (such as Covid-19) can be significantly affected by non-pharmaceutical interventions (NPIs), such as full or partial lockdowns. Bayesian Susceptible-Infected-Removed (SIR) models can be applied to the spatio-temporal spread of infectious disease (STIF) (such as Covid-19). In causal inference it is classically of interest to investigate counterfactuals. In the context of STIF it is possible to use nowcasting to assess the possible counterfactual realization of disease in incidence that would have been evidenced with no NPI. Classic lagged dependency spatio-temporal IF models will be discussed and the importance of the ST component in nowcasting will be assessed. The real example of lockdowns for Covid-19 in two US states during 2020 and 2021 is provided. The degeneracy in prediction in longer time periods is highlighted and the wide confidence intervals characterize the forecasts.

10.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22282697

RESUMO

SARS-CoV-2 Omicron has become the predominant variant globally. Current infection models are limited by the need for large datasets or calibration to specific contexts, making them difficult to cater for different settings. To ensure public health decision-makers can easily consider different public health interventions (PHIs) over a wide range of scenarios, we propose a generalized multinomial probabilistic model of airborne infection to systematically capture group characteristics, epidemiology, viral loads, social activities, environmental conditions, and PHIs, with assumptions made on social distancing and contact duration, and estimate infectivity over short time-span group gatherings. This study is related to our 2021 work published in Nature Scientific Reports that modelled airborne SARS-CoV-2 infection (Han, Lam, Li, et al., 2021). It is differentiated from former works on probabilistic infection modelling in terms of the following: (1) predicting new cases arising from more than one infectious in a gathering, (2) incorporating additional key infection factors, and (3) evaluating the effectiveness of multiple PHIs on SARS-CoV-2 infection simultaneously. Although our results reveal that limiting group size has an impact on infection, improving ventilation has a much greater positive health impact. Our model is versatile and can flexibly accommodate other scenarios by allowing new factors to be added, to support public health decision-making.

11.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22283026

RESUMO

Background Healthcare across all sectors, in the UK and globally, was negatively affected by the COVID-19 pandemic. We investigated the effect of the COVID-19 pandemic on the quantity of healthcare services delivered to people with pancreatic cancer. Methods With the approval of NHS England, and drawing from a nationally representative OpenSAFELY-TPP dataset of 24 million patients (over 40% of the English population), we undertook a cohort study of people diagnosed with pancreatic cancer. We queried electronic healthcare records for information on the provision of healthcare services across the pancreatic cancer pathway. To estimate the effect of the COVID-19 pandemic, we predicted the rates of healthcare services if the pandemic had not happened. We used generalised linear models (GLM) and the pre-pandemic data from January 2015 to February 2020 to predict rates in March 2020 to September 2022. The 95% confidence intervals of the predicted values were used to estimate the significance of the difference between the predicted and observed rates. Results The rate of pancreatic cancer and diabetes diagnoses in the cohort was not affected by the pandemic. There were 24,500 people diagnosed with pancreatic cancer from January 2015 to September 2022. The mean age at diagnosis was 72 (SD 11), 48% of people were female, 95% were of White ethnicity and 39% were diagnosed with diabetes. We found a reduction in surgical resections by nearly 25% during the pandemic. In addition, 20%, 10% and 5% fewer people received BMI, HbA1c and liver function tests respectively before they were diagnosed with pancreatic cancer. There was no impact of the pandemic on the number of people making contact with primary care, but the number of contacts increased on average by 1 to 2 per person amongst those who made contact. Abdominal scans decreased by 7% and reporting of jaundice decreased by 20%, but recovered within six months into the pandemic. Emergency department visits, hospital admissions and deaths were not affected. Conclusions The pandemic affected healthcare in England across the pancreatic cancer pathway. Positive lessons could be learnt from services that recovered quickly. The reductions in healthcare experienced by people with cancer have the potential to lead to worse outcomes. Current efforts should focus on addressing the unmet needs of people with cancer.

12.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22282946

RESUMO

Background: Social determinants of health are non-medical factors that influence health outcomes (SDOH). There is a wealth of SDOH information available via electronic health records, clinical reports, and social media, usually in free texts format, which poses a significant challenge and necessitates the use of natural language processing (NLP) techniques to extract key information. Objective: The objective of this research is to advance the automatic extraction of SDOH from clinical texts. Setting and Data: The case reports of COVID-19 patients from the published literature are curated to create a corpus. A portion of the data is annotated by experts to create gold labels, and active learning is used for corpus re-annotation. Methods: A named entity recognition (NER) framework is developed and tested to extract SDOH along with a few prominent clinical entities (diseases, treatments, diagnosis) from the free texts. The proposed model consists of three deep neural networks-A Transformer-based model, a BiLSTM model and a CRF module. Results: The proposed NER implementation achieves an accuracy (F1-score) of 92.98% on our test set and generalizes well on benchmark data. A careful analysis of case examples demonstrates the superiority of the proposed approach in correctly classifying the named entities. Conclusions: NLP can be used to extract key information, such as SDOH from free texts. A more accurate understanding of SDOH is needed to further improve healthcare outcomes.

13.
Preprint | bioRxiv | ID: ppbiorxiv-518611

RESUMO

Despite the worldwide success of mRNA-LNP Covid-19 vaccines, the nanoscale structure of these formulations is still poorly understood. To fill this gap, we used a combination of atomic force microscopy (AFM), dynamic light scattering (DLS), transmission electron microscopy (TEM), cryogenic transmission electron microscopy (cryo-TEM) and the determination of LNP pH gradient to analyze the nanoparticles (NPs) in BNT162b2 (Comirnaty), comparing it with the well characterized pegylated liposomal doxorubicin (Doxil). Comirnaty NPs had similar size to Doxil, however, unlike Doxil liposomes, wherein the stable ammonium and pH gradient enables accumulation of 14C-methylamine in the intraliposomal aqueous phase, Comirnaty LNPs lack such pH gradient in spite of the fact that the pH 4, at which LNPs are prepared, is raised to pH 7.2 after loading of the mRNA. Mechanical manipulation of Comirnaty NPs with AFM revealed soft, compliant structures. The sawtooth-like force transitions seen during cantilever retraction implies that molecular strands, corresponding to mRNA, can be pulled out of NPs, and the process is accompanied by stepwise rupture of mRNA-lipid bonds. Unlike Doxil, cryo-TEM of Comirnaty NPs revealed a granular, solid core enclosed by mono- and bilayers. Negative staining TEM shows 2-5 nm electron-dense spots in the liposom's interior that are aligned into strings, semicircles, or labyrinth-like networks, which may imply crosslink-stabilized supercoils. The neutral intra-LNP core questions the dominance of ionic interactions holding together this scaffold, raising the alternative possibility of hydrogen bonding between the mRNA and the lipids. Such interaction, described previously for another mRNA/lipid complex, is consistent with the steric structure of ionizable lipid in Comirnaty, ALC-0315, displaying free =O and -OH groups. It is hypothesized that the latter groups can get into steric positions that enable hydrogen bonding with the nitrogenous bases in the mRNA. These newly recognized structural features of mRNA-LNP may be important for the vaccine's efficacy.

14.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-518843

RESUMO

The first 2 years of the COVID-19 pandemic were mainly characterized by convergent evolution of mutations of SARS-CoV-2 Spike protein at residues K417, L452, E484, N501 and P681 across different variants of concern (Alpha, Beta, Gamma, and Delta). Since Spring 2022 and the third year of the pandemic, with the advent of Omicron and its sublineages, convergent evolution has led to the observation of different lineages acquiring an additional group of mutations at different amino acid residues, namely R346, K444, N450, N460, F486, F490, Q493, and S494. Mutations at these residues have become increasingly prevalent during Summer and Autumn 2022, with combinations showing increased fitness. The most likely reason for this convergence is the selective pressure exerted by previous infection- or vaccine-elicited immunity. Such accelerated evolution has caused failure of all anti-Spike monoclonal antibodies, including bebtelovimab and cilgavimab. While we are learning how fast coronaviruses can mutate and recombine, we should reconsider opportunities for economically sustainable escape-proof combination therapies, and reevaluate the potential for polyclonal therapies (such as COVID19 convalescent plasma) in immunocompromised patients.

15.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-518956

RESUMO

Protein is the building block for all organisms. Protein structure prediction is always a complicated task in the field of proteomics. DNA and protein databases can find the primary sequence of the peptide chain and even similar sequences in different proteins. Mainly, there are two methodologies based on the presence or absence of a template for Protein structure prediction. Template-based structure prediction (threading and homology modeling) and Template-free structure prediction (ab initio). Numerous web-based servers that either use templates or do not can help us forecast the structure of proteins. In this current study, ORF7a, a transmembrane protein of the SARS-coronavirus, is predicted using Phyre2, IntFOLD, and Robetta. The protein sequence is straightforwardly entered into the sequence bar on all three web servers. Their findings provided information on the domain, the region with the disorder, the global and local quality score, the predicted structure, and the estimated error plot. Our study presents the structural details of the SARS-CoV protein ORF7a. This immunomodulatory component binds to immune cells and induces severe inflammatory reactions.

16.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-518937

RESUMO

The major concern of COVID-19 therapeutic monoclonal antibodies is the loss of efficacy to continuously emerging SARS-CoV-2 variants. To predict the antibodies efficacy to the future Omicron subvariants, we conducted deep mutational scanning (DMS) encompassing all single mutations in the receptor binding domain of BA.2 strain. In case of bebtelovimab that preserves neutralization activity against BA.2 and BA.5, broad range of amino acid substitutions at K444, V445 and G446 and some substitutions at P499 and T500 were indicated to achieve the antibody escape. Among currently increasing subvariants, BA2.75 carrying G446S partly and XBB with V445P and BQ.1 with K444T completely evade the neutralization of bebtelovimab, consistent with the DMS results. DMS can comprehensively characterize the antibody escape for efficient and effective management of future variants.

17.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-518963

RESUMO

The continuous evolution of SARS-CoV-2 strains is contributing to the prolongation of the global pandemic. We previously reported the prevention or more rapid clearance of SARS-CoV-2 from the nasal turbinates and lungs of susceptible K18-hACE2 mice that had been vaccinated intranasally (IN) rather than intramuscularly (IM) with a recombinant MVA (rMVA) expressing a modified S protein of the ancestor SARS-CoV-2 strain. Here, we constructed additional rMVAs and pseudoviruses expressing modified S protein of SARS-CoV-2 variants and compared the ability of vaccines with S proteins that were matched or mismatched to neutralize variants, bind to S proteins and protect K18-hACE2 mice against SARS-CoV-2 challenge. Although vaccines with matched S proteins induced higher neutralizing antibodies, vaccines with mismatched S proteins still protected against severe disease and reduced virus and mRNAs in the lungs and nasal turbinates, though not as well as vaccines with matched S proteins. In mice earlier primed and boosted with rMVA expressing ancestral S, antibodies to the latter increased after one immunization with rMVA expressing Omicron S, but neutralizing antibody to Omicron required a second immunization. Passive transfer of Wuhan immune serum with Omicron S binding but undetectable neutralizing activities reduced infection of the lungs by the variant. Notably, the reduction in infection of the nasal turbinates and lungs was significantly greater when the rMVAs were administered IN rather than IM and this held true for vaccines that were matched or mismatched to the challenge SARS-CoV-2.

18.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-519085

RESUMO

In late 2022, although the SARS-CoV-2 Omicron subvariants have highly diversified, some lineages have convergently acquired amino acid substitutions at five critical residues in the spike protein. Here, we illuminated the evolutionary rules underlying the convergent evolution of Omicron subvariants and the properties of one of the latest lineages of concern, BQ.1.1. Our phylogenetic and epidemic dynamics analyses suggest that Omicron subvariants independently increased their viral fitness by acquiring the convergent substitutions. Particularly, BQ.1.1, which harbors all five convergent substitutions, shows the highest fitness among the viruses investigated. Neutralization assays show that BQ.1.1 is more resistant to breakthrough BA.2/5 infection sera than BA.5. The BQ.1.1 spike exhibits enhanced binding affinity to human ACE2 receptor and greater fusogenicity than the BA.5 spike. However, the pathogenicity of BQ.1.1 in hamsters is comparable to or even lower than that of BA.5. Our multiscale investigations provide insights into the evolutionary trajectory of Omicron subvariants.

19.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-519151

RESUMO

Entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into host cells depends on refolding of the virus-encoded spike protein from a prefusion conformation, metastable after cleavage, to a lower energy, stable postfusion conformation. This transition overcomes kinetic barriers for fusion of viral and target cell membranes. We report here a cryo-EM structure of the intact postfusion spike in a lipid bilayer that represents single-membrane product of the fusion reaction. The structure provides structural definition of the functionally critical membrane-interacting segments, including the fusion peptide and transmembrane anchor. The internal fusion peptide forms a hairpin-like wedge that spans almost the entire lipid bilayer and the transmembrane segment wraps around the fusion peptide at the last stage of membrane fusion. These results advance our understanding of the spike protein in a membrane environment and may guide development of intervention strategies.

20.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-518997

RESUMO

Recent advancements in the use of single-cell technologies in large cohort studies enable the investigation of cellular response and mechanisms associated with disease outcome, including COVID-19. Several efforts have been made using single-cell RNA-sequencing to better understand the immune response to COVID-19 virus infection. Nonetheless, it is often difficult to compare or integrate data from multiple data sets due to challenges in data normalisation, metadata harmonisation, and having a common interface to quickly query and access this vast amount of data. Here we present Covidscope (http://covidsc.d24h.hk/), a well-curated open web resource that currently contains single-cell gene expression data and associated metadata of almost 5 million blood and immune cells extracted from almost 1,000 COVID-19 patients across 20 studies around the world. Our collection contains the integrated data with harmonised metadata and multi-level cell type annotations. By combining NoSQL and optimised index, our Covidscope achieves rapid subsetting of high-dimensional gene expression data based on both data set level, donor-level (e.g., age and sex of patients) and cell-level (e.g., expression of specific gene markers) metadata, enabling multiple efficient downstream single-cell meta-analysis.

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