CoV-Spectrum: analysis of globally shared SARS-CoV-2 data to identify and characterize new variants

CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning

BACKGROUND

Literature about SARS-CoV-2 widely discusses the effects of variations that have spread in the past 3 years. Such information is dispersed in the texts of several research articles, hindering the possibility of practically integrating it with related datasets (e.g., millions of SARS-CoV-2 sequences available to the community). We aim to fill this gap, by mining literature abstracts to extract-for each variant/mutation-its related effects (in epidemiological, immunological, clinical, or viral kinetics terms) with labeled higher/lower levels in relation to the nonmutated virus.

RESULTS

The proposed framework comprises (i) the provisioning of abstracts from a COVID-19-related big data corpus (CORD-19) and (ii) the identification of mutation/variant effects in abstracts using a GPT2-based prediction model. The above techniques enable the prediction of mutations/variants with their effects and levels in 2 distinct scenarios: (i) the batch annotation of the most relevant CORD-19 abstracts and (ii) the on-demand annotation of any user-selected CORD-19 abstract through the CoVEffect web application (http://gmql.eu/coveffect), which assists expert users with semiautomated data labeling. On the interface, users can inspect the predictions and correct them; user inputs can then extend the training dataset used by the prediction model. Our prototype model was trained through a carefully designed process, using a minimal and highly diversified pool of samples.

CONCLUSIONS

The CoVEffect interface serves for the assisted annotation of abstracts, allowing the download of curated datasets for further use in data integration or analysis pipelines. The overall framework can be adapted to resolve similar unstructured-to-structured text translation tasks, which are typical of biomedical domains.

Surveillance and Analysis of SARS-CoV-2 Variant Importation - China, January-June 2022

Introduction

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant is the dominant circulating strain worldwide. To assess the importation of SARS-CoV-2 variants in the mainland of China during the Omicron epidemic, the genomic surveillance data of SARS-CoV-2 from imported coronavirus disease 2019 (COVID-19) cases in the mainland of China during the first half of 2022 were analyzed.

Methods

Sequences submitted from January to July 2022, with a collection date before June 30, 2022, were incorporated. The proportions of SARS-CoV-2 variants as well as the relationships between the origin and destination of each Omicron imported case were analyzed.

Results

4,946 sequences of imported cases were submitted from 27 provincial-level administrative divisions (PLADs), and the median submission interval was within 1 month after collection. In 3,851 Omicron sequences with good quality, 1 recombinant (XU) and 4 subvariants under monitoring (BA.4, BA.5, BA.2.12.1, and BA.2.13) were recorded, and 3 of them (BA.4, BA.5, and BA.2.12.1) caused local transmissions in the mainland of China later than that recorded in the surveillance. Omicron subvariants dominated in the first half of 2022 and shifted from BA.1 to BA.2 then to BA.4 and BA.5. The percentage of BA.2 in the imported SARS-CoV-2 surveillance data was far higher than that in the Global Initiative on Sharing All Influenza Data (GISAID). The imported cases from Hong Kong Special Administrative Region, China, accounted for 32.30% of Omicron cases sampled, and 98.71% of them were BA.2.

Conclusions

The Omicron variant showed the intra-Omicron evolution in the first half of 2022, and all of the Omicron subvariants were introduced into the mainland of China multiple times from multiple different locations.

Quasispecies Analysis of SARS-CoV-2 of 15 Different Lineages during the First Year of the Pandemic Prompts Scratching under the Surface of Consensus Genome Sequences

The tremendous majority of SARS-CoV-2 genomic data so far neglected intra-host genetic diversity. Here, we studied SARS-CoV-2 quasispecies based on data generated by next-generation sequencing (NGS) of complete genomes. SARS-CoV-2 raw NGS data had been generated for nasopharyngeal samples collected between March 2020 and February 2021 by the Illumina technology on a MiSeq instrument, without prior PCR amplification. To analyze viral quasispecies, we designed and implemented an in-house Excel file (“QuasiS”) that can characterize intra-sample nucleotide diversity along the genomes using data of the mapping of NGS reads. We compared intra-sample genetic diversity and global genetic diversity available from Nextstrain. Hierarchical clustering of all samples based on the intra-sample genetic diversity was performed and visualized with the Morpheus web application. NGS mapping data from 110 SARS-CoV-2-positive respiratory samples characterized by a mean depth of 169 NGS reads/nucleotide position and for which consensus genomes that had been obtained were classified into 15 viral lineages were analyzed. Mean intra-sample nucleotide diversity was 0.21 ± 0.65%, and 5357 positions (17.9%) exhibited significant (>4%) diversity, in ≥2 genomes for 1730 (5.8%) of them. ORF10, spike, and N genes had the highest number of positions exhibiting diversity (0.56%, 0.34%, and 0.24%, respectively). Nine hot spots of intra-sample diversity were identified in the SARS-CoV-2 NSP6, NSP12, ORF8, and N genes. Hierarchical clustering delineated a set of six genomes of different lineages characterized by 920 positions exhibiting intra-sample diversity. In addition, 118 nucleotide positions (0.4%) exhibited diversity at both intra- and inter-patient levels. Overall, the present study illustrates that the SARS-CoV-2 consensus genome sequences are only an incomplete and imperfect representation of the entire viral population infecting a patient, and that quasispecies analysis may allow deciphering more accurately the viral evolutionary pathways.

Molecular Epidemiology of the Norwegian SARS-CoV-2 Delta Lineage AY.63

Extensive genomic surveillance has given great insights into the evolution of the SARS-CoV-2 virus and emerging variants. During the summer months of 2021, Norway was dominated by the Pango lineage AY.63 which is a sub-lineage of the highly transmissible Delta variant. Strikingly, AY.63 did not spread in other countries to any significant extent. AY.63 carried a key mutation, A222V, in the spike protein, as well as the deletion of three residues in nsp1. Although these mutations are close to functionally important areas, we did not find any evidence that they induced higher fitness compared to other Delta lineages. This variant was introduced to Norway at a time when there were low levels of SARS-CoV-2 and contact-reducing measures were relaxed, which probably explains why the lineage rose so quickly. Furthermore, we found that the lack of imports of AY.63 from other countries probably led to the eventual demise of the lineage in Norway.

An imported human case with the SARS-CoV-2 Omicron subvariant BA.2.75 in Yunnan Province, China

The Omicron variants spread rapidly worldwide after being initially detected in South Africa in November 2021. It showed increased transmissibility and immune evasion with far more amino acid mutations in the spike (S) protein than the previously circulating variants of concern (VOCs). Notably, on 15 July 2022, we monitored the first VOC / Omicron subvariant BA.2.75 in China from an imported case. Moreover, nowadays, this subvariant still is predominant in India. It has nine additional mutations in the S protein compared to BA.2, three of which (W152R, G446S, and R493Q reversion) might contribute to higher transmissibility and immune escape. This subvariant could cause wider spread and pose a threat to the global situation. Our timely reporting and continuous genomic analysis are essential to fully elucidate the characteristics of the subvariant BA.2.75 in the future.

Modelling the dynamics of infection, waning of immunity and re-infection with the Omicron variant of SARS-CoV-2 in Aotearoa New Zealand

Aotearoa New Zealand experienced a wave of the Omicron variant of SARS-CoV-2 in 2022 with around 200 confirmed cases per 1000 people between January and May. Waning of infection-derived immunity means people become increasingly susceptible to re-infection with SARS-CoV-2 over time. We investigated a model that included waning of vaccine-derived and infection-derived immunity under scenarios representing different levels of behavioural change relative to the first Omicron wave. Because the durability of infection-derived immunity is a key uncertainty in epidemiological models, we investigated outcomes under different assumptions about the speed of waning. The model was used to provide scenarios to the New Zealand Government, helping to inform policy response and healthcare system preparedness ahead of the winter respiratory illness season. In all scenarios investigated, a second Omicron wave was projected to occur in the second half of 2022. The timing of the peak depended primarily on the speed of waning and was typically between August and November. The peak number of daily infections in the second Omicron wave was smaller than in the first Omicron wave. Peak hospital occupancy was also generally lower than in the first wave but was sensitive to the age distribution of infections. A scenario with increased contact rates in older groups had higher peak hospital occupancy than the first wave. Scenarios with relatively high transmission, whether a result of relaxation of control measures or voluntary behaviour change, did not necessarily lead to higher peaks. However, they generally resulted in more sustained healthcare demand (>250 hospital beds throughout the winter period). The estimated health burden of Covid-19 in the medium term is sensitive to the strength and durability of infection-derived and hybrid immunity against reinfection and severe illness, which are uncertain.

The Omicron-transformer: Rise of the subvariants in the age of vaccines

Introduction: Omicron is the latest SARS-CoV-2 variant of concern, the pathogen that causes COVID-19. Since its emergence in late 2021, Omicron has displaced other circulating variants and caused successive waves of infection worldwide throughout 2022. Omicron is characterised by the rapid emergence of many subvariants and high rates of infection in people with vaccine- and/or infection-induced immunity. This review article will consolidate current knowledge regarding Omicron subvariants, the role of boosters, and future vaccine development. Method: This narrative review is based on a literature search using PubMed. Search terms related to Omicron were used and priority was given to published peer-reviewed articles over pre-prints. Results: Studies indicate that vaccinations and boosters are important to reduce disease severity, hospitalisation and death from Omicron. A variety of factors, such as differing host factors, circulating variants, and forces of infection, can influence the benefit of repeated booster administration. Next-generation bivalent vaccines have now been approved in some countries including Singapore and have demonstrated the ability to induce broad variant protection. Future third-generation vaccines involving mucosal vaccines and/or pan-sarbecovirus vaccines may provide broader and longer-lasting protection. Conclusion: Due to current high levels of vaccine- and infection-induced immunity, it is likely that rates of severe illness, hospitalisation, and death due to Omicron will continue to moderate. Nevertheless, the virus is ever-changing, and public health policies, especially those related to vaccinations, will also have to continually evolve and adapt as COVID-19 transitions to endemicity. Keywords: Booster, COVID-19, infectious diseases, Omicron, vaccine

Structural basis for the broad and potent cross-reactivity of an N501Y-centric antibody against sarbecoviruses

More than 80% of SARS-CoV-2 variants, including Alpha and Omicron, contain an N501Y mutation in the receptor-binding domain (RBD) of the spike protein. The N501Y change is an adaptive mutation enabling tighter interaction with the human ACE2 receptor. We have developed a broadly neutralizing antibody (nAb), D27LEY, whose binding affinity was intentionally optimized for Y501. This N501Y-centric antibody not only interacts with the Y501-containing RBDs of SARS-CoV-2 variants, including Omicron, with pico- or subnanomolar binding affinity, but also binds tightly to the RBDs with a different amino acid at residue 501. The crystal structure of the Fab fragment of D27LEY bound to the RBD of the Alpha variant reveals that the Y501-containing loop adopts a ribbon-like topology and serves as a small but major epitope in which Y501 is a part of extensive intermolecular interactions. A hydrophobic cleft on the most conserved surface of the RBD core serves as another major binding epitope. These data explain the broad and potent cross-reactivity of this N501Y-centric antibody, and suggest that a vaccine antigenic component composed of the RBD core and a part of receptor-binding motif (RBM) containing tyrosine at residue 501 might elicit broad and potent humoral responses across sarbecoviruses.

Taxonium, a web-based tool for exploring large phylogenetic trees

The COVID-19 pandemic has resulted in a step change in the scale of sequencing data, with more genomes of SARS-CoV-2 having been sequenced than any other organism on earth. These sequences reveal key insights when represented as a phylogenetic tree, which captures the evolutionary history of the virus, and allows the identification of transmission events and the emergence of new variants. However, existing web-based tools for exploring phylogenies do not scale to the size of datasets now available for SARS-CoV-2. We have developed Taxonium, a new tool that uses WebGL to allow the exploration of trees with tens of millions of nodes in the browser for the first time. Taxonium links each node to associated metadata and supports mutation-annotated trees, which are able to capture all known genetic variation in a dataset. It can either be run entirely locally in the browser, from a server-based backend, or as a desktop application. We describe insights that analysing a tree of five million sequences can provide into SARS-CoV-2 evolution, and provide a tool at cov2tree.org for exploring a public tree of more than five million SARS-CoV-2 sequences. Taxonium can be applied to any tree, and is available at taxonium.org, with source code at github.com/theosanderson/taxonium.

Global Distribution, Dispersal Patterns, and Trend of Several Omicron Subvariants of SARS-CoV-2 across the Globe

Our study aims to describe the global distribution and dispersal patterns of the SARS-CoV-2 Omicron subvariants. Genomic surveillance data were extracted from the CoV-Spectrum platform, searching for BA.1*, BA.2*, BA.3*, BA.4*, and BA.5* variants by geographic region. BA.1* increased in November 2021 in South Africa, with a similar increase across all continents in early December 2021. BA.1* did not reach 100% dominance in all continents. The spread of BA.2*, first described in South Africa, differed greatly by geographic region, in contrast to BA.1*, which followed a similar global expansion, firstly occurring in Asia and subsequently in Africa, Europe, Oceania, and North and South America. BA.4* and BA.5* followed a different pattern, where BA.4* reached high proportions (maximum 60%) only in Africa. BA.5* is currently, by Mid-August 2022, the dominant strain, reaching almost 100% across Europe, which is the first continent aside from Africa to show increasing proportions, and Asia, the Americas, and Oceania are following. The emergence of new variants depends mostly on their selective advantage, translated as enhanced transmissibility and ability to invade people with existing immunity. Describing these patterns is useful for a better understanding of the epidemiology of the VOCs' transmission and for generating hypotheses about the future of emerging variants.

Evolution of a globally unique SARS-CoV-2 Spike E484T monoclonal antibody escape mutation in a persistently infected, immunocompromised individual

Prolonged infections in immunocompromised individuals may be a source for novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants, particularly when both the immune system and antiviral therapy fail to clear the infection and enable within-host evolution. Here we describe a 486-day case of SARS-CoV-2 infection in an immunocompromised individual. Following monotherapy with the monoclonal antibody Bamlanivimab, the individual's virus acquired resistance, likely via the earliest known occurrence of Spike amino acid variant E484T. Recently, E484T has arisen again as a derivative of E484A in the Omicron Variant of Concern, supporting the hypothesis that prolonged infections can give rise to novel variants long before they become prevalent in the human population.

A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike

A major challenge in understanding SARS-CoV-2 evolution is interpreting the antigenic and functional effects of emerging mutations in the viral spike protein. Here we describe a new deep mutational scanning platform based on non-replicative pseudotyped lentiviruses that directly quantifies how large numbers of spike mutations impact antibody neutralization and pseudovirus infection. We demonstrate this new platform by making libraries of the Omicron BA.1 and Delta spikes. These libraries each contain ~7000 distinct amino-acid mutations in the context of up to ~135,000 unique mutation combinations. We use these libraries to map escape mutations from neutralizing antibodies targeting the receptor binding domain, N-terminal domain, and S2 subunit of spike. Overall, this work establishes a high-throughput and safe approach to measure how ~10 5 combinations of mutations affect antibody neutralization and spike-mediated infection. Notably, the platform described here can be extended to the entry proteins of many other viruses.

Characterization of the enhanced infectivity and antibody evasion of Omicron BA.2.75

Recently emerged SARS-CoV-2 Omicron subvariant, BA.2.75, displayed a growth advantage over circulating BA.2.38, BA.2.76, and BA.5 in India. However, the underlying mechanisms for enhanced infectivity, especially compared with BA.5, remain unclear. Here, we show that BA.2.75 exhibits substantially higher affinity for host receptor angiotensin-converting enzyme 2 (ACE2) than BA.5 and other variants. Structural analyses of BA.2.75 spike shows its decreased thermostability and increased frequency of the receptor binding domain (RBD) in the "up" conformation under acidic conditions, suggesting enhanced low-pH-endosomal cell entry. Relative to BA.4/BA.5, BA.2.75 exhibits reduced evasion of humoral immunity from BA.1/BA.2 breakthrough-infection convalescent plasma but greater evasion of Delta breakthrough-infection convalescent plasma. BA.5 breakthrough-infection plasma also exhibits weaker neutralization against BA.2.75 than BA.5, mainly due to BA.2.75's distinct neutralizing antibody (NAb) escape pattern. Antibody therapeutics Evusheld and Bebtelovimab remain effective against BA.2.75. These results suggest BA.2.75 may prevail after BA.4/BA.5, and its increased receptor-binding capability could support further immune-evasive mutations.

Potential intervariant and intravariant recombination of Delta and Omicron variants

Among numerous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concerns, Omicron is more infectious and immune-escaping, while Delta is more pathogenic. Here, we provide evidence for both intervariant and intravariant recombination of the rapidly evolving new SARS-CoV-2 genomes, including XD/XE/XF and BA.3, raising concerns of potential more infectious, immune-escaping, and disease-causing Omicron and Delta-Omicron variants.

Prevalence and risk factors of sleep disturbance in adults with underlying health conditions during the ongoing COVID-19 pandemic

To determine the prevalence of sleep disturbance during the coronavirus disease 2019 (COVID-19) pandemic among US adults who are more vulnerable to complications because of age and co-morbid conditions, and to identify associated sociodemographic and psychosocial factors. Cross-sectional survey linked to 3 active clinical trials and 2 cohort studies, conducted between 11/30/2020 and 3/3/2021. Five academic internal medicine practices and 2 federally qualified health centers. A total of 715 adults ages 23 to 91 years living with one or more chronic conditions. A fifth (20%) of participants reported poor sleep. Black adults were twice as likely to report poor sleep compared to Whites. Self-reported poor physical function (51%), stress (42%), depression (28%), and anxiety (36%) were also common and all significantly associated with poor sleep. Age ≥70 years and having been vaccinated for COVID-19 were protective against poor sleep. Sex, education, income, alcohol use, and employment status were not significantly associated with sleep quality. In this diverse sample of adults with chronic conditions, by race, ethnicity, and socioeconomic status, disparities in sleep health amid the ongoing pandemic were apparent. Worse physical function and mental health were associated with poor sleep and should be considered targets for health system interventions to prevent the many subsequent consequences of disturbed sleep on health outcomes. Measurements: self-reported sleep quality, physical function, stress, depression, and anxiety.

Determinants of Spike infectivity, processing, and neutralization in SARS-CoV-2 Omicron subvariants BA.1 and BA.2

SARS-CoV-2 Omicron rapidly outcompeted other variants and currently dominates the COVID-19 pandemic. Its enhanced transmission and immune evasion are thought to be driven by numerous mutations in the Omicron Spike protein. Here, we systematically introduced BA.1 and/or BA.2 Omicron Spike mutations into the ancestral Spike protein and examined the impacts on Spike function, processing, and susceptibility to neutralization. Individual mutations of S371F/L, S375F, and T376A in the ACE2-receptor-binding domain as well as Q954H and N969K in the hinge region 1 impaired infectivity, while changes to G339D, D614G, N764K, and L981F moderately enhanced it. Most mutations in the N-terminal region and receptor-binding domain reduced the sensitivity of the Spike protein to neutralization by sera from individuals vaccinated with the BNT162b2 vaccine and by therapeutic antibodies. Our results represent a systematic functional analysis of Omicron Spike adaptations that have allowed this SARS-CoV-2 variant to dominate the current pandemic.

CovRadar: continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance

SUMMARY

The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast.

AVAILABILITY AND IMPLEMENTATION

CovRadar is freely accessible at https://covradar.net, its open-source code is available at https://gitlab.com/dacs-hpi/covradar.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

SARS-CoV-2 genomic epidemiology: data and sequencing infrastructure

Background: Genomic surveillance of SARS-CoV-2 is critical in monitoring viral lineages. Available data reveal a significant gap between low- and middle-income countries and the rest of the world. Methods: The SARS-CoV-2 sequencing costs using the Oxford Nanopore MinION device and hardware prices for data computation in Lebanon were estimated and compared with those in developed countries. SARS-CoV-2 genomes deposited on the Global Initiative on Sharing All Influenza Data per 1000 COVID-19 cases were determined per country. Results: Sequencing costs in Lebanon were significantly higher compared with those in developed countries. Low- and middle-income countries showed limited sequencing capabilities linked to the lack of support, high prices, long delivery delays and limited availability of trained personnel. Conclusion: The authors recommend the mobilization of funds to develop whole-genome sequencing-based surveillance platforms and the implementation of genomic epidemiology to better identify and track outbreaks, leading to appropriate and mindful interventions.

Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival

OBJECTIVES

More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain.

METHODS

A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis.

RESULTS

A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins.

CONCLUSIONS

This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.

SARS-CoV-2 Variability in Patients and Wastewaters—Potential Immuno-Modulation during the Shift from Delta to Omicron

The continuous emergence of SARS-CoV-2 variants favors potential co-infections and/or viral mutation events, leading to possible new biological properties. The aim of this work was to characterize SARS-CoV-2 genetic variability during the Delta–Omicron shift in patients and in a neighboring wastewater treatment plant (WWTP) in the same urban area. The surveillance of SARS-CoV-2 was performed by routine screening of positive samples by single nucleotide polymorphism analysis within the S gene. Moreover, additionally to national systematic whole genome sequencing (WGS) once a week in SARS-CoV-2-positive patients, WGS was also applied when mutational profiles were difficult to interpret by routine screening. Thus, WGS was performed on 414 respiratory samples and on four wastewater samples, northeastern France. This allowed us to report (i) the temporally concordant Delta to Omicron viral shift in patients and wastewaters; (ii) the characterization of 21J (Delta) and 21K (Omicron)/BA.1-21L (Omicron)/BA.2-BA.4 mixtures from humans or environmental samples; (iii) the mapping of composite mutations and the predicted impact on immune properties in the viral Spike protein.

Lineage BA.2 dominated the Omicron SARS-CoV-2 epidemic wave in the Philippines

The Omicron severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant led to a dramatic global epidemic wave following detection in South Africa in November 2021. The BA.1 Omicron lineage was dominant and responsible for most SARS-CoV-2 outbreaks in countries around the world during December 2021-January 2022, while other Omicron lineages, including BA.2, accounted for the minority of global isolates. Here, we describe the Omicron wave in the Philippines by analysing genomic data. Our results identify the presence of both BA.1 and BA.2 lineages in the Philippines in December 2021, before cases surged in January 2022. We infer that only the BA.2 lineage underwent sustained transmission in the country, with an estimated emergence around 18 November 2021 (95 per cent highest posterior density: 6-28 November), while despite multiple introductions, BA.1 transmission remained limited. These results suggest that the Philippines was one of the earliest areas affected by BA.2 and reiterate the importance of whole genome sequencing for monitoring outbreaks.

Within-host genetic diversity of SARS-CoV-2 in the context of large-scale hospital-associated genomic surveillance

The COVID-19 pandemic has resulted in extensive surveillance of the genomic diversity of SARS-CoV-2. Sequencing data generated as part of these efforts can also capture the diversity of the SARS-CoV-2 virus populations replicating within infected individuals. To assess this within-host diversity of SARS-CoV-2 we quantified low frequency (minor) variants from deep sequence data of thousands of clinical samples collected by a large urban hospital system over the course of a year. Using a robust analytical pipeline to control for technical artefacts, we observe that at comparable viral loads, specimens from patients hospitalized due to COVID-19 had a greater number of minor variants than samples from outpatients. Since individuals with highly diverse viral populations could be disproportionate drivers of new viral lineages in the patient population, these results suggest that transmission control should pay special attention to patients with severe or protracted disease to prevent the spread of novel variants.

Development and Validation of an In-House Real-Time Reverse-Transcriptase Polymerase Chain Reaction Assay for SARS-CoV-2 Omicron Lineage Subtyping between BA.1 and BA.2

In order to rapidly differentiate sublineages BA.1 and BA.2 of the SARS-CoV-2 variant of concern Omicron, we developed a real-time reverse-transcriptase polymerase chain reaction to target the discriminatory spike protein deletion at amino acid position 69–70 (S:del69–70). Compared to the gold standard of whole genome sequencing, the candidate assay was 100% sensitive and 99.4% specific. Sublineage typing by RT-PCR can provide a rapid, high throughput and cost-effective method to enhance surveillance as well as potentially guiding treatment and infection control decisions.

Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.

Antibody and T-cellular response to COVID-19 booster vaccine in SARS-CoV-1 survivors

The severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) survivors are more likely to produce a potent immune response to SARS-CoV-2 after booster vaccination. We assessed humoral and T cell responses against SARS-CoV-2 in previously vaccinated SARS-CoV-1 survivors and naïve healthy individuals (NHIs) after a booster Ad5-nCoV dose. Boosted SARS-CoV-1 survivors had a high neutralization of SARS-CoV-2 Wuhan-Hu-1 (WA1), Beta, and Delta but is limited to Omicron subvariants (BA.1, BA.2, BA.2.12.1, and BA.4/BA.5). Most boosted SARS-CoV-1 survivors had robust SARS-CoV-2-specific CD4⁺ and CD8⁺ T cell responses. While booster vaccination in NHIs elicited less or ineffective neutralization of WA1, Beta, and Delta, and none of them induced neutralizing antibodies against Omicron subvariants. However, they developed comparable SARS-CoV-2-specific T cell responses compared to boosted SARS-CoV-1 survivors. These findings suggest that boosted Ad5-nCoV would not elicit effective neutralizing antibodies against Omicron subvariants in SARS-CoV-1 survivors and NHIs but induced comparable robust T cell responses. Achieving a high antibody titer in SARS-CoV-1 survivors and NHIs is desirable to generate broad neutralization.

Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.

BA.2.12.1, BA.4 and BA.5 escape antibodies elicited by Omicron infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron sublineages BA.2.12.1, BA.4 and BA.5 exhibit higher transmissibility than the BA.2 lineage1. The receptor binding and immune-evasion capability of these recently emerged variants require immediate investigation. Here, coupled with structural comparisons of the spike proteins, we show that BA.2.12.1, BA.4 and BA.5 (BA.4 and BA.5 are hereafter referred collectively to as BA.4/BA.5) exhibit similar binding affinities to BA.2 for the angiotensin-converting enzyme 2 (ACE2) receptor. Of note, BA.2.12.1 and BA.4/BA.5 display increased evasion of neutralizing antibodies compared with BA.2 against plasma from triple-vaccinated individuals or from individuals who developed a BA.1 infection after vaccination. To delineate the underlying antibody-evasion mechanism, we determined the escape mutation profiles2, epitope distribution3 and Omicron-neutralization efficiency of 1,640 neutralizing antibodies directed against the receptor-binding domain of the viral spike protein, including 614 antibodies isolated from people who had recovered from BA.1 infection. BA.1 infection after vaccination predominantly recalls humoral immune memory directed against ancestral (hereafter referred to as wild-type (WT)) SARS-CoV-2 spike protein. The resulting elicited antibodies could neutralize both WT SARS-CoV-2 and BA.1 and are enriched on epitopes on spike that do not bind ACE2. However, most of these cross-reactive neutralizing antibodies are evaded by spike mutants L452Q, L452R and F486V. BA.1 infection can also induce new clones of BA.1-specific antibodies that potently neutralize BA.1. Nevertheless, these neutralizing antibodies are largely evaded by BA.2 and BA.4/BA.5 owing to D405N and F486V mutations, and react weakly to pre-Omicron variants, exhibiting narrow neutralization breadths. The therapeutic neutralizing antibodies bebtelovimab4 and cilgavimab5 can effectively neutralize BA.2.12.1 and BA.4/BA.5, whereas the S371F, D405N and R408S mutations undermine most broadly sarbecovirus-neutralizing antibodies. Together, our results indicate that Omicron may evolve mutations to evade the humoral immunity elicited by BA.1 infection, suggesting that BA.1-derived vaccine boosters may not achieve broad-spectrum protection against new Omicron variants.

BA.2.12.1, BA.4 and BA.5 escape antibodies elicited by Omicron infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron sublineages BA.2.12.1, BA.4 and BA.5 exhibit higher transmissibility than the BA.2 lineage1. The receptor binding and immune-evasion capability of these recently emerged variants require immediate investigation. Here, coupled with structural comparisons of the spike proteins, we show that BA.2.12.1, BA.4 and BA.5 (BA.4 and BA.5 are hereafter referred collectively to as BA.4/BA.5) exhibit similar binding affinities to BA.2 for the angiotensin-converting enzyme 2 (ACE2) receptor. Of note, BA.2.12.1 and BA.4/BA.5 display increased evasion of neutralizing antibodies compared with BA.2 against plasma from triple-vaccinated individuals or from individuals who developed a BA.1 infection after vaccination. To delineate the underlying antibody-evasion mechanism, we determined the escape mutation profiles2, epitope distribution3 and Omicron-neutralization efficiency of 1,640 neutralizing antibodies directed against the receptor-binding domain of the viral spike protein, including 614 antibodies isolated from people who had recovered from BA.1 infection. BA.1 infection after vaccination predominantly recalls humoral immune memory directed against ancestral (hereafter referred to as wild-type (WT)) SARS-CoV-2 spike protein. The resulting elicited antibodies could neutralize both WT SARS-CoV-2 and BA.1 and are enriched on epitopes on spike that do not bind ACE2. However, most of these cross-reactive neutralizing antibodies are evaded by spike mutants L452Q, L452R and F486V. BA.1 infection can also induce new clones of BA.1-specific antibodies that potently neutralize BA.1. Nevertheless, these neutralizing antibodies are largely evaded by BA.2 and BA.4/BA.5 owing to D405N and F486V mutations, and react weakly to pre-Omicron variants, exhibiting narrow neutralization breadths. The therapeutic neutralizing antibodies bebtelovimab4 and cilgavimab5 can effectively neutralize BA.2.12.1 and BA.4/BA.5, whereas the S371F, D405N and R408S mutations undermine most broadly sarbecovirus-neutralizing antibodies. Together, our results indicate that Omicron may evolve mutations to evade the humoral immunity elicited by BA.1 infection, suggesting that BA.1-derived vaccine boosters may not achieve broad-spectrum protection against new Omicron variants.

Recombination in Coronaviruses, with a Focus on SARS-CoV-2

Recombination is a common evolutionary tool for RNA viruses, and coronaviruses are no exception. We review here the evidence for recombination in SARS-CoV-2 and reconcile nomenclature for recombinants, discuss their origin and fitness, and speculate how recombinants could make a difference in the future of the COVID-19 pandemics.

Enhanced immune activation within the tumor microenvironment and circulation of female high-risk melanoma patients and improved survival with adjuvant CTLA4 blockade compared to males

BACKGROUND

We hypothesized that a gender difference in clinical response may exist to adjuvant CTLA4 blockade with ipilimumab versus high-dose IFNα (HDI). We investigated differences in candidate immune biomarkers in the circulation and tumor microenvironment (TME).

PATIENTS AND METHODS

This gender-based analysis was nested within the E1609 trial that tested adjuvant therapy with ipilimumab 3 mg/kg (ipi3) and 10 mg/kg (ipi10) versus HDI in high risk resected melanoma. We investigated gender differences in treatment efficacy with ipi3 and ipi10 versus HDI while adjusting for age, stage, ECOG performance (PS), ulceration, primary tumor status and lymph node number. Forest plots were created to compare overall survival (OS) and relapse free survival (RFS) between ipi and HDI. Gene expression profiling (GEP) was performed on tumors of 718 (454 male, 264 female) patients. Similarly, serum and peripheral blood mononuclear cells (PBMC) samples were tested for soluble and cellular biomarkers (N = 321 patients; 109 female and 212 male).

RESULTS

The subgroups of female, stage IIIC, PS = 1, ulcerated primary, in-transit metastasis demonstrated significant improvement in RFS and/or OS with ipi3 versus HDI. Female gender was significant for both OS and RFS and was further explored. In the RFS comparison, a multivariate Cox regression model including significant variables indicated a significant interaction between gender and treatment (P = 0.024). In peripheral blood, percentages of CD3+ T cells (P = 0.024) and CD3+ CD4+ helper T cells (P = 0.0001) were higher in females compared to males. Trends toward higher circulating levels of IL1β (P = 0.07) and IL6 (P = 0.06) were also found in females. Males had higher percentages of monocytes (P = 0.03) with trends toward higher percentages of regulatory T cells (T-reg). Tumor GEP analysis supported enhanced infiltration with immune cells including gammadelta T cells (P = 0.005), NK cells (P = 0.01), dendritic cells (P = 0.01), CD4+ T cells (P = 0.03), CD8+ T cells (P = 0.03) and T-reg (P = 0.008) in the tumors of females compared to males and a higher T-effector and IFNγ gene signature score (P = 0.0244).

CONCLUSION

Female gender was associated with adjuvant CTLA4 blockade clinical benefits and female patients were more likely to have evidence of type1 immune activation within the TME and the circulation. Trial registration ClinicalTrials.gov NCT01274338. Registered 11 January 2011, https://www.

CLINICALTRIALS

gov/ct2/show/NCT01274338.

An assessment of the potential impact of the Omicron variant of SARS-CoV-2 in Aotearoa New Zealand

New Zealand delayed the introduction of the Omicron variant of SARS-CoV-2 into the community by the continued use of strict border controls through to January 2022. This allowed time for vaccination rates to increase and the roll out of third doses of the vaccine (boosters) to begin. It also meant more data on the characteristics of Omicron became available prior to the first cases of community transmission. Here we present a mathematical model of an Omicron epidemic, incorporating the effects of the booster roll out and waning of vaccine-induced immunity, and based on estimates of vaccine effectiveness and disease severity from international data. The model considers differing levels of immunity against infection, severe illness and death, and ignores waning of infection-induced immunity. This model was used to provide an assessment of the potential impact of an Omicron wave in the New Zealand population, which helped inform government preparedness and response. At the time the modelling was carried out, the date of introduction of Omicron into the New Zealand community was unknown. We therefore simulated outbreaks with different start dates, as well as investigating different levels of booster uptake. We found that an outbreak starting on 1 February or 1 March led to a lower health burden than an outbreak starting on 1 January because of increased booster coverage, particularly in older age groups. We also found that outbreaks starting later in the year led to worse health outcomes than an outbreak starting on 1 March. This is because waning immunity in older groups started to outweigh the increased protection from higher booster coverage in younger groups. For an outbreak starting on 1 February and with high booster uptake, the number of occupied hospital beds in the model peaked between 800 and 3,300 depending on assumed transmission rates. We conclude that combining an accelerated booster programme with public health measures to flatten the curve are key to avoid overwhelming the healthcare system.

Advancing genomic epidemiology by addressing the bioinformatics bottleneck: Challenges, design principles, and a Swiss example

The SARS-CoV-2 pandemic led to a huge increase in global pathogen genome sequencing efforts, and the resulting data are becoming increasingly important to detect variants of concern, monitor outbreaks, and quantify transmission dynamics. However, this rapid up-scaling in data generation brought with it many IT infrastructure challenges. In this paper, we report about developing an improved system for genomic epidemiology. We (i) highlight key challenges that were exacerbated by the pandemic situation, (ii) provide data infrastructure design principles to address them, and (iii) give an implementation example developed by the Swiss SARS-CoV-2 Sequencing Consortium (S3C) in response to the COVID-19 pandemic. Finally, we discuss remaining challenges to data infrastructure for genomic epidemiology. Improving these infrastructures will help better detect, monitor, and respond to future public health threats.

Mapping Data to Deep Understanding: Making the Most of the Deluge of SARS-CoV-2 Genome Sequences

Next-generation sequencing has been essential to the global response to the COVID-19 pandemic. As of January 2022, nearly 7 million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences are available to researchers in public databases. Sequence databases are an abundant resource from which to extract biologically relevant and clinically actionable information. As the pandemic has gone on, SARS-CoV-2 has rapidly evolved, involving complex genomic changes that challenge current approaches to classifying SARS-CoV-2 variants. Deep sequence learning could be a potentially powerful way to build complex sequence-to-phenotype models. Unfortunately, while they can be predictive, deep learning typically produces "black box" models that cannot directly provide biological and clinical insight. Researchers should therefore consider implementing emerging methods for visualizing and interpreting deep sequence models. Finally, researchers should address important data limitations, including (i) global sequencing disparities, (ii) insufficient sequence metadata, and (iii) screening artifacts due to poor sequence quality control.

Survival among people hospitalized with COVID-19 in Switzerland: a nationwide population-based analysis

BACKGROUND

Increasing age, male sex, and pre-existing comorbidities are associated with lower survival from SARS-CoV-2 infection. The interplay between different comorbidities, age, and sex is not fully understood, and it remains unclear if survival decreases linearly with higher ICU occupancy or if there is a threshold beyond which survival falls.

METHOD

This national population-based study included 22,648 people who tested positive for SARS-CoV-2 infection and were hospitalized in Switzerland between February 24, 2020, and March 01, 2021. Bayesian survival models were used to estimate survival after positive SARS-CoV-2 test among people hospitalized with COVID-19 by epidemic wave, age, sex, comorbidities, and ICU occupancy. Two-way interactions between age, sex, and comorbidities were included to assess the differential risk of death across strata. ICU occupancy was modeled using restricted cubic splines to allow for a non-linear association with survival.

RESULTS

Of 22,648 people hospitalized with COVID-19, 4785 (21.1%) died. The survival was lower during the first epidemic wave than in the second (predicted survival at 40 days after positive test 76.1 versus 80.5%). During the second epidemic wave, occupancy among all available ICU beds in Switzerland varied between 51.7 and 78.8%. The estimated survival was stable at approximately 81.5% when ICU occupancy was below 70%, but worse when ICU occupancy exceeded this threshold (survival at 80% ICU occupancy: 78.2%; 95% credible interval [CrI] 76.1 to 80.1%). Periods with higher ICU occupancy (>70 vs 70%) were associated with an estimated number of 137 (95% CrI 27 to 242) excess deaths. Comorbid conditions reduced survival more in younger people than in older people. Among comorbid conditions, hypertension and obesity were not associated with poorer survival. Hypertension appeared to decrease survival in combination with cardiovascular disease.

CONCLUSIONS

Survival after hospitalization with COVID-19 has improved over time, consistent with improved management of severe COVID-19. The decreased survival above 70% national ICU occupancy supports the need to introduce measures for prevention and control of SARS-CoV-2 transmission in the population well before ICUs are full.

Generalized Methodology for the Quick Prediction of Variant SARS-CoV-2 Spike Protein Binding Affinities with Human Angiotensin-Converting Enzyme II

Variants of the SARS-CoV-2 virus continue to remain a threat 2 years from the beginning of the pandemic. As more variants arise, and the B.1.1.529 (Omicron) variant threatens to create another wave of infections, a method is needed to predict the binding affinity of the spike protein quickly and accurately with human angiotensin-converting enzyme II (ACE2). We present an accurate and convenient energy minimization/molecular mechanics Poisson-Boltzmann surface area methodology previously used with engineered ACE2 therapeutics to predict the binding affinity of the Omicron variant. Without any additional data from the variants discovered after the publication of our first model, the methodology can accurately predict the binding of the spike/ACE2 variant complexes. From this methodology, we predicted that the Omicron variant spike has a Kd of ∼22.69 nM (which is very close to the experimental Kd of 20.63 nM published during the review process of the current report) and that spike protein of the new "Stealth" Omicron variant (BA.2) will display a Kd of ∼12.9 nM with the wild-type ACE2 protein. This methodology can be used with as-yet discovered variants, allowing for quick determinations regarding the variant's infectivity versus either the wild-type virus or its variants.

ATGPred-FL: sequence-based prediction of autophagy proteins with feature representation learning

Autophagy plays an important role in biological evolution and is regulated by many autophagy proteins. Accurate identification of autophagy proteins is crucially important to reveal their biological functions. Due to the expense and labor cost of experimental methods, it is urgent to develop automated, accurate and reliable sequence-based computational tools to enable the identification of novel autophagy proteins among numerous proteins and peptides. For this purpose, a new predictor named ATGPred-FL was proposed for the efficient identification of autophagy proteins. We investigated various sequence-based feature descriptors and adopted the feature learning method to generate corresponding, more informative probability features. Then, a two-step feature selection strategy based on accuracy was utilized to remove irrelevant and redundant features, leading to the most discriminative 14-dimensional feature set. The final predictor was built using a support vector machine classifier, which performed favorably on both the training and testing sets with accuracy values of 94.40% and 90.50%, respectively. ATGPred-FL is the first ATG machine learning predictor based on protein primary sequences. We envision that ATGPred-FL will be an effective and useful tool for autophagy protein identification, and it is available for free at http://lab.malab.cn/~acy/ATGPred-FL , the source code and datasets are accessible at https://github.com/jiaoshihu/ATGPred .

Inferring transmission fitness advantage of SARS-CoV-2 variants of concern from wastewater samples using digital PCR, Switzerland, December 2020 through March 2021

BackgroundThroughout the COVID-19 pandemic, SARS-CoV-2 genetic variants of concern (VOCs) have repeatedly and independently arisen. VOCs are characterised by increased transmissibility, increased virulence or reduced neutralisation by antibodies obtained from prior infection or vaccination. Tracking the introduction and transmission of VOCs relies on sequencing, typically whole genome sequencing of clinical samples. Wastewater surveillance is increasingly used to track the introduction and spread of SARS-CoV-2 variants through sequencing approaches.AimHere, we adapt and apply a rapid, high-throughput method for detection and quantification of the relative frequency of two deletions characteristic of the Alpha, Beta, and Gamma VOCs in wastewater.MethodsWe developed drop-off RT-dPCR assays and an associated statistical approach implemented in the R package WWdPCR to analyse temporal dynamics of SARS-CoV-2 signature mutations (spike Δ69-70 and ORF1a Δ3675-3677) in wastewater and quantify transmission fitness advantage of the Alpha VOC.ResultsBased on analysis of Zurich wastewater samples, the estimated transmission fitness advantage of SARS-CoV-2 Alpha based on the spike Δ69-70 was 0.34 (95% confidence interval (CI): 0.30-0.39) and based on ORF1a Δ3675-3677 was 0.53 (95% CI: 0.49-0.57), aligning with the transmission fitness advantage of Alpha estimated by clinical sample sequencing in the surrounding canton of 0.49 (95% CI: 0.38-0.61).ConclusionDigital PCR assays targeting signature mutations in wastewater offer near real-time monitoring of SARS-CoV-2 VOCs and potentially earlier detection and inference on transmission fitness advantage than clinical sequencing.

Emergence of the novel SARS-CoV-2 lineage VUI-NP13L and massive spread of P.2 in South Brazil

In this study, we analyzed 340 whole genomes of SARS-CoV-2, which were sampled between April and November 2020 in 33 cities of Rio Grande do Sul, South Brazil. We demonstrated the circulation of two novel emergent lineages, VUI-NP13L and VUI-NP13L-like, and five major lineages that had already been assigned (B.1.1.33, B.1.1.28, P.2, B.1.91, B.1.195). P.2 and VUI-NP13L demonstrated a massive spread in October 2020. Constant and consistent genomic surveillance is crucial to identify newly emerging SARS-CoV-2 lineages in Brazil and to guide decision making in the Brazilian Public Healthcare System.