Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data (preprint)

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic "novel" lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances, and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1% frequency, results were more reliable above a 5% threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of noise or bias in wastewater sequencing data and to appreciate the commonalities and differences across methods.

Estimated transmission dynamics of SARS-CoV-2 variants from wastewater are robust to differential shedding (preprint)

The COVID-19 pandemic has accelerated the development and adoption of wastewater-based epidemiology. Wastewater samples can provide genomic information for detecting and assessing the spread of SARS-CoV-2 variants in communities and for estimating important epidemiological parameters such as the growth advantage of the variant. However, despite demonstrated successes, epidemiological data derived from wastewater suffers from potential biases. Of particular concern are differential shedding profiles that different variants of concern exhibit, because they can shift the relationship between viral loads in wastewater and prevalence estimates derived from clinical cases. Using mathematical modeling, simulations, and Swiss surveillance data, we demonstrate that this bias does not affect estimation of the growth advantage of the variant and has only a limited and transient impact on estimates of the effective reproduction number. Thus, population-level epidemiological parameters derived from wastewater maintain their advantages over traditional clinical-derived estimates, even in the presence of differential shedding among variants.

Estimated transmission dynamics of SARS-CoV-2 variants from wastewater are robust to differential shedding (preprint)

The COVID-19 pandemic has accelerated the development and adoption of wastewater-based epidemiology. Wastewater samples can provide genomic information for detecting and assessing the spread of SARS-CoV-2 variants in communities and for estimating important epidemiological parameters such as the growth advantage of the variant. However, despite demonstrated successes, epidemiological data derived from wastewater suffers from potential biases. Of particular concern are differential shedding profiles that different variants of concern exhibit, because they can shift the relationship between viral loads in wastewater and prevalence estimates derived from clinical cases. Using mathematical modeling, simulations, and Swiss surveillance data, we demonstrate that this bias does not affect estimation of the growth advantage of the variant and has only a limited and transient impact on estimates of the effective reproduction number. Thus, population-level epidemiological parameters derived from wastewater maintain their advantages over traditional clinical-derived estimates, even in the presence of differential shedding among variants.

V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation (preprint)

The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, adaptation to higher sample coverage, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting two large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.

How much should we sequence? An analysis of the Swiss SARS- CoV-2 surveillance effort (preprint)

Background During the SARS-CoV-2 pandemic, many countries directed substantial resources towards genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. Aim We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic dataset from Switzerland, comprising more than 143k sequences. Methods We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. Results The impact of downsampling on VOC detection is disparate for the three VOC lineages , but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. Conclusion A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage dependent - something that is unknown at the time of sequencing - and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.

Tracking SARS-CoV-2 genomic variants in wastewater sequencing data with LolliPop (preprint)

During the COVID-19 pandemic, wastewater-based epidemiology has progressively taken a central role as a pathogen surveillance tool. Tracking viral loads and variant outbreaks in sewage offers advantages over clinical surveillance methods by providing unbiased estimates and enabling early detection. However, wastewater-based epidemiology poses new computational research questions that need to be solved in order for this approach to be implemented broadly and successfully. Here, we address the variant deconvolution problem, where we aim to estimate the relative abundances of genomic variants from next-generation sequencing data of a mixed wastewater sample. We introduce LolliPop, a computational method to solve the variant deconvolution problem by simultaneously solving least squares problems and kernel-based smoothing of relative variant abundances from wastewater time series sequencing data. We derive multiple approaches to compute confidence bands, and demonstrate the application of our method to data from the Swiss wastewater surveillance efforts.

Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data (preprint)

Genome sequences allow quantification of changes in case introductions from abroad and local transmission dynamics. We sequenced 11,357 SARS-CoV-2 genomes from Switzerland in 2020 - the 6th largest effort globally. Using these data, we estimated introductions and their persistence throughout 2020. By contrasting estimates with null models, we estimate at least 83% of introductions were adverted during Switzerland's border closures. Further, transmission chain persistence roughly doubled after the partial lockdown was lifted. Then, using a novel phylodynamic method, we suggest transmission in newly introduced outbreaks slowed 36 - 64% upon outbreak detection in summer 2020, but not in fall. This could indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics.

Inferring Transmission Fitness Advantage of SARS-CoV-2 Variants of Concern in Wastewater Using Digital PCR (preprint)

Throughout the global COVID-19 pandemic, SARS-CoV-2 genetic variants of concern (VOCs) have repeatedly and independently arisen. VOCs are characterized by increased transmissibility, increased virulence, or reduced neutralization 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. Here, we adapt and apply a rapid, high-throughput method for detection and quantification of the frequency of two deletions characteristic of the B.1.1.7, B.1.351, and P.1 VOCs in wastewater. We further develop a statistical approach to analyze temporal dynamics in drop-off RT-dPCR assay data to quantify transmission fitness advantage, providing data similar to that obtained from clinical samples. Digital 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.

Quantification of the spread of SARS-CoV-2 variant B.1.1.7 in Switzerland (preprint)

In December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now coined B.1.1.7. Based on the UK data and later additional data from other countries, a transmission advantage of around 40-80% was estimated for this variant. In Switzerland, since spring 2020, we perform whole genome sequencing of SARS-CoV-2 samples obtained from a large diagnostic lab (Viollier AG) on a weekly basis for genomic surveillance. The lab processes SARS-CoV-2 samples from across Switzerland. Based on a total of 7631 sequences obtained from samples collected between 14.12.2020 and 11.02.2021 at Viollier AG, we determine the relative proportion of the B.1.1.7 variant on a daily basis. In addition, we use data from a second lab (Dr Risch) screening all their samples for the B.1.1.7 variant. These two datasets represent 11.5 % of all SARS-CoV-2 confirmed cases across Switzerland during the considered time period. They allow us to quantify the transmission advantage of the B.1.1.7 variant on a national and a regional scale. Taking all our data and estimates together, we propose a transmission advantage of 49-65% of B.1.1.7 compared to the other circulating variants. Further, we estimate the effective reproductive number through time for B.1.1.7 and the other variants, again pointing to a higher transmission rate of B.1.1.7. In particular, for the time period 01.01.2021-17.01.2021, we estimate an average reproductive number for B.1.1.7 of 1.28 [1.07-1.49] while the estimate for the other variants is 0.83 [0.63-1.03], based on the total number of confirmed cases and our Viollier sequencing data. Switzerland tightened measures on 18.01.2021. A comparison of the empirically confirmed case numbers up to 20.02.2021 to a very simple model using the estimates of the reproductive number from the first half of January provides indication that the rate of spread of all variants slowed down recently. In summary, the dynamics of increase in frequency of B.1.1.7 is as expected based on the observations in the UK. Our plots are available online and constantly updated with new data to closely monitor the changes in absolute numbers.

Detection of SARS-CoV-2 variants in Switzerland by genomic analysis of wastewater samples (preprint)

The SARS-CoV-2 lineages B.1.1.7 and 501.V2, which were first detected in the United Kingdom and South Africa, respectively, are spreading rapidly in the human population. Thus, there is an increased need for genomic and epidemiological surveillance in order to detect the strains and estimate their abundances. Here, we report a genomic analysis of SARS-CoV-2 in 48 raw wastewater samples collected from three wastewater treatment plants in Switzerland between July 9 and December 21, 2020. We find evidence for the presence of several mutations that define the B.1.1.7 and 501.V2 lineages in some of the samples, including co-occurrences of up to three B.1.1.7 signature mutations on the same amplicon in four samples from Lausanne and one sample from a Swiss ski resort dated December 9 - 21. These findings suggest that the B.1.1.7 strain could be detected by mid December, two weeks before its first verification in a patient sample from Switzerland. We conclude that sequencing SARS-CoV-2 in community wastewater samples may help detect and monitor the circulation of diverse lineages.

Quantifying SARS-CoV-2 spread in Switzerland based on genomic sequencing data (preprint)

Pathogen genomes provide insights into their evolution and epidemic spread. We sequenced 1,439 SARS-CoV-2 genomes from Switzerland, representing 3-7% of all confirmed cases per week. Using these data, we demonstrate that no one lineage became dominant, pointing against evolution towards general lower virulence. On an epidemiological level, we report no evidence of cryptic transmission before the first confirmed case. We find many early viral introductions from Germany, France, and Italy and many recent introductions from Germany and France. Over the summer, we quantify the number of non-traceable infections stemming from introductions, quantify the effective reproductive number, and estimate the degree of undersampling. Our framework can be applied to quantify evolution and epidemiology in other locations or for other pathogens based on genomic data.

SARS-CoV-2 viroporin triggers the NLRP3 inflammatory pathway (preprint)

Cytokine storm resulting from a heightened inflammatory response is a prominent feature of severe COVID-19 disease. This inflammatory response results from assembly/activation of a cell-intrinsic defense platform known as the inflammasome. We report that the SARS-CoV-2 viroporin encoded by ORF3a activates the NLRP3 inflammasome, the most promiscuous of known inflammasomes. ORF3a triggers IL-1 beta expression via NFkB, thus priming the inflammasome while also activating it via ASC-dependent and -independent modes. ORF3a-mediated inflammasome activation requires efflux of potassium ions and oligomerization between NEK7 and NLRP3. With the selective NLRP3 inhibitor MCC950 able to block ORF3a-mediated inflammasome activation and key ORF3a residues needed for virus release and inflammasome activation conserved in SARS-CoV-2 isolates across continents, ORF3a and NLRP3 present prime targets for intervention.

Genetic determinants of COVID-19 drug efficacy revealed by genome-wide CRISPR screens (preprint)

Immunomodulatory agents dexamethasone and colchicine, antiviral drugs remdesivir, favipiravir and ribavirin, as well as antimalarial drugs chloroquine phosphate and hydroxychloroquine are currently used in the combat against COVID-19. However, whether some of these drugs have clinical efficacy for COVID-19 is under debate. Moreover, these drugs are applied in COVID-19 patients with little knowledge of genetic biomarkers, which will hurt patient outcome. To answer these questions, we designed a screen approach that could employ genome-wide sgRNA libraries to systematically uncover genes crucial for these drugs' action. Here we present our findings, including genes crucial for the import, export, metabolic activation and inactivation of remdesivir, as well as genes that regulate colchicine and dexamethasone's immunosuppressive effects. Our findings provide preliminary information for developing urgently needed genetic biomarkers for these drugs. Such biomarkers will help better interpret COVID-19 clinical trial data and point to how to stratify COVID-19 patients for proper treatment with these drugs.

SARS-CoV-2 spike D614G variant confers enhanced replication and transmissibility (preprint)

During the evolution of SARS-CoV-2 in humans a D614G substitution in the spike (S) protein emerged and became the predominant circulating variant (S-614G) of the COVID-19 pandemic. However, whether the increasing prevalence of the S-614G variant represents a fitness advantage that improves replication and/or transmission in humans or is merely due to founder effects remains elusive. Here, we generated isogenic SARS-CoV-2 variants and demonstrate that the S-614G variant has (i) enhanced binding to human ACE2, (ii) increased replication in primary human bronchial and nasal airway epithelial cultures as well as in a novel human ACE2 knock-in mouse model, and (iii) markedly increased replication and transmissibility in hamster and ferret models of SARS-CoV-2 infection. Collectively, our data show that while the S-614G substitution results in subtle increases in binding and replication in vitro, it provides a real competitive advantage in vivo, particularly during the transmission bottle neck, providing an explanation for the global predominance of S-614G variant among the SARS-CoV-2 viruses currently circulating.

Remdesivir Metabolite GS-441524 Efficiently Inhibits SARS-CoV-2 Infection in Mouse Model (preprint)

The outbreak of coronavirus disease 2019 (COVID-19) rapidly spreads across worldwide and becomes a global pandemic. Remdesivir is the only COVID-19 treatment approved by U.S. Food and Drug Administration (FDA); however, its effectiveness is still under questioning as raised by the results of a large WHO Solidarity Trial. Herein, we report that the parent nucleotide of remdesivir, GS-441524, potently inhibits the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Vero E6 and other cells. It exhibits good plasma distribution and longer half-life (t1/2=4.8h) in rat PK study. GS-441524 is highly efficacious against SARS-CoV-2 in AAV-hACE2 transduced mice and murine hepatitis virus (MHV) in mice, reducing the viral titers in CoV-attacked organs, without noticeable toxicity. Given that GS-441524 was the predominant metabolite of remdesivir in the plasma, the anti-COVID-19 effect of remdesivir may partly come from the effect of GS-441524. Our results also supported that GS-441524 as a promising and inexpensive drug candidate in the treatment of COVID-19 and future emerging CoVs diseases.

Binding Mode of SARS-CoV2 Fusion Peptide to Human Cellular Membrane (preprint)

Infection of human cells by the SARS-CoV2 relies on its binding to a specific receptor and subsequent fusion of the viral and host cell membranes. The fusion peptide (FP), a short peptide segment in the spike protein, plays a central role in the initial penetration of the virus into the host cell membrane, followed by the fusion of the two membranes. Here, we use an array of molecular dynamics (MD) simulations taking advantage of the Highly Mobile Membrane Mimetic (HMMM) model, to investigate the interaction of the SARS-CoV2 FP with a lipid bilayer representing mammalian cellular membranes at an atomic level, and to characterize the membrane-bound form of the peptide. Six independent systems were generated by changing the initial positioning and orientation of the FP with respect to the membrane, and each system was simulated in five independent replicas. In 60% of the simulations, the FP reaches a stable, membrane-bound configuration where the peptide deeply penetrated into the membrane. Clustering of the results reveals two major membrane binding modes, the helix-binding mode and the loop-binding mode. Taken into account the sequence conservation among the viral FPs and the results of mutagenesis studies establishing the role of specific residues in the helical portion of the FP in membrane association, we propose that the helix-binding mode represents more closely the biologically relevant form. In the helix-binding mode, the helix is stabilized in an oblique angle with respect to the membrane with its N-terminus tilted towards the membrane core. Analysis of the FP-lipid interactions shows the involvement of specific residues of the helix in membrane binding previously described as the fusion active core residues. Taken together, the results shed light on a key step involved in SARS-CoV2 infection with potential implications in designing novel inhibitors.

Positive outcomes of COVID-19 research-related gender policy changes (preprint)

The COVID-19 pandemic has exposed and exacerbated gender biases in science, technology, engineering, mathematics, and medicine. Accumulating evidence suggests that female scientists' productivity dropped during the initial lockdown period. With more time being spent on caregiving responsibilities, women may be struggling to collaborate on grant applications and launch new experiments. Scientists with disabilities or who belong to Indigenous nations or communities of color may have less time to devote to research due to health, family, or community needs. Collateral damage in this situation, the appropriate integration of sex, gender, and other identity characteristics in research content may also suffer. Sex and gender are better attended to when female scientists form part of the research team. Research funding agencies have a role to play in mitigating these effects by putting in place gender equity policies that support all applicants and ensure research quality. Accordingly, a national health research funder implemented gender policy changes that included extending deadlines and factoring sex and gender into COVID-19 grant requirements. Following these changes, the funder received more applications from female scientists, awarded a greater proportion of grants to female compared to male scientists, and received and funded more grant applications that considered sex and gender in the content of COVID-19 research. Whether or not these strategies will be sufficient in the long-term to prevent widening of the gender gap in science, technology, engineering, mathematics and medicine requires continued monitoring and oversight. Further work is urgently required to mitigate inequities associated with identity characteristics beyond gender.

Origin of imported SARS-CoV-2 strains in The Gambia identified from whole genome sequences (preprint)

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a positive-sense single stranded RNA virus with high human transmissibility. This study generated Whole Genome data to determine the origin and pattern of transmission of SARS-CoV-2 from the first six cases tested in The Gambia. Total RNA from SARS-CoV-2 was extracted from inactivated nasopharyngeal-oropharyngeal swabs of six cases and converted to cDNA following the ARTIC COVID-19 sequencing protocol. Libraries were constructed with the NEBNext ultra II DNA library prep kit for Illumina and Oxford Nanopore Ligation sequencing kit and sequenced on Illumina MiSeq and Nanopore GridION, respectively. Sequencing reads were mapped to the Wuhan reference genome and compared to eleven other SARS-CoV-2 strains of Asian, European and American origins. A phylogenetic tree was constructed with the consensus genomes for local and non-African strains. Three of the Gambian strains had a European origin (UK and Spain), two strains were of Asian origin (Japan). In The Gambia, Nanopore and Illumina sequencers were successfully used to identify the sources of SARS-CoV-2 infection in COVID-19 cases.

Within-patient genetic diversity of SARS-CoV-2 (preprint)

SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, is evolving into different genetic variants by accumulating mutations as it spreads globally. In addition to this diversity of consensus genomes across patients, RNA viruses can also display genetic diversity within individual hosts, and co-existing viral variants may affect disease progression and the success of medical interventions. To systematically examine the intra-patient genetic diversity of SARS-CoV-2, we processed a large cohort of 3939 publicly-available deeply sequenced genomes with specialised bioinformatics software, along with 749 recently sequenced samples from Switzerland. We found that the distribution of diversity across patients and across genomic loci is very unbalanced with a minority of hosts and positions accounting for much of the diversity. For example, the D614G variant in the Spike gene, which is present in the consensus sequences of 67.4% of patients, is also highly diverse within hosts, with 29.7% of the public cohort being affected by this coexistence and exhibiting different variants. We also investigated the impact of several technical and epidemiological parameters on genetic heterogeneity and found that age, which is known to be correlated with poor disease outcomes, is a significant predictor of viral genetic diversity. Author SummarySince it arose in late 2019, the new coronavirus (SARS-CoV-2) behind the COVID-19 pandemic has mutated and evolved during its global spread. Individual patients may host different versions, or variants, of the virus, hallmarked by different mutations. We examine the diversity of genetic variants coexisting within patients across a cohort of 3939 publicly accessible samples and 749 recently sequenced samples from Switzerland. We find that a small number of patients carry most of the diversity, and that patients with more diversity tend to be older. We also find that most of the diversity is concentrated in certain regions and positions of the virus genome. In particular, we find that a variant reported to increase infectivity is among the most diverse positions. Our study provides a large-scale survey of within-patient diversity of the SARS-CoV-2 genome.

Computational Strategies to Combat COVID-19: Useful Tools to Accelerate SARS-CoV-2 and Coronavirus Research (preprint)

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding, and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are freely available online, either through web applications or public code repositories.