WAVES (Web-based tool for Analysis and Visualization of Environmental Samples)-a web application for visualization of wastewater pathogen sequencing results.

MOTIVATION: Environmental monitoring of pathogens provides an accurate and timely source of information for public health authorities and policymakers. In the last 2 years, wastewater sequencing proved to be an effective way of detection and quantification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants circulating in population. Wastewater sequencing produces substantial amounts of geographical and genomic data. Proper visualization of spatial and temporal patterns in these data is crucial for the assessment of the epidemiological situation and forecasting. Here, we present a web-based dashboard application for the visualization and analysis of data obtained from sequencing of environmental samples. The dashboard provides multi-layered visualization of geographical and genomic data. It allows to display frequencies of detected pathogen variants as well as individual mutation frequencies. The features of WAVES (Web-based tool for Analysis and Visualization of Environmental Samples) for early tracking and detection of novel variants in the wastewater are demonstrated in an example of BA.1 variant and the signature Spike mutation S: E484A. WAVES dashboard is easily customized through the editable configuration file and can be used for different types of pathogens and environmental samples. AVAILABILITY AND IMPLEMENTATION: WAVES source code is freely available at https://github.com/ptriska/WavesDash under MIT license. A demo version of this application can be accessed at: https://wavesdashboard.azurewebsites.net/.

VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples.

BACKGROUND: The genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the Delta variant B.1.617.2 or Omicron variant B.1.1.529). Proportions of these variants circulating in a human population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample. RESULTS: We propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluate the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of the Alpha variant. CONCLUSIONS: VirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read.

Comparison of clinical characteristics among patients infected with alpha vs. delta SARS-CoV-2 variants.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has undergone different molecular changes, sprouting genetic variants of the original wildtype. Clinical comparisons between patients infected with alpha versus delta are scarce. METHODS: In this retrospective observational study, adult patients hospitalized with coronavirus disease 2019 (COVID-19) due to confirmed SARS-CoV­2 alpha or delta infection were included. Patient characteristics, virologic and laboratory parameters, as well as the clinical course were compared in patients infected with alpha vs. delta variants. RESULTS: A total of 106 patients infected with alpha and 215 patients infected with delta were included. Patients infected with the delta variant were admitted to hospital earlier after symptom onset (6 vs. 7 days, p < 0.001). Blood levels of C­reactive protein (43.3 vs. 62.9 mg/l, p = 0.02) and neutrophil count (3.81 vs. 4.53 G/l, p = 0.06) were lower in delta patients. Furthermore, at hospital admission cycle threshold (CT) values were significantly lower in patients infected with the delta variant (22.3 vs. 24.9, p < 0.001). Patients infected with the delta variant needed supplemental oxygen less often during disease course (50% vs. 64%, p = 0.02). Furthermore, there was a statistically non-significant trend towards a lower ICU admission rate among delta patients (16% vs. 24%, p = 0.08) CONCLUSION: Patients diagnosed with the delta variant were admitted to the hospital earlier, had a less severe course of disease and a higher viral replication on admission. This may provide a window of opportunity for antivirals in the hospital setting.

Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale.

SARS-CoV-2 surveillance by wastewater-based epidemiology is poised to provide a complementary approach to sequencing individual cases. However, robust quantification of variants and de novo detection of emerging variants remains challenging for existing strategies. We deep sequenced 3,413 wastewater samples representing 94 municipal catchments, covering >59% of the population of Austria, from December 2020 to February 2022. Our system of variant quantification in sewage pipeline designed for robustness (termed VaQuERo) enabled us to deduce the spatiotemporal abundance of predefined variants from complex wastewater samples. These results were validated against epidemiological records of >311,000 individual cases. Furthermore, we describe elevated viral genetic diversity during the Delta variant period, provide a framework to predict emerging variants and measure the reproductive advantage of variants of concern by calculating variant-specific reproduction numbers from wastewater. Together, this study demonstrates the power of national-scale WBE to support public health and promises particular value for countries without extensive individual monitoring.

Rapid, early and accurate SARS-CoV-2 detection using RT-qPCR in primary care: a prospective cohort study (REAP-1)

ObjectivesWe explore the importance of SARS-CoV-2 sentinel surveillance testing in primary care during a regional COVID-19 outbreak in Austria.DesignProspective cohort study.SettingA single sentinel practice serving 22 829 people in the ski-resort of Schladming-Dachstein.ParticipantsAll 73 patients presenting with mild-to-moderate flu-like symptoms between 24 February and 03 April, 2020.InterventionNasopharyngeal sampling to detect SARS-CoV-2 using real-time reverse transcriptase-quantitative PCR (RT-qPCR).Outcome measuresWe compared RT-qPCR at presentation with confirmed antibody status. We split the outbreak in two parts, by halving the period from the first to the last case, to characterise three cohorts of patients with confirmed infection: early acute (RT-qPCR reactive) in the first half;and late acute (reactive) and late convalescent (non-reactive) in the second half. For each cohort, we report the number of cases detected, the accuracy of RT-qPCR, the duration and variety of symptoms, and the number of viral clades present.ResultsTwenty-two patients were diagnosed with COVID-19 (eight early acute, seven late acute and seven late convalescent), 44 patients tested SARS-CoV-2 negative and 7 were excluded. The sensitivity of RT-qPCR was 100% among all acute cases, dropping to 68.1% when including convalescent. Test specificity was 100%. Mean duration of symptoms for each group were 2 days (range 1–4) among early acute, 4.4 days (1–7) among late acute and 8 days (2–12) among late convalescent. Confirmed infection was associated with loss of taste. Acute infection was associated with loss of taste, nausea/vomiting, breathlessness, sore throat and myalgia;but not anosmia, fever or cough. Transmission clusters of three viral clades (G, GR and L) were identified.ConclusionsRT-qPCR testing in primary care can rapidly and accurately detect SARS-CoV-2 among people with flu-like illness in a heterogeneous viral outbreak. Targeted testing in primary care can support national sentinel surveillance of COVID-19.

Emergence of SARS-CoV-2 Alpha lineage and its correlation with quantitative wastewater-based epidemiology data.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) gave rise to an international public health emergency in 3 months after its emergence in Wuhan, China. Typically for an RNA virus, random mutations occur constantly leading to new lineages, incidental with a higher transmissibility. The highly infective alpha lineage, firstly discovered in the UK, led to elevated mortality and morbidity rates as a consequence of Covid-19, worldwide. Wastewater surveillance proved to be a powerful tool for early detection and subsequent monitoring of the dynamics of SARS-CoV-2 and its variants in a defined catchment. Using a combination of sequencing and RT-qPCR approaches, we investigated the total SARS-CoV-2 concentration and the emergence of the alpha lineage in wastewater samples in Vienna, Austria linking it to clinical data. Based on a non-linear regression model and occurrence of signature mutations, we conclude that the alpha variant was present in Vienna sewage samples already in December 2020, even one month before the first clinical case was officially confirmed and reported by the health authorities. This provides evidence that a well-designed wastewater monitoring approach can provide a fast snapshot and may detect the circulating lineages in wastewater weeks before they are detectable in the clinical samples. Furthermore, declining 14 days prevalence data with simultaneously increasing SARS-CoV-2 total concentration in wastewater indicate a different shedding behavior for the alpha variant. Overall, our results support wastewater surveillance to be a suitable approach to spot early circulating SARS-CoV-2 lineages based on whole genome sequencing and signature mutations analysis.

ACE2 is the critical in vivo receptor for SARS-CoV-2 in a novel COVID-19 mouse model with TNF- and IFNγ-driven immunopathology.

Despite tremendous progress in the understanding of COVID-19, mechanistic insight into immunological, disease-driving factors remains limited. We generated maVie16, a mouse-adapted SARS-CoV-2, by serial passaging of a human isolate. In silico modeling revealed how only three Spike mutations of maVie16 enhanced interaction with murine ACE2. maVie16 induced profound pathology in BALB/c and C57BL/6 mice, and the resulting mouse COVID-19 (mCOVID-19) replicated critical aspects of human disease, including early lymphopenia, pulmonary immune cell infiltration, pneumonia, and specific adaptive immunity. Inhibition of the proinflammatory cytokines IFNγ and TNF substantially reduced immunopathology. Importantly, genetic ACE2-deficiency completely prevented mCOVID-19 development. Finally, inhalation therapy with recombinant ACE2 fully protected mice from mCOVID-19, revealing a novel and efficient treatment. Thus, we here present maVie16 as a new tool to model COVID-19 for the discovery of new therapies and show that disease severity is determined by cytokine-driven immunopathology and critically dependent on ACE2 in vivo.

Severe Coronavirus Disease 2019 (COVID-19) is Associated With Elevated Serum Immunoglobulin (Ig) A and Antiphospholipid IgA Antibodies.

BACKGROUND: Severe coronavirus disease 2019 (COVID-19) frequently entails complications that bear similarities to autoimmune diseases. To date, there are little data on possible immunoglobulin (Ig) A-mediated autoimmune responses. Here, we aim to determine whether COVID-19 is associated with a vigorous total IgA response and whether IgA antibodies are associated with complications of severe illness. Since thrombotic events are frequent in severe COVID-19 and resemble hypercoagulation of antiphospholipid syndrome, our approach focused on antiphospholipid antibodies (aPL). METHODS: In this retrospective cohort study, clinical data and aPL from 64 patients with COVID-19 were compared from 3 independent tertiary hospitals (1 in Liechtenstein, 2 in Switzerland). Samples were collected from 9 April to 1 May 2020. RESULTS: Clinical records of 64 patients with COVID-19 were reviewed and divided into a cohort with mild illness (mCOVID; 41%), a discovery cohort with severe illness (sdCOVID; 22%) and a confirmation cohort with severe illness (scCOVID; 38%). Total IgA, IgG, and aPL were measured with clinical diagnostic kits. Severe illness was significantly associated with increased total IgA (sdCOVID, P = .01; scCOVID, P < .001), but not total IgG. Among aPL, both cohorts with severe illness significantly correlated with elevated anticardiolipin IgA (sdCOVID and scCOVID, P < .001), anticardiolipin IgM (sdCOVID, P = .003; scCOVID, P< .001), and anti-beta 2 glycoprotein-1 IgA (sdCOVID and scCOVID, P< .001). Systemic lupus erythematosus was excluded from all patients as a potential confounder. CONCLUSIONS: Higher total IgA and IgA-aPL were consistently associated with severe illness. These novel data strongly suggest that a vigorous antiviral IgA response, possibly triggered in the bronchial mucosa, induces systemic autoimmunity.

Response to comment on "Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2".

Further analysis of SARS-CoV-2 genome sequencing data identifies several highly recurrent genetic variants with low allele frequencies, which, if filtered out, provide estimates consistent with tighter transmission bottlenecks.

The versatility of external quality assessment for the surveillance of laboratory and in vitro diagnostic performance: SARS-CoV-2 viral genome detection in Austria.

OBJECTIVES: External quality assessment (EQA) schemes provide information on individual and general analytical performance of participating laboratories and test systems. The aim of this study was to investigate the use and performance of SARS-CoV-2 virus genome detection systems in Austrian laboratories and their preparedness to face challenges associated with the pandemic. METHODS: Seven samples were selected to evaluate performance and estimate variability of reported results. Notably, a dilution series was included in the panel as a measure of reproducibility and sensitivity. Several performance criteria were evaluated for individual participants as well as in the cohort of all participants. RESULTS: A total of 109 laboratories participated and used 134 platforms, including 67 different combinations of extraction and PCR platforms and corresponding reagents. There were no false positives and 10 (1.2%) false negative results, including nine in the weakly positive sample (Ct ∼35.9, ∼640 copies/mL). Twenty (22%) laboratories reported results of mutation detection. Twenty-five (19%) test systems included amplification of human RNA as evidence of proper sampling. The overall linearity of Ct values from individual test systems for the dilution series was good, but inter-assay variability was high. Both operator-related and systematic failures appear to have caused incorrect results. CONCLUSIONS: Beyond providing certification for participating laboratories, EQA provides the opportunity for participants to evaluate their performance against others so that they may improve operating procedures and test systems. Well-selected EQA samples offer additional inferences to be made about assay sensitivity and reproducibility, which have practical applications.

SARS-CoV-2 mutations in MHC-I-restricted epitopes evade CD8+ T cell responses.

CD8+ T cell immunity to SARS-CoV-2 has been implicated in COVID-19 severity and virus control. Here, we identified nonsynonymous mutations in MHC-I-restricted CD8+ T cell epitopes after deep sequencing of 747 SARS-CoV-2 virus isolates. Mutant peptides exhibited diminished or abrogated MHC-I binding in a cell-free in vitro assay. Reduced MHC-I binding of mutant peptides was associated with decreased proliferation, IFN-γ production and cytotoxic activity of CD8+ T cells isolated from HLA-matched COVID-19 patients. Single cell RNA sequencing of ex vivo expanded, tetramer-sorted CD8+ T cells from COVID-19 patients further revealed qualitative differences in the transcriptional response to mutant peptides. Our findings highlight the capacity of SARS-CoV-2 to subvert CD8+ T cell surveillance through point mutations in MHC-I-restricted viral epitopes.

Systemic Immunometabolism: Challenges and Opportunities.

Over the past 10 years, the field of immunometabolism made great strides to unveil the crucial role of intracellular metabolism in regulating immune cell function. Emerging insights into how systemic inflammation and metabolism influence each other provide a critical additional dimension on the organismal level. Here, we discuss the concept of systemic immunometabolism and review the current understanding of the communication circuits that underlie the reciprocal impact of systemic inflammation and metabolism across organs in inflammatory and infectious diseases, as well as how these mechanisms apply to homeostasis. We present current challenges of systemic immunometabolic research, and in this context, highlight opportunities and put forward ideas to effectively explore organismal physiological complexity in both health and disease.

Emergence of coronavirus disease 2019 (COVID-19) in Austria.

This is a report on the first identified cases of coronavirus disease 2019 (COVID-19) in Austria. The first documented case was a person who stayed in Kühtai, Tyrol, from 24 to 26 January 2020, and had been infected by a Chinese instructor in Starnberg (Germany) between 20 and 22 January. This counts as a German case since her diagnosis was eventually made in Munich (Germany) on 28 January. On 25 February, two cases imported from Italy were diagnosed in Innsbruck but again no secondary cases were identified in Austria. The first three infections of Austrian inhabitants were detected on 27 February in Vienna. The two resulting clusters finally included 6 (source of initial infection unknown) and 61 cases. Most likely, Italy was the source of the latter cluster. On 12 March the first fatal case of COVID-19 in Austria was reported, a 69-year-old Viennese who died in a Vienna hospital after returning from a cruise ship tour in Italy. On 6 March three autochthonously acquired cases were reported in the Tyrol, all related to the ski resort Ischgl. Of the first 14 Islandic COVID-19 cases infected in Ischgl, 11 had already returned to Iceland on 29 February. We consider that the incriminated barkeeper, who tested PCR positive on 7 March, was neither the primary case nor a superspreader. In our opinion, undetected transmission of SARS-CoV­2 had been ongoing in Ischgl prior to the first laboratory confirmed cases. Our data also underline that the introduction of SARS-CoV­2 into Austria was not one single event.

Dynamics of CD4 T Cell and Antibody Responses in COVID-19 Patients With Different Disease Severity.

Disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ranges from mild illness to severe respiratory disease and death. In this study, we determined the kinetics of viral loads, antibody responses (IgM, IgG, neutralization) and SARS-CoV-2-specific CD4 T cells by quantifying these parameters in 435 serial respiratory and blood samples collected from a cohort of 29 COVID-19 patients with either moderate or severe disease during the whole period of hospitalization or until death. Remarkably, there was no significant difference in the kinetics and plateau levels of neutralizing antibodies among the groups with different disease severity. In contrast, the dynamics of specific CD4 T cell responses differed considerably, but all patients with moderate or severe disease developed robust SARS-CoV-2-specific responses. Of note, none of the patients had detectable cross-reactive CD4 T cells in the first week after symptom onset, which have been described in 20-50% of unexposed individuals. Our data thus provide novel insights into the kinetics of antibody and CD4 T cell responses as well as viral loads that are key to understanding the role of adaptive immunity in combating the virus during acute infection and provide leads for the timing of immune therapies for COVID-19.

Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2.

Superspreading events shaped the coronavirus disease 2019 (COVID-19) pandemic, and their rapid identification and containment are essential for disease control. Here, we provide a national-scale analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) superspreading during the first wave of infections in Austria, a country that played a major role in initial virus transmissions in Europe. Capitalizing on Austria's well-developed epidemiological surveillance system, we identified major SARS-CoV-2 clusters during the first wave of infections and performed deep whole-genome sequencing of more than 500 virus samples. Phylogenetic-epidemiological analysis enabled the reconstruction of superspreading events and charts a map of tourism-related viral spread originating from Austria in spring 2020. Moreover, we exploited epidemiologically well-defined clusters to quantify SARS-CoV-2 mutational dynamics, including the observation of low-frequency mutations that progressed to fixation within the infection chain. Time-resolved virus sequencing unveiled viral mutation dynamics within individuals with COVID-19, and epidemiologically validated infector-infectee pairs enabled us to determine an average transmission bottleneck size of 103 SARS-CoV-2 particles. In conclusion, this study illustrates the power of combining epidemiological analysis with deep viral genome sequencing to unravel the spread of SARS-CoV-2 and to gain fundamental insights into mutational dynamics and transmission properties.

Immunometabolism pathways as the basis for innovative anti-viral strategies (INITIATE): A Marie Sklodowska-Curie innovative training network.

The past century has witnessed major advances in the control of many infectious diseases, yet outbreaks and epidemics caused by (re-) emerging RNA viruses continue to pose a global threat to human health. As illustrated by the global COVID19 pandemic, high healthcare costs, economic disruption and loss of productivity reinforce the unmet medical need to develop new antiviral strategies to combat not only the current pandemic but also future viral outbreaks. Pivotal for effective anti-viral defense is the innate immune system, a first line host response that senses and responds to virus infection. While molecular details of the innate immune response are well characterized, this research field is now being revolutionized with the recognition that cell metabolism has a major impact on the antiviral and inflammatory responses to virus infections. A detailed understanding of the role of metabolic regulation with respect to antiviral and inflammatory responses, together with knowledge of the strategies used by viruses to exploit immunometabolic pathways, will ultimately change our understanding and treatment of pathogenic viral diseases. INITIATE is a Marie Sklodowska-Curie Actions Innovative Training Network (MSCA-ITN), with the goal to train 15 early stage PhD researchers (ESRs) to become experts in antiviral immunometabolism (https://initiate-itn.eu/). To this end, INITIATE brings together a highly complementary international team of academic and corporate leaders from 7 European countries, with outstanding track records in the historically distinct research fields of virology, immunology and metabolism. The ESRs of INITIATE are trained in these interdisciplinary research fields through individual investigator-driven research projects, specialized scientific training events, workshops on academia-industry interactions, outreach & communication. INITIATE will deliver a new generation of creative and entrepreneurial researchers who will be able to face the inevitable future challenges in combating viral diseases.