Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny.

The SARS-CoV-2 genome occupies a unique place in infection biology - it is the most highly sequenced genome on earth (making up over 20% of public sequencing datasets) with fine scale information on sampling date and geography, and has been subject to unprecedented intense analysis. As a result, these phylogenetic data are an incredibly valuable resource for science and public health. However, the vast majority of the data was sequenced by tiling amplicons across the full genome, with amplicon schemes that changed over the pandemic as mutations in the viral genome interacted with primer binding sites. In combination with the disparate set of genome assembly workflows and lack of consistent quality control (QC) processes, the current genomes have many systematic errors that have evolved with the virus and amplicon schemes. These errors have significant impacts on the phylogeny, and therefore over the last few years, many thousands of hours of researchers time has been spent in "eyeballing" trees, looking for artefacts, and then patching the tree. Given the huge value of this dataset, we therefore set out to reprocess the complete set of public raw sequence data in a rigorous amplicon-aware manner, and build a cleaner phylogeny. Here we provide a global tree of 3,960,704 samples, built from a consistently assembled set of high quality consensus sequences from all available public data as of March 2023, viewable at https://viridian.taxonium.org . Each genome was constructed using a novel assembly tool called Viridian ( https://github.com/iqbal-lab-org/viridian ), developed specifically to process amplicon sequence data, eliminating artefactual errors and mask the genome at low quality positions. We provide simulation and empirical validation of the methodology, and quantify the improvement in the phylogeny. Phase 2 of our project will address the fact that the data in the public archives is heavily geographically biased towards the Global North. We therefore have contributed new raw data to ENA/SRA from many countries including Ghana, Thailand, Laos, Sri Lanka, India, Argentina and Singapore. We will incorporate these, along with all public raw data submitted between March 2023 and the current day, into an updated set of assemblies, and phylogeny. We hope the tree, consensus sequences and Viridian will be a valuable resource for researchers.

A replicating LCMV-based vaccine for the treatment of solid tumors.

Harnessing the immune system to eradicate tumors requires identification and targeting of tumor antigens, including tumor-specific neoantigens and tumor-associated self-antigens. Tumor-associated antigens are subject to existing immune tolerance, which must be overcome by immunotherapies. Despite many novel immunotherapies reaching clinical trials, inducing self-antigen-specific immune responses remains challenging. Here, we systematically investigate viral-vector-based cancer vaccines encoding a tumor-associated self-antigen (TRP2) for the treatment of established melanomas in preclinical mouse models, alone or in combination with adoptive T cell therapy. We reveal that, unlike foreign antigens, tumor-associated antigens require replication of lymphocytic choriomeningitis virus (LCMV)-based vectors to break tolerance and induce effective antigen-specific CD8+ T cell responses. Immunization with a replicating LCMV vector leads to complete tumor rejection when combined with adoptive TRP2-specific T cell transfer. Importantly, immunization with replicating vectors leads to extended antigen persistence in secondary lymphoid organs, resulting in efficient T cell priming, which renders previously "cold" tumors open to immune infiltration and reprograms the tumor microenvironment to "hot." Our findings have important implications for the design of next-generation immunotherapies targeting solid cancers utilizing viral vectors and adoptive cell transfer.

Autoreactive T cells targeting type II pneumocyte antigens in COVID-19 convalescent patients.

BACKGROUND: The role of autoreactive T cells on the course of Coronavirus disease-19 (COVID-19) remains elusive. Type II pneumocytes represent the main target cells of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Autoimmune responses against antigens highly expressed in type II pneumocytes may influence the severity of COVID-19 disease. OBJECTIVE: The aim of this study was to investigate autoreactive T cell responses against self-antigens highly expressed in type II pneumocytes in the blood of COVID-19 patients with severe and non-severe disease. METHODS: We collected blood samples of COVID-19 patients with varying degrees of disease severity and of pre-pandemic controls. T cell stimulation assays with peptide pools of type II pneumocyte antigens were performed in two independent cohorts to analyze the autoimmune T cell responses in patients with non-severe and severe COVID-19 disease. Target cell lysis assays were performed with lung cancer cell lines to determine the extent of cell killing by type II PAA-specific T cells. RESULTS: We identified autoreactive T cell responses against four recently described self-antigens highly expressed in type II pneumocytes, known as surfactant protein A, surfactant protein B, surfactant protein C and napsin A, in the blood of COVID-19 patients. These antigens were termed type II pneumocyte-associated antigens (type II PAAs). We found that patients with non-severe COVID-19 disease showed a significantly higher frequency of type II PAA-specific autoreactive T cells in the blood when compared to severely ill patients. The presence of high frequencies of type II PAA-specific T cells in the blood of non-severe COVID-19 patients was independent of their age. We also found that napsin A-specific T cells from convalescent COVID-19 patients could kill lung cancer cells, demonstrating the functional and cytotoxic role of these T cells. CONCLUSIONS: Our data suggest that autoreactive type II PAA-specific T cells have a protective role in SARS-CoV-2 infections and the presence of high frequencies of these autoreactive T cells indicates effective viral control in COVID-19 patients. Type II-PAA-specific T cells may therefore promote the killing of infected type II pneumocytes and viral clearance.

You only waste twice: T cells in parasite-induced organ wasting.

In this issue of Cell Reports, Redford et al.1 uncouple the role of CD4+ and CD8+ T cells in controlling anorexia and wasting of muscle and adipose tissue during chronic parasitic infections. These results shed light on the impact of adaptive immune cells on organ catabolism.

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/.

Comparative analysis of genome-scale, base-resolution DNA methylation profiles across 580 animal species.

Methylation of cytosines is a prototypic epigenetic modification of the DNA. It has been implicated in various regulatory mechanisms across the animal kingdom and particularly in vertebrates. We mapped DNA methylation in 580 animal species (535 vertebrates, 45 invertebrates), resulting in 2443 genome-scale DNA methylation profiles of multiple organs. Bioinformatic analysis of this large dataset quantified the association of DNA methylation with the underlying genomic DNA sequence throughout vertebrate evolution. We observed a broadly conserved link with two major transitions-once in the first vertebrates and again with the emergence of reptiles. Cross-species comparisons focusing on individual organs supported a deeply conserved association of DNA methylation with tissue type, and cross-mapping analysis of DNA methylation at gene promoters revealed evolutionary changes for orthologous genes. In summary, this study establishes a large resource of vertebrate and invertebrate DNA methylomes, it showcases the power of reference-free epigenome analysis in species for which no reference genomes are available, and it contributes an epigenetic perspective to the study of vertebrate evolution.

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.

Macrophage mitochondrial bioenergetics and tissue invasion are boosted by an Atossa-Porthos axis in Drosophila.

Cellular metabolism must adapt to changing demands to enable homeostasis. During immune responses or cancer metastasis, cells leading migration into challenging environments require an energy boost, but what controls this capacity is unclear. Here, we study a previously uncharacterized nuclear protein, Atossa (encoded by CG9005), which supports macrophage invasion into the germband of Drosophila by controlling cellular metabolism. First, nuclear Atossa increases mRNA levels of Porthos, a DEAD-box protein, and of two metabolic enzymes, lysine-α-ketoglutarate reductase (LKR/SDH) and NADPH glyoxylate reductase (GR/HPR), thus enhancing mitochondrial bioenergetics. Then Porthos supports ribosome assembly and thereby raises the translational efficiency of a subset of mRNAs, including those affecting mitochondrial functions, the electron transport chain, and metabolism. Mitochondrial respiration measurements, metabolomics, and live imaging indicate that Atossa and Porthos power up OxPhos and energy production to promote the forging of a path into tissues by leading macrophages. Since many crucial physiological responses require increases in mitochondrial energy output, this previously undescribed genetic program may modulate a wide range of cellular behaviors.

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.

The interplay of immunology and cachexia in infection and cancer.

Diverse inflammatory diseases, infections and malignancies are associated with wasting syndromes. In many of these conditions, the standards for diagnosis and treatment are lacking due to our limited understanding of the causative molecular mechanisms. Here, we discuss the complex immunological context of cachexia, a systemic catabolic syndrome that depletes both fat and muscle mass with profound consequences for patient prognosis. We highlight the main cytokine and immune cell-driven pathways that have been linked to weight loss and tissue wasting in the context of cancer-associated and infection-associated cachexia. Moreover, we discuss the potential immunometabolic consequences of cachexia on the basis of newly identified pathways and explore the multilayered area of immunometabolic crosstalk both upstream and downstream of tissue catabolism. Collectively, this Review highlights the intricate relationship of the immune system with cachexia in the context of malignant and infectious diseases.

Metabolic drug survey highlights cancer cell dependencies and vulnerabilities.

Interrogation of cellular metabolism with high-throughput screening approaches can unravel contextual biology and identify cancer-specific metabolic vulnerabilities. To systematically study the consequences of distinct metabolic perturbations, we assemble a comprehensive metabolic drug library (CeMM Library of Metabolic Drugs; CLIMET) covering 243 compounds. We, next, characterize it phenotypically in a diverse panel of myeloid leukemia cell lines and primary patient cells. Analysis of the drug response profiles reveals that 77 drugs affect cell viability, with the top effective compounds targeting nucleic acid synthesis, oxidative stress, and the PI3K/mTOR pathway. Clustering of individual drug response profiles stratifies the cell lines into five functional groups, which link to specific molecular and metabolic features. Mechanistic characterization of selective responses to the PI3K inhibitor pictilisib, the fatty acid synthase inhibitor GSK2194069, and the SLC16A1 inhibitor AZD3965, bring forth biomarkers of drug response. Phenotypic screening using CLIMET represents a valuable tool to probe cellular metabolism and identify metabolic dependencies at large.

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.