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.

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/.

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.

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.

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.

Characterization of CD8 T Cell-Mediated Mutations in the Immunodominant Epitope GP33-41 of Lymphocytic Choriomeningitis Virus.

Cytotoxic T lymphocytes (CTLs) represent key immune effectors of the host response against chronic viruses, due to their cytotoxic response to virus-infected cells. In response to this selection pressure, viruses may accumulate escape mutations that evade CTL-mediated control. To study the emergence of CTL escape mutations, we employed the murine chronic infection model of lymphocytic choriomeningitis virus (LCMV). We developed an amplicon-based next-generation sequencing pipeline to detect low frequency mutations in the viral genome and identified non-synonymous mutations in the immunodominant LCMV CTL epitope, GP33-41, in infected wildtype mice. Infected Rag2-deficient mice lacking CTLs did not contain such viral mutations. By using transgenic mice with T cell receptors specific to GP33-41, we characterized the emergence of viral mutations in this epitope under varying selection pressure. We investigated the two most abundant viral mutations by employing reverse genetically engineered viral mutants encoding the respective mutations. These experiments provided evidence that these mutations prevent activation and expansion of epitope-specific CD8 T cells. Our findings on the mutational dynamics of CTL escape mutations in a widely-studied viral infection model contributes to our understanding of how chronic viruses interact with their host and evade the immune response. This may guide the development of future treatments and vaccines against chronic infections.

Ornithobacterium rhinotracheale: MALDI-TOF MS and Whole Genome Sequencing Confirm That Serotypes K, L and M Deviate from Well-Known Reference Strains and Numerous Field Isolates.

Ornithobacterium rhinotracheale is one of the most important bacterial agents of respiratory diseases in poultry. For correct identification and characterization of this fastidious bacterium, reliable diagnostic tools are essential. Still, phenotypic tests are used to identify O. rhinotracheale and serotyping is the most common method for characterization, despite known drawbacks and disadvantages such as divergent results, cross-reactivity between strains, or the non-typeability of strains. The intention of the present study was to evaluate MALDI-TOF MS and whole genome sequencing for the identification and characterization of O. rhinotracheale. For this purpose, a selection of 59 well-defined reference strains and 47 field strains derived from outbreaks on Austrian turkey farms were investigated by MALDI-TOF MS. The field strains originated from different geographical areas in Austria with some of the isolates derived from multiple outbreaks on farms within a year, or recurrent outbreaks over several years. MALDI-TOF MS proved a suitable method for identification of O. rhinotracheale to genus or species level except for 3 strains representing serotypes M, K and F. Phylogenetic analysis showed that most strains grouped within one cluster even though they were comprised of different serotypes, while serotypes F, K, and M clearly formed a different cluster. All field isolates from turkey farms clustered together, independent of the origin of the isolates, e.g., geographical area, multiple outbreaks within a year or recurrent outbreaks over several years. Whole genome sequencing of serotype M, K and F strains confirmed the extraordinary status and deviation from known fully-sequenced strains due to a lack of sequence similarity. This was further confirmed by alignments of single genes (16S-RNA and rpoB) and multilocus sequence typing although the demarcation was less obvious. Altogether, the results indicate that these three serotypes belong to a different species than O. rhinotracheale, and might even be members of multiple new species.

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.

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.

Fowl Adenovirus (FAdV) Recombination with Intertypic Crossovers in Genomes of FAdV-D and FAdV-E, Displaying Hybrid Serological Phenotypes.

After analyzing 27 new genomes from fowl adenovirus (FAdV) field isolates and so-far unsequenced prototypes, we report the first evidence for recombination in FAdVs. Recombination was confined to species FAdV-D and FAdV-E, accommodating the largest number of, and the intraspecies-wise most differentiated, types. The majority of detected events occurred in FAdV-E, involving segments with parental origin of all constitutive types. Together with the diversity of breakpoints, this suggests widespread recombination in this species. With possible constraints through species-specific genes and diversification patterns, the recombinogenic potential of FAdVs attains particular interest for inclusion body hepatitis (IBH), an important disease in chickens, caused by types from the recombination-prone species. Autonomously evolving, recombinant segments were associated with major sites under positive selection, among them the capsid protein hexon and fiber genes, the right-terminal ORFs 19, 25, and the ORF20/20A family. The observed mosaicism in genes indicated as targets of adaptive pressures points toward an immune evasion strategy. Intertypic hexon/fiber-recombinants demonstrated hybrid neutralization profiles, retrospectively explaining reported controversies on reference strains B3-A, T8-A, and X11-A. Furthermore, cross-neutralization supported sequence-based evidence for interdomain recombination in fiber and contributed to a tentatively new type. Overall, our findings challenge the purported uniformity of types responsible for IBH, urging more complete identification strategies for FAdVs. Finally, important consequences arise for in vivo studies investigating cross-protection against IBH.

Pleiotropic effects of regulatory variation in tan result in correlation of two pigmentation traits in Drosophila melanogaster.

Traits with a common genetic basis frequently display correlated phenotypic responses to selection or environmental conditions. In Drosophila melanogaster, pigmentation of the abdomen and a trident-shaped region on the thorax are genetically correlated. Here, we used a pooled replicated genomewide association approach (Pool-GWAS) to identify the genetic basis of variation in thoracic trident pigmentation in two Drosophila melanogaster populations. We confirmed the previously reported large effect of ebony and the association of the cosmopolitan inversion In(3R)Payne. For the first time, we identified tan as another major locus contributing to variation in trident pigmentation. Intriguingly, the regulatory variants of tan that were most strongly associated with female abdominal pigmentation also showed a strong association with trident pigmentation. We validated this common genetic basis in transgenic assays and found qualitatively similar effects on trident and abdominal pigmentation. Further work is required to determine whether this genetic correlation is favoured by natural selection or reflects a neutral by-product of a shared regulatory architecture.

Establishment of a de novo Reference Transcriptome of Histomonas meleagridis Reveals Basic Insights About Biological Functions and Potential Pathogenic Mechanisms of the Parasite.

The protozoan flagellate Histomonas meleagridis is the causative agent of histomonosis in poultry. In turkeys, high mortality might be noticed whereas in chickens the disease is less severe despite production losses. Discovered over a century ago, molecular data on this parasite are scarce and genetic studies are in its infancy. To expand genomic information, a de novo transcriptome sequencing of H. meleagridis was performed from a virulent and an attenuated strain, cultivated in vitro as monoxenic mono-eukaryotic culture. Normalized cDNA libraries were prepared and sequenced on Roche 454 GS FLX resulting in 1.17 million reads with an average read length of 458bp. Sequencing reads were assembled into two sets of >4500 contigs, which were further integrated to establish a reference transcriptome for H. meleagridis consisting of 3356 contigs. Following gene ontology analysis, data mining provided novel biological insights into proteostasis, cytoskeleton, metabolism, environmental adaptation and potential pathogenic mechanisms of H. meleagridis. Finally, the transcriptome data was used to perform an in silico drug screen to identify potential anti-histomonal drugs. Altogether, data recruited from virulent and attenuated parasites facilitate a better understanding of the parasites' molecular biology aiding the development of novel diagnostics and future research.

Reconciling Differences in Pool-GWAS Between Populations: A Case Study of Female Abdominal Pigmentation in Drosophila melanogaster.

The degree of concordance between populations in the genetic architecture of a given trait is an important issue in medical and evolutionary genetics. Here, we address this problem, using a replicated pooled genome-wide association study approach (Pool-GWAS) to compare the genetic basis of variation in abdominal pigmentation in female European and South African Drosophila melanogaster. We find that, in both the European and the South African flies, variants near the tan and bric-à-brac 1 (bab1) genes are most strongly associated with pigmentation. However, the relative contribution of these loci differs: in the European populations, tan outranks bab1, while the converse is true for the South African flies. Using simulations, we show that this result can be explained parsimoniously, without invoking different causal variants between the populations, by a combination of frequency differences between the two populations and dominance for the causal alleles at the bab1 locus. Our results demonstrate the power of cost-effective, replicated Pool-GWAS to shed light on differences in the genetic architecture of a given trait between populations.

Using chemical kinetics to model biochemical pathways.

Chemical kinetics is the study of the rate of reactions transforming some chemical entities into other chemical entities. Over the twentieth century it has become one of the cornerstones of biochemistry. When in the second half of the century basic knowledge of cellular processes became sufficient to understand quantitatively metabolic networks, chemical kinetics associated with systems theory led to the development of what would become an important branch of systems biology. In this chapter we introduce basic concepts of chemical and enzyme kinetics, and show how the temporal evolution of a reaction system can be described by ordinary differential equations. Finally we present a method to apply this type of approach to model any regulatory network.

A community-driven global reconstruction of human metabolism.

Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ∼2× more reactions and ∼1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.

Ranked retrieval of Computational Biology models.

BACKGROUND: The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. RESULTS: Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. CONCLUSIONS: The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models.

BACKGROUND: Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. DESCRIPTION: BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. CONCLUSIONS: BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License.

Designing and encoding models for synthetic biology.

A key component of any synthetic biology effort is the use of quantitative models. These models and their corresponding simulations allow optimization of a system design, as well as guiding their subsequent analysis. Once a domain mostly reserved for experts, dynamical modelling of gene regulatory and reaction networks has been an area of growth over the last decade. There has been a concomitant increase in the number of software tools and standards, thereby facilitating model exchange and reuse. We give here an overview of the model creation and analysis processes as well as some software tools in common use. Using markup language to encode the model and associated annotation, we describe the mining of components, their integration in relational models, formularization and parametrization. Evaluation of simulation results and validation of the model close the systems biology 'loop'.