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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.

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.

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.

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.

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.

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.

Many cell-cycle-specific events are supported by stage-specific gene expression. In budding yeast, at least three different nuclear factors seem to cooperate in the periodic activation of G2/M-specific genes 1 , 2 , 3 . Here we show, by using chromatin immunoprecipitation polymerase chain reaction assays, that a positive regulator, Ndd1, becomes associated with G2/M promoter regions in manner that depends on the stage in cell cycle. Its recruitment depends on a permanent protein–DNA complex consisting of the MADS box protein, Mcm1, and a recently identified partner Fkh2, a forkhead/winged helix related transcription factor 4 , 5 . The lethality of Ndd1 depletion is suppressed by fkh2 null mutations, which indicates that Fkh2 may also have a negative regulatory role in the transcription of G2/M-induced RNAs. We conclude that Ndd1–Fkh2 interactions may be the transcriptionally important process targeted by Cdk activity.

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.

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. Wastewater surveillance of SARS-CoV-2 at the national scale tracks emerging variants.