Biology subjects

Webby, R.

Publications and source records attributed to Webby, R..

6 recordsLinked to original sources

bioRxiv2025

Bridging Genomics and Clinical Medicine: RSVrecon Enhances RSV Surveillance with Automated Genotyping and Clinically-important Mutation Reporting

BackgroundRespiratory Syncytial Virus (RSV) causes significant respiratory infections, particularly in young children and elderly adults. Genetic variations in the fusion (F) protein can reduce the efficacy of vaccination and monoclonal antibody treatments, emphasizing the need for genomic surveillance of this virus. MotivationCurrent pipelines for RSV genome assembly focus on sequence reconstruction but often lack features for detecting genotypes, clinically relevant mutations, or presenting results in formats that are suitable for clinical researchers. ResultsWe introduce RSVrecon, an advanced bioinformatics pipeline for comprehensive RSV genome assembly and phylogenetic analysis. RSVrecon processes raw FASTQ files into annotated variant reports and delivers results in multiple formats (CSV, PDF, HTML) tailored to diverse end users. A key innovation of RSVrecon is not only its integrated detection of clinically critical features--including genotype classification and F protein mutation calling, capabilities absent in most analytical pipelines--but also its presentation of these results to clinicians via an integrated, graphical, and user-friendly interface. Its modular design, powered by Nextflows modern framework, ensures a scalable and robust workflow, while user-friendly reports enable seamless translation of genomic data into actionable clinical insights. Benchmarking against existing pipelines using clinical datasets revealed that RSVrecon achieves comparable genomic assembly accuracy while excelling in three key dimensions: (1) expanded functional capabilities, (2) intuitive biological interpretation of the results, and (3) superior user experience and accessibility. By seamlessly translating RSV genomic data into clinically meaningful information, RSVrecon empowers research breakthroughs, guides clinical care decisions, and strengthens surveillance systems. With these features, RSVrecon offers an enhanced approach to RSV surveillance and research. The tool is freely available at https://github.com/stjudecab/rsvrecon and https://github.com/stjudecab/RSVreconPy. Key PointsO_LIRSVrecon enables comprehensive clinical detection for RSV such as identifying genotypes and F protein mutations. C_LIO_LIRSVrecon delivers results through an integrated, graphical, and user-friendly interface for clinicians. C_LIO_LIRSVrecons Nextflow-based design ensures robust, scalable, and consistent performance. C_LIO_LIRSVrecon matches assembly accuracy while excelling in functionality, interpretation, and accessibility during benchmarking. C_LI

bioinformatics↗

bioRxiv2024

Rapid Surge of Reassortant A(H1N1) Influenza Viruses in Danish Swine and their Zoonotic Potential

In 2018, a single detection of a novel reassortant swine influenza A virus (swIAV) was made in Denmark. The hemagglutinin (HA) of the virus was from the H1N1 pandemic 2009 (H1N1pdm09) lineage and the neuraminidase (NA) from the H1N1 Eurasian avian-like swine lineage (H1N1av). By 2022, the novel reassortant virus (H1pdm09N1av) constituted 27 % of swIAVs identified through the Danish passive swIAV surveillance program. Sequencing detected two H1pdm09N1av genotypes; Genotype 1 contained an internal gene cassette of H1N1pdm09 origin, Genotype 2 differed by carrying an NS gene segment of H1N1av origin. The internal gene cassette of Genotype 2 became increasingly dominant, not only in the H1pdm09N1av population, but also in other Danish enzootic swIAV subtypes. Phylogenetic analysis of the HA genes from H1pdm09N1av viruses revealed a monophyletic source, a higher substitution rate compared to other H1N1pdm09 viruses and genetic differences with human seasonal and other swine adapted H1N1pdm09 viruses. Correspondingly, H1pdm09N1av viruses were antigenically distinct from human H1N1pdm09 vaccine viruses. Both H1pdm09N1av genotypes transmitted between ferrets by direct contact, but only Genotype 1 was capable of efficient aerosol transmission. The rapid spread of H1pdm09N1av viruses in Danish swine herds is concerning for swine and human health. Their zoonotic threat is highlighted by the limited pre-existing immunity observed in the human population, aerosol transmission in ferrets and the finding that the internal gene cassette of Genotype 2 was present in the first two zoonotic infections ever detected in Denmark.

genomics↗

bioRxiv2023

Integrated Drivers of Basal and Acute Immunity in Diverse Human Populations

Prior studies have identified genetic, infectious, and biological associations with immune competence and disease severity; however, there have been few integrative analyses of these factors and study populations are often limited in demographic diversity. Utilizing samples from 1,705 individuals in 5 countries, we examined putative determinants of immunity, including: single nucleotide polymorphisms, ancestry informative markers, herpesvirus status, age, and sex. In healthy subjects, we found significant differences in cytokine levels, leukocyte phenotypes, and gene expression. Transcriptional responses also varied by cohort, and the most significant determinant was ancestry. In influenza infected subjects, we found two disease severity immunophenotypes, largely driven by age. Additionally, cytokine regression models show each determinant differentially contributes to acute immune variation, with unique and interactive, location-specific herpesvirus effects. These results provide novel insight into the scope of immune heterogeneity across diverse populations, the integrative effects of factors which drive it, and the consequences for illness outcomes.

immunology↗

bioRxiv2022

Mapping SARS-CoV-2 antigenic relationships and serological responses

During the SARS-CoV-2 pandemic, multiple variants escaping pre-existing immunity emerged, causing concerns about continued protection. Here, we use antigenic cartography to analyze patterns of cross-reactivity among a panel of 21 variants and 15 groups of human sera obtained following primary infection with 10 different variants or after mRNA-1273 or mRNA-1273.351 vaccination. We find antigenic differences among pre-Omicron variants caused by substitutions at spike protein positions 417, 452, 484, and 501. Quantifying changes in response breadth over time and with additional vaccine doses, our results show the largest increase between 4 weeks and >3 months post-2nd dose. We find changes in immunodominance of different spike regions depending on the variant an individual was first exposed to, with implications for variant risk assessment and vaccine strain selection. One sentence summaryAntigenic Cartography of SARS-CoV-2 variants reveals amino acid substitutions governing immune escape and immunodominance patterns.

immunology↗

bioRxiv2020

COVID-19 cytokines and the hyperactive immune response: Synergism of TNF-α and IFN-γ in triggering inflammation, tissue damage, and death

The COVID-19 pandemic has caused significant morbidity and mortality. Currently, there is a critical shortage of proven treatment options and an urgent need to understand the pathogenesis of multi-organ failure and lung damage. Cytokine storm is associated with severe inflammation and organ damage during COVID-19. However, a detailed molecular pathway defining this cytokine storm is lacking, and gaining mechanistic understanding of how SARS-CoV-2 elicits a hyperactive inflammatory response is critical to develop effective therapeutics. Of the multiple inflammatory cytokines produced by innate immune cells during SARS-CoV-2 infection, we found that the combined production of TNF- and IFN-{gamma} specifically induced inflammatory cell death, PANoptosis, characterized by gasdermin-mediated pyroptosis, caspase-8-mediated apoptosis, and MLKL-mediated necroptosis. Deletion of pyroptosis, apoptosis, or necroptosis mediators individually was not sufficient to protect against cell death. However, cells deficient in both RIPK3 and caspase-8 or RIPK3 and FADD were resistant to this cell death. Mechanistically, the JAK/STAT1/IRF1 axis activated by TNF- and IFN-{gamma} co-treatment induced iNOS for the production of nitric oxide. Pharmacological and genetic deletion of this pathway inhibited pyroptosis, apoptosis, and necroptosis in macrophages. Moreover, inhibition of PANoptosis protected mice from TNF- and IFN-{gamma}-induced lethal cytokine shock that mirrors the pathological symptoms of COVID-19. In vivo neutralization of both TNF- and IFN-{gamma} in multiple disease models associated with cytokine storm showed that this treatment provided substantial protection against not only SARS-CoV-2 infection, but also sepsis, hemophagocytic lymphohistiocytosis, and cytokine shock models, demonstrating the broad physiological relevance of this mechanism. Collectively, our findings suggest that blocking the cytokine-mediated inflammatory cell death signaling pathway identified here may benefit patients with COVID-19 or other cytokine storm-driven syndromes by limiting inflammation and tissue damage. The findings also provide a molecular and mechanistic description for the term cytokine storm. Additionally, these results open new avenues for the treatment of other infectious and autoinflammatory diseases and cancers where TNF- and IFN-{gamma} synergism play key pathological roles.

immunology↗

bioRxiv2020

idCOV: a pipeline for quick clade identification of SARS-CoV-2 isolates

idCOV is a phylogenetic pipeline for quickly identifying the clades of SARS-CoV-2 virus isolates from raw sequencing data based on a selected clade-defining marker list. Using a public dataset, we show that idCOV can make equivalent calls as annotated by Nextstrain.org on all three common clade systems using user uploaded FastQ files directly. Web and equivalent command-line interfaces are available. It can be deployed on any Linux environment, including personal computer, HPC and the cloud. The source code is available at https://github.com/xz-stjude/idcov. A documentation for installation can be found at https://github.com/xz-stjude/idcov/blob/master/README.md.

bioinformatics↗