Biology subjects

Ruis, C.

Publications and source records attributed to Ruis, C..

12 recordsLinked to original sources

bioRxiv2026

Hantavirus mutagenesis is impacted by mutagens and host antiviral proteins

Hantaviruses are emerging zoonotic viruses that infect humans with high fatality rates. We currently have a poor understanding of the processes that contribute to hantavirus mutagenesis and therefore the potential for viral adaptation. To understand the drivers of mutations in hantaviruses, we calculated and compared mutational spectra across 14 divergent hantavirus species. We found that mutagens that are conserved across host species have a major impact on hantaviruses mutagenesis, contributing to at least six of the 12 possible mutation types. We found differences in mutational signatures across hantaviruses, some of which may be due to variation in host mutagen levels that are known to influence somatic mutations. However, we could find no evidence for differential mutational signatures between viruses associated with distinct diseases in humans and no evidence of tissue tropism differences between reservoir hosts. Using a novel method to quantify the impact of ZAP-mediated selection, we found that ZAP greatly influences mutational patterns in transition mutation types across hantaviruses. We also find evidence that APOBEC family proteins drive mutagenesis in all hantaviruses, with the likely exception of Nova virus. Our results therefore provide strong support that mutagens and host antiviral proteins are major contributors to hantavirus mutagenesis, thereby generating the genetic diversity necessary for viral adaptation.

microbiology↗

bioRxiv2026

The emergence and molecular evolution of H5N1 influenza viruses in United States dairy cattle

Prior to 2024, highly pathogenic avian influenza H5N1 clade 2.3.4.4b viruses circulated predominantly in wild birds and poultry. In 2024 and 2025, 2.3.4.4b genotypes B3.13 and D1.1 were detected in United States dairy cattle. Using whole-genome and segment-specific phylodynamic inference, we estimate that B3.13 and D1.1 spilled over from wild birds into dairy cattle in late 2023 and late 2024, respectively. Spillover occurred shortly after the formation of the reassortant genotypes and was followed by months of cryptic transmission prior to detection. We found that both B3.13 and D1.1 evolved at higher rates in cattle relative to birds, primarily due to relaxed purifying selection. Site-specific analyses identified genomic sites under positive selection in cattle relative to birds, indicating adaptation and likely contributing to improved viral fitness after spillover. Intensified genomic surveillance in dairy cattle is essential as population immunity introduces additional selection pressures, with ever-changing risk for human emergence.

evolutionary biology↗

bioRxiv2025

Mutational spectra reveal influenza virus transmission routes and adaptation

Influenza A virus remains a major cause of morbidity and mortality in humans and animals with pandemic potential. While control of outbreaks and spillover events remains a key health priority, the transmission routes and adaptations causing these episodes remain unclear. To understand these processes, we compared mutational spectra across the complete diversity of influenza A virus. We find that niche-specific mutagens cause large convergent shifts in mutational spectrum between gastrointestinal and respiratory lineages, allowing inference of transmission route and site of infection, while additional mutational patterns are host-specific, permitting detection of species responsible for outbreaks. By identifying points of spectrum change in phylogenetic trees, we discover novel adaptive mutations enabling sustained respiratory transmission. We conclude that mutational spectra can enable early detection of lineages with increased potential for spillover and onward transmission, and should be considered as a component of genomic surveillance strategies.

microbiology↗

bioRxiv2024

Nasopharyngeal specific selection and emergence of SARS-CoV-2 spike fusion peptide mutation P812S during chronic infection

Omicron emergence represented a seismic event in the COVID-19 pandemic, demonstrating what was essentially antigenic shift in a virus that cannot reassort its genome as influenza can. Understanding the success of Omicron is essential, and yet we have little understanding of the biological underpinnings of its ability to accommodate diverse mutations and bring together deleterious mutations to generate a highly successful new serotype. Persistent SARS-CoV-2 infections are a likely source of new variants and may provide valuable insight into past and future evolutionary trajectories, in particular those involving allosteric interactions that defy genotype to phenotype prediction. Here we observe upper airway specific evolution of SARS-CoV-2 demonstrating fusion peptide (FP) domain mutation S:P812S adjacent to the S2 cleavage site that emerged during a chronic infection in an immunocompromised individual. Indeed, this mutation had previously emerged in an ancestral B lineage as well as the delta variant lineage and transmitted successfully in populations globally, though remains uncharacterised. P812S in spike pseudotyped virus particles did not impact entry efficiency across cell lines expressing endogenous ACE2 and TMPRSS2. However, efficiency of spike cleavage at S1/S2 was reduced and molecular dynamics simulation demonstrated altered S1/S2 loop conformations that possibly impacted furin mediated cleavage. Consistent with impaired S1/S2 cleavage, and reminiscent of Omicron BA.1, cell-cell fusogenicity was severely impaired by introduction of P812S. The mutation also introduced significant perturbations to the FP region and also affected protomer-protomer packing. P812S conferred evasion of a neutralising monoclonal antibody targeting the fusion peptide, consistent with significant structural rearrangements in the FP region. Finally, P812S bearing viruses showed evasion of polyclonal neutralising antibodies in sera from vaccinated individuals at 32{degrees}C (simulating upper respiratory tract) and to a lesser extent at 37{degrees}C. Thus we report a novel mutational adaptation to the upper airway allowing enhanced immune evasion to fusion peptide targeting neutralising antibodies that also incurs a defect in ability to induce syncytia. These data shed light on the balance between upper airway adaptation/immune evasion by SARS-CoV-2, ability to induce syncytia formation, and disease severity given the established link between syncytia and severe COVID-19.

immunology↗

bioRxiv2024

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 4,471,579 samples, built from a consistently assembled set of high quality consensus sequences from all available public data as of June 2024, 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. We hope the tree, consensus sequences and Viridian will be a valuable resource for researchers.

bioinformatics↗

bioRxiv2023

Calculating and applying pathogen mutational spectra using MutTui

Mutational spectra describe the pattern of mutations acquired during evolution and are driven by factors including mutagens, repair processes and selection. Calculating mutational spectra of pathogen genomic datasets may enable analysis of factors that influence these mutational processes, including replication niches, transmission routes and pathogen biology. Here, we introduce MutTui, which can leverage multiple types of sequence data to calculate and compare mutational spectra of DNA and RNA pathogens. MutTui is available at https://github.com/chrisruis/MutTui.

genomics↗

bioRxiv2023

Automated Agnostic Designation of Pathogen Lineages

Pathogen nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were added to a growing global dataset. This approach to dynamic lineage designation is dependent on a large and active epidemiological community identifying and curating each new lineage. This is vulnerable to time-critical delays as well as regional and personal bias. To address these issues, we developed a simple heuristic approach that divides a phylogenetic tree into lineages based on shared ancestral genotypes. We additionally provide a framework that automatically prioritizes the lineages by growth rate and association with key mutations or locations, extensible to any pathogen. Our implementation is efficient on extremely large phylogenetic trees and produces similar results to existing Pango lineage designations when applied to SARS-CoV-2. This method offers a simple, automated and consistent approach to pathogen nomenclature that can assist researchers in developing and maintaining phylogeny-based classifications in the face of ever increasing genomic datasets.

evolutionary biology↗

bioRxiv2022

Mutational spectra distinguish SARS-CoV-2 replication niches

Exposure to different mutagens leaves distinct mutational patterns that can allow prediction of pathogen replication niches (Ruis 2022). We therefore hypothesised that analysis of SARS-CoV-2 mutational spectra might show lineage-specific differences, dependant on the dominant site(s) of replication and onwards transmission, and could therefore rapidly infer virulence of emergent variants of concern (VOC; Konings 2021). Through mutational spectrum analysis, we found a significant reduction in G>T mutations in Omicron, which replicates in the upper respiratory tract (URT), compared to other lineages, which replicate in both upper and lower respiratory tracts (LRT). Mutational analysis of other viruses and bacteria indicates a robust, generalisable association of high G>T mutations with replication within the LRT. Monitoring G>T mutation rates over time, we found early separation of Omicron from Beta, Gamma and Delta, while the mutational burden in Alpha varied consistent with changes in transmission source as social restrictions were lifted. This supports the use of mutational spectra to infer niches of established and emergent pathogens.

microbiology↗

bioRxiv2022

Mutational spectra analysis reveals bacterial niche and transmission routes

As observed in cancers, individual mutagens and defects in DNA repair create distinctive mutational signatures that combine to form context-specific spectra within cells. We reasoned that similar processes must occur in bacterial lineages, potentially allowing decomposition analysis to identify disrupted DNA repair processes and niche-specific mutagen exposure. Here we reconstructed mutational spectra for 84 clades from 31 diverse bacterial species, assigned signatures to specific DNA repair pathways using hypermutator lineages, and, by comparing mutational spectra of clades from different environmental and biological locations, extracted reproducible niche-associated mutational signatures. We show that mutational spectra can predict general and specific bacterial niches and therefore reveal the site of infection and types of transmission routes for established and emergent human bacterial pathogens. One sentence summaryVariable mutagen exposure and DNA repair drive differential mutational spectra between bacteria and enable niche inference

microbiology↗

bioRxiv2020

A dynamic nomenclature proposal for SARS-CoV-2 to assist genomic epidemiology

The ongoing pandemic spread of a novel human coronavirus, SARS-COV-2, associated with severe pneumonia disease (COVID-19), has resulted in the generation of thousands of virus genome sequences. The rate of genome generation is unprecedented, yet there is currently no coherent nor accepted scheme for naming the expanding phylogenetic diversity of SARS-CoV-2. We present a rational and dynamic virus nomenclature that uses a phylogenetic framework to identify those lineages that contribute most to active spread. Our system is made tractable by constraining the number and depth of hierarchical lineage labels and by flagging and declassifying virus lineages that become unobserved and hence are likely inactive. By focusing on active virus lineages and those spreading to new locations this nomenclature will assist in tracking and understanding the patterns and determinants of the global spread of SARS-CoV-2.

microbiology↗

bioRxiv2020

Producing Polished Prokaryotic Pangenomes with the Panaroo Pipeline

Population-level comparisons of prokaryotic genomes must take into account the substantial differences in gene content, resulting from frequent horizontal gene transfer, gene duplication and gene loss. However, the automated annotation of prokaryotic genomes is imperfect, and errors due to fragmented assemblies, contamination, diverse gene families and mis-assemblies accumulate over the population, leading to profound consequences when analysing the set of all genes found in a species. Here we introduce Panaroo, a graph based pangenome clustering tool that is able to account for many of the sources of error introduced during the annotation of prokaryotic genome assemblies. We verified our approach through extensive simulations of de novo assemblies using the infinitely many genes model and by analysing a number of publicly available large bacterial genome datasets. Using a highly clonal Mycobacterium tuberculosis dataset as a negative control case, we show that failing to account for annotation errors can lead to pangenome estimates that are dominated by error. We additionally demonstrate the utility of the improved graphical output provided by Panaroo by performing a pan-genome wide association study in Neisseria gonorrhoeae and by analysing gene gain and loss rates across 51 of the major global pneumococcal sequence clusters. Panaroo is freely available under an open source MIT licence at https://github.com/gtonkinhill/panaroo.

genomics↗

bioRxiv2019

Preadaptation of pandemic GII.4 noroviruses in hidden virus reservoirs years before emergence

The control of pandemic pathogens depends on early prediction of pandemic variants and, more generally, understanding origins of such variants and factors that drive their global spread. This is especially important for GII.4 norovirus, where vaccines under development offer promise to prevent hundreds of millions of annual gastroenteritis cases. Previous studies have suggested that new GII.4 pandemic viruses evolve from previous pandemic variants through substitutions in the antigenic region of the VP1 protein that enable evasion of host population immunity, leading to global spread. In contrast, we show here that the acquisition of new genetic and antigenic characteristics is not the proximal driver of new pandemics. Instead, pandemic GII.4 viruses circulate undetected for years before causing a new pandemic, during which time they diversify and spread over wide geographical areas. Serological data demonstrate that by 2003, some nine years before it emerged as a new pandemic, the ancestral 2012 pandemic strain had already acquired the antigenic characteristics that allowed it to evade prevailing population immunity against the previous 2009 pandemic variant. These results provide strong evidence that viral genetic changes are necessary but not sufficient for GII.4 pandemic spread. Instead, we suggest that it is changes in host population immunity that enable pandemic spread of an antigenically-preadapted GII.4 variant. These results indicate that predicting future GII.4 pandemic variants will require surveillance of currently unsampled reservoir populations. Furthermore, a broadly acting GII.4 vaccine will be critical to prevent future pandemics.\n\nSignificanceNorovirus pandemics and their associated public health and economic costs could be prevented by effective vaccines. However, vaccine development and distribution will require identification of the sources and drivers of new pandemics. We here use phylogenetics and serological experiments to develop and test a new hypothesis of pandemic norovirus emergence. We find that pandemic noroviruses preadapt, diversify and spread worldwide years prior to emergence, strongly indicating that genetic changes are necessary but not sufficient to drive a new pandemic. We instead suggest that changes in population immunity enable pandemic emergence of a pre-adapted low-level variant. These findings indicate that prediction of new pandemics will require surveillance of under-sampled virus reservoirs and that norovirus vaccines will need to elicit broad immunity.

evolutionary biology↗