Virus Evolution

Journal: Virus Evolution

Abbreviation

Virus Evol.

Publisher

Oxford University Press

ISSN

2057-1577

Show all metadata

Search Results

Publications 1 - 10 of 13

Assignment of Epidemiological Lineages in an Emerging Pandemic Using the Pangolin Tool
O’Toole, Áine; Scher, Emily; Underwood, Anthony; et al. (2021)
Virus Evolution
The response of the global virus genomics community to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been unprecedented, with significant advances made towards the ‘real-time’ generation and sharing of SARS-CoV-2 genomic data. The rapid growth in virus genome data production has necessitated the development of new analytical methods that can deal with orders of magnitude of more genomes than previously available. Here, we present and describe Phylogenetic Assignment of Named Global Outbreak Lineages (pangolin), a computational tool that has been developed to assign the most likely lineage to a given SARS-CoV-2 genome sequence according to the Pango dynamic lineage nomenclature scheme. To date, nearly two million virus genomes have been submitted to the web-application implementation of pangolin, which has facilitated the SARS-CoV-2 genomic epidemiology and provided researchers with access to actionable information about the pandemic’s transmission lineages.
The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK
Hill, Verity; du Plessis, Louis; Peacock, Thomas P.; et al. (2022)
Virus Evolution
The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organization as Alpha. Originating in early autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK and the imposition of new restrictions, in particular, the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages that preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically infected individual. We conclude that the latter provides the best explanation of the observed behaviour and dynamics of the variant, although the individual need not be immunocompromised, as persistently infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs and find that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations and a lack of the rapid evolutionary rate on its ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms), it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.
Phenotypic flux: The role of physiology in explaining the conundrum of bacterial persistence amid phage attack
Igler, Claudia (2022)
Virus Evolution
Bacteriophages, the viruses of bacteria, have been studied for over a century. They were not only instrumental in laying the foundations of molecular biology, but they are also likely to play crucial roles in shaping our biosphere and may offer a solution to the control of drug-resistant bacterial infections. However, it remains challenging to predict the conditions for bacterial eradication by phage predation, sometimes even under well-defined laboratory conditions, and, most curiously, if the majority of surviving cells are genetically phage-susceptible. Here, I propose that even clonal phage and bacterial populations are generally in a state of continuous 'phenotypic flux', which is caused by transient and nongenetic variation in phage and bacterial physiology. Phenotypic flux can shape phage infection dynamics by reducing the force of infection to an extent that allows for coexistence between phages and susceptible bacteria. Understanding the mechanisms and impact of phenotypic flux may be key to providing a complete picture of phage-bacteria coexistence. I review the empirical evidence for phenotypic variation in phage and bacterial physiology together with the ways they have been modeled and discuss the potential implications of phenotypic flux for ecological and evolutionary dynamics between phages and bacteria, as well as for phage therapy.
Determinants of SARS-CoV-2 transmission to guide vaccination strategy in an urban area
Brüningk, Sarah Catharina; Klatt, Juliane; Stange, Madlen; et al. (2022)
Virus Evolution
Transmission chains within small urban areas (accommodating ∼30 per cent of the European population) greatly contribute to case burden and economic impact during the ongoing coronavirus pandemic and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in a European urban area, Basel-City (Switzerland). We combined detailed epidemiological, intra-city mobility and socio-economic data sets with whole-genome sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44 per cent of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60 per cent of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare system burden (intensive care unit (ICU) occupancy). Transmissions were driven by socio-economically weaker and highly mobile population groups with mostly cryptic transmissions which lacked genetic and identifiable epidemiological links. Amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90 per cent transmission reduction and 70-90 per cent reduction of severe cases showed that prioritising mobile, socio-economically weaker populations for vaccination would effectively reduce case numbers. However, long-term ICU occupation would also be effectively reduced if senior population groups were prioritised, provided there were no changes in testing and prevention strategies. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area.
SANTA-SIM: Simulating viral sequence evolution dynamics under selection and recombination
Jariani, Abbas; Warth, Christopher; Deforche, Koen; et al. (2019)
Virus Evolution
Simulations are widely used to provide expectations and predictive distributions under known conditions against which to compare empirical data. Such simulations are also invaluable for testing and comparing the behaviour and power of inference methods. We describe SANTA-SIM, a software package to simulate the evolution of a population of gene sequences forwards through time. It models the underlying biological processes as discrete components: replication, recombination, point mutations, insertion–deletions, and selection under various fitness models and population size dynamics. The software is designed to be intuitive to work with for a wide range of users and executable in a cross-platform manner.
The influence of phylodynamic model specifications on parameter estimates of the Zika virus epidemic
Boskova, Veronika; Stadler, Tanja; Magnus, Carsten (2018)
Virus Evolution
Parallel evolution and enhanced virulence upon in vivo passage of an RNA virus in Drosophila melanogaster
Lezcano, Oscar M.; Fuhrmann, Lara; Ramakrishnan, Gayatri; et al. (2023)
Virus Evolution
Virus evolution is strongly affected by antagonistic co-evolution of virus and host. Host immunity positively selects for viruses that evade the immune response, which in turn may drive counter-adaptations in host immune genes. We investigated how host immune pressure shapes virus populations, using the fruit fly Drosophila melanogaster and its natural pathogen Drosophila C virus (DCV), as a model. We performed an experimental evolution study in which DCV was serially passaged for ten generations in three fly genotypes differing in their antiviral RNAi response: wild-type flies and flies in which the endonuclease gene Dicer-2 was either overexpressed or inactivated. All evolved virus populations replicated more efficiently in vivo and were more virulent than the parental stock. The number of polymorphisms increased in all three host genotypes with passage number, which was most pronounced in Dicer-2 knockout flies. Mutational analysis showed strong parallel evolution, as mutations accumulated in a specific region of the VP3 capsid protein in every lineage in a host genotype-independent manner. The parental tyrosine at position ninety-five of VP3 was substituted with either one of five different amino acids in fourteen out of fifteen lineages. However, no consistent amino acid changes were observed in the viral RNAi suppressor gene 1A, nor elsewhere in the genome in any of the host backgrounds. Our study indicates that the RNAi response restricts the sequence space that can be explored by viral populations. Moreover, our study illustrates how evolution towards higher virulence can be a highly reproducible, yet unpredictable process.
Epidemiological inference from pathogen genomes: A review of phylodynamic models and applications
Featherstone, Leo A.; Zhang, Joshua M.; Vaughan, Timothy G.; et al. (2022)
Virus Evolution
Phylodynamics requires an interdisciplinary understanding of phylogenetics, epidemiology, and statistical inference. It has also experienced more intense application than ever before amid the SARS-CoV-2 pandemic. In light of this, we present a review of phylodynamic models beginning with foundational models and assumptions. Our target audience is public health researchers, epidemiologists, and biologists seeking a working knowledge of the links between epidemiology, evolutionary models, and resulting epidemiological inference. We discuss the assumptions linking evolutionary models of pathogen population size to epidemiological models of the infected population size. We then describe statistical inference for phylodynamic models and list how output parameters can be rearranged for epidemiological interpretation. We go on to cover more sophisticated models and finish by highlighting future directions.
Genomic epidemiology of SARS-CoV-2 transmission lineages in Ecuador
Gutierrez, Bernardo; Márquez, Sully; Prado-Vivar, Belén; et al. (2021)
Virus Evolution
Characterisation of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic diversity through space and time can reveal trends in virus importation and domestic circulation and permit the exploration of questions regarding the early transmission dynamics. Here, we present a detailed description of SARS-CoV-2 genomic epidemiology in Ecuador, one of the hardest hit countries during the early stages of the coronavirus-19 pandemic. We generated and analysed 160 whole genome sequences sampled from all provinces of Ecuador in 2020. Molecular clock and phylogeographic analysis of these sequences in the context of global SARS-CoV-2 diversity enable us to identify and characterise individual transmission lineages within Ecuador, explore their spatiotemporal distributions, and consider their introduction and domestic circulation. Our results reveal a pattern of multiple international importations across the country, with apparent differences between key provinces. Transmission lineages were mostly introduced before the implementation of non-pharmaceutical interventions, with differential degrees of persistence and national dissemination.
Estimating the mutational fitness effects distribution during early HIV infection
Bons, Eva; Bertels, Frederic; Regoes, Roland R. (2018)
Virus Evolution
The evolution of HIV during acute infection is often considered a neutral process. Recent analysis of sequencing data from this stage of infection, however, showed high levels of shared mutations between independent viral populations. This suggests that selection might play a role in the early stages of HIV infection. We adapted an existing model for random evolution during acute HIV-infection to include selection. Simulations of this model were used to fit a global mutational fitness effects distribution to previously published sequencing data of the env gene of individuals with acute HIV infection. Measures of sharing between viral populations were used as summary statistics to compare the data to the simulations. We confirm that evolution during acute infection is significantly different from neutral. The distribution of mutational fitness effects is best fit by a distribution with a low, but significant fraction of beneficial mutations and a high fraction of deleterious mutations. While most mutations are neutral or deleterious in this model, about 5% of mutations are beneficial. These beneficial mutations will, on average, result in a small but significant increase in fitness. When assuming no epistasis, this indicates that, at the moment of transmission, HIV is near, but not on the fitness peak for early infection.

Publications 1 - 10 of 13

Journal: Virus Evolution

Abbreviation

Publisher

Journal Volumes

ISSN

Description

Filters

Search Results