Limited cross-species virus transmission in a spatially restricted coral reef fish community

The Great Barrier Reef (GBR) - the largest coral reef ecosystem in the world - supports over 1,200 fish species with some of the highest population densities and diversities observed in vertebrates, offering a high potential for virus transmission among species. As such, the GBR represents an exceptional natural ecosystem to determine the impact of host community diversity on virus evolution and emergence. In recent decades, the GBR has also experienced significant threats of extinction, making it one of the most vulnerable ecosystems on the planet. Despite the global importance of the GBR, our understanding of virus diversity and connectivity in tropical reef fishes remains poor. Here, we employed metatranscriptomic sequencing to reveal the viromes of sixty-one reef fish species. This identified transcripts representing 132 putative viral sequences, 38 of which exhibited strong phylogenetic relationships with known vertebrate-associated viral genera, including a novel Santee-Cooper ranavirus (Iridoviridae). We found little evidence for virus transmission between fish species living within a very restricted geographical space - a 100-m2 coral reef ecosystem - suggesting that there might be important host barriers to successful cross-species transmission despite regular exposure. We also identified differences in virome composition among reef fish families, such that cryptobenthic reef fishes - characterized by small body sizes and short life spans - exhibited greater virome richness compared to large reef fishes. This study suggests that there are important barriers to cross-species virus transmission and that successful emergence in a reef fish community likely requires active host adaptation, even among closely related host species

Inferring demographic parameters in bacterial genomic data using Bayesian and hybrid phylogenetic methods.

BACKGROUND: Recent developments in sequencing technologies make it possible to obtain genome sequences from a large number of isolates in a very short time. Bayesian phylogenetic approaches can take advantage of these data by simultaneously inferring the phylogenetic tree, evolutionary timescale, and demographic parameters (such as population growth rates), while naturally integrating uncertainty in all parameters. Despite their desirable properties, Bayesian approaches can be computationally intensive, hindering their use for outbreak investigations involving genome data for a large numbers of pathogen isolates. An alternative to using full Bayesian inference is to use a hybrid approach, where the phylogenetic tree and evolutionary timescale are estimated first using maximum likelihood. Under this hybrid approach, demographic parameters are inferred from estimated trees instead of the sequence data, using maximum likelihood, Bayesian inference, or approximate Bayesian computation. This can vastly reduce the computational burden, but has the disadvantage of ignoring the uncertainty in the phylogenetic tree and evolutionary timescale. RESULTS: We compared the performance of a fully Bayesian and a hybrid method by analysing six whole-genome SNP data sets from a range of bacteria and simulations. The estimates from the two methods were very similar, suggesting that the hybrid method is a valid alternative for very large datasets. However, we also found that congruence between these methods is contingent on the presence of strong temporal structure in the data (i.e. clocklike behaviour), which is typically verified using a date-randomisation test in a Bayesian framework. To reduce the computational burden of this Bayesian test we implemented a date-randomisation test using a rapid maximum likelihood method, which has similar performance to its Bayesian counterpart. CONCLUSIONS: Hybrid approaches can produce reliable inferences of evolutionary timescales and phylodynamic parameters in a fraction of the time required for fully Bayesian analyses. As such, they are a valuable alternative in outbreak studies involving a large number of isolates

Faecal virome of the Australian grey-headed flying fox from urban/ suburban environments contains novel coronaviruses, retroviruses and sapoviruses

Bats are important reservoirs for viruses of public health and veterinary concern. Virus studies in Australian bats usually target the families Paramyxoviridae, Coronaviridae and Rhabdoviridae, with little known about their overall virome composition. We used metatranscriptomic sequencing to characterise the faecal virome of greyheaded flying foxes from three colonies in urban/suburban locations from two Australian states. We identified viruses from three mammalian-infecting (Coronaviridae, Caliciviridae, Retroviridae) and one possible mammalianinfecting (Birnaviridae) family. Of particular interest were a novel bat betacoronavirus (subgenus Nobecovirus) and a novel bat sapovirus (Caliciviridae), the first identified in Australian bats, as well as a potentially exogenous retrovirus. The novel betacoronavirus was detected in two sampling locations 1375 km apart and falls in a viral lineage likely with a long association with bats. This study highlights the utility of unbiased sequencing of faecal samples for identifying novel viruses and revealing broad-scale patterns of virus ecology and evolution

Cross-validation to select Bayesian hierarchical models in phylogenetics.

BACKGROUND: Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance. RESULTS: We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models. CONCLUSIONS: Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult

COVID-19 vaccine strategies for Aotearoa New Zealand:a mathematical modelling study

Summary: Background: COVID-19 elimination measures, including border closures have been applied in New Zealand. We have modelled the potential effect of vaccination programmes for opening borders.Methods: We used a deterministic age-stratified Susceptible, Exposed, Infectious, Recovered (SEIR) model. We minimised spread by varying the age-stratified vaccine allocation to find the minimum herd immunity requirements (the effective reproduction number Reff<1 with closed borders) under various vaccine effectiveness (VE) scenarios and R0 values. We ran two-year open-border simulations for two vaccine strategies: minimising Reff and targeting high-risk groups.Findings: Targeting of high-risk groups will result in lower hospitalisations and deaths in most scenarios. Reaching the herd immunity threshold (HIT) with a vaccine of 90% VE against disease and 80% VE against infection requires at least 86•5% total population uptake for R0=4•5 (with high vaccination coverage for 30–49-year-olds) and 98•1% uptake for R0=6. In a two-year open-border scenario with 10 overseas cases daily and 90% total population vaccine uptake (including 0–15 year olds) with the same vaccine, the strategy of targeting high-risk groups is close to achieving HIT, with an estimated 11,400 total hospitalisations (peak 324 active and 36 new daily cases in hospitals), and 1,030 total deaths.Interpretation: Targeting high-risk groups for vaccination will result in fewer hospitalisations and deaths with open borders compared to targeting reduced transmission. With a highly effective vaccine and a high total uptake, opening borders will result in increasing cases, hospitalisations, and deaths. Other public health and social measures will still be required as part of an effective pandemic response.Funding: This project was funded by the Health Research Council [20/1018].Research in contex

Five Challenges in the Field of Viral Diversity and Evolution

Viral diversity and evolution play a central role in processes such as disease emergence, vaccine failure, drug resistance, and virulence. However, significant challenges remain to better understand and manage these processes. Here, we discuss five of these challenges. These include improving our ability to predict viral evolution, developing more relevant experimental evolutionary systems, integrating viral dynamics and evolution at different scales, more thoroughly characterizing the virosphere, and deepening our understanding of virus-virus interactions. Intensifying future research on these areas should improve our ability to combat viral diseases, as well as to more efficiently use viral diversity and evolution for biotechnological purposes

The origins of SARS-CoV-2: a critical review

Since the first reports of a novel severe acute respiratory syndrome (SARS)-like coronavirus in December 2019 in Wuhan, China, there has been intense interest in understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the human population. Recent debate has coalesced around two competing ideas: a “laboratory escape” scenario and zoonotic emergence. Here, we critically review the current scientific evidence that may help clarify the origin of SARS-CoV-2

A generic assay for whole-genome amplification and deep sequencing of enterovirus A71

Enterovirus A71 (EV-A71) has emerged as the most important cause of large outbreaks of severe and sometimes fatal hand, foot and mouth disease (HFMD) across the Asia-Pacific region. EV-A71 outbreaks have been associated with (sub)genogroup switches, sometimes accompanied by recombination events. Understanding EV-A71 population dynamics is therefore essential for understanding this emerging infection, and may provide pivotal information for vaccine development. Despite the public health burden of EV-A71, relatively few EV-A71 complete-genome sequences are available for analysis and from limited geographical localities. The availability of an efficient procedure for whole-genome sequencing would stimulate effort to generate more viral sequence data. Herein, we report for the first time the development of a next-generation sequencing based protocol for whole-genome sequencing of EV-A71 directly from clinical specimens. We were able to sequence viruses of subgenogroup C4 and B5, while RNA from culture materials of diverse EV-A71 subgenogroups belonging to both genogroup B and C was successfully amplified. The nature of intra-host genetic diversity was explored in 22 clinical samples, revealing 107 positions carrying minor variants (ranging from 0 to 15 variants per sample). Our analysis of EV-A71 strains sampled in 2013 showed that they all belonged to subgenogroup B5, representing the first report of this subgenogroup in Vietnam. In conclusion, we have successfully developed a high-throughput next-generation sequencing-based assay for whole-genome sequencing of EV-A71 from clinical samples

Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2

Publisher Copyright: © 2021 O'Toole Á et al.Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the software tool grinch (global report investigating novel coronavirus haplotypes), we track the international spread of lineages of concern with automated daily reports, Further, we have built a custom tracking website (cov-lineages.org/global_report.html) which hosts this daily report and will continue to include novel SARS-CoV-2 lineages of concern as they are detected.Peer reviewe