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.

How accurately can we assess zoonotic risk?

Identifying the animal reservoirs from which zoonotic viruses will likely emerge is central to understanding the determinants of disease emergence. Accordingly, there has been an increase in studies attempting zoonotic "risk assessment." Herein, we demonstrate that the virological data on which these analyses are conducted are incomplete, biased, and rapidly changing with ongoing virus discovery. Together, these shortcomings suggest that attempts to assess zoonotic risk using available virological data are likely to be inaccurate and largely only identify those host taxa that have been studied most extensively. We suggest that virus surveillance at the human-animal interface may be more productive.

The phylogenomics of evolving virus virulence.

How virulence evolves after a virus jumps to a new host species is central to disease emergence. Our current understanding of virulence evolution is based on insights drawn from two perspectives that have developed largely independently: long-standing evolutionary theory based on limited real data examples that often lack a genomic basis, and experimental studies of virulence-determining mutations using cell culture or animal models. A more comprehensive understanding of virulence mutations and their evolution can be achieved by bridging the gap between these two research pathways through the phylogenomic analysis of virus genome sequence data as a guide to experimental study.

Host and geography impact virus diversity in New Zealand's longfin and shortfin eels.

The fishing and aquaculture industry is vital for global food security, yet viral diseases can result in mass fish die-off events. Determining the viromes of traditionally understudied species, such as fish, enhances our understanding of the global virosphere and the factors that influence virome composition and disease emergence. Very little is known about the viruses present in New Zealand's native fish species, including the shortfin eel (Anguilla australis) and the longfin eel (Anguilla dieffenbachii), both of which are fished culturally by Maori (the indigenous population of New Zealand) and commercially. Through a total RNA metatranscriptomic analysis of longfin and shortfin eels across three different geographic locations in the South Island of New Zealand, we aimed to determine whether viruses had jumped between the two eel species and whether eel virome composition was impacted by life stage, species, and geographic location. We identified nine viral species spanning eight different families, thereby enhancing our understanding of eel virus diversity in New Zealand and the host range of these viral families. Viruses of the family Flaviviridae (genus Hepacivirus) were widespread and found in both longfin and shortfin eels, indicative of cross-species transmission or virus-host co-divergence. Notably, both host specificity and geographic location appeared to influence eel virome composition, highlighting the complex interaction between viruses, hosts, and their ecosystems. This study broadens our understanding of viromes in aquatic hosts and highlights the importance of gaining baseline knowledge of fish viral abundance and diversity, particularly in aquatic species that are facing population declines.

Exploring the depth and breadth of the genomics toolbox during the COVID-19 pandemic: insights from Aotearoa New Zealand.

BACKGROUND: Genomic technologies have become routine in the surveillance and monitoring of the coronavirus disease 2019 (COVID-19) pandemic, as evidenced by the millions of SARS-CoV-2 sequences uploaded to international databases. Yet the ways in which these technologies have been applied to manage the pandemic are varied. MAIN TEXT: Aotearoa New Zealand was one of a small number of countries to adopt an elimination strategy for COVID-19, establishing a managed isolation and quarantine system for all international arrivals. To aid our response, we rapidly set up and scaled our use of genomic technologies to help identify community cases of COVID-19, to understand how they had arisen, and to determine the appropriate action to maintain elimination. Once New Zealand pivoted from elimination to suppression in late 2021, our genomic response changed to focusing on identifying new variants arriving at the border, tracking their incidence around the country, and examining any links between specific variants and increased disease severity. Wastewater detection, quantitation and variant detection were also phased into the response. Here, we explore New Zealand's genomic journey through the pandemic and provide a high-level overview of the lessons learned and potential future capabilities to better prepare for future pandemics. CONCLUSIONS: Our commentary is aimed at health professionals and decision-makers who might not be familiar with genetic technologies, how they can be used, and why this is an area with great potential to assist in disease detection and tracking now and in the future.

Transcriptome Mining Expands Knowledge of RNA Viruses across the Plant Kingdom.

Our current understanding of plant viruses stems largely from those affecting economically important plants. Yet plant species in cultivation represent a small and biased subset of the plant kingdom. Here, we describe virus diversity and abundance in 1,079 transcriptomes from species across the breadth of the plant kingdom (Archaeplastida) by analyzing open-source data from the 1000 Plant Transcriptomes Initiative (1KP). We identified 104 potentially novel viruses, of which 40% were single-stranded positive-sense RNA viruses across eight orders, including members of the Hepelivirales, Tymovirales, Cryppavirales, Martellivirales, and Picornavirales. One-third of the newly described viruses were double-stranded RNA viruses from the orders Durnavirales and Ghabrivirales. The remaining were negative-sense RNA viruses from the Rhabdoviridae, Aspiviridae, Yueviridae, and Phenuiviridae and the newly proposed Viridisbunyaviridae. Our analysis considerably expands the known host range of 13 virus families to include lower plants (e.g., Benyviridae and Secoviridae) and 4 virus families to include alga hosts (e.g., Tymoviridae and Chrysoviridae). More broadly, however, a cophylogeny analysis revealed that the evolutionary history of these families is largely driven by cross-species transmission events. The discovery of the first 30-kDa movement protein in a nonvascular plant suggests that the acquisition of plant virus movement proteins occurred prior to the emergence of the plant vascular system. Together, these data highlight that numerous RNA virus families are associated with older evolutionary plant lineages than previously thought and that the apparent scarcity of RNA viruses found in lower plants likely reflects a lack of investigation rather than their absence. IMPORTANCE Our knowledge of plant viruses is mainly limited to those infecting economically important host species. In particular, we know little about those viruses infecting basal plant lineages such as the ferns, lycophytes, bryophytes, and charophytes. To expand this understanding, we conducted a broad-scale viral survey of species across the breadth of the plant kingdom. We found that basal plants harbor a wide diversity of RNA viruses, including some that are sufficiently divergent to likely compose a new virus family. The basal plant virome revealed offers key insights into the evolutionary history of core plant virus gene modules and genome segments. More broadly, this work emphasizes that the scarcity of viruses found in these species to date most likely reflects the limited research in this area.

Airborne Transmission of SARS-CoV-2 Delta Variant within Tightly Monitored Isolation Facility, New Zealand (Aotearoa).

In New Zealand, international arrivals are quarantined and undergo severe acute respiratory syndrome coronavirus 2 screening; those who test positive are transferred to a managed isolation facility (MIF). Solo traveler A and person E from a 5-person travel group (BCDEF) tested positive. After transfer to the MIF, person A and group BCDEF occupied rooms >2 meters apart across a corridor. Persons B, C, and D subsequently tested positive; viral sequences matched A and were distinct from E. The MIF was the only shared location of persons A and B, C, and D, and they had no direct contact. Security camera footage revealed 4 brief episodes of simultaneous door opening during person A's infectious period. This public health investigation demonstrates transmission from A to B, C, and D while in the MIF, with airborne transmission the most plausible explanation. These findings are of global importance for coronavirus disease public health interventions and infection control practices.

Real-Time Genomics for Tracking Severe Acute Respiratory Syndrome Coronavirus 2 Border Incursions after Virus Elimination, New Zealand.

Since severe acute respiratory syndrome coronavirus 2 was first eliminated in New Zealand in May 2020, a total of 13 known coronavirus disease (COVID-19) community outbreaks have occurred, 2 of which led health officials to issue stay-at-home orders. These outbreaks originated at the border via isolating returnees, airline workers, and cargo vessels. Because a public health system was informed by real-time viral genomic sequencing and complete genomes typically were available within 12 hours of community-based positive COVID-19 test results, every outbreak was well-contained. A total of 225 community cases resulted in 3 deaths. Real-time genomics were essential for establishing links between cases when epidemiologic data could not do so and for identifying when concurrent outbreaks had different origins.

Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 during Border Quarantine and Air Travel, New Zealand (Aotearoa).

The strategy in New Zealand (Aotearoa) to eliminate coronavirus disease requires that international arrivals undergo managed isolation and quarantine and mandatory testing for severe acute respiratory syndrome coronavirus 2. Combining genomic and epidemiologic data, we investigated the origin of an acute case of coronavirus disease identified in the community after the patient had spent 14 days in managed isolation and quarantine and had 2 negative test results. By combining genomic sequence analysis and epidemiologic investigations, we identified a multibranched chain of transmission of this virus, including on international and domestic flights, as well as a probable case of aerosol transmission without direct person-to-person contact. These findings show the power of integrating genomic and epidemiologic data to inform outbreak investigations.

Use of Genomics to Track Coronavirus Disease Outbreaks, New Zealand.

Real-time genomic sequencing has played a major role in tracking the global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), contributing greatly to disease mitigation strategies. In August 2020, after having eliminated the virus, New Zealand experienced a second outbreak. During that outbreak, New Zealand used genomic sequencing in a primary role, leading to a second elimination of the virus. We generated genomes from 78% of the laboratory-confirmed samples of SARS-CoV-2 from the second outbreak and compared them with the available global genomic data. Genomic sequencing rapidly identified that virus causing the second outbreak in New Zealand belonged to a single cluster, thus resulting from a single introduction. However, successful identification of the origin of this outbreak was impeded by substantial biases and gaps in global sequencing data. Access to a broader and more heterogenous sample of global genomic data would strengthen efforts to locate the source of any new outbreaks.

Genomic Evidence of In-Flight Transmission of SARS-CoV-2 Despite Predeparture Testing.

Since the first wave of coronavirus disease in March 2020, citizens and permanent residents returning to New Zealand have been required to undergo managed isolation and quarantine (MIQ) for 14 days and mandatory testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of October 20, 2020, of 62,698 arrivals, testing of persons in MIQ had identified 215 cases of SARS-CoV-2 infection. Among 86 passengers on a flight from Dubai, United Arab Emirates, that arrived in New Zealand on September 29, test results were positive for 7 persons in MIQ. These passengers originated from 5 different countries before a layover in Dubai; 5 had negative predeparture SARS-CoV-2 test results. To assess possible points of infection, we analyzed information about their journeys, disease progression, and virus genomic data. All 7 SARS-CoV-2 genomes were genetically identical, except for a single mutation in 1 sample. Despite predeparture testing, multiple instances of in-flight SARS-CoV-2 transmission are likely.

Continental synchronicity of human influenza virus epidemics despite climatic variation.

The factors that determine the pattern and rate of spread of influenza virus at a continental-scale are uncertain. Although recent work suggests that influenza epidemics in the United States exhibit a strong geographical correlation, the spatiotemporal dynamics of influenza in Australia, a country and continent of approximately similar size and climate complexity but with a far smaller population, are not known. Using a unique combination of large-scale laboratory-confirmed influenza surveillance comprising >450,000 entries and genomic sequence data we determined the local-level spatial diffusion of this important human pathogen nationwide in Australia. We used laboratory-confirmed influenza data to characterize the spread of influenza virus across Australia during 2007-2016. The onset of established epidemics varied across seasons, with highly synchronized epidemics coinciding with the emergence of antigenically distinct viruses, particularly during the 2009 A/H1N1 pandemic. The onset of epidemics was largely synchronized between the most populous cities, even those separated by distances of >3000 km and those that experience vastly diverse climates. In addition, by analyzing global phylogeographic patterns we show that the synchronized dissemination of influenza across Australian cities involved multiple introductions from the global influenza population, coupled with strong domestic connectivity, rather than through the distinct radial patterns of geographic dispersal that are driven by work-flow transmission as observed in the United States. In addition, by comparing the spatial structure of influenza A and B, we found that these viruses tended to occupy different geographic regions, and peak in different seasons, perhaps indicative of moderate cross-protective immunity or viral interference effects. The highly synchronized outbreaks of influenza virus at a continental-scale revealed here highlight the importance of coordinated public health responses in the event of the emergence of a novel, human-to-human transmissible, virus.

Correction: Continental synchronicity of human influenza virus epidemics despite climactic variation.

[This corrects the article DOI: 10.1371/journal.ppat.1006780.].

High diversity and rapid spatial turnover of integron gene cassettes in soil.

Integrons are genetic elements that promote rapid adaptation in bacteria by capturing exogenous, mobile gene cassettes. Recently, a subset of gene cassettes has facilitated the global spread of antibiotic resistance. However, outside clinical settings, very little is known about their diversity and spatial ecology. To address this question, we sequenced integron gene cassettes from soils sampled across Australia and Antarctica. We recovered 44 970 open reading frames that encoded 27 215 unique proteins, representing an order of magnitude more cassettes than previous sequencing efforts. We found that cassettes have extremely high local richness, significantly greater than previously predicted, with estimates ranging from 4000 to 18 000 unique cassettes per 0.3 g of soil. We show that cassettes have a heterogeneous distribution across space, and that they exhibit rapid turnover with distance. Similarity between samples drops to between 0.1% and 10% at distances of as little as 100 m. Together, these data provide key insights into the ecology and size of the gene cassette metagenome.

Comparative analysis estimates the relative frequencies of co-divergence and cross-species transmission within viral families.

The cross-species transmission of viruses from one host species to another is responsible for the majority of emerging infections. However, it is unclear whether some virus families have a greater propensity to jump host species than others. If related viruses have an evolutionary history of co-divergence with their hosts there should be evidence of topological similarities between the virus and host phylogenetic trees, whereas host jumping generates incongruent tree topologies. By analyzing co-phylogenetic processes in 19 virus families and their eukaryotic hosts we provide a quantitative and comparative estimate of the relative frequency of virus-host co-divergence versus cross-species transmission among virus families. Notably, our analysis reveals that cross-species transmission is a near universal feature of the viruses analyzed here, with virus-host co-divergence occurring less frequently and always on a subset of viruses. Despite the overall high topological incongruence among virus and host phylogenies, the Hepadnaviridae, Polyomaviridae, Poxviridae, Papillomaviridae and Adenoviridae, all of which possess double-stranded DNA genomes, exhibited more frequent co-divergence than the other virus families studied here. At the other extreme, the virus and host trees for all the RNA viruses studied here, particularly the Rhabdoviridae and the Picornaviridae, displayed high levels of topological incongruence, indicative of frequent host switching. Overall, we show that cross-species transmission plays a major role in virus evolution, with all the virus families studied here having the potential to jump host species, and that increased sampling will likely reveal more instances of host jumping.

Virological factors that increase the transmissibility of emerging human viruses.

The early detection of pathogens with epidemic potential is of major importance to public health. Most emerging infections result in dead-end "spillover" events in which a pathogen is transmitted from an animal reservoir to a human but is unable to achieve the sustained human-to-human transmission necessary for a full-blown epidemic. It is therefore critical to determine why only some virus infections are efficiently transmitted among humans whereas others are not. We sought to determine which biological features best characterized those viruses that have achieved sustained human transmission. Accordingly, we compiled a database of 203 RNA and DNA human viruses and used an information theoretic approach to assess which of a set of key biological variables were the best predictors of human-to-human transmission. The variables analyzed were as follows: taxonomic classification; genome length, type, and segmentation; the presence or absence of an outer envelope; recombination frequency; duration of infection; host mortality; and whether or not a virus exhibits vector-borne transmission. This comparative analysis revealed multiple strong associations. In particular, we determined that viruses with low host mortality, that establish long-term chronic infections, and that are nonsegmented, nonenveloped, and, most importantly, not transmitted by vectors were more likely to be transmissible among humans. In contrast, variables including genome length, genome type, and recombination frequency had little predictive power. In sum, we have identified multiple biological features that seemingly determine the likelihood of interhuman viral transmissibility, in turn enabling general predictions of whether viruses of a particular type will successfully emerge in human populations.

A comparison of methods for estimating substitution rates from ancient DNA sequence data.

BACKGROUND: Phylogenetic analysis of DNA from modern and ancient samples allows the reconstruction of important demographic and evolutionary processes. A critical component of these analyses is the estimation of evolutionary rates, which can be calibrated using information about the ages of the samples. However, the reliability of these rate estimates can be negatively affected by among-lineage rate variation and non-random sampling. Using a simulation study, we compared the performance of three phylogenetic methods for inferring evolutionary rates from time-structured data sets: regression of root-to-tip distances, least-squares dating, and Bayesian inference. We also applied these three methods to time-structured mitogenomic data sets from six vertebrate species. RESULTS: Our results from 12 simulation scenarios show that the three methods produce reliable estimates when the substitution rate is high, rate variation is low, and samples of similar ages are not all grouped together in the tree (i.e., low phylo-temporal clustering). The interaction of these factors is particularly important for least-squares dating and Bayesian estimation of evolutionary rates. The three estimation methods produced consistent estimates of rates across most of the six mitogenomic data sets, with sequence data from horses being an exception. CONCLUSIONS: We recommend that phylogenetic studies of ancient DNA sequences should use multiple methods of inference and test for the presence of temporal signal, among-lineage rate variation, and phylo-temporal clustering in the data.

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.