Reconstruction and prediction of viral disease epidemics.

A growing number of infectious pathogens are spreading among geographic regions. Some pathogens that were previously not considered to pose a general threat to human health have emerged at regional and global scales, such as Zika and Ebola Virus Disease. Other pathogens, such as yellow fever virus, were previously thought to be under control but have recently re-emerged, causing new challenges to public health organisations. A wide array of new modelling techniques, aided by increased computing capabilities, novel diagnostic tools, and the increased speed and availability of genomic sequencing allow researchers to identify new pathogens more rapidly, assess the likelihood of geographic spread, and quantify the speed of human-to-human transmission. Despite some initial successes in predicting the spread of acute viral infections, the practicalities and sustainability of such approaches will need to be evaluated in the context of public health responses.

Phylogenetic clustering of hepatitis C virus among people who inject drugs in Vancouver, Canada.

UNLABELLED: Little is known about factors associated with hepatitis C virus (HCV) transmission among people who inject drugs (PWID). Phylogenetic clustering and associated factors were evaluated among PWID in Vancouver, Canada. Data were derived from the Vancouver Injection Drug Users Study. Participants who were HCV antibody-positive at enrolment and those with HCV antibody seroconversion during follow-up (1996 to 2012) were tested for HCV RNA and sequenced (Core-E2 region). Phylogenetic trees were inferred using maximum likelihood analysis and clusters were identified using ClusterPicker (90% bootstrap threshold, 0.05 genetic distance threshold). Factors associated with clustering were assessed using logistic regression. Among 655 eligible participants, HCV genotype prevalence was: G1a: 48% (n=313), G1b: 6% (n=41), G2a: 3% (n=20), G2b: 7% (n=46), G3a: 33% (n=213), G4a: <1% (n=4), G6a: 1% (n=8), G6e: <1% (n=1), and unclassifiable: 1% (n=9). The mean age was 36 years, 162 (25%) were female, and 164 (25%) were HIV+. Among 501 participants with HCV G1a and G3a, 31% (n=156) were in a pair/cluster. Factors independently associated with phylogenetic clustering included: age <40 (versus age≥40, adjusted odds ratio [AOR]=1.64; 95% confidence interval [CI] 1.03, 2.63), human immunodeficiency virus (HIV) infection (AOR=1.82; 95% CI 1.18, 2.81), HCV seroconversion (AOR=3.05; 95% CI 1.40, 6.66), and recent syringe borrowing (AOR 1.59; 95% CI 1.07, 2.36). CONCLUSION: In this sample of PWID, one-third demonstrated phylogenetic clustering. Factors independently associated with phylogenetic clustering included younger age, recent HCV seroconversion, prevalent HIV infection, and recent syringe borrowing. Strategies to enhance the delivery of prevention and/or treatment strategies to those with HIV and recent HCV seroconversion should be explored, given an increased likelihood of HCV transmission in these subpopulations.

The evolutionary history of hepaciviruses.

In the search for natural reservoirs of hepatitis C virus (HCV), a broad diversity of non-human viruses within the Hepacivirus genus has been uncovered. However, the evolutionary dynamics that shaped the diversity and timescale of hepaciviruses evolution remain elusive. To gain further insights into the origins and evolution of this genus, we screened a large dataset of wild mammal samples (n = 1,672) from Africa and Asia, and generated 34 full-length hepacivirus genomes. Phylogenetic analysis of these data together with publicly available genomes emphasizes the importance of rodents as hepacivirus hosts and we identify 13 rodent species and 3 rodent genera (in Cricetidae and Muridae families) as novel hosts of hepaciviruses. Through co-phylogenetic analyses, we demonstrate that hepacivirus diversity has been affected by cross-species transmission events against the backdrop of detectable signal of virus-host co-divergence in the deep evolutionary history. Using a Bayesian phylogenetic multidimensional scaling approach, we explore the extent to which host relatedness and geographic distances have structured present-day hepacivirus diversity. Our results provide evidence for a substantial structuring of mammalian hepacivirus diversity by host as well as geography, with a somewhat more irregular diffusion process in geographic space. Finally, using a mechanistic model that accounts for substitution saturation, we provide the first formal estimates of the timescale of hepacivirus evolution and estimate the origin of the genus to be about 22 million years ago. Our results offer a comprehensive overview of the micro- and macroevolutionary processes that have shaped hepacivirus diversity and enhance our understanding of the long-term evolution of the Hepacivirus genus.

Estimating reassortment rates in co-circulating Eurasian swine influenza viruses.

Swine have often been considered as a mixing vessel for different influenza strains. In order to assess their role in more detail, we undertook a retrospective sequencing study to detect and characterize the reassortants present in European swine and to estimate the rate of reassortment between H1N1, H1N2 and H3N2 subtypes with Eurasian (avian-like) internal protein-coding segments. We analysed 69 newly obtained whole genome sequences of subtypes H1N1-H3N2 from swine influenza viruses sampled between 1982 and 2008, using Illumina and 454 platforms. Analyses of these genomes, together with previously published genomes, revealed a large monophyletic clade of Eurasian swine-lineage polymerase segments containing H1N1, H1N2 and H3N2 subtypes. We subsequently examined reassortments between the haemagglutinin and neuraminidase segments and estimated the reassortment rates between lineages using a recently developed evolutionary analysis method. High rates of reassortment between H1N2 and H1N1 Eurasian swine lineages were detected in European strains, with an average of one reassortment every 2-3 years. This rapid reassortment results from co-circulating lineages in swine, and in consequence we should expect further reassortments between currently circulating swine strains and the recent swine-origin H1N1v pandemic strain.

The ecology and age structure of a highly pathogenic avian influenza virus outbreak in wild mute swans.

The first UK epizootic of highly pathogenic (HP) H5N1 influenza in wild birds occurred in 2008, in a population of mute swans that had been the subject of ornithological study for decades. Here we use an innovative combination of ornithological, phylogenetic and immunological approaches to investigate the ecology and age structure of HP H5N1 in nature. We screened samples from swans and waterbirds using PCR and sequenced HP H5N1-positive samples. The outbreak's origin was investigated by linking bird count data with a molecular clock analysis of sampled virus sequences. We used ringing records to reconstruct the age-structure of outbreak mortality, and we estimated the age distribution of prior exposure to avian influenza. Outbreak mortality was low and all HP H5N1-positive mute swans in the affected population were <3 years old. Only the youngest age classes contained an appreciable number of individuals with no detectable antibody responses to viral nucleoprotein. Phylogenetic analysis indicated that the outbreak strain circulated locally for ~1 month before detection and arrived when the immigration rate of migrant waterbirds was highest. Our data are consistent with the hypothesis that HP H5N1 epizootics in wild swans exhibit limited mortality due to immune protection arising from previous exposure. Our study population may represent a valuable resource for investigating the natural ecology and epidemiology of avian influenza.

Epidemic dynamics revealed in dengue evolution.

Dengue is an emerging tropical disease infecting tens of millions of people annually. A febrile illness with potentially severe hemorrhagic manifestations, dengue is caused by mosquito-borne viruses (DENV-1 to -4) that are maintained in endemic transmission in large urban centers of the tropics with periodic epidemic cycles at 3- to 5-year intervals. Puerto Rico (PR), a major population center in the Caribbean, has experienced increasingly severe epidemics since multiple dengue serotypes were introduced beginning in the late 1970s. We document the phylodynamics of DENV-4 between 1981 and 1998, a period of dramatic ecological expansion during which evolutionary change also occurs. The timescale of viral evolution is sufficiently short that viral transmission dynamics can be elucidated from genetic diversity data. Specifically, by combining virus sequence data with confirmed case counts in PR over these two decades, we show that the pattern of cyclic epidemics is strongly correlated with coalescent estimates of effective population size that have been estimated from sampled virus sequences using Bayesian Markov Chain Monte Carlo methods. Thus, we show that the observed epidemiologic dynamics are correlated with similar fluctuations in diversity, including severe interepidemic reductions in genetic diversity compatible with population bottlenecks that may greatly impact DENV evolutionary dynamics. Mean effective population sizes based on genetic data appear to increase prior to isolation counts, suggesting a potential bias in the latter and justifying more active surveillance of DENV activity. Our analysis explicitly integrates epidemiologic and sequence data in a joint model that could be used to further explore transmission models of infectious disease.

New trends of HCV infection in China revealed by genetic analysis of viral sequences determined from first-time volunteer blood donors.

Recently, we studied hepatitis C virus (HCV) sera-prevalence among 559 890 first-time volunteer blood donors in China. From randomly selected 450 anti-HCV positive donors, we detected HCV RNA in 270 donors. In this study, we amplified HCV E1 and/or NS5B sequences from 236 of these donors followed by DNA sequencing and phylogenetic analysis. The results indicate new trends of HCV infection in China. The HCV genotype distribution differed according to the donors' region of origin. Among donors from Guangdong province, we detected subtypes 6a, 1b, 3a, 3b, 2a, and 1a at frequencies of 49.7%, 31.0%, 7.6%, 5.5%, 4.1%, and 2.1%, respectively. Among donors from outside Guangdong, we detected 1b, 2a, 6a, 3b, 3a, 6e, and 6n at frequencies 57.1%, 13.2%, 11.0%, 9.9%, 4.4%, 2.2%, and 2.2%, respectively. Although we found no significant differences among regions in age or gender, subtype 6a was more common (P < 0.001) in donors from Guangdong than those from elsewhere, whilst subtypes 1b (P < 0.02) and 2a (P < 0.001) were more frequent outside Guangdong. Disregarding origins, the male/female ratio was higher for subtype 6a-infected donors (P < 0.05) than for subtype 1b donors, whilst the mean age of subtype 2a donors was 8-10 years older (P < 0.05) than that for all other subtypes. Detailed phylogenetic analysis of our sequence data provides further insight into the transmission of HCV within China, and between China and other countries. The predominance of HCV 6a among blood donors in Guangdong is striking and mandates studies into risk factors for its acquisition.

Phylodynamics for cell biologists.

Multicellular organisms are composed of cells connected by ancestry and descent from progenitor cells. The dynamics of cell birth, death, and inheritance within an organism give rise to the fundamental processes of development, differentiation, and cancer. Technical advances in molecular biology now allow us to study cellular composition, ancestry, and evolution at the resolution of individual cells within an organism or tissue. Here, we take a phylogenetic and phylodynamic approach to single-cell biology. We explain how "tree thinking" is important to the interpretation of the growing body of cell-level data and how ecological null models can benefit statistical hypothesis testing. Experimental progress in cell biology should be accompanied by theoretical developments if we are to exploit fully the dynamical information in single-cell data.

The epidemic behavior of the hepatitis C virus.

Hepatitis C virus (HCV) is a leading worldwide cause of liver disease. Here, we use a new model of HCV spread to investigate the epidemic behavior of the virus and to estimate its basic reproductive number from gene sequence data. We find significant differences in epidemic behavior among HCV subtypes and suggest that these differences are largely the result of subtype-specific transmission patterns. Our model builds a bridge between the disciplines of population genetics and mathematical epidemiology by using pathogen gene sequences to infer the population dynamic history of an infectious disease.

Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings.

Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements during outbreaks are, however, difficult to obtain and may not be available during future epidemics. The Ebola virus disease (EVD) outbreak in West Africa between 2014-16 demonstrated how quickly pathogens can spread to large urban centers following one cross-species transmission event. Here we describe a flexible transmission model to test the utility of generalised human movement models in estimating EVD cases and spatial spread over the course of the outbreak. A transmission model that includes a general model of human mobility significantly improves prediction of EVD's incidence compared to models without this component. Human movement plays an important role not only to ignite the epidemic in locations previously disease free, but over the course of the entire epidemic. We also demonstrate important differences between countries in population mixing and the improved prediction attributable to movement metrics. Given their relative rareness, locally derived mobility data are unlikely to exist in advance of future epidemics or pandemics. Our findings show that transmission patterns derived from general human movement models can improve forecasts of spatio-temporal transmission patterns in places where local mobility data is unavailable.

High prevalence of hepatitis C virus infection and predominance of genotype 4 in rural Gabon.

Hepatitis C (HCV) molecular epidemiology is documented poorly in central African countries. In response to this, a population-based study of 319 consenting adults resident in a remote village of Gabon was undertaken (mean age: 38 years; age range: 13-85+; sex ratio: 0.74). Screening for anti-HCV antibodies was performed using ELISA and recombinant immunoblot assay. Seropositive samples were assessed further with viral load and genotyping techniques. Sixty-six (20.7%) individuals were HCV seropositive. Viral loads ranged from 600 to 24.9 million IU/ml (median: 372,500). Seroprevalence and viral loads increased significantly with age (P < 10(-5) and P < 0.003, respectively). HCV sequences of the 5'UTR genome region were obtained from 60 (90.9%) samples and NS5B region sequences were obtained from 22 (36.6%) samples. All strains belonged to subtypes of genotype 4: 4e (72.7%), 4c (13.6%), 4p (4.5%), 4r (4.5%) and one unclassified genotype 4 strain. Evolutionary analysis of the subtype 4e sequences indicates a period of raised transmission during the early twentieth century.

Evolution of the human immunodeficiency virus envelope gene is dominated by purifying selection.

The evolution of the human immunodeficiency virus (HIV-1) during chronic infection involves the rapid, continuous turnover of genetic diversity. However, the role of natural selection, relative to random genetic drift, in governing this process is unclear. We tested a stochastic model of genetic drift using partial envelope sequences sampled longitudinally in 28 infected children. In each case the Bayesian posterior (empirical) distribution of coalescent genealogies was estimated using Markov chain Monte Carlo methods. Posterior predictive simulation was then used to generate a null distribution of genealogies assuming neutrality, with the null and empirical distributions compared using four genealogy-based summary statistics sensitive to nonneutral evolution. Because both null and empirical distributions were generated within a coalescent framework, we were able to explicitly account for the confounding influence of demography. From the distribution of corrected P-values across patients, we conclude that empirical genealogies are more asymmetric than expected if evolution is driven by mutation and genetic drift only, with an excess of low-frequency polymorphisms in the population. This indicates that although drift may still play an important role, natural selection has a strong influence on the evolution of HIV-1 envelope. A negative relationship between effective population size and substitution rate indicates that as the efficacy of selection increases, a smaller proportion of mutations approach fixation in the population. This suggests the presence of deleterious mutations. We therefore conclude that intrahost HIV-1 evolution in envelope is dominated by purifying selection against low-frequency deleterious mutations that do not reach fixation.

First Complete Genome Sequences of Zika Virus Isolated from Febrile Patient Sera in Ecuador.

Here, we present the complete genome sequences of two Zika virus (ZIKV) strains, EcEs062_16 and EcEs089_16, isolated from the sera of febrile patients in Esmeraldas City, in the northern coastal province of Esmeraldas, Ecuador, in April 2016. These are the first complete ZIKV genomes to be reported from Ecuador.

An integrated framework for the inference of viral population history from reconstructed genealogies.

We describe a unified set of methods for the inference of demographic history using genealogies reconstructed from gene sequence data. We introduce the skyline plot, a graphical, nonparametric estimate of demographic history. We discuss both maximum-likelihood parameter estimation and demographic hypothesis testing. Simulations are carried out to investigate the statistical properties of maximum-likelihood estimates of demographic parameters. The simulations reveal that (i) the performance of exponential growth model estimates is determined by a simple function of the true parameter values and (ii) under some conditions, estimates from reconstructed trees perform as well as estimates from perfect trees. We apply our methods to HIV-1 sequence data and find strong evidence that subtypes A and B have different demographic histories. We also provide the first (albeit tentative) genetic evidence for a recent decrease in the growth rate of subtype B.

Testing macro-evolutionary models using incomplete molecular phylogenies.

Phylogenies reconstructed from gene sequences can be used to investigate the tempo and mode of species diversification. Here we develop and use new statistical methods to infer past patterns of speciation and extinction from molecular phylogenies. Specifically, we test the null hypothesis that per-lineage speciation and extinction rates have remained constant through time. Rejection of this hypothesis may provide evidence for evolutionary events such as adaptive radiations or key adaptations. In contrast to previous approaches, our methods are robust to incomplete taxon sampling and are conservative with respect to extinction. Using simulation we investigate, first, the adverse effects of failing to take incomplete sampling into account and, second, the power and reliability of our tests. When applied to published phylogenies our tests suggest that, in some cases, speciation rates have decreased through time.

Genetic diversity and models of viral evolution for the hepatitis C virus.

In this review we discuss the application of theoretical frameworks to the interpretation of viral gene sequence data, with particular reference to the hepatitis C virus (HCV). The increasing availability of such data means that it is now possible (and necessary) to proceed from simple qualitative models of viral evolution, to more quantitative frameworks based on statistical inference, notably population genetics and molecular phylogenetics. We argue that these approaches are invaluable tools to the virologist and are essential for understanding the dynamics of viral infection and the outcome of therapeutic strategies. We use several recent HCV data-sets to illustrate the methods.

The evolutionary dynamics of influenza A virus adaptation to mammalian hosts.

Few questions on infectious disease are more important than understanding how and why avian influenza A viruses successfully emerge in mammalian populations, yet little is known about the rate and nature of the virus' genetic adaptation in new hosts. Here, we measure, for the first time, the genomic rate of adaptive evolution of swine influenza viruses (SwIV) that originated in birds. By using a curated dataset of more than 24 000 human and swine influenza gene sequences, including 41 newly characterized genomes, we reconstructed the adaptive dynamics of three major SwIV lineages (Eurasian, EA; classical swine, CS; triple reassortant, TR). We found that, following the transfer of the EA lineage from birds to swine in the late 1970s, EA virus genes have undergone substantially faster adaptive evolution than those of the CS lineage, which had circulated among swine for decades. Further, the adaptation rates of the EA lineage antigenic haemagglutinin and neuraminidase genes were unexpectedly high and similar to those observed in human influenza A. We show that the successful establishment of avian influenza viruses in swine is associated with raised adaptive evolution across the entire genome for many years after zoonosis, reflecting the contribution of multiple mutations to the coordinated optimization of viral fitness in a new environment. This dynamics is replicated independently in the polymerase genes of the TR lineage, which established in swine following separate transmission from non-swine hosts.

Measuring the Temporal Structure in Serially-Sampled Phylogenies.

Nucleotide sequences sampled at different times (serially-sampled sequences) allow researchers to study the rate of evolutionary change and the demographic history of populations. Some phylogenies inferred from serially-sampled sequences are described as having strong 'temporal clustering', such that sequences from the same sampling time tend to to cluster together and to be the direct ancestors of sequences from the following sampling time. The degree to which phylogenies exhibit these properties is thought to reflect interesting biological processes, such as positive selection or deviation from the molecular clock hypothesis.Here we introduce the Temporal Clustering (TC) statistic, which is the first quantitative measure of the degree of topological 'temporal clustering' in a serially-sampled phylogeny. The TC statistic represents the expected deviation of an observed phylogeny from the null hypothesis of no temporal clustering, as a proportion of the range of possible values, and can therefore be compared among phylogeny of different sizes.We apply the TC statistic to a range of serially-sampled sequence datasets, which represent both rapidly-evolving viruses and ancient mitochondrial DNA. In addition, the TC statistic was calculated for phylogenies simulated under a neutral coalescent process.Our results indicate significant temporal clustering in many empirical datasets. However, we also find that such clustering is exhibited by trees simulated under a neutral coalescent process; hence the observation of significant 'temporal clustering' cannot unambiguously indicate that presence of strong positive selection in a population.Quantifying topological structure in this manner will provide new insights into the evolution of measurably evolving populations.

Impact of HIV on host-virus interactions during early hepatitis C virus infection.

BACKGROUND: Human immunodeficiency virus (HIV) may influence the outcome and natural history of hepatitis C virus (HCV) infection through an impact on acute HCV-specific T cell responses. METHODS: Fifty-five HIV-positive males with acute HCV infection were identified; monoinfected individuals (n = 8) were used for peripheral blood mononuclear cell comparison. In 14 coinfected and 8 HCV-monoinfected patients, HCV-specific T cell responses against a range of HCV antigens were assessed using interferon (IFN)-gamma enzyme-linked immunospot (ELISpot) and proliferation assays. E1/E2 region genetic diversity and the selection pressure on the virus were measured in 8 coinfected patients by use of cloned sequences over time. RESULTS: HCV persisted in 52 (95%) coinfected individuals. HCV/HIV coinfection significantly reduced IFN-gamma ELISpot responses versus those in HCV-monoinfected individuals, especially against nonstructural proteins (1/10 vs. 5/8; P = .008). In coinfected patients, increased HCV genetic diversity was observed between the first and subsequent time points, with no evidence for positive selection in the E1/E2 region sequenced. CONCLUSION: HIV coinfection is associated with increased rates of HCV persistence and a lack of critical CD4 T cell responses, with no evidence of immune selection pressure during early HCV infection. Loss of key cellular immune responses against HCV during acute disease may contribute to the failure of early host control of HCV in HCV/HIV-coinfected patients.