Accurate quantification of within- and between-host HBV evolutionary rates requires explicit transmission chain modelling

Inferring Viral Transmission Time from Phylogenies for Known Transmission Pairs

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

Inferring viral transmission time from phylogenies for known transmission pairs

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously-described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time-calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

Reconstruction of the Origin and Dispersal of the Worldwide Dominant Hepatitis B Virus Subgenotype D1

Hepatitis B is a potentially life-threatening liver infection caused by the hepatitis B virus (HBV). HBV-D1 is the dominant subgenotype in the Mediterranean basin, Eastern Europe, and Asia. However, little is currently known about its evolutionary history and spatio-temporal dynamics. We use Bayesian phylodynamic inference to investigate the temporal history of HBV-D1, for which we calibrate the molecular clock using ancient sequences, and reconstruct the viral global spatial dynamics based, for the first time, on full-length publicly available HBV-D1 genomes from a wide range of sampling dates. We pinpoint the origin of HBV subgenotype D1 before the current era (BCE) in Turkey/Anatolia. The spatial reconstructions reveal global viral transmission with a high degree of mixing. By combining modern-day and ancient sequences, we ensure sufficient temporal signal in HBV-D1 data to enable Bayesian phylodynamic inference using a molecular clock for time calibration. Our results shed light on the worldwide HBV-D1 epidemics and suggest that this originally Middle Eastern virus significantly affects more distant countries, such as those in mainland Europe.

Cross-scale dynamics and the evolutionary emergence of infectious diseases

When emerging pathogens encounter new host species for which they are poorly adapted, they must evolve to escape extinction. Pathogens experience selection on traits at multiple scales, including replication rates within host individuals and transmissibility between hosts. We analyze a stochastic model linking pathogen growth and competition within individuals to transmission between individuals. Our analysis reveals a new factor, the cross-scale reproductive number of a mutant virion, that quantifies how quickly mutant strains increase in frequency when they initially appear in the infected host population. This cross-scale reproductive number combines with viral mutation rates, single-strain reproductive numbers, and transmission bottleneck width to determine the likelihood of evolutionary emergence, and whether evolution occurs swiftly or gradually within chains of transmission. We find that wider transmission bottlenecks facilitate emergence of pathogens with short-term infections, but hinder emergence of pathogens exhibiting cross-scale selective conflict and long-term infections. Our results provide a framework to advance the integration of laboratory, clinical, and field data in the context of evolutionary theory, laying the foundation for a new generation of evidence-based risk assessment of emergence threats.

Estimating hepatitis B virus cccDNA persistence in chronic infection

Hepatitis B virus (HBV) infection is a major global health problem with over 240 million infected individuals at risk of developing progressive liver disease and hepatocellular carcinoma. HBV is an enveloped DNA virus that establishes its genome as an episomal, covalently closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Currently, available standard-of-care treatments for chronic hepatitis B (CHB) include nucleos(t)ide analogues (NAs) that suppress HBV replication but do not target the cccDNA and hence rarely cure infection. There is considerable interest in determining the lifespan of cccDNA molecules to design and evaluate new curative treatments. We took a novel approach to this problem by developing a new mathematical framework to model changes in evolutionary rates during infection which, combined with previously determined within-host evolutionary rates of HBV, we used to determine the lifespan of cccDNA. We estimate that during HBe-antigen positive (HBeAgPOS) infection the cccDNA lifespan is 61 (36-236) days, whereas during the HBeAgNEG phase of infection it is only 26 (16-81) days. We found that cccDNA replicative capacity declined by an order of magnitude between HBeAgPOS and HBeAgNEG phases of infection. Our estimated lifespan of cccDNA is too short to explain the long durations of chronic infection observed in patients on NA treatment, suggesting that either a sub-population of long-lived hepatocytes harbouring cccDNA molecules persists during therapy, or that NA therapy does not suppress all viral replication. These results provide a greater understanding of the biology of the cccDNA reservoir and can aid the development of new curative therapeutic strategies for treating CHB.

Genomic and phylodynamic analysis of sapoviruses isolated in Henan Province, China

In this study, we determined the near-complete and partial genome sequences of ten SaV isolates. Phylogenetic analysis based on full-length VP1 and RdRp nucleotide sequences indicated that nine isolates were of GI.1 and one was GII.3. Evolutionary dynamics analysis indicated that GI.1 and GII.3 SaVs evolved at different rates, the latter evolving more rapidly. Cluster analysis indicated that distantly related GI.1 SaVs were more similar in their amino acid compositions than were GII.3 SaVs. The data provided in this study may facilitate studies on SaV genomic diversity and epidemiological patterns in China and worldwide.

Evolutionary dynamics and transmission patterns of Newcastle disease virus in China through Bayesian phylogeographical analysis

The Chinese poultry industry has experienced outbreaks of Newcastle disease (ND) dating back to the 1920s. However, the epidemic has exhibited a downtrend in recent years. In this study, both observational and genetic data [fusion (F) and haemagglutinin-neuraminidase genes (HN)] were analyzed, and phylogeographic analysis based on prevalent genotypes of Newcastle disease virus (NDV) was conducted for better understanding of the evolution and spatiotemporal dynamics of ND in China. In line with the observed trend of epidemic outbreaks, the effective population size of F and HN genes of circulating NDV is no longer growing since 2000, which is supported by 95% highest posterior diversity (HPD) intervals. Phylogeographic analysis indicated that the two eastern coastal provinces, Shandong and Jiangsu were the most relevant hubs for NDV migration, and the geographical regions with active NDV diffusion seemed to be constrained to southern and eastern China. The live poultry trade may play an important role in viral spread. Interestingly, no migration links from wild birds to poultry received Bayes factor support (BF > 3), while the migration links from poultry to wild birds accounted for 64% in all effective migrations. This may indicate that the sporadic cases of ND in wild bird likely spillover events from poultry. These findings contribute to predictive models of NDV transmission, and potentially help in the prevention of future outbreaks.

The phylogenetic approach for viral infectious disease evolution and epidemiology: An updating review

In the last decade, the phylogenetic approach is recurrent in molecular evolutionary analysis. On 12 May, 2019, about 2 296 213 papers are found, but typing "phylogeny" or "epidemiology AND phylogeny" only 199 804 and 20 133 are retrieved, respectively. Molecular epidemiology in infectious diseases is widely used to define the source of infection as so as the ancestral relationships of individuals sampled from a population. Coalescent theory and phylogeographic analysis have had scientific application in several, recent pandemic events, and nosocomial outbreaks. Hepatitis viruses and immunodeficiency virus (human immunodeficiency virus) have been largely studied. Phylogenetic analysis has been recently applied on Polyomaviruses so as in the more recent outbreaks due to different arboviruses type as Zika and chikungunya viruses discovering the source of infection and the geographic spread. Data on sequences isolated by the microorganism are essential to apply the phylogenetic tools and research in the field of infectious disease phylodinamics is growing up. There is the need to apply molecular phylogenetic and evolutionary methods in areas out of infectious diseases, as translational genomics and personalized medicine. Lastly, the application of these tools in vaccine strategy so as in antibiotic and antiviral researchers are encouraged.

Tracing Ancient Human Migrations into Sahul Using Hepatitis B Virus Genomes

The entry point and timing of ancient human migration into continental Sahul (the combined landmass of Australia, New Guinea, and Tasmania) are subject to debate. Unique strains of hepatitis B virus (HBV) are endemic among modern-day Australian Aboriginals (HBV/C4) and Indigenous Melanesians (HBV/C3). We postulated that HBV genomes could be used to infer human population movements because the main HBV transmission route in endemic populations is via mother-to-child for genotypes B and C infections. Phylogenetic and phylogeographic analyses of HBV genomes inferred the origin of HBV/C4 to be >59 thousand years ago (ka) (95% HPD: 34-85 ka), and most likely to have occurred on the Sunda Shelf (southeast extension of the continental shelf of Southeast Asia). Our analysis further suggested an age of >51 ka (95% Highest Posterior Density (HPD): 36-67 ka) for the most recent common ancestor of HBV/C4 in Australia, correlating with the arrival time of anatomically modern humans into Australia, with the entry point suggested along a southern route via Timor. While we also inferred the origin of HBC/C3 to be on the Sunda Shelf, our analyses suggested that it was carried into Melanesia by Indigenous Melanesians who migrated through New Guinea north of the highlands. These findings reveal that HBV genomes can be used to infer ancient human population movements.

Intrahost Selection Pressure Drives Equine Arteritis Virus Evolution during Persistent Infection in the Stallion Reproductive Tract

Equine arteritis virus (EAV) is the causative agent of equine viral arteritis (EVA), a reproductive and respiratory disease of horses. Following natural infection, 10 to 70% of infected stallions can become carriers of EAV and continue to shed virus in the semen. In this study, sequential viruses isolated from nasal secretions, buffy coat cells, and semen of seven experimentally infected and two naturally infected EAV carrier stallions were deep sequenced to elucidate the intrahost microevolutionary process after a single transmission event. Analysis of variants from nasal secretions and buffy coat cells lacked extensive positive selection; however, characteristics of the mutant spectra were different in the two sample types. In contrast, the initial semen virus populations during acute infection have undergone a selective bottleneck, as reflected by the reduction in population size and diversifying selection at multiple sites in the viral genome. Furthermore, during persistent infection, extensive genome-wide purifying selection shaped variant diversity in the stallion reproductive tract. Overall, the nonstochastic nature of EAV evolution during persistent infection was driven by active intrahost selection pressure. Among the open reading frames within the viral genome, ORF3, ORF5, and the nsp2-coding region of ORF1a accumulated the majority of nucleotide substitutions during persistence, with ORF3 and ORF5 having the highest intrahost evolutionary rates. The findings presented here provide a novel insight into the evolutionary mechanisms of EAV and identified critical regions of the viral genome likely associated with the establishment and maintenance of persistent infection in the stallion reproductive tract.IMPORTANCE EAV can persist in the reproductive tract of infected stallions, and consequently, long-term carrier stallions constitute its sole natural reservoir. Previous studies demonstrated that the ampullae of the vas deferens are the primary site of viral persistence in the stallion reproductive tract and the persistence is associated with a significant inflammatory response that is unable to clear the infection. This is the first study that describes EAV full-length genomic evolution during acute and long-term persistent infection in the stallion reproductive tract using next-generation sequencing and contemporary sequence analysis techniques. The data provide novel insight into the intrahost evolution of EAV during acute and persistent infection and demonstrate that persistent infection is characterized by extensive genome-wide purifying selection and a nonstochastic evolutionary pattern mediated by intrahost selective pressure, with important nucleotide substitutions occurring in ORF1a (region encoding nsp2), ORF3, and ORF5.

Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling

Hantaviruses are zoonotic hemorrhagic fever viruses for which prevention of human spillover remains the first priority in disease management. Tailored intervention measures require an understanding of the drivers of enzootic dynamics, commonly inferred from distorted human incidence data. Here, we use longitudinal sampling of approximately three decades of Puumala orthohantavirus (PUUV) evolution in isolated reservoir populations to estimate PUUV evolutionary rates, and apply these to study the impact of environmental factors on viral spread. We find that PUUV accumulates genetic changes at a rate of ∼10⁻⁴ substitutions per site per year and that land cover type defines the dispersal dynamics of PUUV, with forests facilitating and croplands impeding virus spread. By providing reliable short-term PUUV evolutionary rate estimates, this work facilitates the evaluation of spatial risk heterogeneity starting from timed phylogeographic reconstructions based on virus sampling in its animal reservoir, thereby side-stepping the need for difficult-to-collect human disease incidence data.

Inconsistent temporal patterns of genetic variation of HCV among high-risk subjects may impact inference of transmission networks

Hepatitis-C Virus (HCV) sequences are often used to establish networks of people who inject drugs (PWID). However, the degree to which within-host evolutionary dynamics affect those inferences has not been carefully studied. Here, we analyzed 702 longitudinally-sampled HCV E1 sequences from 88 HCV+ people who inject drugs (PWID) in the Baltimore Before and After Acute Study of Hepatitis (BBAASH) cohort. Individuals were tested for HCV RNA over multiple visits to the clinic, and the HCV E1 gene was sequenced for HCV+ samples. Genetic clustering was performed on the full set of sequences using a 3% genetic distance threshold to define epidemiological linkage. Maximum-likelihood (ML) phylogenies were inferred to assess evolutionary relationships. We found 22 clusters containing sequences sampled over five or more years (long-term clusters, LTC), of which 17 had >1 subject. In six of the multi-subject LTC, one subject had a sequence sampled >3 years earlier or later than the next-closest subject in the cluster (time-gap LTC). ML trees showed that, in three of the time-gap LTC, two subjects had identical sequences despite 7-10 years separating the sampling times. In four of the time-gap LTC for whom additional data were available, the subject with the later detected shared variant had both different variants and visits with no detectable HCV RNA (RNA-) prior to the appearance of the shared variant. In the subject with the earlier detection of the shared variant, different variants and RNA- visits were also detected in multiple cases subsequent to appearance of the shared variant. Complex patterns of shared viral variation among PWID reflect on-going re-infection, multiple transmission partners, and/or inconsistent detection of viral variants. Our results suggest that transmission events are currently underestimated by analysis of sequences at a single point in time.

Role of viral load in Hepatitis B virus evolution in persistently normal ALT chronically infected patients

Chronic HBV infection has been associated with severe liver disease although most of them do not progress to this stage. Even though low replicative carriers form the largest group of HBV chronically infected patients, there is a paucity of longitudinal studies to evaluate the molecular evolution of the whole genome in this subset of patients. In this study, longitudinal samples from 10 patients with persistently normal ALT levels were collected. HBV full-length genome sequences were obtained from 3 samples per patient (baseline, 5 and 10-years of follow-up). Patients were grouped according to HBV-DNA level into <10³ IU/ml (group A) or > 10³ IU/ml (group B). The substitution rate was inversely related with HBV-DNA levels. Moreover, the rate in the 10-year follow-up was significantly higher in group A (6.9 × 10^-4 ± 1.3 × 10^-4) than group B (2.7 × 10^-4 ± 7.4 × 10^-5 substitution/site/year, p < .001). Most of the substitutions were in the Core region and the majority were non-synonymous changes. The rate of nucleotide substitution was inversely related to HBV-DNA levels, highlighting the role of viral load in the HBV intra-host dynamics, even in low replicative state patients. Moreover, the difference in the substitution rate between the analysed groups was mainly consequence of substitutions restricted to the Core region, particularly in the simple coding region and antigenic epitopes, which suggest that the immune pressure drives the different evolutionary behaviour of groups.

Evolution of HIV-1 within untreated individuals and at the population scale in Uganda

HIV-1 undergoes multiple rounds of error-prone replication between transmission events, resulting in diverse viral populations within and among individuals. In addition, the virus experiences different selective pressures at multiple levels: during the course of infection, at transmission, and among individuals. Disentangling how these evolutionary forces shape the evolution of the virus at the population scale is important for understanding pathogenesis, how drug- and immune-escape variants are likely to spread in populations, and the development of preventive vaccines. To address this, we deep-sequenced two regions of the HIV-1 genome (p24 and gp41) from 34 longitudinally-sampled untreated individuals from Rakai District in Uganda, infected with subtypes A, D, and inter-subtype recombinants. This dataset substantially increases the availability of HIV-1 sequence data that spans multiple years of untreated infection, in particular for different geographical regions and viral subtypes. In line with previous studies, we estimated an approximately five-fold faster rate of evolution at the within-host compared to the population scale for both synonymous and nonsynonymous substitutions, and for all subtypes. We determined the extent to which this mismatch in evolutionary rates can be explained by the evolution of the virus towards population-level consensus, or the transmission of viruses similar to those that establish infection within individuals. Our findings indicate that both processes are likely to be important.