The epidemic behavior of the hepatitis C virus

Evolutionary Analysis Provides Insight Into the Origin and Adaptation of HCV

Hepatitis C virus (HCV) belongs to the Hepacivirus genus and is genetically heterogeneous, with seven major genotypes further divided into several recognized subtypes. HCV origin was previously dated in a range between ∼200 and 1000 years ago. Hepaciviruses have been identified in several domestic and wild mammals, the largest viral diversity being observed in bats and rodents. The closest relatives of HCV were found in horses/donkeys (equine hepaciviruses, EHV). However, the origin of HCV as a human pathogen is still an unsolved puzzle. Using a selection-informed evolutionary model, we show that the common ancestor of extant HCV genotypes existed at least 3000 years ago (CI: 3192–5221 years ago), with the oldest genotypes being endemic to Asia. EHV originated around 1100 CE (CI: 291–1640 CE). These time estimates exclude that EHV transmission was mainly sustained by widespread veterinary practices and suggest that HCV originated from a single zoonotic event with subsequent diversification in human populations. We also describe a number of biologically important sites in the major HCV genotypes that have been positively selected and indicate that drug resistance-associated variants are significantly enriched at positively selected sites. HCV exploits several cell-surface molecules for cell entry, but only two of these (CD81 and OCLN) determine the species-specificity of infection. Herein evolutionary analyses do not support a long-standing association between primates and hepaciviruses, and signals of positive selection at CD81 were only observed in Chiroptera. No evidence of selection was detected for OCLN in any mammalian order. These results shed light on the origin of HCV and provide a catalog of candidate genetic modulators of HCV phenotypic diversity.

Towards a genomics-informed, real-time, global pathogen surveillance system

The recent Ebola and Zika epidemics demonstrate the need for the continuous surveillance, rapid diagnosis and real-time tracking of emerging infectious diseases. Fast, affordable sequencing of pathogen genomes - now a staple of the public health microbiology laboratory in well-resourced settings - can affect each of these areas. Coupling genomic diagnostics and epidemiology to innovative digital disease detection platforms raises the possibility of an open, global, digital pathogen surveillance system. When informed by a One Health approach, in which human, animal and environmental health are considered together, such a genomics-based system has profound potential to improve public health in settings lacking robust laboratory capacity.

Analysis of molecular evolution of nucleocapsid protein in Newcastle disease virus

The present study investigated the molecular evolution of nucleocapsid protein (NP) in different Newcastle disease virus (NDV) genotypes. The evolutionary timescale and rate were estimated using the Bayesian Markov chain Monte Carlo (MCMC) method. The p-distance, Bayesian skyline plot (BSP), and positively selected sites were also analyzed. The MCMC tree indicated that NDV diverged about 250 years ago with a rapid evolution rate (1.059 × 10^-2 substitutions/site/year) and that different NDV genotypes formed three lineages. The p-distance results reflected the great genetic diversity of NDV. BSP analysis suggested that the effective population size of NDV has been increasing since 2000 and that the basic reproductive number (R₀) of NDV ranged from 1.003 to 1.006. The abundance of negatively selected sites in the NP and the mean dN/dS value of 0.07 indicated that the NP of NDV may have undergone purifying selection. However, the predicted positively selected site at position 370 was located in the known effective epitopic region of the NP. In conclusion, although NDV evolved at a high rate and showed great genetic diversity, the structure and function of the NP had been well conserved. However, R₀>1 suggests that NDV might have been causing an epidemic since the time of radiation.

Multi-drug resistant Klebsiella pneumoniae strains circulating in hospital setting: whole-genome sequencing and Bayesian phylogenetic analysis for outbreak investigations

Carbapenems resistant Enterobacteriaceae infections are increasing worldwide representing an emerging public health problem. The application of phylogenetic and phylodynamic analyses to bacterial whole genome sequencing (WGS) data have become essential in the epidemiological surveillance of multi-drug resistant nosocomial pathogens. Between January 2012 and February 2013, twenty-one multi-drug resistant K. pneumoniae strains, were collected from patients hospitalized among different wards of the University Hospital Campus Bio-Medico. Epidemiological contact tracing of patients and Bayesian phylogenetic analysis of bacterial WGS data were used to investigate the evolution and spatial dispersion of K. pneumoniae in support of hospital infection control. The epidemic curve of incident K. pneumoniae cases showed a bimodal distribution of cases with two peaks separated by 46 days between November 2012 and January 2013. The time-scaled phylogeny suggested that K. pneumoniae strains isolated during the study period may have been introduced into the hospital setting as early as 2007. Moreover, the phylogeny showed two different epidemic introductions in 2008 and 2009. Bayesian genomic epidemiology is a powerful tool that promises to improve the surveillance and control of multi-drug resistant pathogens in an effort to develop effective infection prevention in healthcare settings or constant strains reintroduction.

Insight into the global evolution of Rodentia associated Morbilli-related paramyxoviruses

One portion of the family Paramyxoviridae is a group of Unclassified Morbilli-Related Viruses (UMRV) recently recognized in wild small mammals. At a global level, the evolutionary history of these viruses is not properly understood and the relationships between UMRV and their hosts still remain largely unstudied. The present study revealed, for the first time, that Rodentia associated UMRV emerged from a common ancestor in southern Africa more than 4000 years ago. Sequenced UMRV originating from different regions in the world, clustered into four well-supported viral lineages, which suggest that strain diversification occurred during host dispersal and associated exchanges, with purifying selection pressure as the principal evolutionary force. In addition, multi-introductions on different continents and islands of Rodentia associated UMRV and spillover between rodent species, most probably Rattus rattus, were detected and indicate that these animals are implicated in the vectoring and in the worldwide emergence of this virus group. The natural history and the evolution dynamics of these zoonotic viruses, originating from and hosted by wild animals, are most likely shaped by commensalism related to human activities.

Broadly neutralizing antibodies with few somatic mutations and hepatitis C virus clearance

Here, we report the isolation of broadly neutralizing mAbs (bNAbs) from persons with broadly neutralizing serum who spontaneously cleared hepatitis C virus (HCV) infection. We found that bNAbs from two donors bound the same epitope and were encoded by the same germline heavy chain variable gene segment. Remarkably, these bNAbs were encoded by antibody variable genes with sparse somatic mutations. For one of the most potent bNAbs, these somatic mutations were critical for antibody neutralizing breadth and for binding to autologous envelope variants circulating late in infection. However, somatic mutations were not necessary for binding of the bNAb unmutated ancestor to envelope proteins of early autologous transmitted/founder viruses. This study identifies a public B cell clonotype favoring early recognition of a conserved HCV epitope, proving that anti-HCV bNAbs can achieve substantial neutralizing breadth with relatively few somatic mutations, and identifies HCV envelope variants that favored selection and maturation of an anti-HCV bNAb in vivo. These data provide insight into the molecular mechanisms of immune-mediated clearance of HCV infection and present a roadmap to guide development of a vaccine capable of stimulating anti-HCV bNAbs with a physiologic number of somatic mutations characteristic of vaccine responses.

Tracing the epidemic history of hepatitis C virus genotypes in Saudi Arabia

HCV genotype 4 is highly prevalent in many Middle Eastern countries, yet little is known about the genotype's epidemic history at the subtype-level in this region. To address the dearth of data from Saudi Arabia (SA) we genotyped 230 HCV isolates in the core/E- and NS5B-region and analyzed using Bayesian phylogenetic approaches. HCV genotype 4 (HCV/4) was positive in 61.7% (142/230) of isolates belonging to 7 different subtypes with the predominance of 4d (73/142; 51.4%) followed by 4a (51/142; 35.9%). Phylogenetic analysis also revealed a distinct epidemiological cluster of HCV/4d for Saudi Arabia. HCV/1 appeared as the second most prevalent genotype positive in 31.3% (72/230) of isolates with the predominance of 1b (53/72; 73.6%) followed by 1a (16/72; 22.2%), and 1g (3/72; 4.1%). A small proportion of isolates belonged to HCV/3a (12/230; 5.2%), and HCV/2a (4/230; 1.7%). We estimate that the genotype 4 common ancestor existed around 1935 (1850-1985). Genotype 4 originated plausibly in Central Africa and multiple subtypes disseminated across African borders since ~1970, including subtype 4d which dominates current HCV infections in Saudi Arabia. The Bayesian skyline plot (BSP) analysis showed that genotype 4d entered the Saudi population in 1900. The effective number of HCV infections grew gradually until the second half of the 1950s and more rapidly until the early-80s through the use of imported blood units and blood products. Subsequently, the rate of HCV infection in the Saudi Arabian population was stabilized through effective screening of blood and infection control measures.

The epidemic dynamics of hepatitis C virus subtypes 4a and 4d in Saudi Arabia

The relatedness between viral variants sampled at different locations through time can provide information pertinent to public health that cannot readily be obtained through standard surveillance methods. Here, we use virus genetic data to identify the transmission dynamics that drive the hepatitis C virus subtypes 4a (HCV4a) and 4d (HCV4d) epidemics in Saudi Arabia. We use a comprehensive dataset of newly generated and publicly available sequence data to infer the HCV4a and HCV4d evolutionary histories in a Bayesian statistical framework. We also introduce a novel analytical method for an objective assessment of the migration intensity between locations. We find that international host mobility patterns dominate over within country spread in shaping the Saudi Arabia HCV4a epidemic, while this may be different for the HCV4d epidemic. This indicates that the subtypes 4a and 4d burden can be most effectively reduced by combining the prioritized screening and treatment of Egyptian immigrants with domestic prevention campaigns. Our results highlight that the joint investigation of evolutionary and epidemiological processes can provide valuable public health information, even in the absence of extensive metadata information.

Analysis of Evolutionary Processes of Species Jump in Waterfowl Parvovirus

Waterfowl parvoviruses are classified into goose parvovirus (GPV) and Muscovy duck parvovirus (MDPV) according to their antigenic features and host preferences. A novel duck parvovirus (NDPV), identified as a new variant of GPV, is currently infecting ducks, thus causing considerable economic loss. This study analyzed the molecular evolution and population dynamics of the emerging parvovirus capsid gene to investigate the evolutionary processes concerning the host shift of NDPV. Two important amino acids changes (Asn-489 and Asn-650) were identified in NDPV, which may be responsible for host shift of NDPV. Phylogenetic analysis indicated that the currently circulating NDPV originated from the GPV lineage. The Bayesian Markov chain Monte Carlo tree indicated that the NDPV diverged from GPV approximately 20 years ago. Evolutionary rate analyses demonstrated that GPV evolved with 7.674 × 10^-4 substitutions/site/year, and the data for MDPV was 5.237 × 10^-4 substitutions/site/year, whereas the substitution rate in NDPV branch was 2.25 × 10^-3 substitutions/site/year. Meanwhile, viral population dynamics analysis revealed that the GPV major clade, including NDPV, grew exponentially at a rate of 1.717 year^-1. Selection pressure analysis showed that most sites are subject to strong purifying selection and no positively selected sites were found in NDPV. The unique immune-epitopes in waterfowl parvovirus were also estimated, which may be helpful for the prediction of antibody binding sites against NDPV in ducks.

Implications of hepatitis C virus subtype 1a migration patterns for virus genetic sequencing policies in Italy

Background

In-depth phylogeographic analysis can reveal migration patterns relevant for public health planning. Here, as a model, we focused on the provenance, in the current Italian HCV subtype 1a epidemic, of the NS3 resistance-associated variant (RAV) Q80K, known to interfere with the action of NS3/4A protease inhibitor simeprevir. HCV1a migration patterns were analysed using Bayesian phylodynamic tools, capitalising on newly generated and publicly available time and geo-referenced NS3 encoding virus genetic sequence data.

Results

Our results showed that both immigration and local circulation fuel the current Italian HCV1a epidemic. The United States and European continental lineages dominate import into Italy, with the latter taking the lead from the 1970s onwards. Since similar migration patterns were found for Q80K and other lineages, no clear differentiation of the risk for failing simeprevir can be made between patients based on their migration and travel history. Importantly, since HCV only occasionally recombines, these results are readily transferable to the genetic sequencing policy concerning NS5A RAVs.

Conclusions

The patient migration and travel history cannot be used to target only part of the HCV1a infected population for drug resistance testing before start of antiviral therapy. Consequently, it may be cost-effective to expand genotyping efforts to all HCV1a infected patients eligible for simeprevir-based therapies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-017-0913-3) contains supplementary material, which is available to authorized users.

Inferring epidemiological parameters from phylogenies using regression-ABC: A comparative study

Inferring epidemiological parameters such as the R₀ from time-scaled phylogenies is a timely challenge. Most current approaches rely on likelihood functions, which raise specific issues that range from computing these functions to finding their maxima numerically. Here, we present a new regression-based Approximate Bayesian Computation (ABC) approach, which we base on a large variety of summary statistics intended to capture the information contained in the phylogeny and its corresponding lineage-through-time plot. The regression step involves the Least Absolute Shrinkage and Selection Operator (LASSO) method, which is a robust machine learning technique. It allows us to readily deal with the large number of summary statistics, while avoiding resorting to Markov Chain Monte Carlo (MCMC) techniques. To compare our approach to existing ones, we simulated target trees under a variety of epidemiological models and settings, and inferred parameters of interest using the same priors. We found that, for large phylogenies, the accuracy of our regression-ABC is comparable to that of likelihood-based approaches involving birth-death processes implemented in BEAST2. Our approach even outperformed these when inferring the host population size with a Susceptible-Infected-Removed epidemiological model. It also clearly outperformed a recent kernel-ABC approach when assuming a Susceptible-Infected epidemiological model with two host types. Lastly, by re-analyzing data from the early stages of the recent Ebola epidemic in Sierra Leone, we showed that regression-ABC provides more realistic estimates for the duration parameters (latency and infectiousness) than the likelihood-based method. Overall, ABC based on a large variety of summary statistics and a regression method able to perform variable selection and avoid overfitting is a promising approach to analyze large phylogenies.

Given the rapid evolution of many pathogens, analysing their genomes by means of phylogenies can inform us about how they spread. This is the focus of the field known as “phylodynamics”. Most existing methods inferring epidemiological parameters from virus phylogenies are limited by the difficulty of handling complex likelihood functions, which commonly incorporate latent variables. Here, we use an alternative method known as regression-based Approximate Bayesian Computation (ABC), which circumvents this problem by using simulations and dataset comparisons. Since phylogenies are difficult to compare to one another, we introduce many summary statistics to describe them and take advantage of current machine learning techniques able to perform variable selection. We show that the accuracy we reach is comparable to that of existing methods. This accuracy increases with phylogeny size and can even be higher than that of existing methods for some parameters. Overall, regression-based ABC opens new perspectives to infer epidemiological parameters from large phylogenies.

Characterization of Hepatitis C Virus (HCV) Envelope Diversification from Acute to Chronic Infection within a Sexually Transmitted HCV Cluster by Using Single-Molecule, Real-Time Sequencing

In contrast to other available next-generation sequencing platforms, PacBio single-molecule, real-time (SMRT) sequencing has the advantage of generating long reads albeit with a relatively higher error rate in unprocessed data. Using this platform, we longitudinally sampled and sequenced the hepatitis C virus (HCV) envelope genome region (1,680 nucleotides [nt]) from individuals belonging to a cluster of sexually transmitted cases. All five subjects were coinfected with HIV-1 and a closely related strain of HCV genotype 4d. In total, 50 samples were analyzed by using SMRT sequencing. By using 7 passes of circular consensus sequencing, the error rate was reduced to 0.37%, and the median number of sequences was 612 per sample. A further reduction of insertions was achieved by alignment against a sample-specific reference sequence. However, in vitro recombination during PCR amplification could not be excluded. Phylogenetic analysis supported close relationships among HCV sequences from the four male subjects and subsequent transmission from one subject to his female partner. Transmission was characterized by a strong genetic bottleneck. Viral genetic diversity was low during acute infection and increased upon progression to chronicity but subsequently fluctuated during chronic infection, caused by the alternate detection of distinct coexisting lineages. SMRT sequencing combines long reads with sufficient depth for many phylogenetic analyses and can therefore provide insights into within-host HCV evolutionary dynamics without the need for haplotype reconstruction using statistical algorithms.IMPORTANCE Next-generation sequencing has revolutionized the study of genetically variable RNA virus populations, but for phylogenetic and evolutionary analyses, longer sequences than those generated by most available platforms, while minimizing the intrinsic error rate, are desired. Here, we demonstrate for the first time that PacBio SMRT sequencing technology can be used to generate full-length HCV envelope sequences at the single-molecule level, providing a data set with large sequencing depth for the characterization of intrahost viral dynamics. The selection of consensus reads derived from at least 7 full circular consensus sequencing rounds significantly reduced the intrinsic high error rate of this method. We used this method to genetically characterize a unique transmission cluster of sexually transmitted HCV infections, providing insight into the distinct evolutionary pathways in each patient over time and identifying the transmission-associated genetic bottleneck as well as fluctuations in viral genetic diversity over time, accompanied by dynamic shifts in viral subpopulations.

Hepatitis C virus genotype 3A in a population of injecting drug users in Montenegro: Bayesian and evolutionary analysis

Few reports are available on HCV molecular epidemiology among IDUs in Eastern Europe, and none in Montenegro. The aim of this study was to investigate the HCV genotype distribution in Montenegro among IDUs and to perform Bayesian and evolutionary analysis of the most prevalent HCV genotype circulating in this population. Sixty-four HCV-positive IDUs in Montenegro were enrolled between 2013 and 2014, and the NS5B gene was sequenced. The Bayesian analysis showed that the most prevalent subtype was HCV-3a. Phylogenetic data showed that HCV-3a reached Montenegro in the late 1990s, causing an epidemic that exponentially grew between the 1995 and 2005. In the dated tree, four different entries, from 1990 (clade D), 1994 (clade A) to 1999 (clade B) and 2001 (clade C), were identified. In the NS5B protein model, the amino acids variations were located mainly in the palm domain, which contains most of the conserved structural elements of the active site. This study provides an analysis of the virus transmission pathway and the evolution of HCV genotype 3a among IDUs in Montenegro. These data could represent the basis for further strategies aimed to improve disease management and surveillance program development in high-risk populations.

The hepatitis C virus nonstructural protein 3 Q80K polymorphism is frequently detected and transmitted among HIV-infected MSM in the Netherlands

OBJECTIVES

The Q80K polymorphism is a naturally occurring resistance-associated variant in the hepatitis C virus (HCV) nonstructural protein 3 (NS3) region and is likely transmissible between hosts. This study describes the Q80K origin and prevalence among HCV risk groups in the Netherlands and examines whether Q80K is linked to specific transmission networks.

DESIGN AND METHODS

Stored blood samples from HCV genotype 1a-infected patients were used for PCR and sequencing to reconstruct the NS3 maximum likelihood phylogeny. The most recent common ancestor was estimated with a coalescent-based model within a Bayesian statistical framework.

RESULTS

Study participants (n = 150) were either MSM (39%), people who inject drugs (17%), or patients with other (15%) or unknown/unreported (29%) risk behavior. Overall 45% was coinfected with HIV. Q80K was present in 36% (95% confidence interval 28-44%) of patients throughout the sample collection period (2000-2015) and was most prevalent in MSM (52%, 95% confidence interval 38-65%). Five MSM-specific transmission clusters were identified, of which three exclusively contained sequences with Q80K. The HCV-1a most recent common ancestor in the Netherlands was estimated in 1914 (95% higher posterior density 1879-1944) and Q80K originated in 1957 (95% higher posterior density 1942-1970) within HCV-1a clade I. All Q80K lineages could be traced back to this single origin.

CONCLUSION

Q80K is a highly stable and transmissible resistance-associated variant and was present in a large part of Dutch HIV-coinfected MSM. The introduction and expansion of Q80K variants in this key population suggest a founder effect, potentially jeopardizing future treatment with simeprevir.

Hepatitis C Virus Genotype Analyses in Chronic Hepatitis C Patients and Individuals With Spontaneous Virus Clearance Using a Newly Developed Serotyping Assay

BACKGROUND

We developed a novel HCV serotyping assay and detected the genotypes in chronic hepatitis C (CHC) patients and individuals with spontaneous viral clearance (SVC).

METHODS

Nine hundred and ninety-seven patients were enrolled in a previous study; their samples were genotyped originally using the molecular assays. Among them, 190 patients achieved sustained virological response; the post-treatment samples were also serotyped. Moreover, 326 samples from follow-up cohorts were serotyped, among whom 66 were from SVC individuals, and 260 from CHC patients.

RESULTS

Nine hundred and fifty-eight out of 997 samples were available for serotyping, among which 29 samples generated indeterminate serotyping results. The consistency between the genotyping and serotyping assays was 91.50% (850/929). The specificity and sensitivity were 98.45% and 88.77% for genotype 1, 96.42% and 93.97% for genotype 2, and 94.15% and 80.52% for non-genotype 1 or 2. However, only 41 of 60 genotype-6 samples were correctly serotyped. Little difference was found in the 190 paired serotyping results. No difference existed in the genotype distribution between the SVC and CHC groups (P = 0.08).

CONCLUSIONS

The assay provides an accurate alternative for determining HCV genotypes, whereas it is not recommended for detecting genotype 6. Furthermore, it facilitates identifying the genotypes in SVC individuals. HCV genotype has little impact on SVC.

The Phylogeographic and Spatiotemporal Spread of HCV in Pakistani Population

Hepatitis C Virus (HCV) is the most prevalent human pathogen in Pakistan and is the major cause of liver cirrhosis and hepatocellular carcinoma in infected patients. It has shifted from being hypo-endemic to being hyper-endemic. There was no information about the origin and evolution of the local variants. Here we use newly developed phyloinformatic methods of sequence analysis to conduct the first comprehensive investigation of the evolutionary and biogeographic history in unprecedented detail and breadth. Considering evolutionary rate and molecular-clock hypothesis in context, we reconstructed the spatiotemporal spread of HCV in the whole territory of its circulation using a combination of Bayesian MCMC methods utilizing all sequences available in GenBank. Comparative analysis were performed and were addressed. Whole genome and individual gene analysis have shown that sub-types 1a, 1b and 3a are recognized as epidemic strains and are distributed globally. Here we confirm that the origin of HCV 3a genotypes is in South Asia and HCV has evolved in the region to become stably adapted to the host environment.

Epidemic History of Hepatitis C Virus among Patients with Inherited Bleeding Disorders in Iran

The high rate of hepatitis C virus (HCV) infection among transfusion related risk groups such as patients with inherited bleeding disorders highlighting the investigation on prevalent subtypes and their epidemic history among this group. In this study, 166 new HCV NS5B sequences isolated from patients with inherited bleeding disorders together with 29 sequences related to hemophiliacs obtained from a previous study on diversity of HCV in Iran were analyzed. The most prevalent subtype was 1a (65%), followed by 3a (18.7%),1b (14.5%),4(1.2%) and 2k (0.6%). Subtypes 1a and 3a showed exponential expansion during the 20^th century. Whereas expansion of 3a started around 20 years earlier than 1a among the study patients, the epidemic growth of 1a revealed a delay of about 10 years compared with that found for this subtype in developed countries. Our results supported the view that the spread of 3a reached the plateau 10 years prior to the screening of blood donors for HCV. Rather, 1a reached the plateau when screening program was implemented. The differences observed in the epidemic behavior of HCV-1a and 3a may be associated with different transmission routes of two subtypes. Indeed, expansion of 1a was more commonly linked to blood transfusion, while 3a was more strongly associated to drug use and specially IDU after 1960. Our findings also showed HCV transmission through blood products has effectively been controlled from late 1990s. In conclusion, the implementation of strategies such as standard surveillance programs and subsiding antiviral treatments seems to be essential to both prevent new HCV infections and to decline the current and future HCV disease among Iranian patients with inherited bleeding disorders.

Exploring the possibility of arthropod transmission of HCV

Hepatitis C virus (HCV) is a major cause of chronic hepatitis, cirrhosis, and liver cancer occurring in up to 3% of the world's population. Parenteral exposure to HCV is the major mode of transmission of infection. Once established, infection will persist in up to 85% of individuals with only a minority of patients clearing viremia. Egypt has possibly the highest HCV prevalence in the world where 10-20% of the general population are infected with HCV. Endemic HCV appears to be concentrated in the tropics and sub-tropics where there are higher biting rates from insects. The question as to whether a bridge vector transmission is possible, via arthropods, both between humans and/or from an animal reservoir to humans is explored. Mechanical transmission, as opposed to biological transmission, is considered. Mechanical transmission can be an efficient way of transmitting an infection, as effective as biological transmission. Probability of transmission can increase as to the immediate circumstances and conditions at the time. Several factors may enhance mechanical transmission, including high levels of microbes in the vector, frequent biting, the close proximity, and contact between vectors and recipients as well as high density of insects. HCV has been isolated from bodies or heads of mosquitoes collected from the houses of HCV-infected individuals. The possibility of enzootic cycles of HCV tangential transmission via bridging vectors, such as, arthropods needs to be further investigated and possible animal reservoirs, including domestic rural epizootic cycles for HCV infection, requires further research with particular initial emphasis on equine infections. J. Med. Virol. 89:187-194, 2017. © 2016 Wiley Periodicals, Inc.

Genomic Analysis of the Emergence, Evolution, and Spread of Human Respiratory RNA Viruses

The emergence and reemergence of rapidly evolving RNA viruses-particularly those responsible for respiratory diseases, such as influenza viruses and coronaviruses-pose a significant threat to global health, including the potential of major pandemics. Importantly, recent advances in high-throughput genome sequencing enable researchers to reveal the genomic diversity of these viral pathogens at much lower cost and with much greater precision than they could before. In particular, the genome sequence data generated allow inferences to be made on the molecular basis of viral emergence, evolution, and spread in human populations in real time. In this review, we introduce recent computational methods that analyze viral genomic data, particularly in combination with metadata such as sampling time, geographic location, and virulence. We then outline the insights these analyses have provided into the fundamental patterns and processes of evolution and emergence in human respiratory RNA viruses, as well as the major challenges in such genomic analyses.

Historical Trends in the Hepatitis C Virus Epidemics in North America and Australia

BACKGROUND

 Bayesian evolutionary analysis (coalescent analysis) based on genetic sequences has been used to describe the origins and spread of rapidly mutating RNA viruses, such as influenza, Ebola, human immunodeficiency virus (HIV), and hepatitis C virus (HCV).

METHODS

 Full-length subtype 1a and 3a sequences from early HCV infections from the International Collaborative of Incident HIV and Hepatitis C in Injecting Cohorts (InC3), as well as from public databases from a time window of 1977-2012, were used in a coalescent analysis with BEAST software to estimate the origin and progression of the HCV epidemics in Australia and North America. Convergent temporal trends were sought via independent epidemiological modeling.

RESULTS

 The epidemic of subtype 3a had more recent origins (around 1950) than subtype 1a (around 1920) in both continents. In both modeling approaches and in both continents, the epidemics underwent exponential growth between 1955 and 1975, which then stabilized in the late 20th century.

CONCLUSIONS

 Historical events that fuelled the emergence and spread of injecting drug use, such as the advent of intravenous medical therapies and devices, and growth in the heroin trade, as well as population mixing during armed conflicts, were likely drivers for the cross-continental spread of the HCV epidemics.

Peromyscus as a model system for human hepatitis C: An opportunity to advance our understanding of a complex host parasite system

Worldwide, there are 185 million people infected with hepatitis C virus and approximately 350,000 people die each year from hepatitis C associated liver diseases. Human hepatitis C research has been hampered by the lack of an appropriate in vivo model system. Most of the in vivo research has been conducted on chimpanzees, which is complicated by ethical concerns, small sample sizes, high costs, and genetic heterogeneity. The house mouse system has led to greater understanding of a wide variety of human pathogens, but it is unreasonable to expect Mus musculus to be a good model system for every human pathogen. Alternative animal models can be developed in these cases. Ferrets (influenza), cotton rats (human respiratory virus), and woodchucks (hepatitis B) are all alternative models that have led to a greater understanding of human pathogens. Rodent models are tractable, genetically amenable and inbred and outbred strains can provide homogeneity in results. Recently, a rodent homolog of hepatitis C was discovered and isolated from the liver of a Peromyscus maniculatus. This represents the first small mammal (mouse) model system for human hepatitis C and it offers great potential to contribute to our understanding and ultimately aid in our efforts to combat this serious public health concern. Peromyscus are available commercially and can be used to inform questions about the origin, transmission, persistence, pathology, and rational treatment of hepatitis C. Here, we provide a disease ecologist's overview of this new virus and some suggestions for useful future experiments.

Genomic Analysis of Viral Outbreaks

Genomic analysis is a powerful tool for understanding viral disease outbreaks. Sequencing of viral samples is now easier and cheaper than ever before and can supplement epidemiological methods by providing nucleotide-level resolution of outbreak-causing pathogens. In this review, we describe methods used to answer crucial questions about outbreaks, such as how they began and how a disease is transmitted. More specifically, we explain current techniques for viral sequencing, phylogenetic analysis, transmission reconstruction, and evolutionary investigation of viral pathogens. By detailing the ways in which genomic data can help us understand viral disease outbreaks, we aim to provide a resource that will facilitate the response to future outbreaks.

The application of HIV molecular epidemiology to public health

HIV is responsible for one of the largest viral pandemics in human history. Despite a concerted global response for prevention and treatment, the virus persists. Thus, urgent public health action, utilizing novel interventions, is needed to prevent future transmission events, critical to eliminating HIV. For public health planning to prove effective and successful, we need to understand the dynamics of regional epidemics and to intervene appropriately. HIV molecular epidemiology tools as implemented in phylogenetic, phylodynamic and phylogeographic analyses have proven to be powerful tools in public health planning across many studies. Numerous applications with HIV suggest that molecular methods alone or in combination with mathematical modelling can provide inferences about the transmission dynamics, critical epidemiological parameters (prevalence, incidence, effective number of infections, Re, generation times, time between infection and diagnosis), or the spatiotemporal characteristics of epidemics. Molecular tools have been used to assess the impact of an intervention and outbreak investigation which are of great public health relevance. In some settings, molecular sequence data may be more readily available than HIV surveillance data, and can therefore allow for molecular analyses to be conducted more easily. Nonetheless, classic methods have an integral role in monitoring and evaluation of public health programmes, and should supplement emerging techniques from the field of molecular epidemiology. Importantly, molecular epidemiology remains a promising approach in responding to viral diseases.

Integrating molecular epidemiology and social network analysis to study infectious diseases: Towards a socio-molecular era for public health

The number of public health applications for molecular epidemiology and social network analysis has increased rapidly since the improvement in computational capacities and the development of new sequencing techniques. Currently, molecular epidemiology methods are used in a variety of settings: from infectious disease surveillance systems to the description of disease transmission pathways. The latter are of great epidemiological importance as they let us describe how a virus spreads in a community, make predictions for the further epidemic developments, and plan preventive interventions. Social network methods are used to understand how infections spread through communities and what the risk factors for this are, as well as in improved contact tracing and message-dissemination interventions. Research is needed on how to combine molecular and social network data as both include essential, but not fully sufficient information on infection transmission pathways. The main differences between the two data sources are that, firstly, social network data include uninfected individuals unlike the molecular data sampled only from infected network members. Thus, social network data include more detailed picture of a network and can improve inferences made from molecular data. Secondly, network data refer to the current state and interactions within the social network, while molecular data refer to the time points when transmissions happened, which might have happened years before the sampling date. As of today, there have been attempts to combine and compare the data obtained from the two sources. Even though there is no consensus on whether and how social and genetic data complement each other, this research might significantly improve our understanding of how viruses spread through communities.

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We summarise and analyse the roles of molecular evolution studies in molecular epidemiology of infectious diseases.

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We review how social network and molecular sequence data have been integrated in the past.

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We show how integrating social network and molecular evolution approaches may change the study of infectious diseases.

Phylogenetic Analysis and Epidemic History of Hepatitis C Virus Genotype 2 in Tunisia, North Africa

HCV genotype 2 (HCV-2) has a worldwide distribution with prevalence rates that vary from country to country. High genetic diversity and long-term endemicity were suggested in West African countries. A global dispersal of HCV-2 would have occurred during the 20th century, especially in European countries. In Tunisia, genotype 2 was the second prevalent genotype after genotype 1 and most isolates belong to subtypes 2c and 2k. In this study, phylogenetic analyses based on the NS5B genomic sequences of 113 Tunisian HCV isolates from subtypes 2c and 2k were carried out. A Bayesian coalescent-based framework was used to estimate the origin and the spread of these subtypes circulating in Tunisia. Phylogenetic analyses of HCV-2c sequences suggest the absence of country-specific or time-specific variants. In contrast, the phylogenetic grouping of HCV-2k sequences shows the existence of two major genetic clusters that may represent two distinct circulating variants. Coalescent analysis indicated a most recent common ancestor (tMRCA) of Tunisian HCV-2c around 1886 (1869-1902) before the introduction of HCV-2k in 1901 (1867-1931). Our findings suggest that the introduction of HCV-2c in Tunisia is possibly a result of population movements between Tunisia and European population following the French colonization.

Molecular Infectious Disease Epidemiology: Survival Analysis and Algorithms Linking Phylogenies to Transmission Trees

Recent work has attempted to use whole-genome sequence data from pathogens to reconstruct the transmission trees linking infectors and infectees in outbreaks. However, transmission trees from one outbreak do not generalize to future outbreaks. Reconstruction of transmission trees is most useful to public health if it leads to generalizable scientific insights about disease transmission. In a survival analysis framework, estimation of transmission parameters is based on sums or averages over the possible transmission trees. A phylogeny can increase the precision of these estimates by providing partial information about who infected whom. The leaves of the phylogeny represent sampled pathogens, which have known hosts. The interior nodes represent common ancestors of sampled pathogens, which have unknown hosts. Starting from assumptions about disease biology and epidemiologic study design, we prove that there is a one-to-one correspondence between the possible assignments of interior node hosts and the transmission trees simultaneously consistent with the phylogeny and the epidemiologic data on person, place, and time. We develop algorithms to enumerate these transmission trees and show these can be used to calculate likelihoods that incorporate both epidemiologic data and a phylogeny. A simulation study confirms that this leads to more efficient estimates of hazard ratios for infectiousness and baseline hazards of infectious contact, and we use these methods to analyze data from a foot-and-mouth disease virus outbreak in the United Kingdom in 2001. These results demonstrate the importance of data on individuals who escape infection, which is often overlooked. The combination of survival analysis and algorithms linking phylogenies to transmission trees is a rigorous but flexible statistical foundation for molecular infectious disease epidemiology.

Recent work has attempted to use whole-genome sequence data from pathogens to reconstruct the transmission trees linking infectors and infectees in outbreaks. However, transmission trees from one outbreak do not generalize to future outbreaks. Reconstruction of transmission trees is most useful to public health if it leads to generalizable scientific insights about disease transmission. Accurate estimates of transmission parameters can help identify risk factors for transmission and aid the design and evaluation of public health interventions for emerging infections. Using statistical methods for time-to-event data (survival analysis), estimation of transmission parameters is based on sums or averages over the possible transmission trees. By providing partial information about who infected whom, a pathogen phylogeny can reduce the set of possible transmission trees and increase the precision of transmission parameter estimates. We derive algorithms that enumerate the transmission trees consistent with a pathogen phylogeny and epidemiologic data, show how to calculate likelihoods for transmission data with a phylogeny, and apply these methods to a foot and mouth disease outbreak in the United Kingdom in 2001. These methods will allow pathogen genetic sequences to be incorporated into the analysis of outbreak investigations, vaccine trials, and other studies of infectious disease transmission.

How well can the exponential-growth coalescent approximate constant-rate birth-death population dynamics?

One of the central objectives in the field of phylodynamics is the quantification of population dynamic processes using genetic sequence data or in some cases phenotypic data. Phylodynamics has been successfully applied to many different processes, such as the spread of infectious diseases, within-host evolution of a pathogen, macroevolution and even language evolution. Phylodynamic analysis requires a probability distribution on phylogenetic trees spanned by the genetic data. Because such a probability distribution is not available for many common stochastic population dynamic processes, coalescent-based approximations assuming deterministic population size changes are widely employed. Key to many population dynamic models, in particular epidemiological models, is a period of exponential population growth during the initial phase. Here, we show that the coalescent does not well approximate stochastic exponential population growth, which is typically modelled by a birth–death process. We demonstrate that introducing demographic stochasticity into the population size function of the coalescent improves the approximation for values of R₀ close to 1, but substantial differences remain for large R₀. In addition, the computational advantage of using an approximation over exact models vanishes when introducing such demographic stochasticity. These results highlight that we need to increase efforts to develop phylodynamic tools that correctly account for the stochasticity of population dynamic models for inference.

Reconstructing transmission trees for communicable diseases using densely sampled genetic data

Whole genome sequencing of pathogens from multiple hosts in an epidemic offers the potential to investigate who infected whom with unparalleled resolution, potentially yielding important insights into disease dynamics and the impact of control measures. We considered disease outbreaks in a setting with dense genomic sampling, and formulated stochastic epidemic models to investigate person-to-person transmission, based on observed genomic and epidemiological data. We constructed models in which the genetic distance between sampled genotypes depends on the epidemiological relationship between the hosts. A data augmented Markov chain Monte Carlo algorithm was used to sample over the transmission trees, providing a posterior probability for any given transmission route. We investigated the predictive performance of our methodology using simulated data, demonstrating high sensitivity and specificity, particularly for rapidly mutating pathogens with low transmissibility. We then analyzed data collected during an outbreak of methicillin-resistant Staphylococcus aureus in a hospital, identifying probable transmission routes and estimating epidemiological parameters. Our approach overcomes limitations of previous methods, providing a framework with the flexibility to allow for unobserved infection times, multiple independent introductions of the pathogen, and within-host genetic diversity, as well as allowing forward simulation.

Genome-wide analysis for identification of adaptive diversification between hepatitis C virus subtypes 1a and 1b

Hepatitis C virus (HCV) is a major cause of liver disease and has been estimated to infect approximately 2%-3% of the world's population. HCV genotype 1 is the subject of intense research and clinical investigations because of its worldwide prevalence and poor access to treatment for patients in developing countries and marginalized populations. The predominant subtypes 1a and 1b of HCV genotype 1 present considerable differences in epidemiological features. However, the genetic signature underlying such phenotypic functional divergence is still an open question. Here, we performed a genome-wide evolutionary study on HCV subtypes 1a and 1b. The results show that adaptive selection has driven the diversification between these subtypes. Furthermore, the major adaptive divergence-related changes have occurred on proteins E1, NS4B, NS5A, and NS5B. Structurally, a number of adaptively selected sites cluster in functional regions potentially relevant to (i) membrane attachment and (ii) the interactions with viral and host cell factors and the genome template. These results might provide helpful hints about the molecular determinants of epidemiological divergence between HCV 1a and 1b.

Epidemic Reconstruction in a Phylogenetics Framework: Transmission Trees as Partitions of the Node Set

The use of genetic data to reconstruct the transmission tree of infectious disease epidemics and outbreaks has been the subject of an increasing number of studies, but previous approaches have usually either made assumptions that are not fully compatible with phylogenetic inference, or, where they have based inference on a phylogeny, have employed a procedure that requires this tree to be fixed. At the same time, the coalescent-based models of the pathogen population that are employed in the methods usually used for time-resolved phylogeny reconstruction are a considerable simplification of epidemic process, as they assume that pathogen lineages mix freely. Here, we contribute a new method that is simultaneously a phylogeny reconstruction method for isolates taken from an epidemic, and a procedure for transmission tree reconstruction. We observe that, if one or more samples is taken from each host in an epidemic or outbreak and these are used to build a phylogeny, a transmission tree is equivalent to a partition of the set of nodes of this phylogeny, such that each partition element is a set of nodes that is connected in the full tree and contains all the tips corresponding to samples taken from one and only one host. We then implement a Monte Carlo Markov Chain (MCMC) procedure for simultaneous sampling from the spaces of both trees, utilising a newly-designed set of phylogenetic tree proposals that also respect node partitions. We calculate the posterior probability of these partitioned trees based on a model that acknowledges the population structure of an epidemic by employing an individual-based disease transmission model and a coalescent process taking place within each host. We demonstrate our method, first using simulated data, and then with sequences taken from the H7N7 avian influenza outbreak that occurred in the Netherlands in 2003. We show that it is superior to established coalescent methods for reconstructing the topology and node heights of the phylogeny and performs well for transmission tree reconstruction when the phylogeny is well-resolved by the genetic data, but caution that this will often not be the case in practice and that existing genetic and epidemiological data should be used to configure such analyses whenever possible. This method is available for use by the research community as part of BEAST, one of the most widely-used packages for reconstruction of dated phylogenies.

With sequence data becoming available in increasing high volumes and at decreasing costs, there has been substantial recent interest in the possibility of using pathogen genome sequences as a means to retrace the spread of disease amongst the infected hosts in an epidemic. While several such methods exist, many of them are not fully compatible with phylogenetic inference, which is the most commonly-used methodology for exploring the ancestry of the isolates represented by a set of sequences. Procedures using phylogenetics as a basis have either taken a single, fixed phylogenetic tree as input, or have been quite narrow in scope and not available in any current package for general use. For their part, standard phylogenetic methods usually assume a model of the pathogen population that is overly simplistic for the situation in an epidemic. Here, we bridge the gap by introducing a new, highly flexible method, implemented in the publicly-available BEAST package, which simultaneously reconstructs the transmission history of an epidemic and the phylogeny for samples taken from it. We apply the procedure to simulated data and to sequences from the 2003 H7N7 avian influenza outbreak in the Netherlands.

The Genetic Diversity and Evolution of HIV-1 Subtype B Epidemic in Puerto Rico

HIV-1 epidemics in Caribbean countries, including Puerto Rico, have been reported to be almost exclusively associated with the subtype B virus (HIV-1B). However, while HIV infections associated with other clades have been only sporadically reported, no organized data exist to accurately assess the prevalence of non-subtype B HIV-1 infection. We analyzed the nucleotide sequence data of the HIV pol gene associated with HIV isolates from Puerto Rican patients. The sequences (n = 945) were obtained from our “HIV Genotyping” test file, which has been generated over a period of 14 years (2001–2014). REGA subtyping tool found the following subtypes: B (90%), B-like (3%), B/D recombinant (6%), and D/B recombinant (0.6%). Though there were fewer cases, the following subtypes were also found (in the given proportions): A1B (0.3%), BF1 (0.2%), subtype A (01-AE) (0.1%), subtype A (A2) (0.1%), subtype F (12BF) (0.1%), CRF-39 BF-like (0.1%), and others (0.1%). Some of the recombinants were identified as early as 2001. Although the HIV epidemic in Puerto Rico is primarily associated with HIV-1B virus, our analysis uncovered the presence of other subtypes. There was no indication of subtype C, which has been predominantly associated with heterosexual transmission in other parts of the world.

Next-Generation Sequencing Reveals Frequent Opportunities for Exposure to Hepatitis C Virus in Ghana

Globally, hepatitis C Virus (HCV) infection is responsible for a large proportion of persons with liver disease, including cancer. The infection is highly prevalent in sub-Saharan Africa. West Africa was identified as a geographic origin of two HCV genotypes. However, little is known about the genetic composition of HCV populations in many countries of the region. Using conventional and next-generation sequencing (NGS), we identified and genetically characterized 65 HCV strains circulating among HCV-positive blood donors in Kumasi, Ghana. Phylogenetic analysis using consensus sequences derived from 3 genomic regions of the HCV genome, 5'-untranslated region, hypervariable region 1 (HVR1) and NS5B gene, consistently classified the HCV variants (n = 65) into genotypes 1 (HCV-1, 15%) and genotype 2 (HCV-2, 85%). The Ghanaian and West African HCV-2 NS5B sequences were found completely intermixed in the phylogenetic tree, indicating a substantial genetic heterogeneity of HCV-2 in Ghana. Analysis of HVR1 sequences from intra-host HCV variants obtained by NGS showed that three donors were infected with >1 HCV strain, including infections with 2 genotypes. Two other donors share an HCV strain, indicating HCV transmission between them. The HCV-2 strain sampled from one donor was replaced with another HCV-2 strain after only 2 months of observation, indicating rapid strain switching. Bayesian analysis estimated that the HCV-2 strains in Ghana were expanding since the 16^th century. The blood donors in Kumasi, Ghana, are infected with a very heterogeneous HCV population of HCV-1 and HCV-2, with HCV-2 being prevalent. The detection of three cases of co- or super-infections and transmission linkage between 2 cases suggests frequent opportunities for HCV exposure among the blood donors and is consistent with the reported high HCV prevalence. The conditions for effective HCV-2 transmission existed for ~ 3–4 centuries, indicating a long epidemic history of HCV-2 in Ghana.

Phylogenetic Exploration of Nosocomial Transmission Chains of 2009 Influenza A/H1N1 among Children Admitted at Red Cross War Memorial Children's Hospital, Cape Town, South Africa in 2011

Traditional modes of investigating influenza nosocomial transmission have entailed a combination of confirmatory molecular diagnostic testing and epidemiological investigation. Common hospital-acquired infections like influenza require a discerning ability to distinguish between viral isolates to accurately identify patient transmission chains. We assessed whether influenza hemagglutinin sequence phylogenies can be used to enrich epidemiological data when investigating the extent of nosocomial transmission over a four-month period within a paediatric Hospital in Cape Town South Africa. Possible transmission chains/channels were initially determined through basic patient admission data combined with Maximum likelihood and time-scaled Bayesian phylogenetic analyses. These analyses suggested that most instances of potential hospital-acquired infections resulted from multiple introductions of Influenza A into the hospital, which included instances where virus hemagglutinin sequences were identical between different patients. Furthermore, a general inability to establish epidemiological transmission linkage of patients/viral isolates implied that identified isolates could have originated from asymptomatic hospital patients, visitors or hospital staff. In contrast, a traditional epidemiological investigation that used no viral phylogenetic analyses, based on patient co-admission into specific wards during a particular time-frame, suggested that multiple hospital acquired infection instances may have stemmed from a limited number of identifiable index viral isolates/patients. This traditional epidemiological analysis by itself could incorrectly suggest linkage between unrelated cases, underestimate the number of unique infections and may overlook the possible diffuse nature of hospital transmission, which was suggested by sequencing data to be caused by multiple unique introductions of influenza A isolates into individual hospital wards. We have demonstrated a functional role for viral sequence data in nosocomial transmission investigation through its ability to enrich traditional, non-molecular observational epidemiological investigation by teasing out possible transmission pathways and working toward more accurately enumerating the number of possible transmission events.

Mitochondrial DNA Copy Number in Egyptian Patients with Hepatitis C Virus-Related Hepatocellular Carcinoma

AIM

To assess the use of mitochondrial DNA (mtDNA) content as a noninvasive molecular biomarker in hepatitis C virus-related hepatocellular carcinoma (HCV-HCC).

MATERIALS AND METHODS

A total of 135 participants were enrolled in the study. Equal numbers of subjects were enrolled in each of three clinically defined groups: those with HCV-related cirrhosis (HCV-cirrhosis), those with HCV-HCC, and a control group of age- and sex-matched healthy volunteers with no evidence of liver disease. mtDNA concentrations were determined using a quantitative real-time polymerase chain reaction (PCR) technique.

RESULTS

mtDNA content was lowest among the HCV-HCC cases. No statistically significant difference was observed between the group of HCV-cirrhosis and the control group as regards mtDNA level. HCC patients with multicentric hepatic lesions had significantly lower mtDNA content than HCC patients with less advanced disease. When a receiver operating characteristic curve analysis was used, a cutoff of 34 was assigned for mtDNA content to distinguish between HCV-HCC and HCV-cirrhosis patients who are not yet complicated by malignancy. Lower mtDNA content was associated with HCC risk when using either or both healthy controls and HCV-cirrhosis groups for reference.

CONCLUSIONS

mtDNA content analysis could serve as a noninvasive molecular biomarker that reflects tumor burden in HCV-HCC cases and could be used as a predictor of HCC risk in patients of HCV-cirrhosis. In addition, the nonsignificant difference of mtDNA level between HCV-cirrhosis patients and healthy controls could eliminate the gray zone created by the use of alpha-fetoprotein in some cirrhotic patients.

Genetic diversity and evolutionary insights of respiratory syncytial virus A ON1 genotype: global and local transmission dynamics

Human respiratory syncytial virus (RSV) A ON1 genotype, first detected in 2010 in Ontario, Canada, has been documented in 21 countries to date. This study investigated persistence and transmission dynamics of ON1 by grouping 406 randomly selected RSV-positive specimens submitted to Public Health Ontario from August 2011 to August 2012; RSV-A-positive specimens were genotyped. We identified 370 RSV-A (181 NA1, 135 NA2, 51 ON1 3 GA5) and 36 RSV-B positive specimens. We aligned time-stamped second hypervariable region (330 bp) of G-gene sequence data (global, n = 483; and Ontario, n = 60) to evaluate transmission dynamics. Global data suggests that the most recent common ancestor of ON1 emerged during the 2008–2009 season. Mean evolutionary rate of the global ON1 was 4.10 × 10⁻³ substitutions/site/year (95% BCI 3.1–5.0 × 10⁻³), not significantly different to that of Ontario ON1. The estimated mean reproductive number (R₀ = ∼ 1.01) from global and Ontario sequences showed no significant difference and implies stability among global RSV-A ON1. This study suggests that local epidemics exhibit similar underlying evolutionary and epidemiological dynamics to that of the persistent global RSV-A ON1 population. These findings underscore the importance of continual molecular surveillance of RSV in order to gain a better understanding of epidemics.

Modeling hepatitis C virus transmission among people who inject drugs: Assumptions, limitations and future challenges

The discovery of highly effective hepatitis C virus (HCV) treatments has led to discussion of elimination and intensified interest in models of HCV transmission. In developed settings, HCV disproportionally affects people who inject drugs (PWID), and models are typically used to provide an evidence base for the effectiveness of interventions such as needle and syringe programs, opioid substitution therapy and more recently treating PWID with new generation therapies to achieve specified reductions in prevalence and / or incidence. This manuscript reviews deterministic compartmental S-I, deterministic compartmental S-I-S and network-based transmission models of HCV among PWID. We detail typical assumptions made when modeling injecting risk behavior, virus transmission, treatment and re-infection and how they correspond with available evidence and empirical data.

Phylogenetic analysis of the emergence of main hepatitis C virus subtypes in São Paulo, Brazil

Background

It is recognized that hepatitis C virus subtypes (1a, 1b, 2a, 2b, 2c and 3a) originated in Africa and Asia and spread worldwide exponentially during the Second World War (1940) through the transfusion of contaminated blood products, invasive medical and dental procedures, and intravenous drug use. The entry of hepatitis C virus subtypes into different regions occurred at distinct times, presenting exponential growth rates of larger or smaller spread. Our study estimated the growth and spread of the most prevalent subtypes currently circulating in São Paulo.

Methods

A total of 465 non-structural region 5B sequences of hepatitis C virus covering a 14-year time-span were used to reconstruct the population history and estimate the population dynamics and Time to Most Recent Common Ancestor of genotypes using the Bayesian Markov Chain Monte Carlo approach implemented in BEAST (Bayesian evolutionary analysis by sampling tree software/program).

Results

Evolutionary analysis demonstrated that the different hepatitis C virus subtypes had distinct growth patterns. The introduction of hepatitis C virus-1a and -3a were estimated to be circa 1979 and 1967, respectively, whereas hepatitis C virus-1b appears to have a more ancient entry, circa 1923. Hepatitis C virus-1b phylogenies suggest that different lineages circulate in São Paulo, and four well-supported groups (i.e., G1, G2, G3 and G4) were identified. Hepatitis C virus-1a presented the highest growth rate (r = 0.4), but its spread became less marked after the 2000s. Hepatitis C virus-3a grew exponentially until the 1990s and had an intermediate growth rate (r = 0.32). An evident exponential growth (r = 0.26) was found for hepatitis C virus-1b between 1980 and the mid-1990s.

Conclusions

After an initial period of exponential growth, the expansion of the three main subtypes began to decrease. Hepatitis C virus-1b presented inflated genetic diversity, and its transmission may have been sustained by different generations and transmission routes other than blood transfusion. Hepatitis C virus-1a and -3a showed no group stratification, most likely due to their recent entry.

Enhanced HIV-1 surveillance using molecular epidemiology to study and monitor HIV-1 outbreaks among intravenous drug users (IDUs) in Athens and Bucharest

BACKGROUND

A significant increase in HIV-1 diagnoses was reported among Injecting Drug Users (IDUs) in the Athens (17-fold) and Bucharest (9-fold) metropolitan areas starting 2011.

METHODS

Molecular analyses were conducted on HIV-1 sequences from IDUs comprising 51% and 20% of the diagnosed cases among IDUs during 2011-2013 for Greece and Romania, respectively. Phylodynamic analyses were performed using the newly developed birth-death serial skyline model which allows estimating of important epidemiological parameters, as implemented in BEAST programme.

RESULTS

Most infections (>90%) occurred within four and three IDU local transmission networks in Athens and Bucharest, respectively. For all Romanian clusters, the viral strains originated from local circulating strains, whereas in Athens, the local strains seeded only two of the four sub-outbreaks. Birth-death skyline plots suggest a more explosive nature for sub-outbreaks in Bucharest than in Athens. In Athens, two sub-outbreaks had been controlled (Re<1.0) by 2013 and two appeared to be endemic (Re∼1). In Bucharest one outbreak continued to expand (Re>1.0) and two had been controlled (Re<1.0). The lead times were shorter for the outbreak in Athens than in Bucharest.

CONCLUSIONS

Enhanced molecular surveillance proved useful to gain information about the origin, causal pathways, dispersal patterns and transmission dynamics of the outbreaks that can be useful in a public health setting.

Genetic Diversity Underlying the Envelope Glycoproteins of Hepatitis C Virus: Structural and Functional Consequences and the Implications for Vaccine Design

In the 26 years since the discovery of Hepatitis C virus (HCV) a major global research effort has illuminated many aspects of the viral life cycle, facilitating the development of targeted antivirals. Recently, effective direct-acting antiviral (DAA) regimens with >90% cure rates have become available for treatment of chronic HCV infection in developed nations, representing a significant advance towards global eradication. However, the high cost of these treatments results in highly restricted access in developing nations, where the disease burden is greatest. Additionally, the largely asymptomatic nature of infection facilitates continued transmission in at risk groups and resource constrained settings due to limited surveillance. Consequently a prophylactic vaccine is much needed. The HCV envelope glycoproteins E1 and E2 are located on the surface of viral lipid envelope, facilitate viral entry and are the targets for host immunity, in addition to other functions. Unfortunately, the extreme global genetic and antigenic diversity exhibited by the HCV glycoproteins represents a significant obstacle to vaccine development. Here we review current knowledge of HCV envelope protein structure, integrating knowledge of genetic, antigenic and functional diversity to inform rational immunogen design.

Rational Design and Adaptive Management of Combination Therapies for Hepatitis C Virus Infection

Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design.

Evidence of Self-Sustaining Drug Resistant HIV-1 Lineages Among Untreated Patients in the United Kingdom

BACKGROUND

About 10% of new diagnoses of subtype B human immunodeficiency virus type 1 (HIV-1) in the United Kingdom are with viruses showing transmitted drug resistance (TDR). However, there is discordance between the mutation patterns observed in HIV-infected patients failing therapy and those seen in TDR.

METHODS

We extracted all subtype B HIV-1 pol gene sequences from treatment-naive patients within the United Kingdom HIV Drug Resistance Database sampled between 1997 and 2011 and carrying the most common protease inhibitors, nonnucleoside and nucleotide reverse transcriptase inhibitors TDR mutations, namely, L90M, K103N, and T215Y/F/rev, respectively (n = 1140). Transmission clusters (n ≥ 2 sequences) were identified by maximum-likelihood phylogeny using a genetic distance cutoff of ≤ 1.5%. The time of origin and the basic reproductive number (R0) of clusters were estimated by Bayesian methods.

RESULTS

T215rev was present alone in 47% of the sequences (n = 540), K103N in 31% (n = 359), and L90M in 10% (n = 109). The remaining sequences contained T215Y or combinations of L90M, K103N, and T215rev. Fifty-five percent (n = 624) of the sequences formed highly supported transmission clusters (n = 193) containing between 2 and 15 sequences. The time of origin of 10 large clusters (≥ 8 sequences) was estimated to be between 2000 (1999-2002; 95% highest posterior density [HPD]) and 2006 (2005-2007; 95% HPD). The oldest cluster had persisted for nearly 8 years. All 10 clusters had R0s ranging from 1.3 (0.4-2.5; 95% HPD) to 2.8 (0.6-6.5; 95% HPD).

CONCLUSIONS

A high proportion of the most common TDR in subtype B infections in the United Kingdom is derived by onward transmission from treatment-naive patients.

A re-evaluation of the origin of hepatitis C virus genotype 2 in West Africa

Hepatitis C virus (HCV) is classified into seven genotypes based on genetic diversity, and most genotypes have been found in Africa. Infections with HCV genotype 2 (HCV2) are most prevalent in West Africa and it was suggested that HCV2 originated in West Africa. To better understand the evolutionary epidemiology of HCV2 in Africa, we examined new NS5B sequences of HCV2 strains obtained from Côte d'Ivoire, Ghana and Nigeria sequenced at the Centers for Disease Control and Prevention with those available from West, North and Central Africa. Bayesian phylogeographic analysis using a discrete trait model showed that Ghana was the most likely geographical region for the origin of HCV2. Spread of HCV2 from Ghana did not appear to be through diffusion to adjacent countries along the coast. Rather, it was transmitted from Ghana to many distant countries in Africa, suggesting that certain routes of geographical dissemination were historically more efficient than mere proximity and that the HCV2 epidemic history in West Africa is extremely complex.

Mixed HCV infection and reinfection in people who inject drugs--impact on therapy

The majority of new and existing cases of HCV infection in high-income countries occur among people who inject drugs (PWID). Ongoing high-risk behaviours can lead to HCV re-exposure, resulting in mixed HCV infection and reinfection. Assays used to screen for mixed infection vary widely in sensitivity, particularly with respect to their capacity for detecting minor variants (<20% of the viral population). The prevalence of mixed infection among PWID ranges from 14% to 39% when sensitive assays are used. Mixed infection compromises HCV treatment outcomes with interferon-based regimens. HCV reinfection can also occur after successful interferon-based treatment among PWID, but the rate of reinfection is low (0-5 cases per 100 person-years). A revolution in HCV therapeutic development has occurred in the past few years, with the advent of interferon-free, but still genotype-specific regiments based on direct acting antiviral agents. However, little is known about whether mixed infection and reinfection has an effect on HCV treatment outcomes in the setting of new direct-acting antiviral agents. This Review characterizes the epidemiology and natural history of mixed infection and reinfection among PWID, methodologies for detection, the potential implications for HCV treatment and considerations for the design of future studies.

Hepatitis C

Hepatitis C virus (HCV) infection is a major health problem worldwide. The effects of chronic infection include cirrhosis, end-stage liver disease, and hepatocellular carcinoma. As a result of shared routes of transmission, co-infection with HIV is a substantial problem, and individuals infected with both viruses have poorer outcomes than do peers infected with one virus. No effective vaccine exists, although persistent HCV infection is potentially curable. The standard of care has been subcutaneous interferon alfa and oral ribavirin for 24-72 weeks. This treatment results in a sustained virological response in around 50% of individuals, and is complicated by clinically significant adverse events. In the past 10 years, advances in HCV cell culture have enabled an improved understanding of HCV virology, which has led to development of many new direct-acting antiviral drugs that target key components of virus replication. These direct-acting drugs allow for simplified and shortened treatments for HCV that can be given as oral regimens with increased tolerability and efficacy than interferon and ribavirin. Remaining obstacles include access to appropriate care and treatment, and development of a vaccine.

Epidemic history of major genotypes of hepatitis C virus in Uruguay

Worldwide, more than 170 million people are chronically infected with the hepatitis C virus (HCV) and every year die more than 350,000 people from HCV-related liver diseases. Recently, HCV was reclassified into seven major genotypes and 67 subtypes. Some subtypes as 1a, 1b and 3a, have become epidemic as a result of the new parenteral transmission routes and are responsible for most HCV infections in Western countries. HCV 1a subtype have been sub-categorized into two separate sub clades. Recent studies based on the analysis of NS5B genome region, reveal that HCV epidemics in Argentina and Brazil are characterized by multiple introductions events of subtypes 1a, 1b and 3a, followed by subsequent local dispersion. There is no data about HCV genotypes circulating in Uruguay and their evolutionary and demographic history. To this end, a total of 153 HCV NS5B gene sequences were obtained from Uruguayan patients between 2005 and 2011. 86 (56%) sequences grouped with subtype 1a, 40 (26%) with subtype 3a and 27 (18%) with subtype 1b. Furthermore, subtype 1a sequences were distributed among both clades, 1 (n=62, 72%) and 2 (n=24, 28%). Four local HCV clades were found: UY-1a(I), UY-1a(II), UY-1a(III) and UY-3a; comprising a 39% of all HCV viruses analyzed in this study. HCV epidemic in Uruguay has been driving by multiple introductions of subtypes 1a, 1b and 3a and by local dissemination of a few country-specific strains. The evolutionary and demographic history of the major Uruguayan HCV clade UY-1a(I) was reconstructed under two different molecular clock rate models and displayed an epidemic history characterized by an initial phase of rapid expansion followed by a more recent reduction of growth rate since 2000-2005. This is the first comprehensive study about the molecular epidemiology and epidemic history of HCV in Uruguay.

Inferring epidemiological dynamics with Bayesian coalescent inference: the merits of deterministic and stochastic models

Estimation of epidemiological and population parameters from molecular sequence data has become central to the understanding of infectious disease dynamics. Various models have been proposed to infer details of the dynamics that describe epidemic progression. These include inference approaches derived from Kingman’s coalescent theory. Here, we use recently described coalescent theory for epidemic dynamics to develop stochastic and deterministic coalescent susceptible–infected–removed (SIR) tree priors. We implement these in a Bayesian phylogenetic inference framework to permit joint estimation of SIR epidemic parameters and the sample genealogy. We assess the performance of the two coalescent models and also juxtapose results obtained with a recently published birth–death-sampling model for epidemic inference. Comparisons are made by analyzing sets of genealogies simulated under precisely known epidemiological parameters. Additionally, we analyze influenza A (H1N1) sequence data sampled in the Canterbury region of New Zealand and HIV-1 sequence data obtained from known United Kingdom infection clusters. We show that both coalescent SIR models are effective at estimating epidemiological parameters from data with large fundamental reproductive number R0 and large population size S0. Furthermore, we find that the stochastic variant generally outperforms its deterministic counterpart in terms of error, bias, and highest posterior density coverage, particularly for smaller R0 and S0. However, each of these inference models is shown to have undesirable properties in certain circumstances, especially for epidemic outbreaks with R0 close to one or with small effective susceptible populations.

Population expansions shared among coexisting bacterial lineages are revealed by genetic evidence

Comparative population studies can help elucidate the influence of historical events upon current patterns of biodiversity among taxa that coexist in a given geographic area. In particular, comparative assessments derived from population genetics and coalescent theory have been used to investigate population dynamics of bacterial pathogens in order to understand disease epidemics. In contrast, and despite the ecological relevance of non-host associated and naturally occurring bacteria, there is little understanding of the processes determining their diversity. Here we analyzed the patterns of genetic diversity in coexisting populations of three genera of bacteria (Bacillus, Exiguobacterium, and Pseudomonas) that are abundant in the aquatic systems of the Cuatro Cienegas Basin, Mexico. We tested the hypothesis that a common habitat leaves a signature upon the genetic variation present in bacterial populations, independent of phylogenetic relationships. We used multilocus markers to assess genetic diversity and (1) performed comparative phylogenetic analyses, (2) described the genetic structure of bacterial populations, (3) calculated descriptive parameters of genetic diversity, (4) performed neutrality tests, and (5) conducted coalescent-based historical reconstructions. Our results show a trend of synchronic expansions across most populations independent of both lineage and sampling site. Thus, we provide empirical evidence supporting the analysis of coexisting bacterial lineages in natural environments to advance our understanding of bacterial evolution beyond medical or health-related microbes.

Bayesian inference of sampled ancestor trees for epidemiology and fossil calibration

Phylogenetic analyses which include fossils or molecular sequences that are sampled through time require models that allow one sample to be a direct ancestor of another sample. As previously available phylogenetic inference tools assume that all samples are tips, they do not allow for this possibility. We have developed and implemented a Bayesian Markov Chain Monte Carlo (MCMC) algorithm to infer what we call sampled ancestor trees, that is, trees in which sampled individuals can be direct ancestors of other sampled individuals. We use a family of birth-death models where individuals may remain in the tree process after sampling, in particular we extend the birth-death skyline model [Stadler et al., 2013] to sampled ancestor trees. This method allows the detection of sampled ancestors as well as estimation of the probability that an individual will be removed from the process when it is sampled. We show that even if sampled ancestors are not of specific interest in an analysis, failing to account for them leads to significant bias in parameter estimates. We also show that sampled ancestor birth-death models where every sample comes from a different time point are non-identifiable and thus require one parameter to be known in order to infer other parameters. We apply our phylogenetic inference accounting for sampled ancestors to epidemiological data, where the possibility of sampled ancestors enables us to identify individuals that infected other individuals after being sampled and to infer fundamental epidemiological parameters. We also apply the method to infer divergence times and diversification rates when fossils are included along with extant species samples, so that fossilisation events are modelled as a part of the tree branching process. Such modelling has many advantages as argued in the literature. The sampler is available as an open-source BEAST2 package (https://github.com/CompEvol/sampled-ancestors).

A central goal of phylogenetic analysis is to estimate evolutionary relationships and the dynamical parameters underlying the evolutionary branching process (e.g. macroevolutionary or epidemiological parameters) from molecular data. The statistical methods used in these analyses require that the underlying tree branching process is specified. Standard models for the branching process which were originally designed to describe the evolutionary past of present day species do not allow one sampled taxon to be the ancestor of another. However the probability of sampling a direct ancestor is not negligible for many types of data. For example, when fossil and living species are analysed together to infer species divergence times, fossil species may or may not be direct ancestors of living species. In epidemiology, a sampled individual (a host from which a pathogen sequence was obtained) can infect other individuals after sampling, which then go on to be sampled themselves. The models that account for direct ancestors produce phylogenetic trees with a different structure from classic phylogenetic trees and so using these models in inference requires new computational methods. Here we developed a method for phylogenetic analysis that accounts for the possibility of direct ancestors.