Fabio Luciani

Sequential Bottlenecks Drive Viral Evolution in Early Acute Hepatitis C Virus Infection

Hepatitis C is a pandemic human RNA virus, which commonly causes chronic infection and liver disease. The characterization of viral populations that successfully initiate infection, and also those that drive progression to chronicity is instrumental for understanding pathogenesis and vaccine design. A comprehensive and longitudinal analysis of the viral population was conducted in four subjects followed from very early acute infection to resolution of disease outcome. By means of next generation sequencing (NGS) and standard cloning/Sanger sequencing, genetic diversity and viral variants were quantified over the course of the infection at frequencies as low as 0.1%. Phylogenetic analysis of reassembled viral variants revealed acute infection was dominated by two sequential bottleneck events, irrespective of subsequent chronicity or clearance. The first bottleneck was associated with transmission, with one to two viral variants successfully establishing infection. The second occurred approximately 100 days post-infection, and was characterized by a decline in viral diversity. In the two subjects who developed chronic infection, this second bottleneck was followed by the emergence of a new viral population, which evolved from the founder variants via a selective sweep with fixation in a small number of mutated sites. The diversity at sites with non-synonymous mutation was higher in predicted cytotoxic T cell epitopes, suggesting immune-driven evolution. These results provide the first detailed analysis of early within-host evolution of HCV, indicating strong selective forces limit viral evolution in the acute phase of infection.

The epidemiological fitness cost of drug resistance in Mycobacterium tuberculosis

The emergence of antibiotic resistance in Mycobacterium tuberculosis has raised the concern that pathogen strains that are virtually untreatable may become widespread. The acquisition of resistance to antibiotics results in a longer duration of infection in a host, but this resistance may come at a cost through a decreased transmission rate. This raises the question of whether the overall fitness of drug-resistant strains is higher than that of sensitive strains—essential information for predicting the spread of the disease. Here, we directly estimate the transmission cost of drug resistance, the rate at which resistance evolves, and the relative fitness of resistant strains. These estimates are made by using explicit models of the transmission and evolution of sensitive and resistant strains of M. tuberculosis, using approximate Bayesian computation, and molecular epidemiology data from Cuba, Estonia, and Venezuela. We find that the transmission cost of drug resistance relative to sensitivity can be as low as 10%, that resistance evolves at rates of ≈0.0025–0.02 per case per year, and that the overall fitness of resistant strains is comparable with that of sensitive strains. Furthermore, the contribution of transmission to the spread of drug resistance is very high compared with acquired resistance due to treatment failure (up to 99%). Estimating such parameters directly from in vivo data will be critical to understanding and responding to antibiotic resistance. For instance, projections using our estimates suggest that the prevalence of tuberculosis may decline with successful treatment, but the proportion of cases associated with resistance is likely to increase.

Using Approximate Bayesian Computation to Estimate Tuberculosis Transmission Parameters From Genotype Data

Tuberculosis can be studied at the population level by genotyping strains of Mycobacterium tuberculosis isolated from patients. We use an approximate Bayesian computational method in combination with a stochastic model of tuberculosis transmission and mutation of a molecular marker to estimate the net transmission rate, the doubling time, and the reproductive value of the pathogen. This method is applied to a published data set from San Francisco of tuberculosis genotypes based on the marker IS6110. The mutation rate of this marker has previously been studied, and we use those estimates to form a prior distribution of mutation rates in the inference procedure. The posterior point estimates of the key parameters of interest for these data are as follows: net transmission rate, 0.69/year [95% credibility interval (C.I.) 0.38, 1.08]; doubling time, 1.08 years (95% C.I. 0.64, 1.82); and reproductive value 3.4 (95% C.I. 1.4, 79.7). These figures suggest a rapidly spreading epidemic, consistent with observations of the resurgence of tuberculosis in the United States in the 1980s and 1990s.

Contribution of Intra- and Interhost Dynamics to Norovirus Evolution

ABSTRACT Norovirus (NoV) is an emerging RNA virus that has been associated with global epidemics of gastroenteritis. Each global epidemic arises with the emergence of novel antigenic variants. While the majority of NoV infections are mild and self-limiting, in the young, elderly, and immunocompromised, severe and prolonged illness can result. As yet, there is no vaccine or therapeutic treatment to prevent or control infection. In order to design effective control strategies, it is important to understand the mechanisms and source of the new antigenic variants. In this study, we used next-generation sequencing (NGS) technology to investigate genetic diversification in three contexts: the impact of a NoV transmission event on viral diversity and the contribution to diversity of intrahost evolution over both a short period of time (10 days), in accordance with a typical acute NoV infection, and a prolonged period of time (288 days), as observed for NoV chronic infections of immunocompromised individuals. Investigations of the transmission event revealed that minor variants at frequencies as low as 0.01% were successfully transmitted, indicating that transmission is an important source of diversity at the interhost level of NoV evolution. Our results also suggest that chronically infected immunocompromised subjects represent a potential reservoir for the emergence of new viral variants. In contrast, in a typical acute NoV infection, the viral population was highly homogenous and relatively stable. These results indicate that the evolution of NoV occurs through multiple mechanisms.

Incidence of primary hepatitis C infection and risk factors for transmission in an Australian prisoner cohort

BackgroundHepatitis C virus (HCV) infection is common in prisoner populations, particularly those with a history of injecting drug use (IDU). Previous studies of HCV incidence have been based on small case numbers and have not distinguished risk events in prison from those in the community.MethodsHCV incidence was examined in a longitudinal cohort of 488 Australian prisoners with a history of IDU and documented to be seronegative within 12 months prior to enrolment. Inmates were tested for anti-HCV antibodies and viremia, and interviewed about demographic and behavioral risk factors for transmission.ResultsThe cohort was predominantly male (65%) with high rates of prior imprisonment (72%) and tattooing (73%), as well as longstanding IDU (mean 8.5 years). Ninety-four incident HCV cases were identified (incidence 31.6 per 100 person years). Independent associations were observed between incident infection and prior imprisonment (p = 0.02) and tattooing (p = 0.03), and surprisingly also with methadone maintenance treatment (MMT) (p < 0.001).ConclusionsHigh rates of new HCV infection were found in this prisoner cohort reflecting their substantive risk behavior profile, despite having remained uninfected for many years. The association with MMT is challenging and highlights the need for better understanding of prison-specific HCV transmission risks, as well as the uptake and effectiveness of prevention programs.

Epidemiological and clinical consequences of within-host evolution

Many viruses and bacteria are known to evolve rapidly over the course of an infection. However, epidemiological studies generally assume that within-host evolution is an instantaneous process. We argue that the dynamics of within-host evolution has implications at the within-host and at the between-host levels. We first show that epidemiologists should consider within-host evolution, notably because it affects the genotype of the pathogen that is transmitted. We then present studies that investigate evolution at the within-host level and examine the extent to which these studies can help to understand infection traits involved in the epidemiology (e.g. transmission rate, virulence, recovery rate). Finally, we discuss how new techniques for data acquisition can open new perspectives for empirical and theoretical research.

Deep sequencing of evolving pathogen populations: applications, errors, and bioinformatic solutions

Deep sequencing harnesses the high throughput nature of next generation sequencing technologies to generate population samples, treating information contained in individual reads as meaningful. Here, we review applications of deep sequencing to pathogen evolution. Pioneering deep sequencing studies from the virology literature are discussed, such as whole genome Roche-454 sequencing analyses of the dynamics of the rapidly mutating pathogens hepatitis C virus and HIV. Extension of the deep sequencing approach to bacterial populations is then discussed, including the impacts of emerging sequencing technologies. While it is clear that deep sequencing has unprecedented potential for assessing the genetic structure and evolutionary history of pathogen populations, bioinformatic challenges remain. We summarise current approaches to overcoming these challenges, in particular methods for detecting low frequency variants in the context of sequencing error and reconstructing individual haplotypes from short reads.

Next generation deep sequencing and vaccine design: today and tomorrow

Next generation sequencing (NGS) technologies have redefined the modus operandi in both human and microbial genetics research, allowing the unprecedented generation of very large sequencing datasets on a short time scale and at affordable costs. Vaccine development research is rapidly taking full advantage of the advent of NGS. This review provides a concise summary of the current applications of NGS in relation to research seeking to develop vaccines for human infectious diseases, incorporating studies of both the pathogen and the host. We focus on rapidly mutating viral pathogens, which are major targets in current vaccine research. NGS is unraveling the complex dynamics of viral evolution and host responses against these viruses, thus contributing substantially to the likelihood of successful vaccine development.

Short duration of lamivudine for the prevention of hepatitis B virus transmission in pregnancy: lack of potency and selection of resistance mutations

This study sought to assess the antiviral efficacy of lamivudine (LMV) administered during third trimester to reduce maternal viraemia and to identify the emergence of LMV resistance. A prospective observational analysis was performed on 26 mothers with high viral load (>107 IU/mL). Twenty‐one women received LMV (treated group) for an average of 53 days (range 22–88 days), and the remaining five formed the untreated control group. Serum samples from two time points were used to measure HBV DNA levels and antiviral drug resistance. The LMV‐treated women achieved a median HBV DNA reduction of 2.6‐log10 IU/mL. Although end‐of‐treatment (EOT) HBV DNA in four (18%) LMV‐treated women remained at >107 IU/mL (±0.5 log IU/mL), no mother‐to‐baby transmission was observed. In contrast, a baby from the untreated mother was HBsAg positive at 9 months postpartum. Four technologies were used for drug resistance testing. Only ultra‐deep pyrosequencing (UDPS) was sufficiently sensitive to detect minor viral variants down to <1%. UDPS showed that LMV therapy resulted in increased viral quasispecies diversity and positive selection of HBV variants with reverse transcriptase amino acid substitutions at sites associated with primary LMV resistance (rtM204I/V and rtA181T) in four (19%) women. These viral variants were detected mostly at low frequencies (0.63–5.92%) at EOT, but one LMV‐treated mother had an rtA181T variant that increased from 2.2% pretherapy to 25.59% at EOT. This mother was also infected with the vaccine escape variant (sG145R), which was inhibited by LMV treatment. LMV therapy during late pregnancy only reduced maternal viraemia moderately, and drug‐resistant viral variants emerged.

The Evolutionary Dynamics of a Rapidly Mutating Virus within and between Hosts: The Case of Hepatitis C Virus

Many pathogens associated with chronic infections evolve so rapidly that strains found late in an infection have little in common with the initial strain. This raises questions at different levels of analysis because rapid within-host evolution affects the course of an infection, but it can also affect the possibility for natural selection to act at the between-host level. We present a nested approach that incorporates within-host evolutionary dynamics of a rapidly mutating virus (hepatitis C virus) targeted by a cellular cross-reactive immune response, into an epidemiological perspective. The viral trait we follow is the replication rate of the strain initiating the infection. We find that, even for rapidly evolving viruses, the replication rate of the initial strain has a strong effect on the fitness of an infection. Moreover, infections caused by slowly replicating viruses have the highest infection fitness (i.e., lead to more secondary infections), but strains with higher replication rates tend to dominate within a host in the long-term. We also study the effect of cross-reactive immunity and viral mutation rate on infection life history traits. For instance, because of the stochastic nature of our approach, we can identify factors affecting the outcome of the infection (acute or chronic infections). Finally, we show that anti-viral treatments modify the value of the optimal initial replication rate and that the timing of the treatment administration can have public health consequences due to within-host evolution. Our results support the idea that natural selection can act on the replication rate of rapidly evolving viruses at the between-host level. It also provides a mechanistic description of within-host constraints, such as cross-reactive immunity, and shows how these constraints affect the infection fitness. This model raises questions that can be tested experimentally and underlines the necessity to consider the evolution of quantitative traits to understand the outcome and the fitness of an infection.