Roger D. Kouyos

Population biological principles of drug-resistance evolution in infectious diseases

The emergence of resistant pathogens in response to selection pressure by drugs and their possible disappearance when drug use is discontinued are evolutionary processes common to many pathogens. Population biological models have been used to study the dynamics of resistance in viruses, bacteria, and eukaryotic microparasites both at the level of the individual treated host and of the treated host population. Despite the existence of generic features that underlie such evolutionary dynamics, different conclusions have been reached about the key factors affecting the rate of resistance evolution and how to best use drugs to minimise the risk of generating high levels of resistance. Improved understanding of generic versus specific population biological aspects will help to translate results between different studies, and allow development of a more rational basis for sustainable drug use than exists at present.

Molecular Epidemiology Reveals Long-Term Changes in HIV Type 1 Subtype B Transmission in Switzerland

BACKGROUND Sequence data from resistance testing offer unique opportunities to characterize the structure of human immunodeficiency virus (HIV) infection epidemics. METHODS We analyzed a representative set of HIV type 1 (HIV-1) subtype B pol sequences from 5700 patients enrolled in the Swiss HIV Cohort Study. We pooled these sequences with the same number of sequences from foreign epidemics, inferred a phylogeny, and identified Swiss transmission clusters as clades having a minimal size of 10 and containing >or=80% Swiss sequences. RESULTS More than one-half of Swiss patients were included within 60 transmission clusters. Most transmission clusters were significantly dominated by specific transmission routes, which were used to identify the following patient groups: men having sex with men (MSM) (38 transmission clusters; average cluster size, 29 patients) or patients acquiring HIV through heterosexual contact (HETs) and injection drug users (IDUs) (12 transmission clusters; average cluster size, 144 patients). Interestingly, there were no transmission clusters dominated by sequences from HETs only. Although 44% of all HETs who were infected between 1983 and 1986 clustered with injection drug users, this percentage decreased to 18% for 2003-2006 (P<.001), indicating a diminishing role of injection drug users in transmission among HETs over time. CONCLUSIONS Our analysis suggests (1) the absence of a self-sustaining epidemic of HIV-1 subtype B in HETs in Switzerland and (2) a temporally decreasing clustering of HIV infections in HETs and IDUs.

The state of affairs in the kingdom of the Red Queen

One of the most prominent hypotheses to explain the ubiquity of sex and recombination is based on host-parasite interactions. Under the name of the Red Queen hypothesis (RQH), it has had theoretical and empirical support since its conception, but recent theoretical work has shown that the circumstances under which the RQH works remain unclear. Here we review the current status of the theory of the RQH. We argue that recent theoretical work calls for new experimental data and an increased theoretical effort to reveal the driving force of the RQH.

Contribution of a mutational bias in hepatitis C virus replication to the genetic barrier in the development of drug resistance

The development of resistance to direct-acting antivirals (DAAs) targeting the hepatitis C virus (HCV) can compromise therapy. However, mechanisms that determine prevalence and frequency of resistance-conferring mutations remain elusive. Here, we studied the fidelity of the HCV RNA-dependent RNA polymerase NS5B in an attempt to link the efficiency of mismatch formation with genotypic changes observed in vivo. Enzyme kinetic measurements revealed unexpectedly high error rates (approximately 10-3 per site) for G∶U/U∶G mismatches. The strong preference for G∶U/U∶G mismatches over all other mistakes correlates with a mutational bias in favor of transitions over transversions. Deep sequencing of HCV RNA samples isolated from 20 treatment-naïve patients revealed an approximately 75-fold difference in frequencies of the two classes of mutations. A stochastic model based on these results suggests that the bias toward transitions can also affect the selection of resistance-conferring mutations. Collectively, the data provide strong evidence to suggest that the nature of the nucleotide change can contribute to the genetic barrier in the development of resistance to DAAs.

Estimating the Basic Reproductive Number from Viral Sequence Data

Epidemiological processes leave a fingerprint in the pattern of genetic structure of virus populations. Here, we provide a new method to infer epidemiological parameters directly from viral sequence data. The method is based on phylogenetic analysis using a birth-death model (BDM) rather than the commonly used coalescent as the model for the epidemiological transmission of the pathogen. Using the BDM has the advantage that transmission and death rates are estimated independently and therefore enables for the first time the estimation of the basic reproductive number of the pathogen using only sequence data, without further assumptions like the average duration of infection. We apply the method to genetic data of the HIV-1 epidemic in Switzerland.

Ambiguous Nucleotide Calls From Population-based Sequencing of HIV-1 are a Marker for Viral Diversity and the Age of Infection

The fraction of ambiguous nucleotide calls in bulk sequencing of human immunodeficiency virus type 1 (HIV-1) carries important information on viral diversity and the age of infection. In particular, a fraction of ambiguous nucleotides of >.5% provides evidence against a recent infection event <1 year ago.

Phylogenetic approach reveals that virus genotype largely determines HIV set-point viral load.

HIV virulence, i.e. the time of progression to AIDS, varies greatly among patients. As for other rapidly evolving pathogens of humans, it is difficult to know if this variance is controlled by the genotype of the host or that of the virus because the transmission chain is usually unknown. We apply the phylogenetic comparative approach (PCA) to estimate the heritability of a trait from one infection to the next, which indicates the control of the virus genotype over this trait. The idea is to use viral RNA sequences obtained from patients infected by HIV-1 subtype B to build a phylogeny, which approximately reflects the transmission chain. Heritability is measured statistically as the propensity for patients close in the phylogeny to exhibit similar infection trait values. The approach reveals that up to half of the variance in set-point viral load, a trait associated with virulence, can be heritable. Our estimate is significant and robust to noise in the phylogeny. We also check for the consistency of our approach by showing that a trait related to drug resistance is almost entirely heritable. Finally, we show the importance of taking into account the transmission chain when estimating correlations between infection traits. The fact that HIV virulence is, at least partially, heritable from one infection to the next has clinical and epidemiological implications. The difference between earlier studies and ours comes from the quality of our dataset and from the power of the PCA, which can be applied to large datasets and accounts for within-host evolution. The PCA opens new perspectives for approaches linking clinical data and evolutionary biology because it can be extended to study other traits or other infectious diseases.

Low-frequency drug-resistant HIV-1 and risk of virological failure to first-line NNRTI-based ART: a multicohort European case–control study using centralized ultrasensitive 454 pyrosequencing

Objectives It is still debated if pre-existing minority drug-resistant HIV-1 variants (MVs) affect the virological outcomes of first-line NNRTI-containing ART. Methods This Europe-wide case–control study included ART-naive subjects infected with drug-susceptible HIV-1 as revealed by population sequencing, who achieved virological suppression on first-line ART including one NNRTI. Cases experienced virological failure and controls were subjects from the same cohort whose viraemia remained suppressed at a matched time since initiation of ART. Blinded, centralized 454 pyrosequencing with parallel bioinformatic analysis in two laboratories was used to identify MVs in the 1%–25% frequency range. ORs of virological failure according to MV detection were estimated by logistic regression. Results Two hundred and sixty samples (76 cases and 184 controls), mostly subtype B (73.5%), were used for the analysis. Identical MVs were detected in the two laboratories. 31.6% of cases and 16.8% of controls harboured pre-existing MVs. Detection of at least one MV versus no MVs was associated with an increased risk of virological failure (OR = 2.75, 95% CI = 1.35–5.60, P = 0.005); similar associations were observed for at least one MV versus no NRTI MVs (OR = 2.27, 95% CI = 0.76–6.77, P = 0.140) and at least one MV versus no NNRTI MVs (OR = 2.41, 95% CI = 1.12–5.18, P = 0.024). A dose–effect relationship between virological failure and mutational load was found. Conclusions Pre-existing MVs more than double the risk of virological failure to first-line NNRTI-based ART.

Exploring the complexity of the HIV-1 fitness landscape.

Although fitness landscapes are central to evolutionary theory, so far no biologically realistic examples for large-scale fitness landscapes have been described. Most currently available biological examples are restricted to very few loci or alleles and therefore do not capture the high dimensionality characteristic of real fitness landscapes. Here we analyze large-scale fitness landscapes that are based on predictive models for in vitro replicative fitness of HIV-1. We find that these landscapes are characterized by large correlation lengths, considerable neutrality, and high ruggedness and that these properties depend only weakly on whether fitness is measured in the absence or presence of different antiretrovirals. Accordingly, adaptive processes on these landscapes depend sensitively on the initial conditions. While the relative extent to which mutations affect fitness on their own (main effects) or in combination with other mutations (epistasis) is a strong determinant of these properties, the fitness landscape of HIV-1 is considerably less rugged, less neutral, and more correlated than expected from the distribution of main effects and epistatic interactions alone. Overall this study confirms theoretical conjectures about the complexity of biological fitness landscapes and the importance of the high dimensionality of the genetic space in which adaptation takes place.

Inferring Epidemic Contact Structure from Phylogenetic Trees

Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.