Is HIV short-sighted? Insights from a multistrain nested model

An important component of pathogen evolution at the population level is evolution within hosts. Unless evolution within hosts is very slow compared to the duration of infection, the composition of pathogen genotypes within a host is likely to change during the course of an infection, thus altering the composition of genotypes available for transmission as infection progresses. We develop a nested modeling approach that allows us to follow the evolution of pathogens at the epidemiological level by explicitly considering within-host evolutionary dynamics of multiple competing strains and the timing of transmission. We use the framework to investigate the impact of short-sighted within-host evolution on the evolution of virulence of human immunodeficiency virus (HIV), and find that the topology of the within-host adaptive landscape determines how virulence evolves at the epidemiological level. If viral reproduction rates increase significantly during the course of infection, the viral population will evolve a high level of virulence even though this will reduce the transmission potential of the virus. However, if reproduction rates increase more modestly, as data suggest, our model predicts that HIV virulence will be only marginally higher than the level that maximizes the transmission potential of the virus

Short-sighted virus evolution and a germline hypothesis for chronic viral infections

This work was funded by The Wellcome Trust and The Royal Society grant numbers wtvm055984 (KAL) and 107653/Z/15/Z (JG), The Natural Environment Research Council grant number NE/K009524/1 (AG), and The European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant number 614725-PATHPHYLODYN (OGP).With extremely short generation times and high mutability, many viruses can rapidly evolve and adapt to changing environments. This ability is generally beneficial to viruses as it allows them to evade host immune responses, evolve new behaviours, and exploit ecological niches. However, natural selection typically generates adaptation in response to the immediate selection pressures that a virus experiences in its current host. Consequently, we argue that some viruses, particularly those characterised by long durations of infection and ongoing replication, may be susceptible to short-sighted evolution, whereby a virus’ adaptation to its current host will be detrimental to its onward transmission within the host population. Here we outline the concept of short-sighted viral evolution and provide examples of how it may negatively impact viral transmission among hosts. We also propose that viruses that are vulnerable to short-sighted evolution may exhibit strategies that minimise its effects. We speculate on the various mechanisms by which this may be achieved, including viral life history strategies that result in low rates of within-host evolution, or the establishment of a ‘germline’ lineage of viruses that avoids short-sighted evolution. These concepts provide a new perspective on the way in which some viruses have been able to establish and maintain global pandemics.Publisher PDFPeer reviewe

Number of HIV-1 founder variants is determined by the recency of the source partner infection

During sexual transmission, the high genetic diversity of HIV-1 within an individual is frequently reduced to one founder variant that initiates infection. Understanding the drivers of this bottleneck is crucial to developing effective infection control strategies. Little is known about the importance of the source partner during this bottleneck. To test the hypothesis that the source partner affects the number of HIV founder variants, we developed a phylodynamic model calibrated using genetic and epidemiological data on all existing transmission pairs for whom the direction of transmission and the infection stage of the source partner are known. Our results suggest that acquiring infection from someone in the acute (early) stage of infection increases the risk of multiple-founder variant transmission compared with acquiring infection from someone in the chronic (later) stage of infection. This study provides the first direct test of source partner characteristics to explain the low frequency of multiple-founder strain infections

A de novo approach to inferring within-host fitness effects during untreated HIV-1 infection

Funder: Isaac Newton Trust; funder-id: http://dx.doi.org/10.13039/501100004815Funder: Li Ka Shing Foundation; funder-id: http://dx.doi.org/10.13039/100007421Funder: Division of Intramural Research, National Institute of Allergy and Infectious Diseases; funder-id: http://dx.doi.org/10.13039/100006492Funder: Helsingin Yliopisto; funder-id: http://dx.doi.org/10.13039/100007797In the absence of effective antiviral therapy, HIV-1 evolves in response to the within-host environment, of which the immune system is an important aspect. During the earliest stages of infection, this process of evolution is very rapid, driven by a small number of CTL escape mutations. As the infection progresses, immune escape variants evolve under reduced magnitudes of selection, while competition between an increasing number of polymorphic alleles (i.e., clonal interference) makes it difficult to quantify the magnitude of selection acting upon specific variant alleles. To tackle this complex problem, we developed a novel multi-locus inference method to evaluate the role of selection during the chronic stage of within-host infection. We applied this method to targeted sequence data from the p24 and gp41 regions of HIV-1 collected from 34 patients with long-term untreated HIV-1 infection. We identify a broad distribution of beneficial fitness effects during infection, with a small number of variants evolving under strong selection and very many variants evolving under weaker selection. The uniquely large number of infections analysed granted a previously unparalleled statistical power to identify loci at which selection could be inferred to act with statistical confidence. Our model makes no prior assumptions about the nature of alleles under selection, such that any synonymous or non-synonymous variant may be inferred to evolve under selection. However, the majority of variants inferred with confidence to be under selection were non-synonymous in nature, and in most cases were have previously been associated with either CTL escape in p24 or neutralising antibody escape in gp41. We also identified a putative new CTL escape site (residue 286 in gag), and a region of gp41 (including residues 644, 648, 655 in env) likely to be associated with immune escape. Sites inferred to be under selection in multiple hosts have high within-host and between-host diversity although not all sites with high between-host diversity were inferred to be under selection at the within-host level. Our identification of selection at sites associated with resistance to broadly neutralising antibodies (bNAbs) highlights the need to fully understand the role of selection in untreated individuals when designing bNAb based therapies

Using phylogenetics to infer HIV-1 transmission direction between known transmission pairs.

Inferring the transmission direction between linked individuals living with HIV provides unparalleled power to understand the epidemiology that determines transmission. Phylogenetic ancestral-state reconstruction approaches infer the transmission direction by identifying the individual in whom the most recent common ancestor of the virus populations originated. While these methods vary in accuracy, it is unclear why. To evaluate the performance of phylogenetic ancestral-state reconstruction to determine the transmission direction of HIV-1 infection, we inferred the transmission direction for 112 transmission pairs where transmission direction and detailed additional information were available. We then fit a statistical model to evaluate the extent to which epidemiological, sampling, genetic, and phylogenetic factors influenced the outcome of the inference. Finally, we repeated the analysis under real-life conditions with only routinely available data. We found that whether ancestral-state reconstruction correctly infers the transmission direction depends principally on the phylogeny's topology. For example, under real-life conditions, the probability of identifying the correct transmission direction increases from 32%-when a monophyletic-monophyletic or paraphyletic-polyphyletic tree topology is observed and when the tip closest to the root does not agree with the state at the root-to 93% when a paraphyletic-monophyletic topology is observed and when the tip closest to the root agrees with the root state. Our results suggest that documenting larger differences in relative intrahost diversity increases our confidence in the transmission direction inference of linked pairs for population-level studies of HIV. These findings provide a practical starting point to determine our confidence in transmission direction inference from ancestral-state reconstruction

Challenges in control of COVID-19: short doubling time and long delay to effect of interventions

Early assessments of the growth rate of COVID-19 were subject to significant uncertainty, as expected with limited data and difficulties in case ascertainment, but as cases were recorded in multiple countries, more robust inferences could be made. Using multiple countries, data streams and methods, we estimated that, when unconstrained, European COVID-19 confirmed cases doubled on average every 3 days (range 2.2-4.3 days) and Italian hospital and intensive care unit admissions every 2-3 days; values that are significantly lower than the 5-7 days dominating the early published literature. Furthermore, we showed that the impact of physical distancing interventions was typically not seen until at least 9 days after implementation, during which time confirmed cases could grow eightfold. We argue that such temporal patterns are more critical than precise estimates of the time-insensitive basic reproduction number R0 for initiating interventions, and that the combination of fast growth and long detection delays explains the struggle in countries' outbreak response better than large values of R0 alone. One year on from first reporting these results, reproduction numbers continue to dominate the media and public discourse, but robust estimates of unconstrained growth remain essential for planning worst-case scenarios, and detection delays are still key in informing the relaxation and re-implementation of interventions. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'

Bimodal distribution and set point HBV DNA viral loads in chronic infection:retrospective analysis of cohorts from the UK and South Africa

CITATION: Downs, L. O. 2020. Bimodal distribution and set point HBV DNA viral loads in chronic infection : retrospective analysis of cohorts from the UK and South Africa. Wellcome Open Research, 14(5):113, doi: 10.12688/wellcomeopenres.15941.2.The original publication is available at: https://pubmed.ncbi.nlm.nih.govENGLISH ABSTRACT: Hepatitis B virus (HBV) viral load (VL) is used as a biomarker to assess risk of disease progression, and to determine eligibility for treatment. While there is a well recognised association between VL and the expression of the viral e-antigen protein, the distributions of VL at a population level are not well described. We here present cross-sectional, observational HBV VL data from two large population cohorts in the UK and in South Africa, demonstrating a consistent bimodal distribution. The right skewed distribution and low median viral loads are different from the left-skew and higher viraemia in seen in HIV and hepatitis C virus (HCV) cohorts in the same settings. Using longitudinal data, we present evidence for a stable 'set-point' VL in peripheral blood during chronic HBV infection. These results are important to underpin improved understanding of HBV biology, to inform approaches to viral sequencing, and to plan public health interventions.Publisher's versio

Bimodal distribution and set point HBV DNA viral loads in chronic infection:retrospective analysis of cohorts from the UK and South Africa

CITATION: Downs, L. O. 2020. Bimodal distribution and set point HBV DNA viral loads in chronic infection : retrospective analysis of cohorts from the UK and South Africa. Wellcome Open Research, 14(5):113, doi: 10.12688/wellcomeopenres.15941.2.The original publication is available at: https://pubmed.ncbi.nlm.nih.govENGLISH ABSTRACT: Hepatitis B virus (HBV) viral load (VL) is used as a biomarker to assess risk of disease progression, and to determine eligibility for treatment. While there is a well recognised association between VL and the expression of the viral e-antigen protein, the distributions of VL at a population level are not well described. We here present cross-sectional, observational HBV VL data from two large population cohorts in the UK and in South Africa, demonstrating a consistent bimodal distribution. The right skewed distribution and low median viral loads are different from the left-skew and higher viraemia in seen in HIV and hepatitis C virus (HCV) cohorts in the same settings. Using longitudinal data, we present evidence for a stable 'set-point' VL in peripheral blood during chronic HBV infection. These results are important to underpin improved understanding of HBV biology, to inform approaches to viral sequencing, and to plan public health interventions.Publisher's versio

Hepatitis B Virus Adaptation to the CD8+ T Cell Response: Consequences for Host and Pathogen

Chronic viral hepatitis infections are a major public health concern, with an estimated 290 million individuals infected with hepatitis B virus (HBV) globally. This virus has been a passenger in human populations for >30,000 years, and remains highly prevalent in some settings. In order for this endemic pathogen to persist, viral adaptation to host immune responses is pre-requisite. Here, we focus on the interplay between HBV infection and the CD8+ T cell response. We present the evidence that CD8+ T cells play an important role in control of chronic HBV infection and that the selective pressure imposed on HBV through evasion of these immune responses can potentially influence viral diversity, chronicity, and the outcome of infection, and highlight where there are gaps in current knowledge. Understanding the nature and mechanisms of HBV evolution and persistence could shed light on differential disease outcomes, including cirrhosis and hepatocellular carcinoma, and help reach the goal of global HBV elimination by guiding the design of new strategies, including vaccines and therapeutics

Challenges in control of COVID-19: short doubling time and long delay to effect of interventions

From The Royal Society via Jisc Publications RouterHistory: accepted 2021-04-21, pub-electronic 2021-05-31, pub-print 2021-07-19Article version: VoRPublication status: PublishedFunder: Wellcome Trust; Id: http://dx.doi.org/10.13039/100004440; Grant(s): 107652/Z/15/Z, 202562/Z/16/ZFunder: Institute of Population and Public Health; Id: http://dx.doi.org/10.13039/501100000036; Grant(s): CIHR 2019 Novel Coronavirus (COVID-19) rapid reseaFunder: National Institute for Health Research; Id: http://dx.doi.org/10.13039/501100000272Funder: Medical Research Council; Id: http://dx.doi.org/10.13039/501100000265; Grant(s): MR/S020462/1, MR/V038613/1Funder: Public Health Research Programme; Id: http://dx.doi.org/10.13039/501100001921Funder: Biotechnology and Biological Sciences Research Council; Id: http://dx.doi.org/10.13039/501100000268; Grant(s): BB/R009236/1Funder: Royal Society; Id: http://dx.doi.org/10.13039/501100000288; Grant(s): INF\R2\180067Funder: Alan Turing Institute; Id: http://dx.doi.org/10.13039/100012338Early assessments of the growth rate of COVID-19 were subject to significant uncertainty, as expected with limited data and difficulties in case ascertainment, but as cases were recorded in multiple countries, more robust inferences could be made. Using multiple countries, data streams and methods, we estimated that, when unconstrained, European COVID-19 confirmed cases doubled on average every 3 days (range 2.2–4.3 days) and Italian hospital and intensive care unit admissions every 2–3 days; values that are significantly lower than the 5–7 days dominating the early published literature. Furthermore, we showed that the impact of physical distancing interventions was typically not seen until at least 9 days after implementation, during which time confirmed cases could grow eightfold. We argue that such temporal patterns are more critical than precise estimates of the time-insensitive basic reproduction number R0 for initiating interventions, and that the combination of fast growth and long detection delays explains the struggle in countries' outbreak response better than large values of R0 alone. One year on from first reporting these results, reproduction numbers continue to dominate the media and public discourse, but robust estimates of unconstrained growth remain essential for planning worst-case scenarios, and detection delays are still key in informing the relaxation and re-implementation of interventions. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’