Dissecting HIV Virulence: Heritability of Setpoint Viral Load, CD4+ T-Cell Decline, and Per-Parasite Pathogenicity

Virulence decomposition for bifurcating infections

A fundamental goal in infection biology is to understand the emergence of variation in pathogen virulence-here defined as the decrease in host fitness caused by a pathogen. To uncover the sources of such variation, virulence can be decomposed into both host- and pathogen-associated components. However, decomposing virulence can be challenging owing to complex within-host pathogen dynamics such as bifurcating infections, which recently received increased empirical and theoretical attention. Bifurcating infections are characterized by the emergence of two distinct infection types: (i) terminal infections with high pathogen loads resulting in rapid host death, and (ii) persistent infections with lower loads and delayed host death. Here, we propose to use discrete mixture models to perform separate virulence decompositions for each infection type. Using this approach, we reanalysed a recently published experimental dataset on bacterial load and survival in Drosophila melanogaster. This analysis revealed several advantages of the new approach, most importantly the generation of a more comprehensive picture of the varying sources of virulence in different bacterial species. Beyond this application, our approach could provide valuable information for ground-truthing and improving theoretical models of within-host infection dynamics, which are developed to predict variation in infection outcome and pathogen virulence.

Per-pathogen virulence of HIV-1 subtypes A, C and D

HIV-1 subtypes differ in their clinical manifestations and the speed in which they spread. In particular, the frequency of subtype C is increasing relative to subtypes A and D. We investigate whether HIV-1 subtypes A, C and D differ in their per-pathogen virulence and to what extend this explains the difference in spread between these subtypes. We use data from the hormonal contraception and HIV-1 genital shedding and disease progression among women with primary HIV infection study. For each study participant, we determine the set-point viral load value, CD4⁺ T cell level after primary infection and CD4⁺ T cell decline. Based on both the CD4⁺ T cell count after primary infection and CD4⁺ T cell decline, we estimate the time until AIDS. We then obtain our newly introduced measure of virulence as the inverse of the estimated time until AIDS. After fitting a model to the measured virulence and set-point viral load values, we tested if this relation varies per subtype. We found that subtype C has a significantly higher per-pathogen virulence than subtype A. Based on an evolutionary model, we then hypothesize that differences in the primary length of infection period cause the observed variation in the speed of spread of the subtypes.

Mechanisms of damage prevention, signalling and repair impact disease tolerance

The insect gut is frequently exposed to pathogenic threats and must not only clear these potential infections, but also tolerate relatively high microbe loads. In contrast to the mechanisms that eliminate pathogens, we currently know less about the mechanisms of disease tolerance. We investigated how well-described mechanisms that prevent, signal, control or repair damage during infection contribute to the phenotype of disease tolerance. We established enteric infections with the bacterial pathogen Pseudomonas entomophila in transgenic lines of Drosophila melanogaster fruit flies affecting dcy (a major component of the peritrophic matrix), upd3 (a cytokine-like molecule), irc (a negative regulator of reactive oxygen species) and egfr¹ (epithelial growth factor receptor). Flies lacking dcy experienced the highest mortality, while loss of function of either irc or upd3 reduced tolerance in both sexes. The disruption of egfr¹ resulted in a severe loss in tolerance in male flies but had no substantial effect on the ability of female flies to tolerate P. entomophila infection, despite carrying greater microbe loads than males. Together, our findings provide evidence for the role of damage limitation mechanisms in disease tolerance and highlight how sexual dimorphism in these mechanisms could generate sex differences in infection outcomes.

Decomposing virulence to understand bacterial clearance in persistent infections

Following an infection, hosts cannot always clear the pathogen, instead either dying or surviving with a persistent infection. Such variation is ecologically and evolutionarily important because it can affect infection prevalence and transmission, and virulence evolution. However, the factors causing variation in infection outcomes, and the relationship between clearance and virulence are not well understood. Here we show that sustained persistent infection and clearance are both possible outcomes across bacterial species showing a range of virulence in Drosophila melanogaster. Variation in virulence arises because of differences in the two components of virulence: bacterial infection intensity inside the host (exploitation), and the amount of damage caused per bacterium (per parasite pathogenicity). As early-phase exploitation increased, clearance rates later in the infection decreased, whereas there was no apparent effect of per parasite pathogenicity on clearance rates. Variation in infection outcomes is thereby determined by how virulence - and its components - relate to the rate of pathogen clearance. Taken together we demonstrate that the virulence decomposition framework is broadly applicable and can provide valuable insights into host-pathogen interactions.

A phylogeny-aware GWAS framework to correct for heritable pathogen effects on infectious disease traits

Infectious diseases are particularly challenging for genome-wide association studies (GWAS) because genetic effects from two organisms (pathogen and host) can influence a trait. Traditional GWAS assume individual samples are independent observations. However, pathogen effects on a trait can be heritable from donor to recipient in transmission chains. Thus, residuals in GWAS association tests for host genetic effects may not be independent due to shared pathogen ancestry. We propose a new method to estimate and remove heritable pathogen effects on a trait based on the pathogen phylogeny prior to host GWAS, thus restoring independence of samples. In simulations, we show this additional step can increase GWAS power to detect truly associated host variants when pathogen effects are highly heritable, with strong phylogenetic correlations. We applied our framework to data from two different host-pathogen systems, HIV in humans and X. arboricola in A. thaliana. In both systems, the heritability and thus phylogenetic correlations turn out to be low enough such that qualitative results of GWAS do not change when accounting for the pathogen shared ancestry through a correction step. This means that previous GWAS results applied to these two systems should not be biased due to shared pathogen ancestry. In summary, our framework provides additional information on the evolutionary dynamics of traits in pathogen populations and may improve GWAS if pathogen effects are highly phylogenetically correlated amongst individuals in a cohort.

The interplay between replication capacity of HIV-1 and surrogate markers of disease

BACKGROUND

HIV-1 replication capacity (RC) of transmitted/founder viruses may influence the further course of HIV-1 infection.

METHODS

Replication capacities (RCs) of 355 whole genome primary HIV-1 isolates derived from samples acquired during acute and recent primary HIV-1 infection (PHI) were determined using a novel high throughput infection assay in primary cells. The RCs were used to elucidate potential factors that could be associated with RC during PHI.

RESULTS

Increased RC was found to be associated with increased set point viral load (VL), and significant differences in RCs among 13 different HIV-1 subtypes were discerned. Notably, we observed an increase in RCs for primary HIV-1 isolates of HIV-1 subtype B over a 17-year period. Associations were not observed between RC and CD4 count at sample date of RC measurement, CD4 recovery after initiation of antiretroviral treatment (ART), CD4 decline in untreated individuals, and acute retroviral syndrome severity scores.

DISCUSSION

These findings highlight that RCs of primary HIV-1 isolates acquired during the acute and recent phase of infection are more associated with viral factors, i.e., set point VL, than with host factors. Furthermore, we observed a temporal increase in RC for HIV-1 subtype B viruses over a period of 17 years.

Phylogenetic Estimation of the Viral Fitness Landscape of HIV-1 Set-Point Viral Load

Set-point viral load (SPVL), a common measure of human immunodeficiency virus (HIV)-1 virulence, is partially determined by viral genotype. Epidemiological evidence suggests that this viral property has been under stabilising selection, with a typical optimum for the virus between 10⁴ and 10⁵ copies of viral RNA per ml. Here we aimed to detect transmission fitness differences between viruses from individuals with different SPVLs directly from phylogenetic trees inferred from whole-genome sequences. We used the local branching index (LBI) as a proxy for transmission fitness. We found that LBI is more sensitive to differences in infectiousness than to differences in the duration of the infectious state. By analysing subtype-B samples from the Bridging the Evolution and Epidemiology of HIV in Europe project, we inferred a significant positive relationship between SPVL and LBI up to approximately 10⁵ copies/ml, with some evidence for a peak around this value of SPVL. This is evidence of selection against low values of SPVL in HIV-1 subtype-B strains, likely related to lower infectiousness, and perhaps a peak in the transmission fitness in the expected range of SPVL. The less prominent signatures of selection against higher SPVL could be explained by an inherent limit of the method or the deployment of antiretroviral therapy.

Transmitted HIV-1 is more virulent in heterosexual individuals than men-who-have-sex-with-men

Transmission bottlenecks introduce selection pressures on HIV-1 that vary with the mode of transmission. Recent studies on small cohorts have suggested that stronger selection pressures lead to fitter transmitted/founder (T/F) strains. Manifestations of this selection bias at the population level have remained elusive. Here, we analysed early CD4 cell count measurements reported from ∼340,000 infected heterosexual individuals (HET) and men-who-have-sex-with-men (MSM), across geographies, ethnicities and calendar years. The reduction in CD4 counts early in infection is reflective of the virulence of T/F strains. MSM and HET use predominant modes of transmission, namely, anal and penile-vaginal, with among the largest differences in the selection pressures at transmission across modes. Further, in most geographies, the groups show little inter-mixing, allowing for the differential selection bias to be sustained and amplified. We found that the early reduction in CD4 counts was consistently greater in HET than MSM (P<0.05). To account for inherent variations in baseline CD4 counts, we constructed a metric to quantify the extent of progression to AIDS as the ratio of the reduction in measured CD4 counts from baseline and the reduction associated with AIDS. We found that this progression corresponding to the early CD4 measurements was ∼68% for MSM and ∼87% for HET on average (P<10⁻⁴; Cohen’s d, d_s = 0.36), reflecting the more severe disease caused by T/F strains in HET than MSM at the population level. Interestingly, the set-point viral load was not different between the groups (d_s<0.12), suggesting that MSM were more tolerant and not more resistant to their T/F strains than HET. This difference remained when we controlled for confounding factors using multivariable regression. We concluded that the different selection pressures at transmission have resulted in more virulent T/F strains in HET than MSM. These findings have implications for our understanding of HIV-1 pathogenesis, evolution, and epidemiology.

HIV-1 encounters a key bottleneck at the time of its transmission from one individual to another. This transmission bottleneck can differ between modes of transmission. The stronger this bottleneck is, the more fit the virus has to be to be successfully transmitted. Accordingly, the transmitted/founder (T/F) strains of HIV-1 may have different fitness in risk groups that use different modes of transmission. While studies on small cohorts do support this notion, observations of the manifestations of this differential selection bias at the population level have been lacking. Here, we examined reported early CD4 count measurements from ∼340,000 HET and MSM, across geographies, ethnicities, and calendar years. Early CD4 counts are a measure of the severity of the infection due to T/F strains. HET and MSM transmit predominantly via penile-vaginal and anal modes, respectively, and do not inter-mix significantly. Remarkably, we found that HET consistently had lower early CD4 counts than MSM. This difference could not be attributed to potential confounding factors, such as set-point viral load. The difference thus provided evidence that T/F strains had evolved to be more virulent in HET than MSM at the population level. Intervention strategies may benefit from accounting for this difference between risk groups.

A highly virulent variant of HIV-1 circulating in the Netherlands

We discovered a highly virulent variant of subtype-B HIV-1 in the Netherlands. One hundred nine individuals with this variant had a 0.54 to 0.74 log₁₀ increase (i.e., a ~3.5-fold to 5.5-fold increase) in viral load compared with, and exhibited CD4 cell decline twice as fast as, 6604 individuals with other subtype-B strains. Without treatment, advanced HIV-CD4 cell counts below 350 cells per cubic millimeter, with long-term clinical consequences-is expected to be reached, on average, 9 months after diagnosis for individuals in their thirties with this variant. Age, sex, suspected mode of transmission, and place of birth for the aforementioned 109 individuals were typical for HIV-positive people in the Netherlands, which suggests that the increased virulence is attributable to the viral strain. Genetic sequence analysis suggests that this variant arose in the 1990s from de novo mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence.

Virologic Outcomes Among People Living With Human Immunodeficiency Virus With High Pretherapy Viral Load Burden Initiating on Common Core Agents

Background

People living with human immunodeficiency virus (PLWH) initiating antiretroviral therapy (ART) with viral loads (VLs) ≥100 000 copies/mL are less likely to achieve virologic success, but few studies have characterized real-world treatment outcomes.

Methods

ART-naive PLWH with VLs ≥100 000 copies/mL initiating dolutegravir (DTG), elvitegravir (EVG), raltegravir (RAL), or darunavir (DRV) between 12 August 2013 and 31 July 2017 were identified from the OPERA database. Virologic failure was defined as (i) 2 consecutive VLs ≥200 copies/mL after 36 weeks of ART; (ii) 1 VL ≥200 copies/mL with core agent discontinuation after 36 weeks; (iii) 2 consecutive VLs ≥200 copies/mL after suppression (≤50 copies/mL) before 36 weeks; or (iv) 1 VL ≥200 copies/mL with discontinuation after suppression before 36 weeks. Cox modeling estimated the association between regimen and virologic failure.

Results

There were 2038 ART-naive patients with high VL who initiated DTG (36%), EVG (46%), DRV (16%), or RAL (2%). Median follow-up was 18.1 (interquartile range, 12.4–28.9) months. EVG and DTG initiators were similar at baseline, but RAL initiators were older and more likely to be female with low CD4 cell counts while DRV initiators differed notably on factors associated with treatment failure. Virologic failure was experienced by 9.2% DTG, 13.2% EVG, 18.4% RAL, and 18.8% DRV initiators. Compared to DTG, the adjusted hazard ratio (95% confidence interval) was 1.46 (1.05–2.03) for EVG, 2.24 (1.50–3.34) for DRV, and 4.13 (1.85–9.24) for RAL.

Conclusions

ART-naive PLWH with high VLs initiating on DTG were significantly less likely to experience virologic failure compared to EVG, RAL, and DRV initiators.

Antiretroviral therapy-naïve people living with HIV (PLWH) initiating therapy with viral loads ≥100,000 copies/mL varied markedly at baseline. In adjusted models, PLWH initiating dolutegravir-based regimens were less likely to experience virologic failure as compared to elvitegravir, raltegravir and darunavir initiators.

Human immunotypes impose selection on viral genotypes through viral epitope specificity

BACKGROUND

Understanding the genetic interplay between human hosts and infectious pathogens is crucial for how we interpret virulence factors. Here, we tested for associations between HIV and host genetics, and interactive genetic effects on viral load (VL) in HIV+ ART-naive clinical trial participants.

METHODS

HIV genomes were sequenced and the encoded amino acid (AA) variants were associated with VL, human single nucleotide polymorphisms (SNPs) and imputed HLA alleles, using generalized linear models with Bonferroni correction.

RESULTS

Human (388,501 SNPs) and HIV (3,010 variants) genetic data was available for 2,122 persons. Four HIV variants were associated with VL (p-values<1.66×10 -5). Twelve HIV variants were associated with a range of 1-512 human SNPs (p-value<4.28×10 -11). We found 46 associations between HLA alleles and HIV variants (p-values<1.29×10 -7). We found HIV variants and immunotypes when analyzed separately, were associated with lower VL, whereas the opposite was true when analyzed in concert. Epitope binding prediction showed HLA alleles to be weaker binders of associated HIV AA variants relative to alternative variants on the same position.

CONCLUSIONS

Our results show the importance of immunotype specificity on viral antigenic determinants, and the identified genetic interplay puts emphasis that viral and human genetics should be studied in the context of each other.

Increasing prevalence and local transmission of non-B HIV-1 subtypes in the French Antilles and French Guiana between 1995 and 2018

The Caribbean and South American French Overseas Territories (CSAFOT) are the regions most heavily affected by the Human Immunodeficiency Virus type 1 (HIV-1) epidemic in France. Although dominated by HIV-1 subtype B, the detection of non-B subtypes and the great proportion of HIV-positive persons born abroad demonstrated the potential for local spread of non-B subtype strains in CSAFOT. To reconstruct the epidemiologic dynamics of major non-B subtype clusters spreading in CSAFOT, we conducted phylogenetic and evolutionary analyses of 2,523 HIV-1 pol sequences collected from patients living in Martinique, Guadeloupe, and French Guiana from 1995 to 2018. A large variety of HIV-1 non-B subtype strains (eight subtypes, twelve CRFs, and multiple URFs) have been introduced in CSAFOT and their prevalence significantly increases over time in Martinique and Guadeloupe. We identified twelve major transmission networks of non-B subtypes (CRF02_AG and subtypes A3, C, D, and F1) that probably arose in Guadeloupe, Martinique, French Guiana, and mainland France between the late 1970s and the middle 2000s. Phylogeographic analyses support frequent non-B subtype viral transmissions within CSAFOT as well as transatlantic transmission between CSAFOT and mainland France. Domestic transmission networks of non-B subtype variants in CSAFOT comprise both men having sex with men and heterosexual individuals from different age groups. Different HIV-1 non-B subtype variants were sequentially introduced in CSAFOT between the late 1970s and the middle 2000s and are currently spreading through domestic, regional, and/or transatlantic networks of individuals from different age and risk groups.

Heritability of the HIV-1 reservoir size and decay under long-term suppressive ART

The HIV-1 reservoir is the major hurdle to curing HIV-1. However, the impact of the viral genome on the HIV-1 reservoir, i.e. its heritability, remains unknown. We investigate the heritability of the HIV-1 reservoir size and its long-term decay by analyzing the distribution of those traits on viral phylogenies from both partial-pol and viral near full-length genome sequences. We use a unique nationwide cohort of 610 well-characterized HIV-1 subtype-B infected individuals on suppressive ART for a median of 5.4 years. We find that a moderate but significant fraction of the HIV-1 reservoir size 1.5 years after the initiation of ART is explained by genetic factors. At the same time, we find more tentative evidence for the heritability of the long-term HIV-1 reservoir decay. Our findings indicate that viral genetic factors contribute to the HIV-1 reservoir size and hence the infecting HIV-1 strain may affect individual patients’ hurdle towards a cure.

The HIV reservoir is a major hurdle for a cure of HIV, but the factors determining its size and dynamics remain unclear. Here the authors show in a large cohort of 610 HIV-1 infected individuals, who are on suppressive ART for a median of 5.4 years, that viral genetic factors contribute substantially to the HIV-1 reservoir size.

D. de Azevedo S, Delatorre E, Bello G. Few amino acid signatures distinguish HIV-1 subtype B pandemic and non-pandemic strains

The Human Immunodeficiency Virus Type I (HIV-1) subtype B comprises approximately 10% of all HIV infections in the world. The HIV-1 subtype B epidemic comprehends a pandemic variant (named B_PANDEMIC) disseminated worldwide and non-pandemic variants (named B_CAR) that are mostly restricted to the Caribbean. The goal of this work was the identification of amino acid signatures (AAs) characteristic to the B_CAR and B_PANDEMIC variants. To this end, we analyzed HIV-1 subtype B full-length (n = 486) and partial (n = 814) genomic sequences from the Americas classified within the B_CAR and B_PANDEMIC clades and reconstructed the sequences of their most recent common ancestors (MRCA). Analysis of contemporary HIV-1 sequences revealed 13 AAs between B_CAR and B_PANDEMIC variants (four on Gag, three on Pol, three on Rev, and one in Vif, Vpu, and Tat) of which only two (one on Gag and one on Pol) were traced to the MRCA. All AAs correspond to polymorphic sites located outside essential functional proteins domains, except the AAs in Tat. The absence of stringent AAs inherited from their ancestors between modern B_CAR and B_PANDEMIC variants support that ecological factors, rather than viral determinants, were the main driving force behind the successful spread of the B_PANDEMIC strain.

Inferring Phenotypic Trait Evolution on Large Trees With Many Incomplete Measurements

Comparative biologists are often interested in inferring covariation between multiple biological traits sampled across numerous related taxa. To properly study these relationships, we must control for the shared evolutionary history of the taxa to avoid spurious inference. An additional challenge arises as obtaining a full suite of measurements becomes increasingly difficult with increasing taxa. This generally necessitates data imputation or integration, and existing control techniques typically scale poorly as the number of taxa increases. We propose an inference technique that integrates out missing measurements analytically and scales linearly with the number of taxa by using a post-order traversal algorithm under a multivariate Brownian diffusion (MBD) model to characterize trait evolution. We further exploit this technique to extend the MBD model to account for sampling error or non-heritable residual variance. We test these methods to examine mammalian life history traits, prokaryotic genomic and phenotypic traits, and HIV infection traits. We find computational efficiency increases that top two orders-of-magnitude over current best practices. While we focus on the utility of this algorithm in phylogenetic comparative methods, our approach generalizes to solve long-standing challenges in computing the likelihood for matrix-normal and multivariate normal distributions with missing data at scale.

Proliferation and benevolence-A framework for dissecting the mechanisms of microbial virulence and health promotion

Key topics in the study of host–microbe interactions—such as the prevention of drug resistance and the exploitation of beneficial effects of bacteria—would benefit from concerted efforts with both mechanistic and evolutionary approaches. But due to differences in intellectual traditions, insights gained in one field rarely benefit the other. Here, we develop a conceptual and analytical framework for the integrated study of host–microbe interactions. This framework partitions the health effects of microbes and the effector molecules they produce into components with different evolutionary implications. It thereby facilitates the prediction of evolutionary responses to inhibition and exploitation of specific molecular mechanisms.

The Mtb-HIV syndemic interaction: why treating M. tuberculosis infection may be crucial for HIV-1 eradication

Accelerated tuberculosis and AIDS progression seen in HIV-1 and Mycobacterium tuberculosis (Mtb)-coinfected individuals indicates the important interaction between these syndemic pathogens. The immunological interaction between HIV-1 and Mtb has been largely defined by how the virus exacerbates tuberculosis disease pathogenesis. Understanding of the mechanisms by which pre-existing or subsequent Mtb infection may favor the replication, persistence and progression of HIV, is less characterized. We present a rationale for the critical consideration of ‘latent’ Mtb infection in HIV-1 prevention and cure strategies. In support of this position, we review evidence of the effect of Mtb infection on HIV-1 acquisition, replication and persistence. We propose that ‘latent’ Mtb infection may have considerable impact on HIV-1 pathogenesis and the continuing HIV-1 epidemic in sub-Saharan Africa.

Natural selection favoring more transmissible HIV detected in United States molecular transmission network

HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters.

Fast likelihood calculation for multivariate Gaussian phylogenetic models with shifts

Phylogenetic comparative methods (PCMs) have been used to study the evolution of quantitative traits in various groups of organisms, ranging from micro-organisms to animal and plant species. A common approach has been to assume a Gaussian phylogenetic model for the trait evolution along the tree, such as a branching Brownian motion (BM) or an Ornstein-Uhlenbeck (OU) process. Then, the parameters of the process have been inferred based on a given tree and trait data for the sampled species. At the heart of this inference lie multiple calculations of the model likelihood, that is, the probability density of the observed trait data, conditional on the model parameters and the tree. With the increasing availability of big phylogenetic trees, spanning hundreds to several thousand sampled species, this approach is facing a two-fold challenge. First, the assumption of a single Gaussian process governing the entire tree is not adequate in the presence of heterogeneous evolutionary forces acting in different parts of the tree. Second, big trees present a computational challenge, due to the time and memory complexity of the model likelihood calculation. Here, we explore a sub-family, denoted G_LInv, of the Gaussian phylogenetic models, with the transition density exhibiting the properties that the expectation depends Linearly on the ancestral trait value and the variance is Invariant with respect to the ancestral value. We show that G_LInv contains the vast majority of Gaussian models currently used in PCMs, while supporting an efficient (linear in the number of nodes) algorithm for the likelihood calculation. The algorithm supports scenarios with missing data, as well as different types of trees, including trees with polytomies and non-ultrametric trees. To account for the heterogeneity in the evolutionary forces, the algorithm supports models with "shifts" occurring at specific points in the tree. Such shifts can include changes in some or all parameters, as well as the type of the model, provided that the model remains within the G_LInv family. This contrasts with most of the current implementations where, due to slow likelihood calculation, the shifts are restricted to specific parameters in a single type of model, such as the long-term selection optima of an OU process, assuming that all of its other parameters, such as evolutionary rate and selection strength, are global for the entire tree. We provide an implementation of this likelihood calculation algorithm in an accompanying R-package called PCMBase. The package has been designed as a generic library that can be integrated with existing or novel maximum likelihood or Bayesian inference tools.

Automatic generation of evolutionary hypotheses using mixed Gaussian phylogenetic models

Phylogenetic comparative methods (PCMs) are used to study the evolution of various biological species, ranging from microorganisms to animals and plants. These methods combine trait measurements, such as body masses measured in a set of species, with the species’ phylogenetic tree, to quantify the trait’s evolution along the tree. Here, we show that current PCMs fail to reproduce the patterns of evolution of brain and body mass in mammals, because they use mathematical models that cannot represent the heterogeneity of the evolutionary processes acting in different lineages of the tree. As a solution, we propose mixed Gaussian phylogenetic models allowing one to infer changes in the type and magnitude of evolutionary forces occurring on specific branches of the tree.

Phylogenetic comparative methods are widely used to understand and quantify the evolution of phenotypic traits, based on phylogenetic trees and trait measurements of extant species. Such analyses depend crucially on the underlying model. Gaussian phylogenetic models like Brownian motion and Ornstein–Uhlenbeck processes are the workhorses of modeling continuous-trait evolution. However, these models fit poorly to big trees, because they neglect the heterogeneity of the evolutionary process in different lineages of the tree. Previous works have addressed this issue by introducing shifts in the evolutionary model occurring at inferred points in the tree. However, for computational reasons, in all current implementations, these shifts are “intramodel,” meaning that they allow jumps in 1 or 2 model parameters, keeping all other parameters “global” for the entire tree. There is no biological reason to restrict a shift to a single model parameter or, even, to a single type of model. Mixed Gaussian phylogenetic models (MGPMs) incorporate the idea of jointly inferring different types of Gaussian models associated with different parts of the tree. Here, we propose an approximate maximum-likelihood method for fitting MGPMs to comparative data comprising possibly incomplete measurements for several traits from extant and extinct phylogenetically linked species. We applied the method to the largest published tree of mammal species with body- and brain-mass measurements, showing strong statistical support for an MGPM with 12 distinct evolutionary regimes. Based on this result, we state a hypothesis for the evolution of the brain–body-mass allometry over the past 160 million y.

Interaction of the Host and Viral Genome and Their Influence on HIV Disease

The course of Human Immunodeficiency Virus type 1 (HIV) infection is a dynamic interplay in which both host and viral genetic variation, among other factors, influence disease susceptibility and rate of progression. HIV set-point viral load (spVL), a key indicator of HIV disease progression, has an estimated 30% of variance attributable to common heritable effects and roughly 70% attributable to environmental factors and/or additional non-genetic factors. Genome-wide genotyping and sequencing studies have allowed for large-scale association testing studying host and viral genetic variants associated with infection and disease progression. Host genomics of HIV infection has been studied predominantly in Caucasian populations consistently identifying human leukocyte antigen (HLA) genes and C-C motif chemokine receptor 5 as key factors of HIV susceptibility and progression. However, these studies don’t fully assess all classes of genetic variation (e.g., very rare polymorphisms, copy number variants etc.) and do not inform on non-European ancestry groups. Additionally, viral sequence variability has been demonstrated to influence disease progression independently of host genetic variation. Viral sequence variation can be attributed to the rapid evolution of the virus within the host due to the selective pressure of the host immune response. As the host immune system responds to the virus, e.g., through recognition of HIV antigens, the virus is able to mitigate this response by evolving HLA-specific escape mutations. Diversity of viral genotypes has also been correlated with moderate to strong effects on CD4+ T cell decline and some studies showing weak to no correlation with spVL. There is evidence to support these viral genetic factors being heritable between individuals and the evolution of these factors having important consequences in the genetic epidemiology of HIV infection on a population level. This review will discuss the host-pathogen interaction of HIV infection, explore the importance of host and viral genetics for a better understanding of pathogenesis and identify opportunities for additional genetic studies.

Tracing HIV-1 strains that imprint broadly neutralizing antibody responses

Understanding the determinants of broadly neutralizing antibody (bNAb) evolution is crucial for the development of bNAb-based HIV vaccines¹. Despite emerging information on cofactors that promote bNAb evolution in natural HIV-1 infections, in which the induction of bNAbs is genuinely rare², information on the impact of the infecting virus strain on determining the breadth and specificity of the antibody responses to HIV-1 is lacking. Here we analyse the influence of viral antigens in shaping antibody responses in humans. We call the ability of a virus strain to induce similar antibody responses across different hosts its antibody-imprinting capacity, which from an evolutionary biology perspective corresponds to the viral heritability of the antibody responses. Analysis of 53 measured parameters of HIV-1-binding and neutralizing antibody responses in a cohort of 303 HIV-1 transmission pairs (individuals who harboured highly related HIV-1 strains and were putative direct transmission partners or members of an HIV-1 transmission chain) revealed that the effect of the infecting virus on the outcome of the bNAb response is moderate in magnitude but highly significant. We introduce the concept of bNAb-imprinting viruses and provide evidence for the existence of such viruses in a systematic screening of our cohort. The bNAb-imprinting capacity can be substantial, as indicated by a transmission pair with highly similar HIV-1 antibody responses and strong bNAb activity. Identification of viruses that have bNAb-imprinting capacities and their characterization may thus provide the potential to develop lead immunogens.

The HIV-1 Subtype B Epidemic in French Guiana and Suriname Is Driven by Ongoing Transmissions of Pandemic and Non-pandemic Lineages

The HIV-1 subtype B epidemic in French Guiana and Suriname is characterized by the co-circulation of the globally disseminated “B_PANDEMIC” lineage and of non-pandemic subtype B lineages of Caribbean origin (B_CAR). To reconstruct the spatiotemporal pattern of spread of those viral lineages circulating in these two countries, a total of 361 HIV-1 subtype B pol sequences recovered from treatment-naive adult patients from French Guiana and Suriname between 2006 and 2012 were combined with B_PANDEMIC and B_CAR reference sequences. Major Guianese/Surinamese B_PANDEMIC and B_CAR lineages were identified by Maximum Likelihood phylogenetic analysis and the spatiotemporal and demographic parameters estimated using a Bayesian coalescent-based method. We detected four B_CAR and three B_PANDEMIC transmission chains of large size that together comprise most pandemic and non-pandemic subtype B sequences from French Guiana (≥52%) and Suriname (≥70%) here analyzed. These major lineages were probably introduced into French Guiana and Suriname from the Caribbean (B_CAR) and North/South America (B_PANDEMIC) between the middle 1970s and the late 1980s and spread among populations from both countries with roughly comparable demographic growth rates. We detected a significant trend for higher viral loads and higher proportion of homosexual/bisexual men among subjects infected with B_PANDEMIC relative to B_CAR strains in French Guiana. These results show that the HIV subtype B epidemic in French Guiana and Suriname has been driven by multiple active B_CAR and B_PANDEMIC transmission chains that arose since the middle 1970s onward and operate in both countries simultaneously. Although no significant differences in the epidemic potential of major B_CAR and B_PANDEMIC lineages were observed, relevant associations between the infecting subtype B lineage and epidemiological and clinical characteristics were detected in French Guiana.

A Practical Guide to Estimating the Heritability of Pathogen Traits

Pathogen traits, such as the virulence of an infection, can vary significantly between patients. A major challenge is to measure the extent to which genetic differences between infecting strains explain the observed variation of the trait. This is quantified by the trait’s broad-sense heritability, H². A recent discrepancy between estimates of the heritability of HIV-virulence has opened a debate on the estimators’ accuracy. Here, we show that the discrepancy originates from model limitations and important lifecycle differences between sexually reproducing organisms and transmittable pathogens. In particular, current quantitative genetics methods, such as donor–recipient regression of surveyed serodiscordant couples and the phylogenetic mixed model (PMM), are prone to underestimate H², because they neglect or do not fit to the loss of resemblance between transmission partners caused by within-host evolution. In a phylogenetic analysis of 8,483 HIV patients from the United Kingdom, we show that the phenotypic correlation between transmission partners decays with the amount of within-host evolution of the virus. We reproduce this pattern in toy-model simulations and show that a phylogenetic Ornstein–Uhlenbeck model (POUMM) outperforms the PMM in capturing this correlation pattern and in quantifying H². In particular, we show that POUMM outperforms PMM even in simulations without selection—as it captures the mentioned correlation pattern—which has not been appreciated until now. By cross-validating the POUMM estimates with ANOVA on closest phylogenetic pairs, we obtain H² ≈ 0.2, meaning ∼20% of the variation in HIV-virulence is explained by the virus genome both for European and African data.