Population genomics of intrapatient HIV-1 evolution

Comparative Analysis of Within-Host Mutation Patterns and Diversity of Hepatitis C Virus Subtypes 1a, 1b, and 3a

Understanding within-host evolution is critical for predicting viral evolutionary outcomes, yet such studies are currently lacking due to difficulty involving human subjects. Hepatitis C virus (HCV) is an RNA virus with high mutation rates. Its complex evolutionary dynamics and extensive genetic diversity are demonstrated in over 67 known subtypes. In this study, we analyzed within-host mutation frequency patterns of three HCV subtypes, using a large number of samples obtained from treatment-naïve participants by next-generation sequencing. We report that overall mutation frequency patterns are similar among subtypes, yet subtype 3a consistently had lower mutation frequencies and nucleotide diversity, while subtype 1a had the highest. We found that about 50% of genomic sites are highly conserved across subtypes, which are likely under strong purifying selection. We also compared within-host and between-host selective pressures, which revealed that Hyper Variable Region 1 within hosts was under positive selection, but was under slightly negative selection between hosts, which indicates that many mutations created within hosts are removed during the transmission bottleneck. Examining the natural prevalence of known resistance-associated variants showed their consistent existence in the treatment-naïve participants. These results provide insights into the differences and similarities among HCV subtypes that may be used to develop and improve HCV therapies.

Computational Design of gRNAs Targeting Genetic Variants Across HIV-1 Subtypes for CRISPR-Mediated Antiviral Therapy

Clustered regularly interspaced short palindromic repeats (CRISPR)-based HIV-1 genome editing has shown promising outcomes in in vitro and in vivo viral infection models. However, existing HIV-1 sequence variants have been shown to reduce CRISPR-mediated efficiency and induce viral escape. Two metrics, global patient coverage and global subtype coverage, were used to identify guide RNA (gRNA) sequences that account for this viral diversity from the perspectives of cross-patient and cross-subtype gRNA design, respectively. Computational evaluation using these parameters and over 3.6 million possible 20-bp sequences resulted in nine lead gRNAs, two of which were previously published. This analysis revealed the benefit and necessity of considering all sequence variants for gRNA design. Of the other seven identified novel gRNAs, two were of note as they targeted interesting functional regions. One was a gRNA predicted to induce structural disruption in the nucleocapsid binding site (Ψ), which holds the potential to stop HIV-1 replication during the viral genome packaging process. The other was a reverse transcriptase (RT)-targeting gRNA that was predicted to cleave the subdomain responsible for dNTP incorporation. CRISPR-mediated sequence edits were predicted to occur on critical residues where HIV-1 has been shown to develop resistance against antiretroviral therapy (ART), which may provide additional evolutionary pressure at the DNA level. Given these observations, consideration of broad-spectrum gRNAs and cross-subtype diversity for gRNA design is not only required for the development of generalizable CRISPR-based HIV-1 therapy, but also helps identify optimal target sites.

Norovirus evolution in immunodeficient mice reveals potentiated pathogenicity via a single nucleotide change in the viral capsid

Interferons (IFNs) are key controllers of viral replication, with intact IFN responses suppressing virus growth and spread. Using the murine norovirus (MNoV) system, we show that IFNs exert selective pressure to limit the pathogenic evolutionary potential of this enteric virus. In animals lacking type I IFN signaling, the nonlethal MNoV strain CR6 rapidly acquired enhanced virulence via conversion of a single nucleotide. This nucleotide change resulted in amino acid substitution F514I in the viral capsid, which led to >10,000-fold higher replication in systemic organs including the brain. Pathogenicity was mediated by enhanced recruitment and infection of intestinal myeloid cells and increased extraintestinal dissemination of virus. Interestingly, the trade-off for this mutation was reduced fitness in an IFN-competent host, in which CR6 bearing F514I exhibited decreased intestinal replication and shedding. In an immunodeficient context, a spontaneous amino acid change can thus convert a relatively avirulent viral strain into a lethal pathogen.

Intra-host variation and evolutionary dynamics of SARS-CoV-2 populations in COVID-19 patients

BACKGROUND

Since early February 2021, the causative agent of COVID-19, SARS-CoV-2, has infected over 104 million people with more than 2 million deaths according to official reports. The key to understanding the biology and virus-host interactions of SARS-CoV-2 requires the knowledge of mutation and evolution of this virus at both inter- and intra-host levels. However, despite quite a few polymorphic sites identified among SARS-CoV-2 populations, intra-host variant spectra and their evolutionary dynamics remain mostly unknown.

METHODS

Using high-throughput sequencing of metatranscriptomic and hybrid captured libraries, we characterized consensus genomes and intra-host single nucleotide variations (iSNVs) of serial samples collected from eight patients with COVID-19. The distribution of iSNVs along the SARS-CoV-2 genome was analyzed and co-occurring iSNVs among COVID-19 patients were identified. We also compared the evolutionary dynamics of SARS-CoV-2 population in the respiratory tract (RT) and gastrointestinal tract (GIT).

RESULTS

The 32 consensus genomes revealed the co-existence of different genotypes within the same patient. We further identified 40 intra-host single nucleotide variants (iSNVs). Most (30/40) iSNVs presented in a single patient, while ten iSNVs were found in at least two patients or identical to consensus variants. Comparing allele frequencies of the iSNVs revealed a clear genetic differentiation between intra-host populations from the respiratory tract (RT) and gastrointestinal tract (GIT), mostly driven by bottleneck events during intra-host migrations. Compared to RT populations, the GIT populations showed a better maintenance and rapid development of viral genetic diversity following the suspected intra-host bottlenecks.

CONCLUSIONS

Our findings here illustrate the intra-host bottlenecks and evolutionary dynamics of SARS-CoV-2 in different anatomic sites and may provide new insights to understand the virus-host interactions of coronaviruses and other RNA viruses.

Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or "haplotypes." However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

Next Generation Sequencing and Bioinformatics Methodologies for Infectious Disease Research and Public Health: Approaches, Applications, and Considerations for Development of Laboratory Capacity

Next generation sequencing (NGS) combined with bioinformatics has successfully been used in a vast array of analyses for infectious disease research of public health relevance. For instance, NGS and bioinformatics approaches have been used to identify outbreak origins, track transmissions, investigate epidemic dynamics, determine etiological agents of a disease, and discover novel human pathogens. However, implementation of high-quality NGS and bioinformatics in research and public health laboratories can be challenging. These challenges mainly include the choice of the sequencing platform and the sequencing approach, the choice of bioinformatics methodologies, access to the appropriate computation and information technology infrastructure, and recruiting and retaining personnel with the specialized skills and experience in this field. In this review, we summarize the most common NGS and bioinformatics workflows in the context of infectious disease genomic surveillance and pathogen discovery, and highlight the main challenges and considerations for setting up an NGS and bioinformatics-focused infectious disease research public health laboratory. We describe the most commonly used sequencing platforms and review their strengths and weaknesses. We review sequencing approaches that have been used for various pathogens and study questions, as well as the most common difficulties associated with these approaches that should be considered when implementing in a public health or research setting. In addition, we provide a review of some common bioinformatics tools and procedures used for pathogen discovery and genome assembly, along with the most common challenges and solutions. Finally, we summarize the bioinformatics of advanced viral, bacterial, and parasite pathogen characterization, including types of study questions that can be answered when utilizing NGS and bioinformatics.

V-pipe: a computational pipeline for assessing viral genetic diversity from high-throughput data

Motivation

High-throughput sequencing technologies are used increasingly not only in viral genomics research but also in clinical surveillance and diagnostics. These technologies facilitate the assessment of the genetic diversity in intra-host virus populations, which affects transmission, virulence and pathogenesis of viral infections. However, there are two major challenges in analysing viral diversity. First, amplification and sequencing errors confound the identification of true biological variants, and second, the large data volumes represent computational limitations.

Results

To support viral high-throughput sequencing studies, we developed V-pipe, a bioinformatics pipeline combining various state-of-the-art statistical models and computational tools for automated end-to-end analyses of raw sequencing reads. V-pipe supports quality control, read mapping and alignment, low-frequency mutation calling, and inference of viral haplotypes. For generating high-quality read alignments, we developed a novel method, called ngshmmalign, based on profile hidden Markov models and tailored to small and highly diverse viral genomes. V-pipe also includes benchmarking functionality providing a standardized environment for comparative evaluations of different pipeline configurations. We demonstrate this capability by assessing the impact of three different read aligners (Bowtie 2, BWA MEM, ngshmmalign) and two different variant callers (LoFreq, ShoRAH) on the performance of calling single-nucleotide variants in intra-host virus populations. V-pipe supports various pipeline configurations and is implemented in a modular fashion to facilitate adaptations to the continuously changing technology landscape.

Availabilityand implementation

V-pipe is freely available at https://github.com/cbg-ethz/V-pipe.

Supplementary information

Supplementary data are available at Bioinformatics online.

Evidence for adaptive evolution in the receptor-binding domain of seasonal coronaviruses OC43 and 229e

Seasonal coronaviruses (OC43, 229E, NL63, and HKU1) are endemic to the human population, regularly infecting and reinfecting humans while typically causing asymptomatic to mild respiratory infections. It is not known to what extent reinfection by these viruses is due to waning immune memory or antigenic drift of the viruses. Here we address the influence of antigenic drift on immune evasion of seasonal coronaviruses. We provide evidence that at least two of these viruses, OC43 and 229E, are undergoing adaptive evolution in regions of the viral spike protein that are exposed to human humoral immunity. This suggests that reinfection may be due, in part, to positively selected genetic changes in these viruses that enable them to escape recognition by the immune system. It is possible that, as with seasonal influenza, these adaptive changes in antigenic regions of the virus would necessitate continual reformulation of a vaccine made against them.

Efficient inference, potential, and limitations of site-specific substitution models

Natural selection imposes a complex filter on which variants persist in a population resulting in evolutionary patterns that vary greatly along the genome. Some sites evolve close to neutrally, while others are highly conserved, allow only specific states, or only change in concert with other sites. On one hand, such constraints on sequence evolution can be to infer biological function, one the other hand they need to be accounted for in phylogenetic reconstruction. Phylogenetic models often account for this complexity by partitioning sites into a small number of discrete classes with different rates and/or state preferences. Appropriate model complexity is typically determined by model selection procedures. Here, we present an efficient algorithm to estimate more complex models that allow for different preferences at every site and explore the accuracy at which such models can be estimated from simulated data. Our iterative approximate maximum likelihood scheme uses information in the data efficiently and accurately estimates site-specific preferences from large data sets with moderately diverged sequences and known topology. However, the joint estimation of site-specific rates, and site-specific preferences, and phylogenetic branch length can suffer from identifiability problems, while ignoring variation in preferences across sites results in branch length underestimates. Site-specific preferences estimated from large HIV pol alignments show qualitative concordance with intra-host estimates of fitness costs. Analysis of these substitution models suggests near saturation of divergence after a few hundred years. Such saturation can explain the inability to infer deep divergence times of HIV and SIVs using molecular clock approaches and time-dependent rate estimates.

Embracing diversity: how can broadly neutralizing antibodies effectively target a diverse HIV-1 reservoir?

Genetic diversity in the latent proviral reservoir of HIV-1 infected individuals poses a challenge to cure strategies. It has become increasingly evident that diversity increases proportionally with length of active infection, and that functional and/or sterilizing cure strategies will need to overcome this obstacle in individuals who initiated antiretroviral therapy (ART) during chronic infection. Analyzing the results of analytic treatment interruption (ATI) has allowed for the evaluation of such therapeutic strategies in HIV+ individuals. Strategies to overcome the genetic diversity of the HIV-1 reservoir include antibody combinations, pre-screening individuals for bNAb sensitivity, focusing on low-diversity individuals as well as targeting host proteins.

PIQMEE: Bayesian Phylodynamic Method for Analysis of Large Data Sets with Duplicate Sequences

Next-generation sequencing of pathogen quasispecies within a host yields data sets of tens to hundreds of unique sequences. However, the full data set often contains thousands of sequences, because many of those unique sequences have multiple identical copies. Data sets of this size represent a computational challenge for currently available Bayesian phylogenetic and phylodynamic methods. Through simulations, we explore how large data sets with duplicate sequences affect the speed and accuracy of phylogenetic and phylodynamic analysis within BEAST 2. We show that using unique sequences only leads to biases, and using a random subset of sequences yields imprecise parameter estimates. To overcome these shortcomings, we introduce PIQMEE, a BEAST 2 add-on that produces reliable parameter estimates from full data sets with increased computational efficiency as compared with the currently available methods within BEAST 2. The principle behind PIQMEE is to resolve the tree structure of the unique sequences only, while simultaneously estimating the branching times of the duplicate sequences. Distinguishing between unique and duplicate sequences allows our method to perform well even for very large data sets. Although the classic method converges poorly for data sets of 6,000 sequences when allowed to run for 7 days, our method converges in slightly more than 1 day. In fact, PIQMEE can handle data sets of around 21,000 sequences with 20 unique sequences in 14 days. Finally, we apply the method to a real, within-host HIV sequencing data set with several thousand sequences per patient.

Subclinical Cytomegalovirus and Epstein-Barr Virus Shedding Is Associated with Increasing HIV DNA Molecular Diversity in Peripheral Blood during Suppressive Antiretroviral Therapy

Cytomegalovirus (CMV) almost universally infects persons with HIV (PWH), and it is a driver of persistent inflammation and HIV persistence. The mechanisms underlying the association between CMV (and possibly other herpesviruses) and HIV persistence are unclear. Serially collected blood samples were obtained from men who have sex with men (MSM) who started antiretroviral therapy (ART) within 1 year of their estimated date of HIV infection (EDI). Total CMV and Epstein-Barr virus (EBV) DNA were quantified in peripheral blood mononuclear cells by droplet digital PCR (ddPCR). Deep sequencing of the HIV DNA partial env gene was performed, and the dynamics of viral diversity over time were analyzed in relation to CMV and EBV shedding status. In total, 37 MSM PWH were included and followed for a median of 23 months (IQR, 22 to 28). Participants started ART within a median of 3.1 months (IQR, 1.5 to 6.5) after EDI and remained virally suppressed thereafter. A total of 18 participants (48.6%) were classified as high EBV shedders, while 19 (51.4%) were classified as CMV shedders. In longitudinal analyses, normalized molecular diversity levels tended to increase over time among participants with detectable CMV and high EBV DNA (0.03 ± 0.02, P = 0.08), while they significantly declined among participants with no/low viral shedding (-0.04 ± 0.02, P = 0.047, interaction P < 0.01). Subclinical CMV and EBV shedding could contribute to the dynamics of the HIV DNA reservoir during suppressive ART. Whether persistent CMV/EBV replication could be targeted as a strategy to reduce the size of the latent HIV reservoir is an avenue that should be explored.IMPORTANCE As part of this study, we evaluated the molecular characteristics of the HIV DNA reservoir over time during antiretroviral treatment (ART) in relation to those of other chronic viral infections (i.e., cytomegalovirus [CMV] and Epstein-Barr virus [EBV]). We demonstrated that the presence of CMV and high-level EBV DNA in peripheral blood cells was associated with changes in HIV DNA molecular diversity. Specifically, HIV DNA molecular diversity increased over time among participants with detectable CMV and high-level EBV DNA, while it significantly declined among participants with no/low viral shedding. Although the current study design does not allow causality to be inferred, it does support the theory that persistent CMV and EBV shedding could contribute to the dynamics of the HIV DNA reservoir during suppressive ART, even when ART is initiated during the earliest phases of HIV infection.

Genomic Analysis of European Drosophila melanogaster Populations Reveals Longitudinal Structure, Continent-Wide Selection, and Previously Unknown DNA Viruses

Genetic variation is the fuel of evolution, with standing genetic variation especially important for short-term evolution and local adaptation. To date, studies of spatiotemporal patterns of genetic variation in natural populations have been challenging, as comprehensive sampling is logistically difficult, and sequencing of entire populations costly. Here, we address these issues using a collaborative approach, sequencing 48 pooled population samples from 32 locations, and perform the first continent-wide genomic analysis of genetic variation in European Drosophila melanogaster. Our analyses uncover longitudinal population structure, provide evidence for continent-wide selective sweeps, identify candidate genes for local climate adaptation, and document clines in chromosomal inversion and transposable element frequencies. We also characterize variation among populations in the composition of the fly microbiome, and identify five new DNA viruses in our samples.

Modern diagnostic technologies for HIV

Novel diagnostic technologies, including nanotechnology, microfluidics, -omics science, next-generation sequencing, genomics big data, and machine learning, could contribute to meeting the UNAIDS 95-95-95 targets to end the HIV epidemic by 2030. Novel technologies include multiplexed technologies (including biomarker-based point-of-care tests and molecular platform technologies), biomarker-based combination antibody and antigen technologies, dried-blood-spot testing, and self-testing. Although biomarker-based rapid tests, in particular antibody-based tests, have dominated HIV diagnostics since the development of the first HIV test in the mid-1980s, targets such as nucleic acids and genes are now used in nanomedicine, biosensors, microfluidics, and -omics to enable early diagnosis of HIV. These novel technologies show promise as they are associated with ease of use, high diagnostic accuracy, rapid detection, and the ability to detect HIV-specific markers. Additional clinical and implementation research is needed to generate evidence for use of novel technologies and a public health approach will be required to address clinical and operational challenges to optimise their global deployment.

Evaluation of haplotype callers for next-generation sequencing of viruses

Currently, the standard practice for assembling next-generation sequencing (NGS) reads of viral genomes is to summarize thousands of individual short reads into a single consensus sequence, thus confounding useful intra-host diversity information for molecular phylodynamic inference. It is hypothesized that a few viral strains may dominate the intra-host genetic diversity with a variety of lower frequency strains comprising the rest of the population. Several software tools currently exist to convert NGS sequence variants into haplotypes. Previous benchmarks of viral haplotype reconstruction programs used simulation scenarios that are useful from a mathematical perspective but do not reflect viral evolution and epidemiology. Here, we tested twelve NGS haplotype reconstruction methods using viral populations simulated under realistic evolutionary dynamics. We simulated coalescent-based populations that spanned known levels of viral genetic diversity, including mutation rates, sample size and effective population size, to test the limits of the haplotype reconstruction methods and to ensure coverage of predicted intra-host viral diversity levels (especially HIV-1). All twelve investigated haplotype callers showed variable performance and produced drastically different results that were mainly driven by differences in mutation rate and, to a lesser extent, in effective population size. Most methods were able to accurately reconstruct haplotypes when genetic diversity was low. However, under higher levels of diversity (e.g., those seen intra-host HIV-1 infections), haplotype reconstruction quality was highly variable and, on average, poor. All haplotype reconstruction tools, except QuasiRecomb and ShoRAH, greatly underestimated intra-host diversity and the true number of haplotypes. PredictHaplo outperformed, in regard to highest precision, recall, and lowest UniFrac distance values, the other haplotype reconstruction tools followed by CliqueSNV, which, given more computational time, may have outperformed PredictHaplo. Here, we present an extensive comparison of available viral haplotype reconstruction tools and provide insights for future improvements in haplotype reconstruction tools using both short-read and long-read technologies.

HIV RNA Rebound in Seminal Plasma after Antiretroviral Treatment Interruption

If strategies currently in development succeed in eradicating HIV reservoirs in peripheral blood and lymphoid tissues, residual sources of virus may remain in anatomic compartments. Paired blood and semen samples were collected from 12 individuals enrolled in a randomized, double-blind, placebo-controlled therapeutic vaccine clinical trial in people with HIV (PWH) who began antiretroviral therapy (ART) during acute or early infection (ClinicalTrials registration no. NCT01859325). After the week 56 visit (postintervention), all participants interrupted ART. At the first available time points after viral rebound, we sequenced HIV-1 env (C2-V3), gag (p24), and pol (reverse transcriptase) regions amplified from cell-free HIV RNA in blood and seminal plasma using the MiSeq Illumina platform. Comprehensive sequence and phylogenetic analyses were performed to evaluate viral population structure, compartmentalization, and viral diversity in blood and seminal plasma. Compared to that in blood, HIV RNA rebound in semen occurred significantly later (median of 66 versus 42 days post-ART interruption, P < 0.01) and reached lower levels (median 164 versus 16,090 copies/ml, P < 0.01). Three of five participants with available sequencing data presented compartmentalized viral rebound between blood and semen in one HIV coding region. Despite early ART initiation, HIV RNA molecular diversity was higher in semen than in blood in all three coding regions for most participants. Higher HIV RNA molecular diversity in the genital tract (compared to that in blood plasma) and evidence of compartmentalization illustrate the distinct evolutionary dynamics between these two compartments after ART interruption. Future research should evaluate whether the genital compartment might contribute to viral rebound in some PWH interrupting ART.IMPORTANCE To cure HIV, we likely need to target the reservoirs in all anatomic compartments. Here, we used sophisticated statistical and phylogenetic methods to analyze blood and semen samples collected from 12 persons with HIV who began antiretroviral therapy (ART) during very early HIV infection and who interrupted their ART as part of a clinical trial. First, we found that HIV RNA rebound in semen occurred significantly later and reached lower levels than in blood. Second, we found that the virus in semen was genetically different in some participants compared to that in blood. Finally, we found increased HIV RNA molecular diversity in semen compared to that in blood in almost all study participants. These data suggest that the HIV RNA populations emerging from the genital compartment after ART interruption might not be the same as those emerging from blood plasma. Future research should evaluate whether the genital compartment might contribute to viral rebound in some people with HIV (PWH) interrupting ART.

Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses

Next-generation sequencing (NGS) offers a powerful opportunity to identify low-abundance, intra-host viral sequence variants, yet the focus of many bioinformatic tools on consensus sequence construction has precluded a thorough analysis of intra-host diversity. To take full advantage of the resolution of NGS data, we developed HAplotype PHylodynamics PIPEline (HAPHPIPE), an open-source tool for the de novo and reference-based assembly of viral NGS data, with both consensus sequence assembly and a focus on the quantification of intra-host variation through haplotype reconstruction. We validate and compare the consensus sequence assembly methods of HAPHPIPE to those of two alternative software packages, HyDRA and Geneious, using simulated HIV and empirical HIV, HCV, and SARS-CoV-2 datasets. Our validation methods included read mapping, genetic distance, and genetic diversity metrics. In simulated NGS data, HAPHPIPE generated pol consensus sequences significantly closer to the true consensus sequence than those produced by HyDRA and Geneious and performed comparably to Geneious for HIV gp120 sequences. Furthermore, using empirical data from multiple viruses, we demonstrate that HAPHPIPE can analyze larger sequence datasets due to its greater computational speed. Therefore, we contend that HAPHPIPE provides a more user-friendly platform for users with and without bioinformatics experience to implement current best practices for viral NGS assembly than other currently available options.

Quality Control of Next-Generation Sequencing-Based HIV-1 Drug Resistance Data in Clinical Laboratory Information Systems Framework

Next-generation sequencing (NGS) in HIV drug resistance (HIVDR) testing has the potential to improve both clinical and public health settings, however it challenges the normal operations of quality management systems to be more flexible due to its complexity, massive data generation, and rapidly evolving protocols. While guidelines for quality management in NGS data have previously been outlined, little guidance has been implemented for NGS-based HIVDR testing. This document summarizes quality control procedures for NGS-based HIVDR testing laboratories using a laboratory information systems (LIS) framework. Here, we focus in particular on the quality control measures applied on the final sequencing product aligned with the recommendations from the World Health Organization HIV Drug Resistance Laboratory Network.

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

In 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.

Drug Resistance Prediction Using Deep Learning Techniques on HIV-1 Sequence Data

The fast replication rate and lack of repair mechanisms of human immunodeficiency virus (HIV) contribute to its high mutation frequency, with some mutations resulting in the evolution of resistance to antiretroviral therapies (ART). As such, studying HIV drug resistance allows for real-time evaluation of evolutionary mechanisms. Characterizing the biological process of drug resistance is also critically important for sustained effectiveness of ART. Investigating the link between "black box" deep learning methods applied to this problem and evolutionary principles governing drug resistance has been overlooked to date. Here, we utilized publicly available HIV-1 sequence data and drug resistance assay results for 18 ART drugs to evaluate the performance of three architectures (multilayer perceptron, bidirectional recurrent neural network, and convolutional neural network) for drug resistance prediction, jointly with biological analysis. We identified convolutional neural networks as the best performing architecture and displayed a correspondence between the importance of biologically relevant features in the classifier and overall performance. Our results suggest that the high classification performance of deep learning models is indeed dependent on drug resistance mutations (DRMs). These models heavily weighted several features that are not known DRM locations, indicating the utility of model interpretability to address causal relationships in viral genotype-phenotype data.

Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants

The 1918 influenza pandemic is one of the most devastating infectious disease epidemics on record, having caused approximately 50 million deaths worldwide. Control measures, including prohibiting non-essential gatherings as well as closing cinemas and music halls, were applied with varying success and limited knowledge of transmission dynamics. One hundred years later, following developments in the field of mathematical epidemiology, models are increasingly used to guide decision-making and devise appropriate interventions that mitigate the impacts of epidemics. Epidemiological models have been used as decision-making tools during outbreaks in human, animal and plant populations. However, as the subject has developed, human, animal and plant disease modelling have diverged. Approaches have been developed independently for pathogens of each host type, often despite similarities between the models used in these complementary fields. With the increased importance of a One Health approach that unifies human, animal and plant health, we argue that more inter-disciplinary collaboration would enhance each of the related disciplines. This pair of theme issues presents research articles written by human, animal and plant disease modellers. In this introductory article, we compare the questions pertinent to, and approaches used by, epidemiological modellers of human, animal and plant pathogens, and summarize the articles in these theme issues. We encourage future collaboration that transcends disciplinary boundaries and links the closely related areas of human, animal and plant disease epidemic modelling. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

Drug Resistance Evolution in HIV in the Late 1990s: Hard Sweeps, Soft Sweeps, Clonal Interference and the Accumulation of Drug Resistance Mutations

The evolution of drug resistance in pathogens such as HIV is an important and widely known example in the field of evolutionary medicine. Here, we focus on a unique data set from the late 1990s with multiple viral sequences from multiple time points in 118 patients. We study patterns of evolutionary dynamics in the viral populations in these patients who were treated with Reverse Transcriptase Inhibitors and Protease Inhibitors in the late 1990s. Specifically, we aim to visualize and analyze examples of population genetic processes such as selective sweeps and clonal interference. The figures and descriptions in this paper can be used in evolution and population genetics classes. We show and analyze a wide variety of patterns, specifically: soft sweeps, hard sweeps, softening sweeps and hardening sweeps, simultaneous sweeps, accumulation of mutations and clonal interference.

Long-Acting Rilpivirine (RPV) Preexposure Prophylaxis Does Not Inhibit Vaginal Transmission of RPV-Resistant HIV-1 or Select for High-Frequency Drug Resistance in Humanized Mice

The antiretroviral drug rilpivirine was developed into a long-acting formulation (RPV LA) to improve adherence for preexposure prophylaxis (PrEP) to prevent HIV-1 transmission. A concern is that RPV LA will not inhibit transmission of drug-resistant HIV-1 and may select for drug-resistant virus. In female humanized mice, we found that RPV LA inhibited vaginal transmission of WT or 3-fold RPV-resistant HIV-1 but not virus with 30-fold RPV resistance. In animals that became infected despite RPV LA PrEP, WT HIV-1 dissemination was delayed until genital and plasma RPV concentrations waned. RPV resistance was detected at similar low frequencies in untreated and PrEP-treated mice that became infected. These results indicate the importance of maintaining RPV at a sustained threshold after virus exposure to prevent dissemination of HIV-1 after vaginal infection and low-frequency resistance mutations conferred low-level resistance, suggesting that RPV resistance is difficult to develop after HIV-1 infection during RPV LA PrEP.

As a long-acting formulation of the nonnucleoside reverse transcriptase inhibitor rilpivirine (RPV LA) has been proposed for use as preexposure prophylaxis (PrEP) and the prevalence of transmitted RPV-resistant viruses can be relatively high, we evaluated the efficacy of RPV LA to inhibit vaginal transmission of RPV-resistant HIV-1 in humanized mice. Vaginal challenges of wild-type (WT), Y181C, and Y181V HIV-1 were performed in mice left untreated or after RPV PrEP. Plasma viremia was measured for 7 to 10 weeks, and single-genome sequencing was performed on plasma HIV-1 RNA in mice infected during PrEP. RPV LA significantly prevented vaginal transmission of WT HIV-1 and Y181C HIV-1, which is 3-fold resistant to RPV. However, it did not prevent transmission of Y181V HIV-1, which has 30-fold RPV resistance in the viruses used for this study. RPV LA did delay WT HIV-1 dissemination in infected animals until genital and plasma RPV concentrations waned. Animals that became infected despite RPV LA PrEP did not acquire new RPV-resistant mutations above frequencies in untreated mice or untreated people living with HIV-1, and the mutations detected conferred low-level resistance. These data suggest that high, sustained concentrations of RPV were required to inhibit vaginal transmission of HIV-1 with little or no resistance to RPV but could not inhibit virus with high resistance. HIV-1 did not develop high-level or high-frequency RPV resistance in the majority of mice infected after RPV LA treatment. However, the impact of low-frequency RPV resistance on virologic outcome during subsequent antiretroviral therapy still is unclear.

IMPORTANCE The antiretroviral drug rilpivirine was developed into a long-acting formulation (RPV LA) to improve adherence for preexposure prophylaxis (PrEP) to prevent HIV-1 transmission. A concern is that RPV LA will not inhibit transmission of drug-resistant HIV-1 and may select for drug-resistant virus. In female humanized mice, we found that RPV LA inhibited vaginal transmission of WT or 3-fold RPV-resistant HIV-1 but not virus with 30-fold RPV resistance. In animals that became infected despite RPV LA PrEP, WT HIV-1 dissemination was delayed until genital and plasma RPV concentrations waned. RPV resistance was detected at similar low frequencies in untreated and PrEP-treated mice that became infected. These results indicate the importance of maintaining RPV at a sustained threshold after virus exposure to prevent dissemination of HIV-1 after vaginal infection and low-frequency resistance mutations conferred low-level resistance, suggesting that RPV resistance is difficult to develop after HIV-1 infection during RPV LA PrEP.

Linking influenza virus evolution within and between human hosts

Influenza viruses rapidly diversify within individual human infections. Several recent studies have deep-sequenced clinical influenza infections to identify viral variation within hosts, but it remains unclear how within-host mutations fare at the between-host scale. Here, we compare the genetic variation of H3N2 influenza within and between hosts to link viral evolutionary dynamics across scales. Synonymous sites evolve at similar rates at both scales, indicating that global evolution at these putatively neutral sites results from the accumulation of within-host variation. However, nonsynonymous mutations are depleted between hosts compared to within hosts, suggesting that selection purges many of the protein-altering changes that arise within hosts. The exception is at antigenic sites, where selection detectably favors nonsynonymous mutations at the global scale, but not within hosts. These results suggest that selection against deleterious mutations and selection for antigenic change are the main forces that act on within-host variants of influenza virus as they transmit and circulate between hosts.

A cross-sectional study to characterize local HIV-1 dynamics in Washington, DC using next-generation sequencing

Washington, DC continues to experience a generalized HIV-1 epidemic. We characterized the local phylodynamics of HIV-1 in DC using next-generation sequencing (NGS) data. Viral samples from 68 participants from 2016 through 2017 were sequenced and paired with epidemiological data. Phylogenetic and network inferences, drug resistant mutations (DRMs), subtypes and HIV-1 diversity estimations were completed. Haplotypes were reconstructed to infer transmission clusters. Phylodynamic inferences based on the HIV-1 polymerase (pol) and envelope genes (env) were compared. Higher HIV-1 diversity (n.s.) was seen in men who have sex with men, heterosexual, and male participants in DC. 54.0% of the participants contained at least one DRM. The 40-49 year-olds showed the highest prevalence of DRMs (22.9%). Phylogenetic analysis of pol and env sequences grouped 31.9-33.8% of the participants into clusters. HIV-TRACE grouped 2.9-12.8% of participants when using consensus sequences and 9.0-64.2% when using haplotypes. NGS allowed us to characterize the local phylodynamics of HIV-1 in DC more broadly and accurately, given a better representation of its diversity and dynamics. Reconstructed haplotypes provided novel and deeper phylodynamic insights, which led to networks linking a higher number of participants. Our understanding of the HIV-1 epidemic was expanded with the powerful coupling of HIV-1 NGS data with epidemiological data.

Evaluation of A Phylogenetic Pipeline to Examine Transmission Networks in A Canadian HIV Cohort

Keywords: HIV; Canada; molecular phylogenetics; viral evolution; person-to-person transmission inference; transmission network; summary statistics.

Deconvolving mutational patterns of poliovirus outbreaks reveals its intrinsic fitness landscape

Vaccination has essentially eradicated poliovirus. Yet, its mutation rate is higher than that of viruses like HIV, for which no effective vaccine exists. To investigate this, we infer a fitness model for the poliovirus viral protein 1 (vp1), which successfully predicts in vitro fitness measurements. This is achieved by first developing a probabilistic model for the prevalence of vp1 sequences that enables us to isolate and remove data that are subject to strong vaccine-derived biases. The intrinsic fitness constraints derived for vp1, a capsid protein subject to antibody responses, are compared with those of analogous HIV proteins. We find that vp1 evolution is subject to tighter constraints, limiting its ability to evade vaccine-induced immune responses. Our analysis also indicates that circulating poliovirus strains in unimmunized populations serve as a reservoir that can seed outbreaks in spatio-temporally localized sub-optimally immunized populations.

Poliovirus has a higher mutation rate than HIV, yet has been almost eradicated by vaccination while an effective vaccine against HIV does not exist. Here, the authors develop a fitness model for poliovirus viral protein 1 to show that it is subject to stringent evolutionary constraints that limit its ability to avoid vaccine-induced immune responses.

Robust Estimation of Recent Effective Population Size from Number of Independent Origins in Soft Sweeps

Estimating recent effective population size is of great importance in characterizing and predicting the evolution of natural populations. Methods based on nucleotide diversity may underestimate current day effective population sizes due to historical bottlenecks, whereas methods that reconstruct demographic history typically only detect long-term variations. However, soft selective sweeps, which leave a fingerprint of mutational history by recurrent mutations on independent haplotype backgrounds, holds promise of an estimate more representative of recent population history. Here, we present a simple and robust method of estimation based only on knowledge of the number of independent recurrent origins and the current frequency of the beneficial allele in a population sample, independent of the strength of selection and age of the mutation. Using a forward-time theoretical framework, we show the mean number of origins is a function of θ=2Nμ and current allele frequency, through a simple equation, and the distribution is approximately Poisson. This estimate is robust to whether mutants preexisted before selection arose and is equally accurate for diploid populations with incomplete dominance. For fast (e.g., seasonal) demographic changes compared with time scale for fixation of the mutant allele, and for moderate peak-to-trough ratios, we show our constant population size estimate can be used to bound the maximum and minimum population size. Applied to the Vgsc gene of Anopheles gambiae, we estimate an effective population size of roughly 6×107, and including seasonal demographic oscillations, a minimum effective population size >3×107, and a maximum <6×109, suggesting a mean ∼109.

Longitudinal within-host evolution of HIV Nef-mediated CD4, HLA and SERINC5 downregulation activity: a case study

The HIV accessory protein Nef downregulates the viral entry receptor CD4, the Human Leukocyte Antigen (HLA)-A and -B molecules, the Serine incorporator 5 (SERINC5) protein and other molecules from the infected cell surface, thereby promoting viral infectivity, replication and immune evasion. The nef locus also represents one of the most genetically variable regions in the HIV genome, and nef sequences undergo substantial evolution within a single individual over the course of infection. Few studies however have simultaneously characterized the impact of within-host nef sequence evolution on Nef protein function over prolonged timescales. Here, we isolated 50 unique Nef clones by single-genome amplification over an 11-year period from the plasma of an individual who was largely naïve to antiretroviral treatment during this time. Together, these clones harbored nonsynonymous substitutions at 13% of nef’s codons. We assessed their ability to downregulate cell-surface CD4, HLA and SERINC5 and observed that all three Nef functions declined modestly over time, where the reductions in CD4 and HLA downregulation (an average of 0.6% and 2.0% per year, respectively) achieved statistical significance. The results from this case study support all three Nef activities as being important to maintain throughout untreated HIV infection, but nevertheless suggest that, despite nef’s mutational plasticity, within-host viral evolution can compromise Nef function, albeit modestly, over prolonged periods.

Fierce Selection and Interference in B-Cell Repertoire Response to Chronic HIV-1

During chronic infection, HIV-1 engages in a rapid coevolutionary arms race with the host's adaptive immune system. While it is clear that HIV exerts strong selection on the adaptive immune system, the characteristics of the somatic evolution that shape the immune response are still unknown. Traditional population genetics methods fail to distinguish chronic immune response from healthy repertoire evolution. Here, we infer the evolutionary modes of B-cell repertoires and identify complex dynamics with a constant production of better B-cell receptor (BCR) mutants that compete, maintaining large clonal diversity and potentially slowing down adaptation. A substantial fraction of mutations that rise to high frequencies in pathogen-engaging CDRs of BCRs are beneficial, in contrast to many such changes in structurally relevant frameworks that are deleterious and circulate by hitchhiking. We identify a pattern where BCRs in patients who experience larger viral expansions undergo stronger selection with a rapid turnover of beneficial mutations due to clonal interference in their CDR3 regions. Using population genetics modeling, we show that the extinction of these beneficial mutations can be attributed to the rise of competing beneficial alleles and clonal interference. The picture is of a dynamic repertoire, where better clones may be outcompeted by new mutants before they fix.

Learning dynamical information from static protein and sequencing data

Many complex processes, from protein folding to neuronal network dynamics, can be described as stochastic exploration of a high-dimensional energy landscape. Although efficient algorithms for cluster detection in high-dimensional spaces have been developed over the last two decades, considerably less is known about the reliable inference of state transition dynamics in such settings. Here we introduce a flexible and robust numerical framework to infer Markovian transition networks directly from time-independent data sampled from stationary equilibrium distributions. We demonstrate the practical potential of the inference scheme by reconstructing the network dynamics for several protein-folding transitions, gene-regulatory network motifs, and HIV evolution pathways. The predicted network topologies and relative transition time scales agree well with direct estimates from time-dependent molecular dynamics data, stochastic simulations, and phylogenetic trees, respectively. Owing to its generic structure, the framework introduced here will be applicable to high-throughput RNA and protein-sequencing datasets, and future cryo-electron microscopy (cryo-EM) data.

Population Genetics in the Human Microbiome

While the human microbiome's structure and function have been extensively studied, its within-species genetic diversity is less well understood. However, genetic mutations in the microbiome can confer biomedically relevant traits, such as the ability to extract nutrients from food, metabolize drugs, evade antibiotics, and communicate with the host immune system. The population genetic processes by which these traits evolve are complex, in part due to interacting ecological and evolutionary forces in the microbiome. Advances in metagenomic sequencing, coupled with bioinformatics tools and population genetic models, facilitate quantification of microbiome genetic variation and inferences about how this diversity arises, evolves, and correlates with traits of both microbes and hosts. In this review, we explore the population genetic forces (mutation, recombination, drift, and selection) that shape microbiome genetic diversity within and between hosts, as well as efforts towards predictive models that leverage microbiome genetics.

High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast

In rapidly adapting asexual populations, including many microbial pathogens and viruses, numerous mutant lineages often compete for dominance within the population^1-5. These complex evolutionary dynamics determine the outcomes of adaptation, but have been difficult to observe directly. Previous studies have used whole-genome sequencing to follow molecular adaptation^6-10; however, these methods have limited resolution in microbial populations. Here we introduce a renewable barcoding system to observe evolutionary dynamics at high resolution in laboratory budding yeast. We find nested patterns of interference and hitchhiking even at low frequencies. These events are driven by the continuous appearance of new mutations that modify the fates of existing lineages before they reach substantial frequencies. We observe how the distribution of fitness within the population changes over time, and find a travelling wave of adaptation that has been predicted by theory^11-17. We show that clonal competition creates a dynamical 'rich-get-richer' effect: fitness advantages that are acquired early in evolution drive clonal expansions, which increase the chances of acquiring future mutations. However, less-fit lineages also routinely leapfrog over strains of higher fitness. Our results demonstrate that this combination of factors, which is not accounted for in existing models of evolutionary dynamics, is critical in determining the rate, predictability and molecular basis of adaptation.

Single genome sequencing of near full-length HIV-1 RNA using a limiting dilution approach

Sequencing very long stretches of the HIV-1 genome can advance studies on virus evolution and in vivo recombination but remains technically challenging. We developed an efficient procedure to sequence near full-length HIV-1 RNA using a two-amplicon approach. The whole genome was successfully amplified for 107 (88%) of 121 plasma samples including samples from patients infected with HIV-1 subtype A1, B, C, D, F1, G, H, CRF01_AE and CRF02_AG. For the 17 samples with a viral load below 1000 c/ml and the 104 samples with a viral load above 1000 c/ml, the amplification efficiency was respectively 53% and 94%. The sensitivity of the method was further evaluated using limiting dilution of RNA extracted from a plasma pool containing an equimolar mixture of three HIV-1 subtypes (B, C and CRF02_AG) and diluted before and after cDNA generation. Both RNA and cDNA dilution showed comparable sensitivity and equal accuracy in reflecting the subtype distribution of the plasma pool. One single event of in vitro recombination was detected amongst the 41 sequences obtained after cDNA dilution but no indications for in vitro recombination were found after RNA dilution. In conclusion, a two-amplicon strategy and limiting dilution of viral RNA followed by reverse transcription, nested PCR and Sanger sequencing, allows near full genome sequencing of individual HIV-1 RNA molecules. This method will be a valuable tool in the study of virus evolution and recombination.

HIV Diversity and Genetic Compartmentalization in Blood and Testes during Suppressive Antiretroviral Therapy

HIV's ability to persist during suppressive antiretroviral therapy is the main barrier to cure. Immune-privileged tissues, such as the testes, may constitute distinctive sites of HIV persistence, but this has been challenging to study in humans. We analyzed the proviral burden and genetics in the blood and testes of 10 individuals on suppressive therapy who underwent elective gender-affirming surgery. HIV DNA levels in matched blood and testes were quantified by quantitative PCR, and subgenomic proviral sequences (nef region) were characterized from single templates. HIV diversity, compartmentalization, and immune escape burden were assessed using genetic and phylogenetic approaches. Diverse proviruses were recovered from the blood (396 sequences; 354 nef-intact sequences) and testes (326 sequences; 309 nef-intact sequences) of all participants. Notably, the frequency of identical HIV sequences varied markedly between and within individuals. Nevertheless, proviral loads, within-host unique HIV sequence diversity, and the immune escape burden correlated positively between blood and testes. When all intact nef sequences were evaluated, 60% of participants exhibited significant blood-testis genetic compartmentalization, but none did so when the evaluation was restricted to unique sequences per site, suggesting that compartmentalization, when present, is attributable to the clonal expansion of HIV-infected cells. Our observations confirm the testes as a site of HIV persistence and suggest that individuals with larger and more diverse blood reservoirs will have larger and more diverse testis reservoirs. Furthermore, while the testis microenvironment may not be sufficiently unique to facilitate the seeding of unique viral populations therein, differential clonal expansion dynamics may be at play, which may complicate HIV eradication.IMPORTANCE Two key questions in HIV reservoir biology are whether immune-privileged tissues, such as the testes, harbor distinctive proviral populations during suppressive therapy and, if so, by what mechanism. While our results indicated that blood-testis HIV genetic compartmentalization was reasonably common (60%), it was always attributable to differential frequencies of identical HIV sequences between sites. No blood-tissue data set retained evidence of compartmentalization when only unique HIV sequences per site were considered; moreover, HIV immune escape mutation burdens were highly concordant between sites. We conclude that the principal mechanism by which blood and testis reservoirs differ is not via seeding of divergent HIV sequences therein but, rather, via differential clonal expansion of latently infected cells. Thus, while viral diversity and escape-related barriers to HIV eradication are of a broadly similar magnitude across the blood and testes, clonal expansion represents a challenge. The results support individualized analysis of within-host reservoir diversity to inform curative approaches.

Combining Viral Genetics and Statistical Modeling to Improve HIV-1 Time-of-infection Estimation towards Enhanced Vaccine Efficacy Assessment

Knowledge of the time of HIV-1 infection and the multiplicity of viruses that establish HIV-1 infection is crucial for the in-depth analysis of clinical prevention efficacy trial outcomes. Better estimation methods would improve the ability to characterize immunological and genetic sequence correlates of efficacy within preventive efficacy trials of HIV-1 vaccines and monoclonal antibodies. We developed new methods for infection timing and multiplicity estimation using maximum likelihood estimators that shift and scale (calibrate) estimates by fitting true infection times and founder virus multiplicities to a linear regression model with independent variables defined by data on HIV-1 sequences, viral load, diagnostics, and sequence alignment statistics. Using Poisson models of measured mutation counts and phylogenetic trees, we analyzed longitudinal HIV-1 sequence data together with diagnostic and viral load data from the RV217 and CAPRISA 002 acute HIV-1 infection cohort studies. We used leave-one-out cross validation to evaluate the prediction error of these calibrated estimators versus that of existing estimators and found that both infection time and founder multiplicity can be estimated with improved accuracy and precision by calibration. Calibration considerably improved all estimators of time since HIV-1 infection, in terms of reducing bias to near zero and reducing root mean squared error (RMSE) to 5-10 days for sequences collected 1-2 months after infection. The calibration of multiplicity assessments yielded strong improvements with accurate predictions (ROC-AUC above 0.85) in all cases. These results have not yet been validated on external data, and the best-fitting models are likely to be less robust than simpler models to variation in sequencing conditions. For all evaluated models, these results demonstrate the value of calibration for improved estimation of founder multiplicity and of time since HIV-1 infection.

Herpes simplex virus-2 dynamics as a probe to measure the extremely rapid and spatially localized tissue-resident T-cell response

Herpes simplex virus-2 infection is characterized by frequent episodic shedding in the genital tract. Expansion in HSV-2 viral load early during episodes is extremely rapid. However, the virus invariably peaks within 18 hours and is eliminated nearly as quickly. A critical feature of HSV-2 shedding episodes is their heterogeneity. Some episodes peak at 10⁸ HSV DNA copies, last for weeks due to frequent viral re-expansion, and lead to painful ulcers, while others only reach 10³ HSV DNA copies and are eliminated within hours and without symptoms. Within single micro-environments of infection, tissue-resident CD8+ T cells (T_RM ) appear to contain infection within a few days. Here, we review components of T_RM biology relevant to immune surveillance between HSV-2 shedding episodes and containment of infection upon detection of HSV-2 cognate antigen. We then describe the use of mathematical models to correlate large spatial gradients in T_RM density with the heterogeneity of observed shedding within a single person. We describe how models have been leveraged for clinical trial simulation, as well as future plans to model the interactions of multiple cellular subtypes within mucosa, predict the mechanism of action of therapeutic vaccines, and describe the dynamics of 3-dimensional infection environment during the natural evolution of an HSV-2 lesion.

Reduced frequency of HIV superinfection in a high-risk cohort in Zambia

Rates of HIV-1 superinfection, re-infection with a genetically distinct virus despite HIV-1 specific immune responses, vary in different risk populations. We previously found the rates of superinfection were similar to primary HIV infection (PHI) in a Zambian heterosexual transmission cohort. Here, we conduct a similar analysis of 47 HIV-positive Zambians from an acute infection cohort with more frequent follow-up, all infected by non-spousal partners. We identified only one case of superinfection in the first two years, significantly fewer than in our previous study, which was likely due to increased counseling during acute infection and an overall population-wide decline in factors associated with HIV transmission. The predominant virus detected after superinfection was a recombinant of the transmitted founder (TF) and the superinfecting strain. The superinfected individual mounted a neutralizing antibody response to the primary TF virus, which remained TF-specific over time and even after superinfection, did not neutralize the superinfecting variant.

Intra- and interpatient evolution of enterovirus D68 analyzed by whole-genome deep sequencing

Worldwide outbreaks of enterovirus D68 (EV-D68) in 2014 and 2016 have caused serious respiratory and neurological disease. To investigate diversity, spread, and evolution of EV-D68 we performed near full-length deep sequencing in fifty-four samples obtained in Sweden during the 2014 and 2016 outbreaks. In most samples, intrapatient variability was low and dominated by rare synonymous variants, but three patients showed evidence of dual infections with distinct EV-D68 variants from the same subclade. Interpatient evolution showed a very strong temporal signal, with an evolutionary rate of 0.0039 ± 0.0001 substitutions per site and year. Phylogenetic trees reconstructed from the sequences suggest that EV-D68 was introduced into Stockholm several times during the 2016 outbreak. Putative neutralization targets in the BC and DE loops of the VP1 protein were slightly more diverse within-host and tended to undergo more frequent substitution than other genomic regions. However, evolution in these loops did not appear to have been driven the emergence of the 2016 B3-subclade directly from the 2014 B1-subclade. Instead, the most recent ancestor of both clades was dated to 2009. The study provides a comprehensive description of the intra- and interpatient evolution of EV-D68, including the first report of intrapatient diversity and dual infections. The new data along with publicly available EV-D68 sequences are included in an interactive phylodynamic analysis on nextstrain.org/enterovirus/d68 to facilitate timely EV-D68 tracking in the future.

Experimental Evolution of Extreme Resistance to Ionizing Radiation in Escherichia coli after 50 Cycles of Selection

In previous work (D. R. Harris et al., J Bacteriol 191:5240-5252, 2009, https://doi.org/10.1128/JB.00502-09; B. T. Byrne et al., Elife 3:e01322, 2014, https://doi.org/10.7554/eLife.01322), we demonstrated that Escherichia coli could acquire substantial levels of resistance to ionizing radiation (IR) via directed evolution. Major phenotypic contributions involved adaptation of organic systems for DNA repair. We have now undertaken an extended effort to generate E. coli populations that are as resistant to IR as Deinococcus radiodurans After an initial 50 cycles of selection using high-energy electron beam IR, four replicate populations exhibit major increases in IR resistance but have not yet reached IR resistance equivalent to D. radiodurans Regular deep sequencing reveals complex evolutionary patterns with abundant clonal interference. Prominent IR resistance mechanisms involve novel adaptations to DNA repair systems and alterations in RNA polymerase. Adaptation is highly specialized to resist IR exposure, since isolates from the evolved populations exhibit highly variable patterns of resistance to other forms of DNA damage. Sequenced isolates from the populations possess between 184 and 280 mutations. IR resistance in one isolate, IR9-50-1, is derived largely from four novel mutations affecting DNA and RNA metabolism: RecD A90E, RecN K429Q, and RpoB S72N/RpoC K1172I. Additional mechanisms of IR resistance are evident.IMPORTANCE Some bacterial species exhibit astonishing resistance to ionizing radiation, with Deinococcus radiodurans being the archetype. As natural IR sources rarely exceed mGy levels, the capacity of Deinococcus to survive 5,000 Gy has been attributed to desiccation resistance. To understand the molecular basis of true extreme IR resistance, we are using experimental evolution to generate strains of Escherichia coli with IR resistance levels comparable to Deinococcus Experimental evolution has previously generated moderate radioresistance for multiple bacterial species. However, these efforts could not take advantage of modern genomic sequencing technologies. In this report, we examine four replicate bacterial populations after 50 selection cycles. Genomic sequencing allows us to follow the genesis of mutations in populations throughout selection. Novel mutations affecting genes encoding DNA repair proteins and RNA polymerase enhance radioresistance. However, more contributors are apparent.

HIV Subtype and Nef-Mediated Immune Evasion Function Correlate with Viral Reservoir Size in Early-Treated Individuals

The HIV accessory protein Nef modulates key immune evasion and pathogenic functions, and its encoding gene region exhibits high sequence diversity. Given the recent identification of early HIV-specific adaptive immune responses as novel correlates of HIV reservoir size, we hypothesized that viral factors that facilitate the evasion of such responses-namely, Nef genetic and functional diversity-might also influence reservoir establishment and/or persistence. We isolated baseline plasma HIV RNA-derived nef clones from 30 acute/early-infected individuals who participated in a clinical trial of early combination antiretroviral therapy (cART) (<6 months following infection) and assessed each Nef clone's ability to downregulate CD4 and human leukocyte antigen (HLA) class I in vitro We then explored the relationships between baseline clinical, immunological, and virological characteristics and the HIV reservoir size measured 48 weeks following initiation of suppressive cART (where the reservoir size was quantified in terms of the proviral DNA loads as well as the levels of replication-competent HIV in CD4⁺ T cells). Maximal within-host Nef-mediated downregulation of HLA, but not CD4, correlated positively with post-cART proviral DNA levels (Spearman's R = 0.61, P = 0.0004) and replication-competent reservoir sizes (Spearman's R = 0.36, P = 0.056) in univariable analyses. Furthermore, the Nef-mediated HLA downregulation function was retained in final multivariable models adjusting for established clinical and immunological correlates of reservoir size. Finally, HIV subtype B-infected persons (n = 25) harbored significantly larger viral reservoirs than non-subtype B-infected persons (2 infected with subtype CRF01_AE and 3 infected with subtype G). Our results highlight a potentially important role of viral factors-in particular, HIV subtype and accessory protein function-in modulating viral reservoir establishment and persistence.IMPORTANCE While combination antiretroviral therapies (cART) have transformed HIV infection into a chronic manageable condition, they do not act upon the latent HIV reservoir and are therefore not curative. As HIV cure or remission should be more readily achievable in individuals with smaller HIV reservoirs, achieving a deeper understanding of the clinical, immunological, and virological determinants of reservoir size is critical to eradication efforts. We performed a post hoc analysis of 30 participants of a clinical trial of early cART who had previously been assessed in detail for their clinical, immunological, and reservoir size characteristics. We observed that the HIV subtype and autologous Nef-mediated HLA downregulation function correlated with the viral reservoir size measured approximately 1 year post-cART initiation. Our findings highlight virological characteristics-both genetic and functional-as possible novel determinants of HIV reservoir establishment and persistence.

Towards multiscale modeling of the CD8+ T cell response to viral infections

The CD8⁺ T cell response is critical to the control of viral infections. Yet, defining the CD8⁺ T cell response to viral infections quantitatively has been a challenge. Following antigen recognition, which triggers an intracellular signaling cascade, CD8⁺ T cells can differentiate into effector cells, which proliferate rapidly and destroy infected cells. When the infection is cleared, they leave behind memory cells for quick recall following a second challenge. If the infection persists, the cells may become exhausted, retaining minimal control of the infection while preventing severe immunopathology. These activation, proliferation and differentiation processes as well as the mounting of the effector response are intrinsically multiscale and collective phenomena. Remarkable experimental advances in the recent years, especially at the single cell level, have enabled a quantitative characterization of several underlying processes. Simultaneously, sophisticated mathematical models have begun to be constructed that describe these multiscale phenomena, bringing us closer to a comprehensive description of the CD8⁺ T cell response to viral infections. Here, we review the advances made and summarize the challenges and opportunities ahead. This article is categorized under: Analytical and Computational Methods > Computational Methods Biological Mechanisms > Cell Fates Biological Mechanisms > Cell Signaling Models of Systems Properties and Processes > Mechanistic Models.

Link between the numbers of particles and variants founding new HIV-1 infections depends on the timing of transmission

Understanding which HIV-1 variants are most likely to be transmitted is important for vaccine design and predicting virus evolution. Since most infections are founded by single variants, it has been suggested that selection at transmission has a key role in governing which variants are transmitted. We show that the composition of the viral population within the donor at the time of transmission is also important. To support this argument, we developed a probabilistic model describing HIV-1 transmission in an untreated population, and parameterised the model using both within-host next generation sequencing data and population-level epidemiological data on heterosexual transmission. The most basic HIV-1 transmission models cannot explain simultaneously the low probability of transmission and the non-negligible proportion of infections founded by multiple variants. In our model, transmission can only occur when environmental conditions are appropriate (e.g. abrasions are present in the genital tract of the potential recipient), allowing these observations to be reconciled. As well as reproducing features of transmission in real populations, our model demonstrates that, contrary to expectation, there is not a simple link between the number of viral variants and the number of viral particles founding each new infection. These quantities depend on the timing of transmission, and infections can be founded with small numbers of variants yet large numbers of particles. Including selection, or a bias towards early transmission (e.g. due to treatment), acts to enhance this conclusion. In addition, we find that infections initiated by multiple variants are most likely to have derived from donors with intermediate set-point viral loads, and not from individuals with high set-point viral loads as might be expected. We therefore emphasise the importance of considering viral diversity in donors, and the timings of transmissions, when trying to discern the complex factors governing single or multiple variant transmission.

Signatures of selection in the human antibody repertoire: Selective sweeps, competing subclones, and neutral drift

Antibodies are created and refined by somatic evolution in B cell populations, which endows the human immune system with the ability to recognize and eliminate diverse pathogens. However, the evolutionary processes that sculpt antibody repertoires remain poorly understood. Here, using an unbiased repertoire-scale approach, we show that the population genetic signatures of evolution are evident in human B cell lineages and reveal how antibodies evolve somatically. We measured the dynamics and genetic diversity of B cell responses in five adults longitudinally before and after influenza vaccination using high-throughput antibody repertoire sequencing. We identified vaccine-responsive B cell lineages that carry signatures of selective sweeps driven by positive selection, and discovered that they often display evidence for selective sweeps favoring multiple subclones. We also found persistent B cell lineages that exhibit stable population dynamics and carry signatures of neutral drift. By exploiting the relationship between B cell fitness and antibody binding affinity, we demonstrate the potential for using phylogenetic approaches to identify antibodies with high binding affinity. This quantitative characterization reveals that antibody repertoires are shaped by an unexpectedly broad spectrum of evolutionary processes and shows how signatures of evolutionary history can be harnessed for antibody discovery and engineering.

An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar

How viruses evolve within hosts can dictate infection outcomes; however, reconstructing this process is challenging. We evaluate our multiplexed amplicon approach, PrimalSeq, to demonstrate how virus concentration, sequencing coverage, primer mismatches, and replicates influence the accuracy of measuring intrahost virus diversity. We develop an experimental protocol and computational tool, iVar, for using PrimalSeq to measure virus diversity using Illumina and compare the results to Oxford Nanopore sequencing. We demonstrate the utility of PrimalSeq by measuring Zika and West Nile virus diversity from varied sample types and show that the accumulation of genetic diversity is influenced by experimental and biological systems.

Evolutionary dynamics of bacteria in the gut microbiome within and across hosts

Gut microbiota are shaped by a combination of ecological and evolutionary forces. While the ecological dynamics have been extensively studied, much less is known about how species of gut bacteria evolve over time. Here, we introduce a model-based framework for quantifying evolutionary dynamics within and across hosts using a panel of metagenomic samples. We use this approach to study evolution in approximately 40 prevalent species in the human gut. Although the patterns of between-host diversity are consistent with quasi-sexual evolution and purifying selection on long timescales, we identify new genealogical signatures that challenge standard population genetic models of these processes. Within hosts, we find that genetic differences that accumulate over 6-month timescales are only rarely attributable to replacement by distantly related strains. Instead, the resident strains more commonly acquire a smaller number of putative evolutionary changes, in which nucleotide variants or gene gains or losses rapidly sweep to high frequency. By comparing these mutations with the typical between-host differences, we find evidence that some sweeps may be seeded by recombination, in addition to new mutations. However, comparisons of adult twins suggest that replacement eventually overwhelms evolution over multi-decade timescales, hinting at fundamental limits to the extent of local adaptation. Together, our results suggest that gut bacteria can evolve on human-relevant timescales, and they highlight the connections between these short-term evolutionary dynamics and longer-term evolution across hosts.

Measurements of intrahost viral diversity require an unbiased diversity metric

Viruses exist within hosts at large population sizes and are subject to high rates of mutation. As such, viral populations exhibit considerable sequence diversity. A variety of summary statistics have been developed which describe, in a single number, the extent of diversity in a viral population; such measurements allow the diversities of different populations to be compared, and the effect of evolutionary forces on a population to be assessed. Here we highlight statistical artefacts underlying some common measures of sequence diversity, whereby variation in the depth of genome sequencing may substantially affect the extent of diversity measured in a viral population, making comparisons of population diversity invalid. Specifically, naive estimation of sequence entropy provides a systematically biased metric, a lower read depth being expected to produce a lower estimate of diversity. The number of polymorphic loci per kilobase of genome is more unpredictably affected by read depth, giving potentially flawed results at lower sequencing depths. We show that the nucleotide diversity statistic π provides an unbiased estimate of diversity in the sense that the expected value of the statistic is equal to the correct value of the property being measured. Our results are of importance for studies interpreting genome sequence data; we describe how diversity may be assessed in viral populations in a fair and unbiased manner.

Inferring population genetics parameters of evolving viruses using time-series data

With the advent of deep sequencing techniques, it is now possible to track the evolution of viruses with ever-increasing detail. Here, we present Flexible Inference from Time-Series (FITS)-a computational tool that allows inference of one of three parameters: the fitness of a specific mutation, the mutation rate or the population size from genomic time-series sequencing data. FITS was designed first and foremost for analysis of either short-term Evolve & Resequence (E&R) experiments or rapidly recombining populations of viruses. We thoroughly explore the performance of FITS on simulated data and highlight its ability to infer the fitness/mutation rate/population size. We further show that FITS can infer meaningful information even when the input parameters are inexact. In particular, FITS is able to successfully categorize a mutation as advantageous or deleterious. We next apply FITS to empirical data from an E&R experiment on poliovirus where parameters were determined experimentally and demonstrate high accuracy in inference.

Virus-inclusive single-cell RNA sequencing reveals the molecular signature of progression to severe dengue

A fraction of the 400 million people infected with dengue annually progresses to severe dengue (SD). Yet, there are currently no biomarkers to predict disease progression. We profiled the landscape of host transcripts and viral RNA in thousands of single blood cells from dengue patients prior to progressing to SD. We discovered cell type-specific immune activation and candidate predictive biomarkers. We also determined preferential virus association with specific cell populations, particularly naive B cells and monocytes. We explored immune activation of bystander cells, clonality and somatic evolution of adaptive immune repertoires, as well as viral genomics. This multifaceted approach could advance understanding of pathogenesis of any viral infection, map an atlas of infected cells, and promote the development of prognostics.

Dengue virus (DENV) infection can result in severe complications. However, the understanding of the molecular correlates of severity is limited, partly due to difficulties in defining the peripheral blood mononuclear cells (PBMCs) that contain DENV RNA in vivo. Accordingly, there are currently no biomarkers predictive of progression to severe dengue (SD). Bulk transcriptomics data are difficult to interpret because blood consists of multiple cell types that may react differently to infection. Here, we applied virus-inclusive single-cell RNA-seq approach (viscRNA-Seq) to profile transcriptomes of thousands of single PBMCs derived early in the course of disease from six dengue patients and four healthy controls and to characterize distinct leukocyte subtypes that harbor viral RNA (vRNA). Multiple IFN response genes, particularly MX2 in naive B cells and CD163 in CD14⁺ CD16⁺ monocytes, were up-regulated in a cell-specific manner before progression to SD. The majority of vRNA-containing cells in the blood of two patients who progressed to SD were naive IgM B cells expressing the CD69 and CXCR4 receptors and various antiviral genes, followed by monocytes. Bystander, non-vRNA–containing B cells also demonstrated immune activation, and IgG1 plasmablasts from two patients exhibited clonal expansions. Lastly, assembly of the DENV genome sequence revealed diversity at unexpected sites. This study presents a multifaceted molecular elucidation of natural dengue infection in humans with implications for any tissue and viral infection and proposes candidate biomarkers for prediction of SD.

Maintenance and reappearance of extremely divergent intra-host HIV-1 variants

Understanding genetic variation in human immunodeficiency virus (HIV) is clinically and immunologically important for patient treatment and vaccine development. We investigated the longitudinal intra-host genetic variation of HIV in over 3,000 individuals in the US National HIV Surveillance System with at least four reported HIV-1 polymerase (pol) sequences. In this population, we identified 149 putative instances of superinfection (i.e. an individual sequentially infected with genetically divergent, polyphyletic viruses). Unexpectedly, we discovered a group of 240 individuals with consecutively sampled viral strains that were >0.015 substitutions/site divergent, despite remaining monophyletic in the phylogeny. Viruses in some of these individuals had a maximum genetic divergence approaching that found between two random, unrelated HIV-1 subtype-B pol sequences within the US population. Individuals with these highly divergent viruses tended to be diagnosed nearly a decade earlier in the epidemic than people with superinfection or virus with less intra-host genetic variation, and they had distinct transmission risk factor profiles. To better understand this genetic variation in cases with extremely divergent, monophyletic viruses, we performed molecular clock phylogenetic analysis. Our findings suggest that, like Hepatitis C virus, extremely divergent HIV lineages can be maintained within an individual and reemerge over a period of years.