Quantifying selection against synonymous mutations in HIV-1 env evolution

Mutation rate, selection, and epistasis inferred from RNA virus haplotypes via neural posterior estimation

RNA viruses are particularly notorious for their high levels of genetic diversity, which is generated through the forces of mutation and natural selection. However, disentangling these two forces is a considerable challenge, and this may lead to widely divergent estimates of viral mutation rates, as well as difficulties in inferring the fitness effects of mutations. Here, we develop, test, and apply an approach aimed at inferring the mutation rate and key parameters that govern natural selection, from haplotype sequences covering full-length genomes of an evolving virus population. Our approach employs neural posterior estimation, a computational technique that applies simulation-based inference with neural networks to jointly infer multiple model parameters. We first tested our approach on synthetic data simulated using different mutation rates and selection parameters while accounting for sequencing errors. Reassuringly, the inferred parameter estimates were accurate and unbiased. We then applied our approach to haplotype sequencing data from a serial passaging experiment with the MS2 bacteriophage, a virus that parasites Escherichia coli. We estimated that the mutation rate of this phage is around 0.2 mutations per genome per replication cycle (95% highest density interval: 0.051-0.56). We validated this finding with two different approaches based on single-locus models that gave similar estimates but with much broader posterior distributions. Furthermore, we found evidence for reciprocal sign epistasis between four strongly beneficial mutations that all reside in an RNA stem loop that controls the expression of the viral lysis protein, responsible for lysing host cells and viral egress. We surmise that there is a fine balance between over- and underexpression of lysis that leads to this pattern of epistasis. To recap, we have developed an approach for joint inference of the mutation rate and selection parameters from full haplotype data with sequencing errors and used it to reveal features governing MS2 evolution.

Reversions to consensus are positively selected in HIV-1 and bias substitution rate estimates

Human immunodeficiency virus 1 (HIV-1) is a rapidly evolving virus able to evade host immunity through rapid adaptation during chronic infection. The HIV-1 group M has diversified since its zoonosis into several subtypes at a rate of the order of 10^-3 changes per site per year. This rate varies between different parts of the genome, and its inference is sensitive to the timescale and diversity spanned by the sequence data used. Higher rates are estimated on short timescales and particularly for within-host evolution, while rate estimates spanning decades or the entire HIV-1 pandemic tend to be lower. The underlying causes of this difference are not well understood. We investigate here the role of rapid reversions toward a preferred evolutionary sequence state on multiple timescales. We show that within-host reversion mutations are under positive selection and contribute substantially to sequence turnover, especially at conserved sites. We then use the rates of reversions and non-reversions estimated from longitudinal within-host data to parameterize a phylogenetic sequence evolution model. Sequence simulation of this model on HIV-1 phylogenies reproduces diversity and apparent evolutionary rates of HIV-1 in gag and pol, suggesting that a tendency to rapidly revert to a consensus-like state can explain much of the time dependence of evolutionary rate estimates in HIV-1.

Innate immune pathways act synergistically to constrain RNA virus evolution in Drosophila melanogaster

Host-pathogen interactions impose recurrent selective pressures that lead to constant adaptation and counter-adaptation in both competing species. Here, we sought to study this evolutionary arms-race and assessed the impact of the innate immune system on viral population diversity and evolution, using Drosophila melanogaster as model host and its natural pathogen Drosophila C virus (DCV). We isogenized eight fly genotypes generating animals defective for RNAi, Imd and Toll innate immune pathways as well as pathogen-sensing and gut renewal pathways. Wild-type or mutant flies were then orally infected with DCV and the virus was serially passaged ten times via reinfection in naive flies. Viral population diversity was studied after each viral passage by high-throughput sequencing and infection phenotypes were assessed at the beginning and at the end of the evolution experiment. We found that the absence of any of the various immune pathways studied increased viral genetic diversity while attenuating virulence. Strikingly, these effects were observed in a range of host factors described as having mainly antiviral or antibacterial functions. Together, our results indicate that the innate immune system as a whole and not specific antiviral defence pathways in isolation, generally constrains viral diversity and evolution.

Mutation rate of SARS-CoV-2 and emergence of mutators during experimental evolution

Background and objectives

To understand how organisms evolve, it is fundamental to study how mutations emerge and establish. Here, we estimated the rate of mutation accumulation of SARS-CoV-2 in vitro and investigated the repeatability of its evolution when facing a new cell type but no immune or drug pressures.

Methodology

We performed experimental evolution with two strains of SARS-CoV-2, one carrying the originally described spike protein (CoV-2-D) and another carrying the D614G mutation that has spread worldwide (CoV-2-G). After 15 passages in Vero cells and whole genome sequencing, we characterized the spectrum and rate of the emerging mutations and looked for evidences of selection across the genomes of both strains.

Results

From the frequencies of the mutations accumulated, and excluding the genes with signals of selection, we estimate a spontaneous mutation rate of 1.3 × 10 ^-6 ± 0.2 × 10^-6 per-base per-infection cycle (mean across both lineages of SARS-CoV-2 ± 2SEM). We further show that mutation accumulation is larger in the CoV-2-D lineage and heterogeneous along the genome, consistent with the action of positive selection on the spike protein, which accumulated five times more mutations than the corresponding genomic average. We also observe the emergence of mutators in the CoV-2-G background, likely linked to mutations in the RNA-dependent RNA polymerase and/or in the error-correcting exonuclease protein.

Conclusions and implications

These results provide valuable information on how spontaneous mutations emerge in SARS-CoV-2 and on how selection can shape its genome toward adaptation to new environments. Lay Summary: Each time a virus replicates inside a cell, errors (mutations) occur. Here, via laboratory propagation in cells originally isolated from the kidney epithelium of African green monkeys, we estimated the rate at which the SARS-CoV-2 virus mutates-an important parameter for understanding how it can evolve within and across humans. We also confirm the potential of its Spike protein to adapt to a new environment and report the emergence of mutators-viral populations where mutations occur at a significantly faster rate.

Inference of population genetic parameters from an irregular time series of seasonal influenza virus sequences

Basic summary statistics that quantify the population genetic structure of influenza virus are important for understanding and inferring the evolutionary and epidemiological processes. However, the sampling dates of global virus sequences in the last several decades are scattered nonuniformly throughout the calendar. Such temporal structure of samples and the small effective size of viral population hampers the use of conventional methods to calculate summary statistics. Here, we define statistics that overcome this problem by correcting for the sampling-time difference in quantifying a pairwise sequence difference. A simple linear regression method jointly estimates the mutation rate and the level of sequence polymorphism, thus providing an estimate of the effective population size. It also leads to the definition of Wright's FST for arbitrary time-series data. Furthermore, as an alternative to Tajima's D statistic or the site-frequency spectrum, a mismatch distribution corrected for sampling-time differences can be obtained and compared between actual and simulated data. Application of these methods to seasonal influenza A/H3N2 viruses sampled between 1980 and 2017 and sequences simulated under the model of recurrent positive selection with metapopulation dynamics allowed us to estimate the synonymous mutation rate and find parameter values for selection and demographic structure that fit the observation. We found that the mutation rates of HA and PB1 segments before 2007 were particularly high and that including recurrent positive selection in our model was essential for the genealogical structure of the HA segment. Methods developed here can be generally applied to population genetic inferences using serially sampled genetic data.

MrHAMER yields highly accurate single molecule viral sequences enabling analysis of intra-host evolution

Technical challenges remain in the sequencing of RNA viruses due to their high intra-host diversity. This bottleneck is particularly pronounced when interrogating long-range co-evolved genetic interactions given the read-length limitations of next-generation sequencing platforms. This has hampered the direct observation of these genetic interactions that code for protein-protein interfaces with relevance in both drug and vaccine development. Here we overcome these technical limitations by developing a nanopore-based long-range viral sequencing pipeline that yields accurate single molecule sequences of circulating virions from clinical samples. We demonstrate its utility in observing the evolution of individual HIV Gag-Pol genomes in response to antiviral pressure. Our pipeline, called Multi-read Hairpin Mediated Error-correction Reaction (MrHAMER), yields >1000s of viral genomes per sample at 99.9% accuracy, maintains the original proportion of sequenced virions present in a complex mixture, and allows the detection of rare viral genomes with their associated mutations present at <1% frequency. This method facilitates scalable investigation of genetic correlates of resistance to both antiviral therapy and immune pressure and enables the identification of novel host-viral and viral-viral interfaces that can be modulated for therapeutic benefit.

Comprehensive analysis of genomic diversity of SARS-CoV-2 in different geographic regions of India: an endeavour to classify Indian SARS-CoV-2 strains on the basis of co-existing mutations

Accumulation of mutations within the genome is the primary driving force in viral evolution within an endemic setting. This inherent feature often leads to altered virulence, infectivity and transmissibility, and antigenic shifts to escape host immunity, which might compromise the efficacy of vaccines and antiviral drugs. Therefore, we carried out a genome-wide analysis of circulating SARS-CoV-2 strains to detect the emergence of novel co-existing mutations and trace their geographical distribution within India. Comprehensive analysis of whole genome sequences of 837 Indian SARS-CoV-2 strains revealed the occurrence of 33 different mutations, 18 of which were unique to India. Novel mutations were observed in the S glycoprotein (6/33), NSP3 (5/33), RdRp/NSP12 (4/33), NSP2 (2/33), and N (1/33). Non-synonymous mutations were found to be 3.07 times more prevalent than synonymous mutations. We classified the Indian isolates into 22 groups based on their co-existing mutations. Phylogenetic analysis revealed that the representative strains of each group were divided into various sub-clades within their respective clades, based on the presence of unique co-existing mutations. The A2a clade was found to be dominant in India (71.34%), followed by A3 (23.29%) and B (5.36%), but a heterogeneous distribution was observed among various geographical regions. The A2a clade was highly predominant in East India, Western India, and Central India, whereas the A2a and A3 clades were nearly equal in prevalence in South and North India. This study highlights the divergent evolution of SARS-CoV-2 strains and co-circulation of multiple clades in India. Monitoring of the emerging mutations will pave the way for vaccine formulation and the design of antiviral drugs.

Long-term experimental evolution of HIV-1 reveals effects of environment and mutational history

An often-returning question for not only HIV-1, but also other organisms, is how predictable evolutionary paths are. The environment, mutational history, and random processes can all impact the exact evolutionary paths, but to which extent these factors contribute to the evolutionary dynamics of a particular system is an open question. Especially in a virus like HIV-1, with a large mutation rate and large population sizes, evolution is expected to be highly predictable if the impact of environment and history is low, and evolution is not neutral. We investigated the effect of environment and mutational history by analyzing sequences from a long-term evolution experiment, in which HIV-1 was passaged on 2 different cell types in 8 independent evolutionary lines and 8 derived lines, 4 of which involved a switch of the environment. The experiments lasted for 240–300 passages, corresponding to approximately 400–600 generations or almost 3 years. The sequences show signs of extensive parallel evolution—the majority of mutations that are shared between independent lines appear in both cell types, but we also find that both environment and mutational history significantly impact the evolutionary paths. We conclude that HIV-1 evolution is robust to small changes in the environment, similar to a transmission event in the absence of an immune response or drug pressure. We also find that the fitness landscape of HIV-1 is largely smooth, although we find some evidence for both positive and negative epistatic interactions between mutations.

Analysis of the longest evolutionary experiment with HIV-1 to-date reveals continuous viral adaptation over several years. The authors quantify the environment-specific mutations that arise and determine the fraction of mutations that co-occur with significantly different frequencies than expected by chance.

Assessing Genome-Wide Diversity in European Hantaviruses through Sequence Capture from Natural Host Samples

Research on the ecology and evolution of viruses is often hampered by the limitation of sequence information to short parts of the genomes or single genomes derived from cultures. In this study, we use hybrid sequence capture enrichment in combination with high-throughput sequencing to provide efficient access to full genomes of European hantaviruses from rodent samples obtained in the field. We applied this methodology to Tula (TULV) and Puumala (PUUV) orthohantaviruses for which analyses from natural host samples are typically restricted to partial sequences of their tri-segmented RNA genome. We assembled a total of ten novel hantavirus genomes de novo with very high coverage (on average >99%) and sequencing depth (average >247×). A comparison with partial Sanger sequences indicated an accuracy of >99.9% for the assemblies. An analysis of two common vole (Microtus arvalis) samples infected with two TULV strains each allowed for the de novo assembly of all four TULV genomes. Combining the novel sequences with all available TULV and PUUV genomes revealed very similar patterns of sequence diversity along the genomes, except for remarkably higher diversity in the non-coding region of the S-segment in PUUV. The genomic distribution of polymorphisms in the coding sequence was similar between the species, but differed between the segments with the highest sequence divergence of 0.274 for the M-segment, 0.265 for the S-segment, and 0.248 for the L-segment (overall 0.258). Phylogenetic analyses showed the clustering of genome sequences consistent with their geographic distribution within each species. Genome-wide data yielded extremely high node support values, despite the impact of strong mutational saturation that is expected for hantavirus sequences obtained over large spatial distances. We conclude that genome sequencing based on capture enrichment protocols provides an efficient means for ecological and evolutionary investigations of hantaviruses at an unprecedented completeness and depth.

Redondoviridae, a Family of Small, Circular DNA Viruses of the Human Oro-Respiratory Tract Associated with Periodontitis and Critical Illness

The global virome is largely uncharacterized but is now being unveiled by metagenomic DNA sequencing. Exploring the human respiratory virome, in particular, can provide insights into oro-respiratory diseases. Here, we use metagenomics to identify a family of small circular DNA viruses-named Redondoviridae-associated with human diseases. We first identified two redondovirus genomes from bronchoalveolar lavage samples from human lung donors. We then queried thousands of metagenomic samples and recovered 17 additional complete redondovirus genomes. Detections were exclusively in human samples and mostly from respiratory tract and oro-pharyngeal sites, where Redondoviridae was the second most prevalent eukaryotic DNA virus family. Redondovirus sequences were associated with periodontal disease, and abundances decreased with treatment. Some critically ill patients in a medical intensive care unit were found to harbor high levels of redondoviruses in respiratory samples. These results suggest that redondoviruses colonize human oro-respiratory sites and can bloom in several human disorders.

Coupling adaptive molecular evolution to phylodynamics using fitness-dependent birth-death models

Beneficial and deleterious mutations cause the fitness of lineages to vary across a phylogeny and thereby shape its branching structure. While standard phylogenetic models do not allow mutations to feedback and shape trees, birth-death models can account for this feedback by letting the fitness of lineages depend on their type. To date, these multi-type birth-death models have only been applied to cases where a lineage’s fitness is determined by a single character state. We extend these models to track sequence evolution at multiple sites. This approach remains computationally tractable by tracking the genotype and fitness of lineages probabilistically in an approximate manner. Although approximate, we show that we can accurately estimate the fitness of lineages and site-specific mutational fitness effects from phylogenies. We apply this approach to estimate the population-level fitness effects of mutations in Ebola and influenza virus, and compare our estimates with in vitro fitness measurements for these mutations.

The Puzzle of HIV Neutral and Selective Evolution

HIV is one of the fastest evolving organisms known. It evolves about 1 million times faster than its host, humans. Because HIV establishes chronic infections, with continuous evolution, its divergence within a single infected human surpasses the divergence of the entire humanoid history. Yet, it is still the same virus, infecting the same cell types and using the same replication machinery year after year. Hence, one would think that most mutations that HIV accumulates are neutral. But the picture is more complicated than that. HIV evolution is also a clear example of strong positive selection, that is, mutants have a survival advantage. How do these facts come together?

Evolution of HIV-1 within untreated individuals and at the population scale in Uganda

HIV-1 undergoes multiple rounds of error-prone replication between transmission events, resulting in diverse viral populations within and among individuals. In addition, the virus experiences different selective pressures at multiple levels: during the course of infection, at transmission, and among individuals. Disentangling how these evolutionary forces shape the evolution of the virus at the population scale is important for understanding pathogenesis, how drug- and immune-escape variants are likely to spread in populations, and the development of preventive vaccines. To address this, we deep-sequenced two regions of the HIV-1 genome (p24 and gp41) from 34 longitudinally-sampled untreated individuals from Rakai District in Uganda, infected with subtypes A, D, and inter-subtype recombinants. This dataset substantially increases the availability of HIV-1 sequence data that spans multiple years of untreated infection, in particular for different geographical regions and viral subtypes. In line with previous studies, we estimated an approximately five-fold faster rate of evolution at the within-host compared to the population scale for both synonymous and nonsynonymous substitutions, and for all subtypes. We determined the extent to which this mismatch in evolutionary rates can be explained by the evolution of the virus towards population-level consensus, or the transmission of viruses similar to those that establish infection within individuals. Our findings indicate that both processes are likely to be important.

Neutral Theory and Rapidly Evolving Viral Pathogens

The evolution of viral pathogens is shaped by strong selective forces that are exerted during jumps to new hosts, confrontations with host immune responses and antiviral drugs, and numerous other processes. However, while undeniably strong and frequent, adaptive evolution is largely confined to small parts of information-packed viral genomes, and the majority of observed variation is effectively neutral. The predictions and implications of the neutral theory have proven immensely useful in this context, with applications spanning understanding within-host population structure, tracing the origins and spread of viral pathogens, predicting evolutionary dynamics, and modeling the emergence of drug resistance. We highlight the multiple ways in which the neutral theory has had an impact, which has been accelerated in the age of high-throughput, high-resolution genomics.

Mapping mutational effects along the evolutionary landscape of HIV envelope

The immediate evolutionary space accessible to HIV is largely determined by how single amino acid mutations affect fitness. These mutational effects can shift as the virus evolves. However, the prevalence of such shifts in mutational effects remains unclear. Here, we quantify the effects on viral growth of all amino acid mutations to two HIV envelope (Env) proteins that differ at >100 residues. Most mutations similarly affect both Envs, but the amino acid preferences of a minority of sites have clearly shifted. These shifted sites usually prefer a specific amino acid in one Env, but tolerate many amino acids in the other. Surprisingly, shifts are only slightly enriched at sites that have substituted between the Envs—and many occur at residues that do not even contact substitutions. Therefore, long-range epistasis can unpredictably shift Env’s mutational tolerance during HIV evolution, although the amino acid preferences of most sites are conserved between moderately diverged viral strains.

The virus that causes AIDS, or HIV, has a protein called Env on its surface, which is essential for the virus to infect cells. Env can also be recognized by the immune system, which then targets the virus for destruction or blocks it from infecting cells. Unfortunately, Env evolves very quickly, which means that HIV can evade our defenses. However, there are limits to how much this protein can change, since it still needs to perform its essential role in helping viruses enter cells.

In the century since HIV first appeared in human populations, the virus has evolved considerably. There are now many HIV strains that infect people, and they bear Env proteins with substantially different sequences. However, it is not clear if these changes in sequence have resulted in Envs from distinct strains being able to tolerate different mutations.

To examine this question, Haddox et al. compared how the Envs from two strains of HIV react to modifications in their sequences. They created all possible individual mutations in the proteins, and the resulting collections of mutated viruses were then tested for their ability to infect cells in the laboratory.

Most mutations had similar effects in both Env proteins. This allowed Haddox et al. to identify portions of the protein that easily accommodate changes, and portions that must remain unchanged for viruses to remain infectious—at least in the laboratory. Some of these mutations are under different types of pressures when the virus faces the immune system, and those were identified using computational approaches.

However, some mutations were tolerated differently by the two Env proteins. Therefore, viral strains differ in how their Env proteins can evolve. The parts of Env that showed differences in mutational tolerance between the strains were not necessarily the parts that differ in sequence. This shows that changes in sequence in one part of the protein can modify how other portions evolve.

It remains to be determined whether changes in tolerance to mutations translate into differences in how the virus can escape immunity. This is an important question given that the rapid evolution of Env is a major obstacle to creating a vaccine for HIV.

New windows into retroviral RNA structures

Background

The multiple roles of both viral and cellular RNAs have become increasingly apparent in recent years, and techniques to model them have become significantly more powerful, enabling faster and more accurate visualization of RNA structures.

Main body

Techniques such as SHAPE (selective 2’OH acylation analysed by primer extension) have revolutionized the field, and have been used to examine RNAs belonging to many and diverse retroviruses. Secondary structure probing reagents such as these have been aided by the development of faster methods of analysis either via capillary or next-generation sequencing, allowing the analysis of entire genomes, and of retroviral RNA structures within virions. Techniques to model the three-dimensional structures of these large RNAs have also recently developed.

Conclusions

The flexibility of retroviral RNAs, both structural and functional, is clear from the results of these new experimental techniques. Retroviral RNA structures and structural changes control many stages of the lifecycle, and both the RNA structures themselves and their interactions with ligands are potential new drug targets. In addition, our growing understanding of retroviral RNA structures is aiding our knowledge of cellular RNA form and function.

Evaluation of global HIV/SIV envelope gp120 RNA structure and evolution within and among infected hosts

Lentiviral RNA genomes contain structural elements that play critical roles in viral replication. Although structural features of 5'-untranslated regions have been well characterized, attempts to identify important structures in other genomic regions by Selective 2'-Hydroxyl Acylation analyzed by Primer Extension (SHAPE) have led to conflicting structural and mechanistic conclusions. Previous approaches accounted neither for sequence heterogeneity that is ubiquitous in viral populations, nor for selective constraints operating at the protein level. We developed an approach that augments SHAPE with phylogenetic analyses and applied it to investigate structure in coding regions (cRNA) within the HIV and SIV envelope genes. Analysis of single-genome SHAPE data with phylogenetic information from diverse lentiviral sequences argues against the conservation of a putative global gp120 RNA structure but points to the existence of core RNA sub-structures. Our findings establish a framework for considering sequence heterogeneity and protein function in de novo RNA structure inference approaches.

In vivo mutation rates and the landscape of fitness costs of HIV-1

Mutation rates and fitness costs of deleterious mutations are difficult to measure in vivo but essential for a quantitative understanding of evolution. Using whole genome deep sequencing data from longitudinal samples during untreated HIV-1 infection, we estimated mutation rates and fitness costs in HIV-1 from the dynamics of genetic variation. At approximately neutral sites, mutations accumulate with a rate of 1.2 × 10-5 per site per day, in agreement with the rate measured in cell cultures. We estimated the rate from G to A to be the largest, followed by the other transitions C to T, T to C, and A to G, while transversions are less frequent. At other sites, mutations tend to reduce virus replication. We estimated the fitness cost of mutations at every site in the HIV-1 genome using a model of mutation selection balance. About half of all non-synonymous mutations have large fitness costs (>10 percent), while most synonymous mutations have costs <1 percent. The cost of synonymous mutations is especially low in most of pol where we could not detect measurable costs for the majority of synonymous mutations. In contrast, we find high costs for synonymous mutations in important RNA structures and regulatory regions. The intra-patient fitness cost estimates are consistent across multiple patients, indicating that the deleterious part of the fitness landscape is universal and explains a large fraction of global HIV-1 group M diversity.

Experimental Estimation of the Effects of All Amino-Acid Mutations to HIV's Envelope Protein on Viral Replication in Cell Culture

HIV is notorious for its capacity to evade immunity and anti-viral drugs through rapid sequence evolution. Knowledge of the functional effects of mutations to HIV is critical for understanding this evolution. HIV's most rapidly evolving protein is its envelope (Env). Here we use deep mutational scanning to experimentally estimate the effects of all amino-acid mutations to Env on viral replication in cell culture. Most mutations are under purifying selection in our experiments, although a few sites experience strong selection for mutations that enhance HIV's replication in cell culture. We compare our experimental measurements of each site's preference for each amino acid to the actual frequencies of these amino acids in naturally occurring HIV sequences. Our measured amino-acid preferences correlate with amino-acid frequencies in natural sequences for most sites. However, our measured preferences are less concordant with natural amino-acid frequencies at surface-exposed sites that are subject to pressures absent from our experiments such as antibody selection. Our data enable us to quantify the inherent mutational tolerance of each site in Env. We show that the epitopes of broadly neutralizing antibodies have a significantly reduced inherent capacity to tolerate mutations, rigorously validating a pervasive idea in the field. Overall, our results help disentangle the role of inherent functional constraints and external selection pressures in shaping Env's evolution.

Evidence of a Direct Evolutionary Selection for Strong Folding and Mutational Robustness Within HIV Coding Regions

A large number of studies demonstrated the importance of different HIV RNA structural elements at all stages of the viral life cycle. Nevertheless, the significance of many of these structures is unknown, and plausibly new regions containing RNA structure-mediated regulatory signals remain to be identified. An important characteristic of genomic regions carrying functionally significant secondary structures is their mutational robustness, that is, the extent to which a sequence remains constant in spite of despite mutations in terms of its underlying secondary structure. Structural robustness to mutations is expected to be important in the case of functional RNA structures in viruses with high mutation rate; it may prevent fitness loss due to disruption of possibly functional conformations, pointing to the specific significance of the corresponding genomic region. In the current work, we perform a genome-wide computational analysis to detect signals of a direct evolutionary selection for strong folding and RNA structure-based mutational robustness within HIV coding sequences. We provide evidence that specific regions of HIV structural genes undergo an evolutionary selection for strong folding; in addition, we demonstrate that HIV Rev responsive element seems to undergo a direct evolutionary selection for increased secondary structure robustness to point mutations. We believe that our analysis may enable a better understanding of viral evolutionary dynamics at the RNA structural level and may benefit to practical efforts of engineering antiviral vaccines and novel therapeutic approaches.

The population genetics of drug resistance evolution in natural populations of viral, bacterial and eukaryotic pathogens

Drug resistance is a costly consequence of pathogen evolution and a major concern in public health. In this review, we show how population genetics can be used to study the evolution of drug resistance and also how drug resistance evolution is informative as an evolutionary model system. We highlight five examples from diverse organisms with particular focus on: (i) identifying drug resistance loci in the malaria parasite Plasmodium falciparum using the genomic signatures of selective sweeps, (ii) determining the role of epistasis in drug resistance evolution in influenza, (iii) quantifying the role of standing genetic variation in the evolution of drug resistance in HIV, (iv) using drug resistance mutations to study clonal interference dynamics in tuberculosis and (v) analysing the population structure of the core and accessory genome of Staphylococcus aureus to understand the spread of methicillin resistance. Throughout this review, we discuss the uses of sequence data and population genetic theory in studying the evolution of drug resistance.

Population genomics of intrapatient HIV-1 evolution

Many microbial populations rapidly adapt to changing environments with multiple variants competing for survival. To quantify such complex evolutionary dynamics in vivo, time resolved and genome wide data including rare variants are essential. We performed whole-genome deep sequencing of HIV-1 populations in 9 untreated patients, with 6-12 longitudinal samples per patient spanning 5-8 years of infection. The data can be accessed and explored via an interactive web application. We show that patterns of minor diversity are reproducible between patients and mirror global HIV-1 diversity, suggesting a universal landscape of fitness costs that control diversity. Reversions towards the ancestral HIV-1 sequence are observed throughout infection and account for almost one third of all sequence changes. Reversion rates depend strongly on conservation. Frequent recombination limits linkage disequilibrium to about 100 bp in most of the genome, but strong hitch-hiking due to short range linkage limits diversity.

Widespread signatures of local mRNA folding structure selection in four Dengue virus serotypes

BACKGROUND

It is known that mRNA folding can affect and regulate various gene expression steps both in living organisms and in viruses. Previous studies have recognized functional RNA structures in the genome of the Dengue virus. However, these studies usually focused either on the viral untranslated regions or on very specific and limited regions at the beginning of the coding sequences, in a limited number of strains, and without considering evolutionary selection.

RESULTS

Here we performed the first large scale comprehensive genomics analysis of selection for local mRNA folding strength in the Dengue virus coding sequences, based on a total of 1,670 genomes and 4 serotypes. Our analysis identified clusters of positions along the coding regions that may undergo a conserved evolutionary selection for strong or weak local folding maintained across different viral variants. Specifically, 53-66 clusters for strong folding and 49-73 clusters for weak folding (depending on serotype) aggregated of positions with a significant conservation of folding energy signals (related to partially overlapping local genomic regions) were recognized. In addition, up to 7% of these positions were found to be conserved in more than 90% of the viral genomes. Although some of the identified positions undergo frequent synonymous / non-synonymous substitutions, the selection for folding strength therein is preserved, and thus cannot be trivially explained based on sequence conservation alone.

CONCLUSIONS

The fact that many of the positions with significant folding related signals are conserved among different Dengue variants suggests that a better understanding of the mRNA structures in the corresponding regions may promote the development of prospective anti- Dengue vaccination strategies. The comparative genomics approach described here can be employed in the future for detecting functional regions in other pathogens with very high mutations rates.

Evaluation of influenza vaccine effectiveness and description of circulating strains in outpatient settings in South Africa, 2014

The effectiveness of the trivalent seasonal influenza vaccine during the 2014 season in South Africa was assessed using a test-negative case-control study design including 472 cases and 362 controls. Influenza A(H3N2) was the dominant strain circulating. The overall vaccine effectiveness estimate, adjusted for age and underlying conditions, was 43·1% (95% CI: -26·8-74·5). 2014 H3N2 viruses from South Africa were mainly in sublineage 3C.3 with accumulation of amino acid changes that differentiate them from the vaccine strain in 3C.1.

Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes

HIV and related primate lentiviruses possess single-stranded RNA genomes. Multiple regions of these genomes participate in critical steps in the viral replication cycle, and the functions of many RNA elements are dependent on the formation of defined structures. The structures of these elements are still not fully understood, and additional functional elements likely exist that have not been identified. In this work, we compared three full-length HIV-related viral genomes: HIV-1NL4-3, SIVcpz, and SIVmac (the latter two strains are progenitors for all HIV-1 and HIV-2 strains, respectively). Model-free RNA structure comparisons were performed using whole-genome structure information experimentally derived from nucleotide-resolution SHAPE reactivities. Consensus secondary structures were constructed for strongly correlated regions by taking into account both SHAPE probing structural data and nucleotide covariation information from structure-based alignments. In these consensus models, all known functional RNA elements were recapitulated with high accuracy. In addition, we identified multiple previously unannotated structural elements in the HIV-1 genome likely to function in translation, splicing and other replication cycle processes; these are compelling targets for future functional analyses. The structure-informed alignment strategy developed here will be broadly useful for efficient RNA motif discovery.

The relationship between dN/dS and scaled selection coefficients

Numerous computational methods exist to assess the mode and strength of natural selection in protein-coding sequences, yet how distinct methods relate to one another remains largely unknown. Here, we elucidate the relationship between two widely used phylogenetic modeling frameworks: dN/dS models and mutation-selection (MutSel) models. We derive a mathematical relationship between dN/dS and scaled selection coefficients, the focal parameters of MutSel models, and use this relationship to gain deeper insight into the behaviors, limitations, and applicabilities of these two modeling frameworks. We prove that, if all synonymous changes are neutral, standard MutSel models correspond to dN/dS ≤ 1. However, if synonymous codons differ in fitness, dN/dS can take on arbitrarily high values even if all selection is purifying. Thus, the MutSel modeling framework cannot necessarily accommodate positive, diversifying selection, while dN/dS cannot distinguish between purifying selection on synonymous codons and positive selection on amino acids. We further propose a new benchmarking strategy of dN/dS inferences against MutSel simulations and demonstrate that the widely used Goldman-Yang-style dN/dS models yield substantially biased dN/dS estimates on realistic sequence data. In contrast, the less frequently used Muse-Gaut-style models display much less bias. Strikingly, the least-biased and most precise dN/dS estimates are never found in the models with the best fit to the data, measured through both AIC and BIC scores. Thus, selecting models based on goodness-of-fit criteria can yield poor parameter estimates if the models considered do not precisely correspond to the underlying mechanism that generated the data. In conclusion, establishing mathematical links among modeling frameworks represents a novel, powerful strategy to pinpoint previously unrecognized model limitations and strengths.

Silent mutations at codons 65 and 66 in reverse transcriptase alleviate indel formation and restore fitness in subtype B HIV-1 containing D67N and K70R drug resistance mutations

Resistance to combined antiretroviral therapy (cART) in HIV-1-infected individuals is typically due to nonsynonymous mutations that change the protein sequence; however, the selection of synonymous or ‘silent’ mutations in the HIV-1 genome with cART has been reported. These silent K65K and K66K mutations in the HIV-1 reverse transcriptase (RT) occur in over 35% of drug-experienced individuals and are highly associated with the thymidine analog mutations D67N and K70R, which confer decreased susceptibility to most nucleoside and nucleotide RT inhibitors. However, the basis for selection of these silent mutations under selective drug pressure is unknown. Using Illumina next-generation sequencing, we demonstrate that the D67N/K70R substitutions in HIV-1 RT increase indel frequency by 100-fold at RT codons 65–67, consequently impairing viral fitness. Introduction of either K65K or K66K into HIV-1 containing D67N/K70R reversed the error-prone DNA synthesis at codons 65–67 in RT and improved viral replication fitness, but did not impact RT inhibitor drug susceptibility. These data provide new mechanistic insights into the role of silent mutations selected during antiretroviral therapy and have broader implications for the relevance of silent mutations in the evolution and fitness of RNA viruses.

Uneven genetic robustness of HIV-1 integrase

Genetic robustness (tolerance of mutation) may be a naturally selected property in some viruses, because it should enhance adaptability. Robustness should be especially beneficial to viruses like HIV-1 that exhibit high mutation rates and exist in immunologically hostile environments. Surprisingly, however, the HIV-1 capsid protein (CA) exhibits extreme fragility. To determine whether fragility is a general property of HIV-1 proteins, we created a large library of random, single-amino-acid mutants in HIV-1 integrase (IN), covering >40% of amino acid positions. Despite similar degrees of sequence variation in naturally occurring IN and CA sequences, we found that HIV-1 IN was significantly more robust than CA, with random nonsilent IN mutations only half as likely to cause lethal defects. Interestingly, IN and CA were similar in that a subset of mutations with high in vitro fitness were rare in natural populations. IN mutations of this type were more likely to occur in the buried interior of the modeled HIV-1 intasome, suggesting that even very subtle fitness effects suppress variation in natural HIV-1 populations. Lethal mutations, in particular those that perturbed particle production, proteolytic processing, and particle-associated IN levels, were strikingly localized at specific IN subunit interfaces. This observation strongly suggests that binding interactions between particular IN subunits regulate proteolysis during HIV-1 virion morphogenesis. Overall, use of the IN mutant library in conjunction with structural models demonstrates the overall robustness of IN and highlights particular regions of vulnerability that may be targeted in therapeutic interventions.

IMPORTANCE

The HIV-1 integrase (IN) protein is responsible for the integration of the viral genome into the host cell chromosome. To measure the capacity of IN to maintain function in the face of mutation, and to probe structure/function relationships, we created a library of random single-amino-acid IN mutations that could mimic the types of mutations that naturally occur during HIV-1 infection. Previously, we measured the robustness of HIV-1 capsid in this manner and determined that it is extremely intolerant of mutation. In contrast to CA, HIV-1 IN proved relatively robust, with far fewer mutations causing lethal defects. However, when we subsequently mapped the lethal mutations onto a model of the structure of the multisubunit IN-viral DNA complex, we found the lethal mutations that caused virus morphogenesis defects tended to be highly localized at subunit interfaces. This discovery of vulnerable regions of HIV-1 IN could inform development of novel therapeutics.

Identifying selection in the within-host evolution of influenza using viral sequence data

The within-host evolution of influenza is a vital component of its epidemiology. A question of particular interest is the role that selection plays in shaping the viral population over the course of a single infection. We here describe a method to measure selection acting upon the influenza virus within an individual host, based upon time-resolved genome sequence data from an infection. Analysing sequence data from a transmission study conducted in pigs, describing part of the haemagglutinin gene (HA1) of an influenza virus, we find signatures of non-neutrality in six of a total of sixteen infections. We find evidence for both positive and negative selection acting upon specific alleles, while in three cases, the data suggest the presence of time-dependent selection. In one infection we observe what is potentially a specific immune response against the virus; a non-synonymous mutation in an epitope region of the virus is found to be under initially positive, then strongly negative selection. Crucially, given the lack of homologous recombination in influenza, our method accounts for linkage disequilibrium between nucleotides at different positions in the haemagglutinin gene, allowing for the analysis of populations in which multiple mutations are present at any given time. Our approach offers a new insight into the dynamics of influenza infection, providing a detailed characterisation of the forces that underlie viral evolution.

The evolution of the influenza virus is of great importance for human health. Through evolution, current influenza viruses develop the ability to infect people who have been vaccinated against earlier strains. New strains of influenza that infect birds and pigs could evolve to infect and spread between people, causing a global pandemic. The influenza virus lives within a human or animal host, so that viral evolution happens within, or in the spread between, individuals. As such, what happens to the virus during the course of an infection is a question of great interest. We here describe a statistical method that uses viral genome sequence data to measure how evolution affects the influenza virus within a single host. Studying data from infections transmitted between pigs, we find evidence for evolutionary adaptation in six of sixteen animals for which data were available. In one case, an immune response mounted by a pig against the virus is apparent. Our method provides a statistical framework for using sequence data to study viral evolution on very short timescales, enabling new research into within-host viral evolution.

Implications of HIV RNA structure for recombination, speciation, and the neutralism-selectionism controversy

The conflict between the needs to encode both a protein (impaired by non-synonymous mutation), and nucleic acid structure (impaired by synonymous or non-synonymous mutation), can sometimes be resolved in favour of the nucleic acid because its structure is critical for a selectively advantageous genome-wide activity--recombination. However, above a sequence difference threshold, recombination is impaired. It may then be advantageous for new species to arise. Building on the work of Grantham and others critical of the neutralist viewpoint, heuristic support for this hypothesis emerged from studies of the base composition and structure of retroviral genomes. The extreme enrichment in the purine A of the RNA of human immunodeficiency virus (HIV-1), parallels the mild purine-loading of the RNAs of most organisms, for which there is an adaptive explanation--immune evasion. However, human T cell leukaemia virus (HTLV-1), with the potential to invade the same host cell, shows extreme enrichment in the pyrimidine C. Assuming the low GC% HIV and the high GC% HTLV-1 to share a common ancestor, it was postulated that differences in GC% had arisen to prevent homologous recombination between these emerging lentiviral species. Sympatrically isolated by this intracellular reproductive barrier, prototypic HIV-1 seized the AU-rich (low GC%) high ground (thus committing to purine A rather than purine G). Prototypic HTLV-1 forwent this advantage and evolved an independent evolutionary strategy--similar to that of the GC%-rich Epstein-Barr virus--profound latency maintained by transcription of one purine-rich mRNA. The evidence supporting these interpretations is reviewed.