Forward mutation rate of human immunodeficiency virus type 1 in a T lymphoid cell line

Antigen-specific and cross-reactive T cells in protection and disease

Human T cells have a diverse T-cell receptor (TCR) repertoire that endows them with the ability to identify and defend against a broad spectrum of antigens. The universe of possible antigens that T cells may encounter, however, is even larger. To effectively surveil such a vast universe, the T-cell repertoire must adopt a high degree of cross-reactivity. Likewise, antigen-specific and cross-reactive T-cell responses play pivotal roles in both protective and pathological immune responses in numerous diseases. In this review, we explore the implications of these antigen-driven T-cell responses, with a particular focus on CD8+ T cells, using infection, neurodegeneration, and cancer as examples. We also summarize recent technological advances that facilitate high-throughput profiling of antigen-specific and cross-reactive T-cell responses experimentally, as well as computational biology approaches that predict these interactions.

HIV-1 usurps transcription start site heterogeneity of host RNA polymerase II to maximize replication fitness

HIV-1 relies on host RNA polymeraseII (Pol II) to transcribe its genome and uses multiple transcription start sites (TSS), including three consecutive guanosines located near the U3-R junction, to generate transcripts containing three, two, and one guanosine at the 5' end, referred to as 3G, 2G, and 1G RNA, respectively. The 1G RNA is preferentially selected for packaging, indicating that these 99.9% identical RNAs exhibit functional differences and highlighting the importance of TSS selection. Here, we demonstrate that TSS selection is regulated by sequences between the CATA/TATA box and the beginning of R. Furthermore, we have generated two HIV-1 mutants with distinct 2-nucleotide modifications that predominantly express 3G RNA or 1G RNA. Both mutants can generate infectious viruses and undergo multiple rounds of replication in T cells. However, both mutants exhibit replication defects compared to the wild-type virus. The 3G-RNA-expressing mutant displays an RNA genome-packaging defect and delayed replication kinetics, whereas the 1G-RNA-expressing mutant exhibits reduced Gag expression and a replication fitness defect. Additionally, reversion of the latter mutant is frequently observed, consistent with sequence correction by plus-strand DNA transfer during reverse transcription. These findings demonstrate that HIV-1 maximizes its replication fitness by usurping the TSS heterogeneity of host RNA Pol II to generate unspliced RNAs with different specialized roles in viral replication. The three consecutive guanosines at the junction of U3 and R may also maintain HIV-1 genome integrity during reverse transcription. These studies reveal the intricate regulation of HIV-1 RNA and complex replication strategy.

Global landscape of SARS-CoV-2 mutations and conserved regions

BACKGROUND

At the end of December 2019, a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) disease (COVID-19) has been identified in Wuhan, a central city in China, and then spread to every corner of the globe. As of October 8, 2022, the total number of COVID-19 cases had reached over 621 million worldwide, with more than 6.56 million confirmed deaths. Since SARS-CoV-2 genome sequences change due to mutation and recombination, it is pivotal to surveil emerging variants and monitor changes for improving pandemic management.

METHODS

10,287,271 SARS-CoV-2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24, 2020, to April 2022. Python programming language (version 3.8.0) software was utilized to process FASTA files to identify variants and sequence conservation. The NCBI RefSeq SARS-CoV-2 genome (accession no. NC_045512.2) was considered as the reference sequence.

RESULTS

Six mutations had more than 50% frequency in global SARS-CoV-2. These mutations include the P323L (99.3%) in NSP12, D614G (97.6) in S, the T492I (70.4) in NSP4, R203M (62.8%) in N, T60A (61.4%) in Orf9b, and P1228L (50.0%) in NSP3. In the SARS-CoV-2 genome, no mutation was observed in more than 90% of nsp11, nsp7, nsp10, nsp9, nsp8, and nsp16 regions. On the other hand, N, nsp3, S, nsp4, nsp12, and M had the maximum rate of mutations. In the S protein, the highest mutation frequency was observed in aa 508-635(0.77%) and aa 381-508 (0.43%). The highest frequency of mutation was observed in aa 66-88 (2.19%), aa 7-14, and aa 164-246 (2.92%) in M, E, and N proteins, respectively.

CONCLUSION

Therefore, monitoring SARS-CoV-2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS-CoV-2 diagnostic efficiency and design safe and effective vaccines against emerging variants.

Emerging and Re-Emerging Viral Infections: An Indian Perspective

Emerging and re-emerging viral infections pose a constant threat, especially in healthcare settings. Viral infections can be thought of as an ecological system, like a forest or a pond, with different species competing for resources. Pandemics tend to occur when there is a disruption to this ecosystem, such as introducing a strain of virus into humans or animals that they have no immunity against. Around 60% of human infectious diseases and 75% of emerging infections are zoonotic, with two-thirds originating in wildlife. There is an ongoing risk of viral diseases as the human population continues to grow and the rate of urbanization increases. The emergence and re-emergence of viral diseases are influenced by a variety of virologic and environmental factors. These factors can be roughly categorized as affecting humans, the environment and/or ecology, and viruses. The spread of zoonotic diseases among humans can be prevented by reducing the transmission risk associated with wildlife and exotic pets through education, legislation, and behavioral change programs that target individuals at risk for exposure.

Molecular Biology and Diversification of Human Retroviruses

Studies of retroviruses have led to many extraordinary discoveries that have advanced our understanding of not only human diseases, but also molecular biology as a whole. The most recognizable human retrovirus, human immunodeficiency virus type 1 (HIV-1), is the causative agent of the global AIDS epidemic and has been extensively studied. Other human retroviruses, such as human immunodeficiency virus type 2 (HIV-2) and human T-cell leukemia virus type 1 (HTLV-1), have received less attention, and many of the assumptions about the replication and biology of these viruses are based on knowledge of HIV-1. Existing comparative studies on human retroviruses, however, have revealed that key differences between these viruses exist that affect evolution, diversification, and potentially pathogenicity. In this review, we examine current insights on disparities in the replication of pathogenic human retroviruses, with a particular focus on the determinants of structural and genetic diversity amongst HIVs and HTLV.

Role of artificial intelligence in peptide vaccine design against RNA viruses

RNA viruses have high rate of replication and mutation that help them adapt and change according to their environmental conditions. Many viral mutants are the cause of various severe and lethal diseases. Vaccines, on the other hand have the capacity to protect us from infectious diseases by eliciting antibody or cell-mediated immune responses that are pathogen-specific. While there are a few reviews pertaining to the use of artificial intelligence (AI) for SARS-COV-2 vaccine development, none focus on peptide vaccination for RNA viruses and the important role played by AI in it. Peptide vaccine which is slowly coming to be recognized as a safe and effective vaccination strategy has the capacity to overcome the mutant escape problem which is also being currently faced by SARS-COV-2 vaccines in circulation.Here we review the present scenario of peptide vaccines which are developed using mathematical and computational statistics methods to prevent the spread of disease caused by RNA viruses. We also focus on the importance and current stage of AI and mathematical evolutionary modeling using machine learning tools in the establishment of these new peptide vaccines for the control of viral disease.

Development of a User-Friendly Pipeline for Mutational Analyses of HIV Using Ultra-Accurate Maximum-Depth Sequencing

Human immunodeficiency virus type 2 (HIV-2) accumulates fewer mutations during replication than HIV type 1 (HIV-1). Advanced studies of HIV-2 mutagenesis, however, have historically been confounded by high background error rates in traditional next-generation sequencing techniques. In this study, we describe the adaptation of the previously described maximum-depth sequencing (MDS) technique to studies of both HIV-1 and HIV-2 for the ultra-accurate characterization of viral mutagenesis. We also present the development of a user-friendly Galaxy workflow for the bioinformatic analyses of sequencing data generated using the MDS technique, designed to improve replicability and accessibility to molecular virologists. This adapted MDS technique and analysis pipeline were validated by comparisons with previously published analyses of the frequency and spectra of mutations in HIV-1 and HIV-2 and is readily expandable to studies of viral mutation across the genomes of both viruses. Using this novel sequencing pipeline, we observed that the background error rate was reduced 100-fold over standard Illumina error rates, and 10-fold over traditional unique molecular identifier (UMI)-based sequencing. This technical advancement will allow for the exploration of novel and previously unrecognized sources of viral mutagenesis in both HIV-1 and HIV-2, which will expand our understanding of retroviral diversity and evolution.

Enhanced enzyme kinetics of reverse transcriptase variants cloned from animals infected with SIVmac239 lacking viral protein X

HIV Type 1 (HIV-1) and simian immunodeficiency virus (SIV) display differential replication kinetics in macrophages. This is because high expression levels of the active host deoxynucleotide triphosphohydrolase sterile α motif domain and histidine-aspartate domain-containing protein 1 (SAMHD1) deplete intracellular dNTPs, which restrict HIV-1 reverse transcription, and result in a restrictive infection in this myeloid cell type. Some SIVs overcome SAMHD1 restriction using viral protein X (Vpx), a viral accessory protein that induces proteasomal degradation of SAMHD1, increasing cellular dNTP concentrations and enabling efficient proviral DNA synthesis. We previously reported that SAMHD1-noncounteracting lentiviruses may have evolved to harbor RT proteins that efficiently polymerize DNA, even at low dNTP concentrations, to circumvent SAMHD1 restriction. Here we investigated whether RTs from SIVmac239 virus lacking a Vpx protein evolve during in vivo infection to more efficiently synthesize DNA at the low dNTP concentrations found in macrophages. Sequence analysis of RTs cloned from Vpx (+) and Vpx (-) SIVmac239-infected animals revealed that Vpx (-) RTs contained more extensive mutations than Vpx (+) RTs. Although the amino acid substitutions were dispersed indiscriminately across the protein, steady-state and pre-steady-state analysis demonstrated that selected SIVmac239 Vpx (-) RTs are characterized by higher catalytic efficiency and incorporation efficiency values than RTs cloned from SIVmac239 Vpx (+) infections. Overall, this study supports the possibility that the loss of Vpx may generate in vivo SIVmac239 RT variants that can counteract the limited availability of dNTP substrate in macrophages.

The Determination of HIV-1 RT Mutation Rate, Its Possible Allosteric Effects, and Its Implications on Drug Resistance

The high mutation rate of the human immunodeficiency virus type 1 (HIV-1) plays a major role in treatment resistance, from the development of vaccines to therapeutic drugs. In addressing the crux of the issue, various attempts to estimate the mutation rate of HIV-1 resulted in a large range of 10⁻⁵–10⁻³ errors/bp/cycle due to the use of different types of investigation methods. In this review, we discuss the different assay methods, their findings on the mutation rates of HIV-1 and how the locations of mutations can be further analyzed for their allosteric effects to allow for new inhibitor designs. Given that HIV is one of the fastest mutating viruses, it serves as a good model for the comprehensive study of viral mutations that can give rise to a more horizontal understanding towards overall viral drug resistance as well as emerging viral diseases.

Analysis of unusual and signature APOBEC-mutations in HIV-1 pol next-generation sequences

Introduction

At low mutation-detection thresholds, next generation sequencing (NGS) for HIV-1 genotypic resistance testing is susceptible to artifactual detection of mutations arising from PCR error and APOBEC-mediated G-to-A hypermutation.

Methods

We analyzed published HIV-1 pol Illumina NGS data to characterize the distribution of mutations at eight NGS mutation detection thresholds: 20%, 10%, 5%, 2%, 1%, 0.5%, 0.2%, and 0.1%. At each threshold, we determined proportions of amino acid mutations that were unusual (defined as having a prevalence <0.01% in HIV-1 group M sequences) or signature APOBEC mutations.

Results

Eight studies, containing 855 samples, in the NCBI Sequence Read Archive were analyzed. As detection thresholds were lowered, there was a progressive increase in the proportion of positions with usual and unusual mutations and in the proportion of all mutations that were unusual. The median proportion of positions with an unusual mutation increased gradually from 0% at the 20% threshold to 0.3% at the 1% threshold and then exponentially to 1.3% (0.5% threshold), 6.9% (0.2% threshold), and 23.2% (0.1% threshold). In two of three studies with available plasma HIV-1 RNA levels, the proportion of positions with unusual mutations was negatively associated with virus levels. Although the complete set of signature APOBEC mutations was much smaller than that of unusual mutations, the former outnumbered the latter in one-sixth of samples at the 0.5%, 1%, and 2% thresholds.

Conclusions

The marked increase in the proportion of positions with unusual mutations at thresholds below 1% and in samples with lower virus loads suggests that, at low thresholds, many unusual mutations are artifactual, reflecting PCR error or G-to-A hypermutation. Profiling the numbers of unusual and signature APOBEC pol mutations at different NGS mutation detection thresholds may be useful to avoid selecting a threshold that is too low and poses an unacceptable risk of identifying artifactual mutations.

Parallel evolution of HIV-1 in a long-term experiment

One of the most intriguing puzzles in biology is the degree to which evolution is repeatable. The repeatability of evolution, or parallel evolution, has been studied in a variety of model systems, but has rarely been investigated with clinically relevant viruses. To investigate parallel evolution of HIV-1, we passaged two replicate HIV-1 populations for almost 1 year in each of two human T-cell lines. For each of the four evolution lines, we determined the genetic composition of the viral population at nine time points by deep sequencing the entire genome. Mutations that were carried by the majority of the viral population accumulated continuously over 1 year in each evolution line. Many majority mutations appeared in more than one evolution line, that is, our experiments showed an extreme degree of parallel evolution. In one of the evolution lines, 62% of the majority mutations also occur in another line. The parallelism impairs our ability to reconstruct the evolutionary history by phylogenetic methods. We show that one can infer the correct phylogenetic topology by including minority mutations in our analysis. We also find that mutation diversity at the beginning of the experiment is predictive of the frequency of majority mutations at the end of the experiment.

Constrained Mutational Sampling of Amino Acids in HIV-1 Protease Evolution

The evolution of HIV-1 protein sequences should be governed by a combination of factors including nucleotide mutational probabilities, the genetic code, and fitness. The impact of these factors on protein sequence evolution is interdependent, making it challenging to infer the individual contribution of each factor from phylogenetic analyses alone. We investigated the protein sequence evolution of HIV-1 by determining an experimental fitness landscape of all individual amino acid changes in protease. We compared our experimental results to the frequency of protease variants in a publicly available data set of 32,163 sequenced isolates from drug-naïve individuals. The most common amino acids in sequenced isolates supported robust experimental fitness, indicating that the experimental fitness landscape captured key features of selection acting on protease during viral infections of hosts. Amino acid changes requiring multiple mutations from the likely ancestor were slightly less likely to support robust experimental fitness than single mutations, consistent with the genetic code favoring chemically conservative amino acid changes. Amino acids that were common in sequenced isolates were predominantly accessible by single mutations from the likely protease ancestor. Multiple mutations commonly observed in isolates were accessible by mutational walks with highly fit single mutation intermediates. Our results indicate that the prevalence of multiple-base mutations in HIV-1 protease is strongly influenced by mutational sampling.

APOBEC3G Regulation of the Evolutionary Race Between Adaptive Immunity and Viral Immune Escape Is Deeply Imprinted in the HIV Genome

APOBEC3G (A3G) is a host enzyme that mutates the genomes of retroviruses like HIV. Since A3G is expressed pre-infection, it has classically been considered an agent of innate immunity. We and others previously showed that the impact of A3G-induced mutations on the HIV genome extends to adaptive immunity also, by generating cytotoxic T cell (CTL) escape mutations. Accordingly, HIV genomic sequences encoding CTL epitopes often contain A3G-mutable “hotspot” sequence motifs, presumably to channel A3G action toward CTL escape. Here, we studied the depths and consequences of this apparent viral genome co-evolution with A3G. We identified all potential CTL epitopes in Gag, Pol, Env, and Nef restricted to several HLA class I alleles. We simulated A3G-induced mutations within CTL epitope-encoding sequences, and flanking regions. From the immune recognition perspective, we analyzed how A3G-driven mutations are predicted to impact CTL-epitope generation through modulating proteasomal processing and HLA class I binding. We found that A3G mutations were most often predicted to result in diminishing/abolishing HLA-binding affinity of peptide epitopes. From the viral genome evolution perspective, we evaluated enrichment of A3G hotspots at sequences encoding CTL epitopes and included control sequences in which the HIV genome was randomly shuffled. We found that sequences encoding immunogenic epitopes exhibited a selective enrichment of A3G hotspots, which were strongly biased to translate to non-synonymous amino acid substitutions. When superimposed on the known mutational gradient across the entire length of the HIV genome, we observed a gradient of A3G hotspot enrichment, and an HLA-specific pattern of the potential of A3G hotspots to lead to CTL escape mutations. These data illuminate the depths and extent of the co-evolution of the viral genome to subvert the host mutator A3G.

Early HIV infection predictions: role of viral replication errors

In order to prevent and/or control infections it is necessary to understand their early-time dynamics. However this is precisely the phase of HIV about which the least is known. To investigate the initial stages of HIV infection within a host we have developed a multi-type, continuous-time branching process model. This model is a stochastic extension of the standard viral dynamics model, under the assumption that the number of cell targets for viral infection is constant, biologically reasonable since, during the earliest stages of HIV infection, very few cells are infected relative to their total population size. We use our model to investigate three important clinical characteristics of early HIV infection following intravenous challenge: risk of infection, time to infection clearance (assuming failed infection), and time to infection detection. Our focus is on the impact of errors in viral replication that result in non-infectious virus production on these characteristics. Only a small fraction of circulating virus in any chronically infected individual is capable of infecting susceptible cells: estimates range from 1/10⁴ - 1/10³. Characterization and quantification of the processes by which virus becomes defective remains incomplete. We consider two mechanisms that result in defective virus: (1) Copying errors, i.e., lethal errors in reverse transcription, which introduce mutations into the HIV-1 proviral genome, some of which may cripple the viral genome produced, and (2) Packaging errors, i.e., errors during viral packaging, at the end of the viral replication cycle, which cause defective virus by packaging new virions without, for example, viral RNA or key proteins required for infectivity. We show that assumptions on mechanisms of defective virus production can significantly impact early HIV infection model predictions. For example, the risk of infection is orders of magnitude higher if all defective virus is associated with packaging errors, but infection is predicted to be detectable sooner following HIV exposure if all defective virus is associated with copying errors. Thus, in order to make reliable predictions of risk, clearance time, and detection time, better characterization of viral replication is required.

Time Intervals in Sequence Sampling, Not Data Modifications, Have a Major Impact on Estimates of HIV Escape Rates

The ability of human immunodeficiency virus (HIV) to avoid recognition by humoral and cellular immunity (viral escape) is well-documented, but the strength of the immune response needed to cause such a viral escape remains poorly quantified. Several previous studies observed a more rapid escape of HIV from CD8 T cell responses in the acute phase of infection compared to chronic infection. The rate of HIV escape was estimated with the help of simple mathematical models, and results were interpreted to suggest that CD8 T cell responses causing escape in acute HIV infection may be more efficient at killing virus-infected cells than responses that cause escape in chronic infection, or alternatively, that early escapes occur in epitopes mutations in which there is minimal fitness cost to the virus. However, these conclusions were challenged on several grounds, including linkage and interference of multiple escape mutations due to a low population size and because of potential issues associated with modifying the data to estimate escape rates. Here we use a sampling method which does not require data modification to show that previous results on the decline of the viral escape rate with time since infection remain unchanged. However, using this method we also show that estimates of the escape rate are highly sensitive to the time interval between measurements, with longer intervals biasing estimates of the escape rate downwards. Our results thus suggest that data modifications for early and late escapes were not the primary reason for the observed decline in the escape rate with time since infection. However, longer sampling periods for escapes in chronic infection strongly influence estimates of the escape rate. More frequent sampling of viral sequences in chronic infection may improve our understanding of factors influencing the rate of HIV escape from CD8 T cell responses.

Are RNA Viruses Candidate Agents for the Next Global Pandemic? A Review

Pathogenic RNA viruses are potentially the most important group involved in zoonotic disease transmission, and they represent a challenge for global disease control. Their biological diversity and rapid adaptive rates have proved to be difficult to overcome and to anticipate by modern medical technology. Also, the anthropogenic change of natural ecosystems and the continuous population growth are driving increased rates of interspecies contacts and the interchange of pathogens that can develop into global pandemics. The combination of molecular, epidemiological, and ecological knowledge of RNA viruses is therefore essential towards the proper control of these emergent pathogens. This review outlines, throughout different levels of complexity, the problems posed by RNA viral diseases, covering some of the molecular mechanisms allowing them to adapt to new host species-and to novel pharmaceutical developments-up to the known ecological processes involved in zoonotic transmission.

Mechanisms and Factors That Drive Extensive Human Immunodeficiency Virus Type-1 Hypervariability: An Overview

The extensive hypervariability of human immunodeficiency virus type-1 (HIV-1) populations represents a major barrier against the success of currently available antiretroviral therapy. Moreover, it is still the most important obstacle that faces the development of an effective preventive vaccine against this infectious virus. Indeed, several factors can drive such hypervariability within and between HIV-1 patients. These factors include: first, the very low fidelity nature of HIV-1 reverse transcriptase; second, the extremely high HIV-1 replication rate; and third, the high genomic recombination rate that the virus has. All these factors together with the APOBEC3 proteins family and the immune and antiviral drugs pressures drive the extensive hypervariability of HIV-1 populations. Studying these factors and the mechanisms that drive such hypervariability will provide valuable insights that may guide the development of effective therapeutic and preventive strategies against HIV-1 infection in the near future. To this end, in this review, we summarized recent advances in this area of HIV-1 research.

Single-Strand Consensus Sequencing Reveals that HIV Type but not Subtype Significantly Impacts Viral Mutation Frequencies and Spectra

A long-standing question of human immunodeficiency virus (HIV) genetic variation and evolution has been whether differences exist in mutation rate and/or mutation spectra among HIV types (i.e., HIV-1 versus HIV-2) and among HIV groups (i.e., HIV-1 groups M-P and HIV-2 groups A-H) and HIV-1 Group M subtypes (i.e., subtypes A-D, F-H, and J-K). To address this, we developed a new single-strand consensus sequencing assay for the determination of HIV mutation frequencies and spectra using the Illumina sequencing platform. This assay enables parallel and standardized comparison of HIV mutagenesis among various viral vectors with lower background error than traditional methods of Illumina library preparation. We found significant differences in viral mutagenesis between HIV types but intriguingly no significant differences among HIV-1 Group M subtypes. More specifically, HIV-1 exhibited higher transition frequencies than HIV-2, due mostly to single G-to-A mutations and (to a lesser extent) G-to-A hypermutation. These data suggest that HIV-2 RT exhibits higher fidelity during viral replication, and taken together, these findings demonstrate that HIV type but not subtype significantly affects viral mutation frequencies and spectra. These differences may inform antiviral and vaccine strategies.

Rate-limiting Pyrophosphate Release by HIV Reverse Transcriptase Improves Fidelity

Previous measurements of the rates of polymerization and pyrophosphate release with DNA templates showed that pyrophosphate (PP_i) dissociation was fast after nucleotide incorporation so that it did not contribute to enzyme specificity (k_cat/K_m). Here, kinetic parameters governing nucleotide incorporation and PP_i release were determined using an RNA template. Compared with a DNA template of the same sequence, the rate of chemistry increased by up to 10-fold (250 versus 24 s^-1), whereas the rate of PP_i release decreased to approximately 58 s^-1 so that PP_i release became the rate-limiting step. During processive nucleotide incorporation, the first nucleotide (TTP) was incorporated at a fast rate (152 s^-1), whereas the rates of incorporation of remaining nucleotides (CGTCG) were much slower with an average rate of 24 s^-1, suggesting that sequential incorporation events were limited by the relatively slow PP_i release step. The accompanying paper shows that slow PP_i release allows polymerization and RNase H to occur at comparable rates. Although PP_i release is the rate-determining step, it is not the specificity-determining step for correct incorporation based on our current estimates of the rate of reversal of the chemistry step (3 s^-1). In contrast, during misincorporation, PP_i release became extremely slow, which we estimated to be ∼0.002 s^-1 These studies establish the mechanistic basis for DNA polymerase fidelity during reverse transcription and provide a free energy profile. We correct previous underestimates of discrimination by including the slow PP_i release step. Our current estimate of 2.4 × 10⁶ is >20-fold greater than estimated previously.

HIV-1 drug resistance and resistance testing

The global scale-up of antiretroviral (ARV) therapy (ART) has led to dramatic reductions in HIV-1 mortality and incidence. However, HIV drug resistance (HIVDR) poses a potential threat to the long-term success of ART and is emerging as a threat to the elimination of AIDS as a public health problem by 2030. In this review we describe the genetic mechanisms, epidemiology, and management of HIVDR at both individual and population levels across diverse economic and geographic settings. To describe the genetic mechanisms of HIVDR, we review the genetic barriers to resistance for the most commonly used ARVs and describe the extent of cross-resistance between them. To describe the epidemiology of HIVDR, we summarize the prevalence and patterns of transmitted drug resistance (TDR) and acquired drug resistance (ADR) in both high-income and low- and middle-income countries (LMICs). We also review to two categories of HIVDR with important public health relevance: (i) pre-treatment drug resistance (PDR), a World Health Organization-recommended HIVDR surveillance metric and (ii) and pre-exposure prophylaxis (PrEP)-related drug resistance, a type of ADR that can impact clinical outcomes if present at the time of treatment initiation. To summarize the implications of HIVDR for patient management, we review the role of genotypic resistance testing and treatment practices in both high-income and LMIC settings. In high-income countries where drug resistance testing is part of routine care, such an understanding can help clinicians prevent virological failure and accumulation of further HIVDR on an individual level by selecting the most efficacious regimens for their patients. Although there is reduced access to diagnostic testing and to many ARVs in LMIC, understanding the scientific basis and clinical implications of HIVDR is useful in all regions in order to shape appropriate surveillance, inform treatment algorithms, and manage difficult cases.

Minimal Contribution of APOBEC3-Induced G-to-A Hypermutation to HIV-1 Recombination and Genetic Variation

Although the predominant effect of host restriction APOBEC3 proteins on HIV-1 infection is to block viral replication, they might inadvertently increase retroviral genetic variation by inducing G-to-A hypermutation. Numerous studies have disagreed on the contribution of hypermutation to viral genetic diversity and evolution. Confounding factors contributing to the debate include the extent of lethal (stop codon) and sublethal hypermutation induced by different APOBEC3 proteins, the inability to distinguish between G-to-A mutations induced by APOBEC3 proteins and error-prone viral replication, the potential impact of hypermutation on the frequency of retroviral recombination, and the extent to which viral recombination occurs in vivo, which can reassort mutations in hypermutated genomes. Here, we determined the effects of hypermutation on the HIV-1 recombination rate and its contribution to genetic variation through recombination to generate progeny genomes containing portions of hypermutated genomes without lethal mutations. We found that hypermutation did not significantly affect the rate of recombination, and recombination between hypermutated and wild-type genomes only increased the viral mutation rate by 3.9 × 10-5 mutations/bp/replication cycle in heterozygous virions, which is similar to the HIV-1 mutation rate. Since copackaging of hypermutated and wild-type genomes occurs very rarely in vivo, recombination between hypermutated and wild-type genomes does not significantly contribute to the genetic variation of replicating HIV-1. We also analyzed previously reported hypermutated sequences from infected patients and determined that the frequency of sublethal mutagenesis for A3G and A3F is negligible (4 × 10-21 and1 × 10-11, respectively) and its contribution to viral mutations is far below mutations generated during error-prone reverse transcription. Taken together, we conclude that the contribution of APOBEC3-induced hypermutation to HIV-1 genetic variation is substantially lower than that from mutations during error-prone replication.

HIV-1 Mutation and Recombination Rates Are Different in Macrophages and T-cells

High rates of mutation and recombination help human immunodeficiency virus (HIV) to evade the immune system and develop resistance to antiretroviral therapy. Macrophages and T-cells are the natural target cells of HIV-1 infection. A consensus has not been reached as to whether HIV replication results in differential recombination between primary T-cells and macrophages. Here, we used HIV with silent mutation markers along with next generation sequencing to compare the mutation and the recombination rates of HIV directly in T lymphocytes and macrophages. We observed a more than four-fold higher recombination rate of HIV in macrophages compared to T-cells (p < 0.001) and demonstrated that this difference is not due to different reliance on C-X-C chemokine receptor type 4 (CXCR4) and C-C chemokine receptor type 5 (CCR5) co-receptors between T-cells and macrophages. We also found that the pattern of recombination across the HIV genome (hot and cold spots) remains constant between T-cells and macrophages despite a three-fold increase in the overall recombination rate. This indicates that the difference in rates is a general feature of HIV DNA synthesis during macrophage infection. In contrast to HIV recombination, we found that T-cells have a 30% higher mutation rate than macrophages (p < 0.001) and that the mutational profile is similar between these cell types. Unexpectedly, we found no association between mutation and recombination in macrophages, in contrast to T-cells. Our data highlights some of the fundamental difference of HIV recombination and mutation amongst these two major target cells of infection. Understanding these differences will provide invaluable insights toward HIV evolution and how the virus evades immune surveillance and anti-retroviral therapeutics.

Reverse Transcription of Retroviruses and LTR Retrotransposons

The enzyme reverse transcriptase (RT) was discovered in retroviruses almost 50 years ago. The demonstration that other types of viruses, and what are now called retrotransposons, also replicated using an enzyme that could copy RNA into DNA came a few years later. The intensity of the research in both the process of reverse transcription and the enzyme RT was greatly stimulated by the recognition, in the mid-1980s, that human immunodeficiency virus (HIV) was a retrovirus and by the fact that the first successful anti-HIV drug, azidothymidine (AZT), is a substrate for RT. Although AZT monotherapy is a thing of the past, the most commonly prescribed, and most successful, combination therapies still involve one or both of the two major classes of anti-RT drugs. Although the basic mechanics of reverse transcription were worked out many years ago, and the first high-resolution structures of HIV RT are now more than 20 years old, we still have much to learn, particularly about the roles played by the host and viral factors that make the process of reverse transcription much more efficient in the cell than in the test tube. Moreover, we are only now beginning to understand how various host factors that are part of the innate immunity system interact with the process of reverse transcription to protect the host-cell genome, the host cell, and the whole host, from retroviral infection, and from unwanted retrotransposition.

Rapid Determination of HIV-1 Mutant Frequencies and Mutation Spectra Using an mCherry/EGFP Dual-Reporter Viral Vector

The high mutation rate of human immunodeficiency virus type-1 (HIV-1) has been a pivotal factor in its evolutionary success as a human pathogen, driving the emergence of drug resistance, immune system escape, and invasion of distinct anatomical compartments. Extensive research has focused on understanding how various cellular and viral factors alter the rates and types of mutations produced during viral replication. Here, we describe a single-cycle dual-reporter vector assay that relies upon the detection of mutations that eliminate either expression of mCherry or enhanced green fluorescent protein (EGFP). The reporter-based method can be used to efficiently quantify changes in mutant frequencies and mutation spectra that arise due to a variety of factors, including viral mutagens, drug resistance mutations, cellular physiology, and APOBEC3 proteins.

Recombination Enhances HIV-1 Envelope Diversity by Facilitating the Survival of Latent Genomic Fragments in the Plasma Virus Population

HIV-1 is subject to immune pressure exerted by the host, giving variants that escape the immune response an advantage. Virus released from activated latent cells competes against variants that have continually evolved and adapted to host immune pressure. Nevertheless, there is increasing evidence that virus displaying a signal of latency survives in patient plasma despite having reduced fitness due to long-term immune memory. We investigated the survival of virus with latent envelope genomic fragments by simulating within-host HIV-1 sequence evolution and the cycling of viral lineages in and out of the latent reservoir. Our model incorporates a detailed mutation process including nucleotide substitution, recombination, latent reservoir dynamics, diversifying selection pressure driven by the immune response, and purifying selection pressure asserted by deleterious mutations. We evaluated the ability of our model to capture sequence evolution in vivo by comparing our simulated sequences to HIV-1 envelope sequence data from 16 HIV-infected untreated patients. Empirical sequence divergence and diversity measures were qualitatively and quantitatively similar to those of our simulated HIV-1 populations, suggesting that our model invokes realistic trends of HIV-1 genetic evolution. Moreover, reconstructed phylogenies of simulated and patient HIV-1 populations showed similar topological structures. Our simulation results suggest that recombination is a key mechanism facilitating the persistence of virus with latent envelope genomic fragments in the productively infected cell population. Recombination increased the survival probability of latent virus forms approximately 13-fold. Prevalence of virus with latent fragments in productively infected cells was observed in only 2% of simulations when we ignored recombination, while the proportion increased to 27% of simulations when we allowed recombination. We also found that the selection pressures exerted by different fitness landscapes influenced the shape of phylogenies, diversity trends, and survival of virus with latent genomic fragments. Our model predicts that the persistence of latent genomic fragments from multiple different ancestral origins increases sequence diversity in plasma for reasonable fitness landscapes.

Increasing evidence suggests that HIV-1 released from activated latent cells survives in productively infected cells in patient plasma despite competition against better adapted virus variants that have evolved in response to the host immune pressure. Long-term survival requires that latent virus forms adapt to the host immune response so that they are not outcompeted. We simulated the dynamics of HIV-1 envelope sequence evolution in response to host immune pressure to investigate how virus from activated latent cells can survive despite having reduced fitness compared to the more evolved virus variants in patient plasma. The evolutionary trends of our simulated virus populations followed closely those observed in HIV-1 sequence data from 16 patients. Our simulation results suggest that recombination facilitates the survival of genomic fragments originating from virus activated from latent cells. Our model further predicts that sequence diversity increases with the number of latent genomic fragments from different origins that persist in plasma.

Broad CTL Response in Early HIV Infection Drives Multiple Concurrent CTL Escapes

Recent studies have highlighted the ability of HIV to escape from cytotoxic T lymphocyte (CTL) responses that concurrently target multiple viral epitopes. Yet, the viral dynamics involved in such escape are incompletely understood. Previous analyses have made several strong assumptions regarding HIV escape from CTL responses such as independent or non-concurrent escape from individual CTL responses. Using experimental data from evolution of HIV half genomes in four patients we observe concurrent viral escape from multiple CTL responses during early infection (first 100 days of infection), providing confirmation of a recent result found in a study of one HIV-infected patient. We show that current methods of estimating CTL escape rates, based on the assumption of independent escapes, are biased and perform poorly when CTL escape proceeds concurrently at multiple epitopes. We propose a new method for analyzing longitudinal sequence data to estimate the rate of CTL escape across multiple epitopes; this method involves few parameters and performs well in simulation studies. By applying our novel method to experimental data, we find that concurrent multiple escapes occur at rates between 0.03 and 0.4 day⁻¹, a relatively broad range that reflects uncertainty due to sparse sampling and wide ranges of parameter values. However, we show that concurrent escape at rates 0.1–0.2 day⁻¹ across multiple epitopes is consistent with our patient datasets.

Since the early 1990s, cytotoxic T lymphocytes (CTLs) have been known to play an important role in HIV infection with CTLs targeting HIV epitopes and, in turn, HIV escapes arising through mutations in the targeted epitopes. Over the past decade, studies have shown that CTL responses concurrently target multiple HIV epitopes, yet the effect of concurrent responses on HIV dynamics and evolution is not well understood. Through an analysis of patient datasets and a novel statistical method, we show that during early HIV infection concurrent CTL responses drive concurrent HIV escapes at multiple epitopes with significant pressure, suggesting a complex picture in which HIV simultaneously explores multiple mutational pathways to escape from broad and potent CTL response.

Lack of mutational hot spots during decitabine-mediated HIV-1 mutagenesis

Decitabine has previously been shown to induce lethal mutagenesis of human immunodeficiency virus type 1 (HIV-1). However, the factors that determine the susceptibilities of individual sequence positions in HIV-1 to decitabine have not yet been defined. To investigate this, we performed Illumina high-throughput sequencing of multiple amplicons prepared from proviral DNA that was recovered from decitabine-treated cells infected with HIV-1. We found that decitabine induced an ≈4.1-fold increase in the total mutation frequency of HIV-1, primarily due to a striking ≈155-fold increase in the G-to-C transversion frequency. Intriguingly, decitabine also led to an ≈29-fold increase in the C-to-G transversion frequency. G-to-C frequencies varied substantially (up to ≈80-fold) depending upon sequence position, but surprisingly, mutational hot spots (defined as upper outliers within the mutation frequency distribution) were not observed. We further found that every single guanine position examined was significantly susceptible to the mutagenic effects of decitabine. Taken together, these observations demonstrate for the first time that decitabine-mediated HIV-1 mutagenesis is promiscuous and occurs in the absence of a clear bias for mutational hot spots. These data imply that decitabine-mediated G-to-C mutagenesis is a highly effective antiviral mechanism for extinguishing HIV-1 infectivity.

HIV-1 and HIV-2 exhibit similar mutation frequencies and spectra in the absence of G-to-A hypermutation

BACKGROUND

Human immunodeficiency virus type 2 (HIV-2) is often distinguished clinically by lower viral loads, reduced transmissibility, and longer asymptomatic periods than for human immunodeficiency virus type 1 (HIV-1). Differences in the mutation frequencies of HIV-1 and HIV-2 have been hypothesized to contribute to the attenuated progression of HIV-2 observed clinically.

RESULTS

To address this hypothesis, we performed Illumina sequencing of multiple amplicons prepared from cells infected with HIV-1 or HIV-2, resulting in ~4.7 million read pairs and the identification of ~200,000 mutations after data processing. We observed that: (1) HIV-2 displayed significantly lower total mutation, substitution, and transition mutation frequencies than that of HIV-1, along with a mutation spectrum markedly less biased toward G-to-A transitions, (2) G-to-A hypermutation consistent with the activity of APOBEC3 proteins was observed for both HIV-1 and HIV-2 despite the presence of Vif, (3) G-to-A hypermutation was significantly higher for HIV-1 than for HIV-2, and (4) HIV-1 and HIV-2 total mutation frequencies were not significantly different in the absence of G-to-A hypermutants.

CONCLUSIONS

Taken together, these data demonstrate that HIV-2 exhibits a distinct mutational spectrum and a lower mutation frequency relative to HIV-1. However, the observed differences were primarily due to reduced levels of G-to-A hypermutation for HIV-2. These findings suggest that HIV-2 may be less susceptible than HIV-1 to APOBEC3-mediated hypermutation, but that the fidelities of other mutational sources (such as reverse transcriptase) are relatively similar for HIV-1 and HIV-2. Overall, these data imply that differences in replication fidelity are likely not a major contributing factor to the unique clinical features of HIV-2 infection.

High-throughput profiling of point mutations across the HIV-1 genome

Background

The HIV-1 pandemic is not the result of a static pathogen but a large genetically diverse and dynamic viral population. The virus is characterized by a highly mutable genome rendering efforts to design a universal vaccine a significant challenge and drives the emergence of drug resistant variants upon antiviral pressure. Gaining a comprehensive understanding of the mutational tolerance of each HIV-1 genomic position is therefore of critical importance.

Results

Here we combine high-density mutagenesis with the power of next-generation sequencing to gauge the replication capacity and therefore mutational tolerability of single point mutations across the entire HIV-1 genome. We were able to achieve the evaluation of point mutational effects on viral replicative capacity for 5,553 individual HIV-1 nucleotide positions – representing 57% of the viral genome. Replicative capacity was assessed at 3,943 nucleotide positions for a single alternate base change, 1,459 nucleotide positions for two alternate base changes, and 151 nucleotide positions for all three possible alternate base changes. This resulted in the study of how a total of 7,314 individual point mutations impact HIV-1 replication on a single experimental platform. We further utilize the dataset for a focused structural analysis on a capsid inhibitor binding pocket.

Conclusion

The approach presented here can be applied to any pathogen that can be genetically manipulated in a laboratory setting. Furthermore, the methodology can be utilized under externally applied selection conditions, such as drug or immune pressure, to identify genetic elements that contribute to drug or host interactions, and therefore mutational routes of pathogen resistance and escape.

Electronic supplementary material

The online version of this article (doi:10.1186/s12977-014-0124-6) contains supplementary material, which is available to authorized users.

Retroviral vectors for analysis of viral mutagenesis and recombination

Retrovirus population diversity within infected hosts is commonly high due in part to elevated rates of replication, mutation, and recombination. This high genetic diversity often complicates the development of effective diagnostics, vaccines, and antiviral drugs. This review highlights the diverse vectors and approaches that have been used to examine mutation and recombination in retroviruses. Retroviral vectors for these purposes can broadly be divided into two categories: those that utilize reporter genes as mutation or recombination targets and those that utilize viral genes as targets of mutation or recombination. Reporter gene vectors greatly facilitate the detection, quantification, and characterization of mutants and/or recombinants, but may not fully recapitulate the patterns of mutagenesis or recombination observed in native viral gene sequences. In contrast, the detection of mutations or recombination events directly in viral genes is more biologically relevant but also typically more challenging and inefficient. We will highlight the advantages and disadvantages of the various vectors and approaches used as well as propose ways in which they could be improved.

Short communication: HIV-1 gag genetic variation in a single acutely infected participant defined by high-resolution deep sequencing

Acute HIV-1 infection is characterized by the rapid generation of highly diverse genetic variants to adapt to the new host environment. Understanding the dynamics of viral genetic variation at this stage of infection is critical for vaccine design efforts and early drug treatment. Here, using a high-resolution deep sequencing approach targeting the HIV-1 gag region, we reveal very early immune pressure with dramatic subpopulation shifts in a single acutely infected participant providing further insight into the genetic dynamics of acute HIV-1 infection.

Mutations in HIV-1 reverse transcriptase affect the errors made in a single cycle of viral replication

The genetic variation in HIV-1 in patients is due to the high rate of viral replication, the high viral load, and the errors made during viral replication. Some of the mutations in reverse transcriptase (RT) that alter the deoxynucleoside triphosphate (dNTP)-binding pocket, including those that confer resistance to nucleoside/nucleotide analogs, affect dNTP selection during replication. The effects of mutations in RT on the spectrum (nature, position, and frequency) of errors made in vivo are poorly understood. We previously determined the mutation rate and the frequency of different types of mutations and identified hot spots for mutations in a lacZα (the α complementing region of lacZ) reporter gene carried by an HIV-1 vector that replicates using wild-type RT. We show here that four mutations (Y115F, M184V, M184I, and Q151M) in the dNTP-binding pocket of RT that had relatively small effects on the overall HIV-1 mutation rate (less than 3-fold compared to the wild type) significantly increased mutations at some specific positions in the lacZα reporter gene. We also show that changes in a sequence that flanks the reporter gene can affect the mutations that arise in the reporter. These data show that changes either in HIV-1 RT or in the sequence of the nucleic acid template can affect the spectrum of mutations made during viral replication. This could, by implication, affect the generation of drug-resistant mutants and immunological-escape mutants in patients.

IMPORTANCE

RT is the viral enzyme that converts the RNA genome of HIV into DNA. Errors made during replication allow the virus to escape from the host's immune system and to develop resistance to the available anti-HIV drugs. We show that four different mutations in RT which are known to be associated with resistance to anti-RT drugs modestly increased the overall frequency of errors made during viral replication. However, the increased errors were not uniformly distributed; the additional errors occurred at a small number of positions (hot spots). Moreover, some of the RT mutations preferentially affected the nature of the errors that were made (some RT mutations caused an increase in insertion and deletion errors; others caused an increase in substitution errors). We also show that sequence changes in a region adjacent to a target gene can affect the errors made within the target gene.

Constructing lower-bounds for CTL escape rates in early SIV infection

Intrahost human and simian immunodeficiency virus (HIV and SIV) evolution is marked by repeated viral escape from cytotoxic T-lymphocyte (CTL) response. Typically, the first such CTL escape starts around the time of peak viral load and completes within one or two weeks. Many authors have developed methods to quantify CTL escape rates, but existing methods depend on sampling at two or more timepoints. Since many datasets capture the dynamics of the first CTL escape at a single timepoint, we develop inference methods applicable to single timepoint datasets. To account for model uncertainty, we construct estimators which serve as lower bounds for the escape rate. These lower-bound estimators allow for statistically meaningful comparison of escape rates across different times and different compartments. We apply our methods to two SIV datasets, showing that escape rates are relatively high during the initial days of the first CTL escape and drop to lower levels as the escape proceeds.

Fifteen to twenty percent of HIV substitution mutations are associated with recombination

HIV undergoes high rates of mutation and recombination during reverse transcription, but it is not known whether these events occur independently or are linked mechanistically. Here we used a system of silent marker mutations in HIV and a single round of infection in primary T lymphocytes combined with a high-throughput sequencing and mathematical modeling approach to directly estimate the viral recombination and mutation rates. From >7 million nucleotides (nt) of sequences from HIV infection, we observed 4,801 recombination events and 859 substitution mutations (≈1.51 and 0.12 events per 1,000 nt, respectively). We used experimental controls to account for PCR-induced and transfection-induced recombination and sequencing error. We found that the single-cycle virus-induced mutation rate is 4.6 × 10(-5) mutations per nt after correction. By sorting of our data into recombined and nonrecombined sequences, we found a significantly higher mutation rate in recombined regions (P = 0.003 by Fisher's exact test). We used a permutation approach to eliminate a number of potential confounding factors and confirm that mutation occurs around the site of recombination and is not simply colocated in the genome. By comparing mutation rates in recombined and nonrecombined regions, we found that recombination-associated mutations account for 15 to 20% of all mutations occurring during reverse transcription.

Identifying recombination hot spots in the HIV-1 genome

HIV-1 infection is characterized by the rapid generation of genetic diversity that facilitates viral escape from immune selection and antiretroviral therapy. Despite recombination's crucial role in viral diversity and evolution, little is known about the genomic factors that influence recombination between highly similar genomes. In this study, we use a minimally modified full-length HIV-1 genome and high-throughput sequence analysis to study recombination in gag and pol in T cells. We find that recombination is favored at a number of recombination hot spots, where recombination occurs six times more frequently than at corresponding cold spots. Interestingly, these hot spots occur near important features of the HIV-1 genome but do not occur at sites immediately around protease inhibitor or reverse transcriptase inhibitor drug resistance mutations. We show that the recombination hot and cold spots are consistent across five blood donors and are independent of coreceptor-mediated entry. Finally, we check common experimental confounders and find that these are not driving the location of recombination hot spots. This is the first study to identify the location of recombination hot spots between two similar viral genomes with great statistical power and under conditions that closely reflect natural recombination events among HIV-1 quasispecies.

IMPORTANCE

The ability of HIV-1 to evade the immune system and antiretroviral therapy depends on genetic diversity within the viral quasispecies. Retroviral recombination is an important mechanism that helps to generate and maintain this genetic diversity, but little is known about how recombination rates vary within the HIV-1 genome. We measured recombination rates in gag and pol and identified recombination hot and cold spots, demonstrating that recombination is not random but depends on the underlying gene sequence. The strength and location of these recombination hot and cold spots can be used to improve models of viral dynamics and evolution, which will be useful for the design of robust antiretroviral therapies.

QColors: an algorithm for conservative viral quasispecies reconstruction from short and non-contiguous next generation sequencing reads

Next generation sequencing technologies have recently been applied to characterize mutational spectra of the heterogeneous population of viral genotypes (known as a quasispecies) within HIV-infected patients. Such information is clinically relevant because minority genetic subpopulations of HIV within patients enable viral escape from selection pressures such as the immune response and antiretroviral therapy. However, methods for quasispecies sequence reconstruction from next generation sequencing reads are not yet widely used and remains an emerging area of research. Furthermore, the majority of research methodology in HIV has focused on 454 sequencing, while many next-generation sequencing platforms used in practice are limited to shorter read lengths relative to 454 sequencing. Little work has been done in determining how best to address the read length limitations of other platforms. The approach described here incorporates graph representations of both read differences and read overlap to conservatively determine the regions of the sequence with sufficient variability to separate quasispecies sequences. Within these tractable regions of quasispecies inference, we use constraint programming to solve for an optimal quasispecies subsequence determination via vertex coloring of the conflict graph, a representation which also lends itself to data with non-contiguous reads such as paired-end sequencing. We demonstrate the utility of the method by applying it to simulations based on actual intra-patient clonal HIV-1 sequencing data.

Computational inference methods for selective sweeps arising in acute HIV infection

During the first weeks of human immunodeficiency virus-1 (HIV-1) infection, cytotoxic T-lymphocytes (CTLs) select for multiple escape mutations in the infecting HIV population. In recent years, methods that use escape mutation data to estimate rates of HIV escape have been developed, thereby providing a quantitative framework for exploring HIV escape from CTL response. Current methods for escape-rate inference focus on a specific HIV mutant selected by a single CTL response. However, recent studies have shown that during the first weeks of infection, CTL responses occur at one to three epitopes and HIV escape occurs through complex mutation pathways. Consequently, HIV escape from CTL response forms a complex, selective sweep that is difficult to analyze. In this work, we develop a model of initial infection, based on the well-known standard model, that allows for a description of multi-epitope response and the complex mutation pathways of HIV escape. Under this model, we develop Bayesian and hypothesis-test inference methods that allow us to analyze and estimate HIV escape rates. The methods are applied to two HIV patient data sets, concretely demonstrating the utility of our approach.

Variation of HIV-1 mutation spectra among cell types

The high rates of mutation, recombination, and replication drive HIV-1 diversity. In this study, we investigated how cell type affects viral mutation rate and mutation spectra. In studying four different cell types, no differences in mutation rate were observed, but intriguingly cell type differences impacted HIV-1 mutation spectra. This is the first description of significant differences in HIV-1 mutation spectra observed in different cell types in the absence of changes in the viral mutation rate.

Comparison of the Mechanisms of Drug Resistance among HIV, Hepatitis B, and Hepatitis C

Human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV) are the most prevalent deadly chronic viral diseases. HIV is treated by small molecule inhibitors. HBV is treated by immunomodulation and small molecule inhibitors. HCV is currently treated primarily by immunomodulation but many small molecules are in clinical development. Although HIV is a retrovirus, HBV is a double-stranded DNA virus, and HCV is a single-stranded RNA virus, antiviral drug resistance complicates the development of drugs and the successful treatment of each of these viruses. Although their replication cycles, therapeutic targets, and evolutionary mechanisms are different, the fundamental approaches to identifying and characterizing HIV, HBV, and HCV drug resistance are similar. This review describes the evolution of HIV, HBV, and HCV within individuals and populations and the genetic mechanisms associated with drug resistance to each of the antiviral drug classes used for their treatment.

The origin of genetic diversity in HIV-1

One of the hallmarks of HIV infection is the rapid development of a genetically complex population (quasispecies) from an initially limited number of infectious particles. Genetic diversity remains one of the major obstacles to eradication of HIV. The viral quasispecies can respond rapidly to selective pressures, such as that imposed by the immune system and antiretroviral therapy, and frustrates vaccine design efforts. Two unique features of retroviral replication are responsible for the unprecedented variation generated during infection. First, mutations are frequently introduced into the viral genome by the error prone viral reverse transcriptase and through the actions of host cellular factors, such as the APOBEC family of nucleic acid editing enzymes. Second, the HIV reverse transcriptase can utilize both copies of the co-packaged viral genome in a process termed retroviral recombination. When the co-packaged viral genomes are genetically different, retroviral recombination can lead to the shuffling of mutations between viral genomes in the quasispecies. This review outlines the stages of the retroviral life cycle where genetic variation is introduced, focusing on the principal mechanisms of mutation and recombination. Understanding the mechanistic origin of genetic diversity is essential to combating HIV.

Optimal antiviral switching to minimize resistance risk in HIV therapy

The development of resistant strains of HIV is the most significant barrier to effective long-term treatment of HIV infection. The most common causes of resistance development are patient noncompliance and pre-existence of resistant strains. In this paper, methods of antiviral regimen switching are developed that minimize the risk of pre-existing resistant virus emerging during therapy switches necessitated by virological failure. Two distinct cases are considered; a single previous virological failure and multiple virological failures. These methods use optimal control approaches on experimentally verified mathematical models of HIV strain competition and statistical models of resistance risk. It is shown that, theoretically, order-of-magnitude reduction in risk can be achieved, and multiple previous virological failures enable greater success of these methods in reducing the risk of subsequent treatment failures.

Fitness costs and diversity of the cytotoxic T lymphocyte (CTL) response determine the rate of CTL escape during acute and chronic phases of HIV infection

HIV-1 often evades cytotoxic T cell (CTL) responses by generating variants that are not recognized by CTLs. We used single-genome amplification and sequencing of complete HIV genomes to identify longitudinal changes in the transmitted/founder virus from the establishment of infection to the viral set point at 1 year after the infection. We found that the rate of viral escape from CTL responses in a given patient decreases dramatically from acute infection to the viral set point. Using a novel mathematical model that tracks the dynamics of viral escape at multiple epitopes, we show that a number of factors could potentially contribute to a slower escape in the chronic phase of infection, such as a decreased magnitude of epitope-specific CTL responses, an increased fitness cost of escape mutations, or an increased diversity of the CTL response. In the model, an increase in the number of epitope-specific CTL responses can reduce the rate of viral escape from a given epitope-specific CTL response, particularly if CD8+ T cells compete for killing of infected cells or control virus replication nonlytically. Our mathematical framework of viral escape from multiple CTL responses can be used to predict the breadth and magnitude of HIV-specific CTL responses that need to be induced by vaccination to reduce (or even prevent) viral escape following HIV infection.

Clinical significance of HIV reverse-transcriptase inhibitor-resistance mutations

In this article, we summarize recent knowledge on drug-resistance mutations within HIV reverse transcriptase (RT). Several large-scale HIV-1 genotypic analyses have revealed that the most prevalent nucleos(t)ide analog RT inhibitor (NRTI)-resistance mutation is M184V/I followed by a series of thymidine analog-associated mutations: M41L, D67N, K70R, L210W, T215Y/F and K219Q/E. Among non-nucleoside RT inhibitor (NNRTI)-resistance mutations, K103N was frequently observed, followed by Y181C and G190A. Interestingly, V106M was identified in HIV-1 subtype C as a subtype-specific multi-NNRTI-resistance mutation. Regarding mutations in the HIV-1 RT C-terminal region, including the connection subdomain and RNase H domain, their clinical impacts are still controversial, although their effects on NRTI and NNRTI resistance have been confirmed in vitro. In HIV-2 infections, the high prevalence of the Q151M mutation associated with multi-NRTI resistance has been frequently observed.

Controlling the Evolution of Resistance

Evolution has long been understood as the driving force for many problems of medical interest. The evolution of drug resistance in HIV and bacterial infections is recognized as one of the most significant emerging problems in medicine. In cancer therapy, the evolution of resistance to chemotherapeutic agents is often the differentiating factor between effective therapy and disease progression or death. Interventions to manage the evolution of resistance have, up to this point, been based on steady-state analysis of mutation and selection models. In this paper, we review the mathematical methods applied to studying evolution of resistance in disease. We present a broad review of several classical applications of mathematical modeling of evolution, and review in depth two recent problems which demonstrate the potential for interventions which exploit the dynamic behavior of resistance evolution models. The first problem addresses the problem of sequential treatment failures in HIV; we present a review of our recent publications addressing this problem. The second problem addresses a novel approach to gene therapy for pancreatic cancer treatment, where selection is used to encourage optimal spread of susceptibility genes through a target tumor, which is then eradicated during a second treatment phase. We review the recent in Vitro laboratory work on this topic, present a new mathematical model to describe the treatment process, and show why model-based approaches will be necessary to successfully implement this novel and promising approach.

Nature, position, and frequency of mutations made in a single cycle of HIV-1 replication

There is considerable HIV-1 variation in patients. The extent of the variation is due to the high rate of viral replication, the high viral load, and the errors made during viral replication. Mutations can arise from errors made either by host DNA-dependent RNA polymerase II or by HIV-1 reverse transcriptase (RT), but the relative contributions of these two enzymes to the mutation rate are unknown. In addition, mutations in RT can affect its fidelity, but the effect of mutations in RT on the nature of the mutations that arise in vivo is poorly understood. We have developed an efficient system, based on existing technology, to analyze the mutations that arise in an HIV-1 vector in a single cycle of replication. A lacZalpha reporter gene is used to identify viral DNAs that contain mutations which are analyzed by DNA sequencing. The forward mutation rate in this system is 1.4 x 10(-5) mutations/bp/cycle, equivalent to the retroviral average. This rate is about 3-fold lower than previously reported for HIV-1 in vivo and is much lower than what has been reported for purified HIV-1 RT in vitro. Although the mutation rate was not affected by the orientation of lacZalpha, the sites favored for mutations (hot spots) in lacZalpha depended on which strand of lacZalpha was present in the viral RNA. The pattern of hot spots seen in lacZalpha in vivo did not match any of the published data obtained when purified RT was used to copy lacZalpha in vitro.

Mutation rates and intrinsic fidelity of retroviral reverse transcriptases

Retroviruses are RNA viruses that replicate through a DNA intermediate, in a process catalyzed by the viral reverse transcriptase (RT). Although cellular polymerases and host factors contribute to retroviral mutagenesis, the RT errors play a major role in retroviral mutation. RT mutations that affect the accuracy of the viral polymerase have been identified by in vitro analysis of the fidelity of DNA synthesis, by using enzymological (gel-based) and genetic assays (e.g., M13mp2 lacZ forward mutation assays). For several amino acid substitutions, these observations have been confirmed in cell culture using viral vectors. This review provides an update on studies leading to the identification of the major components of the fidelity center in retroviral RTs.

Modeling sequence evolution in acute HIV-1 infection

We describe a mathematical model and Monte Carlo (MC) simulation of viral evolution during acute infection. We consider both synchronous and asynchronous processes of viral infection of new target cells. The model enables an assessment of the expected sequence diversity in new HIV-1 infections originating from a single transmitted viral strain, estimation of the most recent common ancestor (MRCA) of the transmitted viral lineage, and estimation of the time to coalesce back to the MRCA. We also calculate the probability of the MRCA being the transmitted virus or an evolved variant. Excluding insertions and deletions, we assume HIV-1 evolves by base substitution without selection pressure during the earliest phase of HIV-1 infection prior to the immune response. Unlike phylogenetic methods that follow a lineage backwards to coalescence, we compare the observed data to a model of the diversification of a viral population forward in time. To illustrate the application of these methods, we provide detailed comparisons of the model and simulations results to 306 envelope sequences obtained from eight newly infected subjects at a single time point. The data from 68 patients were in good agreement with model predictions, and hence compatible with a single-strain infection evolving under no selection pressure. The diversity of the samples from the other two patients was too great to be explained by the model, suggesting multiple HIV-1-strains were transmitted. The model can also be applied to longitudinal patient data to estimate within-host viral evolutionary parameters.

Emerging and re-emerging viruses in Malaysia, 1997-2007

Over the past decade, a number of unique zoonotic and non-zoonotic viruses have emerged in Malaysia. Several of these viruses have resulted in significant morbidity and mortality to those affected and they have imposed a tremendous public health and economic burden on the state. Amongst the most devastating was the outbreak of Nipah virus encephalitis in 1998, which resulted in 109 deaths. The culling of more than a million pigs, identified as the amplifying host, ultimately brought the outbreak under control. A year prior to this, and subsequently again in 2000 and 2003, large outbreaks of hand-foot-and-mouth disease due to enterovirus 71, with rare cases of fatal neurological complications, were reported in young children. Three other new viruses – Tioman virus (1999), Pulau virus (1999), and Melaka virus (2006) – whose origins have all been linked to bats, have been added to the growing list of novel viruses being discovered in Malaysia. The highly pathogenic H5N1 avian influenza has also been detected in Malaysia with outbreaks in poultry in 2004, 2006, and 2007. Fortunately, no human infections were reported. Finally, the HIV/AIDS epidemic has seen the emergence of an HIV-1 recombinant form (CRF33_01B) in HIV-infected individuals from various risk groups, with evidence of ongoing and rapid expansion.

HLA class I-driven evolution of human immunodeficiency virus type 1 subtype c proteome: immune escape and viral load

Human immunodeficiency virus type 1 (HIV-1) mutations that confer escape from cytotoxic T-lymphocyte (CTL) recognition can sometimes result in lower viral fitness. These mutations can then revert upon transmission to a new host in the absence of CTL-mediated immune selection pressure restricted by the HLA alleles of the prior host. To identify these potentially critical recognition points on the virus, we assessed HLA-driven viral evolution using three phylogenetic correction methods across full HIV-1 subtype C proteomes from a cohort of 261 South Africans and identified amino acids conferring either susceptibility or resistance to CTLs. A total of 558 CTL-susceptible and -resistant HLA-amino acid associations were identified and organized into 310 immunological sets (groups of individual associations related to a single HLA/epitope combination). Mutations away from seven susceptible residues, including four in Gag, were associated with lower plasma viral-RNA loads (q < 0.2 [where q is the expected false-discovery rate]) in individuals with the corresponding HLA alleles. The ratio of susceptible to resistant residues among those without the corresponding HLA alleles varied in the order Vpr > Gag > Rev > Pol > Nef > Vif > Tat > Env > Vpu (Fisher's exact test; P < or = 0.0009 for each comparison), suggesting the same ranking of fitness costs by genes associated with CTL escape. Significantly more HLA-B (chi(2); P = 3.59 x 10(-5)) and HLA-C (chi(2); P = 4.71 x 10(-6)) alleles were associated with amino acid changes than HLA-A, highlighting their importance in driving viral evolution. In conclusion, specific HIV-1 residues (enriched in Vpr, Gag, and Rev) and HLA alleles (particularly B and C) confer susceptibility to the CTL response and are likely to be important in the development of vaccines targeted to decrease the viral load.