A hybrid stochastic-deterministic approach to explore multiple infection and evolution in HIV

To study viral evolutionary processes within patients, mathematical models have been instrumental. Yet, the need for stochastic simulations of minority mutant dynamics can pose computational challenges, especially in heterogeneous systems where very large and very small sub-populations coexist. Here, we describe a hybrid stochastic-deterministic algorithm to simulate mutant evolution in large viral populations, such as acute HIV-1 infection, and further include the multiple infection of cells. We demonstrate that the hybrid method can approximate the fully stochastic dynamics with sufficient accuracy at a fraction of the computational time, and quantify evolutionary end points that cannot be expressed by deterministic models, such as the mutant distribution or the probability of mutant existence at a given infected cell population size. We apply this method to study the role of multiple infection and intracellular interactions among different virus strains (such as complementation and interference) for mutant evolution. Multiple infection is predicted to increase the number of mutants at a given infected cell population size, due to a larger number of infection events. We further find that viral complementation can significantly enhance the spread of disadvantageous mutants, but only in select circumstances: it requires the occurrence of direct cell-to-cell transmission through virological synapses, as well as a substantial fitness disadvantage of the mutant, most likely corresponding to defective virus particles. This, however, likely has strong biological consequences because defective viruses can carry genetic diversity that can be incorporated into functional virus genomes via recombination. Through this mechanism, synaptic transmission in HIV might promote virus evolvability.     

Persistent infection and promiscuous recombination of multiple genotypes of an RNA virus within a single host generate extensive diversity

Recombination and reassortment of viral genomes are major processes contributing to the creation of new, emerging viruses. These processes are especially significant in long-term persistent infections where multiple viral genotypes co-replicate in a single host, generating abundant genotypic variants, some of which may possess novel host-colonizing and pathogenicity traits. In some plants, successive vegetative propagation of infected tissues and introduction of new genotypes of a virus by vector transmission allows for viral populations to increase in complexity for hundreds of years allowing co-replication and subsequent recombination of the multiple viral genotypes. Using a resequencing microarray, we examined a persistent infection by a Citrus tristeza virus (CTV) complex in citrus, a vegetatively propagated, globally important fruit crop, and found that the complex comprised three major and a number of minor genotypes. Subsequent deep sequencing analysis of the viral population confirmed the presence of the three major CTV genotypes and, in addition, revealed that the minor genotypes consisted of an extraordinarily large number of genetic variants generated by promiscuous recombination between the major genotypes. Further analysis provided evidence that some of the recombinants underwent subsequent divergence, further increasing the genotypic complexity. These data demonstrate that persistent infection of multiple viral genotypes within a host organism is sufficient to drive the large-scale production of viral genetic variants that may evolve into new and emerging viruses.     

Viral infection in internally structured hosts. I. Conditions for persistent infection

For a virus population within its host, two important levels of structure can be considered: multiple cell types which can be infected, and tissue types or body compartments which may be coupled via movement. We develop a model with both types of structure. Migration between compartments can create "sources" and "sinks" within the virus population, where realized viral growth rate and abundance is lowered in some compartments compared to what would be observed in isolation. Using both analytical and numerical methods, we investigate how this within-host spatial structure affects the conditions for persistent viral infection. We find that migration between compartments makes the establishment of infection more difficult than it would be in the absence of migration, implying that within-host spatial structure combined with viral movement decreases the likelihood of viral establishment. If migration is symmetrical and compartments are heterogeneous, an increase in migration rates between compartments generally makes establishment less likely. This may help to explain the tissue specificity observed for many viruses. There are, however, important exceptions to this result. These include circumstances where the virus initially invades a compartment that is unfavorable to population growth and migration is necessary to infect other parts of the host body. Stochastic aspects of viral establishment may also favor increased migration as it tends to dampen the amplitude of fluctuations in population size during the initial transient phase of establishment.     

Loss and Recovery of Genetic Diversity in Adapting Populations of HIV

The evolution of drug resistance in HIV occurs by the fixation of specific, well-known, drug-resistance mutations, but the underlying population genetic processes are not well understood. By analyzing within-patient longitudinal sequence data, we make four observations that shed a light on the underlying processes and allow us to infer the short-term effective population size of the viral population in a patient. Our first observation is that the evolution of drug resistance usually occurs by the fixation of one drug-resistance mutation at a time, as opposed to several changes simultaneously. Second, we find that these fixation events are accompanied by a reduction in genetic diversity in the region surrounding the fixed drug-resistance mutation, due to the hitchhiking effect. Third, we observe that the fixation of drug-resistance mutations involves both hard and soft selective sweeps. In a hard sweep, a resistance mutation arises in a single viral particle and drives all linked mutations with it when it spreads in the viral population, which dramatically reduces genetic diversity. On the other hand, in a soft sweep, a resistance mutation occurs multiple times on different genetic backgrounds, and the reduction of diversity is weak. Using the frequency of occurrence of hard and soft sweeps we estimate the effective population size of HIV to be ( confidence interval ). This number is much lower than the actual number of infected cells, but much larger than previous population size estimates based on synonymous diversity. We propose several explanations for the observed discrepancies. Finally, our fourth observation is that genetic diversity at non-synonymous sites recovers to its pre-fixation value within 18 months, whereas diversity at synonymous sites remains depressed after this time period. These results improve our understanding of HIV evolution and have potential implications for treatment strategies.     

Variability of HIV infections.

Genetic variation is the hallmark of infections with lentiviruses in general and the human immunodeficiency viruses (HIV-1, HIV-2) in particular. This article reviews both experimental evidence for the variability of the HIV genome during the course of an individual infection and mathematical models that outline the potential importance of antigenic variation as a major factor to drive disease progression. The essential idea is that the virus evades immune pressure by the continuous production of new mutants resistant to current immunological attack. This results in the accumulation of antigenic diversity during the asymptomatic period. The existence of an antigenic diversity threshold is derived from the asymmetric interaction between the virus quasispecies and the CD4 cell population: CD4 cells mount immune responses some of which are directed against specific HIV variants, but each virus strain can induce depletion of all CD4 cells and therefore impair immune responses regardless of their specificity. Therefore, increasing HIV diversity enables the virus population to escape from control by the immune system. In this context the observed genetic variability is responsible for the fact that the virus establishes a persistent infection without being cleared by the immune response and induces immunodeficiency disease after a long and variable incubation period. Mathematical biology has revealed a novel mechanism for viral pathogenesis.     

The dynamic genetic repertoire of microbial communities

Community genomic data have revealed multiple levels of variation between and within microbial consortia. This variation includes large-scale differences in gene content between ecosystems as well as within-population sequence heterogeneity. In the present review, we focus specifically on how fine-scale variation within microbial and viral populations is apparent from community genomic data. A major unresolved question is how much of the observed variation is due to neutral vs. adaptive processes. Limited experimental data hint that some of this fine-scale variation may be in part functionally relevant, whereas sequence-based and modeling analyses suggest that much of it may be neutral. While methods for interpreting population genomic data are still in their infancy, we discuss current interpretations of existing datasets in the light of evolutionary processes and models. Finally, we highlight the importance of virus–host dynamics in generating and shaping within-population diversity.     

Infection with multiple human immunodeficiency virus type 1 variants is associated with faster disease progression

Human immunodeficiency virus type 1 (HIV-1)-infected individuals develop a genetically diverse virus population over time, but often only a limited number of viral variants are transmitted from a chronic carrier to a newly infected person. Interestingly, many women but few men are infected by multiple HIV-1 variants from a single partner. To determine whether the complexity of the infecting virus population influences clinical outcome, we examined viral diversity in the HIV-1 envelope sequences present at primary infection in 156 women from Kenya for whom we had follow-up data on viral RNA levels and CD4 T-cell counts. Eighty-nine women had multiple viral genotypes, while 67 women had a single genotype at primary infection. Women who acquired multiple viral genotypes had a significantly higher viral load (median, 4.84 versus 4.64 log(10) copies/ml, P = 0.04) and a significantly lower CD4(+)-T-cell count (median, 416 versus 617 cells/mm(3), P = 0.01) 4 to 24 months after infection compared to women who were infected with a single viral genotype. These studies suggest that early HIV-1 genetic diversity is linked to faster disease progression.     

Patterns of genetic diversity in the polymorphic ground snake (Sonora semiannulata)

We evaluated the genetic diversity of a snake species with color polymorphism to understand the evolutionary processes that drive genetic structure across a large geographic region. Specifically, we analyzed genetic structure of the highly polymorphic ground snake, Sonora semiannulata, (1) among populations, (2) among color morphs (3) at regional and local spatial scales, using an amplified fragment length polymorphism dataset and multiple population genetic analyses, including F_ST-based and clustering analytical techniques. Based upon these methods, we found that there was moderate to low genetic structure among populations. However, this diversity was not associated with geographic locality at either spatial scale. Similarly, we found no evidence for genetic divergence among color morphs at either spatial scale. These results suggest that despite dramatic color polymorphism, this phenotypic diversity is not a major driver of genetic diversity within or among populations of ground snakes. We suggest that there are two mechanisms that could explain existing genetic diversity in ground snakes: recent range expansion from a genetically diverse founder population and current or recent gene flow among populations. Our findings have further implications for the types of color polymorphism that may generate genetic diversity in snakes.     

Use of a high resolution melting (HRM) assay to compare gag, pol, and env diversity in adults with different stages of HIV infection

Background

Cross-sectional assessment of HIV incidence relies on laboratory methods to discriminate between recent and non-recent HIV infection. Because HIV diversifies over time in infected individuals, HIV diversity may serve as a biomarker for assessing HIV incidence. We used a high resolution melting (HRM) diversity assay to compare HIV diversity in adults with different stages of HIV infection. This assay provides a single numeric HRM score that reflects the level of genetic diversity of HIV in a sample from an infected individual.

Methods

HIV diversity was measured in 203 adults: 20 with acute HIV infection (RNA positive, antibody negative), 116 with recent HIV infection (tested a median of 189 days after a previous negative HIV test, range 14–540 days), and 67 with non-recent HIV infection (HIV infected >2 years). HRM scores were generated for two regions in gag, one region in pol, and three regions in env.

Results

Median HRM scores were higher in non-recent infection than in recent infection for all six regions tested. In multivariate models, higher HRM scores in three of the six regions were independently associated with non-recent HIV infection.

Conclusions

The HRM diversity assay provides a simple, scalable method for measuring HIV diversity. HRM scores, which reflect the genetic diversity in a viral population, may be useful biomarkers for evaluation of HIV incidence, particularly if multiple regions of the HIV genome are examined.     

Sequential bottlenecks drive viral evolution in early acute hepatitis C virus infection

Hepatitis C is a pandemic human RNA virus, which commonly causes chronic infection and liver disease. The characterization of viral populations that successfully initiate infection, and also those that drive progression to chronicity is instrumental for understanding pathogenesis and vaccine design. A comprehensive and longitudinal analysis of the viral population was conducted in four subjects followed from very early acute infection to resolution of disease outcome. By means of next generation sequencing (NGS) and standard cloning/Sanger sequencing, genetic diversity and viral variants were quantified over the course of the infection at frequencies as low as 0.1%. Phylogenetic analysis of reassembled viral variants revealed acute infection was dominated by two sequential bottleneck events, irrespective of subsequent chronicity or clearance. The first bottleneck was associated with transmission, with one to two viral variants successfully establishing infection. The second occurred approximately 100 days post-infection, and was characterized by a decline in viral diversity. In the two subjects who developed chronic infection, this second bottleneck was followed by the emergence of a new viral population, which evolved from the founder variants via a selective sweep with fixation in a small number of mutated sites. The diversity at sites with non-synonymous mutation was higher in predicted cytotoxic T cell epitopes, suggesting immune-driven evolution. These results provide the first detailed analysis of early within-host evolution of HCV, indicating strong selective forces limit viral evolution in the acute phase of infection.     

Within-host spatial dynamics of viruses and defective interfering particles

Defective-interfering (DI) viruses arise spontaneously by deletion mutations. The shortened genomes of the DI particles cannot replicate unless they coinfect a cell with a wild-type virus. Upon coinfection, the DI genome replicates more quickly and outcompetes the wild type. The coinfected cell produces mostly DI viruses. At the population level, the abundances of DI and wild-type viruses fluctuate dramatically under some conditions. In other cases, the DI viruses appear to mediate persistent infections with relatively low levels of host cell death. This moderation of viral damage has led some to suggest DI particles as therapeutic agents. Previous mathematical models have shown that either fluctuation or persistence can occur for plausible parameter values. I develop new mathematical models for the population dynamics of DI and wild-type viruses. My work extends the theory by developing specific predictions that can be tested in the laboratory. These predictions, if borne out by experiment, will explain the key processes that control the diversity of observed outcomes. The most interesting prediction concerns the rate at which killed host cells are replaced. A low rate of replacement causes powerful epidemics followed by a crash in viral abundance. As the rate of replacement increases, the frequency of oscillations increases in DI and wild-type viral abundances, but the severity (amplitude) of the fluctuations declines. At higher replacement rates for host cells, nearly all cells become infected by DI particles and a low level of fluctuating, wild-type viremia persists.     

The geometry of coexistence

Understanding the processes that maintain diversity has been the focus of extensive study, yet there is much that has not been integrated into a cohesive framework. First, there is a separation of perspective. Ecological and evolutionary approaches to diversity have progressed in largely parallel directions. Second, there is a separation of emphasis. In both ecology and population genetics, classical theories favour local explanations with emphasis on population dynamics and selection within populations, while contemporary theories favour spatial explanations, with emphasis on population structure and interactions among populations. What is lacking is a comparative approach that evaluates the relative importance of local and spatial processes in maintaining genetic and ecological diversity. I present a framework for diversity maintenance that emphasizes the comparative approach. I use a well-known but little-used mathematical approach, the perturbation theorem for dynamical systems, to identify key points of contact between ecological and population genetic theories of coexistence. These connections provide for a synthesis of several important concepts: population structure (source-sink versus extinction-colonization), spatial heterogeneity (intrinsic versus extrinsic) in fitness and competitive ability, and temporal scales over which local and spatial processes influence diversity. This framework ties together a large and diverse body of theory and data from ecology and population genetics. It yields comparative predictions that can serve as guidelines in biodiversity management.     

Spontaneous clearance of viral infections by mesoscopic fluctuations

Spontaneous disease extinction can occur due to a rare stochastic fluctuation. We explore this process, both numerically and theoretically, in two minimal models of stochastic viral infection dynamics. We propose a method that reduces the complexity in models of viral infections so that the remaining dynamics can be studied by previously developed techniques for analyzing epidemiological models. Using this technique, we obtain an expression for the infection clearance time as a function of kinetic parameters. We apply our theoretical results to study stochastic infection clearance for specific stages of HIV and HCV dynamics. Our results show that the typical time for stochastic clearance of a viral infection increases exponentially with the size of the population, but infection still can be cleared spontaneously within a reasonable time interval in a certain population of cells. We also show that the clearance time is exponentially sensitive to the viral decay rate and viral infectivity but only linearly dependent on the lifetime of an infected cell. This suggests that if standard drug therapy fails to clear an infection then intensifying therapy by adding a drug that reduces the rate of cell infection rather than immune modulators that hasten infected cell death may be more useful in ultimately clearing remaining pockets of infection.     

Tracking Dengue Virus Intra-host Genetic Diversity during Human-to-Mosquito Transmission

Dengue virus (DENV) infection of an individual human or mosquito host produces a dynamic population of closely-related sequences. This intra-host genetic diversity is thought to offer an advantage for arboviruses to adapt as they cycle between two very different host species, but it remains poorly characterized. To track changes in viral intra-host genetic diversity during horizontal transmission, we infected Aedes aegypti mosquitoes by allowing them to feed on DENV2-infected patients. We then performed whole-genome deep-sequencing of human- and matched mosquito-derived DENV samples on the Illumina platform and used a sensitive variant-caller to detect single nucleotide variants (SNVs) within each sample. >90% of SNVs were lost upon transition from human to mosquito, as well as from mosquito abdomen to salivary glands. Levels of viral diversity were maintained, however, by the regeneration of new SNVs at each stage of transmission. We further show that SNVs maintained across transmission stages were transmitted as a unit of two at maximum, suggesting the presence of numerous variant genomes carrying only one or two SNVs each. We also present evidence for differences in selection pressures between human and mosquito hosts, particularly on the structural and NS1 genes. This analysis provides insights into how population drops during transmission shape RNA virus genetic diversity, has direct implications for virus evolution, and illustrates the value of high-coverage, whole-genome next-generation sequencing for understanding viral intra-host genetic diversity.     

Exploiting Genetic Interference for Antiviral Therapy

Rapidly evolving viruses are a major threat to human health. Such viruses are often highly pathogenic (e.g., influenza virus, HIV, Ebola virus) and routinely circumvent therapeutic intervention through mutational escape. Error-prone genome replication generates heterogeneous viral populations that rapidly adapt to new selection pressures, leading to resistance that emerges with treatment. However, population heterogeneity bears a cost: when multiple viral variants replicate within a cell, they can potentially interfere with each other, lowering viral fitness. This genetic interference can be exploited for antiviral strategies, either by taking advantage of a virus’s inherent genetic diversity or through generating de novo interference by engineering a competing genome. Here, we discuss two such antiviral strategies, dominant drug targeting and therapeutic interfering particles. Both strategies harness the power of genetic interference to surmount two particularly vexing obstacles—the evolution of drug resistance and targeting therapy to high-risk populations—both of which impede treatment in resource-poor settings.     

Quantifying the Diversification of Hepatitis C Virus (HCV) during Primary Infection: Estimates of the In Vivo Mutation Rate

Hepatitis C virus (HCV) is present in the host with multiple variants generated by its error prone RNA-dependent RNA polymerase. Little is known about the initial viral diversification and the viral life cycle processes that influence diversity. We studied the diversification of HCV during acute infection in 17 plasma donors, with frequent sampling early in infection. To analyze these data, we developed a new stochastic model of the HCV life cycle. We found that the accumulation of mutations is surprisingly slow: at 30 days, the viral population on average is still 46% identical to its transmitted viral genome. Fitting the model to the sequence data, we estimate the median in vivo viral mutation rate is 2.5×10⁻⁵ mutations per nucleotide per genome replication (range 1.6–6.2×10⁻⁵), about 5-fold lower than previous estimates. To confirm these results we analyzed the frequency of stop codons (N = 10) among all possible non-sense mutation targets (M = 898,335), and found a mutation rate of 2.8–3.2×10⁻⁵, consistent with the estimate from the dynamical model. The slow accumulation of mutations is consistent with slow turnover of infected cells and replication complexes within infected cells. This slow turnover is also inferred from the viral load kinetics. Our estimated mutation rate, which is similar to that of other RNA viruses (e.g., HIV and influenza), is also compatible with the accumulation of substitutions seen in HCV at the population level. Our model identifies the relevant processes (long-lived cells and slow turnover of replication complexes) and parameters involved in determining the rate of HCV diversification.     

Emergence of distinct multiarmed immunoregulatory antigen-presenting cells during persistent viral infection

During persistent viral infection, adaptive immune responses are suppressed by immunoregulatory factors, contributing to viral persistence. Although this suppression is mediated by inhibitory factors, the mechanisms by which virus-specific T?cells encounter and integrate immunoregulatory signals during persistent infection are unclear. We show that a distinct population of IL-10-expressing immunoregulatory antigen-presenting cells (APCs) is amplified during chronic versus acute lymphocytic choriomeningitis virus (LCMV) infection and suppresses T?cell responses. Although acute LCMV infection induces the expansion of immunoregulatory APCs, they subsequently decline. However, during persistent LCMV infection, immunoregulatory APCs are amplified and parallel the viral replication kinetics. Further characterization demonstrates that immunoregulatory APCs are molecularly and metabolically distinct, and exhibit increased expression of T?cell-interacting molecules and negative regulatory factors that suppress T?cell responses. Thus, immunoregulatory APCs are amplified during viral persistence and deliver inhibitory signals that suppress antiviral T?cell immunity and likely contribute to persistent infection.     

Genetically Engineered Human Cancer Models Utilizing Mammalian Transgene Expression

Cancer models are vital to cancer biology research, and multiple cancer models are currently available that utilize either murine or human cells, each with particular strengths and weaknesses. The ability to transform primary human cells into tumors through the expression of specific transgenes offers many advantages as a cancer model, including genetic malleability and the ability to transform specific cell types. Until recently, the conversion of primary human cells into tumors through transgene expression required the use of viral genetic elements, which unfortunately adds uncertainty regarding which cancer pathways are affected and how they are affected. In recent years multiple reports have described the transformation of primary human cells into tumors using only mammalian transgenes. This review focuses on these five cancer models, comparing the different cell types which were transformed into tumors and which transgenes were expressed, as well as the cancer pathways affected in the disparate models. These genetically-engineered human cancer models offer a valuable tool to complement existing cancer models and further cancer research.     

Approximate Bayesian computation reveals the factors that influence genetic diversity and population structure of foxsnakes

Contemporary geographical range and patterns of genetic diversity within species reflect complex interactions between multiple factors acting across spatial and temporal scales, and it is notoriously difficult to disentangle causation. Here, we quantify patterns of genetic diversity and genetic population structure using mitochondrial DNA sequences (101 individuals, cytochrome b) and microsatellites (816 individuals, 12 loci) and use Approximate Bayesian computation methods to test competing models of the demographic history of eastern and western foxsnakes. Our analyses indicate that post-glacial colonization and past population declines, probably caused by the infilling of deciduous forest and cooler temperatures since the mid-Holocene, largely underpin large-scale genetic patterns for foxsnakes. At finer geographical scales, our results point to more recent anthropogenic habitat loss as having accentuated genetic population structure by causing further declines and fragmentation.