Exceptional Heterogeneity in Viral Evolutionary Dynamics Characterises Chronic Hepatitis C Virus Infection

The treatment of HCV infection has seen significant progress, particularly since the approval of new direct-acting antiviral drugs. However these clinical achievements have been made despite an incomplete understanding of HCV replication and within-host evolution, especially compared with HIV-1. Here, we undertake a comprehensive analysis of HCV within-host evolution during chronic infection by investigating over 4000 viral sequences sampled longitudinally from 15 HCV-infected patients. We compare our HCV results to those from a well-studied HIV-1 cohort, revealing key differences in the evolutionary behaviour of these two chronic-infecting pathogens. Notably, we find an exceptional level of heterogeneity in the molecular evolution of HCV, both within and among infected individuals. Furthermore, these patterns are associated with the long-term maintenance of viral lineages within patients, which fluctuate in relative frequency in peripheral blood. Together, our findings demonstrate that HCV replication behavior is complex and likely comprises multiple viral subpopulations with distinct evolutionary dynamics. The presence of a structured viral population can explain apparent paradoxes in chronic HCV infection, such as rapid fluctuations in viral diversity and the reappearance of viral strains years after their initial detection.     

Optimal replication of poliovirus within cells

We construct a mathematical model of the within-cell replication of poliovirus, a prototypic RNA virus, and use realistic parameter estimates to describe the increase of copy number of the viral genome. Our initial model is essentially an exponential growth model; we also consider modifications of this model to account for resource utilization. The saturation of viral replication dynamics observed in experimental systems can be explained in terms of heavy resource use by the virus. We then use our models to consider the conditions under which the growth of poliovirus is optimized. Intriguingly, if poliovirus has optimized its replication within cells, the predicted ratio of positive to negative strands is close to what is actually observed. We interpret our findings in terms of the evolution of life-history traits.     

Structured model of influenza virus replication in MDCK cells

Intracellular events that take place during influenza virus replication in animal cells are well understood qualitatively. However, to better understand the complex interaction of the virus with its host cell and to quantitatively analyze the use of cellular resources for virion formation or the overall dynamic for the entire infection cycle, a mathematical model for influenza virus replication has to be formulated. Here, we present a structured model for the single-cell reproductive cycle of influenza A virus in animal cells that accounts for the individual steps of the process such as attachment, internalization, genome replication and translation, and progeny virion assembly. The model describes an average cell surrounded by a small quantity of medium and infected by a low number of virus particles. The model allows estimation of the cellular resources consumed by virus replication. Simulation results show that the number of cellular surface receptors and endosomes, as well as other resources, such as the number of free nucleotides or amino acids, is not significantly influenced by influenza virus propagation. A factor that limits the growth rate of progeny viruses and their release is the total amount of matrix proteins (M1) in the nucleus while other newly synthesized viral proteins (e.g., nucleoprotein NP) and viral RNAs accumulate. During budding, synthesis of vRNPs (viral ribonucleoprotein complexes) represents another limiting factor. Based on this model it is also possible to analyze effects of parameter changes on the dynamics of virus replication, to identify possible targets for molecular engineering, or to develop strategies for improving yields in vaccine production processes. Furthermore, a better insight into the interactions of viruses and host cells might help to improve our understanding of virus-related diseases and to develop therapies.     

ODE models for oncolytic virus dynamics

Replicating oncolytic viruses are able to infect and lyse cancer cells and spread through the tumor, while leaving normal cells largely unharmed. This makes them potentially useful in cancer therapy, and a variety of viruses have shown promising results in clinical trials. Nevertheless, consistent success remains elusive and the correlates of success have been the subject of investigation, both from an experimental and a mathematical point of view. Mathematical modeling of oncolytic virus therapy is often limited by the fact that the predicted dynamics depend strongly on particular mathematical terms in the model, the nature of which remains uncertain. We aim to address this issue in the context of ODE modeling, by formulating a general computational framework that is independent of particular mathematical expressions. By analyzing this framework, we find some new insights into the conditions for successful virus therapy. We find that depending on our assumptions about the virus spread, there can be two distinct types of dynamics. In models of the first type (the “fast spread” models), we predict that the viruses can eliminate the tumor if the viral replication rate is sufficiently high. The second type of models is characterized by a suboptimal spread (the “slow spread” models). For such models, the simulated treatment may fail, even for very high viral replication rates. Our methodology can be used to study the dynamics of many biological systems, and thus has implications beyond the study of virus therapy of cancers.     

Eco‐evolutionary dynamics in a coevolving host–virus system

Eco‐evolutionary dynamics have been shown to be important for understanding population and community stability and their adaptive potential. However, coevolution in the framework of eco‐evolutionary theory has not been addressed directly. Combining experiments with an algal host and its viral parasite, and mathematical model analyses we show eco‐evolutionary dynamics in antagonistic coevolving populations. The interaction between antagonists initially resulted in arms race dynamics (ARD) with selective sweeps, causing oscillating host–virus population dynamics. However, ARD ended and populations stabilised after the evolution of a general resistant host, whereas a trade‐off between host resistance and growth then maintained host diversity over time (trade‐off driven dynamics). Most importantly, our study shows that the interaction between ecology and evolution had important consequences for the predictability of the mode and tempo of adaptive change and for the stability and adaptive potential of populations.     

Towards Predictive Computational Models of Oncolytic Virus Therapy: Basis for Experimental Validation and Model Selection

Oncolytic viruses are viruses that specifically infect cancer cells and kill them, while leaving healthy cells largely intact. Their ability to spread through the tumor makes them an attractive therapy approach. While promising results have been observed in clinical trials, solid success remains elusive since we lack understanding of the basic principles that govern the dynamical interactions between the virus and the cancer. In this respect, computational models can help experimental research at optimizing treatment regimes. Although preliminary mathematical work has been performed, this suffers from the fact that individual models are largely arbitrary and based on biologically uncertain assumptions. Here, we present a general framework to study the dynamics of oncolytic viruses that is independent of uncertain and arbitrary mathematical formulations. We find two categories of dynamics, depending on the assumptions about spatial constraints that govern that spread of the virus from cell to cell. If infected cells are mixed among uninfected cells, there exists a viral replication rate threshold beyond which tumor control is the only outcome. On the other hand, if infected cells are clustered together (e.g. in a solid tumor), then we observe more complicated dynamics in which the outcome of therapy might go either way, depending on the initial number of cells and viruses. We fit our models to previously published experimental data and discuss aspects of model validation, selection, and experimental design. This framework can be used as a basis for model selection and validation in the context of future, more detailed experimental studies. It can further serve as the basis for future, more complex models that take into account other clinically relevant factors such as immune responses.     

Clearance of a productive lentivirus infection in calves experimentally inoculated with caprine arthritis-encephalitis virus

Lentiviruses have long been considered host-specific pathogens, but several recent observations demonstrated their capacity to conquer new hosts from different species, genera, and families. From these cross-species infections emerged new animal and human infectious diseases. The successful colonization and adaptation of a lentivirus to a nonnatural host depends on unspecific and specific host barriers. Some of those barriers exert a relative control of viral replication (i.e., cytotoxic T-lymphocyte response, viral inhibitory factors), but none of them was found able to totally clear the infection once the retrovirus is fully adapted in its host. In this study we examined the evolution of the host-lentivirus interactions occurring in an experimental animal model of cross-species infection in order to analyze the efficiency of those barriers in preventing the establishment of a persistent infection. Five newborn calves were inoculated with caprine arthritis-encephalitis virus (CAEV), and the evolution of infection was studied for more than 12 months. All the animals seroconverted in the first 0.75 to 1 month following the inoculation and remained seropositive for the remaining time of the experiment. Viral infection was productive during 4 months with isolation of replication competent virus from the blood cells and organs of the early euthanized animals. After 4 months of infection, neither replication-competent virus nor virus genome could be detected in blood cells or in the classical target organs, even after an experimental immunosuppression. No evidence of in vitro restriction of CAEV replication was observed in cells from tissues explanted from organs of these calves. These data provide the demonstration of a natural clearance of lentivirus infection following experimental inoculation of a nonnatural host, enabling perspectives of development of new potential vaccine strategies to fight against lentivirus infections.     

Residual Viremia in Treated HIV+ Individuals

Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads. However, some residual virus remains, below the level of detection, in HIV-infected patients on ART. The source of this viremia is an area of debate: does it derive primarily from activation of infected cells in the latent reservoir, or from ongoing viral replication? Observations seem to be contradictory: there is evidence of short term evolution, implying that there must be ongoing viral replication, and viral strains should thus evolve. However, phylogenetic analyses, and rare emergent drug resistance, suggest no long-term viral evolution, implying that virus derived from activated latent cells must dominate. We use simple deterministic and stochastic models to gain insight into residual viremia dynamics in HIV-infected patients. Our modeling relies on two underlying assumptions for patients on suppressive ART: that latent cell activation drives viral dynamics and that the reproductive ratio of treated infection is less than 1. Nonetheless, the contribution of viral replication to residual viremia in patients on ART may be non-negligible. However, even if the portion of viremia attributable to viral replication is significant, our model predicts (1) that latent reservoir re-seeding remains negligible, and (2) some short-term viral evolution is permitted, but long-term evolution can still be limited: stochastic analysis of our model shows that de novo emergence of drug resistance is rare. Thus, our simple models reconcile the seemingly contradictory observations on residual viremia and, with relatively few parameters, recapitulates HIV viral dynamics observed in patients on suppressive therapy.     

Methodology for the Efficient Generation of Fluorescently Tagged Vaccinia Virus Proteins

Tagging of viral proteins with fluorescent proteins has proven an indispensable approach to furthering our understanding of virus-host interactions. Vaccinia virus (VACV), the live vaccine used in the eradication of smallpox, is particularly amenable to fluorescent live-cell microscopy owing to its large virion size and the ease with which it can be engineered at the genome level. We report here an optimized protocol for generating recombinant viruses. The minimal requirements for targeted homologous recombination during vaccinia replication were determined, which allows the simplification of construct generation. This enabled the alliance of transient dominant selection (TDS) with a fluorescent reporter and metabolic selection to provide a rapid and modular approach to fluorescently label viral proteins. By streamlining the generation of fluorescent recombinant viruses, we are able to facilitate downstream applications such as advanced imaging analysis of many aspects of the virus-host interplay that occurs during virus replication.     

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.     

Understanding hepatitis C viral dynamics with direct-acting antiviral agents due to the interplay between intracellular replication and cellular infection dynamics

The current paradigm for modeling viral kinetics and resistance evolution after treatment initiation considers only the level of circulating virus and cellular infection (CI model), while the intra-cellular level is disregarded. This model was successfully used to explain HIV dynamics and Hepatitis C virus (HCV) dynamics during interferon-based therapy. However, in the new era of direct-acting antiviral agents (DAAs) against HCV, viral kinetics is characterized by a more rapid decline of the wild-type virus as well as an early emergence of resistant strains that jeopardize the treatment outcome. Although the CI model can be extended to describe these new kinetic patterns, this approach has qualitative and quantitative limitations. Instead, we suggest that a more appropriate approach would consider viral dynamics at the cell infection level, as done currently, as well as at the intracellular level. Indeed, whereas in HIV integrated DNA serves as a static replication unit and mutations occur only once per infected cell, HCV replication is deeply affected by DAAs and furthermore processes of resistance evolution can occur at the intra-cellular level with a faster time-scale.We propose a comprehensive model of HCV dynamics that considers both extracellular and intracellular levels of infection (ICCI model). Intracellular viral genomic units are used to form replication units, which in turn synthesize genomic units that are packaged and secreted as virions infecting more target cells. Resistance evolution is modeled intra-cellularly, by different genomic- and replication-unit strains with particular relative-fitness and drug sensitivity properties, allowing for a rapid resistance takeover.Using the ICCI model, we show that the rapid decline of wild-type virus results from the ability of DAAs to destabilize the intracellular replication. On the other hand, this ability also favors the rapid emergence, intracellularly, of resistant virus. By considering the interaction between intracellular and extracellular infection we show that resistant virus, able to maintain a high level of intracellular replication, may nevertheless be unable to maintain rapid enough de novo infection rate at the extracellular level. Hence this model predicts that in HCV, and contrary to our experience with HIV, the emergence of productively resistant virus may not systematically prevent from a viral decline in the long-term. Thus, the ICCI model can explain the transient viral rebounds observed with DAA treatment as well as the viral resistance found in most patients with viral relapse at the end of DAA combination therapy.     

The Double-Edged Sword: How Evolution Can Make or Break a Live-Attenuated Virus Vaccine

Even students who reject evolution are often willing to consider cases in which evolutionary biology contributes to, or undermines, biomedical interventions. Moreover, the intersection of evolutionary biology and biomedicine is fascinating in its own right. This review offers an overview of the ways in which evolution has impacted the design and deployment of live-attenuated virus vaccines, with subsections that may be useful as lecture material or as the basis for case studies in classes at a variety of levels. Live-attenuated virus vaccines have been modified in ways that restrain their replication in a host so that infection (vaccination) produces immunity but not disease. Applied evolution, in the form of serial passage in novel host cells, is a “classical” method to generate live-attenuated viruses. However, many live-attenuated vaccines exhibit reversion to virulence through back-mutation of attenuating mutations, compensatory mutations elsewhere in the genome, recombination or reassortment, or changes in quasispecies diversity. Additionally, the combination of multiple live-attenuated strains may result in competition or facilitation between individual vaccine viruses, resulting in undesirable increases in virulence or decreases in immunogenicity. Genetic engineering informed by evolutionary thinking has led to a number of novel approaches to generate live-attenuated virus vaccines that contain substantial safeguards against reversion to virulence and that ameliorate interference among multiple vaccine strains. Finally, vaccines have the potential to shape the evolution of their wild-type counterparts in counter-productive ways; at the extreme, vaccine-driven eradication of a virus may create an empty niche that promotes the emergence of new viral pathogens.     

Highlights from this issue

Autophagy is acknowledged as an important cellular defense mechanism against intracellular pathogens. As with other innate immune responses, pathogens have adapted to evade autophagy and in some cases, subvert the pathway to promote their own replication. Poliovirus, a prototypical small positive-strand RNA virus that replicates and assembles in the cytoplasm of the host cell, utilizes membranes derived from the autophagic pathway to aid viral replication and egress from the cell. Recently we made the surprising discovery that GFP-LC3-staining vesicles are physically immobilized during poliovirus infection. Here we discuss our model for the mechanism of vesicle immobilization and the predictions it makes for pathogens that subvert the autophagic pathway to their own ends.     

Autophagy and RNA virus interactomes reveal IRGM as a common target

Several intracellular pathogens have the ability to avoid or exploit the otherwise destructive process of autophagy. RNA viruses are constantly confronted with cellular autophagy, and several of them hijack autophagy during the infectious cycle to improve their own replication. Nevertheless, our knowledge of viral molecular strategies used to manipulate autophagy remains limited. Our study allowed the identification of molecular interactions between 44 autophagy-associated proteins and 83 viral proteins belonging to five different RNA virus families. This interactome revealed that the autophagy network machinery is highly targeted by RNA viruses. Interestingly, whereas some autophagy-associated proteins are targeted by only one RNA virus family, others are recurrent targets of several families. Among them, we found IRGM as the most targeted autophagy-associated protein. Downregulation of IRGM expression prevents autophagy induction by measles virus, HCV and HIV-1, and compromises viral replication. Our work combined interactomic and analytical approaches to identify potential pathogen virulence factors targeting autophagy.     

Autophagy and RNA virus interactomes reveal IRGM as a common target

Several intracellular pathogens have the ability to avoid or exploit the otherwise destructive process of autophagy. RNA viruses are constantly confronted with cellular autophagy, and several of them hijack autophagy during the infectious cycle to improve their own replication. Nevertheless, our knowledge of viral molecular strategies used to manipulate autophagy remains limited. Our study allowed the identification of molecular interactions between 44 autophagy-associated proteins and 83 viral proteins belonging to five different RNA virus families. This interactome revealed that the autophagy network machinery is highly targeted by RNA viruses. Interestingly, whereas some autophagy-associated proteins are targeted by only one RNA virus family, others are recurrent targets of several families. Among them, we found IRGM as the most targeted autophagy-associated protein. Downregulation of IRGM expression prevents autophagy induction by measles virus, HCV and HIV-1, and compromises viral replication. Our work combined interactomic and analytical approaches to identify potential pathogen virulence factors targeting autophagy.     

口蹄疫病毒反向遗传学研究进展

反向遗传学操作技术在口蹄疫病毒(FMDV)病原学基础研究领域的应用, 使得人们能够在基因组整体水平上研究病毒基因的功能。得益于反向遗传学系统的不断完善和发展, 目前人们对FMDV分子病原学也有了更加深入的认识和理解。本文结合实验室在FMDV反向遗传学方向上所开展的探索性研究工作, 综述了国内外利用反向遗传学操作技术在研究FMDV分子致病机制、病毒毒力与变异的关系、病毒复制的影响因素、新型FMD基因疫苗的研制等领域所取得的进展, 展望FMDV反向遗传学研究新动向。     

Next-generation sequencing: A new avenue to understand viral RNA–protein interactions

The genomes of RNA viruses present an astonishing source of both sequence and structural diversity. From intracellular viral RNA-host interfaces to interactions between the RNA genome and structural proteins in virus particles themselves, almost the entire viral lifecycle is accompanied by a myriad of RNA–protein interactions that are required to fulfill their replicative potential. It is therefore important to characterize such rich and dynamic collections of viral RNA–protein interactions to understand virus evolution and their adaptation to their hosts and environment. Recent advances in next-generation sequencing technologies have allowed the characterization of viral RNA–protein interactions, including both transient and conserved interactions, where molecular and structural approaches have fallen short. In this review, we will provide a methodological overview of the high-throughput techniques used to study viral RNA–protein interactions, their biochemical mechanisms, and how they evolved from classical methods as well as one another. We will discuss how different techniques have fueled virus research to characterize how viral RNA and proteins interact, both locally and on a global scale. Finally, we will present examples on how these techniques influence the studies of clinically important pathogens such as HIV-1 and SARS-CoV-2.     

Generation of measles virus defective interfering particles and their presence in a preparation of attenuated live-virus vaccine.

By starting from a thrice-purified wild-type measles virus plaque, the generation of detectable subgenomic RNAs was achieved within a series of five serial infections of Vero cells. The evolution of these subgenomic RNAs was followed for seven serial passages and ended with the preparation of a highly interfering viral stock. On the other hand, the detection of discrete subgenomic RNAs was achieved during the first infection of Vero cells with at least one of three measles virus vaccine preparations tested. These subgenomic RNAs, which interfered very efficiently with the replication of the endogenous standard genomes upon vaccine infection but showed a moderate interfering activity with a standard virus stock derived by plaque purification from the vaccine preparation, resulted from the presence of defective interfering particles in the vaccine preparation. The relevance of this finding for the attenuation, stability, and potential capacity for persistent infection of such a vaccine is discussed.