Presence of oseltamivir-resistant pandemic A/H1N1 minor variants before drug therapy with subsequent selection and transmission

Efficacy of oseltamivir treatment in influenza virus-infected obese mice

Obesity has been epidemiologically and empirically linked with more severe diseases upon influenza infection. To ameliorate severe disease, treatment with antivirals, such as the neuraminidase inhibitor oseltamivir, is suggested to begin within days of infection especially in high-risk hosts. However, this treatment can be poorly effective and may generate resistance variants within the treated host. Here, we hypothesized that obesity would reduce oseltamivir treatment effectiveness in the genetically obese mouse model. We demonstrated that oseltamivir treatment does not improve viral clearance in obese mice. While no traditional variants associated with oseltamivir resistance emerged, we did note that drug treatment failed to quench the viral population and did lead to phenotypic drug resistance in vitro. Together, these studies suggest that the unique pathogenesis and immune responses in obese mice could have implications for pharmaceutical interventions and the within-host dynamics of the influenza virus population. IMPORTANCE Influenza virus infections, while typically resolving within days to weeks, can turn critical, especially in high-risk populations. Prompt antiviral administration is crucial to mitigating these severe sequalae, yet concerns remain if antiviral treatment is effective in hosts with obesity. Here, we show that oseltamivir does not improve viral clearance in genetically obese or type I interferon receptor-deficient mice. This suggests a blunted immune response may impair oseltamivir efficacy and render a host more susceptible to severe disease. This study furthers our understanding of oseltamivir treatment dynamics both systemically and in the lungs of obese mice, as well as the consequences of oseltamivir treatment for the within-host emergence of drug-resistant variants.

Influenza polymerase inhibitor resistance: Assessment of the current state of the art - A report of the isirv Antiviral group

It is more than 20 years since the neuraminidase inhibitors, oseltamivir and zanamivir were approved for the treatment and prevention of influenza. Guidelines for global surveillance and methods for evaluating resistance were established initially by the Neuraminidase Inhibitor Susceptibility Network (NISN), which merged 10 years ago with the International Society for influenza and other Respiratory Virus Diseases (isirv) to become the isirv-Antiviral Group (isirv-AVG). With the ongoing development of new influenza polymerase inhibitors and recent approval of baloxavir marboxil, the isirv-AVG held a closed meeting in August 2019 to discuss the impact of resistance to these inhibitors. Following this meeting and review of the current literature, this article is intended to summarize current knowledge regarding the clinical impact of resistance to polymerase inhibitors and approaches for surveillance and methods for laboratory evaluation of resistance, both in vitro and in animal models. We highlight limitations and gaps in current knowledge and suggest some strategies for addressing these gaps, including the need for additional clinical studies of influenza antiviral drug combinations. Lessons learned from influenza resistance monitoring may also be helpful for establishing future drug susceptibility surveillance and testing for SARS-CoV-2.

Understanding the Impact of Resistance to Influenza Antivirals

Influenza poses a significant burden on society and health care systems. Although antivirals are an integral tool in effective influenza management, the potential for the emergence of antiviral-resistant viruses can lead to uncertainty and hesitation among front-line prescribers and policy makers. Here, we provide an overview of influenza antiviral resistance in context, exploring the key concepts underlying its development and clinical impact. Due to the acute nature of influenza in immunocompetent patients, resistant viruses that develop during antiviral treatment of a single patient ("treatment-emergent resistance") are usually cleared in a relatively short time, with no impact on future antiviral efficacy. In addition, although available data are limited by small numbers of patients, they show that antiviral treatment still provides clinical benefit to the patient within whom resistance emerges. In contrast, the sustained community transmission of resistant variants in the absence of treatment ("acquired resistance") is of greater concern and can potentially render front-line antivirals ineffective. Importantly, however, resistant viruses are usually associated with reduced fitness such that their widespread transmission is relatively rare. Influenza antivirals are an essential part of effective influenza management due to their ability to reduce the risk of complications and death in infected patients. Although antiviral resistance should be taken seriously and requires continuous careful monitoring, it is not comparable to antibiotic resistance in bacteria, which can become permanent and widespread, with far-reaching medical consequences. The benefits of antiviral treatment far outweigh concerns of potential resistance, which in the vast majority of cases does not have a significant clinical impact.

Molecular pathway of influenza pan-neuraminidase inhibitor resistance in an immunocompromised patient

BACKGROUND

Neuraminidase (NA) inhibitors (NAIs), including oseltamivir and zanamivir, play an important therapeutic role against influenza infections in immunocompromised patients. In such settings, however, NAI therapy may lead to the emergence of resistance involving mutations within the influenza surface genes. The aim of this study was to investigate the evolution of NA and haemagglutinin (HA) genes of influenza A(H1N1)pdm09 virus in an immunocompromised patient receiving oseltamivir then zanamivir therapies.

METHODS

Nasopharyngeal swab (NPS) samples were collected between 27 January 2018 and 11 April 2018 from a haematopoietic stem cell transplant recipient. These include 10 samples collected either pre-therapy, during oseltamivir and zanamivir treatment as well as after therapy. The A(H1N1)pdm09 HA/NA genes were sequenced. The H275Y NA substitution was quantified by droplet digital RT-PCR assay. A(H1N1)pdm09 recombinant viruses containing HA mutations were tested by HA elution experiments to investigate in vitro binding properties.

RESULTS

Oseltamivir rapidly induced the H275Y NA mutation which constituted 98.33% of the viral population after 15 days of oseltamivir treatment. The related HA gene contained S135A and P183S substitutions within the receptor-binding site. After a switch to zanamivir, 275H/Y and 119E/G/D mixed populations were detected. In the last samples, the double H275Y-E119G NA variant dominated with S135A and P183S HA substitutions.

CONCLUSIONS

This report confirms that oseltamivir can rapidly induce the emergence of the H275Y substitution in A(H1N1)pdm09 viruses and subsequent switch to zanamivir can lead to additional substitutions at codon E119 resulting in multi-drug resistance. Such data additionally suggest a potential compensatory role for HA substitutions near the receptor binding site.

Substitutions at H134 and in the 430-loop region in influenza B neuraminidases can confer reduced susceptibility to multiple neuraminidase inhibitors

With the introduction of the influenza specific neuraminidase inhibitors (NAIs) in 1999, there were concerns about the emergence and spread of resistant viruses in the community setting. Surveillance and testing of community isolates for their susceptibility to the NAIs was initially carried out by the Neuraminidase Inhibitor Susceptibility Network (NISN) and has subsequently been taken on by the global WHO influenza network laboratories. During the NISN surveillance, we identified two Yamagata lineage influenza B viruses with amino acid substitutions of H134Y (B/Auckland/2/2001) or W438R (B/Yokohama/12/2005) which had slightly elevated IC₅₀ values for zanamivir and/or oseltamivir, but not sufficiently to be characterized as mild outliers at the time. As it has now been well demonstrated that mixed populations can mask the true magnitude of resistance of a mutant, we re-examined both of these isolates by plaque purification to see if the true susceptibilities were being masked due to mixed populations. Results confirmed that the B/Auckland isolate contained both wild type and H134Y mutant populations, with mutant IC₅₀ values > 250 nM for both oseltamivir and peramivir in the enzyme inhibition assay. The B/Yokohama isolate also contained both wild type and W438R mutant populations, the latter now demonstrating IC₅₀ values > 400 nM for zanamivir, oseltamivir and peramivir. In addition, plaque purification of the B/Yokohama isolate identified viruses with other single neuraminidase substitutions H134Y, H134R, H431R, or T436P. H134R and H431R viruses had IC₅₀ values > 400 nM and >250 nM respectively against all three NAIs. All changes conferred much greater resistance to peramivir than to zanamivir, and less to oseltamivir, and affected the kinetics of binding and dissociation of the NAIs. Most affected affinity (K_m) for the MUNANA substrate, but some had decreased while others had increased affinity. Despite resistance in the enzyme assay, no reduced susceptibility was seen in plaque reduction assays in MDCK cells for any of the mutant viruses. None of these substitutions was in the active site. Modelling suggests that these substitutions affect the 150 and 430-loop regions described for influenza A NAs, suggesting they may also be important for substrate and inhibitor binding for influenza B NAs.

Deep sequencing of 2009 influenza A/H1N1 virus isolated from volunteer human challenge study participants and natural infections

Nasal wash samples from 15 human volunteers challenged with GMP manufactured influenza A/California/04/2009(H1N1) and from 5 naturally infected influenza patients of the 2009 pandemic were deep sequenced using viral targeted hybridization enrichment. Ten single nucleotide polymorphism (SNP) positions were found in the challenge virus. Some of the nonsynonymous changes in the inoculant virus were maintained in some challenge participants, but not in others, indicating that virus is evolving away from the Vero cell adapted inoculant, for example SNPs in the neuraminidase. Many SNP sites in challenge patients and naturally infected patients were found, many not identified previously. The SNPs identified, and phylogenetic analyses, showed that intrahost evolution of the virus are different in challenge participants and naturally infected patients. This study, using hybridization enrichment without PCR, provided an accurate and unbiased assessment of differential intrahost viral evolution from a uniform influenza inoculant in humans and comparison to naturally infected patients.

Whole Genome Sequencing of A(H3N2) Influenza Viruses Reveals Variants Associated with Severity during the 2016⁻2017 Season

Influenza viruses cause a remarkable disease burden and significant morbidity and mortality worldwide, and these impacts vary between seasons. To understand the mechanisms associated with these differences, a comprehensive approach is needed to characterize the impact of influenza genomic traits on the burden of disease. During 2016–2017, a year with severe A(H3N2), we sequenced 176 A(H3N2) influenza genomes using next generation sequencing (NGS) for routine surveillance of circulating influenza viruses collected via the French national influenza community-based surveillance network or from patients hospitalized in the intensive care units of the University Hospitals of Lyon, France. Taking into account confounding factors, sequencing and clinical data were used to identify genomic variants and quasispecies associated with influenza severity or vaccine failure. Several amino acid substitutions significantly associated with clinical traits were found, including NA V263I and NS1 K196E which were associated with severity and co-occurred only in viruses from the 3c.2a1 clade. Additionally, we observed that intra-host diversity as a whole and on a specific set of gene segments increased with severity. These results support the use of whole genome sequencing as a tool for the identification of genetic traits associated with severe influenza in the context of influenza surveillance.

Laboratory Methods in Molecular Epidemiology: Viral Infections

Viruses, which are the most abundant biological entities on the planet, have been regarded as the "dark matter" of biology in the sense that despite their ubiquity and frequent presence in large numbers, their detection and analysis are not always straightforward. The majority of them are very small (falling under the limit of 0.5 μm), and collectively, they are extraordinarily diverse. In fact, the majority of the genetic diversity on the planet is found in the so-called virosphere, or the world of viruses. Furthermore, the most frequent viral agents of disease in humans display an RNA genome, and frequently evolve very fast, due to the fact that most of their polymerases are devoid of proofreading activity. Therefore, their detection, genetic characterization, and epidemiological surveillance are rather challenging. This review (part of the Curated Collection on Advances in Molecular Epidemiology of Infectious Diseases) describes many of the methods that, throughout the last few decades, have been used for viral detection and analysis. Despite the challenge of having to deal with high genetic diversity, the majority of these methods still depend on the amplification of viral genomic sequences, using sequence-specific or sequence-independent approaches, exploring thermal profiles or a single nucleic acid amplification temperature. Furthermore, viral populations, and especially those with RNA genomes, are not usually genetically uniform but encompass swarms of genetically related, though distinct, viral genomes known as viral quasispecies. Therefore, sequence analysis of viral amplicons needs to take this fact into consideration, as it constitutes a potential analytic problem. Possible technical approaches to deal with it are also described here. *This article is part of a curated collection.

Seasonal Genetic Drift of Human Influenza A Virus Quasispecies Revealed by Deep Sequencing

After a pandemic wave in 2009 following their introduction in the human population, the H1N1pdm09 viruses replaced the previously circulating, pre-pandemic H1N1 virus and, along with H3N2 viruses, are now responsible for the seasonal influenza type A epidemics. So far, the evolutionary potential of influenza viruses has been mainly documented by consensus sequencing data. However, like other RNA viruses, influenza A viruses exist as a population of diverse, albeit related, viruses, or quasispecies. Interest in this quasispecies nature has increased with the development of next generation sequencing (NGS) technologies that allow a more in-depth study of the genetic variability. NGS deep sequencing methodologies were applied to determine the whole genome genetic heterogeneity of the three categories of influenza A viruses that circulated in humans between 2007 and 2012 in France, directly from clinical respiratory specimens. Mutation frequencies and single nucleotide polymorphisms were used for comparisons to address the level of natural intrinsic heterogeneity of influenza A viruses. Clear differences in single nucleotide polymorphism profiles between seasons for a given subtype also revealed the constant genetic drift that human influenza A virus quasispecies undergo.

Comparison of early and recent influenza A(H1N1)pdm09 isolates harboring or not the H275Y neuraminidase mutation, in vitro and in animal models

After 6 years of circulation in humans, a novel antigenic variant of influenza A(H1N1)pdm09 (i.e., A/Michigan/45/2015) emerged in 2015-16 and has predominated thereafter worldwide. Herein, we compared in vitro and in vivo properties of 2016 wild-type (WT) A/Michigan/45/15-like isolate and its H275Y neuraminidase (NA) variant to the original A/California/07/09-like counterparts. The H275Y mutation induced comparable levels of resistance to oseltamivir and peramivir without altering zanamivir susceptibility in both 2009 and 2016 isolates. In vitro, the two WT isolates had comparable replicative properties. The 2016-H275Y isolate had lower titers at 36 h post-inoculation (PI) (P < 0.05) while the 2009-H275Y titers were lower at both 24 h (P < 0.01) and 36 h PI (P < 0.001) vs the respective WTs. In mice, the 2016-WT isolate caused less weight losses (P < 0.001) and lower lung viral titers (LVTs) (P < 0.01) vs the 2009-WT. The LVTs of 2016-WT and 2016-H275Y groups were comparable whereas the 2009-H275Y LVTs were lower vs the respective WT (P < 0.01). Ferrets infected with the 2016-WT isolate and their contacts had higher nasal viral titers (NVTs) at early time points vs the 2009-WT group (P < 0.01). Also, NVTs of 2016-H275Y animals were lower vs the 2016-WT group at early time points in both infected (P < 0.01) and contact animals (P < 0.001). In conclusion, while the H275Y mutation similarly impacts the A/California/07/2009- and A/Michigan/45/2015-like A(H1N1)pdm09 NAs, the fitness of these isolates differs according to animal models with the 2016 virus being less virulent in mice but slightly more virulent in ferrets, potentially reflecting a period of cumulative changes in surface and internal genes.

Intra-host and intra-household diversity of influenza A viruses during household transmissions in the 2013 season in 2 peri-urban communities of South Africa

Limited information is available on influenza virus sequence drift between transmission events. In countries with high HIV burdens, like South Africa, the direct and indirect effect of HIV on influenza sequence drift between transmission events may be of public health concern. To this end, we measured hemagglutinin sequence diversity between influenza transmission events using data and specimens from a study investigating household transmission dynamics of seasonal influenza viruses in 2 peri-urban communities in South Africa during the 2013 influenza season. Thirty index cases and 107 of 110 eligible household contacts were enrolled into the study, 47% (14/30) demonstrating intra-household laboratory-confirmed influenza transmission. In this study 35 partial hemagglutinin gene sequences were obtained by Sanger sequencing from 11 index cases (sampled at enrolment only) and 16 secondary cases (8 cases sampled at 1 and 8 cases sampled at 2 time-points). Viral sequence identities confirmed matched influenza transmission pairs within the 11 households with corresponding sequenced index and secondary cases. Phylogenetic analysis revealed 10 different influenza viral lineages in the 14 households. Influenza A(H1N1)pdm09 strains were shown to be genetically distinct between the 2 communities (from distinct geographic regions), which was not observed for the influenza A(H3N2) strains. Intra-host/intra-household influenza A(H3N2) sequence drift was identified in 2 households. The first was a synonymous mutation between the index case and a household contact, and the second a non-synonymous mutation between 2 serial samples taken at days 0 and 4 post enrolment from an HIV-infected secondary case. Limited inter-household sequence diversity was observed as highlighted by sharing of the same influenza strain between different households within each community. The limited intra-household sequence drift is in line with previous studies also using Sanger sequencing, corroborating the presence of strict selective bottlenecks that limit sequence variance. We were not able to directly ascertain the effect of HIV on influenza sequence drift between transmission events.

Intermittent treatment of severe influenza

Severe, long-lasting influenza infections are often caused by new strains of the virus. The long duration of these infections leads to an increased opportunity for the emergence of drug resistant mutants. This is particularly problematic since for new strains there is often no vaccine, so drug treatment is the first line of defense. One strategy for trying to minimize drug resistance is to apply drugs periodically. During treatment phases the wild-type virus decreases, but resistant virus might increase; when there is no treatment, wild-type virus will hopefully out-compete the resistant virus, driving down the number of resistant virus. A stochastic model of severe influenza is combined with a model of drug resistance to simulate long-lasting infections and intermittent treatment with two types of antivirals: neuraminidase inhibitors, which block release of virions; and adamantanes, which block replication of virions. Each drug's ability to reduce emergence of drug resistant mutants is investigated. We find that cell regeneration is required for successful implementation of intermittent treatment and that the optimal cycling parameters change with regeneration rate.

Predictive Modeling of Influenza Shows the Promise of Applied Evolutionary Biology

Seasonal influenza is controlled through vaccination campaigns. Evolution of influenza virus antigens means that vaccines must be updated to match novel strains, and vaccine effectiveness depends on the ability of scientists to predict nearly a year in advance which influenza variants will dominate in upcoming seasons. In this review, we highlight a promising new surveillance tool: predictive models. Based on data-sharing and close collaboration between the World Health Organization and academic scientists, these models use surveillance data to make quantitative predictions regarding influenza evolution. Predictive models demonstrate the potential of applied evolutionary biology to improve public health and disease control. We review the state of influenza predictive modeling and discuss next steps and recommendations to ensure that these models deliver upon their considerable biomedical promise.

The Combined Effect of Oseltamivir and Favipiravir on Influenza A Virus Evolution

Influenza virus inflicts a heavy death toll annually and resistance to existing antiviral drugs has generated interest in the development of agents with novel mechanisms of action. Favipiravir is an antiviral drug that acts by increasing the genome-wide mutation rate of influenza A virus (IAV). Potential synergistic benefits of combining oseltamivir and favipiravir have been demonstrated in animal models of influenza, but the population-level effects of combining the drugs are unknown. In order to elucidate the underlying evolutionary processes at play, we performed genome-wide sequencing of IAV experimental populations subjected to serial passaging in vitro under a combined protocol of oseltamivir and favipiravir. We describe the interplay between mutation, selection, and genetic drift that ultimately culminates in population extinction. In particular, selective sweeps around oseltamivir resistance mutations reduce genome-wide variation while deleterious mutations hitchhike to fixation given the increased mutational load generated by favipiravir. This latter effect reduces viral fitness and accelerates extinction compared with IAV populations treated with favipiravir alone, but risks spreading both established and newly emerging mutations, including possible drug resistance mutations, if transmission occurs before the viral populations are eradicated.

Oseltamivir-zanamivir combination therapy suppresses drug-resistant H1N1 influenza A viruses in the hollow fiber infection model (HFIM) system

Drug-resistant influenza is a significant threat to global public health. Until new antiviral agents with novel mechanisms of action become available, there is a pressing need for alternative treatment strategies with available influenza antivirals. Our aims were to evaluate the antiviral activity of two neuraminidase inhibitors (oseltamivir and zanamivir) as combination therapy against H1N1 influenza A viruses, as these agents bind to the neuraminidase active site differently: oseltamivir requires a conformational change for binding whereas zanamivir does not. We performed pharmacodynamic studies in the hollow fiber infection model (HFIM) system with oseltamivir (75mg Q12h, t1/2: 8h) and zanamivir (600mg Q12h, t1/2: 2.5h), given as mono- or combination therapy, against viruses with varying susceptibilities to oseltamivir and zanamivir. Each antiviral suppressed the replication of influenza strains which were resistant to the other neuraminidase inhibitor, showing each drug does not engender cross-resistance to the other compound. Oseltamivir/zanamivir combination therapy was as effective at suppressing oseltamivir- and zanamivir-resistant influenza viruses and the combination regimen inhibited viral replication at a level that was similar to the most effective monotherapy arm. However, combination therapy offered a clear benefit by preventing the emergence and spread of drug-resistant viruses. These findings demonstrate that combination therapy with two agents that target the same viral protein through distinctly different binding interactions is a feasible strategy to combat resistance emergence. This is a novel finding that may be applicable to other viral and non-viral diseases for which different classes of agents do not exist.

Transmission Bottleneck Size Estimation from Pathogen Deep-Sequencing Data, with an Application to Human Influenza A Virus

The bottleneck governing infectious disease transmission describes the size of the pathogen population transferred from the donor to the recipient host. Accurate quantification of the bottleneck size is particularly important for rapidly evolving pathogens such as influenza virus, as narrow bottlenecks reduce the amount of transferred viral genetic diversity and, thus, may decrease the rate of viral adaptation. Previous studies have estimated bottleneck sizes governing viral transmission by using statistical analyses of variants identified in pathogen sequencing data. These analyses, however, did not account for variant calling thresholds and stochastic viral replication dynamics within recipient hosts. Because these factors can skew bottleneck size estimates, we introduce a new method for inferring bottleneck sizes that accounts for these factors. Through the use of a simulated data set, we first show that our method, based on beta-binomial sampling, accurately recovers transmission bottleneck sizes, whereas other methods fail to do so. We then apply our method to a data set of influenza A virus (IAV) infections for which viral deep-sequencing data from transmission pairs are available. We find that the IAV transmission bottleneck size estimates in this study are highly variable across transmission pairs, while the mean bottleneck size of 196 virions is consistent with a previous estimate for this data set. Furthermore, regression analysis shows a positive association between estimated bottleneck size and donor infection severity, as measured by temperature. These results support findings from experimental transmission studies showing that bottleneck sizes across transmission events can be variable and influenced in part by epidemiological factors.IMPORTANCE The transmission bottleneck size describes the size of the pathogen population transferred from the donor to the recipient host and may affect the rate of pathogen adaptation within host populations. Recent advances in sequencing technology have enabled bottleneck size estimation from pathogen genetic data, although there is not yet a consistency in the statistical methods used. Here, we introduce a new approach to infer the bottleneck size that accounts for variant identification protocols and noise during pathogen replication. We show that failing to account for these factors leads to an underestimation of bottleneck sizes. We apply this method to an existing data set of human influenza virus infections, showing that transmission is governed by a loose, but highly variable, transmission bottleneck whose size is positively associated with the severity of infection of the donor. Beyond advancing our understanding of influenza virus transmission, we hope that this work will provide a standardized statistical approach for bottleneck size estimation for viral pathogens.

Evolution of the neuraminidase gene of seasonal influenza A and B viruses in Thailand between 2010 and 2015

The neuraminidase inhibitors (NAIs) oseltamivir and zanamivir are commonly used for the treatment and control of influenza A and B virus infection. However, the emergence of new influenza virus strains with reduced susceptibility to NAIs may appear with the use of these antivirals or even naturally. We therefore screened the neuraminidase (NA) sequences of seasonal influenza virus A(H1N1), A(H1N1)pdm09, A(H3N2), and influenza B virus strains identified in Thailand for the presence of substitutions previously reported to reduce susceptibility to NAIs. We initially examined oseltamivir resistance (characterized by the H275Y mutation in the NA gene) in 485 A(H1N1)pdm09 strains circulating in Thailand and found that 0.82% (4/485) had this substitution. To further evaluate the evolution of the NA gene, we also randomly selected 98 A(H1N1)pdm09, 158 A(H3N2), and 69 influenza B virus strains for NA gene amplification and sequencing, which revealed various amino acid mutations in the active site of the NA protein previously shown to be associated with reduced susceptibility to NAIs. Phylogenetic analysis of the influenza virus strains from this study and elsewhere around the world, together with the estimations of nucleotide substitution rates and selection pressure, and the predictions of B-cell epitopes and N-linked glycosylation sites all provided evidence for the ongoing evolution of NA. The overall rates of NA evolution for influenza A viruses were higher than for influenza B virus at the nucleotide level, although influenza B virus possessed more genealogical diversity than that of influenza A viruses. The continual surveillance of the antigenic changes associated with the NA protein will not only contribute to the influenza virus database but may also provide a better understanding of selection pressure exerted by antiviral use.

The effective rate of influenza reassortment is limited during human infection

We characterise the evolutionary dynamics of influenza infection described by viral sequence data collected from two challenge studies conducted in human hosts. Viral sequence data were collected at regular intervals from infected hosts. Changes in the sequence data observed across time show that the within-host evolution of the virus was driven by the reversion of variants acquired during previous passaging of the virus. Treatment of some patients with oseltamivir on the first day of infection did not lead to the emergence of drug resistance variants in patients. Using an evolutionary model, we inferred the effective rate of reassortment between viral segments, measuring the extent to which randomly chosen viruses within the host exchange genetic material. We find strong evidence that the rate of effective reassortment is low, such that genetic associations between polymorphic loci in different segments are preserved during the course of an infection in a manner not compatible with epistasis. Combining our evidence with that of previous studies we suggest that spatial heterogeneity in the viral population may reduce the extent to which reassortment is observed. Our results do not contradict previous findings of high rates of viral reassortment in vitro and in small animal studies, but indicate that in human hosts the effective rate of reassortment may be substantially more limited.

The influenza virus is an important cause of disease in the human population. During the course of an infection the virus can evolve rapidly. An important mechanism of viral evolution is reassortment, whereby different segments of the influenza genome are shuffled with other segments, producing new viral combinations. Here we study natural selection and reassortment during the course of infections occurring in human hosts. Examining viral genome sequence data from these infections, we note that genetic variants that were acquired during the growth of viruses in culture are selected against in the human host. In addition, we find evidence that the effective rate of reassortment is low. We suggest that the spatial separation between viruses in different parts of the host airway may limit the extent to which genetically distinct segments reassort with one another. Within the global population of influenza viruses, reassortment remains an important factor. However, reassortment is not so rapid as to exclude the possibility of interactions between genome segments affecting the course of influenza evolution during a single infection.

Vaccination has minimal impact on the intrahost diversity of H3N2 influenza viruses

While influenza virus diversity and antigenic drift have been well characterized on a global scale, the factors that influence the virus’ rapid evolution within and between human hosts are less clear. Given the modest effectiveness of seasonal vaccination, vaccine-induced antibody responses could serve as a potent selective pressure for novel influenza variants at the individual or community level. We used next generation sequencing of patient-derived viruses from a randomized, placebo-controlled trial of vaccine efficacy to characterize the diversity of influenza A virus and to define the impact of vaccine-induced immunity on within-host populations. Importantly, this study design allowed us to isolate the impact of vaccination while still studying natural infection. We used pre-season hemagglutination inhibition and neuraminidase inhibition titers to quantify vaccine-induced immunity directly and to assess its impact on intrahost populations. We identified 166 cases of H3N2 influenza over 3 seasons and 5119 person-years. We obtained whole genome sequence data for 119 samples and used a stringent and empirically validated analysis pipeline to identify intrahost single nucleotide variants at ≥1% frequency. Phylogenetic analysis of consensus hemagglutinin and neuraminidase sequences showed no stratification by pre-season HAI and NAI titer, respectively. In our study population, we found that the vast majority of intrahost single nucleotide variants were rare and that very few were found in more than one individual. Most samples had fewer than 15 single nucleotide variants across the entire genome, and the level of diversity did not significantly vary with day of sampling, vaccination status, or pre-season antibody titer. Contrary to what has been suggested in experimental systems, our data indicate that seasonal influenza vaccination has little impact on intrahost diversity in natural infection and that vaccine-induced immunity may be only a minor contributor to antigenic drift at local scales.

Influenza is a significant global health problem. Vaccination is the best way to prevent influenza virus infection, and seasonal influenza vaccines are considered for reformulation each year in order to keep up with the virus’ evolution. Despite these efforts, vaccine recipients often develop an immune response that does not protect from infection. Given the current recommendation that all people over 6 months of age get vaccinated, it is important to understand how vaccination itself may impact viral evolution during natural human infection. We studied how vaccination may alter viral evolution within individuals, as each person harbors many highly-related influenza variants that differ in their ability to escape the immune response. We compared groups of people in a vaccine trial to determine the impact that vaccination has on viral diversity and variant selection within individuals. We did not detect significant differences in the number of variants detected or in the prevalence of mutations that could impact antibody binding based on vaccination group or antibody response. Our work suggests that vaccination is not a major factor in driving the emergence of new influenza strains at the level of the individual host.

Understanding the complex evolution of rapidly mutating viruses with deep sequencing: Beyond the analysis of viral diversity

With the advent of affordable deep sequencing technologies, detection of low frequency variants within genetically diverse viral populations can now be achieved with unprecedented depth and efficiency. The high-resolution data provided by next generation sequencing technologies is currently recognised as the gold standard in estimation of viral diversity. In the analysis of rapidly mutating viruses, longitudinal deep sequencing datasets from viral genomes during individual infection episodes, as well as at the epidemiological level during outbreaks, now allow for more sophisticated analyses such as statistical estimates of the impact of complex mutation patterns on the evolution of the viral populations both within and between hosts. These analyses are revealing more accurate descriptions of the evolutionary dynamics that underpin the rapid adaptation of these viruses to the host response, and to drug therapies. This review assesses recent developments in methods and provide informative research examples using deep sequencing data generated from rapidly mutating viruses infecting humans, particularly hepatitis C virus (HCV), human immunodeficiency virus (HIV), Ebola virus and influenza virus, to understand the evolution of viral genomes and to explore the relationship between viral mutations and the host adaptive immune response. Finally, we discuss limitations in current technologies, and future directions that take advantage of publically available large deep sequencing datasets.

An experimental evaluation of drug-induced mutational meltdown as an antiviral treatment strategy

The rapid evolution of drug resistance remains a critical public health concern. The treatment of influenza A virus (IAV) has proven particularly challenging, due to the ability of the virus to develop resistance against current antivirals and vaccines. Here, we evaluate a novel antiviral drug therapy, favipiravir, for which the mechanism of action in IAV involves an interaction with the viral RNA-dependent RNA polymerase resulting in an effective increase in the viral mutation rate. We used an experimental evolution framework, combined with novel population genetic method development for inference from time-sampled data, to evaluate the effectiveness of favipiravir against IAV. Evaluating whole genome polymorphism data across 15 time points under multiple drug concentrations and in controls, we present the first evidence for the ability of IAV populations to effectively adapt to low concentrations of favipiravir. In contrast, under high concentrations, we observe population extinction, indicative of mutational meltdown. We discuss the observed dynamics with respect to the evolutionary forces at play and emphasize the utility of evolutionary theory to inform drug development.

Droplet digital PCR to investigate quasi-species at codons 119 and 275 of the A(H1N1)pdm09 neuraminidase during zanamivir and oseltamivir therapies

The H275Y and E119D neuraminidase (NA) mutations constitute important molecular markers of resistance to NA inhibitors in A(H1N1) pdm09 viruses. We used reverse transcriptase-droplet digital PCR amplification (RT-ddPCR) to analyze quasi-species at codons 275 and 119 of the NA in A(H1N1) pdm09 viruses recovered from an immuncompromised patient who received oseltamivir and zanamivir therapies. RT-ddPCR assays detected and quantified H275Y and E119D mutations with an efficiency that was comparable to that of high throughput sequencing (HiSeq 2500 Illumina, San Diego, CA) technology. With its sensitivity and reproducibility, RT-ddPCR could be a reliable method for accurate detection and quantification of major NAI-resistance mutations in clinical settings. J. Med. Virol. 89:737-741, 2017. © 2016 Wiley Periodicals, Inc.

Genomic Analysis of the Emergence, Evolution, and Spread of Human Respiratory RNA Viruses

The emergence and reemergence of rapidly evolving RNA viruses-particularly those responsible for respiratory diseases, such as influenza viruses and coronaviruses-pose a significant threat to global health, including the potential of major pandemics. Importantly, recent advances in high-throughput genome sequencing enable researchers to reveal the genomic diversity of these viral pathogens at much lower cost and with much greater precision than they could before. In particular, the genome sequence data generated allow inferences to be made on the molecular basis of viral emergence, evolution, and spread in human populations in real time. In this review, we introduce recent computational methods that analyze viral genomic data, particularly in combination with metadata such as sampling time, geographic location, and virulence. We then outline the insights these analyses have provided into the fundamental patterns and processes of evolution and emergence in human respiratory RNA viruses, as well as the major challenges in such genomic analyses.

Deep Sequencing Reveals Potential Antigenic Variants at Low Frequencies in Influenza A Virus-Infected Humans

Influenza vaccines must be frequently reformulated to account for antigenic changes in the viral envelope protein, hemagglutinin (HA). The rapid evolution of influenza virus under immune pressure is likely enhanced by the virus's genetic diversity within a host, although antigenic change has rarely been investigated on the level of individual infected humans. We used deep sequencing to characterize the between- and within-host genetic diversity of influenza viruses in a cohort of patients that included individuals who were vaccinated and then infected in the same season. We characterized influenza HA segments from the predominant circulating influenza A subtypes during the 2012-2013 (H3N2) and 2013-2014 (pandemic H1N1; H1N1pdm) flu seasons. We found that HA consensus sequences were similar in nonvaccinated and vaccinated subjects. In both groups, purifying selection was the dominant force shaping HA genetic diversity. Interestingly, viruses from multiple individuals harbored low-frequency mutations encoding amino acid substitutions in HA antigenic sites at or near the receptor-binding domain. These mutations included two substitutions in H1N1pdm viruses, G158K and N159K, which were recently found to confer escape from virus-specific antibodies. These findings raise the possibility that influenza antigenic diversity can be generated within individual human hosts but may not become fixed in the viral population even when they would be expected to have a strong fitness advantage. Understanding constraints on influenza antigenic evolution within individual hosts may elucidate potential future pathways of antigenic evolution at the population level.

IMPORTANCE

Influenza vaccines must be frequently reformulated due to the virus's rapid evolution rate. We know that influenza viruses exist within each infected host as a "swarm" of genetically distinct viruses, but the role of this within-host diversity in the antigenic evolution of influenza has been unclear. We characterized here the genetic and potential antigenic diversity of influenza viruses infecting humans, some of whom became infected despite recent vaccination. Influenza virus between- and within-host genetic diversity was not significantly different in nonvaccinated and vaccinated humans, suggesting that vaccine-induced immunity does not exert strong selective pressure on viruses replicating in individual people. We found low-frequency mutations, below the detection threshold of traditional surveillance methods, in nonvaccinated and vaccinated humans that were recently associated with antibody escape. Interestingly, these potential antigenic variants did not reach fixation in infected people, suggesting that other evolutionary factors may be hindering their emergence in individual humans.

Detection of Rare Drug Resistance Mutations by Digital PCR in a Human Influenza A Virus Model System and Clinical Samples

Digital PCR (dPCR) is being increasingly used for the quantification of sequence variations, including single nucleotide polymorphisms (SNPs), due to its high accuracy and precision in comparison with techniques such as quantitative PCR (qPCR) and melt curve analysis. To develop and evaluate dPCR for SNP detection using DNA, RNA, and clinical samples, an influenza virus model of resistance to oseltamivir (Tamiflu) was used. First, this study was able to recognize and reduce off-target amplification in dPCR quantification, thereby enabling technical sensitivities down to 0.1% SNP abundance at a range of template concentrations, a 50-fold improvement on the qPCR assay used routinely in the clinic. Second, a method was developed for determining the false-positive rate (background) signal. Finally, comparison of dPCR with qPCR results on clinical samples demonstrated the potential impact dPCR could have on clinical research and patient management by earlier (trace) detection of rare drug-resistant sequence variants. Ultimately this could reduce the quantity of ineffective drugs taken and facilitate early switching to alternative medication when available. In the short term such methods could advance our understanding of microbial dynamics and therapeutic responses in a range of infectious diseases such as HIV, viral hepatitis, and tuberculosis. Furthermore, the findings presented here are directly relevant to other diagnostic areas, such as the detection of rare SNPs in malignancy, monitoring of graft rejection, and fetal screening.

Clinical Implications of Antiviral Resistance in Influenza

Influenza is a major cause of severe respiratory infections leading to excessive hospitalizations and deaths globally; annual epidemics, pandemics, and sporadic/endemic avian virus infections occur as a result of rapid, continuous evolution of influenza viruses. Emergence of antiviral resistance is of great clinical and public health concern. Currently available antiviral treatments include four neuraminidase inhibitors (oseltamivir, zanamivir, peramivir, laninamivir), M2-inibitors (amantadine, rimantadine), and a polymerase inhibitor (favipiravir). In this review, we focus on resistance issues related to the use of neuraminidase inhibitors (NAIs). Data on primary resistance, as well as secondary resistance related to NAI exposure will be presented. Their clinical implications, detection, and novel therapeutic options undergoing clinical trials are discussed.

Optimization of Droplet Digital PCR from RNA and DNA extracts with direct comparison to RT-qPCR: Clinical implications for quantification of Oseltamivir-resistant subpopulations

The recent introduction of Droplet Digital PCR (ddPCR) has provided researchers with a tool that permits direct quantification of nucleic acids from a wide range of samples with increased precision and sensitivity versus RT-qPCR. The sample interdependence of RT-qPCR stemming from the measurement of Cq and ΔCq values is eliminated with ddPCR which provides an independent measure of the absolute nucleic acid concentration for each sample without standard curves thereby reducing inter-well and inter-plate variability. Well-characterized RNA purified from H275-wild type (WT) and H275Y-point mutated (MUT) neuraminidase of influenza A (H1N1) pandemic 2009 virus was used to demonstrate a ddPCR optimization workflow to assure robust data for downstream analysis. The ddPCR reaction mix was also tested with RT-qPCR and gave excellent reaction efficiency (between 90% and 100%) with the optimized MUT/WT duplexed assay thus enabling the direct comparison of the two platforms from the same reaction mix and thermal cycling protocol. ddPCR gave a marked improvement in sensitivity (>30-fold) for mutation abundance using a mixture of purified MUT and WT RNA and increased precision (>10 fold, p<0.05 for both inter- and intra-assay variability) versus RT-qPCR from patient samples to accurately identify residual mutant viral population during recovery.

Emerging and resistant infections

The lungs are a major target for infection and a key battleground in the fight against the development of antimicrobial drug-resistant pathogens. Ventilator-associated pneumonia (VAP) is associated with mortality rates of 24-50%. The optimal duration of antibiotic therapy against VAP is unknown, but prolonged courses are associated with the emergence of bacterial resistance. De-escalation strategies in which treatment is discontinued based on signs of clinical resolution, fixed durations of therapy (generally 7-8 d), or serum procalcitonin responses have been shown to decrease antibiotic consumption. Outcomes are comparable to longer treatment courses, with the possible exception of VAP due to nonfermenting, gram-negative bacilli such as Pseudomonas aeruginosa. Staphylococcus aureus is a leading cause of VAP and other infections. Outcomes after S. aureus infection are shaped by the interplay between environmental, bacterial, and host genetic factors. It is increasingly clear that mechanisms of pathogenesis vary in different types of S. aureus infections. Genome-scale studies of S. aureus strains, host responses, and host genetics are redefining our understanding of the pathogenic mechanisms underlying VAP. Genome-sequencing technologies are also revolutionizing our understanding of the molecular epidemiology, evolution, and transmission of influenza. Deep sequencing using next-generation technology platforms is defining the remarkable genetic diversity of influenza strains within infected hosts. Investigators have demonstrated that antiviral drug-resistant influenza may be present prior to the initiation of treatment. Moreover, drug-resistant minor variant influenza strains can be transmitted from person to person in the absence of selection pressure. Studies of lung infections and the causative pathogens will remain at the cutting edge of clinical and basic medical research.

Deep sequencing analysis of viral infection and evolution allows rapid and detailed characterization of viral mutant spectrum

Motivation: The study of RNA virus populations is a challenging task. Each population of RNA virus is composed of a collection of different, yet related genomes often referred to as mutant spectra or quasispecies. Virologists using deep sequencing technologies face major obstacles when studying virus population dynamics, both experimentally and in natural settings due to the relatively high error rates of these technologies and the lack of high performance pipelines. In order to overcome these hurdles we developed a computational pipeline, termed ViVan (Viral Variance Analysis). ViVan is a complete pipeline facilitating the identification, characterization and comparison of sequence variance in deep sequenced virus populations.

Results: Applying ViVan on deep sequenced data obtained from samples that were previously characterized by more classical approaches, we uncovered novel and potentially crucial aspects of virus populations. With our experimental work, we illustrate how ViVan can be used for studies ranging from the more practical, detection of resistant mutations and effects of antiviral treatments, to the more theoretical temporal characterization of the population in evolutionary studies.

Availability and implementation: Freely available on the web at http://www.vivanbioinfo.org

Contact: nshomron@post.tau.ac.il

Supplementary information:Supplementary data are available at Bioinformatics online.

Effective lethal mutagenesis of influenza virus by three nucleoside analogs

Lethal mutagenesis is a broad-spectrum antiviral strategy that exploits the high mutation rate and low mutational tolerance of many RNA viruses. This approach uses mutagenic drugs to increase viral mutation rates and burden viral populations with mutations that reduce the number of infectious progeny. We investigated the effectiveness of lethal mutagenesis as a strategy against influenza virus using three nucleoside analogs, ribavirin, 5-azacytidine, and 5-fluorouracil. All three drugs were active against a panel of seasonal H3N2 and laboratory-adapted H1N1 strains. We found that each drug increased the frequency of mutations in influenza virus populations and decreased the virus' specific infectivity, indicating a mutagenic mode of action. We were able to drive viral populations to extinction by passaging influenza virus in the presence of each drug, indicating that complete lethal mutagenesis of influenza virus populations can be achieved when a sufficient mutational burden is applied. Population-wide resistance to these mutagenic agents did not arise after serial passage of influenza virus populations in sublethal concentrations of drug. Sequencing of these drug-passaged viral populations revealed genome-wide accumulation of mutations at low frequency. The replicative capacity of drug-passaged populations was reduced at higher multiplicities of infection, suggesting the presence of defective interfering particles and a possible barrier to the evolution of resistance. Together, our data suggest that lethal mutagenesis may be a particularly effective therapeutic approach with a high genetic barrier to resistance for influenza virus.

IMPORTANCE

Influenza virus is an RNA virus that causes significant morbidity and mortality during annual epidemics. Novel therapies for RNA viruses are needed due to the ease with which these viruses evolve resistance to existing therapeutics. Lethal mutagenesis is a broad-spectrum strategy that exploits the high mutation rate and the low mutational tolerance of most RNA viruses. It is thought to possess a higher barrier to resistance than conventional antiviral strategies. We investigated the effectiveness of lethal mutagenesis against influenza virus using three different drugs. We showed that influenza virus was sensitive to lethal mutagenesis by demonstrating that all three drugs induced mutations and led to an increase in the generation of defective viral particles. We also found that it may be difficult for resistance to these drugs to arise at a population-wide level. Our data suggest that lethal mutagenesis may be an attractive anti-influenza strategy that warrants further investigation.

Multiple influenza A (H3N2) mutations conferring resistance to neuraminidase inhibitors in a bone marrow transplant recipient

Immunocompromised patients are predisposed to infections caused by influenza virus. Influenza virus may produce considerable morbidity, including protracted illness and prolonged viral shedding in these patients, thus prompting higher doses and prolonged courses of antiviral therapy. This approach may promote the emergence of resistant strains. Characterization of neuraminidase (NA) inhibitor (NAI)-resistant strains of influenza A virus is essential for documenting causes of resistance. In this study, using quantitative real-time PCR along with conventional Sanger sequencing, we identified an NAI-resistant strain of influenza A (H3N2) virus in an immunocompromised patient. In-depth analysis by deep gene sequencing revealed that various known markers of antiviral resistance, including transient R292K and Q136K substitutions and a sustained E119K (N2 numbering) substitution in the NA protein emerged during prolonged antiviral therapy. In addition, a combination of a 4-amino-acid deletion at residues 245 to 248 (Δ245-248) accompanied by the E119V substitution occurred, causing resistance to or reduced inhibition by NAIs (oseltamivir, zanamivir, and peramivir). Resistant variants within a pool of viral quasispecies arose during combined antiviral treatment. More research is needed to understand the interplay of drug resistance mutations, viral fitness, and transmission.

Evolution of oseltamivir resistance mutations in Influenza A(H1N1) and A(H3N2) viruses during selection in experimentally infected mice

The evolution of oseltamivir resistance mutations during selection through serial passages in animals is still poorly described. Herein, we assessed the evolution of neuraminidase (NA) and hemagglutinin (HA) genes of influenza A/WSN/33 (H1N1) and A/Victoria/3/75 (H3N2) viruses recovered from the lungs of experimentally infected BALB/c mice receiving suboptimal doses (0.05 and 1 mg/kg of body weight/day) of oseltamivir over two generations. The traditional phenotypic and genotypic methods as well as deep-sequencing analysis were used to characterize the potential selection of mutations and population dynamics of oseltamivir-resistant variants. No oseltamivir-resistant NA or HA changes were detected in the recovered A/WSN/33 viruses. However, we observed a positive selection of the I222T NA substitution in the recovered A/Victoria/3/75 viruses, with a frequency increasing over time and with an oseltamivir concentration from 4% in the initial pretherapy inoculum up to 28% after two lung passages. Although the presence of mixed I222T viral populations in mouse lungs only led to a minimal increase in oseltamivir 50% enzyme-inhibitory concentrations (IC50s) (by a mean of 5.7-fold) compared to that of the baseline virus, the expressed recombinant A/Victoria/3/75 I222T NA protein displayed a 16-fold increase in the oseltamivir IC50 level compared to that of the recombinant wild type (WT). In conclusion, the combination of serial in vivo passages under neuraminidase inhibitor (NAI) pressure and temporal deep-sequencing analysis enabled, for the first time, the identification and selection of the oseltamivir-resistant I222T NA mutation in an influenza H3N2 virus. Additional in vivo selection experiments with other antivirals and drug combinations might provide important information on the evolution of antiviral resistance in influenza viruses.

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

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

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

Andrographolide as an anti-H1N1 drug and the mechanism related to retinoic acid-inducible gene-I-like receptors signaling pathway

OBJECTIVE

To observe the anti-virus effects of andrographolide (AD) on the retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) signaling pathway when immunological cells were infected with H1N1.

METHODS

Leukomonocyte was obtained from umbilical cord blood by Ficoll density gradient centrifugation, and immunological cells were harvested after cytokines stimulation. Virus infected cell model was established by H1N1 co-cultured with normal human bronchial epithelial cell line (16HBE). The optimal concentration of AD was defined by methyl-thiazolyl-tetrazolium (MTT) assay. After the virus infected cell model was established, AD was added into the medium as a treatment intervention. After 24-h co-culture, cell supernatant was collected for interferon gamma (IFN-γ) and interleukin-4 (IL-4) enzyme-linked immunosorbent assay (ELISA) detection while immunological cells for real-time polymerase chain reaction (RT-PCR).

RESULTS

The optimal concentration of AD for anti-virus effect was 250 μg/mL. IL-4 and IFN-γ in the supernatant and mRNA levels in RLRs pathway increased when cells was infected by virus, RIG-I, IFN-β promoter stimulator-1 (IPS-1), interferon regulatory factor (IRF)-7, IRF-3 and nuclear transcription factor κB (NF-κB) mRNA levels increased significantly (P<0.05). When AD was added into co-culture medium, the levels of IL-4 and IFN-γ were lower than those in the non-interference groups and the mRNA expression levels decreased, RIG-I, IPS-1, IRF-7, IRF-3 and NF-κB decreased significantly in each group with significant statistic differences (P<0.05).

CONCLUSIONS

The RLRs mediated viral recognition provided a potential molecular target for acute viral infections and andrographolide could ameliorate H1N1 virus-induced cell mortality. And the antiviral effects might be related to its inhibition of viral-induced activation of the RLRs signaling pathway.

Deep sequencing: becoming a critical tool in clinical virology

Population (Sanger) sequencing has been the standard method in basic and clinical DNA sequencing for almost 40 years; however, next-generation (deep) sequencing methodologies are now revolutionizing the field of genomics, and clinical virology is no exception. Deep sequencing is highly efficient, producing an enormous amount of information at low cost in a relatively short period of time. High-throughput sequencing techniques have enabled significant contributions to multiples areas in virology, including virus discovery and metagenomics (viromes), molecular epidemiology, pathogenesis, and studies of how viruses to escape the host immune system and antiviral pressures. In addition, new and more affordable deep sequencing-based assays are now being implemented in clinical laboratories. Here, we review the use of the current deep sequencing platforms in virology, focusing on three of the most studied viruses: human immunodeficiency virus (HIV), hepatitis C virus (HCV), and influenza virus.

Detection and management of antiviral resistance for influenza viruses

Neuraminidase inhibitors (NAIs) are first-line agents for the treatment and prevention of influenza virus infections. As for other antivirals, the development of resistance to NAIs has become an important concern particularly in the case of A(H1N1) viruses and oseltamivir. The most frequently reported change conferring oseltamivir resistance in that viral context is the H275Y neuraminidase mutation (N1 numbering). Recent studies have shown that, in the presence of the appropriate permissive mutations, the H275Y variant can retain virulence and transmissibility in some viral backgrounds. Most oseltamivir-resistant influenza A virus infections can be managed with the use of inhaled or intravenous zanamivir, another NAI. New NAI compounds and non-neuraminidase agents as well as combination therapies are currently in clinical evaluation for the treatment for severe influenza infections.

Influenza virus drug resistance: a time-sampled population genetics perspective

The challenge of distinguishing genetic drift from selection remains a central focus of population genetics. Time-sampled data may provide a powerful tool for distinguishing these processes, and we here propose approximate Bayesian, maximum likelihood, and analytical methods for the inference of demography and selection from time course data. Utilizing these novel statistical and computational tools, we evaluate whole-genome datasets of an influenza A H1N1 strain in the presence and absence of oseltamivir (an inhibitor of neuraminidase) collected at thirteen time points. Results reveal a striking consistency amongst the three estimation procedures developed, showing strongly increased selection pressure in the presence of drug treatment. Importantly, these approaches re-identify the known oseltamivir resistance site, successfully validating the approaches used. Enticingly, a number of previously unknown variants have also been identified as being positively selected. Results are interpreted in the light of Fisher's Geometric Model, allowing for a quantification of the increased distance to optimum exerted by the presence of drug, and theoretical predictions regarding the distribution of beneficial fitness effects of contending mutations are empirically tested. Further, given the fit to expectations of the Geometric Model, results suggest the ability to predict certain aspects of viral evolution in response to changing host environments and novel selective pressures.

Evolution of the influenza A virus genome during development of oseltamivir resistance in vitro

Influenza A virus (IAV) is a major cause of morbidity and mortality throughout the world. Current antiviral therapies include oseltamivir, a neuraminidase inhibitor that prevents the release of nascent viral particles from infected cells. However, the IAV genome can evolve rapidly, and oseltamivir resistance mutations have been detected in numerous clinical samples. Using an in vitro evolution platform and whole-genome population sequencing, we investigated the population genomics of IAV during the development of oseltamivir resistance. Strain A/Brisbane/59/2007 (H1N1) was grown in Madin-Darby canine kidney cells with or without escalating concentrations of oseltamivir over serial passages. Following drug treatment, the H274Y resistance mutation fixed reproducibly within the population. The presence of the H274Y mutation in the viral population, at either a low or a high frequency, led to measurable changes in the neuraminidase inhibition assay. Surprisingly, fixation of the resistance mutation was not accompanied by alterations of viral population diversity or differentiation, and oseltamivir did not alter the selective environment. While the neighboring K248E mutation was also a target of positive selection prior to H274Y fixation, H274Y was the primary beneficial mutation in the population. In addition, once evolved, the H274Y mutation persisted after the withdrawal of the drug, even when not fixed in viral populations. We conclude that only selection of H274Y is required for oseltamivir resistance and that H274Y is not deleterious in the absence of the drug. These collective results could offer an explanation for the recent reproducible rise in oseltamivir resistance in seasonal H1N1 IAV strains in humans.

Emergence of an oseltamivir-resistant influenza A/H3N2 virus in an elderly patient receiving a suboptimal dose of antiviral prophylaxis

We report the emergence of an influenza virus A/H3N2-E119V neuraminidase variant from an elderly patient with renal dysfunction who received a suboptimal dose of oseltamivir prophylaxis. In neuraminidase inhibition assays, the E119V variant showed a 413-fold increase in the 50% inhibitory oseltamivir concentration and grew at titers comparable to those of the wild type in vitro.

3D Molecular Modelling Study of the H7N9 RNA-Dependent RNA Polymerase as an Emerging Pharmacological Target

Currently not much is known about the H7N9 strain, and this is the major drawback for a scientific strategy to tackle this virus. Herein, the 3D complex structure of the H7N9 RNA-dependent RNA polymerase has been established using a repertoire of molecular modelling techniques including homology modelling, molecular docking, and molecular dynamics simulations. Strikingly, it was found that the oligonucleotide cleft and tunnel in the H7N9 RNA-dependent RNA polymerase are structurally very similar to the corresponding region on the hepatitis C virus RNA-dependent RNA polymerase crystal structure. A direct comparison and a 3D postdynamics analysis of the 3D complex of the H7N9 RNA-dependent RNA polymerase provide invaluable clues and insight regarding the role and mode of action of a series of interacting residues on the latter enzyme. Our study provides a novel and efficiently intergraded platform with structural insights for the H7N9 RNA-dependent RNA Polymerase. We propose that future use and exploitation of these insights may prove invaluable in the fight against this lethal, ongoing epidemic.

Using high-throughput sequencing to leverage surveillance of genetic diversity and oseltamivir resistance: a pilot study during the 2009 influenza A(H1N1) pandemic

BACKGROUND

Influenza viruses display a high mutation rate and complex evolutionary patterns. Next-generation sequencing (NGS) has been widely used for qualitative and semi-quantitative assessment of genetic diversity in complex biological samples. The "deep sequencing" approach, enabled by the enormous throughput of current NGS platforms, allows the identification of rare genetic viral variants in targeted genetic regions, but is usually limited to a small number of samples.

METHODOLOGY AND PRINCIPAL FINDINGS

We designed a proof-of-principle study to test whether redistributing sequencing throughput from a high depth-small sample number towards a low depth-large sample number approach is feasible and contributes to influenza epidemiological surveillance. Using 454-Roche sequencing, we sequenced at a rather low depth, a 307 bp amplicon of the neuraminidase gene of the Influenza A(H1N1) pandemic (A(H1N1)pdm) virus from cDNA amplicons pooled in 48 barcoded libraries obtained from nasal swab samples of infected patients (n  =  299) taken from May to November, 2009 pandemic period in Mexico. This approach revealed that during the transition from the first (May-July) to second wave (September-November) of the pandemic, the initial genetic variants were replaced by the N248D mutation in the NA gene, and enabled the establishment of temporal and geographic associations with genetic diversity and the identification of mutations associated with oseltamivir resistance.

CONCLUSIONS

NGS sequencing of a short amplicon from the NA gene at low sequencing depth allowed genetic screening of a large number of samples, providing insights to viral genetic diversity dynamics and the identification of genetic variants associated with oseltamivir resistance. Further research is needed to explain the observed replacement of the genetic variants seen during the second wave. As sequencing throughput rises and library multiplexing and automation improves, we foresee that the approach presented here can be scaled up for global genetic surveillance of influenza and other infectious diseases.

Influenza

Influenza is a common virus whose ability to change its genetic makeup allows for disease of pandemic proportion. This article summarizes the different strains of influenza circulating in the United States for the past century, the diagnosis and treatment of influenza, as well as the different ways to prevent disease. This information will be of value to clinicians caring for patients both in the hospital and in the community.

Progressive emergence of an oseltamivir-resistant A(H3N2) virus over two courses of oseltamivir treatment in an immunocompromised paediatric patient

A minor viral population of oseltamivir‐resistant A(H3N2) viruses (E119V neuraminidase mutation) was selected and maintained in a continually infected immunocompromised child following initial oseltamivir treatment. A subsequent course of oseltamivir given 7 weeks later rapidly selected for the E119V variant resulting in a near‐pure population of the resistant virus. The study highlights the challenges of oseltamivir treatment of immunocompromised patients that are continually shedding virus and demonstrates the ability of the E119V oseltamivir‐resistant virus to be maintained for prolonged periods even in the absence of drug‐selective pressure.

Ultra-deep mutant spectrum profiling: improving sequencing accuracy using overlapping read pairs

Backgound

High throughput sequencing is beginning to make a transformative impact in the area of viral evolution. Deep sequencing has the potential to reveal the mutant spectrum within a viral sample at high resolution, thus enabling the close examination of viral mutational dynamics both within- and between-hosts. The challenge however, is to accurately model the errors in the sequencing data and differentiate real viral mutations, particularly those that exist at low frequencies, from sequencing errors.

Results

We demonstrate that overlapping read pairs (ORP) -- generated by combining short fragment sequencing libraries and longer sequencing reads -- significantly reduce sequencing error rates and improve rare variant detection accuracy. Using this sequencing protocol and an error model optimized for variant detection, we are able to capture a large number of genetic mutations present within a viral population at ultra-low frequency levels (<0.05%).

Conclusions

Our rare variant detection strategies have important implications beyond viral evolution and can be applied to any basic and clinical research area that requires the identification of rare mutations.

Influenza virus resistance to antiviral therapy

Antiviral drugs for influenza therapy and prophylaxis are either of the adamantane or neuraminidase inhibitor (NAI) class. However, the NAIs are mainly prescribed nowadays, because of widespread adamantane resistance among influenza A viruses and ineffectiveness of adamantanes against influenza B. Emergence and spread of NAI resistance would further limit our therapeutic options. Taking into account the previous spread of oseltamivir-resistant viruses during the 2007/2008 season preceding the last pandemic, emergence of yet another naturally NAI-resistant influenza virus may not be an unlikely event. This previous incident also underlines the importance of resistance surveillance and asks for a better understanding of the mechanisms underlying primary resistance development. We provide an overview of the major influenza antiviral resistance mechanisms and future therapies for influenza. Here, we call for a better understanding of the effect of virus mutations upon antiviral treatment and for a tailored antiviral approach to severe influenza virus infections.