Rapid emergence of protease inhibitor resistance in hepatitis C virus

An oral non-covalent non-peptidic inhibitor of SARS-CoV-2 Mpro ameliorates viral replication and pathogenesis in vivo

Safe, effective, and low-cost oral antiviral therapies are needed to treat those at high risk for developing severe COVID-19. To that end, we performed a high-throughput screen to identify non-peptidic, non-covalent inhibitors of the SARS-CoV-2 main protease (Mpro), an essential enzyme in viral replication. NZ-804 was developed from a screening hit through iterative rounds of structure-guided medicinal chemistry. NZ-804 potently inhibits SARS-CoV-2 Mpro (0.009 μM IC50) as well as SARS-CoV-2 replication in human lung cell lines (0.008 μM EC50) and primary human airway epithelial cell cultures. Antiviral activity is maintained against distantly related sarbecoviruses and endemic human CoV OC43. In SARS-CoV-2 mouse and hamster disease models, NZ-804 therapy given once or twice daily significantly diminished SARS-CoV-2 replication and pathogenesis. NZ-804 synthesis is low cost and uncomplicated, simplifying global production and access. These data support the exploration of NZ-804 as a therapy for COVID-19 and future emerging sarbecovirus infections.

Effects of SARS-CoV-2 Main Protease Mutations at Positions L50, E166, and L167 Rendering Resistance to Covalent and Noncovalent Inhibitors

SARS-CoV-2 propagation under nirmatrelvir and ensitrelvir pressure selects for main protease (MPro) drug-resistant mutations E166V (DRM2), L50F/E166V (DRM3), E166A/L167F (DRM4), and L50F/E166A/L167F (DRM5). DRM2-DRM5 undergoes N-terminal autoprocessing to produce mature MPro with dimer dissociation constants (Kdimer) 2-3 times larger than that of the wildtype. Co-selection of L50F restores catalytic activity of DRM2 and DRM4 from ∼10 to 30%, relative to that of the wild-type enzyme, without altering Kdimer. Binding affinities and thermodynamic profiles that parallel the drug selection pressure, exhibiting significant decreases in affinity through entropy/enthalpy compensation, were compared with GC373. Reorganization of the active sites due to mutations observed in the inhibitor-free DRM3 and DRM4 structures as compared to MProWT may account for the reduced binding affinities, although DRM2 and DRM3 complexes with ensitrelvir are almost identical to MProWT-ensitrelvir. Chemical reactivity changes of the mutant active sites due to differences in electrostatic and protein dynamics effects likely contribute to losses in binding affinities.

Multidrug Combinations against SARS-CoV-2 Using GS-441524 or Ivermectin with Molnupiravir and/or Nirmatrelvir in Reconstituted Human Nasal Airway Epithelia

Background. The emergence, global spread, and persistence of SARS-CoV-2 resulted in an unprecedented need for effective antiviral drugs. Throughout the pandemic, various drug development and treatment strategies were adopted, including repurposing of antivirals designed for other viruses along with a multitude of other drugs with varying mechanisms of action (MoAs). Furthermore, multidrug treatment against COVID-19 is an ongoing topic and merits further investigation. Method/Objectives. We assessed the efficacy of multidrug treatment against SARS-CoV-2 in reconstituted human nasal epithelia, using combinations of molnupiravir and nirmatrelvir as a baseline, adding suboptimal concentrations of either GS-441524 or ivermectin, attempting to increase overall antiviral activity while lowering the overall therapeutic dose. Results. Nirmatrelvir combined with molnupiravir, GS-441524, or ivermectin at suboptimal concentrations show increased antiviral activity compared to single treatment. No triple combinations showed improved inhibition of SARS-CoV-2 replication beyond what was observed for double treatments. Conclusions. In general, we observed that the addition of a third compound is not beneficial for antiviral activity, while various double combinations exhibit increased antiviral activity over single treatment.

Modeling the emergence of viral resistance for SARS-CoV-2 during treatment with an anti-spike monoclonal antibody

To mitigate the loss of lives during the COVID-19 pandemic, emergency use authorization was given to several anti-SARS-CoV-2 monoclonal antibody (mAb) therapies for the treatment of mild-to-moderate COVID-19 in patients with a high risk of progressing to severe disease. Monoclonal antibodies used to treat SARS-CoV-2 target the spike protein of the virus and block its ability to enter and infect target cells. Monoclonal antibody therapy can thus accelerate the decline in viral load and lower hospitalization rates among high-risk patients with variants susceptible to mAb therapy. However, viral resistance has been observed, in some cases leading to a transient viral rebound that can be as large as 3-4 orders of magnitude. As mAbs represent a proven treatment choice for SARS-CoV-2 and other viral infections, evaluation of treatment-emergent mAb resistance can help uncover underlying pathobiology of SARS-CoV-2 infection and may also help in the development of the next generation of mAb therapies. Although resistance can be expected, the large rebounds observed are much more difficult to explain. We hypothesize replenishment of target cells is necessary to generate the high transient viral rebound. Thus, we formulated two models with different mechanisms for target cell replenishment (homeostatic proliferation and return from an innate immune response antiviral state) and fit them to data from persons with SARS-CoV-2 treated with a mAb. We showed that both models can explain the emergence of resistant virus associated with high transient viral rebounds. We found that variations in the target cell supply rate and adaptive immunity parameters have a strong impact on the magnitude or observability of the viral rebound associated with the emergence of resistant virus. Both variations in target cell supply rate and adaptive immunity parameters may explain why only some individuals develop observable transient resistant viral rebound. Our study highlights the conditions that can lead to resistance and subsequent viral rebound in mAb treatments during acute infection.

Combination Therapy with UV-4B and Molnupiravir Enhances SARS-CoV-2 Suppression

The host targeting antiviral, UV-4B, and the RNA polymerase inhibitor, molnupiravir, are two orally available, broad-spectrum antivirals that have demonstrated potent activity against SARS-CoV-2 as monotherapy. In this work, we evaluated the effectiveness of UV-4B and EIDD-1931 (molnupiravir's main circulating metabolite) combination regimens against the SARS-CoV-2 beta, delta, and omicron BA.2 variants in a human lung cell line. Infected ACE2 transfected A549 (ACE2-A549) cells were treated with UV-4B and EIDD-1931 both as monotherapy and in combination. Viral supernatant was sampled on day three when viral titers peaked in the no-treatment control arm, and levels of infectious virus were measured by plaque assay. The drug-drug effect interaction between UV-4B and EIDD-1931 was also defined using the Greco Universal Response Surface Approach (URSA) model. Antiviral evaluations demonstrated that treatment with UV-4B plus EIDD-1931 enhanced antiviral activity against all three variants relative to monotherapy. These results were in accordance with those obtained from the Greco model, as these identified the interaction between UV-4B and EIDD-1931 as additive against the beta and omicron variants and synergistic against the delta variant. Our findings highlight the anti-SARS-CoV-2 potential of UV-4B and EIDD-1931 combination regimens, and present combination therapy as a promising therapeutic strategy against SARS-CoV-2.

A Novel Approach to Develop New and Potent Inhibitors for the Simultaneous Inhibition of Protease and Helicase Activities of HCV NS3/4A Protease: A Computational Approach

Infection of hepatitis C (HCV) is a major threat to human health throughout the world. The current therapy program suffers from restricted efficiency and low tolerance, and there is serious demand frr novel medication. NS3/4A protease is observed to be very effective target for the treatment of HCV. A data set of the already reported HCV NS3/4A protease inhibitors was first docked into the NS3/4A protease (PDB ID: 4A92A) active sites of both protease and helicase sites for calculating the docking score, binding affinity, binding mode, and solvation energy. Then the data set of these reported inhibitors was used in a computer-based program "RECAP Analyses" implemented in MOE to fragment every molecule in the subset according to simple retrosynthetic analysis rules. The RECAP analysis fragments were then used in another computer-based program "RECAP Synthesis" to randomly recombine and generate synthetically reasonable novel chemical structures. The novel chemical structures thus produced were then docked against HCV NS3/4A. After a thorough validation of all undertaken steps, based on Lipinski's rule of five, docking score, binding affinity, solvation energy, and Van der Waal's interactions with HCV NS3/4A, 12 novel chemical structures were identified as inhibitors of HCV NS3/4A. The novel structures thus designed are hoped to play a key role in the development of new effective inhibitors of HCV.

Mechanisms and Consequences of Genetic Variation in Hepatitis C Virus (HCV)

Chronic infection with hepatitis C virus (HCV) is an important contributor to the global incidence of liver diseases, including liver cirrhosis and hepatocellular carcinoma. Although common for single-stranded RNA viruses, HCV displays a remarkable high level of genetic diversity, produced primarily by the error-prone viral polymerase and host immune pressure. The high genetic heterogeneity of HCV has led to the evolution of several distinct genotypes and subtypes, with important consequences for pathogenesis, and clinical outcomes. Genetic variability constitutes an evasion mechanism against immune suppression, allowing the virus to evolve epitope escape mutants that avoid immune recognition. Thus, heterogeneity and variability of the HCV genome represent a great hindrance for the development of vaccines against HCV. In addition, the high genetic plasticity of HCV allows the virus to rapidly develop antiviral resistance mutations, leading to treatment failure and potentially representing a major hindrance for the cure of chronic HCV patients. In this chapter, we will present the central role that genetic diversity has in the viral life cycle and epidemiology of HCV. Incorporation errors and recombination, both the result of HCV polymerase activity, represent the main mechanisms of HCV evolution. The molecular details of both mechanisms have been only partially clarified and will be presented in the following sections. Finally, we will discuss the major consequences of HCV genetic diversity, namely its capacity to rapidly evolve antiviral and immunological escape variants that represent an important limitation for clearance of acute HCV, for treatment of chronic hepatitis C and for broadly protective vaccines.

The art of managing hepatitis C virus in special population groups: a paradigm shift

The first direct-acting antiviral (DAA) medications were approved for the treatment of chronic hepatitis C virus (HCV) in 2011. Later, the appearance of novel DAAs had revolutionized the landscape of HCV treatment whose early treatment options were limited to interferon (IFN) either alone or in combinations. This review discusses the paradigm shift in legibility for treating different groups of patients with HCV after the introduction of DAAs, along with the consequent changes in treatment guidelines. IFN-based therapy was the firstly used for treating chronic HCV. Unfortunately, it exhibited many pitfalls, such as low efficacy in some patients and unsuitability for usage in lots of patients with some specific conditions, which could be comorbidities such as autoimmune thyroiditis, or liver related as in decompensated cirrhosis. Furthermore, IFN failed to treat all the extrahepatic manifestations of HCV. Nowadays, the breakthroughs brought by DAAs have benefited the patients and enabled the treatment of those who could not be treated or did not usually respond well to IFN. DAAs achieve a high success rate of HCV eradication in addition to avoiding unfavorable harms and, sometimes, adverse effects related to the previously used PEGylated IFN regimens.

Interdisciplinary in silico studies to understand in-depth molecular level mechanism of drug resistance involving NS3-4A protease of HCV

Hepatitis C virus (HCV) causes hepatitis, a life-threatening disease responsible for liver cirrhosis. Urgent measures have been taken to develop therapeutics against this deadly pathogen. NS3/4A protease is an extremely important target. A series of inhibitors have been developed against this viral protease including Faldaprevir. Unfortunately, the error-prone viral RNA polymerase causes the emergence of resistance, thereby causing reduced effectiveness of those peptidomimetic inhibitors. Among the drug resistant variants, three single amino acid residues (R155, A156 and D168) are notable for their presence in clinical isolates and also their effectivity against most of the known inhibitors in clinical development. Therefore, it is crucial to understand the mechanistic role of those drug resistant variants while designing potent novel inhibitors. In this communication, we have deeply analyzed through using in silico studies to understand the molecular mechanism of alteration of inhibitor binding between wild type and its R155K, A156V and D168V variants. Principal component analysis was carried to identify the backbone fluctuations of important residues in HCV NS3/4A responsible for the inhibitor binding and maintaining drug resistance. Free energy landscape as a function of the principal components has been used to identify the stability and conformation of the key residues that regulate inhibitor binding and their impact in developing drug resistance. Our findings are consistent with the trend of experimental results. The observations are also true in case of other Faldaprevir-like peptidomimetic inhibitors. Understanding this binding mechanism would be significant for the development of novel inhibitors with less susceptibility towards drug resistance.

Design of an optimal combination therapy with broadly neutralizing antibodies to suppress HIV-1

Infusion of broadly neutralizing antibodies (bNAbs) has shown promise as an alternative to anti-retroviral therapy against HIV. A key challenge is to suppress viral escape, which is more effectively achieved with a combination of bNAbs. Here, we propose a computational approach to predict the efficacy of a bNAb therapy based on the population genetics of HIV escape, which we parametrize using high-throughput HIV sequence data from bNAb-naive patients. By quantifying the mutational target size and the fitness cost of HIV-1 escape from bNAbs, we predict the distribution of rebound times in three clinical trials. We show that a cocktail of three bNAbs is necessary to effectively suppress viral escape, and predict the optimal composition of such bNAb cocktail. Our results offer a rational therapy design for HIV, and show how genetic data can be used to predict treatment outcomes and design new approaches to pathogenic control.

Recombinant Full-Length Hepatitis C Virus E1E2 Dimer Elicits Pangenotypic Neutralizing Antibodies

An effective prophylactic vaccine would be beneficial for controlling and eradicating hepatitis C virus (HCV) infections. However, the high diversity across HCV genotypes is a major challenge for vaccine development. Selection of the appropriate immunogen is critical to elicit broad HCV neutralizing antibodies (NAbs). To increase the antigenic coverage of heterodimer glycoproteins, we designed and produced recombinant E1E2 antigens for genotypes 1a/1b/2a/3a/6a from an IgG Fc-tagged precursor protein in FreeStyle 293-F cells. The recombinant E1 and E2 antigens were localized and associated with the endoplasmic reticulum and co-purified from membrane extracts. By examining the interactions with HCV entry co-receptors and the blockade of HCV infection, we found that these purified Fc-E1E2 proteins displayed correct folding and function. Mouse immunization results showed that each recombinant E1E2 antigen could elicit a pangenotypic antibody response to itself and other genotypes. We also found that the pentavalent formula triggered a relatively higher and more uniform NAb titer and T cell response than monovalent antigens. Taken together, our findings may provide a useful strategy for the vaccine development of HCV and other viruses with highly heterogeneous surface glycoproteins.

Advances in Parameter Estimation and Learning from Data for Mathematical Models of Hepatitis C Viral Kinetics

Mathematical models, some of which incorporate both intracellular and extracellular hepatitis C viral kinetics, have been advanced in recent years for studying HCV–host dynamics, antivirals mode of action, and their efficacy. The standard ordinary differential equation (ODE) hepatitis C virus (HCV) kinetic model keeps track of uninfected cells, infected cells, and free virus. In multiscale models, a fourth partial differential equation (PDE) accounts for the intracellular viral RNA (vRNA) kinetics in an infected cell. The PDE multiscale model is substantially more difficult to solve compared to the standard ODE model, with governing differential equations that are stiff. In previous contributions, we developed and implemented stable and efficient numerical methods for the multiscale model for both the solution of the model equations and parameter estimation. In this contribution, we perform sensitivity analysis on model parameters to gain insight into important properties and to ensure our numerical methods can be safely used for HCV viral dynamic simulations. Furthermore, we generate in-silico patients using the multiscale models to perform machine learning from the data, which enables us to remove HCV measurements on certain days and still be able to estimate meaningful observations with a sufficiently small error.

Molnupiravir combined with different repurposed drugs further inhibits SARS-CoV-2 infection in human nasal epithelium in vitro

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide pandemic with unprecedented economic and societal impact. Currently, several vaccines are available and multitudes of antiviral treatments have been proposed and tested. Although many of the vaccines show clinical efficacy, they are not equally accessible worldwide. Additionally, due to the continuous emergence of new variants and generally short duration of immunity, the development of effective antiviral treatments remains of the utmost importance. Since the emergence of SARS-CoV-2, substantial efforts have been undertaken to repurpose existing drugs for accelerated clinical testing and emergency use authorizations. However, drug-repurposing studies using cellular assays often identify hits that later prove ineffective clinically, highlighting the need for more complex screening models. To this end, we evaluated the activity of single compounds that have either been tested clinically or already undergone extensive preclinical profiling, using a standardized in vitro model of human nasal epithelium. Furthermore, we also evaluated drug combinations based on a sub-maximal concentration of molnupiravir. We report the antiviral activity of 95 single compounds and 30 combinations. We show that only a few single agents are highly effective in inhibiting SARS-CoV-2 replication while selected drug combinations containing 10 µM molnupiravir boosted antiviral activity compared to single compound treatment. These data indicate that molnupiravir-based combinations are worthy of further consideration as potential treatment strategies against coronavirus disease 2019 (COVID-19).

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Not many single compounds exhibit antiviral activity against SARS-CoV-2.

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The RdRp inhibitor, molnupiravir, inhibits SARS-CoV-2 at various concentrations.

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Combinations containing 10 µM molnupiravir boost antiviral activity.

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Combination treatment might provide additional therapeutic benefit against COVID-19.

Mutational spectrum of hepatitis C virus in patients with chronic hepatitis C determined by single molecule real-time sequencing

The emergence of hepatitis C virus (HCV) with resistance-associated substitution (RAS), produced by mutations in the HCV genome, is a major problem in direct acting antivirals (DAA) treatment. This study aimed to clarify the mutational spectrum in HCV-RNA and the substitution pattern for the emergence of RASs in patients with chronic HCV infection. HCV-RNA from two HCV replicon cell lines and the serum HCV-RNA of four non-liver transplant and four post-liver transplant patients with unsuccessful DAA treatment were analyzed using high-accuracy single-molecule real-time long-read sequencing. Transition substitutions, especially A>G and U>C, occurred prominently under DAAs in both non-transplant and post-transplant patients, with a mutational bias identical to that occurring in HCV replicon cell lines during 10-year culturing. These mutational biases were reproduced in natural courses after DAA treatment. RASs emerged via both transition and transversion substitutions. NS3-D168 and NS5A-L31 RASs resulted from transversion mutations, while NS5A-Y93 RASs was caused by transition substitutions. The fidelity of the RNA-dependent RNA polymerase, HCV-NS5B, produces mutational bias in the HCV genome, characterized by dominant transition mutations, notably A>G and U>C substitutions. However, RASs are acquired by both transition and transversion substitutions, and the RASs-positive HCV clones are selected and proliferated under DAA treatment pressure.

Safety, pharmacokinetics and antiviral activity of PGT121, a broadly neutralizing monoclonal antibody against HIV-1: a randomized, placebo-controlled, phase 1 clinical trial

Human immunodeficiency virus (HIV)-1-specific broadly neutralizing monoclonal antibodies are currently under development to treat and prevent HIV-1 infection. We performed a single-center, randomized, double-blind, dose-escalation, placebo-controlled trial of a single administration of the HIV-1 V3-glycan-specific antibody PGT121 at 3, 10 and 30 mg kg-1 in HIV-uninfected adults and HIV-infected adults on antiretroviral therapy (ART), as well as a multicenter, open-label trial of one infusion of PGT121 at 30 mg kg-1 in viremic HIV-infected adults not on ART (no. NCT02960581). The primary endpoints were safety and tolerability, pharmacokinetics (PK) and antiviral activity in viremic HIV-infected adults not on ART. The secondary endpoints were changes in anti-PGT121 antibody titers and CD4+ T-cell count, and development of HIV-1 sequence variations associated with PGT121 resistance. Among 48 participants enrolled, no treatment-related serious adverse events, potential immune-mediated diseases or Grade 3 or higher adverse events were reported. The most common reactions among PGT121 recipients were intravenous/injection site tenderness, pain and headache. Absolute and relative CD4+ T-cell counts did not change following PGT121 infusion in HIV-infected participants. Neutralizing anti-drug antibodies were not elicited. PGT121 reduced plasma HIV RNA levels by a median of 1.77 log in viremic participants, with a viral load nadir at a median of 8.5 days. Two individuals with low baseline viral loads experienced ART-free viral suppression for ≥168 days following antibody infusion, and rebound viruses in these individuals demonstrated full or partial PGT121 sensitivity. The trial met the prespecified endpoints. These data suggest that further investigation of the potential of antibody-based therapeutic strategies for long-term suppression of HIV is warranted, including in individuals off ART and with low viral load.

Epistatic interactions promote persistence of NS3-Q80K in HCV infection by compensating for protein folding instability

The Q80K polymorphism in the NS3-4A protease of the hepatitis C virus is associated with treatment failure of direct-acting antiviral agents. This polymorphism is highly prevalent in genotype 1a infections and stably transmitted between hosts. Here, we investigated the underlying molecular mechanisms of evolutionarily conserved coevolving amino acids in NS3-Q80K and revealed potential implications of epistatic interactions in immune escape and variants persistence. Using purified protein, we characterized the impact of epistatic amino acid substitutions on the physicochemical properties and peptide cleavage kinetics of the NS3-Q80K protease. We found that Q80K destabilized the protease protein fold (p < 0.0001). Although NS3-Q80K showed reduced peptide substrate turnover (p < 0.0002), replicative fitness in an H77S.3 cell culture model of infection was not significantly inferior to the WT virus. Epistatic substitutions at residues 91 and 174 in NS3-Q80K stabilized the protein fold (p < 0.0001) and leveraged the WT protease stability. However, changes in protease stability inversely correlated with enzymatic activity. In infectious cell culture, these secondary substitutions were not associated with a gain of replicative fitness in NS3-Q80K variants. Using molecular dynamics, we observed that the total number of residue contacts in NS3-Q80K mutants correlated with protein folding stability. Changes in the number of contacts reflected the compensatory effect on protein folding instability by epistatic substitutions. In summary, epistatic substitutions in NS3-Q80K contribute to viral fitness by mechanisms not directly related to RNA replication. By compensating for protein-folding instability, epistatic interactions likely protect NS3-Q80K variants from immune cell recognition.

Mechanistic Modeling of SARS-CoV-2 and Other Infectious Diseases and the Effects of Therapeutics

Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical, and modeling communities during the early days of the AIDS epidemic. Its successes led to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus and cytomegalovirus, which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus, West Nile virus, Zika virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. We then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize nonpharmaceutical and pharmaceutical interventions of the coronavirus disease 2019 (COVID-19) pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein, "Everything should be made as simple as possible, but not simpler," and this idea underlies the modeling we describe below.

Design and Synthesis of HCV-E2 Glycoprotein Epitope Mimics in Molecular Construction of Potential Synthetic Vaccines

Hepatitis C virus remains a global threat, despite the availability of highly effective direct-acting antiviral (DAA) drugs. With thousands of new infections annually, the need for a prophylactic vaccine is evident. However, traditional vaccine design has been unable to provide effective vaccines so far. Therefore, alternative strategies need to be investigated. In this work, a chemistry-based approach is explored towards fully synthetic peptide-based vaccines using epitope mimicry, by focusing on highly effective and conserved amino acid sequences in HCV, which, upon antibody binding, inhibit its bio-activity. Continuous and discontinuous epitope mimics were both chemically synthesized based on the HCV-E2 glycoprotein while using designed fully synthetic cyclic peptides. These cyclic epitope mimics were assembled on an orthogonally protected scaffold. The scaffolded epitope mimics have been assessed in immunization experiments to investigate the elicitation of anti-HCV-E2 glycoprotein antibodies. The neutralizing potential of the elicited antibodies was investigated, representing a first step in employing chemically synthesized epitope mimics as a novel strategy towards vaccine design.

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.

Quantitative differences between intra-host HCV populations from persons with recently established and persistent infections

Detection of incident hepatitis C virus (HCV) infections is crucial for identification of outbreaks and development of public health interventions. However, there is no single diagnostic assay for distinguishing recent and persistent HCV infections. HCV exists in each infected host as a heterogeneous population of genomic variants, whose evolutionary dynamics remain incompletely understood. Genetic analysis of such viral populations can be applied to the detection of incident HCV infections and used to understand intra-host viral evolution. We studied intra-host HCV populations sampled using next-generation sequencing from 98 recently and 256 persistently infected individuals. Genetic structure of the populations was evaluated using 245,878 viral sequences from these individuals and a set of selected features measuring their diversity, topological structure, complexity, strength of selection, epistasis, evolutionary dynamics, and physico-chemical properties. Distributions of the viral population features differ significantly between recent and persistent infections. A general increase in viral genetic diversity from recent to persistent infections is frequently accompanied by decline in genomic complexity and increase in structuredness of the HCV population, likely reflecting a high level of intra-host adaptation at later stages of infection. Using these findings, we developed a machine learning classifier for the infection staging, which yielded a detection accuracy of 95.22 per cent, thus providing a higher accuracy than other genomic-based models. The detection of a strong association between several HCV genetic factors and stages of infection suggests that intra-host HCV population develops in a complex but regular and predictable manner in the course of infection. The proposed models may serve as a foundation of cyber-molecular assays for staging infection, which could potentially complement and/or substitute standard laboratory assays.

Extended interaction networks with HCV protease NS3-4A substrates explain the lack of adaptive capability against protease inhibitors

Inhibitors against the NS3-4A protease of hepatitis C virus (HCV) have proven to be useful drugs in the treatment of HCV infection. Although variants have been identified with mutations that confer resistance to these inhibitors, the mutations do not restore replicative fitness and no secondary mutations that rescue fitness have been found. To gain insight into the molecular mechanisms underlying the lack of fitness compensation, we screened known resistance mutations in infectious HCV cell culture with different genomic backgrounds. We observed that the Q41R mutation of NS3-4A efficiently rescues the replicative fitness in cell culture for virus variants containing mutations at NS3-Asp168 To understand how the Q41R mutation rescues activity, we performed protease activity assays complemented by molecular dynamics simulations, which showed that protease-peptide interactions far outside the targeted peptide cleavage sites mediate substrate recognition by NS3-4A and support protease cleavage kinetics. These interactions shed new light on the mechanisms by which NS3-4A cleaves its substrates, viral polyproteins and a prime cellular antiviral adaptor protein, the mitochondrial antiviral signaling protein MAVS. Peptide binding is mediated by an extended hydrogen-bond network in NS3-4A that was effectively optimized for protease-MAVS binding in Asp168 variants with rescued replicative fitness from NS3-Q41R. In the protease harboring NS3-Q41R, the N-terminal cleavage products of MAVS retained high affinity to the active site, rendering the protease susceptible for potential product inhibition. Our findings reveal delicately balanced protease-peptide interactions in viral replication and immune escape that likely restrict the protease adaptive capability and narrow the virus evolutionary space.

Virological patterns of hepatitis C virus patients with failure to the current-generation direct-acting antivirals

There are few data on the virological characterisation of patients with failure to current-generation direct-acting antivirals (DAAs), namely elbasvir/grazoprevir, sofosbuvir/velpatasvir and glecaprevir/pibrentasvir. This study aimed to characterise virological patterns in patients with failure to current DAA regimens as well as the efficacy of re-treatment. All 61 consecutive hepatitis C virus (HCV) treatment-naïve patients with failure to current DAAs from January 2018 to February 2019 were enrolled. Sanger sequencing of NS3, NS5A and NS5B proteins was performed using homemade protocols. NS5A resistance-associated substitutions (RASs) were more frequent in the 17 patients treated with sofosbuvir/velpatasvir (89.5%) and 33 patients treated with elbasvir/grazoprevir (97%) compared with the 11 patients treated with glecaprevir/pibrentasvir (18.2%) (P = 0.002 and 0.000, respectively). NS3 RASs were more often detected in the 33 patients with failure to elbasvir/grazoprevir (30.3%) than in the 11 patients treated with glecaprevir/pibrentasvir (9.1%). NS3 RASs were also detected in 12% of sofosbuvir/velpatasvir-treated patients. NS5B RASs were infrequently identified. Of the glecaprevir/pibrentasvir-treated patients, 73% did not show RASs in any HCV regions, a prevalence higher than that observed in those treated with elbasvir/grazoprevir (0%; P < 0.05) or sofosbuvir/velpatasvir (12%; P < 0.05). Of the 61 patients, 21 (34.4%) were re-treated with sofosbuvir/velpatasvir and voxilaprevir. All patients achieved sustained virological response at 12 weeks (SVR12). To our knowledge, this is one of the first real-life studies describing patients who failed current-generation DAAs; the prevalence of RASs differed according to the DAA regimen used, and the efficacy of re-treatment was high.

Effect of drug dose and timing of treatment on the emergence of drug resistance in vivo in a malaria model

BACKGROUND AND OBJECTIVES

There is a significant interest in identifying clinically effective drug treatment regimens that minimize the de novo evolution of antimicrobial resistance in pathogen populations. However, in vivo studies that vary treatment regimens and directly measure drug resistance evolution are rare. Here, we experimentally investigate the role of drug dose and treatment timing on resistance evolution in an animal model.

METHODOLOGY

In a series of experiments, we measured the emergence of atovaquone-resistant mutants of Plasmodium chabaudi in laboratory mice, as a function of dose or timing of treatment (day post-infection) with the antimalarial drug atovaquone.

RESULTS

The likelihood of high-level resistance emergence increased with atovaquone dose. When varying the timing of treatment, treating either very early or late in infection reduced the risk of resistance. When we varied starting inoculum, resistance was more likely at intermediate inoculum sizes, which correlated with the largest population sizes at time of treatment.

CONCLUSIONS AND IMPLICATIONS

(i) Higher doses do not always minimize resistance emergence and can promote the emergence of high-level resistance. (ii) Altering treatment timing affects the risk of resistance emergence, likely due to the size of the population at the time of treatment, although we did not test the effect of immunity whose influence may have been important in the case of late treatment. (iii) Finding the 'right' dose and 'right' time to maximize clinical gains and limit resistance emergence can vary depending on biological context and was non-trivial even in our simplified experiments.

LAY SUMMARY

In a mouse model of malaria, higher drug doses led to increases in drug resistance. The timing of drug treatment also impacted resistance emergence, likely due to the size of the population at the time of treatment.

Hepatitis C Virus Vaccine: Challenges and Prospects

The hepatitis C virus (HCV) causes both acute and chronic infection and continues to be a global problem despite advances in antiviral therapeutics. Current treatments fail to prevent reinfection and remain expensive, limiting their use to developed countries, and the asymptomatic nature of acute infection can result in individuals not receiving treatment and unknowingly spreading HCV. A prophylactic vaccine is therefore needed to control this virus. Thirty years since the discovery of HCV, there have been major gains in understanding the molecular biology and elucidating the immunological mechanisms that underpin spontaneous viral clearance, aiding rational vaccine design. This review discusses the challenges facing HCV vaccine design and the most recent and promising candidates being investigated.

A Parameter Estimation Method for Multiscale Models of Hepatitis C Virus Dynamics

Mathematical models that are based on differential equations require detailed knowledge about the parameters that are included in the equations. Some of the parameters can be measured experimentally while others need to be estimated. When the models become more sophisticated, such as in the case of multiscale models of hepatitis C virus dynamics that deal with partial differential equations (PDEs), several strategies can be tried. It is possible to use parameter estimation on an analytical approximation of the solution to the multiscale model equations, namely the long-term approximation, but this limits the scope of the parameter estimation method used and a long-term approximation needs to be derived for each model. It is possible to transform the PDE multiscale model to a system of ODEs, but this has an effect on the model parameters themselves and the transformation can become problematic for some models. Finally, it is possible to use numerical solutions for the multiscale model and then use canned methods for the parameter estimation, but the latter is making the user dependent on a black box without having full control over the method. The strategy developed here is to start by working directly on the multiscale model equations for preparing them toward the parameter estimation method that is fully coded and controlled by the user. It can also be adapted to multiscale models of other viruses. The new method is described, and illustrations are provided using a user-friendly simulator that incorporates the method.

Interferon at the cellular, individual, and population level in hepatitis C virus infection: Its role in the interferon-free treatment era

The advent of powerful direct-acting antiviral agents (DAAs) has revolutionized the treatment of hepatitis C. DAAs cure nearly all patients with short duration, oral treatments. Significant efforts are now underway to optimize DAA-based treatments. We discuss the potential role of interferon in this optimization. Clinical studies present compelling evidence that DAAs perform better in treatment-naive individuals than in individuals who previously failed treatment with interferon, a surprising correlation because interferon and DAAs are thought to act independently. Recent mathematical models explore a mechanistic hypothesis underlying this correlation. The hypothesis invokes the action of interferon at the cellular, individual, and population levels. Strong interferon responses prevent the productive infection of cells, reduce viral replication, and impede the development of resistance to DAAs in infected individuals and improve cure rates elicited by DAAs in treated populations. The models develop descriptions of these processes, integrate them into a comprehensive framework, and capture clinical data quantitatively, providing a successful test of the hypothesis. Individuals with strong endogenous interferon responses thus present a promising subpopulation for reducing DAA treatment durations. This review discusses the conceptual advances made by the models, highlights the new insights they unravel, and examines their applicability to optimize DAA-based treatments.

Early HCV viral kinetics under DAAs may optimize duration of therapy in patients with compensated cirrhosis

BACKGROUND & AIMS

Detailed hepatitis C virus (HCV) kinetics modelling is scarce in patients with advanced liver disease receiving direct-acting antivirals (DAAs). Due to budget restrictions, patients and health systems would benefit from the shortest possible treatment course. We investigated whether modelling very early HCV kinetics in cirrhotic patients under DAAs therapy could be used to individualize care and reduce treatment duration to achieve cure.

METHODS

We included 74 patients with HCV-related cirrhosis who received interferon-free treatments for 12-24 weeks. HCV genotype, liver disease stage and treatment regimen were recorded. Viral load was determined prospectively at very frequent intervals until target not detected (TND, <15 IU/mL). A viral kinetic model was used to predict time to cure based on HCV clearance in extracellular body fluid (CL-EF).

RESULTS

Sixty-eight patients (92%) achieved cure. Thirteen (18%) had MELD ≥15, 35 (47%) were Child-Pugh (CTP) ≥7. Median time to reach TND was 2 weeks (IQR: 1-4 weeks). Modelling indicated an average DAAs efficacy in blocking viral production of ε = 99.1%. HCV half-life (t1/2 ) was significantly shorter in patients with CTP <7, LSM <21 kPa or MELD <15 (1.5 vs 2.5 hours; P = 0.0057). The overall median CL-EF was 5.6 weeks (4.1-7.8). A CTP >7 and a LSM ≥21 kPa were significantly (P = 0.016) associated with longer CL-EF.

CONCLUSIONS

The study provides insights into HCV dynamics during DAAs therapy in patients with compensated and decompensated cirrhosis. Viral kinetics modelling suggests that treatment duration may be optimized in patients with compensated cirrhosis.

Mutational pathway maps and founder effects define the within-host spectrum of hepatitis C virus mutants resistant to drugs

Knowledge of the within-host frequencies of resistance-associated amino acid variants (RAVs) is important to the identification of optimal drug combinations for the treatment of hepatitis C virus (HCV) infection. Multiple RAVs may exist in infected individuals, often below detection limits, at any resistance locus, defining the diversity of accessible resistance pathways. We developed a multiscale mathematical model to estimate the pre-treatment frequencies of the entire spectrum of mutants at chosen loci. Using a codon-level description of amino acids, we performed stochastic simulations of intracellular dynamics with every possible nucleotide variant as the infecting strain and estimated the relative infectivity of each variant and the resulting distribution of variants produced. We employed these quantities in a deterministic multi-strain model of extracellular dynamics and estimated mutant frequencies. Our predictions captured database frequencies of the RAV R155K, resistant to NS3/4A protease inhibitors, presenting a successful test of our formalism. We found that mutational pathway maps, interconnecting all viable mutants, and strong founder effects determined the mutant spectrum. The spectra were vastly different for HCV genotypes 1a and 1b, underlying their differential responses to drugs. Using a fitness landscape determined recently, we estimated that 13 amino acid variants, encoded by 44 codons, exist at the residue 93 of the NS5A protein, illustrating the massive diversity of accessible resistance pathways at specific loci. Accounting for this diversity, which our model enables, would help optimize drug combinations. Our model may be applied to describe the within-host evolution of other flaviviruses and inform vaccine design strategies.

Advanced Hepatitis C Virus Replication PDE Models within a Realistic Intracellular Geometric Environment

The hepatitis C virus (HCV) RNA replication cycle is a dynamic intracellular process occurring in three-dimensional space (3D), which is difficult both to capture experimentally and to visualize conceptually. HCV-generated replication factories are housed within virus-induced intracellular structures termed membranous webs (MW), which are derived from the Endoplasmatic Reticulum (ER). Recently, we published 3D spatiotemporal resolved diffusion⁻reaction models of the HCV RNA replication cycle by means of surface partial differential equation (sPDE) descriptions. We distinguished between the basic components of the HCV RNA replication cycle, namely HCV RNA, non-structural viral proteins (NSPs), and a host factor. In particular, we evaluated the sPDE models upon realistic reconstructed intracellular compartments (ER/MW). In this paper, we propose a significant extension of the model based upon two additional parameters: different aggregate states of HCV RNA and NSPs, and population dynamics inspired diffusion and reaction coefficients instead of multilinear ones. The combination of both aspects enables realistic modeling of viral replication at all scales. Specifically, we describe a replication complex state consisting of HCV RNA together with a defined amount of NSPs. As a result of the combination of spatial resolution and different aggregate states, the new model mimics a cis requirement for HCV RNA replication. We used heuristic parameters for our simulations, which were run only on a subsection of the ER. Nevertheless, this was sufficient to allow the fitting of core aspects of virus reproduction, at least qualitatively. Our findings should help stimulate new model approaches and experimental directions for virology.

The review of differential equation models of HBV infection dynamics

Understanding the infection and pathogenesis mechanism of hepatitis B virus (HBV) is very important for the prevention and treatment of hepatitis B. Mathematical models contribute to illuminate the dynamic process of HBV replication in vivo. Therefore, in this paper we review the viral dynamics in HBV infection, which may help us further understand the dynamic mechanism of HBV infection and efficacy of antiviral treatment. Firstly, we introduce a family of deterministic models by considering different biological mechanisms, such as, antiviral therapy, CTL immune response, multi-types of infected hepatocytes, time delay and spatial diffusion. Particularly, we briefly describe the stochastic models of HBV infection. Secondly, we introduce the commonly used parameter estimation methods for HBV viral dynamic models and briefly discuss how to use these methods to estimate unknown parameters (such as drug efficacy) through two specific examples. We also discuss the idea and method of model identification and use a specific example to illustrate its application. Finally, we propose three new research programs, namely, considering HBV drug-resistant strain, coupling within-host and between-host dynamics in HBV infection and linking population dynamics with evolutionary dynamics of HBV diversity.

The Discovery and Early Clinical Evaluation of the HCV NS3/4A Protease Inhibitor Asunaprevir (BMS-650032)

The discovery of asunaprevir (1) began with the concept of engaging the small and well-defined S₁’ pocket of the hepatitis C virus (HCV) NS3/4A protease that was explored in the context of tripeptide carboxylic acid-based inhibitors. A cyclopropyl-acyl sulfonamide moiety was found to be the optimal element at the P₁-P₁’ interface enhancing the potency of carboxylic acid-based prototypes by 10- to >100-fold, dependent upon the specific background. Optimization for oral bioavailability identified a 1-substituted isoquinoline-based P₂* element that conferred a significant exposure advantage in rats compared to the matched 4-substituted quinoline isomer. BMS-605339 (30) was the first cyclopropyl-acyl sulfonamide derivative advanced into clinical trials that demonstrated dose-related reductions in plasma viral RNA in HCV-infected patients. However, 30 was associated with cardiac events observed in a normal healthy volunteer (NHV) and an HCV-infected patient that led to the suspension of the development program. Using a Langendorff rabbit heart model, a limited structure-cardiac liability relationship was quickly established that led to the discovery of 1. This compound, which differs from 30 only by changes in the substitution pattern of the P₂* isoquinoline heterocycle and the addition of a single chlorine atom to the molecular formula, gave a dose-dependent reduction in plasma viral RNA following oral administration to HCV-infected patients without the burden of the cardiac events that had been observed with 30. A small clinical trial of the combination of 1 with the HCV NS5A inhibitor daclatasvir (2) established for the first time that a chronic genotype 1 (GT-1) HCV infection could be cured by therapy with two direct-acting antiviral agents in the absence of exogenous immune-stimulating agents. Development of the combination of 1 and 2 was initially focused on Japan where the patient population is predominantly infected with GT-1b virus, culminating in marketing approval which was granted on July 4, 2014. In order to broaden therapy to include GT-1a infections, a fixed dose triple combination of 1, 2, and the allosteric NS5B inhibitor beclabuvir (3) was developed, approved by the Japanese health authorities for the treatment of HCV GT-1 infection on December 20, 2016 and marketed as Ximency^®.

Low-Fidelity Assembly of Influenza A Virus Promotes Escape from Host Cells

Influenza viruses inhabit a wide range of host environments using a limited repertoire of protein components. Unlike viruses with stereotyped shapes, influenza produces virions with significant morphological variability even within clonal populations. Whether this tendency to form pleiomorphic virions is coupled to compositional heterogeneity and whether it affects replicative fitness remains unclear. Here, we address these questions by developing a strain of influenza A virus amenable to rapid compositional characterization through quantitative, site-specific labeling of viral proteins. Using this strain, we find that influenza A produces virions with broad variations in size and composition from even single infected cells. This phenotypic variability contributes to virus survival during environmental challenges, including exposure to antivirals. Complementing genetic adaptations that act over larger populations and longer times, this "low-fidelity" assembly of influenza A virus allows small populations to survive environments that fluctuate over individual replication cycles.

Next-generation sequencing analysis of new genotypes appearing during antiviral treatment of chronic hepatitis C reveals that these are selected from pre-existing minor strains

Coinfection with more than one hepatitis C virus (HCV) genotype is common, but its dynamics, particularly during antiviral treatment, remain largely unknown. We employed next-generation sequencing (NGS) to analyse sequential serum and peripheral blood mononuclear cell (PBMC) samples in seven patients with transient presence or permanent genotype change during antiviral treatment with interferon and ribavirin. Specimens were collected right before the therapy initiation and at 2, 4, 6, 8, 12, 20, 24, 36, 44 and 48 weeks during treatment and 6 months after treatment ceased. A mixture of two different genotypes was detected in the pretreatment samples from five patients and the minor genotype constituted 0.02 to 38 %. A transient or permanent change of the predominant genotype was observed in six patients. In three cases genotype 3 was replaced as the predominant genotype by genotype 4, in two cases genotype 3 was replaced by genotype 1, and in one subject genotype 1 was replaced by genotype 4. The PBMC- and serum-derived sequences were frequently discordant with respect to genotype and/or genotype proportions. In conclusion, pre-existing minor HCV genotypes can be selected rapidly during antiviral treatment and become transiently or permanently predominant. In coinfections involving genotype 3, genotype 3 was eliminated first from both the serum and PBMC compartments. The PBMC- and serum-derived HCV sequences were frequently discordant with respect to genotype and/or genotype proportions, suggesting that they constitute separate compartments with their own dynamics.

Molecular Mechanism of Resistance in a Clinically Significant Double-Mutant Variant of HCV NS3/4A Protease

Despite significant progress in hepatitis C virus (HCV) protease inhibitor (PI) drug design, resistance remains a problem causing treatment failure. Double-substitution variants, notably Y56H/D168A, have emerged in patients who fail therapy with a PI-containing regimen. The resistance conferred by Asp168 substitutions has been well characterized and avoided in newer inhibitors. However, an additional mutation at Tyr56 confers resistance to even the most robust inhibitors. Here, we elucidate the molecular mechanisms of resistance for the Y56H/D168A variant against grazoprevir (and four analogs), paritaprevir, and danoprevir through inhibition assays, co-crystal structures, and molecular dynamics simulations. The PIs' susceptibility to Y56H/D168A varies, with those stacking on the catalytic His57 losing the most potency. For such inhibitors, the Y56H substitution disrupts favorable stacking interactions with the neighboring catalytic His57. This indirect mechanism of resistance threatens to cause multi-PI failure as all HCV PIs in clinical development rely on interactions with the catalytic triad.

Comparison of antiviral resistance across acute and chronic viral infections

Antiviral therapy can lead to drug resistance, but multiple factors determine the frequency of drug resistance mutations and the clinical consequences. When chronic infections caused by Human Immunodeficiency Virus (HIV), Hepatitis C Virus (HCV) and Hepatitis B Virus (HBV) are compared with acute infections such as influenza virus, respiratory syncytial virus (RSV), and other respiratory viruses, there are similarities in how and why antiviral resistance substitutions occur, but the clinical significance can be quite different. Emergence of resistant variants has implications for design of new therapeutics, treatment guidelines, clinical trial design, resistance monitoring, reporting, and interpretation. In this discussion paper, we consider the molecular factors contributing to antiviral drug resistance substitutions, and a comparison is made between chronic and acute infections. The implications of resistance are considered for clinical trial endpoints and public health, as well as the requirements for therapeutic monitoring in clinical practice with acute viral infections.

Superinfection and cure of infected cells as mechanisms for hepatitis C virus adaptation and persistence

RNA viruses exist as a genetically diverse quasispecies with extraordinary ability to adapt to abrupt changes in the host environment. However, the molecular mechanisms that contribute to their rapid adaptation and persistence in vivo are not well studied. Here, we probe hepatitis C virus (HCV) persistence by analyzing clinical samples taken from subjects who were treated with a second-generation HCV protease inhibitor. Frequent longitudinal viral load determinations and large-scale single-genome sequence analyses revealed rapid antiviral resistance development, and surprisingly, dynamic turnover of dominant drug-resistant mutant populations long after treatment cessation. We fitted mathematical models to both the viral load and the viral sequencing data, and the results provided strong support for the critical roles that superinfection and cure of infected cells play in facilitating the rapid turnover and persistence of viral populations. More broadly, our results highlight the importance of considering viral dynamics and competition at the intracellular level in understanding rapid viral adaptation. Thus, we propose a theoretical framework integrating viral and molecular mechanisms to explain rapid viral evolution, resistance, and persistence despite antiviral treatment and host immune responses.

Modelling how responsiveness to interferon improves interferon-free treatment of hepatitis C virus infection

Direct-acting antiviral agents (DAAs) for hepatitis C treatment tend to fare better in individuals who are also likely to respond well to interferon-alpha (IFN), a surprising correlation given that DAAs target specific viral proteins whereas IFN triggers a generic antiviral immune response. Here, we posit a causal relationship between IFN-responsiveness and DAA treatment outcome. IFN-responsiveness restricts viral replication, which would prevent the growth of viral variants resistant to DAAs and improve treatment outcome. To test this hypothesis, we developed a multiscale mathematical model integrating IFN-responsiveness at the cellular level, viral kinetics and evolution leading to drug resistance at the individual level, and treatment outcome at the population level. Model predictions quantitatively captured data from over 50 clinical trials demonstrating poorer response to DAAs in previous non-responders to IFN than treatment-naïve individuals, presenting strong evidence supporting the hypothesis. Model predictions additionally described several unexplained clinical observations, viz., the percentages of infected individuals who 1) spontaneously clear HCV, 2) get chronically infected but respond to IFN-based therapy, and 3) fail IFN-based therapy but respond to DAA-based therapy, resulting in a comprehensive understanding of HCV infection and treatment. An implication of the causal relationship is that failure of DAA-based treatments may be averted by adding IFN, a strategy of potential use in settings with limited access to DAAs. A second, wider implication is that individuals with greater IFN-responsiveness would require shorter DAA-based treatment durations, presenting a basis and a promising population for response-guided therapy.

Modeling how reversal of immune exhaustion elicits cure of chronic hepatitis C after the end of treatment with direct-acting antiviral agents

A fraction of chronic hepatitis C patients treated with direct‐acting antivirals (DAAs) achieved sustained virological responses (SVR), or cure, despite having detectable viremia at the end of treatment (EOT). This observation, termed EOT⁺/SVR, remains puzzling and precludes rational optimization of treatment durations. One hypothesis to explain EOT⁺/SVR, the immunologic hypothesis, argues that the viral decline induced by DAAs during treatment reverses the exhaustion of cytotoxic T lymphocytes (CTLs), which then clear the infection after treatment. Whether the hypothesis is consistent with data of viral load changes in patients who experienced EOT⁺/SVR is unknown. Here, we constructed a mathematical model of viral kinetics incorporating the immunologic hypothesis and compared its predictions with patient data. We found the predictions to be in quantitative agreement with patient data. Using the model, we unraveled an underlying bistability that gives rise to EOT⁺/SVR and presents a new avenue to optimize treatment durations. Infected cells trigger both activation and exhaustion of CTLs. CTLs in turn kill infected cells. Due to these competing interactions, two stable steady states, chronic infection and viral clearance, emerge, separated by an unstable steady state with intermediate viremia. When treatment during chronic infection drives viremia sufficiently below the unstable state, spontaneous viral clearance results post‐treatment, marking EOT⁺/SVR. The duration to achieve this desired reduction in viremia defines the minimum treatment duration required for ensuring SVR, which our model can quantify. Estimating parameters defining the CTL response of individuals to HCV infection would enable the application of our model to personalize treatment durations.

Numerical schemes for solving and optimizing multiscale models with age of hepatitis C virus dynamics

Age-structured PDE models have been developed to study viral infection and treatment. However, they are notoriously difficult to solve. Here, we investigate the numerical solutions of an age-based multiscale model of hepatitis C virus (HCV) dynamics during antiviral therapy and compare them with an analytical approximation, namely its long-term approximation. First, starting from a simple yet flexible numerical solution that also considers an integral approximated over previous iterations, we show that the long-term approximation is an underestimate of the PDE model solution as expected since some infection events are being ignored. We then argue for the importance of having a numerical solution that takes into account previous iterations for the associated integral, making problematic the use of canned solvers. Second, we demonstrate that the governing differential equations are stiff and the stability of the numerical scheme should be considered. Third, we show that considerable gain in efficiency can be achieved by using adaptive stepsize methods over fixed stepsize methods for simulating realistic scenarios when solving multiscale models numerically. Finally, we compare between several numerical schemes for the solution of the equations and demonstrate the use of a numerical optimization scheme for the parameter estimation performed directly from the equations.

Innate and Adaptive Immune Responses in Chronic HCV Infection

Hepatitis C virus (HCV) remains a public health problem of global importance, even in the era of potent directly-acting antiviral drugs. In this chapter, I discuss immune responses to acute and chronic HCV infection. The outcome of HCV infection is influenced by viral strategies that limit or delay the initiation of innate antiviral responses. This delay may enable HCV to establish widespread infection long before the host mounts effective T and B cell responses. HCV's genetic agility, resulting from its high rate of replication and its error prone replication mechanism, enables it to evade immune recognition. Adaptive immune responses fail to keep up with changing viral epitopes. Neutralizing antibody epitopes may be hidden by decoy structures, glycans, and lipoproteins. T cell responses fail due to changing epitope sequences and due to exhaustion, a phenomenon that may have evolved to limit immune-mediated pathology. Despite these difficulties, innate and adaptive immune mechanisms do impact HCV replication. Immune-mediated clearance of infection is possible, occurring in 20-50% of people who contract the disease. New developments raise hopes for effective immunological interventions to prevent or treat HCV infection.

Indeterminate genotypes of hepatitis C virus by the Abbott RealTime HCV Genotype II assay in Morocco. About eight cases resolved by a sequencing method

The early detection and genotyping of the hepatitis C virus (HCV) are important in the management of this infection. The genotype is the major factor influencing treatment decisions. That's why it is necessary to use fast and accurate methods in its determination. This study reports, over a period of 3 years (from May 2012 to July 2015), the percentage of indeterminate genotypes by the Abbott RealTime HCV Genotype II test and their results using a sequencing technique. Of 309 samples of 309 patients tested, 11 were indeterminate (4.4%). There were three cases of cross-reactivity (1b/4 in one case, 2/5 in two cases) and a possible co-infection 1 + 4. Among those indeterminate genotypes, cross-reactivities and co-infections, ten samples were tested by sequencing. The results were for four of them a 1d subtype, five were a 2i subtype and one was a 2l subtype. These results support the thesis of complementarity between the two methods: genotyping for the detection of mixed reactions and sequencing for resolving indeterminate cases by genotyping.

Ultra-Deep Genomic Sequencing of HCV NS5A Resistance-Associated Substitutions in HCV/HIV Coinfected Patients

BACKGROUND AND AIMS

The prevalence of naturally occurring HCV-NS5A resistance-associated substitutions (RAS) to DAA drugs might affect the response to treatment in HCV/HIV coinfected subjects. There are limited data on the frequency of HCV-NS5A naturally occurring drug-RAS at baseline in HCV/HIV coinfected patients when ultra-deep sequencing methodologies are applied.

METHODS

HCV-NS5A-RAS were evaluated among 25 subjects in each group. Patients were matched by age, gender, and hepatic fibrosis stage category to control for selection bias.

RESULTS

Within subtype 1a, RAS were observed in 28% of HCV monoinfected and 48% of HCV/HIV coinfected subjects. More patients in the HCV/HIV coinfected group had clinically relevant mutations to DAA directed at NS5A.

CONCLUSION

While the clinical significance of this observation may be limited in highly drug adherent populations, some HCV/HIV coinfected persons may be at greater risk of viral resistance if suboptimal dosing occurs.

Integrated pharmacokinetic/viral dynamic model for daclatasvir/asunaprevir in treatment of patients with genotype 1 chronic hepatitis C

In order to develop an integrated pharmacokinetic/viral dynamic (PK/VD) model to predict long-term virological response rates to daclatasvir (DCV) and asunaprevir (ASV) combination therapy in patients infected with genotype 1 (GT1) chronic hepatitis C virus (HCV), a systematic publication search was conducted for DCV and ASV administered alone and/or in combination in healthy subjects or patients with GT1 HCV infection. On the basis of a constructed meta-database, an integrated PK/VD model was developed, which adequately described both DCV and ASV PK profiles and viral load time curves. The IC₅₀ values of DCV and ASV were estimated to be 0.041 and 2.45 μg/L, respectively, in GT1A patients. A sigmoid E_max function was applied to describe the antiviral effects of DCV and ASV, depending on the drug concentrations in the effect compartment. An empirical exponential function revealed that IC₅₀ changing over time described drug resistance in HCV GT1A patients during DCV or ASV monotherapy. Finally, the PK/VD model was evaluated externally by comparing the expected and observed virological response rates during and post-treatment with DCV and ASV combination therapy in HCV GT1B patients. Both the rates were in general agreement. Our PK/VD model provides a useful platform for the characterization of pharmacokinetic/pharmacodynamic relationships and the prediction of long-term virological response rates to aid future development of direct acting antiviral drugs.

Modulation of Lipid Droplet Metabolism-A Potential Target for Therapeutic Intervention in Flaviviridae Infections

Lipid droplets (LDs) are endoplasmic reticulum (ER)-related dynamic organelles that store and regulate fatty acids and neutral lipids. They play a central role in cellular energy storage, lipid metabolism and cellular homeostasis. It has become evident that viruses have co-evolved in order to exploit host lipid metabolic pathways. This is especially characteristic of the Flaviviridae family, including hepatitis C virus (HCV) and several flaviviruses. Devoid of an appropriate lipid biosynthetic machinery of their own, these single-strand positive-sense RNA viruses can induce dramatic changes in host metabolic pathways to establish a favorable environment for viral multiplication and acquire essential components to facilitate their assembly and traffic. Here we have reviewed the current knowledge on the intracellular life cycle of those from the Flaviviridae family, with particular emphasis on HCV and dengue virus (DENV), and their association with the biosynthesis and metabolism of LDs, with the aim to identify potential antiviral targets for development of novel therapeutic interventions.

Modelling the effects of phylogeny and body size on within-host pathogen replication and immune response

Understanding how quickly pathogens replicate and how quickly the immune system responds is important for predicting the epidemic spread of emerging pathogens. Host body size, through its correlation with metabolic rates, is theoretically predicted to impact pathogen replication rates and immune system response rates. Here, we use mathematical models of viral time courses from multiple species of birds infected by a generalist pathogen (West Nile Virus; WNV) to test more thoroughly how disease progression and immune response depend on mass and host phylogeny. We use hierarchical Bayesian models coupled with nonlinear dynamical models of disease dynamics to incorporate the hierarchical nature of host phylogeny. Our analysis suggests an important role for both host phylogeny and species mass in determining factors important for viral spread such as the basic reproductive number, WNV production rate, peak viraemia in blood and competency of a host to infect mosquitoes. Our model is based on a principled analysis and gives a quantitative prediction for key epidemiological determinants and how they vary with species mass and phylogeny. This leads to new hypotheses about the mechanisms that cause certain taxonomic groups to have higher viraemia. For example, our models suggest that higher viral burst sizes cause corvids to have higher levels of viraemia and that the cellular rate of virus production is lower in larger species. We derive a metric of competency of a host to infect disease vectors and thereby sustain the disease between hosts. This suggests that smaller passerine species are highly competent at spreading the disease compared with larger non-passerine species. Our models lend mechanistic insight into why some species (smaller passerine species) are pathogen reservoirs and some (larger non-passerine species) are potentially dead-end hosts for WNV. Our techniques give insights into the role of body mass and host phylogeny in the spread of WNV and potentially other zoonotic diseases. The major contribution of this work is a computational framework for infectious disease modelling at the within-host level that leverages data from multiple species. This is likely to be of interest to modellers of infectious diseases that jump species barriers and infect multiple species. Our method can be used to computationally determine the competency of a host to infect mosquitoes that will sustain WNV and other zoonotic diseases. We find that smaller passerine species are more competent in spreading the disease than larger non-passerine species. This suggests the role of host phylogeny as an important determinant of within-host pathogen replication. Ultimately, we view our work as an important step in linking within-host viral dynamics models to between-host models that determine spread of infectious disease between different hosts.

A Robust and Efficient Numerical Method for RNA-Mediated Viral Dynamics

The multiscale model of hepatitis C virus (HCV) dynamics, which includes intracellular viral RNA (vRNA) replication, has been formulated in recent years in order to provide a new conceptual framework for understanding the mechanism of action of a variety of agents for the treatment of HCV. We present a robust and efficient numerical method that belongs to the family of adaptive stepsize methods and is implicit, a Rosenbrock type method that is highly suited to solve this problem. We provide a Graphical User Interface that applies this method and is useful for simulating viral dynamics during treatment with anti-HCV agents that act against HCV on the molecular level.

3D Spatially Resolved Models of the Intracellular Dynamics of the Hepatitis C Genome Replication Cycle

Mathematical models of virus dynamics have not previously acknowledged spatial resolution at the intracellular level despite substantial arguments that favor the consideration of intracellular spatial dependence. The replication of the hepatitis C virus (HCV) viral RNA (vRNA) occurs within special replication complexes formed from membranes derived from endoplasmatic reticulum (ER). These regions, termed membranous webs, are generated primarily through specific interactions between nonstructural virus-encoded proteins (NSPs) and host cellular factors. The NSPs are responsible for the replication of the vRNA and their movement is restricted to the ER surface. Therefore, in this study we developed fully spatio-temporal resolved models of the vRNA replication cycle of HCV. Our simulations are performed upon realistic reconstructed cell structures-namely the ER surface and the membranous webs-based on data derived from immunostained cells replicating HCV vRNA. We visualized 3D simulations that reproduced dynamics resulting from interplay of the different components of our models (vRNA, NSPs, and a host factor), and we present an evaluation of the concentrations for the components within different regions of the cell. Thus far, our model is restricted to an internal portion of a hepatocyte and is qualitative more than quantitative. For a quantitative adaption to complete cells, various additional parameters will have to be determined through further in vitro cell biology experiments, which can be stimulated by the results deccribed in the present study.