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

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

The COVID-19 pandemic has led to over 760 million cases and 6.9 million deaths worldwide. To mitigate the loss of lives, 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 susceptible variants. 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 anti-viral 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.

The Intrapopulation Genetic Diversity of RNA Virus May Influence the Sensitivity of Chlorine Disinfection

RNA virus populations are not clonal; rather, they comprise a mutant swarm in which sequences are slightly different from the master sequence. Genetic diversity within a population (intrapopulation genetic diversity) is critical for RNA viruses to survive under environmental stresses. Disinfection has become an important practice in the control of pathogenic viruses; however, the impact of intrapopulation genetic diversity on the sensitivity of disinfection, defined as -log10 (postdisinfected infectious titer/predisinfected titer), has not been elucidated. In this study, we serially passaged populations of rhesus rotavirus. We demonstrated that populations with reduced chlorine sensitivity emerged at random and independently of chlorine exposure. Sequencing analysis revealed that compared with sensitive populations, less-sensitive ones had higher non-synonymous genetic diversity of the outer capsid protein gene, suggesting that changes in the amino acid sequences of the outer capsid protein were the main factors influencing chlorine sensitivity. No common mutations were found among less-sensitive populations, indicating that rather than specific mutations, the diversity of the outer capsid protein itself was associated with the disinfection sensitivity and that the disinfection sensitivity changed stochastically. Simulation results suggest that the disinfection sensitivity of a genetically diverse population is destabilized if cooperative viral clusters including multiple sequences are formed. These results advocate that any prevention measures leading to low intrapopulation genetic diversity are important to prevent the spread and evolution of pathogenic RNA viruses in society.

Phylodynamic analysis in the understanding of the current COVID-19 pandemic and its utility in vaccine and antiviral design and assessment

Over the last decades, the use of phylogenetic methods in the study of emerging infectious diseases has gained considerable traction in public health. Particularly, the integration of phylogenetic analyses with the understanding of the pathogen dynamics at the population level has provided powerful tools for epidemiological surveillance systems. In the same way, the development of statistical methods and theory, as well as improvement of computational efficiency for evolutionary analysis, has expanded the use of these tools for vaccine and antiviral development. Today with the Coronavirus Disease 2019 (COVID-19), this seems to be critical. In this article, we discuss how the application of phylodynamic analysis can improve the understanding of current pandemic dynamics as well as the design, selection, and evaluation of vaccine candidates and antivirals.

HIV influences clustering and intracellular replication of hepatitis C virus

HCV and HIV coinfection is common and HIV leads to increased HCV viraemia and accelerated disease progression. However, the biological basis of this interaction remains poorly understood and little is known about the impact of HIV on HCV replication at the cellular level. We analysed HCV RNA, based on single-cell laser-capture microdissection, in liver biopsies from monoinfected (n = 4) and HCV/HIV-coinfected (n = 5) participants. HCV RNA was assayed in 3200 hepatocytes with information of spatial position. We compared HCV RNA levels and clustering properties of infection between mono- and coinfected participants, and developed a mathematical model of infection. Although the median plasma HCV RNA level and the fraction of infected cells were comparable in monoinfected (7.0 log₁₀ IU/mL and ~ 30%) and coinfected (7.3 log₁₀ IU/mL and ~ 40%) participants, the median HCV RNA per infected hepatocyte in monoinfected (2.8IU) was significantly lower than in coinfected (8.2IU) participants (p = .03). Clustering of infected cells was more prominent in monoinfected participants (91% of samples) than in coinfected participants (~48%), p = .0045, suggesting that spatial spread may be influenced by HIV coinfection. Interestingly, when clustering does occur, the size of clusters is similar in both types of infection. A mathematical model of infection suggested that HIV allows higher intracellular accumulation of HCV RNA by impeding the export of HCV RNA. Our observations show that HIV coinfection impacts intracellular accumulation of HCV RNA and the clustering of HCV-infected cells, but to a less extent the fraction of HCV-infected cells.

Cross-scale dynamics and the evolutionary emergence of infectious diseases

When emerging pathogens encounter new host species for which they are poorly adapted, they must evolve to escape extinction. Pathogens experience selection on traits at multiple scales, including replication rates within host individuals and transmissibility between hosts. We analyze a stochastic model linking pathogen growth and competition within individuals to transmission between individuals. Our analysis reveals a new factor, the cross-scale reproductive number of a mutant virion, that quantifies how quickly mutant strains increase in frequency when they initially appear in the infected host population. This cross-scale reproductive number combines with viral mutation rates, single-strain reproductive numbers, and transmission bottleneck width to determine the likelihood of evolutionary emergence, and whether evolution occurs swiftly or gradually within chains of transmission. We find that wider transmission bottlenecks facilitate emergence of pathogens with short-term infections, but hinder emergence of pathogens exhibiting cross-scale selective conflict and long-term infections. Our results provide a framework to advance the integration of laboratory, clinical, and field data in the context of evolutionary theory, laying the foundation for a new generation of evidence-based risk assessment of emergence threats.

Mathematical modeling of hepatitis C RNA replication, exosome secretion and virus release

Hepatitis C virus (HCV) causes acute hepatitis C and can lead to life-threatening complications if it becomes chronic. The HCV genome is a single plus strand of RNA. Its intracellular replication is a spatiotemporally coordinated process of RNA translation upon cell infection, RNA synthesis within a replication compartment, and virus particle production. While HCV is mainly transmitted via mature infectious virus particles, it has also been suggested that HCV-infected cells can secrete HCV RNA carrying exosomes that can infect cells in a receptor independent manner. In order to gain insight into these two routes of transmission, we developed a series of intracellular HCV replication models that include HCV RNA secretion and/or virus assembly and release. Fitting our models to in vitro data, in which cells were infected with HCV, suggests that initially most secreted HCV RNA derives from intracellular cytosolic plus-strand RNA, but subsequently secreted HCV RNA derives equally from the cytoplasm and the replication compartments. Furthermore, our model fits to the data suggest that the rate of virus assembly and release is limited by host cell resources. Including the effects of direct acting antivirals in our models, we found that in spite of decreasing intracellular HCV RNA and extracellular virus concentration, low level HCV RNA secretion may continue as long as intracellular RNA is available. This may possibly explain the presence of detectable levels of plasma HCV RNA at the end of treatment even in patients that ultimately attain a sustained virologic response.

Approximately 70 million people are chronically infected with hepatitis C virus (HCV), which if left untreated may lead to cirrhosis and liver cancer. However, modern drug therapy is highly effective and hepatitis C is the first chronic virus infection that can be cured with short-term therapy in almost all infected individuals. The within-host transmission of HCV occurs mainly via infectious virus particles, but experimental studies suggest that there may be additional receptor-independent cell-to-cell transmission by exosomes that carry the HCV genome. In order to understand the intracellular HCV lifecycle and HCV RNA spread, we developed a series of mathematical models that take both exosomal secretion and viral secretion into account. By fitting these models to in vitro data, we found that secretion of both HCV RNA as well as virus probably occurs and that the rate of virus assembly is likely limited by cellular co-factors on which the virus strongly depends for its own replication. Furthermore, our modeling predicted that the parameters governing the processes in the viral lifecycle that are targeted by direct acting antivirals are the most sensitive to perturbations, which may help explain their ability to cure this infection.

Fitness-associated substitutions following failure of direct-acting antivirals assessed by deep sequencing of full-length hepatitis C virus genomes

BACKGROUND

In hepatitis C virus (HCV) infection, treatment failure is generally associated with the selection of resistance-associated substitutions (RAS) conferring reduced susceptibility to direct-acting antiviral (DAA) drugs. Resistant variants continue to replicate after the end of treatment with potential for transmission. This may result from the selection of "fitness-associated substitutions".

AIM

To characterise potential "fitness-associated substitutions" in patients infected with genotype 3a failing DAA drugs METHODS: By means of shotgun metagenomics, we sequenced full-length HCV genomes at treatment initiation and at virological relapse in eight patients infected with genotype 3a with cirrhosis failing sofosbuvir and an NS5A inhibitor. The impact of amino acid changes occurring outside of DAA target regions selected in at least two patients were assessed on the in vitro susceptibility to an NS5A inhibitor and replication capacity.

RESULTS

At treatment failure, besides selection of known NS5A RASs, especially Y93H, a large number of amino acid changes was observed outside of DAA target regions. We identified four amino acid positions at which observed changes substantially improved in vitro replication capacity without affecting NS5A inhibitor susceptibility.

CONCLUSIONS

This is the first in vivo observation combined with in vitro confirmation of selection of phenotypically characterised "fitness-associated substitutions" together with RASs at the time of sofosbuvir-NS5A inhibitor treatment failure in patients infected with genotype 3a with cirrhosis. Our findings may explain the persistence of resistant HCV variants after treatment in patients who did not achieve sustained virological remission.

Molecular and Structural Mechanism of Pan-Genotypic HCV NS3/4A Protease Inhibition by Glecaprevir

Hepatitis C virus, causative agent of chronic viral hepatitis, infects 71 million people worldwide and is divided into seven genotypes and multiple subtypes with sequence identities between 68 to 82%. While older generation direct-acting antivirals had varying effectiveness against different genotypes, the newest NS3/4A protease inhibitors including glecaprevir (GLE) have pan-genotypic activity. The structural basis for pan-genotypic inhibition and effects of polymorphisms on inhibitor potency were not well-known due to lack of crystal structures of GLE-bound NS3/4A or genotypes other than 1. In this study, we determined the crystal structures of NS3/4A from genotypes 1a, 3a, 4a, and 5a in complex with GLE. Comparison with the highly similar grazoprevir indicated the mechanism of GLE's drastic improvement in potency. We found that, while GLE is highly potent against wild-type NS3/4A of all genotypes, specific resistance-associated substitutions (RASs) confer orders of magnitude loss in inhibition. Our crystal structures reveal molecular mechanisms behind pan-genotypic activity of GLE, including potency loss due to RASs at D168. Our structures permit for the first time analysis of changes due to polymorphisms among genotypes, providing insights into design principles that can aid future drug development and potentially can be extended to other proteins.

Evolutionary Pathways to Persistence of Highly Fit and Resistant Hepatitis C Virus Protease Inhibitor Escape Variants

Protease inhibitors (PIs) are important components of treatment regimens for patients with chronic hepatitis C virus (HCV) infection. However, emergence and persistence of antiviral resistance could reduce their efficacy. Thus, defining resistance determinants is highly relevant for efforts to control HCV. Here, we investigated patterns of PI resistance-associated substitutions (RASs) for the major HCV genotypes and viral determinants for persistence of key RASs. We identified protease position 156 as a RAS hotspot for genotype 1-4, but not 5 and 6, escape variants by resistance profiling using PIs grazoprevir and paritaprevir in infectious cell culture systems. However, except for genotype 3, engineered 156-RASs were not maintained. For genotypes 1 and 2, persistence of 156-RASs depended on genome-wide substitution networks, co-selected under continued PI treatment and identified by next-generation sequencing with substitution linkage and haplotype reconstruction. Persistence of A156T for genotype 1 relied on compensatory substitutions increasing replication and assembly. For genotype 2, initial selection of A156V facilitated transition to 156L, persisting without compensatory substitutions. The developed genotype 1, 2, and 3 variants with persistent 156-RASs had exceptionally high fitness and resistance to grazoprevir, paritaprevir, glecaprevir, and voxilaprevir. A156T dominated in genotype 1 glecaprevir and voxilaprevir escape variants, and pre-existing A156T facilitated genotype 1 escape from clinically relevant combination treatments with grazoprevir/elbasvir and glecaprevir/pibrentasvir. In genotype 1 infected patients with treatment failure and 156-RASs, we observed genome-wide selection of substitutions under treatment. Conclusion: Comprehensive PI resistance profiling for HCV genotypes 1-6 revealed 156-RASs as key determinants of high-level resistance across clinically relevant PIs. We obtained in vitro proof of concept for persistence of highly fit genotype 1-3 156-variants, which might pose a threat to clinically relevant combination treatments.

Within-host infectious disease models accommodating cellular coinfection, with an application to influenza

Within-host models are useful tools for understanding the processes regulating viral load dynamics. While existing models have considered a wide range of within-host processes, at their core these models have shown remarkable structural similarity. Specifically, the structure of these models generally consider target cells to be either uninfected or infected, with the possibility of accommodating further resolution (e.g. cells that are in an eclipse phase). Recent findings, however, indicate that cellular coinfection is the norm rather than the exception for many viral infectious diseases, and that cells with high multiplicity of infection are present over at least some duration of an infection. The reality of these cellular coinfection dynamics is not accommodated in current within-host models although it may be critical for understanding within-host dynamics. This is particularly the case if multiplicity of infection impacts infected cell phenotypes such as their death rate and their viral production rates. Here, we present a new class of within-host disease models that allow for cellular coinfection in a scalable manner by retaining the low-dimensionality that is a desirable feature of many current within-host models. The models we propose adopt the general structure of epidemiological ‘macroparasite’ models that allow hosts to be variably infected by parasites such as nematodes and host phenotypes to flexibly depend on parasite burden. Specifically, our within-host models consider target cells as ‘hosts’ and viral particles as ‘macroparasites’, and allow viral output and infected cell lifespans, among other phenotypes, to depend on a cell’s multiplicity of infection. We show with an application to influenza that these models can be statistically fit to viral load and other within-host data, and demonstrate using model selection approaches that they have the ability to outperform traditional within-host viral dynamic models. Important in vivo quantities such as the mean multiplicity of cellular infection and time-evolving reassortant frequencies can also be quantified in a straightforward manner once these macroparasite models have been parameterized. The within-host model structure we develop here provides a mathematical way forward to address questions related to the roles of cellular coinfection, collective viral interactions, and viral complementation in within-host viral dynamics and evolution.

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.

HCV transmission in high-risk communities in Bulgaria

Background

The rate of HIV infection in Bulgaria is low. However, the rate of HCV-HIV-coinfection and HCV infection is high, especially among high-risk communities. The molecular epidemiology of those infections has not been studied before.

Methods

Consensus Sanger sequences of HVR1 and NS5B from 125 cases of HIV/HCV coinfections, collected during 2010–2014 in 15 different Bulgarian cities, were used for preliminary phylogenetic evaluation. Next-generation sequencing (NGS) data of the hypervariable region 1 (HVR1) analyzed via the Global Hepatitis Outbreak and Surveillance Technology (GHOST) were used to evaluate genetic heterogeneity and possible transmission linkages. Links between pairs that were below and above the established genetic distance threshold, indicative of transmission, were further examined by generating k-step networks.

Results

Preliminary genetic analyses showed predominance of HCV genotype 1a (54%), followed by 1b (20.8%), 2a (1.4%), 3a (22.3%) and 4a (1.4%), indicating ongoing transmission of many HCV strains of different genotypes. NGS of HVR1 from 72 cases showed significant genetic heterogeneity of intra-host HCV populations, with 5 cases being infected with 2 different genotypes or subtypes and 6 cases being infected with 2 strains of same subtype. GHOST revealed 8 transmission clusters involving 30 cases (41.7%), indicating a high rate of transmission.

Four transmission clusters were found in Sofia, three in Plovdiv, and one in Peshtera. The main risk factor for the clusters was injection drug use. Close genetic proximity among HCV strains from the 3 Sofia clusters, and between HCV strains from Peshtera and one of the two Plovdiv clusters confirms a long and extensive transmission history of these strains in Bulgaria.

Conclusions

Identification of several HCV genotypes and many HCV strains suggests a frequent introduction of HCV to the studied high-risk communities. GHOST detected a broad transmission network, which sustains circulation of several HCV strains since their early introduction in the 3 cities. This is the first report on the molecular epidemiology of HIV/HCV coinfections in Bulgaria.