Modeling suggests that virion production cycles within individual cells is key to understanding acute hepatitis B virus infection kinetics

A multiscale model of the action of a capsid assembly modulator for the treatment of chronic hepatitis B

Chronic hepatitis B virus (HBV) infection is strongly associated with increased risk of liver cancer and cirrhosis. While existing treatments effectively inhibit the HBV life cycle, viral rebound frequently occurs following treatment interruption. Consequently, functional cure rates of chronic HBV infection remain low and there is increased interest in a novel treatment modality, capsid assembly modulators (CAMs). Here, we develop a multiscale mathematical model of CAM treatment in chronic HBV infection. By fitting the model to participant data from a phase I trial of the first-generation CAM vebicorvir, we estimate the drug's dose-dependent effectiveness and identify the physiological mechanisms that drive the observed biphasic decline in HBV DNA and RNA, and mechanistic differences between HBeAg-positive and negative infection. Finally, we demonstrate analytically and numerically that the relative change of HBV RNA more accurately reflects the antiviral effectiveness of a CAM than the relative change in HBV DNA.

Modeling of hepatitis B virus kinetics and accumulation of cccDNA in primary human hepatocytes

Background & Aims

Knowledge about early HBV covalently closed circular DNA (cccDNA) accumulation post infection is lacking. We characterized and mathematically modeled HBV infection kinetics during early infection and treatment in primary human hepatocytes (PHHs).

Methods

PHHs were inoculated with HBV, and infection was monitored with and without treatment with the nucleoside analog entecavir (ETV), the HBV-entry inhibitor Myr-preS1, or both ETV + Myr-preS1. Extracellular HBV DNA (exHBV), total intracellular HBV DNA (inHBV), and cccDNA were frequently measured during the 12 days post inoculation. A multicompartmental mathematical model was developed to explain HBV infection dynamics.

Results

Multiphasic exHBV and inHBV kinetics were overall similar in untreated and Myr-preS1-treated PHHs. In ETV-treated PHHs (either alone or with Myr-preS1), exHBV and inHBV initially declined and did not resurge. ETV-treated cultures had significantly (p=0.002) lower mean cccDNA levels at Day 2 post inoculation (4.3 ± 0.1 vs. 4.7 ± 0.1) and reached plateau slower (5 vs. 2 days) than untreated and Myr-preS1-treated cultures, respectively. Modeling predicts that the recycling of inHBV into cccDNA stops when cccDNA reaches a maximum and HBV secretion changes depending on the concentration of inHBV. Even when initiated at the time of inoculation, ETV did not prevent or eradicate infection but rather blocked inHBV accumulation gradually, reaching 97% efficacy by the end of the 12-day experiment and resulting in an average 44% slower cccDNA accumulation.

Conclusions

The study provides insight into the interrelationships and dynamics of cccDNA accumulation, inHBV accumulation, and secretion of exHBV containing particles. Although kinetics and modeling support the conclusion that the level of cccDNA in the cell is regulated, the mechanisms that determine HBV capsid secretion vs. recycling to the nucleus for cccDNA accumulation require further investigation.

Impact and implications

Using primary human hepatocytes (PHHs), we characterize early HBV kinetics post infection. HBV-infected PHH were treated with an entry inhibitor to characterize the accumulation of intracellular and extracellular HBV DNA and the nuclear episomal viral genome called covalently closed circular DNA (cccDNA) in the absence of HBV spread. Kinetic and mathematical modeling in PHHs confirms that the replication inhibitor, entecavir, strongly blocks intracellular HBV DNA accumulation, which also slowed the accumulation of cccDNA. However, modeling indicates that effects on cccDNA accumulation are not directly determined by intracellular HBV DNA levels, supporting the conclusion that cccDNA levels within the cell are regulated in some yet-to-be-elucidated manner.

Modeling of hepatitis B virus infection spread in primary human hepatocytes

Chronic hepatitis B virus (HBV) infection poses a significant global health threat, causing severe liver diseases including cirrhosis and hepatocellular carcinoma. We characterized HBV DNA kinetics in primary human hepatocytes (PHH) over 32 days post-inoculation (pi) and used agent-based modeling (ABM) to gain insights into HBV lifecycle and spread. Parallel PHH cultures were mock-treated or HBV entry inhibitor Myr-preS1 (6.25 μg/mL) was initiated 24h pi. In untreated PHH, 3 viral DNA kinetic patterns were identified: (1) an initial decline, followed by (2) rapid amplification, and (3) slower amplification/accumulation. In the presence of Myr-preS1, viral DNA and infected cell numbers in phase 3 were effectively blocked, with minimal to no increase. This suggests that phase 2 represents viral amplification in initially infected cells, while phase 3 corresponds to viral spread to naïve cells. The ABM reproduced well the HBV kinetic patterns observed and predicted that the viral eclipse phase lasts between 18 and 38 hours. After the eclipse phase, the viral production rate increases over time, starting with a slow production cycle of 1 virion per day, which gradually accelerates to 1 virion per hour after 3 days. Approximately 4 days later, virion production reaches a steady state production rate of 4 virions/hour. The estimated median efficacy of Myr-preS1 in blocking HBV spread was 91% (range: 90-92%). The HBV kinetics and the predicted estimates of the HBV eclipse phase duration and HBV production cycles in PHH are similar of those predicted in uPA/SCID mice with human livers.

Theoretical modeling of hepatitis C acute infection in liver-humanized mice support pre-clinical assessment of candidate viruses for controlled-human-infection studies

Designing and carrying out a controlled human infection (CHI) model for hepatitis C virus (HCV) is critical for vaccine development. However, key considerations for a CHI model protocol include understanding of the earliest viral-host kinetic events during the acute phase and susceptibility of the viral isolate under consideration for use in the CHI model to antiviral treatment before any infections in human volunteers can take place. Humanized mouse models lack adaptive immune responses but provide a unique opportunity to obtain quantitative understanding of early HCV kinetics and develop mathematical models to further understand viral and innate immune response dynamics during acute HCV infection. We show that the models reproduce the measured HCV kinetics in humanized mice, which are consistent with early acute HCV-host dynamics in immunocompetent chimpanzees. Our findings suggest that humanized mice are well-suited to support development of a CHI model. In-silico and in-vivo modeling estimates provide a starting point to characterize candidate viruses for testing in CHI model studies.

A multiscale model of the action of a capsid assembly modulator for the treatment of chronic hepatitis B

Chronic hepatitis B virus (HBV) infection is strongly associated with increased risk of liver cancer and cirrhosis. While existing treatments effectively inhibit the HBV life cycle, viral rebound occurs rapidly following treatment interruption. Consequently, functional cure rates of chronic HBV infection remain low and there is increased interest in a novel treatment modality, capsid assembly modulators (CAMs). Here, we develop a multiscale mathematical model of CAM treatment in chronic HBV infection. By fitting the model to participant data from a phase I trial of the first-generation CAM vebicorvir, we estimate the drug's dose-dependent effectiveness and identify the physiological mechanisms that drive the observed biphasic decline in HBV DNA and RNA, and mechanistic differences between HBeAg-positive and negative infection. Finally, we demonstrate analytically and numerically that HBV RNA is more sensitive than HBV DNA to increases in CAM effectiveness.

Mathematical Models of Early Hepatitis B Virus Dynamics in Humanized Mice

Analyzing the impact of the adaptive immune response during acute hepatitis B virus (HBV) infection is essential for understanding disease progression and control. Here we developed mathematical models of HBV infection which either lack terms for adaptive immune responses, or assume adaptive immune responses in the form of cytolytic immune killing, non-cytolytic immune cure, or non-cytolytic-mediated block of viral production. We validated the model that does not include immune responses against temporal serum hepatitis B DNA (sHBV) and temporal serum hepatitis B surface-antigen (HBsAg) experimental data from mice engrafted with human hepatocytes (HEP). Moreover, we validated the immune models against sHBV and HBsAg experimental data from mice engrafted with HEP and human immune system (HEP/HIS). As expected, the model that does not include adaptive immune responses matches the observed high sHBV and HBsAg concentrations in all HEP mice. By contrast, while all immune response models predict reduction in sHBV and HBsAg concentrations in HEP/HIS mice, the Akaike Information Criterion cannot discriminate between non-cytolytic cure (resulting in a class of cells refractory to reinfection) and antiviral block functions (of up to 99 % viral production 1-3 weeks following peak viral load). We can, however, reject cytolytic killing, as it can only match the sHBV and HBsAg data when we predict unrealistic levels of hepatocyte loss.

How robust are estimates of key parameters in standard viral dynamic models?

Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely.