Chemical combinations elucidate pathway interactions and regulation relevant to Hepatitis C replication

Abstract

The search for effective Hepatitis C antiviral therapies has recently focused on host sterol metabolism and protein prenylation pathways that indirectly affect viral replication. However, inhibition of the sterol pathway with statin drugs has not yielded consistent results in patients. Here, we present a combination chemical genetic study to explore how the sterol and protein prenylation pathways work together to affect hepatitis C viral replication in a replicon assay. In addition to finding novel targets affecting viral replication, our data suggest that the viral replication is strongly affected by sterol pathway regulation. There is a marked transition from antagonistic to synergistic antiviral effects as the combination targets shift downstream along the sterol pathway. We also show how pathway regulation frustrates potential hepatitis C therapies based on the sterol pathway, and reveal novel synergies that selectively inhibit hepatitis C replication over host toxicity. In particular, combinations targeting the downstream sterol pathway enzymes produced robust and selective synergistic inhibition of hepatitis C replication. Our findings show how combination chemical genetics can reveal critical pathway connections relevant to viral replication, and can identify potential treatments with an increased therapeutic window.

Figure 1

Chemical probes used to modulate targets relating to the sterol biosynthesis pathway, and also to target a proviral pathway mediated by host protein prenylation. The schematic diagram shows the sterol biosynthesis pathway, showing where it interacts with protein prenylation through geranylgeranyl transferase (PGGT). Each chemical probe is shown with a marker connecting it to an enzymatic target, either as an inhibitor/antagonist or as an agonist.

Figure 2

Single-agent activity for the chemical probes in this study. (A) In each panel we show the response curves for both the viral replicon and host viability assays after 48 h treatment with serial two-fold dilutions of compounds, with reference lines at 0 and 50% inhibition. IC₅₀ values are given for each probe. Data represent means from at least three biological replicates of each drug at each concentration tested. Standard errors, estimated from the median absolute deviation (see Materials and methods), ranged between 3 and 20% at each tested dose, with the largest errors occurring where the response transitioned from inactive to inhibitory. (B) Effect on HCV protein synthesis by treatment of replicon cells for 96 h with the chemical probes used in this study. Protein bands from two western blots were quantified using densitometry. Expressed levels of HCV proteins NS3 and NS5A are shown as ratios normalized to GAPDH (see Materials and methods). Each blot is a representative chosen from three separate experiments.

Figure 3

Overview of the HCV replicon and host responses showing the observed combination activity. Dose-matrix data were obtained by testing all pairs of serially diluted (two-fold) concentrations for each pair of probes (Supplementary Table S1). Activity values A=−log₁₀(T/U) were calculated at each dosing point by comparing the treated T viability level to untreated values V obtained from ∼20 vehicle-treated wells arranged on each experimental plate (see Materials and methods). Dose matrices were obtained with at least four replicates. Uncertainties on the activity, estimated from the scatter between replicates (see Materials and methods), were typically ∼0.1, averaged across each dosing matrix (Supplementary Table S1). For each pair of chemical probes, the level of interaction observed between the agents is shown as a circle scaled to the synergy score S, relative to a ‘superposed effect’ (SPE) model of non-interaction (see Materials and methods). The SPE model interpolates smoothly between single-agent effects that can be either inhibitory or stimulatory. Positive S (solid or red circles) correspond to synergistic interaction when both agents are inhibitory, and to the dominance at high combined concentrations of the inhibitory agent when one of the agents has stimulatory activity (e.g. squalestatin). Negative S corresponded to antagonism between inhibitors or dominance of the stimulatory agent. A synergy score of 1 means that there was a volume of 1 between the observed response and the SPE model surface, integrated over the dose matrix. The scale of these scores depends on the number and density of concentration points tested, and thus is mainly useful for comparisons between combinations, rather than providing an absolute reference level for synergy. Given that the individual activity measurements tended to have standard errors of σ_a∼0.1, only synergy scores outside of ±3 can be considered significant, when integrated over the 64 combination dosing points. (A) In the replicon assay, combinations targeting sterol pathway enzymes downstream of OSC mostly appear to synergize more toward antiviral activity, and those upstream of OSC mostly appear to show ‘epistasis,’ where the effect of modulating an upstream target dominates over those of downstream targets at high combined concentrations. (B) Most combinations in the host toxicity assay produce responses that are close to the SPE expectation, indicating the model represents typical levels of interaction between compounds reasonably well. Where it does occur, strong synergistic viability inhibition (S>3) is associated with compounds (e.g. clomiphene, terconazole and triparanol) that also show strong synergies outside of the sterol pathway (with TOFA and clomiphene, or GGTI-286), and host activity within the pathway obvious mechanism-dependent patterns.

Figure 4

Multi-target interactions in the replicon assay. Each panel presents a schematic of the sterol pathway showing the connection to replicon replication mediated by protein prenylation, along with response matrices for combinations representing different kinds of mechanistic interactions. Dose matrices, colored to show the activity at each dose point, are shown with green markers indicating the targets of each combination, and with shape symbols to indicate the type of interaction seen (either synergy or epistasis with an arrow indicating the direction of dominance from single agent to combination activity). (A) Combinations targeting the top of the sterol pathway produced epistatic responses, where the upstream agent's response predominates at high concentrations, irrespective of the pro- or antiviral activity of the single agents. (B) Targeting the lower end of the pathway led to inhibitory synergy in both the replicon and host viability assays, especially when both agents were downstream of OSC. (C) Inhibitors of the prenylation pathway interacted weakly (close to the SPE expectation) with probes targeting enzymes at the upper end of the sterol pathway, but had significant interactions further downstream. The strongest synergies were produced in combination with agents targeting enzymes downstream of OSC.

Figure 5

Validation experiments. (A) Evidence of epistasis at the level of HCV protein expression, after 96 h in Huh-luc/neo-ET replicon cells, between upstream-targeting simvastatin and downstream-targeting U18666A. Protein bands were quantified using densitometry and levels of expressed HCV proteins NS3 and NS5A are shown as ratios normalized to GAPDH. (B) Sterol pathway regulation revealed by HMGCR protein expression in HuH-7 cells 16 h after exposure to chemical inhibitors, showing feedback effects for probes targeting the upper end of the pathway. Antibodies specific for HMGCR and GAPDH were used to probe western blots of proteins separated by 10% Bis–Tris SDS/PAGE (see Materials and methods). (C) Confirmation that agents targeting the upper and lower pathway have respectively pro- and antiviral effects at 72 h in quantitative RT–PCR experiments on Huh-luc/neo-ET cells. Averaged expression levels from triplicate experiments were calculated after normalizing replicon copy number to total cellular RNA (see Materials and methods), and error bars show 95% confidence (two standard deviations).