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Research Article
24 September 2018

Development and Validation of a Phenotypic High-Content Imaging Assay for Assessing the Antiviral Activity of Small-Molecule Inhibitors Targeting Zika Virus

ABSTRACT

Zika virus (ZIKV) has been linked to the development of microcephaly in newborns, as well as Guillain-Barré syndrome. There are currently no drugs available to treat ZIKV infection, and accordingly, there is an unmet medical need for the discovery of new therapies. High-throughput drug screening efforts focusing on indirect readouts of cell viability are prone to a higher frequency of false positives in cases where the virus is viable in the cell but the cytopathic effect (CPE) is reduced or delayed. Here, we describe a fast and label-free phenotypic high-content imaging assay to detect cells affected by the virus-induced CPE using automated imaging and analysis. Protection from the CPE correlates with a decrease in viral antigen production, as observed by immunofluorescence. We trained our assay using a collection of nucleoside analogues with activity against ZIKV; the previously reported antiviral activities of 2′-C-methylribonucleosides and ribavirin against the Zika virus in Vero cells were confirmed using our developed method. To validate the ability of our assay to reveal new anti-ZIKV compounds, we profiled a novel library of 24 natural product derivatives and found compound 1 to be an inhibitor of the ZIKV-induced cytopathic effect; the activity of the compound was confirmed in human fetal neural stem cells (NSCs). The described technique can be easily leveraged as a primary screening assay for profiling of the activities of large compound libraries against ZIKV and can be expanded to other ZIKV strains and other cell lines displaying morphological changes upon ZIKV infection.

INTRODUCTION

The reemergence of the Zika virus (ZIKV) in recent years as an infectious agent of global concern has driven extensive scientific investigation into the pathology and treatment of infection (1, 2). This pathogen from the viral family Flaviviridae is transmitted by Aedes mosquitoes and is associated with microcephaly in newborns and neural inflammatory diseases, such as Guillain-Barré syndrome, and ophthalmological complications in adults (3, 4). No approved therapy is currently available to treat ZIKV infection, stressing the importance of developing new vaccines and antivirals.
Viral polymerases remain attractive targets in the development of antivirals due to their proven clinical usefulness and their essential activity in viral life cycles (57). Nucleoside analogues abrogate nucleic acid synthesis and, consequently, viral genome replication when incorporated by the viral polymerase and represent an important component of treatment for numerous viral infections. Drug repurposing studies have recently identified numerous candidate inhibitors of ZIKV replication (8, 9), including the nucleoside analogue prodrug nucleotide (ProTide) sofosbuvir, a direct-acting antiviral against hepatitis C virus (HCV) (1012). Other nucleoside analogues that have been investigated for anti-ZIKV activity (targeting the viral polymerase or nucleoside biosynthesis) include 7-deaza-2′-C-methyladenosine (7-deaza-2′-CMA) (13, 14), the adenosine analogue NITD008 (15), 2′-C-methylribonucleosides (14, 16, 17), 3′-O-methylribonucleosides (14), ribavirin (18), and 5-fluorouracil (19).
Testing of antiviral activity in cell-based phenotypic assays has been conducted in many of these studies. The readouts of antiviral activity used to assess compound efficacy and toxicity include the results of quantitative reverse transcription-PCR of viral RNA (20), plaque reduction assays (14), cell viability assays (19), caspase activation assays (21), luciferase Zika virus assays (22), Zika replicon assays (23), and immunofluorescence-based detection of the virus (9). While these assays are robust, most methods are either too labor-intensive or prohibitively expensive for primary large-scale compound library screening. Furthermore, protection from virus-induced cell morphology changes, or cytopathic effects (CPE) (24), is inferred from indirect measurements. Morphological confirmation of the antiviral effect in cellular systems has become increasingly used in drug development in recent years due to technological innovations in robotics, imaging, and automated image analysis, as these screens are target agnostic and can help discover first-in-class inhibitors (25). In this work, we developed a cell-based phenotypic assay using automated image segmentation and analysis to assess the CPE of a recent ZIKV clinical isolate from Panama, H/PAN/2016/BEI-259634, NR-50210 (GenBank accession number KX198135), in Vero cells. This method also allows for visual inspection of microscopy images after hit identification via automated image analysis for added quality control during the primary screening process. Common commercially available cell viability assays report only numerical readouts as a proxy for cell viability. We then trained our developed method to detect antiviral activity using a library of nucleoside analogues. Subsequently, we validated the ability of the developed method to identify new anti-ZIKV chemical entities by using a novel set of marine natural product derivatives and discovered a new chemical scaffold with anti-Zika virus inhibitory activity.

RESULTS AND DISCUSSION

Assessment of CPE.

Cells were cultured in the presence and absence of ZIKV in 1,536-well plates for 72 h at a multiplicity of infection (MOI) of 10 (10 focus-forming units per cell) to ensure that sufficient numbers of cells were undergoing ZIKV-induced morphology changes during viral infection. Bright-field images of the wells were acquired using an ImageXpress Micro high-content imager with a 10× objective lens (Molecular Devices) (Fig. 1A). The cells were subsequently fixed with 4% formaldehyde and stained with 4′,6-diamidino-2-phenylindole (DAPI). The plates were reimaged to acquire pictures of the cell nuclei (Fig. 1B). The images were then analyzed using a custom module in MetaXpress software (Molecular Devices) to generate segmentation counts of cells undergoing ZIKV-induced morphology changes in the bright-field image, as well as segmentation counts of total cell nuclei (Fig. 1C and D). Percent levels of CPE were determined by dividing the number of cells undergoing ZIKV-induced morphology changes by the total number of cell nuclei and multiplying by 100. The percent CPE was normalized to the CPE for the uninfected controls by subtracting the percent CPE for the uninfected control wells from that for infected wells. Using 128 positive-control and 128 negative-control wells, a Z′ value of 0.50 was obtained; this value is comparable to the Z′ values reported for other phenotypic assays used to screen for ZIKV inhibitors (8, 9, 19) and indicates that the assay is useful as a primary screening tool for large compound libraries. Our method requires only one short staining step (DAPI) and two sets of images to be taken to assess antiviral activity, reducing the amount of sample manipulation and allowing for same-day data acquisition.
FIG 1
FIG 1 Automated segmentation analysis of Vero cells undergoing a ZIKV-induced CPE and total cell nuclei. Cells undergoing ZIKV-induced morphology changes and total cell nuclei were acquired at a ×10 magnification and tabulated using an automated image analysis protocol. (A) Bright-field image of cells infected with ZIKV H/PAN/2016/BEI-259634 at an MOI of 10 at 72 h postinfection. (B) Image of DAPI-stained Vero cells. (C) Segmentation of cells undergoing ZIKV-induced morphology changes using an automated image analysis module. (D) Segmentation of cell nuclei using an automated image analysis module.

Training of antiviral assay using published nucleoside analogues.

We assessed the antiviral activity of a small training library of nucleoside analogues and nucleoside analogue ProTides (26) (Fig. 2). Our selection of nucleoside analogues for testing encompasses three types of structural features known to inhibit viral polymerases by alternative mechanisms. The first category is obligate chain terminators, which lack the 3′ hydroxyl group needed for elongation after incorporation into a nascent RNA strand (14, 16). We selected compounds that lack the 3′ hydroxyl (i.e., replacing it with hydrogen) or that substitute a methoxy or fluoro group in its place (Table 1 and Fig. 2). While compounds with the 3′ modifications have the potential for high potency against enzymatic RNA synthesis when delivered as a nucleoside triphosphate, the 3′ modifications can attenuate nucleoside phosphorylation in cells (27). The second category is nonobligate chain terminators, which typically include 2′ modifications that block chain elongation for conformational or steric reasons (11, 28). In this category, we included the 2′-C-methyl compounds previously shown to be active against ZIKV in cell-based assays plus compounds with additional modifications. Last, we included compounds with nucleobase modifications associated with antiviral activity by lethal mutagenesis (29, 30). While typically potent, these inhibition mechanisms are often associated with greater cytotoxicity. Although cytotoxicity is known for some of the nucleoside analogues that we tested, particularly those used in cancer treatment, such as 5-fluorouridine, we tested these in our assay to confirm if they had any antiviral activity, as described in the literature (19, 31) Since some of the structural modifications in these substrate analogues are known to be associated with reduced nucleo(s/t)ide kinase compatibility, we prepared ProTide prodrugs for a selection of the compounds (26). The ProTide nucleoside monophosphate masking strategy is used in the clinically approved anti-HCV drug sofosbuvir (11).
FIG 2
FIG 2 Structural modifications of polymerase substrate analogue inhibitors tested against Zika virus in the phenotypic high-content imaging assay described in this report.
TABLE 1
TABLE 1 EC50 and CC50 for a selected library of nucleoside analogues using the developed phenotypic assaya
Compound nameEC50 (μM)CC50 (μM)SIb
2′-C-Methylcytidine0.30 (±0.12)>100.00>300
2′-C-Methyladenosine0.60 (±0.25)>100.00>150
2′-C-Methylguanosine2.20 (±0.49)>100.00>40
2′-C-Methyluridine4.21 (±0.96)>100.00>20
Ribavirin20.80 (±4.45)>100.00>4
5-Fluoro-2′-deoxyuridine<0.20<0.20 
5-Fluorouridine1.11 (±0.33)<0.20<0.2
5-Fluorocytidine1.92 (±0.82)<0.20<0.1
Sofosbuvir>100.00>100.00 
2′-O-Methylcytidine>100.00>100.00 
3′-Deoxyadenosine>100.00>100.00 
3′-Deoxycytidine>100.0079.60 (±37.57)<0.8
3′-O-Methylguanosine>100.00>100.00 
3′-O-Methyluridine>100.00>100.00 
9-(β-d-Arabinofuranosyl)guanine>100.00>100.00 
2′-C-Methylcytidine ProTide>100.00>100.00 
2′-C-Methyluridine ProTide>100.00>100.00 
2′-C-Methyladenosine ProTide>100.00>100.00 
3′-Deoxyadenosine ProTide>100.00>100.00 
5′-Fluorocytidine ProTide>100.00>100.00 
3′-O-Methyluridine ProTide>100.00>100.00 
2′-O-Methylcytidine ProTide>100.00>100.00 
3′-Deoxycytidine ProTide>100.00>100.00 
3′-Deoxy-3′-fluoroguanosine ProTide>100.00>100.00 
a
Values are the result of two independent biological replicates (±standard error).
b
SI, selectivity index, which is calculated by dividing the CC50 by the EC50.
Compounds were prespotted onto plates using an acoustic transfer system instrument (EDC Biosciences) in a 10-point, 2-fold dose-response from 100 μM to 0.197 μM. Vero cells and ZIKV were then added to the plates as described above and incubated with the compound for 72 h. Cells and virus were added simultaneously to ensure that hit compounds were not strictly biased toward entry and early life cycle inhibitors. Bright-field and DAPI channel images were acquired as described above; normalized percent activity was plotted versus the concentration of compound and fit to a 50% effective concentration (EC50) function (Collaborative Drug Discovery [CDD] Vault) (Fig. 3). Percent cell viability upon compound treatment was determined by dividing the number of cell nuclei in a compound-treated well by the average number of cell nuclei in control wells treated with vehicle (0.1% dimethyl sulfoxide [DMSO]) and multiplying by 100. The obtained percent cell viability values were then plotted against the compound concentration and fit to a 50% cytotoxic concentration (CC50) function (CDD Vault). The results obtained from our assay demonstrate that the previously studied ribavirin (EC50 = 20.8 μM) and 2′-C-methylribonucleosides are inhibitors of ZIKV replication, with 2′-C-methylcytidine being the most potent (EC50 = 0.297 μM) (Table 1). No cell toxicity was observed for these compounds up to concentrations of 100 μM. None of the other nucleoside analogues tested displayed specific antiviral activity in our assay, and 5-fluorouracil, 5-fluorocytidine, and 5-fluoro-2′-deoxyuridine displayed high levels of cellular toxicity (CC50 < 0.197 μM).
FIG 3
FIG 3 Sample EC50 curve of inhibitor dose-response data acquired from the phenotypic screen. The concentration of inhibitor was plotted against the normalized activity, and an EC50 curve fit was applied to the dose-response data for the ZIKV inhibitor 2′-C-methylguanosine (from CDD Vault and GraphPad Prism, version 6, software). The experiment was repeated in duplicate using two different passages of Vero cells.

Secondary assay counterscreen.

We counterscreened our remaining hit compounds by staining the plates for ZIKV antigen via immunofluorescence (Fig. 4) to confirm the reduction in virus production upon compound treatment. A reduction in the percentage of cells undergoing ZIKV-induced morphology changes observed in a bright-field image upon treatment with the potent 2′-C-methylcytidine correlated with a reduction in the amount of viral antigen, indicating agreement between the results of our image-based methods and those of previously published assays.
FIG 4
FIG 4 2′-C-Methylcytidine inhibits the cellular replication of ZIKV and blocks the cytopathic effect of the virus in Vero cells. 2′-C-Methylcytidine was tested in our phenotypic CPE assay and counterscreened using immunofluorescence. CPE-affected cell (bright field), cell nucleus (blue), and ZIKV antigen (green) image acquisition was performed at a ×10 magnification for uninfected cells, cells infected with ZIKV H/PAN/2016/BEI-259634 at an MOI of 10 for 72 h in the presence of vehicle (DMSO), and cells infected with ZIKV H/PAN/2016/BEI-259634 at an MOI of 10 for 72 h in the presence of various concentrations of 2′-C-methylcytidine.
In contrast to previously published reports that ribavirin has no effect on preventing a CPE in Vero cells (8), we observed a reduction in the number of cells undergoing ZIKV-induced morphology changes during ZIKV infection, as well as a reduction in ZIKV antigen production, via immunofluorescence when cells were treated with ribavirin at high concentrations (Fig. 5). This is most likely due to our direct visualization of a CPE through cell imaging techniques and the higher test concentration of ribavirin (up to 100 μM) used in this study.
FIG 5
FIG 5 Ribavirin reduces the production of ZIKV antigen and blocks the cytopathic effect of the virus in Vero cells. Shown are the results for the testing of ribavirin in our phenotypic CPE assay and counterscreening of the compound using immunofluorescence. CPE-affected cell (bright field), cell nucleus (blue), and ZIKV antigen (green) image acquisition was performed at a ×10 magnification for uninfected cells, cells infected with ZIKV H/PAN/2016/BEI-259634 at an MOI of 10 for 72 h in the presence of vehicle (DMSO), and cells infected with ZIKV H/PAN/2016/BEI-259634 at an MOI of 10 for 72 h in the presence of 100 μM ribavirin.

Screening of a novel library of natural product derivatives using the developed assay.

Here, we briefly describe our fragment-based approach toward the natural product-based small-molecule library used to validate our screening assay. We recently designed, synthesized, and reported on marinopyrrole derivatives as potent anti-methicillin-resistant Staphylococcus aureus (anti-MRSA) and anticancer agents (3239). The logP value of a compound, which is the logarithm of its partition coefficient between n-octanol and water [log(coctanol/cwater)], is a well-established measure of a compound's hydrophilicity. We used the ChemAxon software MarvinSketch (version 15.7.6.0; Hungary) to calculate the calculated logP ( clogP) values for the compounds in our library. As shown in Fig. 6, marinopyrroles 1a and 1b had clogP values of 6.5 and 6.1, respectively, which violates Lipinski's rule of five (40). In order to improve the physicochemical properties, we designed a library containing 24 members with lower clogP values ranging from 2.1 to 5.0. We performed structural simplification and optimization of these marinopyrrole derivatives and came up with a novel series of pyrrolomycin-like derivatives (4146). Compound 1 (Fig. 6), as one of the library members with a clogP value of 4.9, was fully characterized using nuclear magnetic resonance (NMR) and high-resolution mass spectrometry.
FIG 6
FIG 6 A library of natural product derivatives resulted from structural optimization of marinopyrroles.
Validation of the assay as a platform for the identification of new chemical entities with anti-ZIKV activity was conducted using the library of 24 natural products (Fig. 6). Screening of the library revealed compound 1 as being able to prevent a virus-induced CPE, with an EC50 of 5.95 μM and a CC50 of >100 μM (Table 2); all 23 other compounds in the library were inactive in our primary screening assay up to concentrations of 10 μM. A reduction in viral antigen production upon treatment with compound 1 was also observed in the immunofluorescence assay (Fig. 7). To validate the specific anti-ZIKV effects of compound 1, we performed a virus titration plaque assay in the presence of 10 μM of our hit and compared the results for this compound to the results for untreated and DMSO-treated samples. Compound 1 was able to suppress viral titers to undetectable levels at this concentration. Lastly, we tested compound 1 in a luminescence-based cell survival assay (Promega's CellTiter-Glo assay) in a human fetal neural stem cell (NSC) model of ZIKV infection. The compound was able to protect cells from virus-induced cell death, with an EC50 of 8.56 μM and a CC50 of >100 μM (Table 2).
TABLE 2
TABLE 2 EC50 and CC50 for compound 1 using the developed phenotypic assay and CellTiter-Glo assaya
AssayEC50 (μM)CC50 (μM)SI
PA5.95 (±0.72)>100.00>16
CTG8.56 (±0.70)>100.00>11
a
Values are the result of two independent biological replicates (±standard error). PA, phenotypic assay; CTG, CellTiter-Glo assay; SI, selectivity index.
FIG 7
FIG 7 Compound 1 has anti-ZIKV activity in Vero cells. Compound 1 was assessed in the phenotypic CPE assay and counterscreened using immunofluorescence. CPE-affected cell (bright field), cell nucleus (blue), and ZIKV antigen (green) image acquisition was performed at a ×10 magnification for uninfected cells, cells infected with ZIKV H/PAN/2016/BEI-259634 at an MOI of 10 for 72 h in the presence of vehicle (DMSO), and cells infected with ZIKV H/PAN/2016/BEI-259634 at an MOI of 10 for 72 h in the presence of 10 μM compound 1.

Conclusion.

We have developed a rapid phenotypic screen that can be used as a primary screening tool for profiling the activities of large compound libraries against ZIKV. This method can be expanded to other cell lines which display morphological changes during ZIKV infection that can be detected by automated image analysis software. As a proof of concept, we confirmed that 2′-C-methylribonucleosides and ribavirin can protect Vero cells from a ZIKV-induced cytopathic effect and identified compound 1 to be a novel scaffold against ZIKV using our assay. These findings validate our system as a useful tool for the identification of ZIKV inhibitors in a target-agnostic fashion. Future studies will focus on structure-activity relationship (SAR) optimization of compound 1 for further development and the screening of large-scale libraries to identify additional novel chemical entities for the inhibition of ZIKV replication.

MATERIALS AND METHODS

Nucleoside chemistry.

All reagents and chemicals used were purchased from Acros Organics and Fisher Chemical at American Chemical Society grade or higher quality and used as received without further purification. All nucleoside analogues were obtained from Carbosynth LLC, and N-[(S)-(2,3,4,5,6-pentafluorophenoxy)phenoxyphosphinyl]-l-alanine 1-methylethyl ester was obtained from AK Scientific. All reactions were carried out in oven-dried Schlenk tubes under a nitrogen atmosphere, using commercially available anhydrous solvents, and monitored by thin-layer chromatography, with detection by UV light. 1H NMR spectra were acquired on a Varian 400-MHz spectrometer and a Varian 500-MHz NMR spectrometer and recorded at 298 K. Chemical shifts were referenced to the residual protio solvent peak and are given in parts per million (ppm). Splitting patterns are denoted as s (singlet), d (doublet), dd (doublet of doublet), ddd (doublet of doublet of doublet), t (triplet), q (quartet), and m (multiplet).

Synthesis of nucleoside analogue ProTides. (i) General procedure.

To a stirred suspension of nucleotide (0.09 mmol, dried under vacuum at 50°C overnight) in dry tetrahydrofuran (THF; 1 ml) was added a 2.0 M solution of isopropyl magnesium chloride in THF (96 μl, 0.19 mmol). The mixture was stirred at 0°C for 30 min and then allowed to warm to room temperature and stirred for an additional 30 min. The reaction mixture was then cooled to 0°C and N-[(S)-(2,3,4,5,6-pentafluorophenoxy)phenoxyphosphinyl]-l-alanine 1-methylethyl ester (46 mg, 0.10 mmol) was added. The reaction mixture was stirred for 18 h as the temperature was allowed to warm to room temperature. The solvent was removed by rotary evaporation. The reaction mixture was purified first using flash chromatography (0 to 30% methanol [MeOH] in dichloromethane gradient) and then using preparative, normal-phase high-performance liquid chromatography (10 to 40% MeOH in dichloromethane gradient) to afford the nucleoside analogue ProTide, as assessed by NMR.

(ii) 3′-Deoxycytidine ProTide.

The product was obtained in a yield of 7.3 mg (16%). 1H NMR (400 MHz, methanol-d4) δ = 7.89 (d, 1H, J = 7.6 Hz), 7.36 (t, 2H, J = 7.2 Hz), 7.25 (d, 2H, J = 7.8 Hz), 7.19 (t, 1H, J = 7.4 Hz), 5.85 (d, 1H, J = 7.6 Hz), 5.73 (s, 1H), 4.95 (m, 1H), 4.61 (m, 1H), 4.46 (ddd, 1H, J = 2.5, 5.8, 11.6 Hz), 4.28 (m, 2H), 3.89 (m, 1H), 1.96 (m, 2H), 1.32 (dd, 3H, J = 1.1, 7.1 Hz), 1.20 (d, 6H, J = 6.3 Hz).

(iii) 3′-Deoxyadenosine ProTide.

The product was obtained in a yield of 5.0 mg (10.6% yield). 1H NMR (400 MHz, methanol-d4) δ = 8.32 (s, 1H), 8.18 (s, 1H), 7.27 (t, 2H, J = 7.9 Hz), 7.13 (t, 1H, J = 7.4 Hz), 7.08 (d, 2H, J = 7.7 Hz), 6.17 (d, 1H, 3.3 Hz), 5.53 (m, 1H), 4.96 (m, 1H), 4.51 (m, 1H), 3.90 (m, 2H), 3.66 (dd, 1H, J = 3.3, 12.4 Hz), 3.35 (s, 1H), 2.63 (m, 1H), 2.37 (m, 1H), 1.30 (d, 1H, J = 7.2 Hz), 1.22 (t, 6H, J = 6.3 Hz).

(iv) 3′-Deoxy-3′-fluoroguanosine ProTide.

The product was obtained in a yield of 4.8 mg (9.8% yield). 1H NMR (400 MHz, methanol-d4) δ = 7.84 (s, 1H), 7.38 (t, 2H, J = 7.8 Hz), 7.26 (d, 2H, J = 7.9), 7.22 (t, 1H, J = 7.4 Hz), 5.89 (d, 1H, J = 7.7 Hz), 5.12 (m, 1H), 4.95 (m, 1H), 4.50 (m, 1H), 4.37 (q, 2H, J = 5.1 Hz), 3.92 (m, 1H), 3.36 (s, 1H), 1.33 (d, 3H, J = 7.0 Hz), 1.22 (d, 6H, J = 6.4 Hz).

(v) 3′-O-Methyluridine ProTide.

The product was obtained in a yield of 7.0 mg (14.9% yield). 1H NMR (400 MHz, methanol-d4) δ = 7.62 (d, 1H, J = 8.1 Hz), 7.37 (t, 2H, J = 8.2 Hz), 7.25 (d, 2H, J = 7.6 Hz), 7.20 (t, 1H, J = 6.5 Hz), 5.85 (d, 1H, J = 5.1 Hz), 4.97 (m, 1H), 4.33 (m, 1H), 4.27 (m, 1H), 4.22 (m, 2H), 3.91 (m, 1H), 3.82 (t, 1H, J = 5.1 Hz), 3.44 (s, 1H), 1.34 (dd, 3H, J = 1.1, 7.1 Hz), 1.22 (dd, 6H, J = 1.9, 6.3 Hz).

(vi) 5-Fluorocytidine ProTide.

The product was obtained in a yield of 5.2 mg (10.9% yield). 1H NMR (400 MHz, methanol-d4) δ = 7.86 (d, 1H, J = 6.6 Hz), 7.35 (t, 2H, J = 7.6 Hz), 7.25 (d, 2H, J = 8.7 Hz), 7.18 (t, 1H, J = 7.4 Hz), 5.81 (dd, 1H, J = 1.7, 3.7 Hz), 4.94 (m, 1H), 4.41 (ddd, 1H, J = 2.5, 5.7, 11.5 Hz), 4.31 (m, 1H), 4.16 (m, 1H), 4.10 (t, 1H, J = 5.6), 4.03 (dd, 1H, J = 3.6, 5.2 Hz), 3.90 (m, 1H), 1.32 (dd, 3H, J = 1.0, 7.1 Hz), 1.20 (d, 6H, J = 6.3 Hz).

(vii) 2′-O-Methylcytidine ProTide.

The product was obtained in a yield of 7.7 mg (16.3% yield). 1H NMR (400 MHz, methanol-d4) δ = 8.05 (s, 1H), 7.36 (t, 2H, J = 7.6 Hz), 7.25 (d, 2H, J = 8.0 Hz), 7.20 (t, 1H, 7.3 Hz), 6.02 (s, 1H), 5.88 (s, 1H), 4.85 (s, 1H), 4.32 (s, 1H), 4.16 (s, 2H), 3.88 (d, 2H), 3.55 (s, 3H), 1.33 (d, 3H, J = 6.8 Hz), 1.20 (d, 6H, J = 6.2 Hz).

(viii) 2′-C-Methylcytidine ProTide.

The product was obtained in a yield of 8.2 mg (17.4% yield). 1H NMR (400 MHz, methanol-d4) δ = 7.76 (dd, 1H, J = 5.1, 7.6 Hz), 7.37 (t, 2H, J = 7.3 Hz), 7.26 (t, 2H, J = 7.6 Hz), 7.20 (t, 1H, J = 7.6 Hz), 6.02 (s, 1H), 5.87 (t, 1H, J = 9.6 Hz), 4.94 (m, 1H), 4.51 (ddd, 1H, J = 2.0, 5.9, 11.8 Hz), 4.35 (m, 1H), 4.12 (m, 2H), 3.75 (dd, 1H, J = 4.2, 9.3 Hz), 1.31 (dd, 3H, J = 0.9, 7.1 Hz), 1.20 (d, 6H, J = 6.3 Hz), 1.11 (s, 3H).

(ix) 2′-C-Methyladenosine ProTide.

The product was obtained in a yield of 17 mg (35.0% yield). 1H NMR (400 MHz, methanol-d4) δ = 8.24 (s, 1H), 8.21 (s, 1H), 7.34 (t, 2H, J = 7.9 Hz), 7.25 (d, 2H, J = 8.8 Hz), 7.17 (d, 1H, J = 7.2 Hz), 6.10 (s, 1H), 4.84 (m, 1H), 4.50 (m, 2H), 4.25 (m, 2H), 3.91 (m, 1H), 1.30 (dd, 3H, J = 1.0, 7.0 Hz), 1.15 (dd, 6H, J = 6.3, 12.0 Hz), 0.94 (s, 3H).

(x) 2′-C-Methyluridine ProTide.

The product was obtained in a yield of 12 mg (24.5% yield). 1H NMR (400 MHz, methanol-d4) δ = 7.68 (d, 1H, J = 8.1 Hz), 7.37 (t, 2H, J = 5.6, 15.7 Hz), 7.26 (d, 2H, J = 8.7 Hz), 7.20 (t, 1H, J = 7.4, 14.7 Hz), 5.60 (s, 1H), 5.60 (d, 1H, J = 8.1 Hz), 4.95 (m, 1H, 6.3 Hz), 4.50 (ddd, 1H, J = 2.0, 8.5, 11.8 Hz), 4.36 (ddd, 1H, J = 3.6, 5.9, 11.8 Hz), 4.09 (m, 1H), 3.91 (m, 1H), 3.79 (d, 1H, 9.3 Hz), 1.34 (d, 3H, J = 7.1 Hz), 1.21 (d, 6H, J = 6.3 Hz), 1.15 (s, 3H).

Cells.

Vero cells were purchased from ATCC (ATCC CCL-81) and cultured in Dulbecco's modified Eagle medium (DMEM; Gibco) supplemented with 10% fetal bovine serum (FBS; Sigma), 4.5 g/liter d-glucose, 4 mM l-glutamine, and 110 mg/liter sodium pyruvate (Gibco). Culturing of cells was conducted in incubators at 37°C with 5% CO2. Human fetal NSCs were obtained commercially from Clontech (human neural cortex; catalog number Y40050). The NSCs were maintained in Neurobasal-A medium without phenol red (Thermo Fisher) with the addition of B-27 supplement (1:100; catalog number 12587010; Thermo Fisher), N-2 supplement (1:200; catalog number 17502-048; Invitrogen), 20 ng/ml fibroblast growth factor (catalog number 4114-TC-01M; R&D Systems), 20 ng/ml epidermal growth factor (catalog number 236-EG-01M; R&D Systems), GlutaMAX (catalog number 35050061; Thermo Fisher), and sodium pyruvate. The cells were plated into 6-well plates that had been precoated with laminin (10 mg/ml; catalog number L2020; Sigma). Cells were grown to near confluence (80 to 90%) prior to passage. For passaging, cells were rinsed gently with phosphate-buffered saline (without calcium and magnesium), and then Accutase cell detachment solution (catalog number A6964; Sigma) was added for 5 min at 37°C to allow detachment.

Viruses.

The following material was obtained through BEI Resources, NIAID, NIH: Zika virus H/PAN/2016/BEI-259634, NR-50210 (GenBank accession number KX198135). The virus was expanded in Vero cells for 2 to 3 serial passages to amplify the titers. Infected cell supernatants were centrifuged to remove cell debris and then concentrated through a sucrose cushion. Concentrated virus was resuspended in neural maintenance medium base (50% DMEM–F-12 medium–GlutaMAX, 50% Neurobasal-A medium, 1× N-2 supplement, 1× B-27 supplement [Life Technologies]) supplemented with 1% DMSO (Sigma) and 5% FBS (Gibco) and stored at −80°C. Viral stock titers were determined by plaque assay on Vero cells and were greater than or equal to 2 × 108 PFU/ml.

Cytopathic effect assay.

The compounds were prespotted into 1,536-well Greiner black well plates using an acoustic transfer system (EDC Biosciences). Vero cells were seeded at 100 per well in the presence of 0.1% DMSO or test compound and with ZIKV at an MOI of 10 or without virus. The cultures were incubated for 72 h in incubators at 37°C with 5% CO2. The plate wells were then imaged in bright-field mode using an ImageXpress microplate imager (Molecular Devices), and the cells were subsequently fixed with 4% formaldehyde, stained with DAPI in 0.85% NaCl, 0.1% Triton-X, 0.01% sodium azide, and 100 mM ammonium chloride for 1 h, and then imaged to acquire images of cell nuclei. A custom analysis module in MetaXpress software (Molecular Devices) was used to segment and tabulate the total numbers of cells undergoing ZIKV-induced morphology changes in the bright-field mode and total cell nuclei (see below). Data processing, including normalization and EC50 and CC50 calculations, was conducted using CDD Vault (Collaborative Drug Discovery Inc., Burlingame, CA) and GraphPad Prism software (La Jolla, CA).

Automated image analysis module.

Using the MetaXpress Custom Module Editor, an image segmentation protocol was created to quantify Vero cells undergoing a CPE during ZIKV infection in the bright-field mode, and a simple threshold ranging from 0 to 65,535 intensity units was created. Next, a Gaussian filter with a sigma value of 2 was first applied to the image. Using the multiply function, the product of these two images was generated and then multiplied by 5,000. A gradient was then applied to this result using a pixel size of 2. An Open filter was then applied with a Circle filter shape and pixel size of 2, with gray-scale reconstruction included. Subsequently, a Find Round Objects filter was used to detect in the image Vero cells undergoing ZIKV-induced morphology changes; the approximate object minimum was set to 10 μm, the approximate object maximum was set to 30 μm, and the intensity above the local background was 300 intensity units. A filter mask, which was used in the final object quantification, was then created: the breadth of the detected round objects was subjected to a RangeFilter function of 10 to 30 μm inclusive, while the average object intensity was treated to a RangeFilter function of 2,000 to 60,000 intensity units.
To normalize the number of objects detected in bright-field images to the number of cells in a given image, a cell nucleus detection mask for DAPI-stained cells was developed using the MetaXpress Custom Module Editor. An Open filter for circular objects with size of 9 pixels was first applied to the images of DAPI-stained cells. A Gaussian filter with a sigma value of 2 was then applied to the resultant image. A Find Round Objects filter was next used to detect nuclei, with the approximate object minimum being set to 6 μm, the approximate object maximum being set to 25 μm, and the intensity above the local background being 30 intensity units.

Immunofluorescence.

Following bright-field and DAPI imaging, plates were incubated with antiflavivirus group antigen primary antibody (clone D1-4G2-4-15; Millipore) at a 1:200 stock dilution overnight at 4°C. Upon aspiration of the primary antibody from the plates, fluorescein isothiocyanate (FITC) goat anti-mouse IgG (H+L) secondary antibody (Life Technologies) was added at a 1:1,000 stock dilution and the plate was incubated for 1 h at 25°C. Secondary antibody was aspirated; samples were then incubated in a buffer containing 0.85% NaCl, 0.1% Triton-X, 0.01% sodium azide, and 100 mM ammonium chloride and imaged in the FITC channel using an ImageXpress Micro plate imager (Molecular Devices).

ZIKV titration.

The numbers of PFU were calculated using a plaque-forming assay with Vero cells. Vero cells were seeded at a density of 3 × 104 cells per well in 96-well plates and incubated in 5% CO2 at 37°C for 24 h before infection. Inocula were collected from ZIKV H/PAN/2016/BEI-259634-infected NSCs (MOI, 0.1) in the presence of 10 μM compound 1, mock-infected cultures, infected cultures without compound treatment, and infected cultures with the DMSO vehicle at 48 h postinfection. Tenfold serial dilution was performed for each collected inoculum in high-glucose DMEM containing 1% FBS and 1% penicillin-streptomycin. The diluted inocula were added to preseeded Vero cells for 1 h, covered by an agarose overlay, and further incubated for 72 h. The assay was then terminated by fixation with 37% formaldehyde for 24 h. After the fixation, the overlay was removed and stained with 1× crystal violet to count the ZIKV plaques.

CellTiter-Glo assay.

NSCs (5,000 cells/well) were seeded into 384-well plates at 12 h prior to infection. ZIKV H/PAN/2016/BEI-259634 was added at an MOI of 5. In all experiments, mock-infected cells were incubated in parallel. Cell viability was measured using the CellTiter-Glo assay (Promega), and readouts for luminescence intensity were conducted using an EnVision plate reader (PerkinElmer). All data were normalized to those for the DMSO controls and are expressed as relative luminescence intensity.

ACKNOWLEDGMENTS

This research was partially supported by Clinical and Translational (CTRI) pilot grant UL1TR001442. B.W.P., M.C., L.A.L., and C.D.S. thank San Diego State University for financial support. The design and synthesis of a library of natural product derivatives were partially supported by the Nebraska Research Initiative (NRI) and start-up funds to R.L. from the University of Nebraska Medical Center.
We declare that we have no competing interests.

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Information & Contributors

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Published In

cover image Antimicrobial Agents and Chemotherapy
Antimicrobial Agents and Chemotherapy
Volume 62Number 10October 2018
eLocator: e00725-18
PubMed: 30061280

History

Received: 13 April 2018
Returned for modification: 3 May 2018
Accepted: 30 May 2018
Published online: 24 September 2018

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Keywords

  1. Zika virus
  2. antiviral agents
  3. high-throughput screening
  4. cellular imaging

Contributors

Authors

Jean A. Bernatchez
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA
Center for Discovery and Innovation in Parasitic Diseases, University of California, San Diego, La Jolla, California, USA
Zunhua Yang
Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA
Michael Coste
Department of Chemistry and Biochemistry, San Diego State University, San Diego, California, USA
Jerry Li
Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA
Sungjun Beck
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA
Yan Liu
Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA
Alex E. Clark
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA
Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California, USA
Sanford Consortium for Regenerative Medicine, La Jolla, California, USA
Department of Medicine, Division of Regenerative Medicine, School of Medicine, University of California, San Diego, La Jolla, California, USA
Lucas A. Luna
Department of Chemistry and Biochemistry, San Diego State University, San Diego, California, USA
Christal D. Sohl
Department of Chemistry and Biochemistry, San Diego State University, San Diego, California, USA
Byron W. Purse
Department of Chemistry and Biochemistry, San Diego State University, San Diego, California, USA
Rongshi Li
Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA
Jair L. Siqueira-Neto
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA
Center for Discovery and Innovation in Parasitic Diseases, University of California, San Diego, La Jolla, California, USA

Notes

Address correspondence to Rongshi Li, [email protected], or Jair L. Siqueira-Neto, [email protected].

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