Screening the Global Health Priority Box Against Plasmodium berghei Liver Stage Parasites Using an Inexpensive Luciferase Detection Protocol

doi:10.21203/rs.3.rs-4882812/v1

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Screening the Global Health Priority Box Against Plasmodium berghei Liver Stage Parasites Using an Inexpensive Luciferase Detection Protocol

https://doi.org/10.21203/rs.3.rs-4882812/v1

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Background

Malaria, a disease caused by parasites of the genus Plasmodium, continues to impact many regions globally. The rise in resistance to artemisinin-based antimalarial drugs highlights the need for new treatments. Ideally, new antimalarials will kill the asymptomatic liver stages as well as the symptomatic blood stages. While blood stage screening assays are routine and efficient, liver stage screening assays are more complex and costly. To decrease the cost of liver stage screening we utilized a previously reported luciferase detection protocol requiring only common laboratory reagents and adapted this protocol for testing against luciferase-expressing Plasmodium berghei liver stage parasites.

Methods

After optimizing cell lysis conditions, the concentration of reagents, and the density of host hepatocytes (HepG2), we validated the protocol with 28 legacy antimalarials show this simple protocol produces a stable signal useful for obtaining quality small molecule potency data similar to that obtained from a high-content imaging endpoint. We then use the protocol to screen the Global Health Priority Box (GHPB) and confirm the potency of hits in dose-response assays. Selectivity was determined using a galactose-based, 72 hr HepG2 assay to avoid missing mitochondrial-toxic compounds due to the Crabtree effect. Receiver-operator characteristic plots were used to retroactively characterize the screens’ predictive value.

Results

Optimal luciferase signal was achieved using a lower HepG2 seed density (5 x 10³ cells/well of a 384-well plate) compared to many previously-reported luciferase-based screens. While producing lower RLU’s compared to a commercial alternative, our luciferase detection method was found much more stable, with a > 3 hr half-life, and robust enough for producing dose-response plots with as few as 500 sporozoites/well. Our screen of the GHPB resulted in 9 hits with selective activity against P. berghei liver schizonts, including MMV674132 which exhibited 30.2 nM potency. Retrospective analyses show excellent predictive value for both antimalarial activity and cytotoxicity.

Conclusions

We project this method is suitable for high-throughput screening at a cost 20-fold less than using commercial luciferase detection kits, thereby enabling larger liver stage antimalarial screens and hit optimization make-test cycles. Further optimization of the hits detected using this protocol is ongoing.

Malaria continues to afflict half of the world’s population, predominantly in tropical regions such as Africa, South America, and Southeast Asia¹. The disease initially causes low-grade fever, chills, and muscle aches. However, as the disease progresses, symptoms worsen to include high fever and exhaustion, leading to severe malaria, which includes anemia, damage of the organs, and possibly death². Caused by the parasite of the genus Plasmodium, Plasmodium falciparum and Plasmodium vivax are the most widespread, with P. falciparum accounting for 99.7% of malaria cases in Africa and P. vivax accounting for 46% cases in South America and Southeast Asia¹.

Anopheles mosquitoes are the vectors of Plasmodium². During a mosquito bite, the mosquito draws the human’s blood while also injecting its saliva. If the mosquito is carrying Plasmodium, the highly motile and infective form of the parasite, termed sporozoites, are also injected into the skin. These sporozoites then travel to the liver through the lymphatic system to infect hepatocytes. Once a liver cell is infected, the sporozoite replicates through asexual fission, resulting in thousands of parasites, termed merozoites, that will burst out of the hepatocyte and enter the bloodstream to infect red blood cells³. However, for P. vivax and Plasmodium ovale, some sporozoites can become a dormant form of the parasite, termed hypnozoites, that dwell in the liver for months or years before reactivating to cause a relapse blood infection⁴.

The two most effective measures against malaria have been the usage of insecticide and the administration of drugs, however, the rapid rise of resistance to both raises concerns about their long-term effectiveness⁵. To continue malaria control and elimination, requirements for specific types of new antimalarials called target candidate profiles (TCPs), are used to guide new antimalarial development⁶. While much of antimalarial discovery today is focused on the symptom-causing blood stage (TCP1), the liver stage is regarded as an important therapeutic target for P. vivax hypnozoites (TCP3) and a chemopreventive bottleneck for P. falciparum and P. vivax (TCP4). Because of the cost and burdensome logistics of P. falciparum and P. vivax liver stage assays, liver stage active compounds are typically first characterized using the well-established P. berghei murine malaria liver model in which HepG2 human hepatoma cells are infected with P. berghei sporozoites, treated with test compounds, and then assessed for activity at 44-48hrs post infection ^7,8.

Immunofluorescence is one method of measuring parasite inhibition in liver stage assays. Following this method, cells are fixed, parasites are stained with antibodies raised against HSP70 or GAPDH, a DNA stain is added to label both the hepatic and parasite nuclei, and high-content imaging (HCI) is used to quantify parasite growth⁹. While this method is effective, it also consumes much time and invaluable resources, such as the detection antibodies. Another method of measuring P. berghei liver schizont formation is through the usage of Luciferase Reporter Assays (LRA). Photinus pyralis fireflies contain the luciferase gene. This gene codes for the luciferase enzyme which binds to the substrate D-luciferin, causing D-luciferin to undergo oxidative decarboxylation to form oxyluciferin and simultaneously emit energy in the form of light photons. Luciferase has been transgenically engineered into numerous cell-based systems as a reporter for gene expression, cell viability, in vivo imaging, and other applications¹⁰. One strain of P. berghei, PbGFP-Luc_con¹¹, has been used for over a decade to screen thousands of microtiter plates of test compounds, resulting in several new classes of liver stage active antimalarials. However, a hindrance to LRAs is the cost of commercially-sourced detection reagents.

A recent report describes a LRA using only common laboratory reagents and D-luciferin to generate an in-house firefly luciferase assay reagent (FLAR)¹². In this work we describe our application of this protocol into our P. berghei screening platform and then use this platform for screening the Medicines for Malaria Venture Global Health Priority Box (GHPB), an open collection of 240 diverse compounds for broad-application drug screening. Our method reduces the cost and turnaround of liver stage drug screening and development, thereby potentially expediting the availability of new TCP3 and TCP4 antimalarials.

HepG2 Culture

HepG2 cells (Homo sapiens hepatoblastoma, ATCC, cat HB-8065, RRID:CVCL_0027) were cultured in collagen-coated T75 flasks in media consisting of sugar-free DMEM (Gibco, cat 11966-025) supplemented with 10% FBS (Corning, cat 35-016-CV), 25 mM Glucose (Millipore-Sigma, cat 49163), 1 mM Sodium Pyruvate (Corning, cat 25-000-CI), 1x penicillin-streptomycin-neomycin mix (Gibco, cat 15640-055), and 2 mM L-glutamine (Gibco, cat 25030-081). Flasks were kept in an incubator at 37°C and 5% CO₂.

For seeding microtiter plates, TrpysinLE (Gibco, cat 12605-028) was used to harvest cells from a 60–90% confluent T75 flask. The cell density was calculated using trypan blue exclusion on a hemocytometer, diluted as needed (see details below), and cells were seeded into collagen-coated 384 well plates (Greiner Bio-One, cat 781956) using a Biomek NXp (Beckman Coulter).

P. berghei Sporozoite Production

Luciferase-expressing P. berghei ANKA strain GFP-Luc_ama1−eef1a (line 1052cl1) were obtained from the Sporocore at UGA as previously described¹³. Sporozoite isolation was performed as previously described using bicarbonate-free RPMI (KD Medical, cat CUS-0645) as the collection buffer¹⁴.

FLAR Stock Solutions

The following reagents were obtained and made into the indicated stock solutions in cell culture grade water: 25 mM BD Monolight™ D-luciferin (D-luciferin) Potassium Salt (BD Biosciences, cat 556877), 25 mM Adenosine 5′-triphosphate (ATP) disodium salt hydrate (Millipore-Sigma, cat A26209-1G), 200 mM tricine (VWR, cat 97062-642), 10 mM EDTA (J.T. Baker, cat 8993-01), 50 mM MgSO₄ (Millipore Sigma, cat M2643), 10 mM MgCO₃ (VWR, cat 470301-626), and 500 mM DTT (VWR, cat 97063-760). All stock reagents were stored at 4° C, except D-luciferin, ATP, and DTT which were aliquoted and stored at -20°C. Tricine, MgSO₄, and MgCO₃ stocks were all adjusted to have a pH of 7.8. To make a working solution of 1x FLAR, immediately before the assay endpoint the reagents were mixed to make a solution containing 100 µM D-luciferin, 100 µM EDTA, 125 µM ATP, 1.07 mM MgCO₃, 2.67 mM MgSO₄, 20 mM tricine, and 20 mM DTT in cell culture water.

Sporozoite Infection for Endpoint Optimization Studies

Following dissection and quantification of sporozoites, the sporozoite density was set to 250 sporozoites/µL in HepG2 media and serially diluted 1:1 in microcentrifuge tubes using HepG2 media to produce a sporozoite density gradient of 250, 125, 62.5, 31.3, 15.6, 7.81, 3.91, and 1.95 sporozoites/µL. HepG2 cells, seeded at 1.75 x 10⁵ cells/well the day prior, were infected by removing 20 µL of the 40 µL seed volume and adding 20 µL of sporozoite solution to the appropriate rows, resulting in a multiplicity of infection (MOI) of 5.00 x 10³, 2.50 x 10³, 1.25 x 10³, 625, 312, 156, 78, or 39 net sporozoites/well (Fig. S1). Two copies of this plate map were seeded and infected, one for the Triton X lysis endpoint and one for the Freeze/Thaw lysis endpoint. Following infection, plates were spun for 5 min at 200 RCF. After spinning, both plates were stored for 44 hrs in an incubator at 37°C and 5% CO₂.

Cell Lysis and Luciferase Detection Optimization

To test the Triton X cell lysis method, FLAR was prepared at 2x concentration (40 mM Tricine, 200 µM EDTA, 5.34 mM MgSO4, 2.14 mM MgCO3, 40 mM DTT) and split into 4 aliquots. D-luciferin and ATP were added to aliquots to achieve 2x (200 µM D-luciferin and 250 µM ATP), 4x (400 µM D-luciferin and 500 µM ATP), 10x (1 mM D-luciferin and 1.25 mM ATP), and 20x (2 mM D-luciferin and 2.5 mM ATP) concentration. One of the 384 well plates containing the sporozoite dilution series was dumped of its contents and then 20 µL 0.1% (v/v) Triton X in PBS was added into each well and incubated for 30 min at 37°C and 5% CO₂. After Triton X treatment, 20 µL of 2x FLAR was added into each well of the plate such that 2x D-luciferin and ATP were added to row A-D (resulting in 1x final concentration), 4x to rows E-F (resulting in 2x final concentration), 10x to rows I-L (resulting in 5x final concentration), and 20x to rows M-P (resulting in 10x final concentration). To test the Freeze/Thaw lysis method 1x FLAR was prepared and split into 4 aliquots. D-luciferin and ATP were added to aliquots to achieve 1x (100 µM D-luciferin and 125 µM ATP), 2x (200 µM D-luciferin and 250 µM ATP), 5x (500 µM D-luciferin and 625 µM ATP), and 10x (1 mM D-luciferin and 1.25 mM ATP) concentrations. To test the Freeze/Thaw method, the second 384 well plate containing the sporozoite dilution series was dumped of its contents. It was then placed in a -80°C freezer for 15 min and then thawed in an incubator at 37°C for 15 min. After thawing, 40 µL of 2x FLAR was added into each well of the plate such that 1x D-luciferin and ATP were added to row A-D, 2x to rows E-F, 10x to rows I-L, and 20x to rows M-P. The plates were then placed in a SpectraMax i3x plate reader (Molecular Devices), and luminescence quantified for 500 milliseconds.

Infection, Treatment, and Endpoints for Legacy Antimalarial in Dose-Response Plates

HepG2 seeding (1.75 x 10⁵ cells/well), salivary gland dissection, sporozoite quantification, and sporozoite dilution were performed as described above. To test the titration of sporozoite in dose-response format with MMV390048, 20 µL of a 25 sporozoite/µL solution in HepG2 media was added columns 1–8 of 384-well plates (MOI of 500 sporozoites/well), 20 µL of 50 sporozoites/µL was added into columns 9–16 (MOI of 1000 sporozoites/well), and 20 µL of 100 sporozoites/µL was added into columns 17–24 (MOI of 2000 sporozoites/well). To test legacy antimalarials, two independent experiments were performed for each endpoint (LRA or HCI), each with an independent production run of P. berghei sporozoites. These runs were performed with the maximum number of sporozoites available, which resulted in an MOI of 1.28 x 10³ and 1.96 x 10³ sporozoites/well for the LRA replicates and 1.66 x 10³, and 2.00 x 10³ sporozoites/well for HCI replicates. Infected plates were spun for 5 min at 200 RCF and kept for 3 hrs at 37°C and 5% CO₂ prior to compound treatment.

Compound treatment was performed as previously described¹⁴. Dose-response source plates containing 5 µL of 1000x test compounds in a serial dilution in DMSO were prepared in low volume 384-well plates using a Biomek 4000 (Beckman Coulter). Assay plates were treated by transferring 40 nL from screening or dose-response source plates using a pin tool (V&P Scientific) affixed to a Biomek NXp, resulting in a final test concentration of 1x in media.

After 44 hrs, dose-response plates designated for the LRA endpoint underwent the Freeze/Thaw lysis method before detection with 1x FLAR completed with 1x D-luciferin and ATP endpoint described above. Plates designated for the HCI endpoint were fixed with 4% paraformaldehyde (Thermo Scientific, cat 043368.9M) in PBS for 20 min. Following fixation, the plate was washed twice by adding and then dumping 20 µL of PBS per well. Plates were then stained with 50 ng/mL of mouse anti-Plasmodium glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (European Malaria Reagent Repository, cat 13.3) diluted in a 0.3% Triton X and 1% BSA permeabilization and blocking stain buffer overnight at 4°C. Following three washes with PBS, plates were stained with 2 µg/mL of goat anti-mouse AlexaFluor 488 (Invitrogen, cat A11001) diluted in stain buffer and again incubated overnight at 4°C. Following three washes with PBS, plates were counterstained with 10 µg/mL Hoechst 33342 (Invitrogen, cat H21492) for 30min before two washes. Plates were imaged on an ImageXpress Micro Confocal high content system (Molecular Devices). Curve fitting was performed using CDD Vault. Data from all plates were collected, visualized, and analyzed using GraphPad Prism (Version 10.0.3).

HepG2 Seed Density Optimization, Comparison to Bright-Glo™, and Signal Stability

The ideal HepG2 seed density for optimal luciferase signal was determined by seeding a 384-well plate with a gradient of cells. Following trypsin treatment, the HepG2 cell density was adjusted to 400 cells/µL and a 16-channel pipettor was used to add 5 µL cells to columns 1 and 2, 7.5 µL to columns 3 and 4, 10 µL to columns 5 and 6, 12.5 µL to columns 7 and 8, 15 µL to columns 9 and 10, 17.5 µL to columns 11 and 12, 20 µL to columns 13 and 14, 22.5 µL to columns 15 and 16, 25 µL to columns 17 and 18, 31.25 µL to columns 19 and 20, 37.5 µL to columns 21 and 22, and 43.75 µL to columns 23 and 24, thereby delivering 2 x 10³, 3 x 10³, 4 x 10³, 5 x 10³, 6 x 10³, 7 x 10³, 8 x 10³, 9 x 10³, 1 x 10⁴, 1.25 x 10⁴, 1.5 x 10⁴, or 1.75 x 10⁴ cells/well, respectively. Additional media was added to each column to make the total volume per well 40 µL. The next day, sporozoites were harvested as above and the maximum number of sporozoites were infected into wells, resulting in an MOI of 1.224 x 10³ sporozoites per well for replicate 1 and 1.333 x 10³ sporozoite per well for replicate 2. After 44 hrs, media was dumped from the plate and plates were lysed using the Freeze/Thaw method as above. Luminescence signal from four rows of the plate were detected using 40 µL 1x FLAR as above, and four other rows were detected using 20 µL Bright-Glo™ (Promega, cat E2610) per manufacturer’s instructions. Plates were read immediately as above to ascertain the effect of seed density on signal, and then read every 3 min for 3 hrs in a kinetic experiment to characterize signal stability.

GHPB Screen and Dose-Response Confirmation

The GHPB is an open-access collection of compounds (80 for vector control, 80 for zoonotic and neglected diseases, 80 for drug resistant malaria) obtained from Medicines for Malaria Venture. The library was supplied in a 96-well microtiter plate and moved into a low-volume 384-well plate (Greiner Bio-One, cat 784261) using a Biomek NXp to transfer 5 µL of 1 mM compound into the destination wells. MMV390048 was used for the positive control wells and DMSO was used for the negative control wells. The GHPB was screened by seeding 5 x 10³ cells/well which, after 24 hrs, were infected with a maximum available MOI of 1.44 x10³ sporozoites/well. Three hours post-infection, plates were treated with a pin tool as described above. After 44 hrs, media was dumped from the plate, lysed using the Freeze/Thaw method, and luciferase signal was detected with 1x FLAR as described above.

To assess the general cytotoxicity of GHPB compounds, we used HepG2 cells cultured in media containing galactose instead of glucose to avoid false negatives due to the Crabtree effect¹⁵. Following propagation of HepG2 in T-75 flasks with glucose-containing media as above, media was aspirated, the cell monolayer was washed with PBS, and then cells were trypsinized as above. Released cells were then resuspended in media containing glucose-free DMEM (Gibco, cat 11966-025) supplemented with 10% FBS (Corning, cat 35-016-CV), 10 mM Galactose (Sigma, cat G5388), 1 mM Sodium Pyruvate (Corning, cat 25-000-CI), 1x penicillin-streptomycin-neomycin mix (Gibco, cat 15640-055), and 2 mM L-glutamine (Gibco, cat 25030-081). The cell density was calculated using trypan blue exclusion on a hemocytometer, diluted to 50 cells/µL, and 40 µL of cells were seeded into collagen-coated 384 well plates (Greiner Bio-One, cat 781956) using a Biomek NXp (Beckman Coulter), resulting in 2 x 10³ cells/well. The day after seeding, plates were treated with a pin tool as above and cultured for 72 hrs. Plates were then fixed with 4% paraformaldehyde, stained with 10 µg/mL Hoechst 33342, and imaged on an ImageXpress Micro Confocal. Hepatic nuclei were quantified using MetaXpress (Molecular Devices) image analysis software. Both P. berghei liver schizont and HepG2 cytotoxicity data were loaded into CDD Vault for normalization and hit selection.

A total of 35 compounds were identified for resupply of fresh powder for confirmation in dose-response assays. This included 6 hit compounds with > 80% inhibition of P. berghei and < 15% inhibition of HepG2 cells. The other 29 compounds were selected to characterize the P. berghei liver schizont and HepG2 cytotoxicity assays’ positive and negative predictive values. Powders were diluted to 50 mM in DMSO and plated in 1000x source plates as described above. MMV390048 and puromycin were plated as the positive control for P. berghei liver schizont activity and cytotoxicity, respectively. Two independent experiments using 1x FLAR and 5 x 10³ cells/well were performed to assess the potency of these compounds against P. berghei liver schizonts, each with an independent production run of P. berghei sporozoites. These runs were performed with the maximum number of sporozoites available, which resulted in an MOI of 1.22 x 10³ and 1.33 x 10³ sporozoites/well. Separately, two independent runs of the HepG2 cultured in galactose, assayed as described above, were used to assess the cytotoxicity potency and selectivity indices for these compounds. Both P. berghei liver schizont and HepG2 cytotoxicity data were loaded into CDD Vault for normalization, curve fitting, and EC₅₀ calculations. Receiver-operator characteristic (ROC) curves were generated using Graphpad Prism and area under curve (AUC) was calculated using the Wilson/Brown method for both P. berghei liver schizont activity and HepG2 cytotoxicity¹⁶. For P. berghei ROC classification, hits found active in dose-response with an EC₅₀ < 0.333 µM were considered as positives, compounds with an EC₅₀ > 0.333 µM were considered negative as they would be expected to be only partially active or inactive in a 1 µM primary screen (ie see MMV689635 below). For cytotoxicity ROC classification, hits found cytotoxic in dose-response with a CC₅₀ < 2 µM were considered toxic as even a small loss of hepatic nuclei (ie, 15% or more) is indicative of host cell inhibition and thus would be detected as partially active in the 1 µM primary screen (Fig. 6).

To adapt the previously-reported LRA using FLAR¹² for detecting P. berghei liver stage schizont growth, we started by designing an experiment to simultaneously test a range of FLAR concentrations, two different methods for cell lysis, and a range of sporozoite MOI to generate a gradient of schizonts per well in 384-well plates (Fig. S1). To test the effectiveness of each lysis method, two replicate plates were started and used for either lysis via Freeze/Thaw or Triton X. We noted much better luminescence signal using the Freeze/Thaw lysis method (Fig. 1A) and robust signal over background became apparent with an MOI as few as 625 sporozoites/well (Fig. 1B). The concentration of FLAR did not appear to affect overall signal or well-well variability (Fig. 1B). From these results we moved forward with an optimized protocol using Freeze/Thaw lysis and 1x FLAR (Table 1).

We next sought to demonstrate the effectiveness of the LRA using FLAR as an alternative to HCI by testing legacy antimalarials in full dose-response assays. To begin, we used the FLAR protocol to measure the potency of the multi-stage active phosphatidylinositol-4-kinase (PI4K) inhibitor MMV390048 in assays started with an MOI of 0.5 x10³, 1.0 x 10³, or 2.0 x 10³ sporozoites. We noted excellent dose-response curves and similar EC₅₀ calculations for the assays started with all three MOIs, indicating this range was suitable for additional studies (Fig. S2A). Next, we selected a set of 28 legacy, clinically used, or developmental antimalarials and started assay plates with the maximum MOI based on the number of sporozoites harvested from salivary gland dissections (which are variable and somewhat unpredictable across production runs). After testing these 28 inhibitors in two independent experiments using the LRA endpoint and two independent experiments using the HCI endpoint, we found the two endpoints resulted in nearly identical potency calculations (Fig. 2, simple linear regression, Y = 0.9919*X + 0.06728, R² = 0.9863). Of note, the MMV390048 control was one of the 28 developmental antimalarials tested and produced a robust dose-response curve using an MOI of 1.27 x 10³ (run 1) or 1.96 x 10³ (run 2) sporozoites/well (Fig. S2B).

The activity of the 28 validation compounds can be summarized into three groups (Fig. 2A). First were those resulting in a full dose-response curve in both independent experiments. This group included the developmental inhibitors M5717, P218, cipargamin, and DSM265, which were found as the most potent of the entire set. Like MMV390048, the PI4K inhibitor KDU691 killed liver stage schizonts at high nanomolar potency. Also included were legacy antimalarials pyrimethamine, atovaquone, methylene blue, and enantiopure mefloquine. The second group were those which were either potent at the highest dose only, which resulted in a poor curve fit, or in only one of two independent experiments. Interestingly, this group contained the endoperoxides OZ439, OZ277, artesunate, and artemether which are not known for liver stage activity but are also cytotoxic at higher doses. The 8-aminoquinolines (8-AQs) also showed weak activity in this group. While 8-AQs are primarily used for the radical cure of P. vivax malaria, which includes liver-resident hypnozoites, these compounds often show poor activity in vitro as they must be activated by hepatic cytochrome P450 enzymes which are not highly expressed in hepatoma cells^38,39. Several other legacy antimalarials were found inactive in both runs and placed in the third group. Altogether, our results were highly congruent with previous reports on the liver stage activity of these drugs⁴⁰.

We then sought to demonstrate that the FLAR-based LRA could be used for screening compounds libraries in which each well contains a different test compound tested at a single concentration. However, before proceeding, we noted the RLUs being generated in our LRA optimization studies were lower than those obtained in our previous studies⁴¹ and further optimized the protocol to increase the signal. We focused on the HepG2 seed density as the density routinely used in our lab, 1.75 x 10⁴ cells/well in a 384-well microtiter plate format, which is equivalent to 1.61 x 10³ cells/mm² well bottom area, resulted in a complete monolayer immediately after seeding⁴². Given the assay requires one day before infection and two days before the endpoint, we hypothesized infected cells were affected by overcrowding, thereby decreasing the RLU signal. We titrated the number of HepG2 seeded per well and indeed found the seed density affects signal, with a far lower seed density of 5 x 10³ cells/well (equivalent to 459 cells/mm² well bottom area) producing higher RLUs compared to 1.75 x 10⁴ cells/well (one-way ANOVA, F(11,84) = 10.01, p < 0.0001, with Dunnett’s multiple comparisons, p < 0.0001) (Fig. 3A). Additionally, we compared our FLAR with that typically used in the field, Bright-Glo™, in the HepG2 titration experiment over 3 hrs. While Bright-Glo™ exhibited an approximate 3-fold higher signal than FLAR at the first timepoint, Bright-Glo™ signal decreased rapidly (t_{1/2 =}38 min) compared to FLAR (t_1/2 > 3hrs) (Fig. 3B).

We next used the fully optimized LRA assay (using the Freeze/Thaw lysis method, 1x FLAR, and a HepG2 seed density of 5 x 10³ cells/well) to test the Medicines for Malaria Venture Global Health Priority Box (GHPB), an open-source collection of compounds targeting parasite vectors, zoonotic diseases, and drug resistant P. falciparum, at 1 µM^43,44. The GHPB was counter-screened for general cytotoxicity using HepG2 cells cultured in galactose media. This version of cytotoxicity assay is important for detecting mitochondrial inhibitors, as cells cultured in glucose can dispense with mitochondrial respiration and survive on glycolysis alone¹⁵. We detected 8 compounds with > 80% inhibition of P. berghei liver schizonts, which is a relatively high hit rate of 3.3%, but also 38 compounds with > 15% cytotoxicity, which included 2 of the 8 P. berghei liver schizont hits (Fig. 4). To characterize the predictive value of our assays, which requires finding the potency of hit, inactive, and toxic compounds, we picked 35 compounds for confirmation in dose-response assays, including the 6 hits that appeared active (> 80% inhibition against P. berghei liver schizonts) and selective (< 15% inhibition of HepG2) in the primary screens.

Hits were resupplied as powder and tested against P. berghei liver schizonts and HepG2 cells in dose-response from 50 µM—a much higher dose than the primary screen dose of 1 µM—to ensure calculation of potency at doses just higher than the primary screen dose and, therefore, a better understanding of selectivity. All 6 of the resupplied hits that were active and selective in the primary screen (MMV1103183, MMV024825, MMV674132, MMV692630, MMV1266067, and MMV1435700) confirmed to be active and selective in confirmation runs (Fig. 5). An additional three resupplied compounds which were not considered hits in the primary screen (MMV1267536, MMV1804275, and MMV689635) were also active and selective in confirmation runs. Upon further analysis, the EC₅₀ of MMV689635 against P. berghei liver schizonts was just above 1 µM, explaining why they were not also classified as hits from the primary screen. MMV1804275 and MMV1267536, which yielded 66% and 69.1% inhibition of P. berghei liver schizonts in the primary screen, respectively, demonstrate our hit threshold of 80% could be lowered to ensure similar true positives with partial activity in the primary screen are not missed. The remaining 26 resupplied compounds were found either toxic or inactive in dose-response assays. Of the confirmed hits, MMV674132, an imidazopyridazine previously-described as having 44 nM potency against P. falciparum asexual blood stages and 1–3 µM potency against P. falciparum gametocytes⁴⁵, showed the most potency against P. berghei liver schizonts (EC₅₀ = 30.2nM) and only marginal cytotoxicity at doses above 10 µM, resulting in a selectivity index of > 1000 (Fig. 5B).

Lastly, we performed retroactive analyses of how the primary P. berghei screen performed. Using an MOI of only 1.44 x 10³ sporozoites/well we observed RLU’s ranging from 159–370 (x̄ = 266, σ = 51.6) in the DMSO control wells and 0–31 (x̄ = 7.22, σ = 7.32) in the MMV390048 positive control wells. For high-throughput screening purposes, this led to a good coefficient of variance (CV = 19.4), Z’-factor (Z’ = 0.316), and dynamic range (S/N = 36.8). An ROC analysis confirmed the P. berghei assay was perfectly predictive of detecting hits with an EC₅₀ of < 0.333 µM (AUC of 1.0 (95% CI = 1.0–1.0, p < 0.0001) (Fig. 6A). The HepG2 cytotoxicity primary screen was also predictive, with an excellent robust Z-factor (Z’ = 0.733) and ROC AUC of 0.8932 (95% CI = 0.7465–1.000, p = 0.0005) (Fig. 6B). Taken together, these results show FLAR reagent can be used for high-throughput screening in a P. berghei liver schizont LRA with only 1.44 x 10³ sporozoites/well, albeit using more sporozoites will increase the signal and generate higher Z-factors if desired.

Over the past 20 years, several reports describe large antimalarial screening and hit compound development efforts using P. berghei liver stage parasites to characterize liver stage activity^46–53. Resultingly, novel classes of inhibitors with liver stage activity, including M5717¹⁷, cipargamin¹⁹, DSM265²⁰, and MMV390048²⁴, are now in late-stage development or clinical trials. However, given the history of resistance to new antimalarials, the antimalarial development pipeline should continue supporting the discovery and development of new classes against novel targets⁶. While millions of compounds have been tested in P. falciparum blood stage assays, the largest liver stage screen to date was 5 x 10⁵ compounds against luciferase-expressing P. berghei over 18 months using 1603 384-well plates⁵⁴. Following an extensive literature search and review, we could not find an example of an LRA using a non-commercial detection reagent for P. berghei liver stage screening. Conversely, at the time of this report, a search in Pubmed yielded 50 other reports describing implementation of reagents developed by Siebring-van Olst et al.¹² for their LRAs.

Our optimizations occurred in two phases. At first, we used a HepG2 seeding density of 1.75 x 10⁴ cells/well in a 384-well microtiter plate format, which is equivalent to 1.61 x 10³ cells/mm² well bottom area. We chose this number based on our own prior optimizations and other P. berghei liver stage LRAs in a 384-well microtiter plate format^42,49. In the first phase we focused on optimizing reagent concentrations and lysis methods, similar to the approach taken by Siebring-van Olst et al¹². With a working FLAR-based LRA protocol, we then validated the method using legacy and developmental antimalarials tested in dose-response and compared the potency obtained versus that obtained using HCI. We chose to compare our results with HCI as HCI allows for the direct observation and quantification of P. berghei liver schizont growth and is therefore an excellent benchmark⁹. While we obtained nearly identical potency results for the legacy antimalarials using either detection method, we noted the net RLU’s obtained were lower than expected⁴¹. We next performed a second phase of optimization focused on the fundamental element of HepG2 seed density. Interestingly, a much lower seed density of 5 x10³, which is less than a third the density previously used, led to ideal RLU signal intensities. This simple finding could be impactful for the field as P. berghei LRAs performed in 96, 384, and 1536-well microtiter plate formats typically also use a much higher density as we did in our first phase of studies^41,49,55.

We concluded our optimization studies by comparing the performance of our FLAR against a commonly used commercial detection reagent, Bright-Glo™. We found Bright-Glo™ is brighter than our FLAR but does not provide as stable a signal over time. This is not unexpected as the product use guide for Bright-Glo™ states Bright-Glo™ should be used for signal intensity while another Promega product, Steady-Glo™, is less bright but should be used when a longer half-life is needed⁵⁶. For P. berghei liver stage LRA’s, it is possible that Bright-Glo™ is ubiquitously used because only a fraction of the hepatocytes are infected with luciferase-expressing parasites, thus signal amplification could be useful. Conversely, a longer half-life could be important when screening larger libraries, where many microtiter plates could be simultaneously subjected to an endpoint using automated liquid handling and then read in sequence over several hours. Further delving into the workflow and cost of luciferase detection reagents, Bright-Glo™ can be used without first removing media from assay plates. We did not test this approach during our optimization studies because previous reports of P. berghei liver stage LRAs frequently take advantage of a single assay plate to also generate cytotoxicity data by first using a cell viability reporter, reading the plate, dumping the reagents, and then adding luciferase detection reagents. As such, the general workflow for obtaining both the cytotoxicity and efficacy endpoints would be unchanged if using either a commercial product like Bright-Glo™ or FLAR. Because both methods include addition of FLAR to empty plates, only 10 mL of Bright-Glo™ is needed to detect luminescence from a full 96, 384, or 1536-well microtiter plate, while our FLAR protocol was optimized for 20 mL of FLAR to detect luminescence from a similar plate. We calculated that 20mL of FLAR, which is more than enough to run one 96, 384, or 1536-well microtiter plate, costs < $8. Conversely, 10 mL of Bright-Glo™ reagent costs $160, which is nearly 20x more expensive. Ideally, our adaptation of the protocol developed by Siebring-van Olst et al. for P. berghei liver stage assays will increase liver stage screening efficiency for the field.

We found our FLAR was useful for detecting hits in a single-point screen of the GHPB. Similar to past screens of open-source libraries, we noted a large proportion of the library was cytotoxic at 1 µM and therefore unlikely to exhibit parasite-specific activity or be a safe starting point for drug development. Even though we could have used an HCI endpoint or a viability reagent to quantify HepG2 viability in the P. berghei liver stage screen itself, we opted to use our galactose assay in cytotoxicity-dedicated plates for both the primary screen and dose-response confirmation runs. The galactose assay is advantageous because of its ability to detect mitochondrial inhibitors, the lower seed density (2.0 x 10³ cells/well) which increase the dynamic range of the assay, the additional 28 hrs incubation time (72 hr for the galactose cytotoxicity assay versus 44 hr for the P. berghei LRA) to detect slow-acting compounds, and the use of HCI to quantify cytotoxicity phenotypes in otherwise live cells⁵⁷. Of note, unlike using HCI as the endpoint for the P. berghei liver stage assay, the galactose assay uses only Hoechst stain as a marker, which is widely available and inexpensive. In conclusion, we hope the FLAR reagent described in this report can be used by other in the antimalarial drug discovery field and the hits identified from the GHPB can be assessed for further development.

Ethics Approval Animal use protocols were reviewed and approved by the UGA IACUC (A2023 03-018).

Consent for Publication not applicable

Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests The authors have no competing interests to declare.

Funding Financial support provided by the Global Health Innovation Technology Fund (GHIT) (G2023-104R1 to SPM), Medicines for Malaria Venture (RD/15/0022 to SPM), and the National Institutes of Allergy and Infectious Diseases of the National Institutes of Health (1R01AI15329001 to DEK).

Authors’ contributions Conceptualization-GBN, SPM; Data curation-GBN, CAC, OM, SPM; Formal Analysis-GBN, OM, SPM; Funding acquisition-SPM; Investigation-GBN, CAC, AR, OM, SPM; Methodology-GBN, CAC, OM, SPM; Project administration-SPM; Resources-AKP, RS, AE, RC, SPM; Supervision-DEK, SPM; Validation-SPM; Visualization-GBN, SPM; Writing-original draft-GBN, SPM; all authors reviewed and edited the manuscript.

Acknowledgements Monoclonal antibody 13.3 (anti-GAPDH) was obtained from The European Malaria Reagent Repository (http://www.malariaresearch.eu). The imaging data used in this publication was produced in collaboration with the Biomedical Microscopy Core at the University of Georgia, which is supported by the Georgia Research Alliance. Mosquitoes infected with P. berghei were purchased form the Sporocore at UGA. The GHPB and powder of hits were provided by Medicines for Malaria Venture.

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Table 1 is available in the Supplementary Files section.

No competing interests reported.

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Table 1. Preparation of optimized FLAR buffer. Buffer is made immediately before the assay endpoint. A 20 mL volume is sufficient for addition of up to 200 µL per well of a 96-well plate, 50 µL per well of a 384-well plate, or 10 µL per well of a 1536 well plate (with a margin remaining).
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Supplemental Figure 1. 384 well-plate mapping of optimization assay. “Spz” indicates the net number of sporozoites added per well. Aliquotes of FLAR were supplemented with 1x, 2x, 5x, or 10x ATP and D-luciferin. For example, 1x FLAR had 100µM D-luciferin and 125µM ATP, while 2x FLAR had a two-fold higher concentration of D-luciferin and ATP.
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Supplemental Figure 2. Potency data for the MMV390048 control using the luciferase protocol. A) A titration of 500, 1000, or 2000 sporozoites/well (MOI) was tested with the MMV390048 control to see how potency is affected by MOI. Data shown are from a single matching experiment including all three MOIs. B) Dose-response plot of MMV390048 control from validation assays (Fig. 2) using an MOI of 1267 and 1964 sporozoites/well for runs 1 and 2, respectively . Bars represent S.E.M. of replicate wells at each dose.

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Screening the Global Health Priority Box Against Plasmodium berghei Liver Stage Parasites Using an Inexpensive Luciferase Detection Protocol

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Abstract

Figures

Introduction

Materials and Methods

HepG2 Culture

P. berghei Sporozoite Production

FLAR Stock Solutions

Sporozoite Infection for Endpoint Optimization Studies

Cell Lysis and Luciferase Detection Optimization

Infection, Treatment, and Endpoints for Legacy Antimalarial in Dose-Response Plates

HepG2 Seed Density Optimization, Comparison to Bright-Glo™, and Signal Stability

GHPB Screen and Dose-Response Confirmation

Results

Discussion

Declarations

References

Table 1

Additional Declarations

Supplementary Files

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