Using a SYBR Green-based quantitative PCR method to quantify the fold-change between treated and untreated samples
Percent proliferation is the standard RSA measurement to determine whether a parasite is artemisinin resistant or sensitive. This is calculated by dividing the percent parasitemia in the treated (DHA) sample over the percent parasitemia in the untreated (DMSO) sample. Parasitemia is determined either by counting the number of viable and nonviable parasites using blood smears and microscopy or by flow cytometry. Determining parasitemia with microscopy is cost effective and convenient but is also highly variable and time-consuming. Flow cytometry is typically very accurate; however, the process must be begun at upon reaching a timepoint, adding a substantial time investment at the point of sampling. To find another measurement of parasitemia that could be automated and have less variability, qPCR on parasite genomic DNA was tested. A standard curve of percent parasitemia (as measured by flow cytometry) shows excellent inverse correlation with Ct values as measured by qPCR (Figure 1). To quantify the difference between treated and untreated final RSA samples, fold change (2ΔCt) was calculated according to equation 1.
RSA readout at 120 h provides superior differentiation between sensitive and resistant isolates
The standard RSA determines parasite viability at 72 h after drug treatment. However, a common problem in the final readout (using either microscopy, flow cytometry, or qPCR) is the difficulty in differentiating between pyknotic (nonviable) parasites and viable parasites 72 h after drug treatment. It is also difficult to measure viable parasitemia when it can be as low as 0.01% (or even 0% in some cases), especially when measuring ART sensitive parasites (22). To address these issues, the time to readout was extended by an additional intraerythrocytic development cycle (48 h). This extension was added to both allow parasites an additional expansion cycle, creating larger differences to distinguish resistant and sensitive isolates, and to allow erythrocytes to clear pyknotic parasites. This additional cycle provides a much greater separation between resistance and sensitive parasite isolates (Figure 2).
Assay set-up conditions have a substantial impact on RSA outcomes
The RSA is a growth assay targeted at a very narrow window of the parasite intraerythrocytic development cycle. In order to maximize the precision of the assay, the growth and the timing of the target window were carefully optimized. First, as it has been established that growth rates can vary based on parasitemia, the effect of varying starting parasitemias on RSA outcome was observed (23). RSA was performed on three parasite isolates (3D7, 1337, and 4673) at varying starting parasitemias as determined by a microscopist, and samples were collected at 72h and 120h (Additional file 2A and 2B, respectively). For the three parasite isolates tested, 3D7 was the ART sensitive control and 1337 and 4673 were two ART resistant parasite isolates as determined by their PC1/2 values (1337 PC1/2 = 7.84 and 4673 PC1/2 = 5.34). The 0.25% starting parasitemia showed the most distinguishable phenotype between the ART sensitive 3D7 control and the two ART resistant isolates at 120 h (Additional file 2B). It was noted internally that determinations of parasitemia by microscopy varied widely and underestimated parasitemia compared to flow cytometry, likely due to the difficulty of correctly identifying new invasions. A comparison of RSA results from isolates set up at 0.25% parasitemia determined by microscopy and 0.5% parasitemia determined by flow cytometry showed no difference between the two (Additional file 3). As a result, in subsequent set-ups starting parasitemia was determined by flow cytometry and was normalized to 0.5% parasitemia.
A key factor in the RSA is applying the drug treatment in the tight 0-3 h window of the parasite life cycle that can differentiate ART resistant parasites from ART sensitive parasites. Therefore, the time from Percoll synchronization to drug treatment was also varied to find the optimal time for drug treatment. The same three parasite isolates, (3D7, 1337, and 4673), were set up and treated with 700nM DHA 4 h, 6h, 8 h, or 10 h after Percoll synchronization and samples collected at 72 h and 120 h post-drug treatment (Additional file 2C and 2D, respectively). All parasites were set up at a starting parasitemia of 0.5% as measured by flow cytometry. The time that resulted in the most consistent and distinguishable phenotypes between the ART sensitive and resistant isolates was 6 h post-Percoll synchronization. Controlling these factors resulted in a more consistent and reproducible RSA phenotype.
Defining the eRRSA as an improvement over the standard RSA
Based on the previously described optimizations, the eRRSA is defined as a single layer Percoll synchronization, flow cytometry measurement of parasite parasitemia and stage prior to assay set-up, 700nM DHA treatment of 200ul of parasites at 2% hematocrit and 0.5% parasitemia in 96-well plates that are set up at 6 h post-Percoll synchronization, drug washed off 6 h after application, and samples for qPCR readout collected at 120 h post-drug treatment (Additional file 4). This protocol provides the most consistent and high-throughput results. These modifications made to the standard RSA are a new in vitro ART resistance phenotyping method: the Extended Ring-stage Recovery assay (eRRSA).
eRRSA correlates better with PC1/2 than RSA
The RSA was introduced as an in vitro method that better captures the gold standard for in vivo ART resistance, PC1/2, than the traditional IC50. For a new assay to be relevant, it should perform at least comparably to the existing standard. Therefore, the eRRSA was used to assay 15 isolates from Southeast Asia with varying known PC1/2 and kelch13 mutations collected between 2008 and 2012 (Table 1). We collected at least three biological replicates (each with three technical replicates) for each isolate and collected samples at 72 h and 120 h post-drug treatment and compared the viability of treated and untreated parasites at each stage.
The fold change data was then compared to PC1/2: at the 72 h timepoint across 15 isolates, the eRRSA has a Spearman correlation coefficient of -0.6071 (Figure 3A). This is comparable to other RSA correlations in the field, showing that the improvements made to the RSA protocol do not significantly affect the outcome while increasing efficiency and ease of the assay (8, 17). The 120 h correlations, however, improved Spearman correlation between fold change and PC1/2 to -0.8393 (Figure 3B).