Qualification of Standard Membrane-Feeding Assay with <em>Plasmodium falciparum</em> Malaria and Potential Improvements for Future Assays

<div><p>Vaccines that interrupt malaria transmission are of increasing interest and a robust functional assay to measure this activity would promote their development by providing a biologically relevant means of evaluating potential vaccine candidates. Therefore, we aimed to qualify the standard membrane-feeding assay (SMFA). The assay measures the transmission-blocking activity of antibodies by feeding cultured <i>P. falciparum</i> gametocytes to <i>Anopheles</i> mosquitoes in the presence of the test antibodies and measuring subsequent mosquito infection. The International Conference on Harmonisation (ICH) Harmonised Tripartite Guideline Q2(R1) details characteristics considered in assay validation. Of these characteristics, we decided to qualify the SMFA for Precision, Linearity, Range and Specificity. The transmission-blocking 4B7 monoclonal antibody was tested over 6 feeding experiments at several concentrations to determine four suitable concentrations that were tested in triplicate in the qualification experiments (3 additional feeds) to evaluate Precision, Linearity and Range. For Specificity, 4B7 was tested in the presence of normal mouse IgG. We determined intra- and inter-assay variability of % inhibition of mean oocyst intensity at each concentration of 4B7 (lower concentrations showed higher variability). We also showed that % inhibition was dependent on 4B7 concentration and the activity is specific to 4B7. Since obtaining empirical data is time-consuming, we generated a model using data from all 9 feeds and simulated the effects of different parameters on final readouts to improve the assay procedure and analytical methods for future studies. For example, we estimated the effect of number of mosquitoes dissected on variability of % inhibition, and simulated the relationship between % inhibition in oocyst intensity and % inhibition of prevalence of infected mosquitos at different mean oocysts in the control. SMFA is one of the few biological assays used in preclinical and early clinical development of transmission-blocking vaccines, and this study strongly supports its further development and application.</p> </div

Increased CD40 Expression Enhances Early STING-Mediated Type I Interferon Response and Host Survival in a Rodent Malaria Model

<div><p>Both type I interferon (IFN-I) and CD40 play a significant role in various infectious diseases, including malaria and autoimmune disorders. CD40 is mostly known to function in adaptive immunity, but previous observations of elevated CD40 levels early after malaria infection of mice led us to investigate its roles in innate IFN-I responses and disease control. Using a <i>Plasmodium yoelii nigeriensis</i> N67 and C57BL/6 mouse model, we showed that infected CD40^-/- mice had reduced STING and serum IFN-β levels day-2 post infection, higher day-4 parasitemia, and earlier deaths. CD40 could greatly enhance STING-stimulated luciferase signals driven by the IFN-β promoter <i>in vitro</i>, which was mediated by increased STING protein levels. The ability of CD40 to influence STING expression was confirmed in CD40^-/- mice after malaria infection. Substitutions at CD40 TRAF binding domains significantly decreased the IFN-β signals and STING protein level, which was likely mediated by changes in STING ubiquitination and degradation. Increased levels of CD40, STING, and ISRE driven luciferase signal in RAW Lucia were observed after phagocytosis of N67-infected red blood cells (iRBCs), stimulation with parasite DNA/RNA, or with selected TLR ligands [LPS, poly(I:C), and Pam3CSK4]. The results suggest stimulation of CD40 expression by parasite materials through TLR signaling pathways, which was further confirmed in bone marrow derived dendritic cells/macrophages (BMDCs/BMDMs) and splenic DCs from CD40^-/-, TLR3^-/- TLR4^-/-, TRIF^-/-, and MyD88^-/- mice after iRBC stimulation or parasite infection. Our data connect several signaling pathways consisting of phagocytosis of iRBCs, recognition of parasite DNA/RNA (possibly GPI) by TLRs, elevated levels of CD40 and STING proteins, increased IFN-I production, and longer host survival time. This study reveals previously unrecognized CD40 function in innate IFN-I responses and protective pathways in infections with malaria strains that induce a strong IFN-I response, which may provide important information for better understanding and management of malaria.</p></div

Sample mean of oocyst counts by proportion of mosquitoes with any infection.

<p>Each point represents one COM. Black line is the fit from the zero-inflated negative binomial model. The blue dotted line is a nonparametric moving window average (specifically, a kernel smoother with a normal kernel with bandwidth 0.5 log₁₀ chosen to be slightly overfit).</p

Dose dependent % inhibition in mean oocyst intensity by 4B7 mAb.

<p>Various concentrations of 4B7 mAbs (ranging from 1 to 375 µg/ml) were tested over 6 independent feeding experiments (Feed 1–6). Different symbols represent data from different feeding experiments.</p

Effect of modifications of assay on the sensitivity of SMFA.

<p>In this simulation, we assumed there were two test samples (T₁ and T₂), and true PIm of T₁ (50 or 70% inhibition compared to control) was higher than the true PIm of T₂ (0, 10, 20, 30, 40 or 50%). Three different dissection conditions were simulated; 1) total of 20 mosquitoes were dissected from a single COM (m = 20), 2) total of 60 from a single COM (m = 60), and 3) total of 60, but from three COM (m = 20×3). In addition, we stimulated either: 1) T₁ and T₂ were tested in the same feeding experiment (SF), or 2) tested in different feeding experiments (DF). We assumed the mean number of oocysts in the control was 20. For each test condition, 10,000 data were generated to calculate the probability of feeds in which T₁ showed higher PIm (i.e., lower mean oocyst number) than that T₂.</p

Effect of mean number of oocysts in the control on the two % inhibitions.

<p>The % inhibition of prevalence (PIp) is plotted against % inhibition in mean oocyst intensity (PIm) at different mean number of oocysts in the control.</p

Repeatability (intra-feed variance) and Intermediate Precision (inter-feed variance) of SMFA.

a<p>Concentration of 4B7 mAb in a feeder [µg/ml].</p>b<p>Intra-feed variance estimates the variability between three PIm values (each one using one test COM and one control COM) where the test samples have the same 4B7 concentration and both PIm are measured on the same feed. We use U-statistics to estimate the intra-feed variance for each of the 3 feeds, as well as to estimate the overall estimate that combines the 3 feeds.</p>c<p>Inter-feed variance is similar to the intra-feed variance, except that the variability is between two PIm values from identically concentrated test samples where one value is measured on one feed and the other value is measured on a second feed. Again we use U-statistics. We give the pairwise estimates and an overall estimate of inter-feed variance.</p

Estimated variances of arithmetic mean and median methods^a.

a<p>Variances were calculated in the condition where 20 mosquitoes from a single COM were dissected.</p>b<p>Concentration of 4B7 mAb in a feeder [µg/ml].</p>c<p>Variance of PIm when calculated using arithmetic mean.</p>d<p>Variance of PIm when calculated using median. The value “n missing” is the number out of 100,000 simulations with median = 0 in the control so that percent inhibition of a test could not be calculated.</p>e<p>Average of variance (SMFA using mean)/variance (SMFA using median) from 100,000 simulations. This many simulations ensures that we have 95% confidence that the estimates of the expected variance ratios are within 0.04 of their true values.</p

Intra- and inter-feed variability in PIm of 4B7 mAb.

<p>Four concentrations (1, 6, 23 and 94 µg/ml) of 4B7 mAb were tested in triplicate in each feed, and three independent feeds were performed (Feed 7, 8 and 9). Since there were 3 COM of negative control and 3 COM of 4B7 mAb at each concentration, 9 different numbers of PIm were calculated (individual dots) at each concentration in each feed. Bar represents the mean of the 9 calculated data.</p

Relationship between mean number of oocysts and the standard deviation.

<p>For each COM, mean number of oocysts and standard deviation were calculated. Data from all COM tested in 9 independent feeding experiments are shown. Different symbols represent data from different feeding experiments and the line represents the best-fit curve from the zero-inflated negative binomial model. The R² value for the fit is 0.94. Gray lines represent 95% confidence intervals calculated using the t-distribution (for the means) or chi square distribution (for the standard deviations).</p