Experimental study of the relationship between Plasmodium gametocyte density and infection success in mosquitoes; implications for the evaluation of malaria transmission-reducing interventions

Abstract

The evaluation of transmission reducing interventions (TRI) to control malaria widely uses membrane feeding assays. In such assays, the intensity of Plasmodium infection in the vector might affect the measured efficacy of the candidates to block transmission. Gametocyte density in the host blood is a determinant of the infection success in the mosquito, however, uncertain estimates of parasite densities and intrinsic characteristics of the infected blood can induce variability. To reduce this variation, a feasible method is to dilute infectious blood samples. We describe the effect of diluting samples of Plasmodium-containing blood samples to allow accurate relative measures of gametocyte densities and their impact on mosquito infectivity and TRI efficacy. Natural Plasmodium falciparum samples were diluted to generate a wide range of parasite densities, and fed to Anopheles coluzzii mosquitoes. This was compared with parallel dilutions conducted on Plasmodium berghei infections. We examined how blood dilution influences the observed blocking activity of anti-Pbs28 monoclonal antibody using the P. berghei/Anopheles stephensi system. In the natural species combination P. falciparum/An. coluzzii, blood dilution using heat-inactivated, infected blood as diluents, revealed positive near linear relationships, between gametocyte densities and oocyst loads in the range tested. A similar relationship was observed in the P. berghei/An. stephensi system when using a similar dilution method. In contrast, diluting infected mice blood with fresh uninfected blood dramatically increases the infectiousness. This suggests that highly infected mice blood contains inhibitory factors or reduced blood moieties, which impede infection and may in turn, lead to misinterpretation when comparing individual TRI evaluation assays. In the lab system, the transmission blocking activity of an antibody specific for Pbs28 was confirmed to be density-dependent. This highlights the need to carefully interpret evaluations of TRI candidates, regarding gametocyte densities in the P. berghei/An. stephensi system.

Transmission-blocking activity is determined by transmission-reducing activity and number of control oocysts in Plasmodium falciparum standard membrane-feeding assay

“…A preceding study with anti-Pbs28 mAb using P. berghei parasites has shown that TBA level decreased as m o -contl increased, while there was no correlation between TRA and m o -contl [27]. Our 4B7 mAb data tested with P. falciparum parasites also reached the same conclusion (Fig.…”

Modulation of transmission success of Plasmodium falciparum gametocytes (sexual stages) in various species of Anopheles by erythrocytic asexual stage parasites

“…In all the future studies we fixed gametocyte concentration at 0.3% and varied other components. A similar positive association between gametocyte density and mosquito infection has been reported in many previous published studies using murine and human malaria parasites (both lab adapted and field isolates) in different anopheline species (Carter and Graves, 1988; Da et al, 2015; Dawes et al, 2009; Drakeley et al, 1999; Poudel et al, 2008; Sinden et al, 2007). Apart from the actual number of gametocytes, maturity and sex ratios of the gametocytes and the presence of natural immune factors can also influence the outcome of infection in the mosquitoes.…”

Estimating the effects of variation in viremia on mosquito susceptibility, infectiousness, and R0 of Zika in Aedes aegypti

“…Mosquito vectors are often exposed to hosts that individually vary in pathogen loads, which can result in variation in the proportion of the mosquito population that becomes infectious [15, 36]. To date, only a few studies have explored how viral concentration impacts measures of vector competence for ZIKV [16–18], and no studies have explicitly linked this source of variation to metrics of transmission risk.…”