The parasite that causes malaria, named Plasmodium falciparum, has a life cycle that involves both humans and mosquitoes. Starting in the saliva of female Anopheles mosquitoes, it enters a person’s bloodstream when the insects feed. It then moves to the person’s liver, where it infects liver cells and matures into a stage known as schizonts. The schizonts then divide to form thousands of so-called merozoites, which burst out of the liver cells and into the bloodstream. The merozoites infect red blood cells, producing more schizonts and yet more merozoites, which continue the infection.

To complete its life cycle, the parasite must return to a mosquito. Some of the parasites in the person’s blood transform into male and female cells called gametocytes that are taken up by a mosquito when it feeds on that person. Inside the mosquito, male and female parasites reproduce to create the next generation of parasites. The new parasites then move to the mosquito’s salivary glands, ready to begin another infection. Stopping the parasite being transmitted from humans to mosquitoes will stop the spread of malaria in the population. Yet it has proven difficult to study this part of the life cycle from natural infections.

Here, Reuling et al. report a new method for generating gametocytes in human volunteers that will enable closer study of the biology of malaria transmission. The method is developed using the Controlled Human Malaria Infection (CHMI) model. Healthy volunteers without a history of malaria are bitten by mosquitoes infected with malaria parasites. Shortly afterwards, the volunteers are given a drug treatment to control and reduce their symptoms. The gametocytes form during this phase of the infection. At the end of the experiment, all the volunteers receive a final treatment that completely cures the infection.

Reuling et al. recruited 16 volunteers and assigned them to four groups at random. Each group received a different drug regime. Roughly a week after the mosquito bites, all participants showed malaria parasites in their blood, and between 8.5 and 12 days later, mature gametocytes started to appear. This early appearance suggests that the parasites start to transform into gametocytes when they first emerge from the liver. The experiment also revealed that female gametocytes stay in the blood for a longer period than their male counterparts.

These results are proof of principle for a new way to investigate malaria infection. The new model provides a controlled method for studying P. falciparum gametocytes in people. In the future, it could help to test the impact of drugs and vaccines on gametocytes. Understanding more about these parasites’ biology could lead to treatments that block malaria transmission.

Malaria, a disease caused by Plasmodium parasites, continues to be a public health burden. Despite a reduction in the malaria case incidence of ~40%, and mortality by 62% over the last decade, malaria caused ~429,000 deaths in 2015 (World Health Organization, 2016). Apart from the direct health implications, malaria is a substantial contributor to ongoing poverty in affected countries. Recently, the spread of artemisinin-resistant parasites has emerged as a global health concern. Both the recent gains in malaria control and concerns about artemisinin resistance have stimulated programs to eliminate malaria (World Health Organization, 2016). Novel interventions may support malaria elimination efforts in endemic settings (Griffin et al., 2010) that are further dependent on political and financial commitments to maximize coverage with currently available interventions and improve surveillance systems to optimize disease notification and treatment (Moonen et al., 2010).

A major challenge to eliminating malaria is its highly efficient transmission by Anopheles mosquitoes. Transmission to mosquitoes starts when a small proportion of asexual parasites commit to form male and female gametocytes. It is currently unclear what stimulates gametocyte commitment and when gametocyte commitment first occurs (Nilsson et al., 2015). Upon commitment, maturation of gametocytes takes place predominantly in the bone marrow, and requires 7 days (range 4–12) of development. (Eichner et al., 2001) Subsequently, mature gametocytes (parasites that are not associated with clinical disease) appear in the peripheral blood, where they may circulate for an average of 6 days (Eichner et al., 2001; Bousema et al., 2010). During this period, blood-feeding Anophelines may ingest gametocytes where, after a sporogonic development phase, sporozoites reach the mosquito salivary gland rendering the mosquito infectious to humans upon its next bite. Early work based on the microscopic evaluation of experimental P. falciparum infection (malariatherapy) studies reported that gametocytes may make their appearance in small numbers around 10 days following the first day of fever (Shute and Maryon, 1951; Ciuca et al., 1937).

The renewed focus on malaria elimination requires a thorough understanding of malaria transmission dynamics - when mature male and female gametocytes are first produced upon infection and how long they circulate in peripheral blood (Sinden, 2017). These parameters are difficult to measure in naturally acquired infections where frequent super-infections, immunity and other factors dictate parasite and gametocyte dynamics (Bousema and Drakeley, 2011). Interventions that specifically aim to reduce gametocyte development, circulation time or infectivity are highly desirable in the context of malaria elimination and require effective models for the early clinical evaluation.

The controlled human malaria infection (CHMI) model allows the induction of parasitemia under highly standardized conditions and plays an important role in the assessment of safety and efficacy of novel antimalarial drugs and vaccines (Sauerwein et al., 2011). Preliminary evidence for the induction of female gametocytes in CHMI studies with blood stage inoculum was recently demonstrated using piperaquine monotherapy (Pasay et al., 2016; Farid et al., 2017).

In this study, we aimed to develop a CHMI transmission model to induce gametocyte carriage after mosquito bite infection. The primary objective of the current trial was to safely induce gametocytemia in study participants by the use of different (sub)curative drug regimens based on sulfadoxine-pyrimethamine (Bousema and Drakeley, 2011; Butcher, 1997) and piperaquine (Adjalley et al., 2011).

From a total of 49 screened candidate participants, 16 volunteers were included in a first cohort and randomly assigned to four study arms prior to challenge (Figure 1). After observed transient liver enzyme elevations in the first cohort, the study was temporarily put on hold and the already initiated infections in the second cohort of 13 participants were abrogated by curative treatment on day 3 post challenge. The hold was lifted after reviewing safety data. Participants from the first cohort completed all study visits, and form the basis of the current manuscript; their baseline characteristics are shown in Table 1. After exposure to bites of a standard protocol of five P. falciparum infected mosquitoes, all participants developed parasitemia on days 6.5–12 post-challenge; peak parasite densities ranged from 1050 to 63113 Pf/mL (Figure 2; Figure 2—figure supplement 1; Table 2; Supplementary file 1). Due to asexual recrudescence in seven of the eight participants after a subcurative treatment (T1) with LD-PIP, a curative treatment (T2) had to be administered before day 21 post challenge. The median period between T1 and T2 was 9.1 (range of 7.7–11.7), 10.0 (range of 9.2–10.2), 4.7 (range of 2–10.7), and 2.5 (range of 1.5–5.0) days for study arms LD-SP/SP, LD-SP/PIP, LD-PIP/PIP, and LD-PIP/SP, respectively. In participants receiving a subcurative LD-SP as T1, no recrudescent infection occurred and T2 was initiated on day 21 per protocol. One participant from treatment arm LD-PIP/PIP developed asexual recrudescence after T2, and received end treatment with atovaquone/proguanil on day 36. The remaining participants did not develop recrudescent infections after T2, and were treated with atovaquone/proguanil on day 42 as per protocol.

Figure 1

Download asset Open asset

Figure 2 with 1 supplement see all

Download asset Open asset

All participants also developed gametocytemia as determined by Pfs25 qRT-PCR (Figure 2; Figure 3A; Figure 2—figure supplement 1). Gametocytes were first detected 8.5–12 days after the initial peak of asexual parasites with no statistically significant difference in time to gametocyte appearance between study arms (p=0.26) (Table 2). The median peak density of gametocytes was 83 gametocytes/mL (range 11–1285) when all study participants were considered. Peak gametocyte densities were higher in the study arm randomised to LD-PIP/SP, with a median of 627 gametocytes/mL (range of 199–1285), compared to 38 gametocytes/mL (range of 11–368), 30 gametocytes/mL (range of 13–101), 83 gametocytes/mL (range of 46–99), for arms LD-SP/SP, LD-SP/PIP, and LD-PIP/PIP, respectively (Figure 2; Figure 2—figure supplement 1; Table 2).

Figure 3

Download asset Open asset

Thirteen (81%, 13/16) participants showed gametocytes on at least 5 consecutive days. The mean number of consecutive gametocyte-positive days was 24.5 (range of 17–25) for the LD-PIP/SP arm and was higher than for other arms (Table 2; Figure 2). Using multi-level logistic regression (random effect for within-group variation), we estimated that the average proportion of days that individuals tested positive for gametocytes was 27.4% (LD-SP/SP), 35.9% (LD-SP/PIP), 51.4% (LD-PIP/PIP), and 48.3% (LD-PIP/SP) (Table 2). The LD-PIP/PIP and LD-PIP/SP arms (i.e. those receiving ‘low dose PIP’) each had significantly higher average proportions of gametocyte-positive days than both arms LD-SP/SP and LD-SP/PIP (posterior probability 90.8% and 86.1%, respectively; 81.1% joint probability of arms LD-PIP/PIP and LD-PIP/SP both being higher than both LD-SP/SP and LD-SP/PIP). Furthermore, the area under the curve (AUC) for gametocyte density showed a statistically significant difference between arms (p=0.04). The LD-PIP/SP arm had a significantly higher gametocyte load (area under the curve) than each of the other three treatment arms (94.4% posterior probability of being the highest; Figure 3B). After correction for the asexual AUC, the probabilities of the gametocyte AUC in the LD-PIP/SP arm being higher than the other three decreased to 97.2%, 96.3%, and 96.2% (from 99,1%, 98.9%, and 95.4%), and the probability of LD-PIP/SP being higher than all other study arms decreased to 94.0%.

Both female and male gametocytes were detected in 14/16 (88%) participants (Figure 4; Figure 4—figure supplement 1). Gametocyte sex-ratio’s and circulation times have to be interpreted with caution since they rely on two separate qRT-PCR assays with differences in assay sensitivity (Figure 5; Supplementary file 2, 3). On average 2.5 times as many female gametocytes were observed compared to male gametocytes per measured time-point (Figure 4; mean ratio 2.5 (SD = 2.5)). Combining all treatment arms, the best estimate of gametocyte half-life was 5.1 days (95% CI 4.1–6.1) for female gametocytes and 2.7 days (95% CI 1.5–3.9) for male gametocytes (Figure 4—figure supplement 2).

Figure 4 with 2 supplements see all

Download asset Open asset

Figure 5 with 2 supplements see all

Download asset Open asset

Gametocytes are produced from their asexual progenitors, and hence asexual parasite kinetics and gametocyte kinetics are related. The AUC of asexual parasitemia was statistically significantly associated with the AUC of gametocytemia (r² = 0.31, p=0.026), as shown in Figure 3C. The mean time-window between the first asexual parasites and the first appearance of gametocytes was 10.6 (SD = 0.65) days, see Table 2. Membrane feeding experiments were performed as an exploratory objective, and confirmed infectivity of gametocytes in three mosquitoes from three study arms on days 25 (LD-PIP/SP and LD-SP/SP arms) and 31 (LD-SP/PIP arm) post-infection. Mean gametocyte densities at those time-points were 106 gametocytes/mL (SD = 175), and 28 gametocytes/mL (SD = 47), respectively. Expressed as a proportion of all examined mosquitoes, 0.0002% (3/14400) of mosquitoes became infected in these exploratory assessments. Possible and probable related adverse events after challenge infection are shown in Figure 6 and Table 3. The most frequently reported adverse events were fatigue, malaise, headache, fever, nausea, and chills. Grade three adverse events were reported in 14/16 (88%) participants, and were predominated by headache (n = 8), chills (n = 6), and nausea (n = 5). All possible and probable related adverse events resolved by the end of study. No serious adverse events occurred. The median number of adverse events was 20.5 per individual; the median number of adverse events with a grade three severity score was 1.5 per individual. There was no evidence for a difference between study arms in the occurrence of adverse events (p=0.49) or grade three adverse events (p=0.28).

Figure 6 with 1 supplement see all

Download asset Open asset

Laboratory abnormalities during the study are shown in Table 4. Most prevalent abnormalities were elevated transaminases (ALT/AST) (n = 16), decreased lymphocytes (n = 15), decreased neutrophils (n = 13), and decreased platelets (n = 12). The only grade three laboratory abnormalities were elevated ALT (n = 8), and elevated AST (n = 7). 16/16 (100%) volunteers showed mild to severe ALT/AST elevations. 5/16 (31%) mild (grade 1); 3/16 (19%) moderate (grade 2), and 8/16 (50%) severe (grade 3) (up to 25 x ULN) ALT/AST elevations. These derangements were transient, and returned to baseline values within the normal range before the end of the study. A detailed overview of these liver function test derangements can be found in the supporting information (Figure 6—figure supplement 1). These unexpected safety findings were reported to the Safety Monitoring Committee (SMC) and CCMO, and thoroughly reviewed.

Here, we present a CHMI model to induce mature gametocytes after mosquito bite infection in malaria-naive study participants. The timing of the first appearance of gametocytes suggests that a fraction of the first wave of asexual parasites commit to the production of male and female gametocytes. With the use of antimalarial drugs that attenuates asexual stage infections but leave (developing) gametocytes unaffected, we determined biologically plausible half-lives of male and female gametocytes, and show preliminary evidence of the potential of this model to complete the lifecycle of malaria in mosquito feeding assays.

Malaria elimination efforts require a thorough understanding of the transmissibility of infections. Gametocyte commitment occurs for a fraction of asexual parasites under regulation of the transcription factor AP2-G with the entire progeny of a sexually committed schizont forming either male or female gametocytes (Kafsack et al., 2014). Our findings, based on novel sex-specific gametocyte qRT-PCR, confirm earlier work from malariatherapy studies where gametocytes were first detected by microscopy at 9–11 days after asexual parasites (Ciuca et al., 1937; Shute and Maryon, 1951). These data indicate very early gametocyte commitment and are in line with our earlier observations that Pfs16 mRNA, the earliest gametocyte transcript, is detectable at the moment of peak parasitemia in CHMI models (Schneider et al., 2004). This timing is highly relevant for understanding gametocyte transmission biology. The circulation of mature gametocytes has not been reported in previous CHMI trials using curative regimens of chloroquine, artemether-lumefantrine, or atovaqoune-proguanil, and our data illustrate the differential impact of antimalarial drugs on developing gametocytes. Once treatment is initiated, gametocyte production ceases abruptly (in the case of artemisinins), remains unaffected, or may even be stimulated under drug pressure as suggested for sulfadoxine-pyrimethamine and piperaquine (Bousema and Drakeley, 2011; Butcher, 1997; Adjalley et al., 2011). In our study, we aimed for a protracted low density of asexual parasitemia demonstrating that early abrogation of asexual infections by both sulfadoxine-pyrimethamine and piperaquine permits successful mature gametocyte development. SP has long been associated with a rapid appearance of gametocytes that is too early to be explained by de novo gametocyte production upon drug pressure and has thus been hypothesized to reflect an efflux of sequestered gametocytes upon treatment (Butcher, 1997). Evidence for the permissiveness of piperaquine to (developing) gametocytes is more recent (Pasay et al., 2016; Farid et al., 2017; Adjalley et al., 2011). In the current study, group sizes are limited and comparisons between treatment arms have to be interpreted with caution. CHMI studies are logistically challenging and the number of volunteers that can be monitored to ensure participant safety is an important consideration when defining the study size. Our sample size calculation was based on the optimistic assumption that the vast majority of volunteers would develop mature gametocytes; an assumption that was supported by the current data. With our limited study size, our findings indicate that none of the study drugs prevented the appearance of gametocytes after treatment, thereby suggesting limited or no effect of PIP and SP on developing or mature gametocytes (Bolscher et al., 2015). We hypothesized that slow acting drugs may promote the development of gametocytes (Méndez et al., 2002), potentially via microvesicles that are derived from infected erythrocytes (Nilsson et al., 2015) and differences between drug regimens in the rate at which asexual parasites are cleared upon T1 and T2 would result in different gametocyte dynamics. Although our findings indicate highest gametocyte concentrations in the LD-PIP/SP arm, more observations and thus additional studies are needed to allow the construction of a model that allows a quantification of gametocyte commitment at different time-points during the study (e.g. prior to T1, during the phase of parasite recrudescence and following T2). One hypothesis would be similar gametocyte commitment in all arms after T1 but a more rapid release of gametocytes that accumulated in the bone marrow between T1 and T2.

We present the novel evidence that both male and female gametocytes appear early, upon infection. Our findings suggest an earlier appearance of female gametocytes (18.8 days (SD 1.8) compared to male gametocytes 20.3 days (SD 1. 2)) and a longer circulation time of female gametocytes that is in line with previous estimates from naturally infected individuals (Bousema et al., 2010; Ciuca et al., 1937). Whilst both male and female gametocytes are consistently detected at densities of 0.1 gametocyte/µL (Stone et al., 2017), the highly abundant Pfs25 mRNA makes the female gametocyte qRT-PCR more sensitive than the male PfMGET qRT-PCR. Differences in gametocyte dynamics between male and female gametocytes should therefore be interpreted with caution. Gametocyte densities remained below the threshold of detection by microscopy throughout the study period and were strongly associated with the preceding densities of the asexual progenitors. Participants in the LD-PIP/SP study arm showed the highest gametocytes densities, and a mean female/male sex ratio of 4.1 (SD = 5.1), in line with gametocyte sex-ratios in natural infections (~3 to 5 females to one male) (Ciuca et al., 1937; Delves et al., 2013). We confirmed the infectivity of gametocytes in three mosquitoes from three study arms. The very low rate of infected mosquito corroborates observations from naturally acquired infections where mosquito infection becomes highly unlikely below 1000–10,000 gametocytes/mL (Gonçalves et al., 2016). The sporadic mosquito infections thus demonstrate that mature gametocytes in sex-ratios supportive of mosquito infections can be achieved in CHMI transmission models. Studies on the evaluation of TBIs will need a further optimized protocol aimed to achieve higher gametocyte densities by increasing duration and load of the asexual parasite burden. For the evaluation of gametocytocidal interventions in the CHMI transmission model, gametocyte densities should be sufficiently high to quantify an intervention-associated reduction in gametocyte appearance or gametocyte half-life. For the evaluation of interventions that reduce the transmissibility of gametocytes, higher mosquito infections should be achieved at proportions that allow the detection of meaningful reductions in mosquito infection rates in experimental arms. Low infectivity in membrane feeding assays may be overcome by achievement of higher gametocyte densities in the model, and the use of gametocyte concentration methods (Reuling et al., 2017), or by direct skin feeding assays (Bousema et al., 2012).

In line with recent findings, we observed recrudescent infections in 7/8 participants treated with LD-PIP (Pasay et al., 2016). Recrudescent infections were not observed in arms that first received LD-SP, suggesting that this dose, although 1/3 of the standard curative dose of sulfadoxine-pyrimethamine, is curative at asexual parasite densities observed in our participants. It has been hypothesized that the prolonged parasitemia under drug pressure increases gametocyte commitment (WWARN Gametocyte Study Group, 2016). The duration of parasite multiplication between T1 and T2 was relatively short in this study (2–5 days) for subjects with recrudescent infections, and the contribution of drug pressure may thus have been limited. The current findings suggest that further lowering the SP dose may be considered to prolong asexual parasite exposure.

The liver enzyme elevations found in our study led to a structured risk analysis, and review by independent experts. Transient, asymptomatic liver function test (LFT) derangements have been reported in volunteers in previous CHMI studies, and are likely to be related to the asexual stage parasitemia, and subsequent treatment.

Detailed studies on gametocyte biology and dynamics, and the early development of novel drugs and vaccines that target malaria transmission (TBIs) are currently restricted to in vitro assays, such as drug sensitivity assays, and standard membrane feeding assays (SMFA) (Bousema and Drakeley, 2011; Wells et al., 2009). Recently, a humanized mice model has been developed to investigate P. falciparum sexual commitment that could, therefore, bridge in vitro assays to in vivo animal studies that take into account drug metabolism and gametocyte sequestration (Duffier et al., 2016). Also, an experimental Plasmodium vivax transmission model in human has been reported (Griffin et al., 2016). However, mechanisms underlying P. falciparum gametocytogenesis and dynamics have never been addressed in a controlled clean system in humans.

Here, we present a novel CHMI transmission model for P. falciparum that can be used to study gametocyte biology and dynamics providing novel insights and tools in malaria transmission and elimination efforts. The dynamics of gametocyte commitment, maturation, sex ratio, and sequestration found in our model reflect parasite dynamics found in naturally acquired infections, although parasite densities are much lower than in many endemic settings. This model can be used to evaluate the effect of drugs and vaccines on gametocyte dynamics and sex ratios. With its current performance, the CHMI transmission model may allow testing of vaccination strategies that reduce the production of gametocytes from their asexual progenitors or accelerate their clearance from the blood stream (Stone et al., 2016), and the testing of gametocytocidal drugs (White, 2013). To allow testing of sterilizing effect of drugs on circulating gametocytes (White et al., 2014) or the effect of antibodies that interfere with gametocyte fertilisation inside the mosquito gut (Stone et al., 2016), the model needs to be optimized to achieve considerably higher mosquito infection rates. The current work lays the foundation for fulfilling the critical unmet need to evaluate transmission-blocking interventions against falciparum malaria for downstream selection and clinical development.

1. 1. Reuling IJ
   2. Bousema T
   3. Sauerwein RW

   (2017) Available at Dryad Digital Repository under a CC0 Public Domain Dedication

   Data from: Induction of Plasmodium falciparum gametocytemia in the Controlled Human Malaria Infection model: a randomised trial comparing four antimalarial drug regimens.

   https://doi.org/10.5061/dryad.60h41

1. 1. Adjalley SH
   2. Johnston GL
   3. Li T
   4. Eastman RT
   5. Ekland EH
   6. Eappen AG
   7. Richman A
   8. Sim BK
   9. Lee MC
   10. Hoffman SL
   11. Fidock DA

   (2011) Quantitative assessment of Plasmodium falciparum sexual development reveals potent transmission-blocking activity by methylene blue

   PNAS 108:E1214–E1223.

   https://doi.org/10.1073/pnas.1112037108

   • PubMed
   • Google Scholar
2. 1. Bolscher JM
   2. Koolen KM
   3. van Gemert GJ
   4. van de Vegte-Bolmer MG
   5. Bousema T
   6. Leroy D
   7. Sauerwein RW
   8. Dechering KJ

   (2015) A combination of new screening assays for prioritization of transmission-blocking antimalarials reveals distinct dynamics of marketed and experimental drugs

   Journal of Antimicrobial Chemotherapy 70:1357–1366.

   https://doi.org/10.1093/jac/dkv003

   • PubMed
   • Google Scholar
3. 1. Bousema T
   2. Churcher TS
   3. Morlais I
   4. Dinglasan RR

   (2013) Can field-based mosquito feeding assays be used for evaluating transmission-blocking interventions?

   Trends in Parasitology 29:53–59.

   https://doi.org/10.1016/j.pt.2012.11.004

   • PubMed
   • Google Scholar
4. 1. Bousema T
   2. Dinglasan RR
   3. Morlais I
   4. Gouagna LC
   5. van Warmerdam T
   6. Awono-Ambene PH
   7. Bonnet S
   8. Diallo M
   9. Coulibaly M
   10. Tchuinkam T
   11. Mulder B
   12. Targett G
   13. Drakeley C
   14. Sutherland C
   15. Robert V
   16. Doumbo O
   17. Touré Y
   18. Graves PM
   19. Roeffen W
   20. Sauerwein R
   21. Birkett A
   22. Locke E
   23. Morin M
   24. Wu Y
   25. Churcher TS

   (2012) Mosquito feeding assays to determine the infectiousness of naturally infected Plasmodium falciparum gametocyte carriers

   PLoS One 7:e42821.

   https://doi.org/10.1371/journal.pone.0042821

   • PubMed
   • Google Scholar
5. 1. Bousema T
   2. Drakeley C

   (2011) Epidemiology and infectivity of Plasmodium falciparum and Plasmodium vivax gametocytes in relation to malaria control and elimination

   Clinical Microbiology Reviews 24:377–410.

   https://doi.org/10.1128/CMR.00051-10

   • PubMed
   • Google Scholar
6. 1. Bousema T
   2. Okell L
   3. Shekalaghe S
   4. Griffin JT
   5. Omar S
   6. Sawa P
   7. Sutherland C
   8. Sauerwein R
   9. Ghani AC
   10. Drakeley C

   (2010) Revisiting the circulation time of Plasmodium falciparum gametocytes: molecular detection methods to estimate the duration of gametocyte carriage and the effect of gametocytocidal drugs

   Malaria Journal 9:136.

   https://doi.org/10.1186/1475-2875-9-136

   • PubMed
   • Google Scholar
7. 1. Butcher GA

   (1997) Antimalarial drugs and the mosquito transmission of Plasmodium

   International Journal for Parasitology 27:975–987.

   https://doi.org/10.1016/S0020-7519(97)00079-9

   • PubMed
   • Google Scholar
8. 1. Cheng Q
   2. Lawrence G
   3. Reed C
   4. Stowers A
   5. Ranford-Cartwright L
   6. Creasey A
   7. Carter R
   8. Saul A

   (1997) Measurement of Plasmodium falciparum growth rates in vivo: a test of malaria vaccines

   The American Journal of Tropical Medicine and Hygiene 57:495–500.

   https://doi.org/10.4269/ajtmh.1997.57.495

   • PubMed
   • Google Scholar
9. Book

   1. Ciuca MBL
   2. Chearescu M
   3. Lavrinenko N

   (1937)

   Contribution À L’étude De L’infection Expérimentale Au Plasmodium Falciparum

   Hamburg: Festchrift Institute Bernard Nocht.

   • Google Scholar
10. 1. Delves MJ
    2. Ruecker A
    3. Straschil U
    4. Lelièvre J
    5. Marques S
    6. López-Barragán MJ
    7. Herreros E
    8. Sinden RE

    (2013) Male and female Plasmodium falciparum mature gametocytes show different responses to antimalarial drugs

    Antimicrobial Agents and Chemotherapy 57:3268–3274.

    https://doi.org/10.1128/AAC.00325-13

    • PubMed
    • Google Scholar
11. 1. Duffier Y
    2. Lorthiois A
    3. Cisteró P
    4. Dupuy F
    5. Jouvion G
    6. Fiette L
    7. Mazier D
    8. Mayor A
    9. Lavazec C
    10. Moreno Sabater A

    (2016) A humanized mouse model for sequestration of Plasmodium falciparum sexual stages and in vivo evaluation of gametocytidal drugs

    Scientific Reports 6:35025.

    https://doi.org/10.1038/srep35025

    • PubMed
    • Google Scholar
12. 1. Eichner M
    2. Diebner HH
    3. Molineaux L
    4. Collins WE
    5. Jeffery GM
    6. Dietz K

    (2001) Genesis, sequestration and survival of Plasmodium falciparum gametocytes: parameter estimates from fitting a model to malariatherapy data

    Transactions of the Royal Society of Tropical Medicine and Hygiene 95:497–501.

    https://doi.org/10.1016/S0035-9203(01)90016-1

    • PubMed
    • Google Scholar
13. 1. Farid R
    2. Dixon MW
    3. Tilley L
    4. McCarthy JS

    (2017) Initiation of gametocytogenesis at very low parasite density in Plasmodium falciparum infection

    The Journal of Infectious Diseases 215:1167–1174.

    https://doi.org/10.1093/infdis/jix035

    • PubMed
    • Google Scholar
14. 1. Gonçalves BP
    2. Drakeley C
    3. Bousema T

    (2016) Infectivity of microscopic and submicroscopic malaria parasite infections in areas of low malaria endemicity

    Journal of Infectious Diseases 213:1516–1517.

    https://doi.org/10.1093/infdis/jiw044

    • PubMed
    • Google Scholar
15. 1. Graumans W
    2. Tadesse FG
    3. Andolina C
    4. van Gemert GJ
    5. Teelen K
    6. Lanke K
    7. Gadisa E
    8. Yewhalaw D
    9. van de Vegte-Bolmer M
    10. Siebelink-Stoter R
    11. Reuling I
    12. Sauerwein R
    13. Bousema T

    (2017) Semi-high-throughput detection of Plasmodium falciparum and Plasmodium vivax oocysts in mosquitoes using bead-beating followed by circumsporozoite ELISA and quantitative PCR

    Malaria Journal 16:356.

    https://doi.org/10.1186/s12936-017-2011-9

    • PubMed
    • Google Scholar
16. 1. Griffin JT
    2. Hollingsworth TD
    3. Okell LC
    4. Churcher TS
    5. White M
    6. Hinsley W
    7. Bousema T
    8. Drakeley CJ
    9. Ferguson NM
    10. Basáñez MG
    11. Ghani AC

    (2010) Reducing Plasmodium falciparum malaria transmission in Africa: a model-based evaluation of intervention strategies

    PLoS Medicine 7:e1000324.

    https://doi.org/10.1371/journal.pmed.1000324

    • PubMed
    • Google Scholar
17. 1. Griffin P
    2. Pasay C
    3. Elliott S
    4. Sekuloski S
    5. Sikulu M
    6. Hugo L
    7. Khoury D
    8. Cromer D
    9. Davenport M
    10. Sattabongkot J
    11. Ivinson K
    12. Ockenhouse C
    13. McCarthy J

    (2016) Safety and reproducibility of a clinical trial system using induced blood stage plasmodium vivax infection and its potential as a model to evaluate malaria transmission

    PLOS Neglected Tropical Diseases 10:e0005139.

    https://doi.org/10.1371/journal.pntd.0005139

    • PubMed
    • Google Scholar
18. 1. Hermsen CC
    2. Telgt DS
    3. Linders EH
    4. van de Locht LA
    5. Eling WM
    6. Mensink EJ
    7. Sauerwein RW

    (2001) Detection of Plasmodium falciparum malaria parasites in vivo by real-time quantitative PCR

    Molecular and Biochemical Parasitology 118:247–251.

    https://doi.org/10.1016/S0166-6851(01)00379-6

    • PubMed
    • Google Scholar
19. 1. Kafsack BF
    2. Rovira-Graells N
    3. Clark TG
    4. Bancells C
    5. Crowley VM
    6. Campino SG
    7. Williams AE
    8. Drought LG
    9. Kwiatkowski DP
    10. Baker DA
    11. Cortés A
    12. Llinás M

    (2014) A transcriptional switch underlies commitment to sexual development in malaria parasites

    Nature 507:248–252.

    https://doi.org/10.1038/nature12920

    • PubMed
    • Google Scholar
20. 1. Lasonder E
    2. Rijpma SR
    3. van Schaijk BC
    4. Hoeijmakers WA
    5. Kensche PR
    6. Gresnigt MS
    7. Italiaander A
    8. Vos MW
    9. Woestenenk R
    10. Bousema T
    11. Mair GR
    12. Khan SM
    13. Janse CJ
    14. Bártfai R
    15. Sauerwein RW

    (2016) Integrated transcriptomic and proteomic analyses of P. falciparum gametocytes: molecular insight into sex-specific processes and translational repression

    Nucleic Acids Research 44:6087–6101.

    https://doi.org/10.1093/nar/gkw536

    • PubMed
    • Google Scholar
21. 1. Laurens MB
    2. Duncan CJ
    3. Epstein JE
    4. Hill AV
    5. Komisar JL
    6. Lyke KE
    7. Ockenhouse CF
    8. Richie TL
    9. Roestenberg M
    10. Sauerwein RW
    11. Spring MD
    12. Talley AK
    13. Moorthy VS
    14. Consensus Group on Design of Clinical Trials of Controlled Human Malaria Infection

    (2012) A consultation on the optimization of controlled human malaria infection by mosquito bite for evaluation of candidate malaria vaccines

    Vaccine 30:5302–5304.

    https://doi.org/10.1016/j.vaccine.2012.04.088

    • PubMed
    • Google Scholar
22. 1. Lensen A
    2. Mulder L
    3. Tchuinkam T
    4. Willemsen L
    5. Eling W
    6. Sauerwein R

    (1998) Mechanisms that reduce transmission of Plasmodium falciparum malaria in semiimmune and nonimmune persons

    The Journal of Infectious Diseases 177:1358–1363.

    https://doi.org/10.1086/515263

    • PubMed
    • Google Scholar
23. 1. Moonen B
    2. Cohen JM
    3. Snow RW
    4. Slutsker L
    5. Drakeley C
    6. Smith DL
    7. Abeyasinghe RR
    8. Rodriguez MH
    9. Maharaj R
    10. Tanner M
    11. Targett G

    (2010) Operational strategies to achieve and maintain malaria elimination

    The Lancet 376:1592–1603.

    https://doi.org/10.1016/S0140-6736(10)61269-X

    • PubMed
    • Google Scholar
24. 1. Méndez F
    2. Muñoz A
    3. Carrasquilla G
    4. Jurado D
    5. Arévalo-Herrera M
    6. Cortese JF
    7. Plowe CV

    (2002) Determinants of treatment response to sulfadoxine-pyrimethamine and subsequent transmission potential in falciparum malaria

    American Journal of Epidemiology 156:230–238.

    https://doi.org/10.1093/aje/kwf030

    • PubMed
    • Google Scholar
25. 1. Nilsson SK
    2. Childs LM
    3. Buckee C
    4. Marti M

    (2015) Targeting human transmission biology for malaria elimination

    PLoS Pathogens 11:e1004871.

    https://doi.org/10.1371/journal.ppat.1004871

    • PubMed
    • Google Scholar
26. 1. Ouédraogo AL
    2. Guelbéogo WM
    3. Cohuet A
    4. Morlais I
    5. King JG
    6. Goncalves BP
    7. Bastiaens GJH
    8. Vaanhold M
    9. Sattabongkot J
    10. Wu Y
    11. Coulibaly M
    12. Ibrahima B
    13. Jones S
    14. Morin M
    15. Drakeley C
    16. Dinglasan RR
    17. Bousema T

    (2013)

    A protocol for membrane feeding assays to determine the infectiousness of P. falciparum naturally infected individuals to Anopheles gambiae

    MalariaWorld Journal 4:16.

    • Google Scholar
27. 1. Pasay CJ
    2. Rockett R
    3. Sekuloski S
    4. Griffin P
    5. Marquart L
    6. Peatey C
    7. Wang CY
    8. O'Rourke P
    9. Elliott S
    10. Baker M
    11. Möhrle JJ
    12. McCarthy JS

    (2016) Piperaquine monotherapy of drug-susceptible plasmodium falciparum infection results in rapid clearance of parasitemia but is followed by the appearance of gametocytemia

    Journal of Infectious Diseases 214:105–113.

    https://doi.org/10.1093/infdis/jiw128

    • PubMed
    • Google Scholar
28. 1. Pett H
    2. Gonçalves BP
    3. Dicko A
    4. Nébié I
    5. Tiono AB
    6. Lanke K
    7. Bradley J
    8. Chen I
    9. Diawara H
    10. Mahamar A
    11. Soumare HM
    12. Traore SF
    13. Baber I
    14. Sirima SB
    15. Sauerwein R
    16. Brown J
    17. Gosling R
    18. Felger I
    19. Drakeley C
    20. Bousema T

    (2016) Comparison of molecular quantification of Plasmodium falciparum gametocytes by Pfs25 qRT-PCR and QT-NASBA in relation to mosquito infectivity

    Malaria Journal 15:539.

    https://doi.org/10.1186/s12936-016-1584-z

    • PubMed
    • Google Scholar
29. 1. Ponnudurai T
    2. Lensen AH
    3. Meis JF
    4. Meuwissen JH

    (1986) Synchronization of Plasmodium falciparum gametocytes using an automated suspension culture system

    Parasitology 93:263–274.

    https://doi.org/10.1017/S003118200005143X

    • PubMed
    • Google Scholar
30. 1. Ponnudurai T
    2. Lensen AH
    3. Van Gemert GJ
    4. Bensink MP
    5. Bolmer M
    6. Meuwissen JH

    (1989) Infectivity of cultured Plasmodium falciparum gametocytes to mosquitoes

    Parasitology 98:165–173.

    https://doi.org/10.1017/S0031182000062065

    • PubMed
    • Google Scholar
31. 1. Reuling IJ
    2. Stone WJR
    3. van de Vegte-Bolmer M
    4. van Gemert GJ
    5. Siebelink-Stoter R
    6. Graumans W
    7. Lanke K
    8. Bousema T
    9. Sauerwein RW

    (2017) Concentration of Plasmodium falciparum gametocytes in whole blood samples by magnetic cell sorting enhances parasite infection rates in mosquito feeding assays

    Malaria Journal 16:315.

    https://doi.org/10.1186/s12936-017-1959-9

    • PubMed
    • Google Scholar
32. 1. Sauerwein RW
    2. Roestenberg M
    3. Moorthy VS

    (2011) Experimental human challenge infections can accelerate clinical malaria vaccine development

    Nature Reviews Immunology 11:57–64.

    https://doi.org/10.1038/nri2902

    • PubMed
    • Google Scholar
33. 1. Schneider P
    2. Schoone G
    3. Schallig H
    4. Verhage D
    5. Telgt D
    6. Eling W
    7. Sauerwein R

    (2004) Quantification of Plasmodium falciparum gametocytes in differential stages of development by quantitative nucleic acid sequence-based amplification

    Molecular and Biochemical Parasitology 137:35–41.

    https://doi.org/10.1016/j.molbiopara.2004.03.018

    • PubMed
    • Google Scholar
34. 1. Shute PG
    2. Maryon M

    (1951) A study of gametocytes in a West African strain of Plasmodium falciparum

    Transactions of the Royal Society of Tropical Medicine and Hygiene 44:421–438.

    https://doi.org/10.1016/S0035-9203(51)80020-8

    • PubMed
    • Google Scholar
35. 1. Sinden RE

    (2017) Developing transmission-blocking strategies for malaria control

    PLoS Pathogens 13:e1006336.

    https://doi.org/10.1371/journal.ppat.1006336

    • PubMed
    • Google Scholar
36. 1. Staedke SG
    2. Sendagire H
    3. Lamola S
    4. Kamya MR
    5. Dorsey G
    6. Rosenthal PJ

    (2004) Relationship between age, molecular markers, and response to sulphadoxine-pyrimethamine treatment in Kampala, Uganda

    Tropical Medicine and International Health 9:624–629.

    https://doi.org/10.1111/j.1365-3156.2004.01239.x

    • PubMed
    • Google Scholar
37. 1. Stone W
    2. Grabias B
    3. Lanke K
    4. Zheng H
    5. Locke E
    6. Diallo D
    7. Birkett A
    8. Morin M
    9. Bousema T
    10. Kumar S

    (2015) A comparison of Plasmodium falciparum circumsporozoite protein-based slot blot and ELISA immuno-assays for oocyst detection in mosquito homogenates

    Malaria Journal 14:451.

    https://doi.org/10.1186/s12936-015-0954-2

    • PubMed
    • Google Scholar
38. 1. Stone W
    2. Sawa P
    3. Lanke K
    4. Rijpma S
    5. Oriango R
    6. Nyaurah M
    7. Osodo P
    8. Osoti V
    9. Mahamar A
    10. Diawara H
    11. Woestenenk R
    12. Graumans W
    13. van de Vegte-Bolmer M
    14. Bradley J
    15. Chen I
    16. Brown J
    17. Siciliano G
    18. Alano P
    19. Gosling R
    20. Dicko A
    21. Drakeley C
    22. Bousema T

    (2017) A molecular assay to quantify male and female plasmodium falciparum gametocytes: results from 2 randomized controlled trials using primaquine for gametocyte clearance

    The Journal of Infectious Diseases 216:457–467.

    https://doi.org/10.1093/infdis/jix237

    • Google Scholar
39. 1. Stone WJ
    2. Dantzler KW
    3. Nilsson SK
    4. Drakeley CJ
    5. Marti M
    6. Bousema T
    7. Rijpma SR

    (2016) Naturally acquired immunity to sexual stage P. falciparum parasites

    Parasitology 143:187–198.

    https://doi.org/10.1017/S0031182015001341

    • PubMed
    • Google Scholar
40. 1. Stone WJ
    2. Eldering M
    3. van Gemert GJ
    4. Lanke KH
    5. Grignard L
    6. van de Vegte-Bolmer MG
    7. Siebelink-Stoter R
    8. Graumans W
    9. Roeffen WF
    10. Drakeley CJ
    11. Sauerwein RW
    12. Bousema T

    (2013) The relevance and applicability of oocyst prevalence as a read-out for mosquito feeding assays

    Scientific Reports 3:3418.

    https://doi.org/10.1038/srep03418

    • PubMed
    • Google Scholar
41. 1. Team SD

    (2016)

    rstanarm: Bayesian applied regression modeling via Stan

    rstanarm: Bayesian applied regression modeling via Stan.

    • Google Scholar
42. 1. Wells TN
    2. Alonso PL
    3. Gutteridge WE

    (2009) New medicines to improve control and contribute to the eradication of malaria

    Nature Reviews Drug Discovery 8:879–891.

    https://doi.org/10.1038/nrd2972

    • PubMed
    • Google Scholar
43. 1. White NJ
    2. Ashley EA
    3. Recht J
    4. Delves MJ
    5. Ruecker A
    6. Smithuis FM
    7. Eziefula AC
    8. Bousema T
    9. Drakeley C
    10. Chotivanich K
    11. Imwong M
    12. Pukrittayakamee S
    13. Prachumsri J
    14. Chu C
    15. Andolina C
    16. Bancone G
    17. Hien TT
    18. Mayxay M
    19. Taylor WR
    20. von Seidlein L
    21. Price RN
    22. Barnes KI
    23. Djimdé A
    24. ter Kuile F
    25. Gosling R
    26. Chen I
    27. Dhorda MJ
    28. Stepniewska K
    29. Guérin P
    30. Woodrow CJ
    31. Dondorp AM
    32. Day NP
    33. Nosten FH

    (2014) Assessment of therapeutic responses to gametocytocidal drugs in Plasmodium falciparum malaria

    Malaria Journal 13:483.

    https://doi.org/10.1186/1475-2875-13-483

    • PubMed
    • Google Scholar
44. 1. White NJ

    (2013) Primaquine to prevent transmission of falciparum malaria

    The Lancet Infectious Diseases 13:175–181.

    https://doi.org/10.1016/S1473-3099(12)70198-6

    • PubMed
    • Google Scholar
45. 1. Witkowski B
    2. Duru V
    3. Khim N
    4. Ross LS
    5. Saintpierre B
    6. Beghain J
    7. Chy S
    8. Kim S
    9. Ke S
    10. Kloeung N
    11. Eam R
    12. Khean C
    13. Ken M
    14. Loch K
    15. Bouillon A
    16. Domergue A
    17. Ma L
    18. Bouchier C
    19. Leang R
    20. Huy R
    21. Nuel G
    22. Barale JC
    23. Legrand E
    24. Ringwald P
    25. Fidock DA
    26. Mercereau-Puijalon O
    27. Ariey F
    28. Ménard D

    (2017) A surrogate marker of piperaquine-resistant Plasmodium falciparum malaria: a phenotype-genotype association study

    The Lancet Infectious Diseases 17:174–183.

    https://doi.org/10.1016/S1473-3099(16)30415-7

    • PubMed
    • Google Scholar
46. Book

    1. World Health Organization

    (2016)

    Eliminating Malaria, Vol 24

    World Health Organization.

    • Google Scholar
47. Report

    1. World Health Organization

    (2016)

    World Malaria Report

    World Health Organization.

    • Google Scholar
48. 1. WWARN Gametocyte Study Group

    (2016) Gametocyte carriage in uncomplicated Plasmodium falciparum malaria following treatment with artemisinin combination therapy: a systematic review and meta-analysis of individual patient data

    BMC Medicine 14:79.

    https://doi.org/10.1186/s12916-016-0621-7

    • PubMed
    • Google Scholar

Author details

1. Isaie J Reuling

   Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1783-0735

2. Lisanne A van de Schans

   Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

   Contribution

   Formal analysis, Investigation, Visualization, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

3. Luc E Coffeng

   Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands

   Contribution

   Formal analysis, Writing—review and editing

   Competing interests

   No competing interests declared

4. Kjerstin Lanke

   Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

   Contribution

   Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

5. Lisette Meerstein-Kessel

   Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

   Contribution

   Data curation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

6. Wouter Graumans

   Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

   Contribution

   Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3952-6491

7. Geert-Jan van Gemert

   Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

   Contribution

   Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

8. Karina Teelen

   Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

   Contribution

   Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

9. Rianne Siebelink-Stoter

   Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

   Contribution

   Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

10. Marga van de Vegte-Bolmer

    Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

    Contribution

    Methodology, Writing—review and editing

    Competing interests

    No competing interests declared

11. Quirijn de Mast

    Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Investigation, Writing—review and editing

    Competing interests

    No competing interests declared

12. André J van der Ven

    Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Investigation, Writing—review and editing

    Competing interests

    No competing interests declared

13. Karen Ivinson

    PATH Malaria Vaccine Initiative, Washington, United States

    Contribution

    Resources, Validation, Project administration, Writing—review and editing

    Competing interests

    No competing interests declared

14. Cornelus C Hermsen

    Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

    Contribution

    Methodology, Writing—review and editing

    Competing interests

    No competing interests declared

15. Sake de Vlas

    Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands

    Contribution

    Formal analysis, Writing—review and editing

    Competing interests

    No competing interests declared

16. John Bradley

    MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine, London, United Kingdom

    Contribution

    Formal analysis, Writing—review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-9449-4608

17. Katharine A Collins

    Clinical Tropical Medicine Laboratory, QIMR Berghofer, Brisbane, Australia

    Contribution

    Conceptualization, Writing—review and editing

    Competing interests

    No competing interests declared

18. Christian F Ockenhouse

    PATH Malaria Vaccine Initiative, Washington, United States

    Contribution

    Conceptualization, Resources, Writing—review and editing

    Competing interests

    No competing interests declared

19. James McCarthy

    Clinical Tropical Medicine Laboratory, QIMR Berghofer, Brisbane, Australia

    Contribution

    Conceptualization, Resources, Writing—review and editing

    Competing interests

    No competing interests declared

20. Robert W Sauerwein

    Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

    Contribution

    Conceptualization, Supervision, Investigation, Writing—review and editing

    Contributed equally with

    Teun Bousema

    Competing interests

    No competing interests declared

21. Teun Bousema

    Department of Medical Microbiology, Radboud university medical center, Nijmegen, Netherlands

    Contribution

    Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Writing—original draft

    Contributed equally with

    Robert W Sauerwein

    For correspondence

    teun.bousema@radboudumc.nl

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-2666-094X

• 1,940

  views

• 292

  downloads

• 52

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.