Person:

Daniels, Rachel

Background: Malaria treatment efforts are hindered by the rapid emergence and spread of drug resistant parasites. Simple assays to monitor parasite drug response in direct patient samples (ex vivo) can detect drug resistance before it becomes clinically apparent, and can inform changes in treatment policy to prevent the spread of resistance. Methods: Parasite drug responses to amodiaquine, artemisinin, chloroquine and mefloquine were tested in approximately 400 Plasmodium falciparum malaria infections in Thiès, Senegal between 2008 and 2011 using a DAPI-based ex vivo drug resistance assay. Drug resistance-associated mutations were also genotyped in pfcrt and pfmdr1. Results: Parasite drug responses changed between 2008 and 2011, as parasites became less sensitive to amodiaquine, artemisinin and chloroquine over time. The prevalence of known resistance-associated mutations also changed over time. Decreased amodiaquine sensitivity was associated with sustained, highly prevalent mutations in pfcrt, and one mutation in pfmdr1 – Y184F – was associated with decreased parasite sensitivity to artemisinin. Conclusions: Directly measuring ex vivo parasite drug response and resistance mutation genotyping over time are useful tools for monitoring parasite drug responses in field samples. Furthermore, these data suggest that the use of amodiaquine and artemisinin derivatives in combination therapies is selecting for increased drug tolerance within this population.

Background: As public health interventions drive parasite populations to elimination, genetic epidemiology models that incorporate population genomics can be powerful tools for evaluating the effectiveness of continued intervention. However, current genetic epidemiology models may not accurately simulate the population genetic profile of parasite populations, particularly with regard to polygenomic (multi-strain) infections. Current epidemiology models simulate polygenomic infections via superinfection (multiple mosquito bites), despite growing evidence that cotransmission (a single mosquito bite) may contribute to polygenomic infections. Methods: Here, we quantified the relatedness of strains within 31 polygenomic infections collected from patients in Thiès, Senegal using a hidden Markov model to measure the proportion of the genome that is inferred to be identical by descent. Results: We found that polygenomic infections can be composed of highly related parasites and that superinfection models drastically underestimate the relatedness of strains within polygenomic infections. Conclusions: Our findings suggest that cotransmission is a major contributor to polygenomic infections in Thiès, Senegal. The incorporation of cotransmission into existing genetic epidemiology models may enhance our ability to characterize and predict changes in population structure associated with reduced transmission intensities and the emergence of important phenotypes like drug resistance that threaten to undermine malaria elimination activities. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0398-0) contains supplementary material, which is available to authorized users.

The effects of persistent Plasmodium falciparum (Pf) infection and multiclonality on subsequent risk of clinical malaria have been reported, but the relationship between these 2 parameters and their relative impacts on the clinical outcome of infection are not understood. A longitudinal cohort study was conducted in a seasonal and high-transmission area of Mali, in which 500 subjects aged 1–65 years were followed for 1 year. Blood samples were collected every 2 weeks, and incident malaria cases were diagnosed and treated. Pf infection in each individual at each time point was assessed by species-specific nested-PCR, and Pf longitudinal prevalence per person (PfLP, proportion of Pf-positive samples over 1 year) was calculated. Multiclonality of Pf infection was measured using a 24-SNP DNA barcoding assay at 4 time-points (two in wet season, and two in dry season) over one year. PfLP was positively correlated with multiclonality at each time point (all r≥0.36; all P≤0.011). When host factors (e.g., age, gender), PfLP, and multiclonality (at the beginning of the transmission season) were analyzed together, only increasing age and high PfLP were associated with reduced clinical malaria occurrence or reduced number of malaria episodes (for both outcomes, P<0.001 for age, and P = 0.005 for PfLP). When age, PfLP and baseline Pf positivity were analyzed together, the effect of high PfLP remained significant even after adjusting for the other two factors (P = 0.001 for malaria occurrence and P<0.001 for number of episodes). In addition to host age and baseline Pf positivity, both of which have been reported as important modifiers of clinical malaria risk, our results demonstrate that persistent parasite carriage, but not baseline multiclonality, is associated with reduced risk of clinical disease in this population. Our study emphasizes the importance of considering repeated parasite exposure in future studies that evaluate clinical malaria risk.

Background: Complex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays. Methods: COIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample. Results: COIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples. Conclusions: The capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI. Electronic supplementary material The online version of this article (doi:10.1186/1475-2875-14-4) contains supplementary material, which is available to authorized users.

Background: Following its recent certification as malaria-free, imported infections now pose the greatest threat for maintaining this status in Sri Lanka. Imported infections may also introduce species that are uncommon or not previously endemic to these areas. We highlight in this case report the increasing importance of less common malaria species such as Plasmodium ovale in elimination settings and discuss its relevance for the risk of malaria resurgence in the country. Case presentation: A 41-year-old patient from southern Sri Lanka was diagnosed with malaria after 8 days of fever. Microscopy of blood smears revealed parasites morphologically similar to P. vivax and the rapid diagnostic test was indicative of non-P. falciparum malaria. He was treated with chloroquine over 3 days and primaquine for 14 days. He was negative for malaria at a one-year follow-up. Molecular testing performed subsequently confirmed that infection was caused by P. ovale curtisi. The patient gave a history of P. vivax malaria treated with chloroquine and primaquine. He also provided a history of travel to malaria endemic regions, including residing in Liberia from May 2012 to November 2013, throughout which he was on weekly malaria prophylaxis with mefloquine. He had also visited India on an eight-day Buddhist pilgrimage tour in September 2014 without malaria prophylaxis. Conclusions: It is crucial that every case of malaria is investigated thoroughly and necessary measures taken to prevent re-introduction of malaria. Accurate molecular diagnostic techniques need to be established in Sri Lanka for the screening and diagnosis of all species of human malaria infections, especially those that may occur with low parasitemia and are likely to be undetected using the standard techniques currently in use. In addition, ascertaining whether an infection occurred through local transmission or by importation is critical in the implementation of an effective plan of action in the country. This new era emphasizes the global nature of regional malaria elimination. Increasing global surveillance and tool development are necessary in order to “fingerprint” parasites and identify their origin.

Using parasite genotyping tools, we screened patients with mild uncomplicated malaria seeking treatment at a clinic in Thiès, Senegal, from 2006 to 2011. We identified a growing frequency of infections caused by genetically identical parasite strains, coincident with increased deployment of malaria control interventions and decreased malaria deaths. Parasite genotypes in some cases persisted clonally across dry seasons. The increase in frequency of genetically identical parasite strains corresponded with decrease in the probability of multiple infections. Further, these observations support evidence of both clonal and epidemic population structures. These data provide the first evidence of a temporal correlation between the appearance of identical parasite types and increased malaria control efforts in Africa, which here included distribution of insecticide treated nets (ITNs), use of rapid diagnostic tests (RDTs) for malaria detection, and deployment of artemisinin combination therapy (ACT). Our results imply that genetic surveillance can be used to evaluate the effectiveness of disease control strategies and assist a rational global malaria eradication campaign.