Rapid selection of sulphadoxine-resistant Plasmodium falciparum and its effect on within-population genetic diversity in Papua New Guinea

Targeted and whole-genome sequencing reveal a north-south divide in P. falciparum drug resistance markers and genetic structure in Mozambique

Mozambique is one of the four African countries which account for over half of all malaria deaths worldwide, yet little is known about the parasite genetic structure in that country. We performed P. falciparum amplicon and whole genome sequencing on 2251 malaria-infected blood samples collected in 2015 and 2018 in seven provinces of Mozambique to genotype antimalarial resistance markers and interrogate parasite population structure using genome-wide microhaplotyes. Here we show that the only resistance-associated markers observed at frequencies above 5% were pfmdr1-184F (59%), pfdhfr-51I/59 R/108 N (99%) and pfdhps-437G/540E (89%). The frequency of pfdhfr/pfdhps quintuple mutants associated with sulfadoxine-pyrimethamine resistance increased from 80% in 2015 to 89% in 2018 (p < 0.001), with a lower expected heterozygosity and higher relatedness of microhaplotypes surrounding pfdhps mutants than wild-type parasites suggestive of recent selection. pfdhfr/pfdhps quintuple mutants also increased from 72% in the north to 95% in the south (2018; p < 0.001). This resistance gradient was accompanied by a concentration of mutations at pfdhps-436 (17%) in the north, a south-to-north increase in the genetic complexity of P. falciparum infections (p = 0.001) and a microhaplotype signature of regional differentiation. The parasite population structure identified here offers insights to guide antimalarial interventions and epidemiological surveys.

coiaf: Directly estimating complexity of infection with allele frequencies

In malaria, individuals are often infected with different parasite strains. The complexity of infection (COI) is defined as the number of genetically distinct parasite strains in an individual. Changes in the mean COI in a population have been shown to be informative of changes in transmission intensity with a number of probabilistic likelihood and Bayesian models now developed to estimate the COI. However, rapid, direct measures based on heterozygosity or FwS do not properly represent the COI. In this work, we present two new methods that use easily calculated measures to directly estimate the COI from allele frequency data. Using a simulation framework, we show that our methods are computationally efficient and comparably accurate to current approaches in the literature. Through a sensitivity analysis, we characterize how the distribution of parasite densities, the assumed sequencing depth, and the number of sampled loci impact the bias and accuracy of our two methods. Using our developed methods, we further estimate the COI globally from Plasmodium falciparum sequencing data and compare the results against the literature. We show significant differences in the estimated COI globally between continents and a weak relationship between malaria prevalence and COI.

Monitoring Plasmodium falciparum and Plasmodium vivax using microsatellite markers indicates limited changes in population structure after substantial transmission decline in Papua New Guinea

Monitoring the genetic structure of pathogen populations may be an economical and sensitive approach to quantify the impact of control on transmission dynamics, highlighting the need for a better understanding of changes in population genetic parameters as transmission declines. Here we describe the first population genetic analysis of two major human malaria parasites, Plasmodium falciparum (Pf) and Plasmodium vivax (Pv), following nationwide distribution of long-lasting insecticide-treated nets (LLINs) in Papua New Guinea (PNG). Parasite isolates from pre- (2005-2006) and post-LLIN (2010-2014) were genotyped using microsatellite markers. Despite parasite prevalence declining substantially (East Sepik Province: Pf = 54.9%-8.5%, Pv = 35.7%-5.6%, Madang Province: Pf = 38.0%-9.0%, Pv: 31.8%-19.7%), genetically diverse and intermixing parasite populations remained. Pf diversity declined modestly post-LLIN relative to pre-LLIN (East Sepik: R_s  = 7.1-6.4, H_E  = 0.77-0.71; Madang: R_s  = 8.2-6.1, H_E  = 0.79-0.71). Unexpectedly, population structure present in pre-LLIN populations was lost post-LLIN, suggesting that more frequent human movement between provinces may have contributed to higher gene flow. Pv prevalence initially declined but increased again in one province, yet diversity remained high throughout the study period (East Sepik: R_s  = 11.4-9.3, H_E  = 0.83-0.80; Madang: R_s  = 12.2-14.5, H_E  = 0.85-0.88). Although genetic differentiation values increased between provinces over time, no significant population structure was observed at any time point. For both species, a decline in multiple infections and increasing clonal transmission and significant multilocus linkage disequilibrium post-LLIN were positive indicators of impact on the parasite population using microsatellite markers. These parameters may be useful adjuncts to traditional epidemiological tools in the early stages of transmission reduction.

The first activation studies of the η-carbonic anhydrase from the malaria parasite Plasmodium falciparum with amines and amino acids

The first activation study of a η-class carbonic anhydrase (CAs, EC 4.2.1.1) is reported. A panel of 24 natural and non-natural amino acids and amines was used to explore the activation profile of Plasmodium falciparum CA (PfACA). The most effective activators belonged to the amino acid chemotype, with d-Glu, l-Asp, l-/d-Phe and l-/d-DOPA possessing activation constant in the range of 82 nM-0.75 µM, whereas l-/d-His, l-Tyr, 4-amino-l-Phe and l-Gln were slightly less effective (K_A in the range of 1.00-2.51 µM. The only amine with submicromolar activating properties was 1-(2-aminoethyl-piperazine) with a K_A of 0.71 µM, whereas histamine, dopamine and serotonin showed K_A ranging between 7.18 and 9.97 µM. As CA activators have scarcely been investigated for their interaction with protozoan CAs, this study may be relevant for an improved understanding of the role of this enzyme in the life cycle of the malaria producing organisms belonging to the genus Plasmodium.