High genetic complexity but low relatedness in Plasmodium falciparum infections from Western Savannah Highlands and coastal equatorial Lowlands of Cameroon

Evaluating the performance of Plasmodium falciparum genetic metrics for inferring National Malaria Control Programme reported incidence in Senegal

BACKGROUND

Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programmes (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence.

METHODS

This study examined parasites from 3147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, a series of Poisson generalized linear mixed-effects models were constructed to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates.

RESULTS

Model-predicted incidence was compared with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (< 10/1000/annual [‰]).

CONCLUSIONS

When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence > 10‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was < 10‰, many of the correlations between parasite genetics and incidence were reversed, which may reflect the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

Amplicon deep sequencing of five highly polymorphic markers of Plasmodium falciparum reveals high parasite genetic diversity and moderate population structure in Ethiopia

BACKGROUND

Plasmodium falciparum genetic diversity can add information on transmission intensity and can be used to track control and elimination interventions.

METHODS

Dried blood spots (DBS) were collected from patients who were recruited for a P. falciparum malaria therapeutic efficacy trial in three malaria endemic sites in Ethiopia from October to December 2015, and November to December 2019. qPCR-confirmed infections were subject to amplicon sequencing of polymorphic markers ama1-D3, csp, cpp, cpmp, msp7. Genetic diversity, the proportion of multiclonal infections, multiplicity of infection, and population structure were analysed.

RESULTS

Among 198 samples selected for sequencing, data was obtained for 181 samples. Mean MOI was 1.38 (95% CI 1.24-1.53) and 17% (31/181) of infections were polyclonal. Mean He across all markers was 0.730. Population structure was moderate; populations from Metema and Metehara 2015 were very similar to each other, but distinct from Wondogent 2015 and Metehara 2019.

CONCLUSION

The high level of parasite genetic diversity and moderate population structure in this study suggests frequent gene flow of parasites among sites. The results obtained can be used as a baseline for additional parasite genetic diversity and structure studies, aiding in the formulation of appropriate control strategies in Ethiopia.

Recent increase in low complexity polygenomic infections and sialic acid-independent invasion pathways in Plasmodium falciparum from Western Gambia

BACKGROUND

The malaria parasite Plasmodium falciparum utilizes multiple alternative receptor-ligand interactions for the invasion of human erythrocytes. While some P. falciparum clones make use of sialic acid (SA) residues on the surface of the human glycophorin receptors to invade the erythrocyte, others use alternative receptors independent of sialic acid residues. We hypothesized that over the years, intensified malaria control interventions and declining prevalence in The Gambia have resulted in a selection of parasites with a dominant invasion pathways and ligand expression profiles.

METHODS

Blood samples were collected from 65 malaria-infected participants with uncomplicated malaria across 3 years (2015, 2016, and 2021). Genetic diversity was determined by genotyping the merozoite surface protein 2 (msp2) polymorphic gene of P. falciparum. Erythrocyte invasion phenotypes were determined using neuraminidase, trypsin, and chymotrypsin enzymes, known to cleave different receptors from the surface of the erythrocyte. Schizont-stage transcript levels were obtained for a panel of 6 P. falciparum invasion ligand genes (eba175, eba181, Rh2b, Rh4, Rh5, and clag2) using 48 successfully cultured isolates.

RESULTS

Though the allelic heterozygosity of msp2 repeat region decreased as expected with reduced transmission, there was an increase in infections with more than a single msp2 allelotype from 2015 to 2021. The invasion phenotypes of these isolates were mostly SA independent with a continuous increase from 2015 to 2021. Isolates from 2021 were highly inhibited by chymotrypsin treatment compared to isolates from 2015 and 2016. Higher invasion inhibition for 2021 isolates was further obtained following erythrocyte treatment with a combination of chymotrypsin and trypsin. The transcript levels of invasion ligand genes varied across years. However, levels of clag2, a rhoptry-associated protein, were higher in 2015 and 2016 isolates than in 2021 isolates, while Rh5 levels were higher in 2021 compared to other years.

CONCLUSIONS

Overall, these findings suggest increasing mixed infections with an increase in the use of sialic-acid independent invasion pathways by P. falciparum clinical isolates in the Western part of Gambia.

Knowledge, attitude, and adherence to malaria control guidelines and the prevalence of Plasmodium species infection in localities across transmission and ecological zones in Cameroon

Background

Despite a scale up of control interventions over the years, malaria remains a major public health and economic concern in Cameroon, contributing considerably to hospitalization and deaths. The effectiveness of control strategies depends on the extent of adherence by the population to national guidelines. This study assessed the influence of human knowledge, attitudes, and practices related to malaria and its control on the prevalence of malaria parasite infection, with implications for the elimination of the disease.

Methodology

This is a cross-sectional community and hospital-based study, covering the five ecological and three malaria transmission zones in Cameroon. A pre-tested semi-structured questionnaire was used to document socio-demographic and clinical parameters as well as knowledge, attitudes, and practices toward malaria control and management. Consenting participants were screened for malaria parasite with rapid diagnostic test (mRDT) of the peripheral blood. Association between qualitative variables was determined using the chi-square test and logistic regression analysis.

Results

A total of 3,360 participants were enrolled, 45.0% (1,513) of whom were mRDT positive, with 14.0% (451/3,216) and 29.6% (951/3,216) having asymptomatic parasitaemia and malaria, respectively. Although most participants knew the cause, symptoms, and control strategies, with 53.6% (1,000/1,867) expertly knowledgeable about malaria overall, only 0.1% (2/1,763) individuals were fully adherent to malaria control measures.

Conclusion

The risk of malaria in Cameroon remains high, with the population considerably knowledgeable about the disease but poorly adherent to national malaria control guidelines. Concerted and more effective strategies aimed at improving knowledge about malaria and adherences to control interventions are necessary to ultimately eliminate the disease.

R H: a genetic metric for measuring intrahost Plasmodium falciparum relatedness and distinguishing cotransmission from superinfection

Multiple-strain (polygenomic) infections are a ubiquitous feature of Plasmodium falciparum parasite population genetics. Under simple assumptions of superinfection, polygenomic infections are hypothesized to be the result of multiple infectious bites. As a result, polygenomic infections have been used as evidence of repeat exposure and used to derive genetic metrics associated with high transmission intensity. However, not all polygenomic infections are the result of multiple infectious bites. Some result from the transmission of multiple, genetically related strains during a single infectious bite (cotransmission). Superinfection and cotransmission represent two distinct transmission processes, and distinguishing between the two could improve inferences regarding parasite transmission intensity. Here, we describe a new metric, R H, that utilizes the correlation in allelic state (heterozygosity) within polygenomic infections to estimate the likelihood that the observed complexity resulted from either superinfection or cotransmission. R H is flexible and can be applied to any type of genetic data. As a proof of concept, we used R H to quantify polygenomic relatedness and estimate cotransmission and superinfection rates from a set of 1,758 malaria infections genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode. Contrary to expectation, we found that cotransmission was responsible for a significant fraction of 43% to 53% of the polygenomic infections collected in three distinct epidemiological regions in Senegal. The prediction that polygenomic infections frequently result from cotransmission stresses the need to incorporate estimates of relatedness within polygenomic infections to ensure the accuracy of genomic epidemiology surveillance data for informing public health activities.