Structure and genetic diversity of Plasmodium malariae in sub-Saharan Africa determined from microsatellite variants and linked SNPs in orthologs of malaria resistance genes

Malaria elimination programs and tools focus on eliminating the main malaria parasites. P falciparum Y P. vivaxbut other species of malaria parasites such as P malariae they are co-transmitted in regions where malaria is endemic and deserve attention to achieve their elimination. Since knowledge of diversity and the effect of removal tools on these minor species has not had much academic or public health focus, this study took advantage of the Pathogen Diversity Network of Africa (PDNA) to collect a set of samples small but the widest of P malariae isolates from seven African and one Asian country, describing the population structure, high genetic diversity, genotypic richness, and species uniformity of malaria parasites.

A high level of genetic diversity is essential for the long-term survival of populations, and the degree of variation determines the species’ ability to adapt to environmental challenges imposed by nature or control interventions. The high diversity in P malariae found here is similar to those previously reported in Kenya and Malawi23, despite the variable and small number of samples analyzed from some of the countries. The intensity of malaria transmission and the history of interventions vary among the different countries represented in this study and could have affected the results. High transmission results in frequent heterologous reassortment of the parasite in the vector mosquito, breaking the linkage disequilibrium between variable loci and increasing genetic diversity within populations. In general, the probability of interbreeding in parasite populations varies from a high to low malaria transmission gradient in the western, central, and eastern directions in sub-Saharan Africa.twenty. Despite this, heterozygosity was high and genetic distance was low between isolates despite differences in malaria transmission intensity, except for the three isolates from Cameroon. The low genetic distance observed in this study requires further validation as there are no studies on P malariae for direct comparison. However, the results obtained are consistent with a recent P falciparum study in nigeriatwenty-one although in stark contrast to an earlier study in Senegal22, suggesting relatively high levels of panmixia in current sampled populations despite different transmission patterns. Indeed, multiple locus genotypes were rare in all populations, an indication of recombination and the absence of the clonal expansion observed in some populations. P falciparum populations with low or seasonal malaria transmission23.

Recurrent promotion of gene flow between parasite populations between countries through human or vector migration might have led to a lack of differentiation based on geographic origin3. This was evident in the low rates of microsatellite differentiation between countries, although the small number of isolates per country population limits the precision of the inferred rates. It is also possible that gene flow alone does not explain the high genetic diversity or lack of geographic differentiation observed in P malariaeOther factors could also be considered, such as the lack of a bottleneck event or an intervention to reduce local diversity.

Analysis of the population structure with neutral microsatellite (ie, SSR) loci identified five clusters, each containing isolates from different countries. This is a further indication of the high intra-population variability in these markers and the absence of population-specific selection of these loci that might drive population differentiation. This structure is not consistent with the isolation by distance seen for P falciparum, where gene pools can be assigned to geographic populations in the West, Central, and East African regions. What P malariae occurs mainly as coinfections with P falciparum, the drivers of such an independent substructure may therefore be different, or this may have been established by an earlier event preceding any population displacement due to demography or isolation. Using the admixture model in STRUCTURE, an optimum of three ancestral groups was determined and this also showed all isolates with components of each ancestry regardless of country of origin. STRUCTURE implements a Bayesian algorithm to identify groups of individuals in Hardy-Weinberg and linkage equilibrium. However, its robustness was shown to be affected by small and unequal sample sizes between subpopulations and/or hierarchical levels of population structure.24.25.

SNP data from selected P malariae orthologs of P falciparum drug resistance genes also clustered isolates into 5 subpopulations, although only 3 less distinct clusters were retained after stringent filtering processes, and subgroup membership did not completely overlap with that determined by microsatellites. The distribution between SNP and microsatellite distance differed, with wider distances between fewer isolates using SSR data. This is to be expected since SSRs are multiallelic, probably neutral, and are more likely to differ between pairs of isolates. Therefore, further investigation into the potential drivers of population differentiation for this parasite species will improve understanding of its complexity, particularly with regard to control and elimination strategies. While it appeared that most infections had mixed (polygenomic) genomes as indicated by FWS, this was affected by the denoising and filtering pipelines used for the analysis. Therefore, further investigation using an appropriate sample size will be necessary to clarify whether there is cotransmission of different clones and a higher possibility of recombination for this Plasmodium species. It is important to point out the high level of complexity of the infection, since it is one of the indices to monitor the effect of the interventions. Unlike P falciparum, the complexity did not appear to be greater at relatively higher malaria transmission settings and may be part of the unique biology of this species that needs further investigation. As drugs and other interventions reduce populations, selection and changes in complexity must be monitored for the species.

Drugs have been a major selective force in P falciparum, with resistance associated with mutations in several genes and positive selection signatures in the genomes. We identified 20 P malariae mutations in orthologous drug resistant genes by combining different sequence alignment and variant calling algorithms. These putative variants have not been described in previous targeted or genomic scans, probably due to differences in the isolates used or the methods applied. Here we keep only high-quality variants compatible with combinations of two mapping and two SNP calling algorithms. Most of the candidate variants were synonymous, but there were several non-synonymous SNPs in seven genes, especially in pmcytbwhose P falciparum resistance of the orthologous unit against atovaquone. Atovaquone is a member of the quinolines, to which resistance in P falciparum have been associated with mutations in the multidrug resistance gene (pfmdr1), chloroquine resistance transporter (pfct) and an amino acid transporter (pfaat1). Most of the LDs observed with the unfiltered data set were not reproducible with the denoised and filtered data set, with the exception of the LD observed in the mitochondrial gene SNPs, either due to common ancestry or selection of the mitochondrial gene. dominant haplotype due to drugs or other factors. Additional candidate variants were observed in pmdhfr Y pmdhps, orthologs of antifolate resistance in P falciparum. The antifolate antimalarials, sulfadoxine-pyrimethamine, are still widely used for chemoprevention against malaria in pregnancy and in combination with amodiaquine for chemoprevention of seasonal malaria in West Africa. These together could be selected for the identified variants. Although the non-synonymous SNPs reported here occurred at low frequencies, further verification, characterization, and association of these SNPs will require further genomic surveillance and phenotype association studies from in vivo and ex vivo therapeutic efficacy tests.

A limitation of this study, which justifies a cautious interpretation of the results, is the small number of samples analyzed in the different countries and the lack of biological and clinical data on the samples. Larger population studies for P malariae Appropriate epidemiological or clinical data are required to validate the findings of smaller studies as reported here. Another limitation is the use of standard bioinformatics pipelines designed to P falciparum. While these may be acceptable for preliminary analysis, custom pipelines that account for potential amplification and sequencing errors may be better for P malariae, particularly due to the paucity of population data with confirmed high-quality variants of this parasite species. The different types of samples analyzed could also be a limitation for this study, dried blood spot samples were more likely to produce poor quality results, possibly due to the low prevalence and low parasite density of non-falciparum species. Therefore, venous blood sampling and more robust molecular techniques that take it into account will be beneficial in future molecular surveillance of P malariae.

The current drive for malaria elimination needs innovative strategies to attack all malaria parasites. One approach may be to integrate genomic surveillance of all plasmodium species in malaria control and elimination programs in sub-Saharan Africa, learning from experience with COVID-19, to refine approaches as new variants are identified and monitored. This study has established the relevance of this in P malariae.

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