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Echeverry, D. F.

Publications and source records attributed to Echeverry, D. F..

5 recordsLinked to original sources

South American Plasmodium falciparum isolates reveal new insights into the role of PfAAT1 in mediating resistance to Chloroquine

Antimalarial drug resistance remains one of the most significant challenges to global malaria control. The emergence of resistance to chloroquine, the first truly globally distributed antimalarial, has been extensively studied but is still not fully understood. While mutations in the Plasmodium falciparum chloroquine resistance transporter (PfCRT) primarily drive resistance, the phenotype is complex and multigenic, with mutations in the putative amino acid transporter PfAAT1 recently confirmed to play a modulatory role. To date studies have focused on PfAAT1 mutations found in African and Southeast Asian P. falciparum lineages, but chloroquine resistance emerged independently in South America, where there may be novel PfAAT1 polymorphisms that are functionally important. We used AlphaFold modelling to reveal high homology between PfAAT1 and the human lysosomal arginine transporter SLC38A9, which allows prediction of membrane orientation and identifies a partially open channel accessible from the cytoplasm. Several PfAAT1 mutations found only in South American isolates sit near the entrance of this pore, most notably V231 where mutation to aspartate is predicted to alter channel conformation and influence transport, while nearby P446A (which is always found in combination with V231D) and I248T are predicted to impact pore flexibility and local structural stability. To functionally validate these insights, we employed CRISPR/Cas9 gene editing across parasite strains with diverse geographic origins. Reverting the regional V231D mutation in the South American 7G8 strain significantly reduced CQ resistance, providing the first functional evidence that this residue modulates drug susceptibility. Furthermore, introducing the apparently Colombia-specific I248T mutation significantly enhanced parasite multiplication rates in 7G8, demonstrating complex fitness and sensitivity trade-offs. Our findings reinforce the distinct evolutionary trajectory for South American CQ resistance and highlight the necessity of including additional pfaat1 mutations in global molecular surveillance strategies. Author SummaryAntimalarial drug resistance is a major threat to global public health. Chloroquine was used widely in the 1950s-60s as part of a global malaria eradication campaign, but resistance emerged in multiple places independently and chloroquine resistant parasites directly led to the death of millions of children. Chloroquine resistance is primarily driven by mutations in the transporter PfCRT which are thought to increase export of chloroquine from the digestive vacuole, where chloroquine acts to prevent the ability of the parasite to digest haemoglobin as a source of energy. However, it is becoming increasingly clear that additional vacuolar transporters can also modulate chloroquine resistance. In this study we focused on mutations in the putative amino acid transporter 1 (PfAAT1) which are specific to South America, where chloroquine resistance emerged independently from Southeast Asia. By integrating AlphaFold structural predictions with CRISPR/Cas9 gene editing across geographically diverse parasite backgrounds we provide the first functional evidence that the region-specific V231D mutation significantly diminishes chloroquine resistance. These findings emphasise that chloroquine resistance in South America followed a unique trajectory and that PfAAT1 is involved in complex fitness and sensitivity trade-offs. This work emphasises the benefits of integrating diverse experimental and modelling approaches with global molecular surveillance.

microbiology↗

Resolving drug selection and migration in an inbred South American Plasmodium falciparum population with identity-by-descent analysis

The human malaria parasite Plasmodium falciparum is globally widespread, but its prevalence varies significantly between and even within countries. Most population genetic studies in P. falciparum focus on regions of high transmission where parasite populations are large and genetically diverse, such as sub-Saharan Africa. Understanding population dynamics in low transmission settings, however, is of particular importance as these are often where drug resistance first evolves. Here, we use the Pacific Coast of Colombia and Ecuador as a model for understanding the population structure and evolution of Plasmodium parasites in small populations harboring low genetic diversity. The combination of low transmission and a high proportion of monoclonal infections means there are few outcrossing events and clonal lineages persist for long periods of time. Yet despite this, the population is evolutionarily labile and has successfully adapted to multiple drug regimes. Using 166 newly sequenced whole genomes, we measure relatedness between parasites, calculated as identity by descent (IBD), and find 17 distinct but highly related clonal lineages, six of which have persisted in the region for at least a decade. This inbred population structure is captured in more detail with IBD than with other common population structure analyses like PCA, ADMIXTURE, and distance-based trees. We additionally use patterns of intra-chromosomal IBD and an analysis of haplotypic variation to explore the role of recombination in spreading drug resistance mutations throughout the region. Two genes associated with chloroquine resistance, crt and aat1, show evidence of hard selective sweeps, while selection appears soft and/or incomplete at three other key resistance loci (dhps, mdr1, and dhfr). Overall, this work highlights the strength of IBD analyses for studying parasite population structure and resistance evolution in regions of low transmission, and emphasizes that drug resistance can evolve and spread in extremely small populations, as will occur in any region nearing malaria elimination.

evolutionary biology↗

From contigs to chromosomes: automatic Improvement of Long Read Assemblies (ILRA)

Recent advances in long read technologies not only enable large consortia to aim to sequence all eukaryotes on Earth, but they also allow individual laboratories to sequence their species of interest with relatively low investment. Although there is a promise of long read technologies to obtain "perfect genomes", the number of contigs often exceeds the number of chromosomes by far, containing many insertion and deletion errors around homopolymer tracks. To overcome these issues, we implemented the ILRA pipeline to correct long read-based assemblies, so contigs are reordered, renamed, merged, circularized, or filtered if erroneous or contaminated, and Illumina reads are used to correct homopolymer errors. We successfully tested our approach by improving the genomes of Trypanosoma brucei and Leptosphaeria spp, and generated four novel Plasmodium falciparum assemblies from field samples. We found that correcting homopolymer tracks reduced the number of genes incorrectly annotated as pseudogenes, but an iterative correction seems to be required to correct larger numbers of sequencing errors. In summary, we described and compared the performance of our new tool, which improved the quality of novel long read assemblies of genomes up to 1Gbp. AvailabilityThe tool is available at GitHub: https://github.com/ThomasDOtto/ILRA.

bioinformatics↗

Identity-by-descent relatedness estimates with uncertainty characterise departure from isolation-by-distance between Plasmodium falciparum populations on the Colombian-Pacific coast

Characterising connectivity between geographically separated biological populations is a common goal in many fields. Recent approaches to understanding connectivity between malaria parasite populations, with implications for disease control efforts, have used estimates of relatedness based on identity-by-descent (IBD). However, uncertainty around estimated relatedness has not been accounted for to date. IBD-based relatedness estimates with uncertainty were computed for pairs of monoclonal Plasmodium falciparum samples collected from five cities on the Colombian-Pacific coast where long-term clonal propagation of P. falciparum is frequent. The cities include two official ports, Buenaventura and Tumaco, that are separated geographically but connected by frequent marine traffic. The fraction of highly-related sample pairs (whose classification accounts for uncertainty) was greater within cities versus between. However, based on both the fraction of highly-related sample pairs and on a threshold-free approach (Wasserstein distances between parasite populations) connectivity between Buenaventura and Tumaco was disproportionally high. Buenaventura-Tumaco connectivity was consistent with three separate transmission events involving parasites from five different clonal components (groups of statistically indistinguishable parasites identified under a graph theoretic framework). To conclude, P. falciparum population connectivity on the Colombian-Pacific coast abides by accessibility not isolation-by-distance, potentially implicating marine traffic in malaria transmission with opportunities for targeted intervention. Further investigations are required to test this and alternative hypotheses. For the first time in malaria epidemiology, we account for uncertainty around estimated relatedness (an important consideration for future studies that plan to use genotype versus whole genome sequence data to estimate IBD-based relatedness); we also use a threshold-free approach to compare parasite populations, and identify clonal components in a statistically principled manner. The approaches we employ could be adapted to other recombining organisms with mixed mating systems, thus have broad relevance.

genetics↗

A molecular barcode and online tool to identify and map imported infection with Plasmodium vivax

Imported cases present a considerable challenge to the elimination of malaria. Traditionally, patient travel history has been used to identify imported cases, but the long-latency liver stages confound this approach in Plasmodium vivax. Molecular tools to identify and map imported cases offer a more robust approach, that can be combined with drug resistance and other surveillance markers in high-throughput, population-based genotyping frameworks. Using a machine learning approach incorporating hierarchical FST (HFST) and decision tree (DT) analysis applied to 831 P. vivax genomes from 20 countries, we identified a 28-Single Nucleotide Polymorphism (SNP) barcode with high capacity to predict the country of origin. The Matthews correlation coefficient (MCC), which provides a measure of the quality of the classifications, ranging from -1 (total disagreement) to 1 (perfect prediction), exceeded 0.9 in 15 countries in cross-validation evaluations. When combined with an existing 37-SNP P. vivax barcode, the 65-SNP panel exhibits MCC scores exceeding 0.9 in 17 countries with up to 30% missing data. As a secondary objective, several genes were identified with moderate MCC scores (median MCC range from 0.54-0.68), amenable as markers for rapid testing using low-throughput genotyping approaches. A likelihood-based classifier framework was established, that supports analysis of missing data and polyclonal infections. To facilitate investigator-lead analyses, the likelihood framework is provided as a web-based, open-access platform (vivaxGEN-geo) to support the analysis and interpretation of data produced either at the 28-SNP core or full 65-SNP barcode. These tools can be used by malaria control programs to identify the main reservoirs of infection so that resources can be focused to where they are needed most.

molecular biology↗