Frontiers in genetics · 2026
Genetic metrics decode Plasmodium falciparum diversity: complexity of infection, parasite connectivity, and transmission intensity in Mainland Tanzania's diverse regions.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Pereus Dativa, Fola Abebe A, Bakari Catherine, Seth Misago D, DeFeo Rebecca, Lyimo Beatus M, Mandara Celine I, Madebe Rashid A, Mbata Doris, Popkin-Hall Zachary R, Moshi Ramadhan, Mbwambo Ruth B, Mbwambo Daniel, Aaron Sijenunu, Lusasi Abdallah, Lazaro Samwel, Giesbrecht David J, Kulohoma Benard, Juliano Jonathan J, Bailey Jeffrey A, Juma Gerald, Mobegi Victor A, Ishengoma Deus S
Аннотация
INTRODUCTION: Recent evidence indicates that an increasing number of endemic countries have deployed and are using genomic surveillance to determine and monitor the trends and patterns of malaria transmission. This study aimed to evaluate and identify the most informative genetic metrics for establishing and monitoring the genetic diversity of Plasmodium falciparum and its correlation with malaria transmission intensities in Mainland Tanzania.
METHODS: A cross-sectional survey of symptomatic patients was conducted in 100 health facilities from February to July 2021 and covered 10 regions categorized into four strata based on transmission intensity. Parasite samples (n = 12,875) were collected as dried blood spots, and all samples with P. falciparum positive test by rapid diagnostic tests (n = 7,199) were sequenced using molecular inversion probes. We targeted 1,832 single nucleotide polymorphisms distributed across the 14 P. falciparum chromosomes. Raw sequence data were analyzed using MIPTools and the final dataset was used to estimate different genetic metrics.
RESULTS: The countrywide mean complexity of infection (COI) was 1.5, with 1,878 (59.6%) of parasite samples being monoclonal. The mean COI was significantly higher in high and moderate transmission strata (p < 0.001) compared to low and very low transmission strata. The odds of polyclonal infections were significantly lower in moderate, low, and very low strata compared to the high transmission stratum (p < 0.001). Parasite genetic differentiation among regions was very low, with fixation index (F ST ) values of 0-0.006. Countrywide parasite populations indicated weak genetic relatedness with pairwise identity by descent (IBD < 0.1). Few pairs (1.8%) met the thresholds of IBD ≥ 50%, and among these, the average pairs of parasites sharing ≥50% IBD were 0.89 and 0.98 for those sharing ≥90%. Discriminant analysis of principal components (DAPC) revealed overlapping parasite population clusters, suggesting genetic similarity among them.
DISCUSSION: The study revealed high complexity and polyclonality, particularly in regions with high transmission intensities. The significant association between COI, polyclonality, and transmission intensity suggests these metrics can be integrated within the current malaria surveillance system and may be useful in assessing trends and patterns of malaria transmission. Further validation is needed to link these measures with the current control strategies and evaluate their use in determining the impact of different malaria interventions in Mainland Tanzania.
METHODS: A cross-sectional survey of symptomatic patients was conducted in 100 health facilities from February to July 2021 and covered 10 regions categorized into four strata based on transmission intensity. Parasite samples (n = 12,875) were collected as dried blood spots, and all samples with P. falciparum positive test by rapid diagnostic tests (n = 7,199) were sequenced using molecular inversion probes. We targeted 1,832 single nucleotide polymorphisms distributed across the 14 P. falciparum chromosomes. Raw sequence data were analyzed using MIPTools and the final dataset was used to estimate different genetic metrics.
RESULTS: The countrywide mean complexity of infection (COI) was 1.5, with 1,878 (59.6%) of parasite samples being monoclonal. The mean COI was significantly higher in high and moderate transmission strata (p < 0.001) compared to low and very low transmission strata. The odds of polyclonal infections were significantly lower in moderate, low, and very low strata compared to the high transmission stratum (p < 0.001). Parasite genetic differentiation among regions was very low, with fixation index (F ST ) values of 0-0.006. Countrywide parasite populations indicated weak genetic relatedness with pairwise identity by descent (IBD < 0.1). Few pairs (1.8%) met the thresholds of IBD ≥ 50%, and among these, the average pairs of parasites sharing ≥50% IBD were 0.89 and 0.98 for those sharing ≥90%. Discriminant analysis of principal components (DAPC) revealed overlapping parasite population clusters, suggesting genetic similarity among them.
DISCUSSION: The study revealed high complexity and polyclonality, particularly in regions with high transmission intensities. The significant association between COI, polyclonality, and transmission intensity suggests these metrics can be integrated within the current malaria surveillance system and may be useful in assessing trends and patterns of malaria transmission. Further validation is needed to link these measures with the current control strategies and evaluate their use in determining the impact of different malaria interventions in Mainland Tanzania.