Evidence map›Paper›PMID 33630855›Full record

ArticlePLoS genetics2021

Evolutionary analyses of the major variant surface antigen-encoding genes reveal population structure of Plasmodium falciparum within and between continents.

Gerry Tonkin-Hill, Shazia Ruybal-Pesántez, Kathryn E Tiedje, Virginie Rougeron, Michael F Duffy, Sedigheh Zakeri, Tepanata Pumpaibool, Pongchai Harnyuttanakorn, OraLee H Branch, Lastenia Ruiz-Mesía and 5 more

Abstract read
In one paragraph

Article in PLoS genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. A paradoxical population structure ofbioRxiv : the preprint server for biology · 2023
    Article
  7. Article
  8. Article
  9. Molecular epidemiology of continuedFrontiers in tropical diseases · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. UnravellingFrontiers in parasitology · 2022
    Article
  14. Article
  15. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Gerry Tonkin-HillSchool of BioSciences, Bio21 Institute, The University of Melbourne, Melbourne, Australia.ORCID 0000-0003-4397-2224
Shazia Ruybal-PesántezSchool of BioSciences, Bio21 Institute, The University of Melbourne, Melbourne, Australia.ORCID 0000-0002-0495-179X
Kathryn E TiedjeSchool of BioSciences, Bio21 Institute, The University of Melbourne, Melbourne, Australia.ORCID 0000-0003-3305-0533
Virginie RougeronLaboratoire MIVEGEC, Université de Montpellier-CNRS-IRD, Montpellier, France.ORCID 0000-0001-5873-5681
Michael F DuffySchool of BioSciences, Bio21 Institute, The University of Melbourne, Melbourne, Australia.ORCID 0000-0001-5635-4033
Sedigheh ZakeriMalaria and Vector Research Group (MVRG), Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.
Tepanata PumpaiboolBiomedical Science, Graduate School, Chulalongkorn University, Bangkok, Thailand.ORCID 0000-0003-0794-2597
Pongchai HarnyuttanakornMalaria Research Programme, College of Public Health Science, Chulalongkorn University, Bangkok, Thailand.ORCID 0000-0001-9017-6656
OraLee H BranchConcordia University, Portland, Oregon, United States of America.ORCID 0000-0002-6720-6906
Lastenia Ruiz-MesíaUniversidad Nacional de la Amazonía Peruana, Iquitos, Perú.ORCID 0000-0002-9385-5416
Thomas S RaskSchool of BioSciences, Bio21 Institute, The University of Melbourne, Melbourne, Australia.
Franck PrugnolleLaboratoire MIVEGEC, Université de Montpellier-CNRS-IRD, Montpellier, France.ORCID 0000-0001-8519-1253
Anthony T PapenfussBioinformatics Division, Walter and Eliza Hall Institute, Melbourne, Australia.ORCID 0000-0002-1102-8506
Yao-Ban ChanSchool of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia.ORCID 0000-0002-8425-8775
Karen P DaySchool of BioSciences, Bio21 Institute, The University of Melbourne, Melbourne, Australia.ORCID 0000-0002-6115-6135

Funding

Temporal strain structure and response to interventions in a high endemicity region of Plasmodium falciparum R01AI149779 · NIAID · UNIVERSITY OF CHICAGO · PI DAY, KAREN PATRICIA, KORAM, KWADWO ANSAH · 2019 to 2023
$3.0M
P.falciparum var gene diversity and malaria controlR01AI084156 · NIAID · UNIVERSITY OF MELBOURNE · PI DAY, KAREN PATRICIA · 2010 to 2014
$1.9M
The impact of seasonality and vector control on the population structure of Plasmodium falciparumR01TW009670 · FIC · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DAY, KAREN PATRICIA, KORAM, KWADWO ANSAH · 2013 to 2016
$1.8M
FIC NIH HHS R01 TW009670NIAID NIH HHS R01 AI084156NIAID NIH HHS R01 AI149779
6 · The paper itself

Abstract

Malaria remains a major public health problem in many countries. Unlike influenza and HIV, where diversity in immunodominant surface antigens is understood geographically to inform disease surveillance, relatively little is known about the global population structure of PfEMP1, the major variant surface antigen of the malaria parasite Plasmodium falciparum. The complexity of the var multigene family that encodes PfEMP1 and that diversifies by recombination, has so far precluded its use in malaria surveillance. Recent studies have demonstrated that cost-effective deep sequencing of the region of var genes encoding the PfEMP1 DBLα domain and subsequent classification of within host sequences at 96% identity to define unique DBLα types, can reveal structure and strain dynamics within countries. However, to date there has not been a comprehensive comparison of these DBLα types between countries. By leveraging a bioinformatic approach (jumping hidden Markov model) designed specifically for the analysis of recombination within var genes and applying it to a dataset of DBLα types from 10 countries, we are able to describe population structure of DBLα types at the global scale. The sensitivity of the approach allows for the comparison of the global dataset to ape samples of Plasmodium Laverania species. Our analyses show that the evolution of the parasite population emerging out of Africa underlies current patterns of DBLα type diversity. Most importantly, we can distinguish geographic population structure within Africa between Gabon and Ghana in West Africa and Uganda in East Africa. Our evolutionary findings have translational implications in the context of globalization. Firstly, DBLα type diversity can provide a simple diagnostic framework for geographic surveillance of the rapidly evolving transmission dynamics of P. falciparum. It can also inform efforts to understand the presence or absence of global, regional and local population immunity to major surface antigen variants. Additionally, we identify a number of highly conserved DBLα types that are present globally that may be of biological significance and warrant further characterization.

Indexed as

Antigenic VariationAntigens, ProtozoanEvolution, MolecularGabonGhanaHumansMalaria, FalciparumMarkov ChainsModels, StatisticalPlasmodium falciparumProtein DomainsProtozoan ProteinsUgandaAntigens, Protozoanerythrocyte membrane protein 1, Plasmodium falciparumProtozoan Proteins

Identifiers

PMID33630855
PMCPMC7906310

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.