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Local population structure of Plasmodium: impact on malaria control and elimination

Stella M Chenet12, Kristan A Schneider34, Leopoldo Villegas56 and Ananias A Escalante12*

Author Affiliations

1 School of Life Sciences, Arizona State University, Tempe, AZ, USA

2 Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ, USA

3 Department MNI, University of Applied Sciences Mittweida, Mittweida, Germany

4 Department of Mathematics, University of Vienna, Vienna, Austria

5 Centro de Investigación de Campo Francesco Vitanza, Tumeremo, Bolívar State, Venezuela

6 ICF International, International Health & Development Division, Calverton, MD, USA

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Malaria Journal 2012, 11:412  doi:10.1186/1475-2875-11-412

Published: 11 December 2012

Abstract

Background

Regardless of the growing interest in detecting population structures in malarial parasites, there have been limited discussions on how to use this concept in control programmes. In such context, the effects of the parasite population structures will depend on interventions’ spatial or temporal scales. This investigation explores the problem of identifying genetic markers, in this case microsatellites, to unveil Plasmodium genetic structures that could affect decisions in the context of elimination. The study was performed in a low-transmission area, which offers a good proxy to better understand problems associated with surveillance at the final stages of malaria elimination.

Methods

Plasmodium vivax samples collected in Tumeremo, Venezuela, between March 2003 and November 2004 were analysed. Since Plasmodium falciparum also circulates in many low endemic areas, P. falciparum samples from the same locality and time period were included for comparison. Plasmodium vivax samples were assayed for an original set of 25 microsatellites and P. falciparum samples were assayed for 12 microsatellites.

Results

Not all microsatellite loci assayed offered reliable local data. A complex temporal-cluster dynamics is found in both P. vivax and P. falciparum. Such dynamics affect the numbers and the type of microsatellites required for identifying individual parasites or parasite clusters when performing cross-sectional studies. The minimum number of microsatellites required to differentiate circulating P. vivax clusters differs from the minimum number of hyper-variable microsatellites required to distinguish individuals within these clusters. Regardless the extended number of microsatellites used in P. vivax, it was not possible to separate all individual infections.

Conclusions

Molecular surveillance has great potential; however, it requires preliminary local studies in order to properly interpret the emerging patterns in the context of elimination. Clonal expansions and clusters turnovers need to be taken into account when using molecular markers. Those affect the number and type of microsatellite markers, as well as, the expected genetic patterns in the context of operational investigations. By considering the local dynamics, elimination programmes could cost-effectively use molecular markers. However, population level studies need to consider the local limitations of a given set of loci in terms of providing epidemiologically relevant information.

Keywords:
Plasmodium; Malaria control; Population structure; Microsatellites; Recrudescence; Linkage disequilibrium