| Literature DB >> 22440199 |
Michael D French1, Thomas S Churcher, María-Gloria Basáñez, Alice J Norton, Nicholas J S Lwambo, Joanne P Webster.
Abstract
Detecting potential changes in genetic diversity in schistosome populations following chemotherapy with praziquantel (PZQ) is crucial if we are to fully understand the impact of such chemotherapy with respect to the potential emergence of resistance and/or other evolutionary outcomes of interventions. Doing so by implementing effective, and cost-efficient sampling protocols will help to optimise time and financial resources, particularly relevant to a disease such as schistosomiasis currently reliant on a single available drug. Here we explore the effect on measures of parasite genetic diversity of applying various field sampling approaches, both in terms of the number of (human) hosts sampled and the number of transmission stages (miracidia) sampled per host for a Schistosoma mansoni population in Tanzania pre- and post-treatment with PZQ. In addition, we explore population structuring within and between hosts by comparing the estimates of genetic diversity obtained assuming a 'component population' approach with those using an 'infrapopulation' approach. We found that increasing the number of hosts sampled, rather than the number of miracidia per host, gives more robust estimates of genetic diversity. We also found statistically significant population structuring (using Wright's F-statistics) and significant differences in the measures of genetic diversity depending on the parasite population definition. The relative advantages, disadvantages and, hence, subsequent reliability of these metrics for parasites with complex life-cycles are discussed, both for the specific epidemiological and ecological scenario under study here and for their future application to other areas and schistosome species.Entities:
Keywords: Monitoring and evaluation; Population genetics; Praziquantel; Preventive chemotherapy; Sampling protocol; Schistosoma mansoni; Stochastic re-sampling; Tanzania
Mesh:
Substances:
Year: 2012 PMID: 22440199 DOI: 10.1016/j.actatropica.2012.03.001
Source DB: PubMed Journal: Acta Trop ISSN: 0001-706X Impact factor: 3.112