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Simulating population genetics of pathogen vectors in changing landscapes: guidelines and application with Triatoma brasiliensis.

Rebaudo F, Costa J, Almeida CE, Silvain JF, Harry M, Dangles O - PLoS Negl Trop Dis (2014)

Bottom Line: We then applied our model with Triatoma brasiliensis, originally restricted to sylvatic habitats and now found in peridomestic and domestic habitats, posing as the most important Trypanosoma cruzi vector in Northeastern Brazil.We focused on the effects of vector migration rate, maximum dispersal distance and attraction by domestic habitat on T. brasiliensis population dynamics and spatial genetic structure.Our hope is that our study may provide a testable and applicable modeling framework to a broad community of epidemiologists for formulating scenarios of landscape change consequences on vector dynamics, with potential implications for their surveillance and control.

View Article: PubMed Central - PubMed

Affiliation: BEI-UR072, IRD, Gif-sur-Yvette, France; LEGS-UPR9034, CNRS-UPSud11, Gif-sur-Yvette, France.

ABSTRACT

Background: Understanding the mechanisms that influence the population dynamics and spatial genetic structure of the vectors of pathogens infecting humans is a central issue in tropical epidemiology. In view of the rapid changes in the features of landscape pathogen vectors live in, this issue requires new methods that consider both natural and human systems and their interactions. In this context, individual-based model (IBM) simulations represent powerful yet poorly developed approaches to explore the response of pathogen vectors in heterogeneous social-ecological systems, especially when field experiments cannot be performed.

Methodology/principal findings: We first present guidelines for the use of a spatially explicit IBM, to simulate population genetics of pathogen vectors in changing landscapes. We then applied our model with Triatoma brasiliensis, originally restricted to sylvatic habitats and now found in peridomestic and domestic habitats, posing as the most important Trypanosoma cruzi vector in Northeastern Brazil. We focused on the effects of vector migration rate, maximum dispersal distance and attraction by domestic habitat on T. brasiliensis population dynamics and spatial genetic structure. Optimized for T. brasiliensis using field data pairwise fixation index (FST) from microsatellite loci, our simulations confirmed the importance of these three variables to understand vector genetic structure at the landscape level. We then ran prospective scenarios accounting for land-use change (deforestation and urbanization), which revealed that human-induced land-use change favored higher genetic diversity among sampling points.

Conclusions/significance: Our work shows that mechanistic models may be useful tools to link observed patterns with processes involved in the population genetics of tropical pathogen vectors in heterogeneous social-ecological landscapes. Our hope is that our study may provide a testable and applicable modeling framework to a broad community of epidemiologists for formulating scenarios of landscape change consequences on vector dynamics, with potential implications for their surveillance and control.

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Evolution of FST through time between two sampled locations.Each point represents the mean of 30 repetitions. Curves were fitted to the general form of a sigmoid function using nls function in R. The different colors corresponds to scenarios with selection and with land-use change (in black); with selection and without land-use change (in red); without selection and without land-use change (in blue); and without selection and with land-use change (in grey).
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pntd-0003068-g004: Evolution of FST through time between two sampled locations.Each point represents the mean of 30 repetitions. Curves were fitted to the general form of a sigmoid function using nls function in R. The different colors corresponds to scenarios with selection and with land-use change (in black); with selection and without land-use change (in red); without selection and without land-use change (in blue); and without selection and with land-use change (in grey).

Mentions: The dynamics of the spatial genetic structure of T. brasiliensis populations strongly differed between the urbanization and the "no land-use change" (control) scenarios (see Figure 4 for FST between individuals located at sampling points A and B). In the control scenarios, FST reached a threshold and stabilized within 100 generations for all couples of sampled locations (e.g., mean FST threshold value of 0.021 between A and B with and without selection, see Figure 4). Contrastingly, FST values did not reach such threshold in the urbanization scenarios (e.g., mean FST threshold value of 0.030 and 0.027 between A and B with and without selection, respectively), except between individuals at sampling locations A, C and E. We found a significant effect of land-use change on FST after 100 generations (e.g., between A and B: F = 24.6, df = 1, p<0.05). Contrastingly, the effect of selection was not significant, even if FST values were generally higher in the scenarios including selection.


Simulating population genetics of pathogen vectors in changing landscapes: guidelines and application with Triatoma brasiliensis.

Rebaudo F, Costa J, Almeida CE, Silvain JF, Harry M, Dangles O - PLoS Negl Trop Dis (2014)

Evolution of FST through time between two sampled locations.Each point represents the mean of 30 repetitions. Curves were fitted to the general form of a sigmoid function using nls function in R. The different colors corresponds to scenarios with selection and with land-use change (in black); with selection and without land-use change (in red); without selection and without land-use change (in blue); and without selection and with land-use change (in grey).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4125301&req=5

pntd-0003068-g004: Evolution of FST through time between two sampled locations.Each point represents the mean of 30 repetitions. Curves were fitted to the general form of a sigmoid function using nls function in R. The different colors corresponds to scenarios with selection and with land-use change (in black); with selection and without land-use change (in red); without selection and without land-use change (in blue); and without selection and with land-use change (in grey).
Mentions: The dynamics of the spatial genetic structure of T. brasiliensis populations strongly differed between the urbanization and the "no land-use change" (control) scenarios (see Figure 4 for FST between individuals located at sampling points A and B). In the control scenarios, FST reached a threshold and stabilized within 100 generations for all couples of sampled locations (e.g., mean FST threshold value of 0.021 between A and B with and without selection, see Figure 4). Contrastingly, FST values did not reach such threshold in the urbanization scenarios (e.g., mean FST threshold value of 0.030 and 0.027 between A and B with and without selection, respectively), except between individuals at sampling locations A, C and E. We found a significant effect of land-use change on FST after 100 generations (e.g., between A and B: F = 24.6, df = 1, p<0.05). Contrastingly, the effect of selection was not significant, even if FST values were generally higher in the scenarios including selection.

Bottom Line: We then applied our model with Triatoma brasiliensis, originally restricted to sylvatic habitats and now found in peridomestic and domestic habitats, posing as the most important Trypanosoma cruzi vector in Northeastern Brazil.We focused on the effects of vector migration rate, maximum dispersal distance and attraction by domestic habitat on T. brasiliensis population dynamics and spatial genetic structure.Our hope is that our study may provide a testable and applicable modeling framework to a broad community of epidemiologists for formulating scenarios of landscape change consequences on vector dynamics, with potential implications for their surveillance and control.

View Article: PubMed Central - PubMed

Affiliation: BEI-UR072, IRD, Gif-sur-Yvette, France; LEGS-UPR9034, CNRS-UPSud11, Gif-sur-Yvette, France.

ABSTRACT

Background: Understanding the mechanisms that influence the population dynamics and spatial genetic structure of the vectors of pathogens infecting humans is a central issue in tropical epidemiology. In view of the rapid changes in the features of landscape pathogen vectors live in, this issue requires new methods that consider both natural and human systems and their interactions. In this context, individual-based model (IBM) simulations represent powerful yet poorly developed approaches to explore the response of pathogen vectors in heterogeneous social-ecological systems, especially when field experiments cannot be performed.

Methodology/principal findings: We first present guidelines for the use of a spatially explicit IBM, to simulate population genetics of pathogen vectors in changing landscapes. We then applied our model with Triatoma brasiliensis, originally restricted to sylvatic habitats and now found in peridomestic and domestic habitats, posing as the most important Trypanosoma cruzi vector in Northeastern Brazil. We focused on the effects of vector migration rate, maximum dispersal distance and attraction by domestic habitat on T. brasiliensis population dynamics and spatial genetic structure. Optimized for T. brasiliensis using field data pairwise fixation index (FST) from microsatellite loci, our simulations confirmed the importance of these three variables to understand vector genetic structure at the landscape level. We then ran prospective scenarios accounting for land-use change (deforestation and urbanization), which revealed that human-induced land-use change favored higher genetic diversity among sampling points.

Conclusions/significance: Our work shows that mechanistic models may be useful tools to link observed patterns with processes involved in the population genetics of tropical pathogen vectors in heterogeneous social-ecological landscapes. Our hope is that our study may provide a testable and applicable modeling framework to a broad community of epidemiologists for formulating scenarios of landscape change consequences on vector dynamics, with potential implications for their surveillance and control.

Show MeSH