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Population Dynamics of Underdominance Gene Drive Systems in Continuous Space.

ABSTRACT: Underdominance systems can quickly spread through a population, but only when introduced in considerable numbers. This promises a gene drive mechanism that is less invasive than homing drives, potentially enabling new approaches in the fight against vector-borne diseases. If regional confinement can indeed be achieved, the decision-making process for a release would likely be much simpler compared to other, more invasive types of drives. The capacity of underdominance gene drive systems to spread in a target population without invading other populations is typically assessed via network models of panmictic demes linked by migration. However, it remains less clear how such systems would behave in more realistic population models where organisms move over a continuous landscape. Here, we use individual-based simulations to study the dynamics of several proposed underdominance systems in continuous-space. We find that all these systems can fail to persist in such environments, even after an initially successful establishment in the release area, confirming previous theoretical results from diffusion theory. At the same time, we find that a two-locus two-toxin-antidote system can invade connected demes through a narrow migration corridor. This suggests that the parameter space where underdominance systems can establish and persist in a release area while at the same time remaining confined to that area could be quite limited, depending on how a population is spatially structured. Overall, these results indicate that realistic spatial context must be considered when assessing strategies for the deployment of underdominance drives.

SUBMITTER: Champer J

PROVIDER: S-EPMC8284921 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Interest in gene drive technology has continued to grow as promising new drive systems have been developed in the lab and discussions are moving towards implementing field trials. The prospect of field trials requires models that incorporate a significant degree of ecological detail, including parameters that change over time in response to environmental data such as temperature and rainfall, leading to seasonal patterns in mosquito population density. Epidemiological outcomes are also of growing importance, as: i) the suitability of a gene drive construct for release will depend on its expected impact on disease transmission, and ii) initial field trials are expected to have a measured entomological outcome and a modeled epidemiological outcome. We present MGDrivE 2 (Mosquito Gene Drive Explorer 2): a significant development from the MGDrivE 1 simulation framework that investigates the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. Key strengths and fundamental improvements of the MGDrivE 2 framework are: i) the ability of parameters to vary with time and induce seasonal population dynamics, ii) an epidemiological module accommodating reciprocal pathogen transmission between humans and mosquitoes, and iii) an implementation framework based on stochastic Petri nets that enables efficient model formulation and flexible implementation. Example MGDrivE 2 simulations are presented to demonstrate the application of the framework to a CRISPR-based split gene drive system intended to drive a disease-refractory gene into a population in a confinable and reversible manner, incorporating time-varying temperature and rainfall data. The simulations also evaluate impact on human disease incidence and prevalence. Further documentation and use examples are provided in vignettes at the project's CRAN repository. MGDrivE 2 is freely available as an open-source R package on CRAN (https://CRAN.R-project.org/package=MGDrivE2). We intend the package to provide a flexible tool capable of modeling gene drive constructs as they move closer to field application and to infer their expected impact on disease transmission.

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Population Dynamics of Underdominance Gene Drive Systems in Continuous Space.

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