A Y chromosome-linked genome editor for efficient population suppression in the malaria vector Anopheles gambiae.

Genetic control - the deliberate introduction of genetic traits to control a pest or vector population - offers a powerful tool to augment conventional mosquito control tools that have been successful in reducing malaria burden but that are compromised by a range of operational challenges. Self-sustaining genetic control strategies have shown great potential in laboratory settings, but hesitancy due to their invasive and persistent nature may delay their implementation. Here, instead, we describe a self-limiting strategy, designed to have geographically and temporally restricted effect, based on a Y chromosome-linked genome editor (YLE).

Prenatal exposure to pesticide mixtures and the placental transcriptome: Insights from trimester-specific, sex-specific and metabolite-scaled analyses in the SAWASDEE cohort.

We investigated the effect of exposure to pesticide mixtures during pregnancy on the placental transcriptome, to link these exposures and placental functions. The Study of Asian Women and their Offspring's Development and Environmental Exposures (SAWASDEE) enrolled pregnant farmworkers from Thailand (n = 248), who were primarily exposed to organophosphate (OP) and pyrethroid pesticides. We measured maternal urinary levels of six non-specific OP metabolites expressed as three summary measures (dimethylalkylphosphates (DMAP), diethylalkylphosphates (DEAP), and dialkylphosphates (DAP) and three pyrethroid metabolites (3-phenoxybenzoic acid (3-PBA), cis- and trans-3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (cis-DCCA, trans-DCCA) during early, middle, and late pregnancy, and adjusted for urine dilution using creatinine.

The potential of gene drives in malaria vector species to control malaria in African environments.

Gene drives are a promising means of malaria control with the potential to cause sustained reductions in transmission. In real environments, however, their impacts will depend on local ecological and epidemiological factors. We develop a data-driven model to investigate the impacts of gene drives that causes vector population suppression.