Initiative Publications

Population modification of Anopheline species to control malaria transmission

Rebeca Carballar-Lejarazú &Anthony A. James


Vector control strategies based on population modification of Anopheline mosquitoes may have a significant role in the malaria eradication agenda. They could consolidate elimination gains by providing barriers to the reintroduction of parasites and competent vectors, and allow resources to be allocated to new control sites while maintaining treated areas free of malaria. Synthetic biological approaches are being used to generate transgenic mosquitoes for population modification. Proofs-of-principle exist for mosquito transgenesis, the construction of anti-parasite effector genes and gene-drive systems for rapidly introgressing beneficial genes into wild populations. Key challenges now are to develop field-ready strains of mosquitoes that incorporate features that maximize safety and efficacy, and specify pathways from discovery to development. We propose three pathways and a framework for target product profiles that maximize safety and efficacy while meeting the demands of the complexity of malaria transmission, and the regulatory and social diversity of potential end-users and stakeholders.

CRISPR in Sub-Saharan Africa: Applications and Education

Christian E. Ogaugwu,1,2,4, Stanley O. Agbo,2 and Modinat A. Adekoya3


Clustered regularly interspaced short palindromic repeats (CRISPR) technology has enabled genetic engineering feats previously considered impracticable, offering great hopes for solutions to problems facing society. We consider it timely to highlight how CRISPR can benefit public health, medicine, and agriculture in sub-Saharan Africa (SSA) and offer recommendations for successful implementation.


Introgression between Anopheles gambiae and Anopheles coluzzii in Burkina Faso and its associations with kdr resistance and Plasmodium infection


Mark J. Hanemaaijer, Hannah Higgins, Ipek Eralp, Youki Yamasaki, Norbert Becker, Oscar D. Kirstein, Gregory C. Lanzaro, Yoosook Lee
Insecticide resistance in Anopheles coluzzii mosquitoes has become widespread throughout West Africa including in Burkina Faso. The insecticide resistance allele (kdr or L1014F) is a prime indicator that is highly correlated with phenotypic resistance in West Africa. Studies from Benin, Ghana and Mali have suggested that the source of the L1014F is introgression of the 2L divergence island via interspecific hybridization with Anopheles gambiae. The goal of this study was to characterize local mosquito populations in the Nouna Department, Burkina Faso with respect to: (i) the extent of introgression between An. coluzzii and An. gambiae, (ii) the frequency of the L1014F mutation and (iii) Plasmodium infection rates.

Split-gene drive system provides flexible application for safe laboratory investigation and potential field deployment

Victor Lopez Del Amo1, Alena L. Bishop1, Hector Sanchez C.2, Jared B. Bennett3, Xuechun Feng1, John M. Marshall2, Ethan Bier1, Valentino M. Gantz1*.


CRISPR-based gene drives spread through populations bypassing the dictates of Mendelian genetics, offering a population-engineering tool for tackling vector-borne diseases, managing crop pests, and helping island conservation efforts; unfortunately, current technologies raise safety concerns for unintended gene propagation. Herein, we address this by splitting the two drive components, Cas9 and gRNAs, into separate alleles to form a novel trans-complementing split–gene-drive (tGD) and demonstrate its ability to promote super-Mendelian inheritance of the separate transgenes. This bi-component nature allows for individual transgene optimization and increases safety by restricting escape concerns to experimentation windows. We employ the tGD and a small– molecule-controlled version to investigate the biology of component inheritance and use our system to study the maternal effects on CRISPR inheritance, impaired homology on efficiency, and resistant allele formation. Lastly, mathematical modeling of tGD spread in a population shows potential advantages for improving current gene-drive technologies for field population modification.

MGDrivE: A modular simulation framework for the spread of gene drives through spatially-explicit mosquito populations

Hector M. Sanchez C.1*, Sean L. Wu1 ‡, Jared B. Bennett2 ‡, John M. Marshall1,3*



Malaria, dengue, Zika, and other mosquito-borne diseases continue to pose a major global health burden through much of the world, despite the widespread distribution of insecticide-based tools and antimalarial drugs. The advent of CRISPR/Cas9-based gene editing and its demonstrated ability to streamline the development of gene drive systems has reignited interest in the application of this technology to the control of mosquitoes and the diseases they transmit. The versatility of this technology has also enabled a wide range of gene drive architectures to be realized, creating a need for their population-level and spatial dynamics to be explored. To this end, we present MGDrivE (Mosquito Gene Drive Explorer): a simulation framework designed to investigate the population dynamics of a variety of gene drive architectures and their spread through 10 spatially-explicit mosquito populations. A key strength of the MGDrivE framework is 11 its modularity: a) a genetic inheritance module accommodates the dynamics of gene 12 drive systems displaying user-defined inheritance patterns, b) a population dynamic 13 module accommodates the life history of a variety of mosquito disease vectors and insect 14 agricultural pest species, and c) a landscape module accommodates the distribution of 15 insect metapopulations connected by migration in space. Example MGDrivE 16 simulations are presented to demonstrate the application of the framework to 1CRISPR/Cas9-based homing gene drive for: a) driving a disease-refractory gene into a 18 population (i.e. population replacement), and b) disrupting a gene required for female 19 fertility (i.e. population suppression), incorporating homing-resistant alleles in both 20 cases. We compare MGDrivE with other genetic simulation packages, and conclude 21 with a discussion of future directions in gene drive modeling.