MGD riv E: A modular simulation framework for the spread of gene drives through spatially explicit mosquito populations

HM, Antoshechkin I, Marshall JM, Akbari OS. Eliminating malaria vectors with precision-guided sterile males

Controlling the principal African malaria vector, the mosquito Anopheles gambiae, is considered essential to curtail malaria transmission. However, existing vector control technologies rely on insecticides, which are becoming increasingly ineffective. Sterile insect technique (SIT) is a powerful suppression approach that has successfully eradicated a number of insect pests, yet the A. gambiae toolkit lacks the requisite technologies for its implementation. SIT relies on iterative mass releases of nonbiting, nondriving, sterile males which seek out and mate with monandrous wild females. Once mated, females are permanently sterilized due to mating-induced refractoriness, which results in population suppression of the subsequent generation. However, sterilization by traditional methods renders males unfit, making the creation of precise genetic sterilization methods imperative. Here, we introduce a vector control technology termed precision-guided sterile insect technique (pgSIT), in A. gambiae for inducible, programmed male sterilization and female elimination for wide-scale use in SIT campaigns. Using a binary CRISPR strategy, we cross separate engineered Cas9 and gRNA strains to disrupt male-fertility and female-essential genes, yielding >99.5% male sterility and >99.9% female lethality in hybrid progeny. We demonstrate that these genetically sterilized males have good longevity, are able to induce sustained population suppression in cage trials, and are predicted to eliminate wild A. gambiae populations using mathematical models, making them ideal candidates for release. This work provides a valuable addition to the malaria genetic biocontrol toolkit, enabling scalable SIT-like confinable, species-specific, and safe suppression in the species.

HM, Marshall JM. MGDrivE 3: A decoupled vector-human framework for epidemiological simulation of mosquito genetic control tools and their surveillance

Novel mosquito genetic control tools, such as CRISPR-based gene drives, hold great promise in reducing the global burden of vector-borne diseases. As these technologies advance through the research and development pipeline, there is a growing need for modeling frameworks incorporating increasing levels of entomological and epidemiological detail in order to address questions regarding logistics and biosafety. Epidemiological predictions are becoming increasingly relevant to the development of target product profiles and the design of field trials and interventions, while entomological surveillance is becoming increasingly important to regulation and biosafety. We present MGDrivE 3 (Mosquito Gene Drive Explorer 3), a new version of a previously-developed framework, MGDrivE 2, that investigates the spatial population dynamics of mosquito genetic control systems and their epidemiological implications. The new framework incorporates three major developments: i) a decoupled sampling algorithm allowing the vector portion of the MGDrivE framework to be paired with a more detailed epidemiological framework, ii) a version of the Imperial College London malaria transmission model, which incorporates age structure, various forms of immunity, and human and vector interventions, and iii) a surveillance module that tracks mosquitoes captured by traps throughout the simulation. Example MGDrivE 3 simulations are presented demonstrating the application of the framework to a CRISPR-based homing gene drive linked to dual disease-refractory genes and their potential to interrupt local malaria transmission. Simulations are also presented demonstrating surveillance of such a system by a network of mosquito traps. MGDrivE 3 is freely available as an open-source R package on CRAN (https://cran.r-project.org/package=MGDrivE2) (version 2.1.0), and extensive examples and vignettes are provided. We intend the software to aid in understanding of human health impacts and biosafety of mosquito genetic control tools, and continue to iterate per feedback from the genetic control community.

Genetic and geographic population structure in the malaria vector, Anopheles farauti, provides a candidate system for pioneering confinable gene-drive releases

Indoor insecticide applications are the primary tool for reducing malaria transmission in the Solomon Archipelago, a region where Anopheles farauti is the only common malaria vector. Due to the evolution of behavioural resistance in some An. farauti populations, these applications have become less effective. New malaria control interventions are therefore needed in this region, and gene-drives provide a promising new technology. In considering developing a population-specific (local) gene-drive in An. farauti, we detail the species' population genetic structure using microsatellites and whole mitogenomes, finding many spatially confined populations both within and between landmasses. This strong population structure suggests that An. farauti would be a useful system for developing a population-specific, confinable gene-drive for field release, where private alleles can be used as Cas9 targets. Previous work on Anopheles gambiae has used the Cardinal gene for the development of a global population replacement gene-drive. We therefore also analyse the Cardinal gene to assess whether it may be a suitable target to engineer a gene-drive for the modification of local An. farauti populations. Despite the extensive population structure observed in An. farauti for microsatellites, only one remote island population from Vanuatu contained fixed and private alleles at the Cardinal locus. Nonetheless, this study provides an initial framework for further population genomic investigations to discover high-frequency private allele targets in localized An. farauti populations. This would enable the development of gene-drive strains for modifying localised populations with minimal chance of escape and may provide a low-risk route to field trial evaluations.

MGSurvE: A framework to optimize trap placement for genetic surveillance of mosquito populations

Genetic surveillance of mosquito populations is becoming increasingly relevant as genetics-based mosquito control strategies advance from laboratory to field testing. Especially applicable are mosquito gene drive projects, the potential scale of which leads monitoring to be a significant cost driver. For these projects, monitoring will be required to detect unintended spread of gene drive mosquitoes beyond field sites, and the emergence of alternative alleles, such as drive-resistant alleles or non-functional effector genes, within intervention sites. This entails the need to distribute mosquito traps efficiently such that an allele of interest is detected as quickly as possible-ideally when remediation is still viable. Additionally, insecticide-based tools such as bednets are compromised by insecticide-resistance alleles for which there is also a need to detect as quickly as possible. To this end, we present MGSurvE (Mosquito Gene SurveillancE): a computational framework that optimizes trap placement for genetic surveillance of mosquito populations such that the time to detection of an allele of interest is minimized. A key strength of MGSurvE is that it allows important biological features of mosquitoes and the landscapes they inhabit to be accounted for, namely: i) resources required by mosquitoes (e.g., food sources and aquatic breeding sites) can be explicitly distributed through a landscape, ii) movement of mosquitoes may depend on their sex, the current state of their gonotrophic cycle (if female) and resource attractiveness, and iii) traps may differ in their attractiveness profile. Example MGSurvE analyses are presented to demonstrate optimal trap placement for: i) an Aedes aegypti population in a suburban landscape in Queensland, Australia, and ii) an Anopheles gambiae population on the island of São Tomé, São Tomé and Príncipe. Further documentation and use examples are provided in project's documentation. MGSurvE is intended as a resource for both field and computational researchers interested in mosquito gene surveillance.

Targeting sex determination to suppress mosquito populations

Each year, hundreds of millions of people are infected with arboviruses such as dengue, yellow fever, chikungunya, and Zika, which are all primarily spread by the notorious mosquito Aedes aegypti. Traditional control measures have proven insufficient, necessitating innovations. In response, here we generate a next-generation CRISPR-based precision-guided sterile insect technique (pgSIT) for Ae. aegypti that disrupts genes essential for sex determination and fertility, producing predominantly sterile males that can be deployed at any life stage. Using mathematical models and empirical testing, we demonstrate that released pgSIT males can effectively compete with, suppress, and eliminate caged mosquito populations. This versatile species-specific platform has the potential for field deployment to effectively control wild populations of disease vectors.

Gene drives for the extinction of wild metapopulations

Population-suppressing gene drives may be capable of extinguishing wild populations, with proposed applications in conservation, agriculture, and public health. However, unintended and potentially disastrous consequences of release of drive-engineered individuals are extremely difficult to predict. We propose a model for the dynamics of a sex ratio-biasing drive, and using simulations, we show that failure of the suppression drive is often a natural outcome due to stochastic and spatial effects. We further demonstrate rock-paper-scissors dynamics among wild-type, drive-infected, and extinct populations that can persist for arbitrarily long times. Gene drive-mediated extinction of wild populations entails critical complications that lurk far beyond the reach of laboratory-based studies. Our findings help in addressing these challenges.

Repeat mediated excision of gene drive elements for restoring wild-type populations

We demonstrate here that single strand annealing (SSA) repair can be co-opted for the precise autocatalytic excision of a drive element. Although SSA is not the predominant form of DNA repair in eukaryotic organisms, we increased the likelihood of its use by engineering direct repeats at sites flanking the drive allele, and then introducing a double-strand DNA break (DSB) at a second endonuclease target site encoded within the drive allele. We have termed this technology Re peat M ediated E xcision of a D rive E lement (ReMEDE). Incorporation of ReMEDE into the previously described mutagenic chain reaction (MCR) gene drive, targeting the yellow gene of Drosophila melanogaster , replaced drive alleles with wild-type alleles demonstrating proof-of-principle. Although the ReMEDE system requires further research and development, the technology has a number of attractive features as a gene drive mitigation strategy, chief among these the potential to restore a wild-type population without releasing additional transgenic organisms or large-scale environmental engineering efforts.

HM, Zhan Y, DeBeaubien NA, Loh YM, Su MP, Montell C, Marshall JM, Akbari OS. Targeting Sex Determination to Suppress Mosquito Populations

Each year, hundreds of millions of people are infected with arboviruses such as dengue, yellow fever, chikungunya, and Zika, which are all primarily spread by the notorious mosquito Aedes aegypti. Traditional control measures have proven insufficient, necessitating innovations. In response, here we generate a next generation CRISPR-based precision-guided sterile insect technique (pgSIT) for Aedes aegypti that disrupts genes essential for sex determination and fertility, producing predominantly sterile males that can be deployed at any life stage. Using mathematical models and empirical testing, we demonstrate that released pgSIT males can effectively compete with, suppress, and eliminate caged mosquito populations. This versatile species-specific platform has the potential for field deployment to effectively control wild populations of disease vectors.

Expansions to the MGDrivE suite for simulating the efficacy of novel gene-drive constructs in the control of mosquito-borne diseases

OBJECTIVE

The MGDrivE (MGDrivE 1 and MGDrivE 2) modeling framework provides a flexible and expansive environment for testing the efficacy of novel gene-drive constructs for the control of mosquito-borne diseases. However, the existing model framework did not previously support several features necessary to simulate some types of intervention strategies. Namely, current MGDrivE versions do not permit modeling of small molecule inducible systems for controlling gene expression in gene drive designs or the inheritance patterns of self-eliminating gene drive mechanisms.

RESULTS

Here, we demonstrate a new MGDrivE 2 module that permits the simulation of gene drive strategies incorporating small molecule-inducible systems and self-eliminating gene drive mechanisms. Additionally, we also implemented novel sparsity-aware sampling algorithms for improved computational efficiency in MGDrivE 2 and supplied an analysis and plotting function applicable to the outputs of MGDrivE 1 and MGDrivE 2.

HMS, Marshall JM. MGDrivE 3: A decoupled vector-human framework for epidemiological simulation of mosquito genetic control tools and their surveillance

Novel mosquito genetic control tools, such as CRISPR-based gene drives, hold great promise in reducing the global burden of vector-borne diseases. As these technologies advance through the research and development pipeline, there is a growing need for modeling frameworks incorporating increasing levels of entomological and epidemiological detail in order to address questions regarding logistics and biosafety. Epidemiological predictions are becoming increasingly relevant to the development of target product profiles and the design of field trials and interventions, while entomological surveillance is becoming increasingly important to regulation and biosafety. We present MGDrivE 3 (Mosquito Gene Drive Explorer 3), a new version of a previously-developed framework, MGDrivE 2, that investigates the spatial population dynamics of mosquito genetic control systems and their epidemiological implications. The new framework incorporates three major developments: i) a decoupled sampling algorithm allowing the vector portion of the MGDrivE framework to be paired with a more detailed epidemiological framework, ii) a version of the Imperial College London malaria transmission model, which incorporates age structure, various forms of immunity, and human and vector interventions, and iii) a surveillance module that tracks mosquitoes captured by traps throughout the simulation. Example MGDrivE 3 simulations are presented demonstrating the application of the framework to a CRISPR-based homing gene drive linked to dual disease-refractory genes and their potential to interrupt local malaria transmission. Simulations are also presented demonstrating surveillance of such a system by a network of mosquito traps. MGDrivE 3 is freely available as an open-source R package on CRAN (https://cran.r-project.org/package=MGDrivE2) (version 2.1.0), and extensive examples and vignettes are provided. We intend the software to aid in understanding of human health impacts and biosafety of mosquito genetic control tools, and continue to iterate per feedback from the genetic control community.

Incorporating ecology into gene drive modelling

Gene drive technology, in which fast-spreading engineered drive alleles are introduced into wild populations, represents a promising new tool in the fight against vector-borne diseases, agricultural pests and invasive species. Due to the risks involved, gene drives have so far only been tested in laboratory settings while their population-level behaviour is mainly studied using mathematical and computational models. The spread of a gene drive is a rapid evolutionary process that occurs over timescales similar to many ecological processes. This can potentially generate strong eco-evolutionary feedback that could profoundly affect the dynamics and outcome of a gene drive release. We, therefore, argue for the importance of incorporating ecological features into gene drive models. We describe the key ecological features that could affect gene drive behaviour, such as population structure, life-history, environmental variation and mode of selection. We review previous gene drive modelling efforts and identify areas where further research is needed. As gene drive technology approaches the level of field experimentation, it is crucial to evaluate gene drive dynamics, potential outcomes, and risks realistically by including ecological processes.

HM, Antoshechkin I, Marshall JM, Akbari OS. Eliminating Malaria Vectors with Precision Guided Sterile Males

Controlling the principal African malaria vector, the mosquito Anopheles gambiae, is considered essential to curtail malaria transmission. However existing vector control technologies rely on insecticides, which are becoming increasingly ineffective. Sterile insect technique (SIT) is a powerful suppression approach that has successfully eradicated a number of insect pests, yet the A. gambiae toolkit lacks the requisite technologies for its implementation. SIT relies on iterative mass-releases of non-biting, non-driving, sterile males which seek out and mate with monandrous wild females. Once mated, females are permanently sterilized due to mating-induced refractoriness, which results in population suppression of the subsequent generation. However, sterilization by traditional methods renders males unfit, making the creation of precise genetic sterilization methods imperative. Here we develop precision guided Sterile Insect Technique (pgSIT) in the mosquito A. gambiae for inducible, programmed male-sterilization and female-elimination for wide scale use in SIT campaigns. Using a binary CRISPR strategy, we cross separate engineered Cas9 and gRNA strains to disrupt male-fertility and female-essential genes, yielding >99.5% male-sterility and >99.9% female-lethality in hybrid progeny. We demonstrate that these genetically sterilized males have good longevity, are able to induce population suppression in cage trials, and are predicted to eliminate wild A. gambiae populations using mathematical models, making them ideal candidates for release. This work provides a valuable addition to the malaria genetic biocontrol toolkit, for the first time enabling scalable SIT-like confinable suppression in the species.

HM, Lee HF, Marshall JM, Dimopoulos G, James AA. Dual effector population modification gene-drive strains of the African malaria mosquitoes, Anopheles gambiae and Anopheles coluzzii

Proposed genetic approaches for reducing human malaria include population modification, which introduces genes into vector mosquitoes to reduce or prevent parasite transmission. We demonstrate the potential of Cas9/guide RNA (gRNA)-based gene-drive systems linked to dual antiparasite effector genes to spread rapidly through mosquito populations. Two strains have an autonomous gene-drive system coupled to dual anti-Plasmodium falciparum effector genes comprising single-chain variable fragment monoclonal antibodies targeting parasite ookinetes and sporozoites in the African malaria mosquitoes Anopheles gambiae (AgTP13) and Anopheles coluzzii (AcTP13). The gene-drive systems achieved full introduction within 3 to 6 mo after release in small cage trials. Life-table analyses revealed no fitness loads affecting AcTP13 gene-drive dynamics but AgTP13 males were less competitive than wild types. The effector molecules reduced significantly both parasite prevalence and infection intensities. These data supported transmission modeling of conceptual field releases in an island setting that shows meaningful epidemiological impacts at different sporozoite threshold levels (2.5 to 10 k) for human infection by reducing malaria incidence in optimal simulations by 50 to 90% within as few as 1 to 2 mo after a series of releases, and by ≥90% within 3 mo. Modeling outcomes for low sporozoite thresholds are sensitive to gene-drive system fitness loads, gametocytemia infection intensities during parasite challenges, and the formation of potentially drive-resistant genome target sites, extending the predicted times to achieve reduced incidence. TP13-based strains could be effective for malaria control strategies following validation of sporozoite transmission threshold numbers and testing field-derived parasite strains. These or similar strains are viable candidates for future field trials in a malaria-endemic region.

HM, Corder RM, Jeffrey Gutiérrez E, Thakre N, Antoshechkin I, Marshall JM, Akbari OS. A confinable female-lethal population suppression system in the malaria vector, Anopheles gambiae

Malaria is among the world's deadliest diseases, predominantly affecting Sub-Saharan Africa and killing over half a million people annually. Controlling the principal vector, the mosquito Anopheles gambiae, as well as other anophelines, is among the most effective methods to control disease spread. Here, we develop a genetic population suppression system termed Ifegenia (inherited female elimination by genetically encoded nucleases to interrupt alleles) in this deadly vector. In this bicomponent CRISPR-based approach, we disrupt a female-essential gene, femaleless (fle), demonstrating complete genetic sexing via heritable daughter gynecide. Moreover, we demonstrate that Ifegenia males remain reproductively viable and can load both fle mutations and CRISPR machinery to induce fle mutations in subsequent generations, resulting in sustained population suppression. Through modeling, we demonstrate that iterative releases of nonbiting Ifegenia males can act as an effective, confinable, controllable, and safe population suppression and elimination system.

MGSurvE: A framework to optimize trap placement for genetic surveillance of mosquito population

Genetic surveillance of mosquito populations is becoming increasingly relevant as genetics-based mosquito control strategies advance from laboratory to field testing. Especially applicable are mosquito gene drive projects, the potential scale of which leads monitoring to be a significant cost driver. For these projects, monitoring will be required to detect unintended spread of gene drive mosquitoes beyond field sites, and the emergence of alternative alleles, such as drive-resistant alleles or non-functional effector genes, within intervention sites. This entails the need to distribute mosquito traps efficiently such that an allele of interest is detected as quickly as possible - ideally when remediation is still viable. Additionally, insecticide-based tools such as bednets are compromised by insecticide-resistance alleles for which there is also a need to detect as quickly as possible. To this end, we present MGSurvE (Mosquito Gene SurveillancE): a computational framework that optimizes trap placement for genetic surveillance of mosquito populations such that the time to detection of an allele of interest is minimized. A key strength of MGSurvE is that it allows important biological features of mosquitoes and the landscapes they inhabit to be accounted for, namely: i) resources required by mosquitoes (e.g., food sources and aquatic breeding sites) can be explicitly distributed through a landscape, ii) movement of mosquitoes may depend on their sex, the current state of their gonotrophic cycle (if female) and resource attractiveness, and iii) traps may differ in their attractiveness profile. Example MGSurvE analyses are presented to demonstrate optimal trap placement for: i) an Aedes aegypti population in a suburban landscape in Queensland, Australia, and ii) an Anopheles gambiae population on the island of São Tomé, São Tomé and Príncipe. Further documentation and use examples are provided in project's documentation. MGSurvE is freely available as an open-source Python package on pypi (https://pypi.org/project/MGSurvE/). It is intended as a resource for both field and computational researchers interested in mosquito gene surveillance.

Targeting Sex Determination to Suppress Mosquito Populations

Each year, hundreds of millions of people are infected with arboviruses such as dengue, yellow fever, chikungunya, and Zika, which are all primarily spread by the notorious mosquito Aedes aegypti. Traditional control measures have proven insuficient, necessitating innovations. In response, here we generate a next generation CRISPR-based precision-guided sterile insect technique (pgSIT) for Aedes aegypti that disrupts genes essential for sex determination and fertility, producing predominantly sterile males that can be deployed at any life stage. Using mathematical models and empirical testing, we demonstrate that released pgSIT males can effectively compete with, suppress, and eliminate caged mosquito populations. This versatile species-specific platform has the potential for field deployment to control wild populations, safely curtailing disease transmission.

Genetic conversion of a split-drive into a full-drive element

The core components of CRISPR-based gene drives, Cas9 and guide RNA (gRNA), either can be linked within a self-contained single cassette (full gene-drive, fGD) or be provided in two separate elements (split gene-drive, sGD), the latter offering greater control options. We previously engineered split systems that could be converted genetically into autonomous full drives. Here, we examine such dual systems inserted at the spo11 locus that are recoded to restore gene function and thus organismic fertility. Despite minimal differences in transmission efficiency of the sGD or fGD drive elements in single generation crosses, the reconstituted spo11 fGD cassette surprisingly exhibits slower initial drive kinetics than the unlinked sGD element in multigenerational cage studies, but then eventually catches up to achieve a similar level of final introduction. These unexpected kinetic behaviors most likely reflect differing transient fitness costs associated with individuals co-inheriting Cas9 and gRNA transgenes during the drive process.

Close-kin mark-recapture methods to estimate demographic parameters of mosquitoes

Close-kin mark-recapture (CKMR) methods have recently been used to infer demographic parameters such as census population size and survival for fish of interest to fisheries and conservation. These methods have advantages over traditional mark-recapture methods as the mark is genetic, removing the need for physical marking and recapturing that may interfere with parameter estimation. For mosquitoes, the spatial distribution of close-kin pairs has been used to estimate mean dispersal distance, of relevance to vector-borne disease transmission and novel biocontrol strategies. Here, we extend CKMR methods to the life history of mosquitoes and comparable insects. We derive kinship probabilities for mother-offspring, father-offspring, full-sibling and half-sibling pairs, where an individual in each pair may be a larva, pupa or adult. A pseudo-likelihood approach is used to combine the marginal probabilities of all kinship pairs. To test the effectiveness of this approach at estimating mosquito demographic parameters, we develop an individual-based model of mosquito life history incorporating egg, larva, pupa and adult life stages. The simulation labels each individual with a unique identification number, enabling close-kin relationships to be inferred for sampled individuals. Using the dengue vector Aedes aegypti as a case study, we find the CKMR approach provides unbiased estimates of adult census population size, adult and larval mortality rates, and larval life stage duration for logistically feasible sampling schemes. Considering a simulated population of 3,000 adult mosquitoes, estimation of adult parameters is accurate when ca. 40 adult females are sampled biweekly over a three month period. Estimation of larval parameters is accurate when adult sampling is supplemented with ca. 120 larvae sampled biweekly over the same period. The methods are also effective at detecting intervention-induced increases in adult mortality and decreases in population size. As the cost of genome sequencing declines, CKMR holds great promise for characterizing the demography of mosquitoes and comparable insects of epidemiological and agricultural significance.

Bayesian network-based risk assessment of synthetic biology: Simulating CRISPR-Cas9 gene drive dynamics in invasive rodent management

Gene drive technology has been proposed to control invasive rodent populations as an alternative to rodenticides. However, this approach has not undergone risk assessment that meets criteria established by Gene Drives on the Horizon, a 2016 report by the National Academies of Sciences, Engineering, and Medicine. To conduct a risk assessment of gene drives, we employed the Bayesian network-relative risk model to calculate the risk of mouse eradication on Southeast Farallon Island using a CRISPR-Cas9 homing gene drive construct. We modified and implemented the R-based model "MGDrivE" to simulate and compare 60 management strategies for gene drive rodent management. These scenarios spanned four gene drive mouse release schemes, three gene drive homing rates, three levels of supplemental rodenticide dose, and two timings of rodenticide application relative to gene drive release. Simulation results showed that applying a supplemental rodenticide simultaneously with gene drive mouse deployment resulted in faster eradication of the island mouse population. Gene drive homing rate had the highest influence on the overall probability of successful eradication, as increased gene drive accuracy reduces the likelihood of mice developing resistance to the CRISPR-Cas9 homing mechanism.

Assessing single-locus CRISPR/Cas9-based gene drive variants in the mosquito Aedes aegypti via single-generation crosses and modeling

The yellow fever mosquito Aedes aegypti is a major vector of arthropod-borne viruses, including dengue, chikungunya, and Zika viruses. A novel approach to mitigate arboviral infections is to generate mosquitoes refractory to infection by overexpressing antiviral effector molecules. Such an approach requires a mechanism to spread these antiviral effectors through a population, for example, by using CRISPR/Cas9-based gene drive systems. Critical to the design of a single-locus autonomous gene drive is that the selected genomic locus is amenable to both gene drive and appropriate expression of the antiviral effector. In our study, we used reverse engineering to target 2 intergenic genomic loci, which had previously shown to be highly permissive for antiviral effector gene expression, and we further investigated the use of 3 promoters (nanos, β2-tubulin, or zpg) for Cas9 expression. We then quantified the accrual of insertions or deletions (indels) after single-generation crossings, measured maternal effects, and assessed fitness costs associated with various transgenic lines to model the rate of gene drive fixation. Overall, MGDrivE modeling suggested that when an autonomous gene drive is placed into an intergenic locus, the gene drive system will eventually be blocked by the accrual of gene drive blocking resistance alleles and ultimately be lost in the population. Moreover, while genomic locus and promoter selection were critically important for the initial establishment of the autonomous gene drive, it was the fitness of the gene drive line that most strongly influenced the persistence of the gene drive in the simulated population. As such, we propose that when autonomous CRISPR/Cas9-based gene drive systems are anchored in an intergenic locus, they temporarily result in a strong population replacement effect, but as gene drive-blocking indels accrue, the gene drive becomes exhausted due to the fixation of CRISPR resistance alleles.

Population replacement gene drive characteristics for malaria elimination in a range of seasonal transmission settings: a modelling study

BACKGROUND

Gene drives are a genetic engineering method where a suite of genes is inherited at higher than Mendelian rates and has been proposed as a promising new vector control strategy to reinvigorate the fight against malaria in sub-Saharan Africa.

METHODS

Using an agent-based model of malaria transmission with vector genetics, the impacts of releasing population-replacement gene drive mosquitoes on malaria transmission are examined and the population replacement gene drive system parameters required to achieve local elimination within a spatially-resolved, seasonal Sahelian setting are quantified. The performance of two different gene drive systems-"classic" and "integral"-are evaluated. Various transmission regimes (low, moderate, and high-corresponding to annual entomological inoculation rates of 10, 30, and 80 infectious bites per person) and other simultaneous interventions, including deployment of insecticide-treated nets (ITNs) and passive healthcare-seeking, are also simulated.

RESULTS

Local elimination probabilities decreased with pre-existing population target site resistance frequency, increased with transmission-blocking effectiveness of the introduced antiparasitic gene and drive efficiency, and were context dependent with respect to fitness costs associated with the introduced gene. Of the four parameters, transmission-blocking effectiveness may be the most important to focus on for improvements to future gene drive strains because a single release of classic gene drive mosquitoes is likely to locally eliminate malaria in low to moderate transmission settings only when transmission-blocking effectiveness is very high (above ~ 80-90%). However, simultaneously deploying ITNs and releasing integral rather than classic gene drive mosquitoes significantly boosts elimination probabilities, such that elimination remains highly likely in low to moderate transmission regimes down to transmission-blocking effectiveness values as low as ~ 50% and in high transmission regimes with transmission-blocking effectiveness values above ~ 80-90%.

CONCLUSION

A single release of currently achievable population replacement gene drive mosquitoes, in combination with traditional forms of vector control, can likely locally eliminate malaria in low to moderate transmission regimes within the Sahel. In a high transmission regime, higher levels of transmission-blocking effectiveness than are currently available may be required.

Reversing insecticide resistance with allelic-drive in Drosophila melanogaster

A recurring target-site mutation identified in various pests and disease vectors alters the voltage gated sodium channel (vgsc) gene (often referred to as knockdown resistance or kdr) to confer resistance to commonly used insecticides, pyrethroids and DDT. The ubiquity of kdr mutations poses a major global threat to the continued use of insecticides as a means for vector control. In this study, we generate common kdr mutations in isogenic laboratory Drosophila strains using CRISPR/Cas9 editing. We identify differential sensitivities to permethrin and DDT versus deltamethrin among these mutants as well as contrasting physiological consequences of two different kdr mutations. Importantly, we apply a CRISPR-based allelic-drive to replace a resistant kdr mutation with a susceptible wild-type counterpart in population cages. This successful proof-of-principle opens-up numerous possibilities including targeted reversion of insecticide-resistant populations to a native susceptible state or replacement of malaria transmitting mosquitoes with those bearing naturally occurring parasite resistant alleles.

Insecticide resistance (IR) poses a major global health challenge. Here, the authors generate common IR mutations in laboratory Drosophila strains and use a CRISPR-based allelic-drive to replace an IR allele with a susceptible wild-type counterpart, providing a potent new tool for vector control.

Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework

Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by spreading transgenes among invaders that induce population collapse, and could be deployed even where traditional control methods are impractical or prohibitively expensive. Here, we develop a high-fidelity model of an island population of invasive rodents that includes three types of suppression gene drive systems. The individual-based model is spatially explicit, allows for overlapping generations and a fluctuating population size, and includes variables for drive fitness, efficiency, resistance allele formation rate, as well as a variety of ecological parameters. The computational burden of evaluating a model with such a high number of parameters presents a substantial barrier to a comprehensive understanding of its outcome space. We therefore accompany our population model with a meta-model that utilizes supervised machine learning to approximate the outcome space of the underlying model with a high degree of accuracy. This enables us to conduct an exhaustive inquiry of the population model, including variance-based sensitivity analyses using tens of millions of evaluations. Our results suggest that sufficiently capable gene drive systems have the potential to eliminate island populations of rodents under a wide range of demographic assumptions, though only if resistance can be kept to a minimal level. This study highlights the power of supervised machine learning to identify the key parameters and processes that determine the population dynamics of a complex evolutionary system.

Exploiting a Y chromosome-linked Cas9 for sex selection and gene drive

CRISPR-based genetic engineering tools aimed to bias sex ratios, or drive effector genes into animal populations, often integrate the transgenes into autosomal chromosomes. However, in species with heterogametic sex chromsomes (e.g. XY, ZW), sex linkage of endonucleases could be beneficial to drive the expression in a sex-specific manner to produce genetic sexing systems, sex ratio distorters, or even sex-specific gene drives, for example. To explore this possibility, here we develop a transgenic line of Drosophila melanogaster expressing Cas9 from the Y chromosome. We functionally characterize the utility of this strain for both sex selection and gene drive finding it to be quite effective. To explore its utility for population control, we built mathematical models illustrating its dynamics as compared to other state-of-the-art systems designed for both population modification and suppression. Taken together, our results contribute to the development of current CRISPR genetic control tools and demonstrate the utility of using sex-linked Cas9 strains for genetic control of animals.

Suppressing mosquito populations with precision guided sterile males

The mosquito Aedes aegypti is the principal vector for arboviruses including dengue/yellow fever, chikungunya, and Zika virus, infecting hundreds of millions of people annually. Unfortunately, traditional control methodologies are insufficient, so innovative control methods are needed. To complement existing measures, here we develop a molecular genetic control system termed precision-guided sterile insect technique (pgSIT) in Aedes aegypti. PgSIT uses a simple CRISPR-based approach to generate flightless females and sterile males that are deployable at any life stage. Supported by mathematical models, we empirically demonstrate that released pgSIT males can compete, suppress, and even eliminate mosquito populations. This platform technology could be used in the field, and adapted to many vectors, for controlling wild populations to curtail disease in a safe, confinable, and reversible manner.

A. aegypti is the principal vector for arboviruses that impact on human health and wellbeing. Here the authors use precision guided sterile insect technique—pgSIT—to suppress or eliminate mosquito populations in multigeneration cage experiments.

A common gene drive language eases regulatory process and eco-evolutionary extensions

Background

Synthetic gene drive technologies aim to spread transgenic constructs into wild populations even when they impose organismal fitness disadvantages. The extraordinary diversity of plausible drive mechanisms and the range of selective parameters they may encounter makes it very difficult to convey their relative predicted properties, particularly where multiple approaches are combined. The sheer number of published manuscripts in this field, experimental and theoretical, the numerous techniques resulting in an explosion in the gene drive vocabulary hinder the regulators’ point of view. We address this concern by defining a simplified parameter based language of synthetic drives.

Results

Employing the classical population dynamics approach, we show that different drive construct (replacement) mechanisms can be condensed and evaluated on an equal footing even where they incorporate multiple replacement drives approaches. Using a common language, it is then possible to compare various model properties, a task desired by regulators and policymakers. The generalization allows us to extend the study of the invasion dynamics of replacement drives analytically and, in a spatial setting, the resilience of the released drive constructs. The derived framework is available as a standalone tool.

Conclusion

Besides comparing available drive constructs, our tool is also useful for educational purpose. Users can also explore the evolutionary dynamics of future hypothetical combination drive scenarios. Thus, our results appraise the properties and robustness of drives and provide an intuitive and objective way for risk assessment, informing policies, and enhancing public engagement with proposed and future gene drive approaches.

Risk management recommendations for environmental releases of gene drive modified insects

The ability to engineer gene drives (genetic elements that bias their own inheritance) has sparked enthusiasm and concerns. Engineered gene drives could potentially be used to address long-standing challenges in the control of insect disease vectors, agricultural pests and invasive species, or help to rescue endangered species. However, risk concerns and uncertainty associated with potential environmental release of gene drive modified insects (GDMIs) have led some stakeholders to call for a global moratorium on such releases or the application of other strict precautionary measures to mitigate perceived risk assessment and risk management challenges. Instead, we provide recommendations that may help to improve the relevance of risk assessment and risk management frameworks for environmental releases of GDMIs. These recommendations include: (1) developing additional and more practical risk assessment guidance to ensure appropriate levels of safety; (2) making policy goals and regulatory decision-making criteria operational for use in risk assessment so that what constitutes harm is clearly defined; (3) ensuring a more dynamic interplay between risk assessment and risk management to manage uncertainty through closely interlinked pre-release modelling and post-release monitoring; (4) considering potential risks against potential benefits, and comparing them with those of alternative actions to account for a wider (management) context; and (5) implementing a modular, phased approach to authorisations for incremental acceptance and management of risks and uncertainty. Along with providing stakeholder engagement opportunities in the risk analysis process, the recommendations proposed may enable risk managers to make choices that are more proportionate and adaptive to potential risks, uncertainty and benefits of GDMI applications, and socially robust.

Potential use of gene drive modified insects against disease vectors, agricultural pests and invasive species poses new challenges for risk assessment

Potential future application of engineered gene drives (GDs), which bias their own inheritance and can spread genetic modifications in wild target populations, has sparked both enthusiasm and concern. Engineered GDs in insects could potentially be used to address long-standing challenges in control of disease vectors, agricultural pests and invasive species, or help to rescue endangered species, and thus provide important public benefits. However, there are concerns that the deliberate environmental release of GD modified insects may pose different or new harms to animal and human health and the wider environment, and raise novel challenges for risk assessment. Risk assessors, risk managers, developers, potential applicants and other stakeholders at many levels are currently discussing whether there is a need to develop new or additional risk assessment guidance for the environmental release of GD modified organisms, including insects. Developing new or additional guidance that is useful and practical is a challenge, especially at an international level, as risk assessors, risk managers and many other stakeholders have different, often contrasting, opinions and perspectives toward the environmental release of GD modified organisms, and on the adequacy of current risk assessment frameworks for such organisms. Here, we offer recommendations to overcome some of the challenges associated with the potential future development of new or additional risk assessment guidance for GD modified insects and provide considerations on areas where further risk assessment guidance may be required.

Population modification strategies for malaria vector control are uniquely resilient to observed levels of gene drive resistance alleles

Cas9/guide RNA (gRNA)-based gene drive systems are expected to play a transformative role in malaria elimination efforts., whether through population modification, in which the drive system contains parasite-refractory genes, or population suppression, in which the drive system induces a severe fitness load resulting in population decline or extinction. DNA sequence polymorphisms representing alternate alleles at gRNA target sites may confer a drive-resistant phenotype in individuals carrying them. Modeling predicts that, for observed levels of SGV at potential target sites and observed rates of de novo DRA formation, population modification strategies are uniquely resilient to DRAs. We conclude that gene drives can succeed when fitness costs incurred by drive-carrying mosquitoes are low enough to prevent strong positive selection for DRAs produced de novo or as part of the SGV and that population modification strategies are less prone to failure due to drive resistance.

HM, Dolgert AJ, León TM, Marshall JM. MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamics

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.

Malaria, dengue and other mosquito-borne diseases continue to pose a major global health burden through much of the world. Currently available tools, such as insecticides and antimalarial drugs, are not expected to be sufficient to eliminate these diseases from highly-endemic areas, hence there is interest in novel strategies including genetics-based approaches. In recent years, the advent of CRISPR-based gene-editing has greatly expanded the range of genetic control tools available, and MGDrivE 1 (Mosquito Gene Drive Explorer 1) was proposed to simulate the dynamics of these systems through spatially-structured mosquito populations. As the technology has advanced and potential field trials are being discussed, models are now needed that incorporate additional details, such as life history parameters that respond to daily and seasonal environmental fluctuations, and transmission of pathogens between mosquito and vertebrate hosts. Here, we present MGDrivE 2, a gene drive simulation framework that significantly improves upon MGDrivE 1 by addressing these modeling needs. MGDrivE 2 has also been reformulated as a stochastic Petri net, enabling model specification to be decoupled from simulation, making it easier to adapt the model for application to other insect and mammalian species.

Inherently confinable split-drive systems in Drosophila

CRISPR-based gene-drive systems, which copy themselves via gene conversion mediated by the homology-directed repair (HDR) pathway, have the potential to revolutionize vector control. However, mutant alleles generated by the competing non-homologous end-joining (NHEJ) pathway, resistant to Cas9 cleavage, can interrupt the spread of gene-drive elements. We hypothesized that drives targeting genes essential for viability or reproduction also carrying recoded sequences that restore endogenous gene functionality should benefit from dominantly-acting maternal clearance of NHEJ alleles combined with recessive Mendelian culling processes. Here, we test split gene-drive (sGD) systems in Drosophila melanogaster that are inserted into essential genes required for viability (rab5, rab11, prosalpha2) or fertility (spo11). In single generation crosses, sGDs copy with variable efficiencies and display sex-biased transmission. In multigenerational cage trials, sGDs follow distinct drive trajectories reflecting their differential tendencies to induce target chromosome damage and/or lethal/sterile mosaic Cas9-dependent phenotypes, leading to inherently confinable drive outcomes.

NHEJ alleles and Cas9 remnants after a gene drive introduction are scientific and public concerns. Here, the authors use split drives with recoded rescue elements to target essential genes and minimize the appearance of NHEJ alleles while also leaving no trace of Cas9.

Split versions of Cleave and Rescue selfish genetic elements for measured self limiting gene drive

Gene drive elements promote the spread of linked traits, providing methods for changing the composition or fate of wild populations. Drive mechanisms that are self-limiting are attractive because they allow control over the duration and extent of trait spread in time and space, and are reversible through natural selection as drive wanes. Self-sustaining Cleave and Rescue (ClvR) elements include a DNA sequence-modifying enzyme such as Cas9/gRNAs that disrupts endogenous versions of an essential gene, a tightly linked recoded version of the essential gene resistant to cleavage (the Rescue), and a Cargo. ClvR spreads by creating loss-of-function (LOF) conditions in which those without ClvR die because they lack functional copies of the essential gene. We use modeling to show that when the Rescue-Cargo and one or both components required for LOF allele creation (Cas9 and gRNA) reside at different locations (split ClvR), drive of Rescue-Cargo is self-limiting due to a progressive decrease in Cas9 frequency, and thus opportunities for creation of LOF alleles, as spread occurs. Importantly, drive strength and duration can be extended in a measured manner-which is still self-limiting-by moving the two components close enough to each other that they experience some degree of linkage. With linkage, Cas9 transiently experiences drive by hitchhiking with Rescue-Cargo until linkage disequilibrium between the two disappears, a function of recombination frequency and number of generations, creating a novel point of control. We implement split ClvR in Drosophila, with key elements on different chromosomes. Cargo/Rescue/gRNAs spreads to high frequency in a Cas9-dependent manner, while the frequency of Cas9 decreases. These observations show that measured, transient drive, coupled with a loss of future drive potential, can be achieved using the simple toolkit that make up ClvR elements-Cas9 and gRNAs and a Rescue/Cargo.

The Origin, Development, Application, Lessons Learned, and Future Regarding the Bayesian Network Relative Risk Model for Ecological Risk Assessment

In 2012, a regional risk assessment was published that applied Bayesian networks (BN) to the structure of the relative risk model. The original structure of the relative risk model (RRM) was published in the late 1990s and developed during the next decade. The RRM coupled with a Monte Carlo analysis was applied to calculating risk to a number of sites and a variety of questions. The sites included watersheds, terrestrial systems, and marine environments and included stressors such as nonindigenous species, effluents, pesticides, nutrients, and management options. However, it became apparent that there were limits to the original approach. In 2009, the relative risk model was transitioned into the structure of a BN. Bayesian networks had several clear advantages. First, BNs innately incorporated categories and, as in the case of the relative risk model, ranks to describe systems. Second, interactions between multiple stressors can be combined using several pathways and the conditional probability tables (CPT) to calculate outcomes. Entropy analysis was the method used to document model sensitivity. As with the RRM, the method has now been applied to a wide series of sites and questions, from forestry management, to invasive species, to disease, the interaction of ecological and human health endpoints, the flows of large rivers, and now the efficacy and risks of synthetic biology. The application of both methods have pointed to the incompleteness of the fields of environmental chemistry, toxicology, and risk assessment. The low frequency of exposure-response experiments and proper analysis have limited the available outputs for building appropriate CPTs. Interactions between multiple chemicals, landscape characteristics, population dynamics and community structure have been poorly characterized even for critical environments. A better strategy might have been to first look at the requirements of modern risk assessment approaches and then set research priorities. Integr Environ Assess Manag 2021;17:79-94. © 2020 SETAC.

Efficient population modification gene-drive rescue system in the malaria mosquito Anopheles stephensi

Cas9/gRNA-mediated gene-drive systems have advanced development of genetic technologies for controlling vector-borne pathogen transmission. These technologies include population suppression approaches, genetic analogs of insecticidal techniques that reduce the number of insect vectors, and population modification (replacement/alteration) approaches, which interfere with competence to transmit pathogens. Here, we develop a recoded gene-drive rescue system for population modification of the malaria vector, Anopheles stephensi, that relieves the load in females caused by integration of the drive into the kynurenine hydroxylase gene by rescuing its function. Non-functional resistant alleles are eliminated via a dominantly-acting maternal effect combined with slower-acting standard negative selection, and rare functional resistant alleles do not prevent drive invasion. Small cage trials show that single releases of gene-drive males robustly result in efficient population modification with ≥95% of mosquitoes carrying the drive within 5-11 generations over a range of initial release ratios.

Adequacy and sufficiency evaluation of existing EFSA guidelines for the molecular characterisation, environmental risk assessment and post-market environmental monitoring of genetically modified insects containing engineered gene drives

Advances in molecular and synthetic biology are enabling the engineering of gene drives in insects for disease vector/pest control. Engineered gene drives (that bias their own inheritance) can be designed either to suppress interbreeding target populations or modify them with a new genotype. Depending on the engineered gene drive system, theoretically, a genetic modification of interest could spread through target populations and persist indefinitely, or be restricted in its spread or persistence. While research on engineered gene drives and their applications in insects is advancing at a fast pace, it will take several years for technological developments to move to practical applications for deliberate release into the environment. Some gene drive modified insects (GDMIs) have been tested experimentally in the laboratory, but none has been assessed in small-scale confined field trials or in open release trials as yet. There is concern that the deliberate release of GDMIs in the environment may have possible irreversible and unintended consequences. As a proactive measure, the European Food Safety Authority (EFSA) has been requested by the European Commission to review whether its previously published guidelines for the risk assessment of genetically modified animals (EFSA, 2012 and 2013), including insects (GMIs), are adequate and sufficient for GDMIs, primarily disease vectors, agricultural pests and invasive species, for deliberate release into the environment. Under this mandate, EFSA was not requested to develop risk assessment guidelines for GDMIs. In this Scientific Opinion, the Panel on Genetically Modified Organisms (GMO) concludes that EFSA's guidelines are adequate, but insufficient for the molecular characterisation (MC), environmental risk assessment (ERA) and post-market environmental monitoring (PMEM) of GDMIs. While the MC,ERA and PMEM of GDMIs can build on the existing risk assessment framework for GMIs that do not contain engineered gene drives, there are specific areas where further guidance is needed for GDMIs.

Gene Drive Dynamics in Natural Populations: The Importance of Density Dependence, Space, and Sex

The spread of synthetic gene drives is often discussed in the context of panmictic populations connected by gene flow and described with simple deterministic models. Under such assumptions, an entire species could be altered by releasing a single individual carrying an invasive gene drive, such as a standard homing drive. While this remains a theoretical possibility, gene drive spread in natural populations is more complex and merits a more realistic assessment. The fate of any gene drive released in a population would be inextricably linked to the population's ecology. Given the uncertainty often involved in ecological assessment of natural populations, understanding the sensitivity of gene drive spread to important ecological factors is critical. Here we review how different forms of density dependence, spatial heterogeneity, and mating behaviors can impact the spread of self-sustaining gene drives. We highlight specific aspects of gene drive dynamics and the target populations that need further research.

Using spatial genetics to quantify mosquito dispersal for control programs

Background

Hundreds of millions of people get a mosquito-borne disease every year and nearly one million die. Transmission of these infections is primarily tackled through the control of mosquito vectors. The accurate quantification of mosquito dispersal is critical for the design and optimization of vector control programs, yet the measurement of dispersal using traditional mark-release-recapture (MRR) methods is logistically challenging and often unrepresentative of an insect’s true behavior. Using Aedes aegypti (a major arboviral vector) as a model and two study sites in Singapore, we show how mosquito dispersal can be characterized by the spatial analyses of genetic relatedness among individuals sampled over a short time span without interruption of their natural behaviors.

Results

Using simple oviposition traps, we captured adult female Ae. aegypti across high-rise apartment blocks and genotyped them using genome-wide SNP markers. We developed a methodology that produces a dispersal kernel for distance which results from one generation of successful breeding (effective dispersal), using the distance separating full siblings and 2nd- and 3rd-degree relatives (close kin). The estimated dispersal distance kernel was exponential (Laplacian), with a mean dispersal distance (and dispersal kernel spread σ) of 45.2 m (95% CI 39.7–51.3 m), and 10% probability of a dispersal > 100 m (95% CI 92–117 m). Our genetically derived estimates matched the parametrized dispersal kernels from previous MRR experiments. If few close kin are captured, a conventional genetic isolation-by-distance analysis can be used, as it can produce σ estimates congruent with the close-kin method if effective population density is accurately estimated. Genetic patch size, estimated by spatial autocorrelation analysis, reflects the spatial extent of the dispersal kernel “tail” that influences, for example, the critical radii of release zones and the speed of Wolbachia spread in mosquito replacement programs.

Conclusions

We demonstrate that spatial genetics can provide a robust characterization of mosquito dispersal. With the decreasing cost of next-generation sequencing, the production of spatial genetic data is increasingly accessible. Given the challenges of conventional MRR methods, and the importance of quantified dispersal in operational vector control decisions, we recommend genetic-based dispersal characterization as the more desirable means of parameterization.

Modeling confinement and reversibility of threshold-dependent gene drive systems in spatially-explicit Aedes aegypti populations

Background

The discovery of CRISPR-based gene editing and its application to homing-based gene drive systems has been greeted with excitement, for its potential to control mosquito-borne diseases on a wide scale, and concern, for the invasiveness and potential irreversibility of a release. Gene drive systems that display threshold-dependent behavior could potentially be used during the trial phase of this technology, or when localized control is otherwise desired, as simple models predict them to spread into partially isolated populations in a confineable manner, and to be reversible through releases of wild-type organisms. Here, we model hypothetical releases of two recently engineered threshold-dependent gene drive systems—reciprocal chromosomal translocations and a form of toxin-antidote-based underdominance known as UD^MEL—to explore their ability to be confined and remediated.

Results

We simulate releases of Aedes aegypti, the mosquito vector of dengue, Zika, and other arboviruses, in Yorkeys Knob, a suburb of Cairns, Australia, where previous biological control interventions have been undertaken on this species. We monitor spread to the neighboring suburb of Trinity Park to assess confinement. Results suggest that translocations could be introduced on a suburban scale, and remediated through releases of non-disease-transmitting male mosquitoes with release sizes on the scale of what has been previously implemented. UD^MEL requires fewer releases to introduce, but more releases to remediate, including of females capable of disease transmission. Both systems are expected to be confineable to the release site; however, spillover of translocations into neighboring populations is less likely.

Conclusions

Our analysis supports the use of translocations as a threshold-dependent drive system capable of spreading disease-refractory genes into Ae. aegypti populations in a confineable and reversible manner. It also highlights increased release requirements when incorporating life history and population structure into models. As the technology nears implementation, further ecological work will be essential to enhance model predictions in preparation for field trials.

Antiviral Effectors and Gene Drive Strategies for Mosquito Population Suppression or Replacement to Mitigate Arbovirus Transmission by Aedes aegypti

The mosquito vector Aedes aegypti transmits arthropod-borne viruses (arboviruses) of medical importance, including Zika, dengue, and yellow fever viruses. Controlling mosquito populations remains the method of choice to prevent disease transmission. Novel mosquito control strategies based on genetically manipulating mosquitoes are being developed as additional tools to combat arbovirus transmission. Genetic control of mosquitoes includes two basic strategies: population suppression and population replacement. The former aims to eliminate mosquito populations while the latter aims to replace wild populations with engineered, pathogen-resistant mosquitoes. In this review, we outline suppression strategies being applied in the field, as well as current antiviral effector genes that have been characterized and expressed in transgenic Ae. aegypti for population replacement. We discuss cutting-edge gene drive technologies that can be used to enhance the inheritance of effector genes, while highlighting the challenges and opportunities associated with gene drives. Finally, we present currently available models that can estimate mosquito release numbers and time to transgene fixation for several gene drive systems. Based on the recent advances in genetic engineering, we anticipate that antiviral transgenic Ae. aegypti exhibiting gene drive will soon emerge; however, close monitoring in simulated field conditions will be required to demonstrate the efficacy and utility of such transgenic mosquitoes.