A theoretical approach to predicting the success of genetic manipulation of malaria mosquitoes in malaria control
© Boëte and Koella; licensee BioMed Central Ltd. 2002
Received: 20 December 2001
Accepted: 25 February 2002
Published: 25 February 2002
Mosquitoes that have been genetically modified to better encapsulate the malaria parasite Plasmodium falciparum are being considered as a possible tool in the control of malaria. Hopes for this have been raised with the identification of genes involved in the encapsulation response and with advances in the tools required to transform mosquitoes. However, we have only very little understanding of the conditions that would allow such genes to spread in natural populations.
We present here a theoretical model that combines population genetical and epidemiological processes, thereby allowing one to predict not only these conditions (intensity of transmission, evolutionary cost of resistance, tools used to drive the genes) but also the impact of the spread of refractoriness on the prevalence of the disease.
The main conclusions are 1) that efficient transposons will generally be able to drive genes that confer refractoriness through populations even if there is a substantial (evolutionary) cost of refractoriness, but 2) that this will decrease malaria prevalence in the human population substantially only if refractoriness is close to 100% effective.
If refractoriness is less than 100% effective (because of, for example, environmentally induced variation in the effectiveness of the mosquito's immune response), control programmes based on genetic manipulation of mosquitoes will have very little impact on the epidemiology of malaria, at least in areas with intense transmission.
Malaria is one of the most serious health problems facing the developing world, killing up to 2.5 million people every year  (i.e. about 5% of all deaths world-wide are directly caused by malaria). The problem is aggravated by the economic conditions in most malarious areas  and can only become more serious with the rapid spread of parasites that are resistant to antimalarial drugs and of mosquitoes that are resistant to insecticides. Thus novel methods of malaria control are desperately needed.
A potential method of malaria control, which is being developed in several laboratories world-wide, is the genetic manipulation of mosquitoes. The idea behind this is to transform mosquitoes with genes that render them refractory against infection by malaria, then release them into natural populations and thus make mosquito populations incapable of transmitting malaria. Hopes for this possibility were raised by the observation that there is some genetic variability for mosquito refractoriness against the malaria parasite [3, 4]. This refractoriness is based on melanotic encapsulation of its early developmental stages . First steps to achieve genetic manipulation have recently been accomplished with the identification of genes responsible for the encapsulation, melanization and death of early malarial infections in the mosquito [6, 7] and with the identification of possible mechanisms of introducing these genes into mosquito genomes [8, 9].
It is therefore time for discussions of how best to employ the tools that produce harmless strains of mosquitoes in attempts to control malaria . There are two major questions on the ecological side of genetic manipulation. First, under what conditions can refractoriness be expected to spread in a natural population of mosquitoes? An answer to this question must take into account three parameters: the benefit of refractoriness that is due to avoiding the malaria parasite's detrimental effects on fecundity [11, 12] and mortality , the cost of refractoriness associated with maintaining  and mounting an immune response in insects , and the efficiency of the transformation system. Second, if not all mosquitoes are completely refractory, what will be the impact of the release of transgenic mosquitoes on the malaria situation?
Answers to these questions can only be found with a combination of theoretical and empirical work on refractoriness in natural populations of mosquitoes. In a step towards this, we present a theoretical model that describes the spread of refractory genes in a population of mosquitoes. Though earlier theoretical models have approached this question [16, 17], none have considered all three parameters mentioned above. Furthermore, we extended the models by combining a population genetical and an epidemiological approach. Not only can such a combination yield different conclusions than either approach on its own , but it also allows one to evaluate the effect of the release of transgenic mosquitoes on the prevalence of malaria in the human population.
We assumed that refractoriness is determined by a single gene and that the dynamics can be described by discrete generations. As the costs and benefits of the refractory gene will differ between males and females, we based our model, describing the spread of a given allele in a population, on the standard population genetics equations for sex-dependent fitness . We further assumed that genetic manipulation is achieved by linking the refractory gene to transposons, which have the tendency to infect the offspring of transfected parents and can therefore spread rapidly through populations, even if they are associated with reduced fitness [20, 21]. We did not take into account the dynamics of the copy number of the transposon within a genome, but simply assumed that the transposon increases the probability that the refractory gene in a heterozyote parent is transmitted to the offspring by the factor ∂, the efficiency of the genetic drive . Thus, if p f,t describes the frequency of the refractory gene in female gametes at generation t, p m,t describes the frequency of the refractory gene in male gametes, W f,RR describes the fitness of females that are homozygous for the refractory gene, W f,RS describes the fitness of females that are heterozygous for the refractory gene, and describes the mean fitness of females, then the frequency of the refractory allele in female gametes at generation t+1 can be described by
An analogous equation describes the spread of the allele for the males.
The fitness of males and females is determined by the cost of maintaining refractoriness. The fitness of females is additionally determined by the burden of the parasite. In both sexes, we assumed that the transposon reduces fitness.
The fitness of sensitive males (harbouring neither transposon nor, obviously, parasite) was assumed to be 1. The fitness of sensitive females is thus 1 - (the burden of the parasite). We assumed that infection by malaria reduces fitness by the parasite's virulence α. The probability that a mosquito is infected when it bites a human host is proportional to the prevalence y of malaria in the human population and to the probability, b, that a mosquitoes will become infected on a single infectious bloodmeal. If a mosquito bites a human, on average, k times during its life, the probability that it will become infected at least once during its life-time is thus proportional to the nonzero-term of the Poisson distribution 1 - exp(- byk). Note that this equation is based on several assumptions, e.g. that infections occur independently of the current infection status of the mosquito. Changing the details of these assumptions, however, will not alter the qualitative conclusions of the model; what is important is that the probability that a mosquito will become infected increases with the prevalence in humans. For the rest of the paper, we assumed that b = 1, without changing the general conclusions. The fitness of sensitive females is then given by w f, SS = 1 - [1 - exp(-yk)]α.
Mosquitoes that are homozygous for the refractory allele are protected from infection with the effectiveness of protection s; the probability that they will become infected is therefore reduced to 1 - exp(- yk(1 - s)). However, they must pay the cost of harbouring two refractory alleles, assumed to be c. Furthermore, as they carry the transposon along with the refractory alleles, their fitness is further reduced by the cost c T of the transposon. Overall, the fitness of females homozygous for refractoriness is thus w f, RR = 1 - [1 - exp(-yk(1 - s))]α - c - c T , while the males suffer from the costs of harbouring the refractory alleles and the transposons and thus have fitness w m, RR = 1 - c - c T .
Finally, heterozygotes were assumed to fall between the refractory and sensitive homozygotes, with the effectiveness of protection and the cost of refractoriness being reduced by h, the level of dominance. Thus, the fitness of heterozygous females is w f, RS = 1 - [1 - exp(-yk(1 - hs))]α - hc - c T and that of males is w m, RS = 1 - hc - c T .
Cost of refractoriness
The cost of refractoriness can be expressed in two ways. On the one hand, there may be a fixed cost involved in maintaining the physiological machinery necessary for the immune encapsulation response. Such a maintenance cost would be expressed as a genetic correlation between the effectiveness of the immune response and other traits that determine fitness. This type of cost has been demonstrated for several insects (e.g. Drosophila), including the mosquito Aedes aegypti, where the effectiveness of encapsulating Sephadex beads is genetically correlated with the mosquito's age at pupation (Koella and Boëte, submitted). On the other hand, the cost may be expressed when the immune response is mounted, so that it is expressed only in infected individuals. Such a conditional cost has also been observed in several insects (e.g. bumble-bees ), including Anopheles gambiae, where mosquitoes with an effective immune response have lower fecundity (Schwartz and Koella, submitted).
To allow for these types of cost, we modelled the cost in two ways. The fixed maintenance cost assumes that the cost c is constant, i.e. c = c0. The conditional cost, in contrast, depends on the rate of infection, and was thus modelled as c = c0[1 - exp(-yk)].
where R0 is the basic reproductive number of malaria, a is the mosquito's biting rate and μ is its mortality rate (and thus the number of bites per life-time is k = a/μ).
The basic reproductive number, on the other hand, is determined by the number of sensitive mosquitoes . Assuming that the population of mosquitoes is at Hardy-Weinberg equilibrium, we therefore write
Spread of refractoriness
We first describe the spread of the allele coding for refractoriness in the absence of a transposon-mediated drive mechanism. As we are interested in the end-result of the evolutionary (control) process, we only show and discuss the predictions of the model at equilibrium.
Fixed maintenance cost
There is a similar threshold for the efficacy of refractoriness. If the efficacy is lower than this threshold, refractoriness cannot spread. Above this threshold, refractoriness will generally spread to a high proportion of the mosquitoes and may reach fixation (Fig. 1c). As the efficacy approaches 100%, the proportion of refractoriness decreases because of the epidemiological feed-back: if refractoriness becomes too effective, the proportion of infected mosquitoes drops to a level where there is little selection pressure for the mosquito to increase its refractoriness. Accordingly, prevalence decreases with the efficacy of refractoriness, but again does not reach 0 (Fig. 1d).
Spread of the tandem refractoriness allele & transposable element
The efficacy of refractoriness and the intensity of transmission, however, have a large effect on the effect of the spread of refractoriness on the prevalence of disease in the human population (Fig. 3e). Even in conditions that allow the allele conferring refractoriness to spread to fixation, the impact on prevalence in humans is slight unless the efficacy of refractoriness is considerable, particularly in areas with intense transmission.
Summary of results
In the absence of the genetic drive provided by a transposon (Figs. 1 &2), the spread of an allele conferring refractoriness is determined by the balance of evolutionary costs (reduced reproductive success of refractory mosquitoes) and benefits (reduced detrimental effect of the parasite) of refractoriness. These are partly determined by the probability that mosquitoes are infected, i.e. by the prevalence of malaria in the human population, which, in turn, is determined by the level of refractoriness in the mosquito population. This epidemiological feedback is the cause of frequency-dependent selection, which prevents the eradication of the parasite.
If a transposon is linked to the gene responsible for refractoriness (Fig. 3), the epidemiological feedback is largely lacking, so that refractoriness is either lost from the population or spreads to fixation. It is reassuring that fairly low efficacy of the genetic drive mechanism ensures the fixation of refractoriness in many situations. The predictions of our equations, which combine population genetical and epidemiological processes, thus corroborate results from previous population genetical  or spatially explicit individual-based  models.
More importantly from the perspective of malaria control, if the efficacy of refractoriness is 100%, genetic manipulation can eradicate malaria from the population. If, however, the refractoriness is less than complete, the impact on the malaria situation is negligible in areas of intermediate to high transmission. This should come as no surprise, as the Macdonald-Ross model of malaria epidemiology shows that reducing the number of (susceptible) mosquitoes is an inefficient way of reducing malaria transmission .
Thus, from the model described here, it is clear that knowledge about three parameters is critical for our understanding of the spread of refractoriness: the benefit of refractoriness, its cost, and its efficacy.
Although there are no quantitative data on any of these parameters, recent studies have started to provide at least some qualitative estimates. The benefit of refractoriness is due to the advantage of reducing the deleterious effects of infection. Though the virulence of the parasite is still being questioned (Ferguson, under review), recent studies have shown that malaria infection reduces the survival of mosquitoes in the field  and their fecundity [11, 12]. A possible cost of refractoriness is due to the physiological cost of mounting an encapsulation immune response. Though studies on mosquitoes have only just started (Koella & Boëte, submitted, Schwartz & Koella, submitted), other insects provide ample evidence of such a cost [14, 15, 25]. Overall, however, the cost of refractoriness appears to outweigh the benefits, as the proportion of refractory mosquitoes in natural populations is negligible .
The efficacy of refractoriness depends not only on its genetic determination, but also on environmentally induced variation. And indeed, the encapsulation response of mosquitoes decreases substantially if larvae are reared in bad conditions , if adults do not obtain a blood meal  and as they age . Thus, it seems unlikely that refractoriness would be completely effective in natural situations.
Criticism of model
Obviously, like any other mathematical (or non-mathematical) model our equations are simple caricatures of the epidemiological and genetic processes being considered. The success of a model will depend on the inclusion of the relevant processes.
There are several reasons for believing that the epidemiological aspect of our model captures some aspect of reality. Compartment models of infectious diseases in general have had considerable success in epidemiology . In particular, compartment models similar to the ones used here have had considerable success in describing epidemiological patterns of malaria . Similar models are considered to be helpful in evaluating the sensitivity of malaria transmission to different control measures  and in predicting the effectiveness of vaccine programs [31–33].
In the population genetical parts of the model, we have made three critical assumptions. First, by following standard ideas of population genetics we have assumed an infinite population size. However, other models have shown that finite populations that take into account density-dependence  change the general conclusions only slightly. Furthermore, as the effective population sizes of mosquitoes are often large , the stochasticity of genetic drift will only affect the initial spread of very rare resistance alleles and have little effect on the outcome of the simulations . Second, refractoriness is determined by an allele at a single locus. Although it is known that several genes are involved in the immune response [4, 35], the main difference between susceptible and refractory mosquitoes appears to be determined by one or very few major genes [6, 7]. Third, our modelling of the transposon neglected several aspects of the biology of transposons, e.g. the regulatory process that determines their copy number [36, 37] and the fact that the refractory gene could disassociate from the transposon, making the system ineffective [38, 39]. Modifying these assumptions will generally make the likelihood that refractoriness spreads to fixation less likely, so that our results are optimistic predictions about the success of a control programme.
The approach offered here can provide insights into the use of genetically engineered mosquitoes for malaria control. The most important one is that, while refractoriness may be driven into a population of mosquitoes despite considerable costs, less than complete refractoriness of mosquitoes harbouring the allele will only slightly decrease the prevalence of infection in the human population, in particular in areas with intense transmission. But clearly, what is needed is more detailed knowledge of the critical parameters involved: costs and benefits of refractoriness and in particular the efficacy of refractoriness. Only this will allow one to give advice about rational malaria control using genetically manipulated mosquitoes.
C.B. was supported by a Bourse Docteur-Ingénieur from CNRS.
- WHO: The World Health Report 1996. Geneva, World Health Organization. 1996Google Scholar
- Manfredi C: Can the resurgence of malaria be partially attributed to structural adjustment programmes?. Parassitologia. 1999, 41: 389-390.PubMedGoogle Scholar
- Collins FH, Sakai RK, Vernick KD, Paskewitz S, Seeley DC, Miller LH, Collins WE, Campbell CC, Gwadz RW: Genetic selection of a Plasmodium-refractory strain of the malaria vector Anopheles gambiae. Science. 1986, 234: 607-610.View ArticlePubMedGoogle Scholar
- Dimopoulos G, Casavant TL, Chang S, Scheetz T, Roberts C, Donohue M, Schultz J, Benes V, Bork P, Ansorge W, Bento Soares M, Kafatos FC: Anopheles gambiae pilot gene discovery project: identification of mosquito innate immunity genes from expressed sequence tags generated from immune-competent cell lines. Proc Nat Acad Sci USA. 2000, 97: 6619-6624. 10.1073/pnas.97.12.6619.PubMed CentralView ArticlePubMedGoogle Scholar
- Paskewitz SM, Brown MR, Lea AO, Collins FH: Ultrastructure of the encapsulation of Plasmodium cynomolgi (B strain) on the midgut of a refractory strain of Anopheles gambiae. J Parasitol. 1988, 74: 432-439.View ArticlePubMedGoogle Scholar
- Gorman MJ, Severson DW, Cornel AJ, Collins FH, Paskewitz SM: Mapping a quantitative trait locus involved in melanotic encapsulation of foreign bodies in the malaria vector, Anopheles gambiae. Genetics. 1997, 146: 965-971.PubMed CentralPubMedGoogle Scholar
- Zheng L, Cornel AJ, Wang R, Erfle H, Voss H, Ansorge W, Kafatos FC, Collins FH: Quantitative trait loci for refractoriness of Anopheles gambiae to Plasmodium cynomolgi B. Science. 1997, 276: 425-428. 10.1126/science.276.5311.425.View ArticlePubMedGoogle Scholar
- Coates CJ, Jasinskiene N, Miyashiro L, James AA: Mariner transposition and transformation of the yellow fever mosquito, Aedes aegypti. Proc Nat Acad Sci USA. 1998, 95: 3748-3751. 10.1073/pnas.95.7.3748.PubMed CentralView ArticlePubMedGoogle Scholar
- Catteruccia F, Nolan T, Loukeris TG, Blass C, Savakis C, Kafatos FC, Crisanti A: Stable germline transformation of the malaria mosquito Anopheles stephensi. Nature. 2000, 405: 959-962. 10.1038/35016096.View ArticlePubMedGoogle Scholar
- Aultmann KS, Beaty BJ, Walker ED: Genetically manipulated vectors of human disease: a practical overview. Trends Parasitol. 2001, 17: 507-509. 10.1016/S1471-4922(01)02094-3.View ArticleGoogle Scholar
- Hogg JC, Hurd H: Malaria-induced reduction of fecundity during the first gonotrophic cycle of Anopheles stephensi mosquitoes. Med Vet Entomol. 1995, 9: 176-180.View ArticlePubMedGoogle Scholar
- Hogg JC, Hurd H: The effects of natural Plasmodium falciparum infection on the fecundity and mortality of Anopheles gambiae in north east Tanzania. Parasitol. 1997, 114: 325-331. 10.1017/S0031182096008542.View ArticleGoogle Scholar
- Anderson RA, Knols BJG, Koella JC: Plasmodium falciparum sporozoites increase feeding-associated mortality of their mosquito hosts Anopheles gambiae s.l. Parasitol. 2000, 120: 329-333. 10.1017/S0031182099005570.View ArticleGoogle Scholar
- Kraaijeveld AR, Godfray HC: Trade-off between parasitoid resistance and larval competitive ability in Drosophila melanogaster. Nature. 1997, 389: 278-280. 10.1038/38483.View ArticlePubMedGoogle Scholar
- Moret Y, Schmid-Hempel P: Survival for immunity: the price of immune system activation for bumblebee workers. Science. 2000, 290: 1166-1168. 10.1126/science.290.5494.1166.View ArticlePubMedGoogle Scholar
- Curtis CF, Sinkins SP: Wolbachia as a possible means of driving genes into populations. Parasitol. 1998, 116: S111-S115.View ArticleGoogle Scholar
- Kiszewski AE, Spielman A: Spatially explicit model of transposon-based genetic drive mechanisms for displacing fluctuating populations of anopheline vector mosquitoes. J Med Entomol. 1998, 35: 584-590.View ArticlePubMedGoogle Scholar
- Doebeli M, Koella JC: Sex and population dynamics. Proc Roy Soc Lond B. 1994, 257: 17-23.View ArticleGoogle Scholar
- Hartl DL, Clark AG: Principles of Population Genetics. Sunderland, Sinauer Associates. 1989Google Scholar
- Kidwell MG, Novy JB, Feeley SM: Rapid unidirectional change of hybrid disgenesis potential in Drosophila. J Heredity. 1981, 72: 32-38.Google Scholar
- Ribeiro JMC, Kidwell MG: Transposable elements as population drive mechanisms: specification of critical parameter values. J Med Entomol. 1994, 31: 10-15.View ArticlePubMedGoogle Scholar
- Ginzburg LR, Bingham PM, Yoo S: On the theory of speciation induced by transposable elements. Genetics. 1984, 107: 331-341.PubMed CentralPubMedGoogle Scholar
- Macdonald G: The Epidemiology and Control of Malaria. London, Oxford University Press. 1957Google Scholar
- Aron JL, May RM: The population dynamics of malaria. In: The Population Dynamics of Infectious Diseases: Theory and Applications. Edited by: Anderson RM. 1982, London, Chapman and Hall, 139-179.View ArticleGoogle Scholar
- Siva-Jothy MT, Tsubaki Y, Hooper RE: Decreased immune response as a proximate cost of copulation and oviposition in a damselfly. Physiol Entomol. 1998, 23: 274-277. 10.1046/j.1365-3032.1998.233090.x.View ArticleGoogle Scholar
- Schwartz A, Koella JC: Melanization of Plasmodium falciparum and C-25 Sephadex beads by field caught Anopheles gambiae (Diptera: Culicidae) from Southern Tanzania. J Med Entomol. 2002, 39: 84-88.View ArticlePubMedGoogle Scholar
- Suwanchaichinda C, Paskewitz SM: Effects of larval nutrition, adult body size, and adult temperature on the ability of Anopheles gambiae (Diptera: Culicidae) to melanize beads. J Med Entomol. 1998, 35: 157-161.View ArticlePubMedGoogle Scholar
- Chun J, Riehle M, Paskewitz SM: Effect of mosquito age and reproductive status on melanization of sephadex beads in Plasmodium-refractory and -susceptible strains of Anopheles gambiae. J Invert Pathol. 1995, 66: 11-17. 10.1006/jipa.1995.1054.View ArticleGoogle Scholar
- Anderson RM, May RM: Infectious Diseases of Humans: Dynamics and Control. Oxford, Oxford University Press. 1991Google Scholar
- Molineaux L, Gramiccia G: The Garki Project: Research on the Epidemiology and Control of Malaria in the Sudan Savanna of West Africa. Geneva, World Health Organization. 1980Google Scholar
- Koella JC: On the use of mathematical models of malaria transmission. Acta Tropica. 1991, 49: 1-25. 10.1016/0001-706X(91)90026-G.View ArticlePubMedGoogle Scholar
- Gupta S, Anderson RM: Predicting the effects of malaria vaccines on the population dynamics of infection and disease. In: Malaria Vaccine Development: A Multi-Immune Response Approach. Edited by: Hoffman SL. 1996, Washington DC, ASM Press, 249-276.Google Scholar
- Gandon S, Mackinnon MJ, Nee S, Read AF: Imperfect vaccines and the evolution of pathogen virulence. Nature. 2001, 414: 751-756. 10.1038/414751a.View ArticlePubMedGoogle Scholar
- Lehmann T, Hawley WA, Grebert H, Collins FH: The effective population size of Anopheles gambiae in Kenya: implications on population structure. Mol Biol Evol. 1998, 15: 264-276.View ArticlePubMedGoogle Scholar
- Dimopoulos G, Seeley D, Wolf A, Kafatos FC: Malaria infection of the mosquito Anopheles gambiae activates immune responsive genes during critical transition stages of the parasite life cycle. EMBO J. 1998, 17: 6115-6123. 10.1093/emboj/17.21.6115.PubMed CentralView ArticlePubMedGoogle Scholar
- Lemaitre B, Coen D: P regulatory products repress in vivo the P promoter activity in P-lacZ fusion genes. Proc Nat Acad Sci USA. 1991, 88: 4419-4423.PubMed CentralView ArticlePubMedGoogle Scholar
- Charlesworth B, Langley CH: The population genetics of Drosophila transposable elements. Ann Rev Genetics. 1989, 23: 251-287. 10.1146/annurev.ge.23.120189.001343.View ArticleGoogle Scholar
- Curtis CF: The case of malaria control by genetic manipulation of its vectors. Parasitol Today. 1994, 10: 371-374. 10.1016/0169-4758(94)90222-4.View ArticlePubMedGoogle Scholar
- Spielman A: Why entomological antimalaria research should not focus on transgenic mosquitoes. Parasitol Today. 1994, 10: 374-371. 10.1016/0169-4758(94)90223-2.View ArticlePubMedGoogle Scholar
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