Cluster 3: Vector-Parasite Interactions
Mosquitoes of the Anopheles genus represent a major threat for human health, as they are the exclusivevectors of malaria. A series of biological features, collectively known as vectorial capacity, renders Anopheles species very efficient vectors for the transmission of Plasmodium parasites, the causative agentsof malaria. These include a genetically determined preference for blood meals on a human host (hostseekingbehaviour) for egg development, a high reproductive rate and a long life span, combined with theinnate ability to support parasite development. Therefore modulation of vector-parasite interactions, hostseekingbehaviour, reproductive biology, and longevity offer key opportunities for interfering with malariatransmission.
So far the most successful interventions that have led to a significant reduction in malariatransmission, chiefly exploited vector control strategies through the use of insecticides. However, recentinsurgence of resistance in mosquitoes and the lack of novel insecticidal compounds constitute majorhurdles in the fight against malaria. The combination of higher transmission rates due to the failure oftraditional vector control measures and the rapid dissemination of drug resistance in Plasmodium parasitesare escalating the number of malaria cases every year in the majority of disease-endemic countries, andlead to the re-introduction of malaria in some European countries. To efficiently and in a timely fashionidentify and address global health issues, including emerging epidemics, novel alternative strategies areurgently needed to monitor risks and to roll back the disease.The specific activities of Cluster 3 will integrate knowledge, research capacity and infrastructures of leadinggroups in the field of vector biology in Europe and Africa with the ultimate aim to reduce the mosquitovectorial capacity. Molecular interactions between malaria parasites and their hosts and vectors have beenstudied intensively in convenient but unnatural model systems, such as the triad Plasmodium berghei, Anopheles gambiae and the mouse. There are pragmatic reasons for this valuable model system approachthat has been and will continue to be very fruitful.
To complement this heuristic approach, a strong focus oncoordinated studies on all three organisms that are actually implicated in natural cases of P. falciparum malaria will be developed. To this end, the impact of genetic variation in all three organisms implicated inmalaria will be considered. The broad aims of Cluster 3 are to understand and describe at the molecular andnucleotide level the functional consequences of genetic variation in these organisms and their interactions.We have focused this project on A. gambiae, the most efficient vector of human malaria in the world. Tohelp tackling the questions poised, a series of protocols and molecular tools will be developed which will beshared by the Network partners and made available to the Scientific Community. Overall, the joint scientificactivities of this Cluster, articulated in 3 work packages described below, are anticipated to considerablyexpand our knowledge of the factors and pathways regulating the success of malaria transmission crucialfor the development of transmission-blocking interventions.
Work package 1.3.1. Vector/Host/Parasite interactions
The uniqueness of this work package is that for the first time it concurrently examines interactions betweenall three organisms implicated in human malaria: the mosquito vector, the mammalian host and theprotozoan parasite. In spite of accumulating evidence that vector - parasite and vector - host interfaces arecrucial for disease transmission, studies in this area remain fragmentary. This work package aims to fill inthis knowledge gap.
WP1.3.1.1. Vector – parasite interface (CNRS, IRD, IC2, SU, FORTH)
This task will build upon knowledgeacquired by the participants of this proposal on the immune responses employed by the vector to limit Plasmodium development (Osta et al., 2004). Mosquitoes efficiently detect and eliminate the vast majority ofthe invading parasites within the first days of infection. However, these significant albeit partial losses arecompensated later in the parasite life cycle by sporogonic amplification of the few surviving parasites. Anumber of genes has been functionally characterised in A. gambiae that regulate the outcome of Plasmodium infection, predominantly by analysis of knockdown phenotypes in a model rodent malariaparasite system (Blandin et al., 2008). This task will expand the available knowledge on anti-Plasmodium genes and extend it to the human malaria parasite and analyse genome-wide responses of A. gambiae tosympatric populations of P. falciparum.
We will further examine signalling events that lead to parasiterecognition and killing, using when appropriate Drosophila model to tackle conserved immune signallingpathways. In addition, we will investigate the role of the mosquito blood cells in antiparasitic responses anddevelop cell-based functional assays. Finally, the role of environmental factors on the establishment of themosquito capacity to transmit malaria will be evaluated in natural mosquito populations. Within the sametask, we will explore whether Plasmodium-borne molecules manipulate mosquito capacity to transmitmalaria. A number of mosquito midgut proteins have been previously identified that interact with parasitesand we will use a variety of biochemical approaches to identify their binding partners from Plasmodium. Anticipated risks and contingency plan: The success of this work package is based on the combination of reverse genetics, biochemical, and molecular biology approaches that will be employed to attain the planned deliverables. The scientific excellence of teams involved and efficient dissemination of results and technologies will constitute decisive components of the success.
WP1.3.1.2. Vector – host interface (UR, ISS, IRD, RUN, CNRS, MRTC, IC2)
Mosquito feeding on themammalian host represents a key step in malaria transmission. During this process, mosquitoes ingestblood that contains a series of biologically active factors (e.g., antibodies, drugs) that may modulate vectorphysiology and vector - parasite interactions. Equally during host biting, mosquitoes inject a cocktail ofsalivary secretions to facilitate blood feeding by manipulating the hemostatic, inflammatory and immuneresponses of the host (Arca et al., 2006). However, the importance of these aspects in parasite transmissionhas been so far overlooked. This task will investigate molecular events at the vector - host interface. We willevaluate the effect of natural and acquired transmission-blocking malaria vaccines on the mosquito vectorialcapacity, including immunity and reproduction. To this end, mosquitoes will be infected with the bloodcontaining a laboratory strain of P. falciparum together with antibodies against sexual parasite stages.
These studies will be extended to analysis of antibodies in naturally acquired transmission-blockingimmunity in malaria endemic countries and their effect on vectorial capacity. In parallel, we will examine therole of salivary secretions on immune responses of the host and on malaria transmission. Usingrecombinant salivary proteins, we will validate the potential use of selected proteins as serological indicatorsof exposure to anopheline mosquitoes and malaria transmission.EVIMalaR: a European Virtual Institute for Malaria Research 30/10/2009Page 18 of 214 Anticipated risks and contingency plan: no risks are associated with this task: experimental P. falciparum infections are routinely performed by RUN and IC, similarly, UR has already identified the major components of the saliva, which will be functionally analysed here.
WP1.3.1.3. Vector life history traits and malaria transmission (IC3, IRD, CNRS, RUN, SU)
We willexamine how modulation of immune signalling cascades affects reproduction and fecundity in females andspermatogenesis in males. These experiments will be extended to evaluate the role of Plasmodium molecules in the modulation of the reproductive success of the vector. Another critical component of malariatransmission is the trophic behaviour of the vector. Transmission is optimum if all blood meals are taken onhuman in contrast to other vertebrate hosts. Mosquito trophic preferences depend on geographical areas,species and mosquito populations (Tirados et al., 2006), but the adaptive benefit of feeding on human oralternative hosts has not been investigated.
We will evaluate the cost of blood meal seeking on human orcalf and the fitness of mosquitoes after feeding on different hosts. Cost of blood seeking will be measuredby releasing starved uninfected mosquitoes in experimental huts containing a human or a cow. Proportion offed mosquitoes will be measured at different time points to assess the energetic cost spent by the vectorsbefore feeding. Anticipated risks and contingency plan: this is a largely understudied area of research, no risks are associated with this task.
Work package 1.3.2. Population genetics of Vector/Host/Parasite interactions. 1.3.2.1. Genetic basis of vector susceptibility to P. falciparum and of P. falciparum variation invector/host infectivity (IC2, IRD, MUK, FORTH, IEDK, UR)
Using a high-throughput SNP genotypingplatform, we will perform association studies to investigate the genetic basis of mosquito susceptibility to P. falciparum infection and the nature of the variation segregating in both species that result in an infection. Todate, the only studies examining the natural pair have identified one large region (~15Mb) in A. gambiae M form that has an impact on infection intensity (Niare et al 2002, Riehle et al 2006, 2007). We have recentlydesigned an Affymetrix SNP chip that interrogates 400,000 positions known to vary in the A. gambiae genome and 1000 positions known to vary in the P. falciparum genome.
Once we have validated the chip,we will use it to carry out genome-wide association studies (GWAS) both in the lab, where conditions can becarefully controlled and in the field, where the roles of both vector and parasite genotype can beinvestigated. Field collected isolates of parasites and A. gambiae S form (AgS) and A. arabiensis (Aa)mosquitoes originating from Uganda and Burkina Faso as well as An. gambiae M form (AgM) from BurkinaFaso will be the focus of this research. Colonies of these three species will be created in Uganda (MUK) andin Burkina Faso (IRD). These colonies will be publicly available and of great use in further downstreamanalyses, both in our network and beyond.Furthermore, the polymorphism of salivary gland genes in natural A. gambiae population will be addressed.Mosquito saliva affects parasite transmission and host immune response and salivary genes seem to beunder strong selective pressure (Valenzuela et al., 2003; Arcà et al., 2007).
It has been suggested thatsalivary proteins may be developed as markers of exposure to mosquitoes (Remoue et al, 2006; Orlandi-Pradines et al, 2007) and/or as vaccine components (Donovan et al, 2007; Fonseca et al, 2007; Gomes et al, 2008). Therefore, it will be important to evaluate the degree of polymorphism in natural A. gambiae population, which is presently totally unknown.Anticipated risks and contingency plan: The success of the chip will largely depend on the scale of linkage disequilibrium which is a currently unknown variable in vector populations. If LD is so small that the chip is of limited value, we can either perform QTL studies using the chip, or we can gather more SNPs via resequencing projects and redesign the chip.
WP1.3.2.2. Genetic basis of host susceptibility to malaria (UR, SU, FORTH, IEDK, WTSI3, UOXF)
Differences in susceptibility to malaria and its disease burden have long been observed betweenpopulations in malaria endemic areas. The existence of a host genetic basis for such differences has beensupported by studies of sympatric populations that share the same environment but suffer different levels ofclinical disease. However, differences in expression patterns of pivotal genes as a point of convergence ofgenetic variations have seldom been addressed and the expression profile of disease related genes inendemic areas remains poorly investigated. A complication is that expression patterns are often commonbetween diseases that share biological grounds. The biological basis of shared expression profiles and the“borrowable” nature of many genetic polymorphisms are yet to be understood.
A population transcriptome isEVIMalaR: a European Virtual Institute for Malaria Research 30/10/2009Page 19 of 214largely the product of the genetic history of that population as much as the genome; it is amenable toanalysis by independent linked and unlinked genetic markers defining population structure analogous to ourreported association of the HbS variant and Y chromosome haplogroups (Berier et al., 2007). Thisclustering approach in defining within village cohorts will be extended to include the HbS, HbC and alphathalpolymorphisms. The former has been shown to protect from clinical malaria in both populations.However there seems to be an overall loss of balancing selection in the Hausa where malaria ischaracteristically of lower burden (Saleh et al., submitted). The impact of the population structure of theHausa on such loss of balancing selection needs to be investigated since endogamy is common practice inthat community where more than 90% of marriages are within village (Ibrahim).Following previous observations on the different susceptibility to malaria among sympatric ethnic groupsand on the role of CD4+CD25+ T-regulatory cells in these differences, we will use immuno-parasitologicaland genetic approaches, based on large-scale surveys in malaria hyperendemic areas and state of the artgenotyping techniques, to focus on human genetic variation at loci involved in the immuno-regulatorynetwork and in the development of autoimmunity.
Many studies in the last fifty years have demonstrated theprotective role of erythrocytic malaria resistance genes against clinical P. falciparum malaria. Fewobservations exist on the possible influence of these conditions on the development of acquired anti-malariaimmunity and no data are available on their possible role on the transmission of the parasite from thevertebrate host to the vector. We will use large-scale genetic, immuno-parasitological, and entomologicalstudies in malaria hyperendemic areas, to test the possible involvement of erythrocytic malaria resistancegenes in the acquisition of humoral immunity against malaria, in gametocytogenesis and in gametocyteinfectivity (Modiano).Studies in Burkina Faso and Mali have demonstrated that the Fulani are less parasitized, less affected bymalaria and have higher anti-malarial responses and splenomegalies than other sympatric groups; thispattern holds despite a lower frequency of established malaria resistance markers, similar malaria exposureand no differences in socio-cultural circumstances (Modiano et al., 1996, Dolo et al., 2005). Data indicatethe existence of genetic differences in immunoregulatory pathways in these different ethnic groups (Luoni et al., 2001, Vafa et al., 2008, Israelsson et al., 2008, Mangano et al., 2008).
We propose to investigategenetic polymorphisms in the Fc?R (i.e the activating Fc?RI, Fc?RIIa, Fc?RIIc, Fc?RIIIa, Fc?RIIIb and theinhibitory Fc?RIIb) and in the C-reactive protein (CRP), innate molecules that are known to be involved inthe shaping of the B-cell compartment, possibly affecting the outcome of malaria disease (Troye-Blomberg).This work package will be closely linked to that of MalariaGEN, a consortium of malaria researchers in 21countries funded by the Grand Challenges in Global Health initiative to investigate mechanisms of hostresistance to malaria by large-scale genome-wide association studies (GWAS) in multiple populations(Kwiatkowski). This includes a case-control study of severe malaria in >20,000 subjects recruited in BurkinaFaso, Cameroon, Gambia, Ghana, Malawi, Mali, Nigeria, Papua New Guinea, Senegal, Sudan, Tanzaniaand Vietnam. There will be synergies and mutual benefits. The coordinator of MalariaGEN, Prof.Kwiatkowski, is a member of Evimalar.
Work package 1.3.3. Bioinformatics WP1.3.3.1. Vector bioinformatics (FORTH, IC2, UR, SU)
Rapid accumulation of biological data calls fordevelopment of powerful databases to allow handling, retrieving and rapidly analysing gathered information.For vector biology, this is addressed by the development of VectorBase, a database that provides storageand analysis for genomic data of arthropod vectors of human diseases (Lawson et al., 2007). VectorBasecontains genome information for A. gambiae and for other insect vectors. In addition to genomic sequences,it has initiated a community annotation system, a modern microarray expression data repository, controlledvocabularies for anatomy and insecticide resistance (Topalis et al., 2008a).
Important part of this workpackage will be continuous development of both the software infrastructure and tools for querying thedatabase. The repertoire of biomedical ontologies will be further extended and made publicly available.Therefore vector bioinformatics will profit different area of research in vector biology and serve as a crossclustertechnological platform. The experimental data generated by microarray studies performed within andoutside of the Consortium will be integrated and easily accessible for alternate analyses and meta-analysesthrough a robust, transparent and comprehensive database. To this end, website serving gene expressionsummary reports suitable for use by microarray experts and non-experts alike has been created and will befurther developed (FORTH, IC2).EVIMalaR: a European Virtual Institute for Malaria Research 30/10/2009Page 20 of 214Finally, a direct bioinformatics analysis of different aspects of processes dealing with vectorial capacity inthe wide sense will be carried out.
Participants of Cluster 3 will be assisted in the analysis of their data up tothe point of inclusion in the database. This assistance will be provided for projects dealing with searchesrelated to gene expression experiments using microarray platforms, proteomic and other post-genomicapproaches (FORTH, IC2, UR, SU). Anticipated risks and contingency plan: no particular risks are envisaged in this work package. As above VectorBase has been developed and expertise are available at leading institutions FORTH and IC2.
WP1.3.3.2. Host bioinformatics (FORTH, IC2, UR)
It is by now established that databases can profitsubstantially from their being based on, or directly linked to ontologies and controlled vocabularies. It isplanned to further develop the toolbox described in Cluster 5 through the development of an ontology ofpopulation biology. The reason for this effort is to be able to assist the members of Cluster 3 in the storageand mining of data, which will be collected in the frame of this project. This ontology, once ready, will beoffered to the members of this network as a free-to-use platform that could be further modified/expanded tomeet specific goals.
As part of the MalariaGEN consortium and the World Antimalarial Resistance Network,the Kwiatkowski lab is developing informatic platforms for integrating phenotypic and genetic data acrossmultiple study sites, and relevant software tools will be made freely available for Evimalar projects. No anticipated difficulties other than a potential, reduced data-flow from the laboratories that collect the relevant data in the field. This, if it occurs, will only affect work in the future, as the first priorities before the population of a database will be the development of the actual ontologies that will not be hindered.
References
Arcà et al., (2005) J Exp Biol, 208: 3971. Blandin SA et al (2008) Cell Host Microbe, 12: 364. Catteruccia etal (2005) Nat Biotechnol., 23: 1414. Lawson et al (2007) Nucl. Acids Res., 35: D503. Osta et al (2004) J. Exp. Biol. 207: 2551. Topalis, et al (2008a) Insect Mol. Biol., 17: 87. Tirados et al (2006) Med Vet Entomol,20: 425. Arcà et al. (2007) Insect Biochem Mol Biol 37: 107. Berir et al (2007) Eur J Hum Genet 15:1183.Dolo et al (2005) Am J Trop Med Hyg 72: 243. Donovan et al. (2007) Infect Immun 75: 2523. Drysdale R etal. (2008) Methods Mol Biol. 420:45. Fonseca et al. (2007) Malar J 6: 77. Gomes et al. (2008) Proc Natl Acad Sci U S A 105: 7845. Israelsson et al (2008) Malaria J 7: 175. Luoni et al (2001) Genes and Immunity 27: 411. Mangano et al (2008) Genes and Immunity 1. Modiano et al (1996) Proc Natl Acad Sci U S A 93:13206. Mungall CJ et al. (2007) Bioinformatics 23: i337. Niare et al (2002) Science 298: 213. Orlandi-Pradines et al. (2007) Microbes Infect 9: 1454. Remoue et al. (2006) Trans R Soc Trop Med Hyg 100: 363.Riehle et al. (2006) Science 312: 557. Riehle et al (2007) Malaria J 6: 87. Topalis P et al. (2008b) Trends Parasitol., 24: 249. Vafa et al (2009) Acta Tropica 109: 12. Valenzuela et al. (2003) Insect Biochem Mol Biol 33: 717.
