Vector Genetics Laboratory
University of California, Davis
Malaria, caused by parasites in the genus Plasmodium, is by far the most significant vector-borne disease of man with 190-311 million clinical cases and 1 million deaths each year. The heaviest burden is in sub-Saharan Africa. Why is Africa hit so hard?
There is no simple answer to this question. Certainly economic and political issues are major contributing factors, but there are biological factors that also contribute, in a major way, to the African malaria problem. Plasmodium falciparum is the most lethal malaria parasite of man and the most important and potent vectors are two closely related and morphologically indistinguishable species; Anopheles gambiae and An. arabiensis. Aspects of the ecology and behavior of these species result in their being exquisitely disposed to transmitting malaria parasites and well adapted to resist efforts to control them. Research being conducted at the Vector Genetics Laboratory at UC Davis is aimed at understanding the genetics of natural populations of these two species and specifically in establishing the genetic basis of traits important for malaria transmission and vector control.
Our approach centers on two common-sense principals:
- use the best tools available to address the problem at hand and
- don’t be afraid to get your hands dirty.
Exciting new tools have been, and continue to be, developed for studying the genetics of disease vectors. The whole genome of Anopheles gambiae was sequenced and published in 2002. This achievement and the work leading up to it provided the means of extending studies of vector population genetics into the era of population genomics. In the not-too-distant past the genetics of mosquito populations were described by determining the distribution of variation in 10-20 genetic markers (isozymes, microsatellite DNA). Today such studies can use hundreds or even thousands of markers such as single nucleotide polymorphisms (SNPs). SNPs are single base pair differences in the DNA of individual mosquitoes. More advanced technologies employing DNA microarrays can allow the simultaneous analysis of hundreds of thousands of markers in a single mosquito (Turner et al. 2005, Neafsey et al. 2010).
The University of California Malaria Research and Control Group (see story in Wing Beats Fall 2007) recently developed what is called a “whole genome tiling array” for An. gambiae. This is a microarray that contains millions of small DNA probes (25 base pairs in length) that cover the entire genome of An. gambiae. This allows us to compare the genomes of individual mosquitoes for 13 million genetic markers! The much higher resolution offered by these new tools not only improves our ability to detect genetic divergence between mosquito populations but allows us to pinpoint precise locations in the genome where they differ. Ultimately this will lead to the identification of genes that affect important traits, such as mate choice, host preference, susceptibility/refractoriness to parasite or virus pathogens, insecticide resistance, etc.
Much of the early work that employed these new tools utilized mosquitoes from laboratory colonies that differed in traits like susceptibility to malaria parasites or insecticide resistance. Such studies have serious limitations however, because often these traits in laboratory strains may not have the same genetic basis that produces these traits in nature (Tripet et al. 2008, Boëte 2009). The Vector Genetic Lab is committed to work based on natural populations and we have conducted extensive field work in Africa in collaboration with institutions throughout Africa. We currently have projects involving fieldwork in Guinea Bissau, Mali, Cameroon, Tanzania and the Comoros Islands.
Identifying immune genes responsible for susceptibility to Plasmodium parasites in A. gambiae in Mali and Cameroon.Significant data implicate various signaling pathways in the mosquito immune system in the regulation of malaria parasite development in the Anopheles gambiae midgut. However, no data are available to confirm that these pathways regulate parasite development in nature. The Vector Genetics lab, in collaboration with the laboratory of Dr. Shirley Luckhart in the Department of Medical Microbiology and Immunology, School of Medicine at UC Davis, have chosen to address this issue using a SNP association approach with field-collected mosquitoes from Mali and Cameroon, countries with high malaria transmission that include the geographic distribution of the most genetically diverged A. gambiae populations yet described.
The first component of this project includes population genetic analyses. Plasmodium falciparum infected and uninfected A. gambiae are being collected from sites in Mali and Cameroon. These sites were carefully selected to include all of the mosquito genetic diversity known to exist in the region (three molecular forms and chromosome inversion polymorphism). Mosquito samples are grouped by site with respect to infection, molecular form and karyotype. Each mosquito is then genotyped for roughly 384 immune signaling gene SNPs and examined if those SNPs are correlated with infection. If any of the 384 SNPs occurs more frequently in infected versus uninfected mosquitoes, they may contribute to making the mosquito susceptible to Plasmodium infection.
In the second project component, selected SNPs of interest will be analyzed to determine their effects on mosquito protein function and on susceptibility to P. falciparum infection in the laboratory using both mosquito cell lines and live mosquitoes from colony. Two genetically distinct strains of A. gambiae, which have been genotyped for the SNPs of interest will be used in the laboratory studies. We will use inhibitors and DNA transfection protocols to mimic the effects of SNP-containing alleles on P. falciparum development in artificially infected mosquitoes. This work will take functional data from Dr. Luckhart’s lab and from the labs of our colleagues to examine the importance of the selected immune signaling pathways in field-collected mosquitoes. These studies will facilitate selection of appropriate gene targets for strategies involving genetically modified mosquitoes for malaria control and provide critical new insights into the immunity in A. gambiae populations.
This project is being conducted in collaboration with Dr. Sékou Traoré, Malaria Research and Training Center, University of Bamako, Mali and Dr. Etienne Fondjo, National Malaria Control Programme, Youndé, Cameroon.
Ecological and genetic determinants of malaria transmitting behaviors in Anopheles arabiensis in Tanzania.Anopheles gambiae is frequently referred to as the most important vector of malaria in Africa and has been the main focus of malaria vector research. Despite this attention, there is growing evidence that it is not this species, but its sister species A. arabiensis that is increasingly responsible for malaria transmission in Africa. Reports indicate that in areas of high insecticide treated net (ITN) coverage, A. arabiensis outcompetes An. gambiae s.s and has become the dominant vector species in many locations. If this phenomenon continues as large-scale ITN programs are rolled out across Africa, this species could become the only medically relevant vector in many parts of the continent. Consequently the ecology, vectorial competence and population genetics of this somewhat neglected vector merit particular attention in preparation for future vector control scenarios.
This research program integrates vector population genomics, ecology and vector behavior with the goal of understanding the determinants of two mosquito behavioral phenotypes crucial to the transmission and control of malaria: (1) host preference and (2) adult resting behavior. Our approach builds upon a sizeable base of preliminary work, conducted in our laboratory, which has identified an extensive panel of A. arabiensis SNP markers, and preliminary field work in Tanzania that has identified a range of appropriate sites where sampling methods have been piloted and the behavior of A. arabiensis is known to vary.
A. arabiensis mosquitoes will be intensively collected from four villages in the Kilombero Valley of Tanzania during the wet and dry seasons to determine the association between their feeding and resting phenotype and environmental factors that vary temporally and spatially (component #1). DNA will be extracted from individual samples and multi-locus SNP genotypes determined from each individual. Genotypes will be organized by phenotype (exophilic vs. endophilic and human fed vs. animal fed) and analyzed to determine SNP allele associations with each phenotype after correcting for population structure (component #2).
Knowledge of the genetic basis of these behavioral changes will be vital for prediction of both possible downstream evolutionary responses to current vector control strategies, and also for the development of novel control strategies that improve the application of currently available vector control methods and/or that are based on vector genetic manipulation.
This project is being conducted in collaboration with Drs. Heather Ferguson and Daniel Haydon, University of Glasgow, UK, Dr. Gerry Killeen, Ifakara Health Institute, Tanzania and Dr. Eleazar Eskin, University of California, Los Angeles.
PopI: An Online Database for Vector Population Genetics.PopI is an individual-level Population Genomics Database for arthropod disease vectors. It is the first open database that combines population, ecology, and individual-level genomic information for arthropod vector species. Content is coordinated by the Vector Genetics Laboratory at UC Davis.
Current research on the genetics of vector populations is evolving toward the integration of genomics with classical population genetics. The relatively new field of “population genomics” will vastly expand our understanding of the biology of human disease vectors by providing a bridge between the laboratory and field. Research in this area promises to:
- define the role of natural variation in complex vector-borne disease transmission cycles
- reveal new targets for the next generation of control methodologies
- improve our understanding of how vector populations evolve to avoid current control measures
- inform the development of vectorborne disease models