1 / 20

Tsetse fly

Tsetse fly. 2. 1. Lessons from triatomine bugs: Chagas disease control. SNP diversity. 3. Combining the tsetse fly genome with disease control. Cool phylogenomics. Michael Gaunt LSHTM/ SANBI. Vector-borne transmission in Trypanosoma cruzi. Sympatric speciation.

kibo-jefferson
Download Presentation

Tsetse fly

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Tsetse fly 2 1 Lessons from triatomine bugs: Chagas disease control SNP diversity 3 Combining the tsetse fly genome with disease control Cool phylogenomics Michael Gaunt LSHTM/ SANBI

  2. Vector-borne transmission in Trypanosoma cruzi Sympatric speciation Triatomines evolved with the formation of South America 95 MYA* Triatomine bugs (Rhodnius sp.) Palms * Gaunt and Miles (2002) reviewed by Science

  3. Sylvatic hosts of T. cruzi

  4. A domesticated vector has nowhere to hide Basis of the Southern cone initiative: Triatoma infestans - a key vector in Argentina, Bolivia, Brazil, Chile, Paraguay, Uruguay and southern Peru - Domiciliated (domesticated) - Susceptible to insecticide (adults and nymphs) - Insecticide control is cheap

  5. Many deaths resulting from a genetically isolated vector population A simple solution……. Chris Schofield 

  6. The success of targeted vector control Apparent distribution of Triatoma infestans 2002 1982 Chris Schofield 

  7. Control Initiatives The Southern Cone Project Objectives 1. Interrupt transfusional transmission 2. Interrupt vectorial transmission Chris Schofield 

  8. The problem The Tsetse Belt Kenya Not a continuous inter-breeding population but distribution of specie and sub-species populations Uganda ?? Tanzania PATTEC Lake Victoria Basin Projects LTTRN - Leverhulme Trust Tsetse Research Network

  9. What might the tsetse genome look like? • EST clustering pipelines from the current tsetse library databases (midgut, salivary gland, and fatbody) • Identified one SNP every 518 base pairs (Pi = 0.0019) • The mosquito genome gives 1 SNP every 785 bp for cds (Pi = 0.0013) and 1/627 overall • Far higher than in Drosophila SNP diversity

  10. A very conservative estimate GACTGATAGACTGATAT----------------------------------GACTGATACACTGATAT-----------------GACTGATAGACTGATATGACTGATACACTGATAT GACTGATAGACTGATAT-----------------GACTGATAGACTGATAT8bp * 8bp STACKPack D2_cluster 6 out of 10 traces Must be present

  11. High levels of heterozygosity would create annotation problems Experimental criticisms • EST SNP diversity doesn’t equate to the total SNP diversity of genomic coding sequences • Controls are needed • However we should not be surprised if SNP diversity was as high as in Anopheles - biogeographically there are strong similarities

  12. What can a genome do? Recipe: • A) Take one draft genome • B) Add a bioinformatics pipeline to • B1) identify small tandem repeats • B2) Design primers for each tandem repeat • C) Apply genome-scale microsatellite loci to field samples

  13. Microsatellites • 70 loci spanning 2Mb of T. cruzi genome. • Resolution of population genetic structure of T. cruzi lineages in principal host species. • Hardy-Weinberg recombination analysis

  14. Bolivia: opossum Philander and Didelphis Biogeographic markers V I C A R I A N C E A L L O P A R Y Brazil: opossum Philander,Didelphis andmonkey Venezuela: opossum Didelphis Isolation not by pure geo-graphic distance

  15. Between species Sympatry and TCIIc

  16. Within species Sympatry and TCI Geneflow

  17. 1 X draft genome next year Funding in place to stripe out the MSATs (NBN) Some MSATs defined Evidence of genetic allopatry Leverhulme network of Chris Schofield coordinates the PATTEC Lake Victoria Basin projects in Kenya, Uganda and Tanzania The State of Play Community ecology Genetics PATTEC Governments • Kenyan and Ugandan governments have taken development loans to control tsetse

  18. Kenyan and Ugandan government Population collections Schofield network Kenya Uganda (Tanzania) Combining public health & pop. gen. PATTEC Morphometrics Proposed strategy MSATs African development loans Targeted tsetse control

  19. In summary T. cruzi and triatomine model are real examples of how thinking big population thinking solves problems • Fly collections are completed • Genome is poised - could be a heterozygosity issue • Good geneticists in Kenya, Uganda and Tanzania • Combine a high throughput, low cost technology (morphometrics) with MSATs - standardize the method …. then we have ignition • Governments are interested and monies are available Goal

  20. Acknowledgements • Win Hide, SANBI, SA • Chris Schofield, LSHTM, UK • Mark Walmawa (SANBI pending) • Christopher Maher & Lincoln Stein (Cold Spring Harbour, US) • Johnson Omur (BTRC, Kenya) • Dan Masiga (ICIPE, Kenya) Tsetse fly • Michael Miles, LSHTM • Martin Llewellyn, LSHTM Chagas disease Funding from the Wellcome Trust, NBN, SA and RCUK fellowship to MWG

More Related