Combining the tsetse fly genome with

disease control

Lessons from triatomine bugs: Chagas disease

control

SNP diversity

Cool phylogenomics

Tsetse fly

1 2

3

Michael GauntLSHTM/ SANBI

Sympatric speciation

Vector-borne transmission in Vector-borne transmission in Trypanosoma cruziTrypanosoma cruzi

Triatomine bugs (Rhodnius sp.)Palms

Triatomines evolved with the formation of South America 95 MYA*

* Gaunt and Miles (2002) reviewed by Science

Sylvatic hosts of Sylvatic hosts of T. cruziT. cruzi

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

A domesticated vector has A domesticated vector has nowhere to hidenowhere to hide

Many deaths resulting from a genetically isolated Many deaths resulting from a genetically isolated vector populationvector population

A simple solution…….A simple solution…….Chris Schofield

Apparent distribution of Triatoma infestans

1982 2002

The success of targeted vector control

Chris Schofield

Control InitiativesObjectives

2. Interrupt vectorial transmission

1. Interrupt transfusional transmission

The Southern Cone ProjectThe Southern Cone Project

Chris Schofield

??

PATTEC Lake Victoria Basin Projects LTTRN - Leverhulme Trust Tsetse Research Network

The Tsetse BeltThe Tsetse Belt

TanzaniaTanzania

KenyaKenya

UgandaUganda

The problem

Not a continuous inter-breeding population but distribution of

specie and sub-species populations

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

A very conservative estimateA very conservative estimateGACTGATAGACTGATAGGACTGATATACTGATAT--------------------------------------------------------------------GACTGATAGACTGATACCACTGATATACTGATAT----------------------------------GACTGATAGACTGATAGGACTGATATACTGATATGACTGATAGACTGATACCACTGATAT ACTGATAT GACTGATAGACTGATAGGACTGATATACTGATAT----------------------------------GACTGATAGACTGATAGGACTGATATACTGATAT

8bp8bp * * 8bp8bp

6 out of 10 traces

Must be present

STACKPackD2_cluster

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

High levels of heterozygosity would create annotation problems

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

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

Brazil: opossum Philander, Didelphis and monkey

Bolivia: opossum Philander and Didelphis

Venezuela: opossum Didelphis

AALLLLOOPPAARRYY

VVIICCAARRIIAANNCCEEIsolation

not bypure

geo-graphicdistance

Biogeographic Biogeographic markersmarkers

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Sympatry and TCIIc

Between speciesBetween species

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Sympatry and TCISympatry and TCI

Geneflow

Within speciesWithin species

The State of PlayThe State of Play

• 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

• Kenyan and Ugandan governments have taken development loans to control tsetse

Community ecology

Genetics

Governments

PATTEC

Combining public health & pop. gen.

• Kenyan and Ugandan government

• Population collections Schofield network– Kenya– Uganda

– (Tanzania)

Morphometrics

MSATs

PATTEC

Proposed strategy

Targeted tsetse control

African development loans

In summaryIn summary

• 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

T. cruzi and triatomine model are real examples of how thinking big population thinking solves problems

Goal

Acknowledgements• Win Hide, SANBI, SAWin Hide, SANBI, SA• Chris Schofield, LSHTM, UKChris Schofield, LSHTM, UK• Mark Walmawa (SANBI pending)Mark Walmawa (SANBI pending)• Christopher Maher & Lincoln Stein

(Cold Spring Harbour, US)

• Johnson Omur (BTRC, Kenya)Johnson Omur (BTRC, Kenya)• Dan Masiga (ICIPE, Kenya)Dan Masiga (ICIPE, Kenya)

Funding from the Wellcome Trust, NBN, SA and RCUK fellowship to MWG

• Michael Miles, LSHTM• Martin Llewellyn, LSHTM

Tsetse fly

Chagas disease