Functional genomics to explore host response to trypanosome infection in particular and stress in ge

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Functional genomics to explore host response to
trypanosome infection in particular and stress in
general.
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Shirakawa Institute of Animal Genetics
KARI-TRC
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Trypanosomosis Is a fatal disease of livestock.
The livestock equivalent of sleeping sickness in
humans
T. congolense, T. vivax
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Role of livestock - (should we all be
vegetarians?) Ghibe valley, Ethiopia
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Origins of NDama and Boran cattle
Boran
NDama
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Boran
NDama
change in PCV
days after infection
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• Studying the tolerant/susceptible phenotype has
  problems
• Separating cause from effect
• Separating relevant from irrelevant.
• Dominance of the what is happening to this
  weeks trendy gene/protein/cytokine? approach.

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• Studying tolerance susceptibility any way has
  problems
• We have no idea of the mechanisms
• We have no idea of effector tissue
• We have no in vitro model

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Mapping trypanotolerance loci of the NDama
would allow the rapid introgression of desired
traits from other breeds into the NDama, while
retaining the trypanotolerance traits or the
rapid introgression of the trypanotolerance trait
from the NDama to other breeds. Mapping of
trypanotolerance loci would also be the first
step in their eventual cloning and manipulation
through genetic engineering techniques
M. Soller and J.S. Beckmann, FAO Consultation
Report, March 1987
CCER June 2002
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Contribution of 10 genes from Boranand NDama
cattle to reduction in degree of trypanosomosis
Boran (relatively susceptible)
NDama (tolerant)
The NDama and Boran each contribute
trypanotolerance alleles at 5 of the 10 most
significant QTL, indicating that a synthetic
breed could have even higher tolerance than the
NDama.
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In mice, we mapped three genomic regions which
determine survival time following T. congolense
infection

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D17Mit46




D17Mit16



D5Mit233


D17Mit7



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D5Mit114




D5Mit24

D1Nds2





MMU17


D1Mit102


80




D1Mit113



D1Mit403

MMU5




MMU1


120cM




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• What are these genes ?
• How do they affect survival ?
• What response pathways are common to
  mouse/cow/human ?
• What does that tell us about how to survive
  trypanosome challenge ?
• The mapping data gives us a point of attack for a
  functional approach.

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Functional genomics technology allows us to look
at what genes respond to infectionAnd
especially what genes respond differently to
infection
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Expression analysis of cow and mouse, resistant
and susceptible.
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Expression studiesCow Ndama vs Boran time
course Ndama x Boran backcross Mouse C57
vs A/J Balb/c time course C57A/J
congenics Various mouse mutants (C57A/J BAC
transgenics)
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Cattle Microarray Time Course Design
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Cattle Microarray Time Course Design
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PCA Liver day 0. 1st component tissue, this is 2nd

• Principle components analysis of data from
  genome-wide expression analysis comparing gene
  expression in liver of Ndama (red) vs Boran
  (blue) in response to infection with T.
  congolense. Light colour day 29 post infection,
  dark day 32 post infection. Components 1 and 2.
  (Components 3 and 4 separate by day post
  infection)

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And the same data for spleen. The biggest effect
we see (after tissue) is breed.

• Principle components analysis of data from
  genome-wide expression analysis comparing gene
  expression in spleen of Ndama (red) vs Boran
  (blue) in response to infection with T.
  congolense. Light colour day 29 post infection,
  dark day 32 post infection. Components 1 and 2.
  (Components 3 and 4 separate by day post
  infection)

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Analysis

• What genes are differentially expressed
  genomewide?
• What pathways are they members of?
• What pathways involve genes in the QTL?
• What pathways are in both lists ?
• Prioritise the list by 'degree of change'
• Look at the biology of each network

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Paraoxonase 3 Chr 4 Near Parasitaemia QTL??
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Paraoxonase 3 (PON3)

• PON1 knockout mice are more susceptible to T.
  congolense
• PON3 is a 40-kDa protein associated with the high
  density lipoprotein fraction of serum
• PON3 rapidly hydrolyzes lactones such as statin
  prodrugs (e.g. lovastatin)
• PON3 is more efficient than rabbit PON1 in
  protecting low density lipoprotein from
  copper-induced oxidation

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Microarray design at each time point
Resistant C57BL/6
Susceptible AJ
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Mouse time course. Liver.
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Cholesterol metabolism
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Endogenous cholesterol production increases after
infection
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Total Cholesterol levels
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African cows to Salford ICU
High cholesterol in African cattle identified as
a protective factor against death from
trypanosomiasis
Is high cholesterol a protective factor in humans
undergoing extreme inflammation?
ICU data and physicians in Salford lab
accessible, plus heamoglobin, creatinine and
glucose clampingfrom normal ICU practice
minimises major confounders
Data cleaning, meta-data capture, analysis
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Congenics

• Lines fixed for alternative alleles of each QTL
  on a susceptible background.

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Breeding congenic Mice carrying the
Trypanotolerance QTLs
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number of differentially expressed genes in C57 v
A/J (green) number of differentially expressed
genes in Tir1AA v Tir1CC (black, gt0.99)
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A/J v C57 expression differences (fold change
gt0.5, P lt0.01) sequence differences (number of
informative SNPs in the 1Kb upstream of each
probed gene) across the C57 and A/J genomes.
(summed in 50 probe bins)
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What to do with candidate genes

• All the obvious things
• Plus
• Exploit the unique populations (and high density
  SNP panels) of cattle
• Recently admixed resistant susceptible
• Multiple resistant breeds
• Multiple resistant species (sheep, goat, wildlife)

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Some conclusions
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Expression analysis in cow and mouse has revealed
some unexpected pathways and interactions.
(Survival seems to be about the innate immune
response and managing cholesterol) Overlaying QTL
and expression data has been incredibly
informative. We have learned a lot about host
response to trypanosomes, but also about How to
survive a tryps infection How to survive in an
ICU in Salford Fundamentals of genome
regulation. If you do high quality science there
will be high quality - but unpredictable -
outcomes.
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Expression analysis in cow and mouse has revealed
some unexpected pathways and interactions.
(Survival seems to be about the innate immune
response and managing cholesterol) Overlaying QTL
and expression data has been incredibly
informative. We have learned a lot about host
response to trypanosomes, but also about How to
survive a tryps infection How to survive in an
ICU in Salford Fundamentals of genome
regulation. If you do high quality science there
will be high quality - but unpredictable -
outcomes. How to analyse this type of data and
extract important differences.
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Overlaying multiple species has been extremely
valuable. There is a clear synergy to be won and
additional livestock species would be extremely
valuable for a range of traits (the
international sheep consortium needs to develop
genetics and genomics resources - draft / skim
genome sequence, dense coverage SNP panels etc.).
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Shirakawa Institute of Animal Genetics
KARI-TRC
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Intersection of Cholesterol and Inflammatory
pathways
Th2 bias
Suppression of cholesterol synthesis
Dunn et al Journal of Experimental Medicine Vol.
203, No. 2, February 20, 2006 401412