Download Host genetics and disease resistance

Identification of gene networks associated with lipid
response to infection with Trypanosoma congolense
Brass A3; Broadhead, A2; Gibson, JP1; Iraqi, FA1, Kemp, SJ2; Musa, H1; Naessens, J1; Noyes, HA2;
1International Livestock Research Institute, P. O. Box 30709, Nairobi, Kenya
2School of Biological Sciences, University of Liverpool, L69 7ZB, UK
3Department of Computer Science, University of Manchester, UK
Introduction
Human African Trypanosomiasis (HAT) or sleeping sickness is caused by
subspecies of the protozoan parasite Trypanosoma brucei. A very similar
disease of cattle (nagana) is caused by Trypanosoma congolense. Both these
parasites live in the blood stream and are fatal unless treated. Estimates of
the number of humans infected vary widely but over 2 million are believed to
be infected in The Democratic Republic of the Congo alone. The cattle
disease has been estimated to cause economic losses of over 4 billion USD
per year and effectively restricts cattle production to areas of Africa where
numbers of the tsetse files that transmit the disease are low. The symptoms
of infection are generally non-specific and include cachexia, fever, anaemia in
cattle and neurological symptoms in humans.
The innate immune response controls infection
African trypanosomes are best known for their extreme antigenic variation. They
generate a new surface coat every seven to 14 days. Large numbers of antibodies are
generated to the surface antigens, and control each wave of parasitaemia. However, the
control of the disease appears to be T cell independent since the disease in T cell
deficient mice is no worse than in wild type mice.
Survival time after infection varies substantially between different inbred strains of mice
and between different breeds of African cattle. We have mapped QTL associated with
survival time in mice and with parasitaemia, anaemia and growth rate in cattle.
120
F2 AJ x C57BL6
AJ
% Survival
100
X
C57BL6
80
60
40
0
1
10
19
28
37
46
55
64
73
82
91
100
109
118
127
136
145
154
163
172
181
190
199
208
217
226
235
244
253
262
271
280
20
Days Post Challenge
Percentage survival of AJ, C57/BL6 mice and F2
AJxC57/BL6 by number of days post challenge.
A common mechanism controls HDL levels and Trypanosomiasis?
QTL for survival post infection with T. congolense and for HDL levels have been
fine mapped to chromosomes 1,5,16 and 17 (Mammalian Genome 2000 11:645648 and Genome Research 2003 13:1654-1664). Two of these QTL on
chromosomes One and Five overlap. Whilst there are many genes under these
QTL it is possible that a common regulatory mechanism controls both
phenotypes.
HDL QTL
Trypanosomiasis QTL
Cyp7a1 and SRB1 may regulate the differences in cholesterol levels.
C57Bl/6 mice are known to have relatively high cholesterol levels and are a
common model for atherosclerosis. Gene expression was measured on
Affymetrix microarrays and a key difference in gene expression in cholesterol
metabolism pathways was found in Cyp7a1 (cholesterol 7 alpha hydroxylase).
Cyp7a1 is the rate limiting step in bile acid synthesis and cholesterol secretion.
Relative expression of this enzyme was inversely correlated with cholesterol
levels at four time points post infection. SRB1 is a selective cholesterol
receptor. Over-expression of SRBI is correlated with to a reduction in plasma
cholesterol and an increase in biliary cholesterol (Nature 1997 387:414-417).
Plasma cholesterol increased in infected C57BL6 but not other strains at day 7
post infection (the peak of parasitaemia) and this correlated with a two fold
drop in SRBI expression in C57BL/6 at this time, consistent with SRBI
contributing to the increase in cholesterol in C57BL/6. SRBI is under the
chromosome 5 QTL, as is ATP10d which may be involved in cholesterol export
from macrophages and has a premature stop codon in C57BL6.
Conclusion
Lipids are known to be involved in the control of trypanosomiasis in humans.
There is a difference in lipid responses between susceptible and resistant
mouse strains. There are also differences in inflammatory responses between
mouse strains. The overlap of QTL for HDL and survival time post infection
suggests that the lipids may be the key regulator of inflammation. This may be
via PPAR, LXR and RXR transcription factors or via another as yet unidentified
mechanism.
Cholesterol levels correlate with survival after infection.
Total cholesterol, HDL and LDL cholesterol and Triglycerides were all measured in
infected mice which were maintained on high and low fat diets. HDL cholesterol and
LDL cholesterol levels both tracked total cholesterol which is shown. Cholesterol levels
declined after infection, and absolute levels correlated with susceptibility to infection.
C57BL/6 mice which survive longest after infection had highest cholesterol levels and
AJ mice which have the shortest survival time had the lowest cholesterol levels on both
diets. There was an indication that the Balb/c mice on the high fat diet survived longer
than the same mice on a low fat diet, but numbers were not sufficient to determine if
this was significant. A further experiment is currently underway to specifically test the
effect of high fat isocaloric diets on survival time.
Lipids and inflammation
Cholesterol synthesis and inflammation are known to be linked by HmgCoA which is the
key step in cholesterol and isoprenoid synthesis. Isoprenoids can regulate inflammatory
/ anti-inflammatory switch (Journal of Experimental Medicine 2006 203:401-412). AJ
mice which have the lowest cholesterol levels and the weakest inflammatory response
also had approximately two fold lower levels of HmgCoAr at all time points post
infection (not shown).
Overlay of gene expression post infection on macrophage gene networks indicates that
the RXR/LXR transcription factors are down regulated in susceptible AJ mice at day 9
post infection (E on map). These are known to also be regulators of inflammation as
well as lipid metabolism suggesting that these pathways may also be involved.