Networks of pathways
Results
Network: Mechanisms of Cytoskeletal changes
Regulation of cellular shape seems to be an important trait associated with the
reaction to Salmonella infection, but also chicken line differences seems to relate to
the expression of the cytoskeleton. Ten pathways regulating changes of the actin
cytoskeleton were found. Regulation of actin cytoskeleton pathway is central to this
process, but nine other pathways were found to regulate this pathway.
Cytoskeletal changes
Adherence
junction
Leukocyte
transendothelial
migration
General
Line A and Line B
Line A
Line B
B-cell receptor
signaling
T-cell receptor
signaling
Focal adhesion
Regulation of
Actin cytoskeleton
Axon guidance
Tight junction
(CAMs –
cell adhesion
molecules)
WNT signaling
The results show (for details per pathway see Additional files 2 and 3) that
within the pathways constituting this network the lines differ in expression level with
a higher expression level of many genes in line B compared to line A. The difference
in expression level disappeared 24 hours following infection with Salmonella, except
for the WNT signalling pathway. In all pathways Salmonella infection induced
expression levels in line A while line B did not respond, or showed a limited number
of genes with up or down regulation. The changes in the expression levels of the
genes resulted in equal expression levels of the genes in nine out of ten pathways 24
hours after Salmonella infection. The results for the “B-cell receptor signalling
pathway” and the “T-cell receptor signalling” pathways are in agreement with the
previously reported data (van Hemert et al., 2006A, B).
Network: Apoptosis mechanism
Apoptosis may be involved in the reaction of an organism to pathogen infection.
Regulation of apoptosis is described in the “Apoptosis” pathway, which is directly or
indirectly regulated through the expression of the genes in other pathways. The results
(for details per pathway see Additional files 2 and 3) indicate that (1) chicken line
differences not affected basal expression levels, but (2) different reaction of the lines
to Salmonella infection. Line A reaction to Salmonella infection is directed to up
regulating an apoptosis related mechanism. The reaction of line B to Salmonella
infection is more directed to up regulation of proliferation and differentiation of cells
which may be related to a growth response of the animal.
Apoptosis
General
Line A and Line B
Line A
Line B
NK cell mediated
cytotoxicity
JAK/STAT
signaling
Apoptosis
(MAPK signaling)
TGF-b signaling
Network: Regulation of energy metabolism
Energy metabolism may be involved in the reaction of the chicken lines to Salmonella
due to activation of cells and defence mechanisms, or reduced feed intake of the
animal. The results (for details per pathway see Additional files 2 and 3) indicate that
chicken line differences affected only fatty acid metabolism with expression levels in
line B higher than in line A. Infection for 24 hours with Salmonella resulted in down
regulation of the expression of genes in the energy metabolism pathways in both lines.
However, after 24 hours the overall expression level in three out of six pathways
indicate a higher expression in line B compared to line A.
Energy metabolism
General
Line A and Line B
Line A
Line B
Glycerolipid
metabolism
Purine metabolism
Insulin signaling
Pentose phosphate
metabolism
Fatty acid
metabolism
Glycolysis
Gluconeogenesis
Other Metabolic pathways
Several other pathways were found by searching the KEGG database that showed
regulated expression either between the chicken lines or after Salmonella infection.
These pathways are not known to act together in networks as describe above.
However, these pathways could be important. Details about the pathways can be
found in additional files 2 and 3. To summarize the results: Four immune response
related pathways neither differed between the lines nor showed response to
Salmonella infection. However, this may be caused by the lack of several immunerelated genes on the microarray. Four individual pathways each related to amino acid
metabolism and protein breakdown showed regulation during several experiments, but
no general conclusion such as for the networks described above could be drawn.
Metabolism of xenobiotics and caprolactam may be regulated during infection, but the
biological meaning of this is unclear. Line B showed infection related down
regulation of estrogen and bile acid biosynthesis. The existing line difference also
showed higher expression in line B compared to line A. Thus, Salmonella infection
increased existing line differences in expression. Finally, a line difference seems to
exist for circadian rhythm and this pathway is down regulated by infection in both
lines.
Discussion
New knowledge derived from pathway analysis
Analysis of microarray data usually starts with listing up and down regulated genes.
Previously, this analysis was reported (van Hemert et al., 2006A, B). The results
indicated line difference in the reaction to Salmonella infection. Line A seems to react
more via a T-cell activation mechanism, while line B reacts via a macrophage
activation mechanism. Differential expression of cytoskeletal genes was also reported.
In this study we used the same experimental data and analyzed it with new tools able
to combine the microarray results with the physiological knowledge available through
databases on the internet. The results indicate up or down regulation of (parts of)
biochemical pathways and networks of biochemical pathways. However, one should
keep in mind that the jejunum tissue samples used are heterogeneous and contain
several cell types. So, diverse parts of the networks may be active in different cell
types, not necessarily within a single cell.
Part of the results confirmed the results previously reported using the list of up
and down regulated genes (van Hemert et al., 2006A, B): e.g. up/down regulation
analysis also indicates important regulation of the expression of cytoskeletal genes.
The pathway analysis expands these findings to create a network of ten biochemical
pathways together regulating the cytoskeletal shape. The induction of the T-cell and
macrophage function reaction responses as reported by van Hemert et al. (van Hemert
et al., 2006A, B) – although important on their own - proved to be part of this process.
Furthermore, the lines differ in their expression level since the pathways in this
network show higher expression in line B compared to line A. Following Salmonella
infection line A increases its expression to the same level of line B. Lines A and B
differ in their Salmonella susceptibility phenotype. The faster growing line A is more
susceptible to Salmonella infection than the slower growing line B. The difference in
the susceptibility phenotype is defined by the fact that line A shows more liver
colonies after infection than line B (van Hemert et al., 2006A, B). Our results suggest
that the underlying difference in the selection background between the lines has
changed expression of the genes in the network regulating the cytoskeleton. This has
apparently influenced the reaction mechanism of the animal to respond to Salmonella
infection. Our results may suggest that in the slower growing line B the expression
level of the genes in this network seems more appropriate to respond to infection than
the expression level in the faster growing line A, which up regulates the gene
expression in response to Salmonella infection. It can be speculated that this
mechanism causes a delay in response of line A related to the difference in
susceptibility phenotype. These results may indicate a causal mechanism for the
difference in susceptibility phenotype between the chicken lines. The different
selection background of the chicken lines has – amongst others – created a difference
in growth rate between the chicken lines as these genes may respond to the growth
rate phenotype of the animal. This is accompanied with a difference in expression
level of the pathways in the network. The most susceptible line A shows a lower
expression level of genes in this network than the less susceptible line B followed by
an up regulation of the genes in the pathways in this network in line A following a
Salmonella infection. If this mechanism proves true the genetic background of the
animal causes difference in growth rate, which causes the differential expression of
the genes in the network, which causes the difference in susceptibility phenotype.
Next the results also provide insight in other mechanisms taking place in the
jejunum of Salmonella infected young chicken.. Pathway analysis suggests that line A
react to Salmonella infection with an apoptotic mechanism while line B resumes
growing (i.e. proliferation and differentiation mechanisms). The latter result may be
supported by the higher expression of genes related to energy metabolism in line B
making energy available for the mechanisms of growth. However, it should be noted
that the expression levels of the genes in the energy metabolism pathways were
reduced in both lines, but the effect was more severe in line A than in line B.
Differences in amino acid metabolism and protein breakdown mechanism may add to
this effect. Furthermore, differential expression of Bile acid synthesis may also add to
this energy availability, and to the functioning capacity of the intestine. These results
may again indicate causal relationships between selection response and differences
between Salmonella susceptibility phenotype of the chicken lines. It can be speculated
that because both lines have similar gene expression levels in energy metabolism
pathways under uninfected conditions the faster growing line A is less robust for
energy availability than the slower growing line B when Salmonella infects the
animal. This causes line A to choose for a more apoptosis mechanism while line B
resumes growing. Again a genetic difference due to the difference in the selection
background of the chicken lines could be causal to the difference in Salmonella
susceptibility.
The lack of differential expression in several immune-related pathways may be
caused by the scarcity of immune genes on the microarray. However, the
adipocytokine signalling pathways showed up regulation following Salmonella
infection, mainly in line A. This may also be related to the growth rate since higher
growth rate often relates to lower adipose tissue thickness – as is also suggested for
these lines in the Fatty acid metabolism pathway. It is known that the adipose tissue
produces many cytokines. Thus, this pathway may be related to the host response to
Salmonella infection. Again it can be speculated that this result relates to the level of
resistance to Salmonella infection.
Finally, part of the results suggests that novel pathways may be involved such as
caprolactam degradation and xenobiotics routes. Gender differences may be involved,
and circadian rhythm may be affected. These pathways suggest novel mechanisms
associated with the hosts’ response to Salmonella infection. Further investigations
validating these mechanisms for the resistance mechanisms are required.