"
Team:USTC-Software/Project/Examples
From 2013.igem.org
| Line 1,284: | Line 1,284: | ||
<h2>Reference</h2> | <h2>Reference</h2> | ||
| - | <p align="justify"><a class="content" href=" | + | <p align="justify"><a class="content" href="http://www.jbc.org/content/275/38/29672.short">Arfin S M, Long A D, Ito E T, et al. Global Gene Expression Profiling in Escherichia coliK12 THE EFFECTS OF INTEGRATION HOST FACTOR[J]. Journal of Biological Chemistry, 2000, 275(38): 29672-29684.</a></br></br> |
| + | <a class="content" href="http://www.jbc.org/content/277/43/40309.short">Hung S, Baldi P, Hatfield G W. Global Gene Expression Profiling in Escherichia coliK12 THE EFFECTS OF LEUCINE-RESPONSIVE REGULATORY PROTEIN[J]. Journal of Biological Chemistry, 2002, 277(43): 40309-40323.</a></br></br> | ||
| - | + | <a class="content" href="http://www.jbc.org/content/278/32/29837.short">Salmon K, Hung S, Mekjian K, et al. Global Gene Expression Profiling in Escherichia coli K12 THE EFFECTS OF OXYGEN AVAILABILITY AND FNR[J]. Journal of Biological Chemistry, 2003, 278(32): 29837-29855.</a></br></br> | |
| - | + | <a class="content" href="http://www.jbc.org/content/280/15/15084.short">Salmon K A, Hung S, Steffen N R, et al. Global Gene Expression Profiling in Escherichia coli K12 EFFECTS OF OXYGEN AVAILABILITY AND ArcA[J]. Journal of Biological Chemistry, 2005, 280(15): 15084-15096.</a> | |
| - | <a class="content" href=" | + | |
| - | + | ||
| - | + | ||
| - | + | ||
| - | + | ||
</p> | </p> | ||
Revision as of 08:34, 27 October 2013
Examples
Test and verify by experiment literatures
To prove our software’s reliability, we search for lots of literatures. It is hard to find an appropriate literature which research the effect of importing an exogenous gene into E.coli K-12. But actually, our software could also simulate the effect of changing endogenous gene by putting the same promoter and gene sequence in. So, we eventually found four literatures to test and verify our software.
Global Gene Expression Profiling in Escherichia coliK12 THE EFFECTS OF INTEGRATION HOST FACTOR
In this literature, Stuart and his team measure the gene expression profiles in otherwise isogenic integration host factor IHF+ and IHF- strains. And IHF is one of the genes in our genetic regulatory network(GRN). By importing the IHF’s promoter and gene sequence, we used our software simulating the enhancement of IHF’s expression and compared the result with the gene expression profile in that literature. There are 30 genes in that profile which are also in our GRN. Here is the list and Genes differentially expressed between E. coli K12 strains IH100 (IHF+) and IH105 (IHF-) with a p value less than 0.0005:
Gene |
Avg |
S.D. |
p value |
Fold |
Compare |
||
IH100 |
IH105 |
IH100 |
IH105 |
||||
glnA |
2.91E-03 |
9.39E-04 |
6.80E-04 |
1.33E-04 |
1.30E-03 |
-3.1 |
fit |
ilvA |
5.06E-04 |
3.42E-04 |
1.86E-05 |
2.26E-05 |
3.00E-05 |
-1.48 |
unfit |
ilvE |
5.81E-04 |
3.58E-04 |
4.70E-05 |
5.77E-05 |
9.80E-04 |
-1.62 |
unfit |
ilvG |
1.97E-04 |
7.67E-05 |
2.65E-05 |
2.23E-05 |
4.40E-04 |
-2.57 |
unfit |
leuA |
6.99E-04 |
1.07E-03 |
9.21E-05 |
9.23E-05 |
1.30E-03 |
1.53 |
fit |
cobT |
1.00E-05 |
7.97E-05 |
7.82E-06 |
2.13E-05 |
8.50E-04 |
7.97 |
unfit |
cobU |
4.26E-05 |
1.22E-04 |
1.79E-05 |
1.95E-05 |
9.90E-04 |
2.85 |
unfit |
lacA |
5.14E-03 |
1.21E-03 |
1.54E-03 |
3.52E-04 |
2.50E-03 |
-4.24 |
unfit |
lacZ |
2.10E-03 |
5.14E-04 |
3.77E-04 |
1.34E-04 |
2.20E-04 |
-4.08 |
unfit |
lacY |
1.62E-03 |
4.08E-04 |
2.53E-04 |
7.95E-05 |
9.80E-05 |
-3.96 |
unfit |
ompF |
7.23E-03 |
2.35E-03 |
1.90E-03 |
3.69E-04 |
2.40E-03 |
-3.07 |
fit |
gltD |
9.91E-04 |
1.40E-04 |
1.88E-04 |
3.06E-05 |
1.10E-04 |
-7.1 |
fit |
lpdA |
1.07E-03 |
7.60E-04 |
1.17E-04 |
7.75E-05 |
4.60E-03 |
-1.41 |
fit |
rffT |
5.81E-06 |
3.65E-05 |
4.66E-06 |
2.86E-05 |
9.40E-04 |
6.28 |
fit |
ndh |
5.03E-05 |
1.46E-04 |
1.94E-05 |
3.29E-05 |
2.50E-03 |
2.9 |
fit |
cheR |
1.29E-04 |
2.68E-05 |
2.07E-04 |
1.75E-05 |
1.30E-03 |
-4.82 |
fit |
sodA |
3.80E-04 |
9.74E-04 |
1.06E-04 |
6.26E-05 |
7.00E-05 |
2.57 |
fit |
sodB |
7.80E-04 |
1.91E-03 |
2.45E-04 |
4.11E-04 |
3.30E-03 |
2.44 |
fit |
cpdB |
1.92E-05 |
7.56E-05 |
1.24E-05 |
1.40E-05 |
9.50E-04 |
3.94 |
fit |
guaA |
8.25E-04 |
4.31E-04 |
5.43E-05 |
1.34E204 |
1.60E203 |
-1.91 |
unfit |
yiaJ |
3.47E-05 |
6.15E-04 |
1.74E-05 |
1.64E204 |
4.10E204 |
17.74 |
fit |
dsdX |
1.05E-05 |
3.88E-05 |
5.23E-06 |
2.44E205 |
1.70E203 |
3.7 |
fit |
oppD |
2.32E-05 |
8.02E-05 |
1.81E-05 |
1.66E205 |
3.50E203 |
3.46 |
fit |
glnL |
2.41E-04 |
3.99E-05 |
4.81E-05 |
2.81E205 |
3.60E204 |
-6.04 |
fit |
oppA |
2.54E-03 |
5.06E-03 |
1.72E-04 |
5.68E204 |
1.40E204 |
2 |
fit |
oppB |
1.06E-04 |
3.57E-04 |
3.06E-05 |
6.22E205 |
3.60E204 |
3.35 |
fit |
proV |
2.50E-05 |
5.30E-05 |
7.34E-06 |
9.57E206 |
3.60E203 |
2.12 |
fit |
rbsC |
4.20E-05 |
1.12E-04 |
1.47E-05 |
2.70E205 |
3.90E203 |
2.67 |
fit |
hdeB |
1.09E-03 |
5.51E-06 |
1.80E-04 |
3.47E206 |
2.00E205 |
-198.5 |
fit |
yefM |
4.63E-04 |
8.12E-04 |
5.02E-05 |
6.07E205 |
1.10E204 |
1.75 |
fit |
The compare result means that whether the result of our software fit to the result of gene expression profile. After statistic, in these 30 genes, there are 21 genes whose result are same to gNAP’s simulation, 70% of the total.
Global Gene Expression Profiling in Escherichia coliK12 THE EFFECTS OF LEUCINE-RESPONSIVE REGULATORY PROTEIN
In this literature, researchers measure the gene expression profiles in Escherichia coli k12 with the effects of leucine-responsive regulatory protein(Lrp). And Lrp is one of the genes in our genetic regulatory network(GRN). By importing the Lrp’s promoter and gene sequence, we used our software simulating the enhancement of Lrp’s expression and compared the result with the gene expression profile in that literature. There are 22 genes in that profile which are also in our GRN. Here is the list and Genes differentially expressed between lrp+ and lrp- (control vs. experimental) E. coli strains with a p value less than 0.001:
Gene name |
Control |
Experimental |
Control |
Experimental |
p value |
PPDE(<p) |
Fold |
Compare result |
|
mean |
mean |
S.D. |
S.D. |
|
|
|
|
uvrA |
0.00128 |
0.00104 |
1.50E-05 |
3.37E-05 |
1.70E-05 |
0.99386 |
-1.23 |
unfit |
gdhA |
9.16E-05 |
2.73E-04 |
1.52E-05 |
2.16E-05 |
2.18E-05 |
0.99329 |
2.98 |
unfit |
oppB* |
7.51E-05 |
0.00114 |
2.12E-05 |
3.79E-04 |
2.48E-05 |
0.99298 |
15.12 |
fit |
artP |
6.73E-05 |
4.23E-04 |
1.24E-05 |
1.16E-04 |
3.60E-05 |
0.992 |
6.28 |
fit |
oppC* |
2.01E-04 |
0.00108 |
2.34E-05 |
3.61E-04 |
5.44E-05 |
0.99074 |
5.38 |
fit |
gltD* |
5.28E-04 |
2.74E-05 |
1.28E-04 |
1.42E-05 |
5.87E-05 |
0.99049 |
-19.27 |
fit |
oppA* |
0.00162 |
0.0316 |
7.63E-04 |
0.0103 |
8.45E-05 |
0.9892 |
19.44 |
fit |
malE* |
3.56E-04 |
2.01E-04 |
2.32E-05 |
2.17E-05 |
1.16E-04 |
0.98793 |
-1.78 |
fit |
oppD* |
8.97E-05 |
6.55E-04 |
2.76E-05 |
2.05E-04 |
1.16E-04 |
0.98793 |
7.3 |
fit |
galP |
3.75E-04 |
2.11E-04 |
2.25E-05 |
2.40E-05 |
1.31E-04 |
0.9874 |
-1.78 |
fit |
lysU* |
1.81E-04 |
0.00124 |
7.48E-05 |
2.78E-04 |
1.44E-04 |
0.98697 |
6.87 |
fit |
hybA |
3.53E-04 |
2.47E-04 |
2.11E-05 |
1.50E-05 |
1.49E-04 |
0.98682 |
-1.43 |
unfit |
hybC |
3.54E-04 |
2.34E-04 |
2.20E-05 |
1.81E-05 |
1.61E-04 |
0.98646 |
-1.51 |
unfit |
ilvG_1* |
4.21E-04 |
9.15E-04 |
7.55E-05 |
6.85E-05 |
2.54E-04 |
0.98411 |
2.17 |
fit |
phoP |
8.29E-05 |
2.10E-04 |
1.20E-05 |
4.42E-05 |
3.16E-04 |
0.98285 |
2.54 |
fit |
emrA |
3.58E-04 |
2.78E-04 |
2.43E-05 |
4.57E-06 |
3.95E-04 |
0.98147 |
-1.29 |
unfit |
glpA |
1.28E-04 |
8.01E-05 |
8.54E-06 |
9.26E-06 |
4.71E-04 |
0.98029 |
-1.59 |
fit |
manA |
8.71E-05 |
2.40E-04 |
2.16E-05 |
4.08E-05 |
4.80E-04 |
0.98016 |
2.75 |
fit |
amn |
4.31E-04 |
6.51E-04 |
4.47E-05 |
4.72E-05 |
6.07E-04 |
0.97848 |
1.51 |
unfit |
speB |
1.21E-04 |
3.56E-05 |
2.09E-05 |
1.08E-05 |
7.73E-04 |
0.97659 |
-3.4 |
fit |
hdeA |
2.40E-04 |
8.29E-04 |
8.46E-05 |
9.90E-05 |
8.12E-04 |
0.97619 |
3.45 |
fit |
lrp* |
2.96E-04 |
1.11E-04 |
6.21E-05 |
2.22E-05 |
8.27E-04 |
0.97604 |
-2.67 |
unfit |
The compare result means that whether the result of our software fit to the result of gene expression profile. After statistic, in these 22 genes, there are 15 genes whose result are same to gNAP’s simulation, 68.2% of the total.
Global Gene Expression Profiling in Escherichia coli K12 THE EFFECTS OF OXYGEN AVAILABILITY AND FNR
In this literature, researchers measure the gene expression profiles in Escherichia coli k12 with the effects of oxygen availability and FNR. And FNR is one of the genes in our genetic regulatory network(GRN). We do not consider the effect of oxygen, but instead, we control the oxygen in the same way and consider the effect of FNR+ and FNR-. By importing the FNR’s promoter and gene sequence, we used our software simulating the enhancement of FNR’s expression and compared the result with the gene expression profile in that literature. There are 38 genes in that profile which are also in our GRN. Here is the list and Genes differentially expressed between FNR+ and FNR- E. coli strains:
Gene |
p value |
PPDE(<p) |
Fold |
Compare result |
trpB |
4.94E-04 |
0.99872 |
9.24 |
fit |
cyoA |
6.96E-07 |
0.99999 |
13.05 |
fit |
gpmA |
1.73E-04 |
0.99939 |
10.41 |
fit |
crr |
6.26E-05 |
0.9997 |
3.47 |
unfit |
nuoE |
1.17E-04 |
0.99953 |
4.49 |
fit |
rplM |
5.72E-06 |
0.99994 |
14.32 |
fit |
gatY |
1.92E-04 |
0.99934 |
8 |
unfit |
trmD |
1.64E-04 |
0.99941 |
2.5 |
fit |
ndh |
8.73E-06 |
0.99992 |
5.06 |
fit |
manY |
2.49E-04 |
0.99921 |
8.35 |
unfit |
manZ |
1.07E-04 |
0.99956 |
2.53 |
unfit |
ompA |
6.57E-06 |
0.99994 |
3.41 |
unfit |
rplT |
3.68E-05 |
0.99979 |
8.41 |
fit |
rpsJ |
6.23E-04 |
0.99849 |
4.27 |
unfit |
cydA |
3.15E-04 |
0.99906 |
4.73 |
unfit |
rplS |
2.70E-07 |
0.99999 |
6.24 |
fit |
ptsG |
3.41E-04 |
0.99901 |
3.17 |
fit |
oppA |
9.06E-14 |
1 |
4.53 |
fit |
talA |
7.62E-05 |
0.99965 |
2.76 |
unfit |
fdhF |
1.84E-04 |
0.99936 |
-2.28 |
fit |
caiT |
2.28E-07 |
0.99999 |
-6.62 |
fit |
pyrD |
6.25E-06 |
0.99994 |
-13.74 |
unfit |
recC |
6.38E-05 |
0.99969 |
-2.29 |
fit |
tdh |
1.06E-05 |
0.99991 |
-3.01 |
fit |
araB |
1.21E-04 |
0.99951 |
-3.59 |
fit |
nanT |
1.13E-05 |
0.99991 |
-3.04 |
fit |
acrF |
1.53E-06 |
0.99998 |
-6.83 |
fit |
pstS |
4.63E-05 |
0.99975 |
-4.35 |
fit |
metL |
3.16E-06 |
0.99996 |
-5.65 |
fit |
mhpF |
2.77E-05 |
0.99983 |
-5.92 |
fit |
glgA |
3.51E-04 |
0.99899 |
-2.33 |
fit |
glnD |
1.09E-05 |
0.99991 |
-6.32 |
unfit |
uraA |
2.11E-04 |
0.99929 |
-2.48 |
fit |
speC |
2.49E-06 |
0.99997 |
-3.54 |
unfit |
fliP |
6.45E-04 |
0.99846 |
-3.58 |
fit |
dinG |
4.66E-05 |
0.99975 |
-3.14 |
unfit |
proW |
3.73E-06 |
0.99996 |
-4.97 |
unfit |
sbcC |
5.66E-04 |
0.99859 |
-3.06 |
unfit |
The compare result means that whether the result of our software fit to the result of gene expression profile. After statistic, in these 38 genes, there are 25 genes whose result are same to gNAP’s simulation, 65.8% of the total.
Global Gene Expression Profiling in Escherichia coli K12 EFFECTS OF OXYGEN AVAILABILITY AND ArcA
In this literature, researchers measure the gene expression profiles in Escherichia coli k12 with the effects of oxygen availability and arcA. And arcA is one of the genes in our genetic regulatory network(GRN). We do not consider the effect of oxygen, but instead, we control the oxygen in the same way and consider the effect of arcA+ and arcA-. By importing the arcA’s promoter and gene sequence, we used our software simulating the enhancement of arcA’s expression and compared the result with the gene expression profile in that literature. There are 43 genes in that profile which are also in our arcA. Here is the list and Genes differentially expressed between arcA+ and arcA- E. coli strains:
Gene name(NIH) and b no. |
p value |
PPDE(<p) |
-Fold |
Compare result |
talA(b2464) |
2.21E-04 |
0.99933 |
3.46 |
unfit |
crr(b2417) |
2.14E-09 |
1 |
3.63 |
fit |
oppA(b1243) |
8.78E-05 |
0.99966 |
3.79 |
fit |
rpsJ(b3321) |
6.28E-06 |
0.99995 |
3.8 |
fit |
ompA(b0957) |
1.48E-06 |
0.99998 |
4.02 |
unfit |
rbsD(b3748) |
3.85E-08 |
1 |
4.83 |
unfit |
rplS(b2606) |
3.02E-05 |
0.99984 |
5.81 |
fit |
nuoE(b2285) |
2.34E-09 |
1 |
8.83 |
unfit |
rplT(b1716) |
4.41E-06 |
0.99996 |
9.01 |
fit |
gatY(b2096) |
3.49E-07 |
0.99999 |
10.72 |
fit |
sdhA(b0723) |
2.06E-07 |
1 |
14.54 |
unfit |
gpmA(b0755) |
1.27E-09 |
1 |
16.95 |
fit |
rplM(b3231) |
3.40E-07 |
0.99999 |
17.05 |
fit |
mdh(b3236) |
4.00E-04 |
0.99896 |
17.95 |
unfit |
nuoB(b2287) |
1.32E-04 |
0.99954 |
19.34 |
unfit |
trpB(b1261) |
3.12E-10 |
1 |
19.97 |
fit |
cyoA(b0432) |
9.70E-10 |
1 |
23.3 |
unfit |
sdhB(b0724) |
1.25E-05 |
0.99992 |
27.87 |
unfit |
sucD(b0729) |
2.42E-05 |
0.99987 |
86.14 |
unfit |
gltA(b0720) |
3.09E-05 |
0.99984 |
107.01 |
fit |
pyrD(b0945) |
5.36E-06 |
0.99996 |
-18.91 |
unfit |
dinG(b0799) |
3.20E-04 |
0.99912 |
-11.79 |
unfit |
gadB(b1493) |
1.87E-08 |
1 |
-11.23 |
fit |
gadA(b3517) |
5.14E-07 |
0.99999 |
-9.44 |
fit |
glnD(b0167) |
8.77E-05 |
0.99966 |
-8.58 |
unfit |
aroM(b0390) |
1.81E-04 |
0.99942 |
-7.13 |
unfit |
pnuC(b0751) |
1.71E-05 |
0.9999 |
-6.22 |
fit |
gadX(b3516) |
2.32E-06 |
0.99998 |
-6.11 |
fit |
sbcC(b0397) |
3.89E-04 |
0.99898 |
-5.59 |
unfit |
xylR(b3569) |
3.55E-04 |
0.99905 |
-5.11 |
fit |
gadW(b3515) |
2.41E-05 |
0.99987 |
-4.63 |
fit |
recC(b2822) |
2.98E-05 |
0.99985 |
-4.62 |
fit |
appC(b0978) |
4.83E-09 |
1 |
-4.01 |
fit |
speC(b2965) |
2.86E-04 |
0.99919 |
-2.97 |
unfit |
glgA(b3429) |
1.74E-04 |
0.99944 |
-2.9 |
fit |
nanT(b3224) |
7.22E-05 |
0.99971 |
-2.46 |
fit |
appB(b0979) |
3.31E-09 |
1 |
-2.43 |
fit |
rhaA(b3903) |
1.48E-04 |
0.9995 |
-2.41 |
fit |
hycD(b2722) |
1.50E-05 |
0.99991 |
-2.21 |
fit |
hdeA(b3510) |
4.82E-09 |
1 |
-2.83 |
fit |
hyaB(b0973) |
7.30E-08 |
1 |
-2.83 |
fit |
uraA(b2497) |
7.91E-05 |
0.99968 |
-2.6 |
fit |
glgC(b3430) |
4.69E-04 |
0.99883 |
-2.15 |
fit |
The compare result means that whether the result of our software fit to the result of gene expression profile. After statistic, in these 38 genes, there are 25 genes whose result are same to gNAP’s simulation, 62.8% of the total.
Consistency
The consistency of the program has also been tested. We inserted a gene as same as a gene in the network and compared the regulations predicted by the program with the original regulations. Without filtering the random similarities, the actual regulations were submerged in the network noise.
Figure 1. The green line represents regulating values.
The blue line
represents regulated values.
Figure 2.Predicted regulation without filtered.
The actual regulations are submerged by the
noise.
With random similarities filtered, all original regulations were picked out. The result shows that the program is consistent with the original network.
Figure 3.The SNR is better.
The actual regulations are
picked out.
Summary
In first two literatures, without the limit of oxygen, the average fitness is up to 69.1%. And in the other two literatures, the average fitness is 64.3%. We thought that it may be the oxygen’s limit which affect the expression of each gene. Gene regulatory network analysis has its weakness about environment’s change. All in all, the total average of fitness is still up to 66.7%. Therefore, we may draw the following conclusion that our software could simulate the impact of new gene to some extent.
Reference
Arfin S M, Long A D, Ito E T, et al. Global Gene Expression Profiling in Escherichia coliK12 THE EFFECTS OF INTEGRATION HOST FACTOR[J]. Journal of Biological Chemistry, 2000, 275(38): 29672-29684. Hung S, Baldi P, Hatfield G W. Global Gene Expression Profiling in Escherichia coliK12 THE EFFECTS OF LEUCINE-RESPONSIVE REGULATORY PROTEIN[J]. Journal of Biological Chemistry, 2002, 277(43): 40309-40323. Salmon K, Hung S, Mekjian K, et al. Global Gene Expression Profiling in Escherichia coli K12 THE EFFECTS OF OXYGEN AVAILABILITY AND FNR[J]. Journal of Biological Chemistry, 2003, 278(32): 29837-29855. Salmon K A, Hung S, Steffen N R, et al. Global Gene Expression Profiling in Escherichia coli K12 EFFECTS OF OXYGEN AVAILABILITY AND ArcA[J]. Journal of Biological Chemistry, 2005, 280(15): 15084-15096.
