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1、Gene expression data displaying up-regulation and down-regulation of amino acid nutritional metabolic modules Jing Li Key Laboratory of Food Nutrition and Safety, Ministry of Education, Tianjin University of Science & Technology, Tianjin, 300457, China AbstractRaw gene expression data and amino aci
2、d metabolic pathway of Saccharomyces cerevisiae were excavated by SMD (Stanford Microarray Database) and KEGG (Kyoto Encyclopedia of Genes and Genomes), respectively. The methionine and cysteine nutritional metabolic modules were selected and analyzed, expecting to establish the relationship between
3、 the modules, and find out the important genes, which made predominant contribution for the up-regulation and down-regulation of modules, to identify the differences and synergies in expression levels. The results show that four common genes exist between these two modules, comprising YAL012W (4.4.1
4、.1), YFR055W (4.4.1.8), YJR130C (2.5.1.48) and YLR303W (2.5.1.49). For methionine modules, the five important genes were YAL012W (4.4.1.1), YDR502C (2.5.1.6), YER043C (3.3.1.1), YGR155W (4.2.1.22) and YLR303W (2.5.1.49), playing a decisive role in the gross of gene expression, while for cysteine mod
5、ules, those are YAL012W (4.4.1.1), YLR303W (2.5.1.49), YNL247W (6.1.1.16) and YCL064C (4.3.1.17). Maybe the cooperative up-regulation relations exist between these two modules, while because of different gene numbers in modules, the synergies between gene expression gross values were not distinct. B
6、ut certain crucial metabolite can be accumulated by controlling the important genes in the metabolic process. Keywords-gene expression; metabolic modules; important genes; up-regulation; down-regulation I. INTRODUCTION DNA microarray is one of the widest technologies in nucleic acid diagnosis in rec
7、ent years. It can provide lots of raw data for multi-gene relations, simultaneously monitor the transcription level of all genes in cells, display a genome-wide portrait of the transcriptome of an organism and disclose the transcriptional level changes of all genes for genomics. Most genes and their
8、 products interact in complex cellular networks 1. Constructing gene network for organisms is a systematic, quantitative method which helps us examine the expression and interaction relationship of all genes, rather than a few of genes, guide directional gene regulation for bioorganisms. By gene reg
9、ulation, the synthesis of certain components (such as nucleic acid, amino acid) or enzymatic reaction (transcription factors, polymerase) can be suspended as desired, while organisms need these, the proceed can resume. Therefore, the survival of organisms can adapt to a variety of environmental cond
10、itions 2. Amino acids, as the precursor substances of protein synthesis, not only affect the protein metabolism, but also participate in steady-state balance in vivo. Therefore, the investigation of amino acid metabolism by gene network is of great importance 3. However, achieving a deeper understan
11、ding of metabolic mechanisms may require global strategies aimed at modeling the functional interrelationships between genes and/or proteins (genes/proteins) as complex interdependent networks 4. Now the investigation of amino acid metabolism is focused on two aspects: a certain amino acid metabolis
12、m and the metabolism among the nutritional products. While taking metabolic modules as units, construct the metabolic pathway interrelations at gene expression level has not reported yet. Saccharomyces cerevisiae as a model organism is favorable in the fundamental investigation for metabolic enginee
13、ring 2. Here we analyze the global expression profile and metabolic pathway of two modules, methionine and cysteine nutritional metabolic modules for Saccharomyces cerevisiae by public database such as SMD (Stanford Microarray Database) and KEGG (Kyoto Encyclopedia of Genes and Genomes), expecting t
14、o establish the relationship between the modules by gene expression data, find out the important genes for the up-regulation and down-regulation of modules, identify the gene expression differences and synergies, in combination with functional and biochemical metabolic pathway analysis. This work pr
15、ovides a detailed laboratory data analysis to guide further biological experiments, potentially controlling industrial microorganisms metabolism, developing nutritional food and preventing diseases. II. METHODS A. SMD displaying gene expression data 592 chip data for Saccharomyces cerevisiae were el
16、igible to collect from SMD (http:/genome-www5.stanford.edu/). Ch1, Ch2 and R/G were extracted and analyzed for each chip. Ch1, Ch2 values suggest the mRNA transcriptional value before and after gene expression, while R/G (normalized mean), that is, Cy5/Cy3, represents the changes before and after ge
17、ne 978-1-4244-4713-8/10/$25.00 2010 IEEEexpression. If the value of R/G is more than 2.0, indicating the up-regulation of gene expression, while less than 0.5, means down-regulation, and between 0.5 and 2.0, the gene expression is supposed to be constant 5,6。 B. KEGG displaying metabolism pathway By
18、 KEGG database (http:/ a total of 205 genes were organized from 16 amino acid metabolism pathways, GENE NAME and GENE ID as well as enzyme name was extracted, trying to construct the connection with SMD database. III. RESULTS AND DISCUSSION A. The relationship of the whole modules expression gross w
19、ith the experimental conditions There are 14 genes in the methionine and 7 genes in the cysteine metabolic modules from KEGG database (Table 1). The Ch1 and Ch2 values for all genes in each module were added, and the gene expression gross value named as SUM(Ch1) and SUM(Ch2), were plotted versus 592
20、 experimental conditions in Figure 1, respectively. It indicated that almost gene expression gross values significantly increased under the experimental conditions of 73-113 and 500. Larger values can be found in modules. For methionine metabolic modules, five larger values of SUM(Ch2) were 602080,
21、563808, 447583, 395675, 317848, respectively. While for cysteine modules, 413756, 238116, 263891, 230359 and 205899 were five larger values, respectively. B. The important genes in two modules Important genes play a predominant role in total expression value and were list as Table 2-3 under the corr
22、esponding experimental conditions of 78, 111,110, 462 and 457. It can be found that for methionine metabolic modules, the important genes mainly concentrated on YAL012W (10), YER043C(1601), YDR502C(1425), YGR155W(2289) and YLR303W(4039) , while the other four genes mainly including as YAL012W(10), Y
23、CL064C(584), YLR303W(4039)and YNL247W (4937) for cysteine modules. 0100200300400500600447583(110)317848(457)395675(462)602080(111)563808(78)SUMGrowth Condition Ch1 Ch2methionine metabolism 0100200300400500600238116(111)205899(480)230359(462)263891(102)413756(78)SUMGrowth Condition Ch1 Ch2cyteinie me
24、tabolism Figure 1 Plots of SUM(Ch1) and SUM(Ch2) versus experimental conditions. C. The relationships between modules at gene expression level From the KEGG database, the two nutritional metabolic modules pathway were acquired. The genes involved in metabolism for Saccharomyces cerevisiae were retai
25、ned, while the genes for other bioorganisms removed, the simplified pathways were displayed in Figure 2-3，the important genes were also marked as bold type. The result show that the common genes of YAL012W (4.4.1.1), YLR303W (2.5.1.49), YFR055W (4.4.1.8) and YJR130C (2.5.1.48) exist between the two
26、modules. Especially, YAL012W (4.4.1.1) and YLR303W (2.5.1.49)were predominated in gene expression gross changes of modules (Figure 4). Figure 2 The methionine metabolism of Saccharomyces cerevisiae. Figure 3 The cysteine metabolism of Saccharomyces cerevisiae. From Figure 2, it can also be concluded
27、 that cystathionine gamma-lyase, as the only connecting way of cysteine metabolism and methionine metabolism, is the important enzyme in establishing the direct relationship between the modules. L-Homocysteine as the mediate product, plays a decisive role in producing methionine. O-acetylhomoserine-
28、lyase is the important enzyme participated in the syntheses of L-Homocysteine, through which the relationship between methionine module and glycine, serine and threonine metabolism module can be constructed. Figure 4 The chemical reaction of participated important genes in methionine metabolism. By
29、comparison of Figure 2 and 3, we can also find that certain crucial metabolite can be accumulated by controlling the important genes in the metabolic process, such as S-adenosyl-L-methionineamine (SAM). It can be catalyzed by S-adenosylmethionine synthetase (2.5.1.6), if inhibited enzyme activity, m
30、ethionine can be accumulated. From Figure 5, we can also find the importance of the cystathionine beta-synthase(4.2.1.22) and cystathionine gamma-lyase (4.4.1.1) in methionine metabolism and cysteine metabolism, maybe indicating synergies between modules. Figure 5 Serine metabolism connected with cy
31、teinie metabolic pathway. D. Each gene expression vatio analysis in modules In the process of selecting the larger values for methionine and cysteine modules, there have been two sets of identical conditions, numbered as 78 and 462, respectively. To further find out the relationship between the modu
32、les, the gene expression ratio, expressed as single gene expression value named as Ch2-Ch1 divided by gross changes named as SUM(Ch2)-SUM(Ch1), was determined at the same conditions of 78 and 462. The results show that for condition (78), GENE ID of 10 and 1425 plays a critical role in expression gr
33、oss values for methionie metabolic modules. The former is also important in cysteine metabolic modules, as displayed in Figure 6. Under conditions of 462, GENE ID named as 4039,1893 and 3296 have the same function in two modules changes, in which the genes numbered as 4039 is up-regulated, while 189
34、3 和 3296 is down-regulated. These three genes are common genes in the modules. E. The up-regulation and down-regulation analysis for modules In the part, we first elect three experiments with the distinct up-regulation and down-regulation expression value for each module. The gene expression ratios
35、for each gene were analyzed in Table 4-5. Then the ten conditions with both largest gene expression gross in two modules were examined in Figure 7-8. The result shows that the determinative gene is different for gross gene expression value, but mainly concentrated on the important genes. Figure 6 Ge
36、ne expression ratios in methionine and cysteine metabolic modules. Figure 7 Plots of gene expression ratios versus genes in methionine metabolism modules. Figure 8 Plots of gene expression ratios versus genes in cysteine metabolism modules. ACKNOWLEDGMENT We are grateful of fund support (20060418) o
37、f Tianjin University of Science and Technology. REFERENCES 1 M. A. Pujana., J. D. J. Han, L. M. Starita., K. N . Stevens, M.Tewari, J. S. Ahn, et al. Network modeling links breast cancer susceptibility and centrosome dysfunction, Nature Genetics, 39(11): 1338-1449. 2 Q. Liu, L. Yu. Yeast: a model bi
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