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Research Article Open Access
Wan et al., J Proteomics Bioinform 2013, S6 DOI: 10.4172/jpb.S6-007
Research Article Open Access
Microarray ProteomicsJ Proteomics Bioinform ISSN:0974-276X JPB, an open access journal
Mechanisms of Radiation Resistance in Deinococcus radiodurans R1 Revealed by the Reconstruction of Gene Regulatory Network Using Bayesian Network ApproachPing Wan1#*, Zongliang Yue1#, Zhan Xie1#, Qiang Gao1, Mengyao Yu1, Zhiwei Yang1 and Jinsong Huang2*1College of Life Science, Capital Normal University, Beijing, 100048, China2Beijing Computing Center, Beijing, 100094, China#Contributed equally
*Corresponding authors: Ping Wan, College of Life Science, Capital Normal, University, Beijing, 100048, China, E-mail: [email protected]
Received May 22, 2013; Accepted June 24, 2013; Published June 27, 2013
Citation: Wan P, Yue Z, Xie Z, Gao Q, Yu M, et al. (2013) Mechanisms of Radiation Resistance in Deinococcus radiodurans R1 Revealed by the Reconstruction of Gene Regulatory Network Using Bayesian Network Approach. J Proteomics Bioinform S6: 007. doi:10.4172/jpb.S6-007
IntroductionThe Gram-positive bacterium Deinococcus radiodurans R1 is the
most radiation-resistant organism described to date [1]. The radiation resistance of D. radiodurans R1 makes it an ideal candidate of many applications in fields ranging from environmental biotechnology to health care.
Although D. radiodurans R1 was discovered in 1956 [2], little is known about the mechanisms of radiation resistance in the bacterium till now. To uncover the mechanisms of the radiation resistance in D. radiodurans R1, White et al. [3] sequenced the whole genome of D. radiodurans R1 in 1999. The genome is composed of two chromosomes (2.65 and 0.412 Mb), a megaplasmid (0.177 Mb), and a small plasmid (0.046 Mb). It was expected that the complete genome sequence would shed light on the extraordinary DNA repair capabilities of D. radiodurans R1. However, analysis of the genome sequence did not provide insight into the genetic basis of the DNA repair capabilities [3,4]. In 2007, Griffiths and Gupta [5] identified 399 unique proteins to D. radiodurans R1, but did not illustrate the biological functions of theseproteins. The emergence of DNA microarray technology [6] enablesresearchers to measure all the gene expression levels of an organismsimultaneously. In 2003, Liu et al. [7] described the transcriptionaldynamics in D. radiodurans R1 cultures following exposure to 15 kGyionizing irradiation. The irradiated culture was then transferred tofresh media to recover. During the recovery, the concentration of 2750D. radiodurans R1 transcripts relative to the unirradiated control atnine different time points over a 24 hour period were analyzed. Theresults indicated that 832 genes were induced and 451 genes wererepressed at one or more of the time points during the recovery period.Liu et al. [7] analyzed the DNA microarray results using hierarchicalclustering. The clustering algorithm is useful in discovering genes thathave similar expression patterns over a set of experiments, but difficultto reveal the process of the transcriptional regulation [8]. Due to thelarge number of loci responding during recovery following irradiation,it is difficult to interpret the significance of these findings.
Currently, two mechanisms explain the radiation resistance in D. radiodurans R1 [1,9]. However, DNA repair system in D. radiodurans R1 seems having no difference with other organisms. The radiation-resistant mechanisms in D. radiodurans R1 are far from complete understood. Bayesin network approach [10] is a promising tool for DNA microarray data analysis [11,12] and biological network reconstruction [13-15]. To explore the mechanisms of radiation resistance in D. radiodurans R1, in this study we for the first time reconstructed the D. radiodurans R1 gene regulatory network using Bayesin network approach. Our results revealed more mechanisms involved in radiation-resistant processes in D. radiodurans R1.
Data and MethodsD. radiodurans R1 DNA microarray data
The D. radiodurans R1 DNA microarray data were retrieved fromreference [7]. The data include 2750 genes. Each gene contains gene expression values at nine time points.
Reconstruction of D. radiodurans R1 gene regulatory network using Bayesian network approach
Bayesian network is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). It consists of two components: the first
AbstractThe mechanisms of radiation resistance in the extreme anti-radiation bacterium Deinococcus radiodurans
R1 have fascinated researchers for more than sixty years. In this study, with the DNA microarray data, we first constructed the gene regulatory network in D. radiodurans R1 using Bayesian network approach. The results of our analysis for the gene regulatory network reveal twelve significant mechanisms of radiation resistance in D. radiodurans R1, of which two mechanisms (DNA repair and reactive oxygen species) are consistent with the well-known knowledge; and two mechanisms (metal ion homeostasis and oxygen transport process) support Daly’s manganese-based radiation protection hypothesis. We also demonstrate that different mechanisms act in concert under the radiation stress in D. radiodurans R1.
Journal of Proteomics & BioinformaticsJo
urna
l of P
roteomics & Bioinformatics
ISSN: 0974-276X
Citation: Wan P, Yue Z, Xie Z, Gao Q, Yu M, et al. (2013) Mechanisms of Radiation Resistance in Deinococcus radiodurans R1 Revealed by the Reconstruction of Gene Regulatory Network Using Bayesian Network Approach. J Proteomics Bioinform S6: 007. doi:10.4172/jpb.S6-007
Page 2 of 5
Microarray ProteomicsJ Proteomics Bioinform ISSN:0974-276X JPB, an open access journal
component is a directed acyclic graph; and the second component is a set of parameters that quantify the network [12]. A Bayesian network is defined as:
11
( ,..., ) ( | ( ))n
B n B i ii
P X X P X pa X=
= =∏
Where:
iX denotes each variable in DAG, ( )ipa X denotes all parent nodes of iX .
In this study, we used the R package bnlearn (http://cran.r-project.org/) to learn the Bayesian network structure.
Figure 1: The gene regulatory network in D. Radiodurans R1. The gene regulatory network includes 1938 nodes and 2635 edges. The red nodes represent unique genes in D. Radiodurans R1. The node size is proportion to the degree of the node.
Citation: Wan P, Yue Z, Xie Z, Gao Q, Yu M, et al. (2013) Mechanisms of Radiation Resistance in Deinococcus radiodurans R1 Revealed by the Reconstruction of Gene Regulatory Network Using Bayesian Network Approach. J Proteomics Bioinform S6: 007. doi:10.4172/jpb.S6-007
Page 3 of 5
Microarray ProteomicsJ Proteomics Bioinform ISSN:0974-276X JPB, an open access journal
Bootstrap test for the Bayesian network
Bootstrap test for the Bayesian network was performed according to the method proposed by Friedman et al. [16]. In this study, we performed the bootstrap test for 150 times. Pair nodes with edge bootstrap values equal to or larger than 0.85 will be used to reconstruct the gene regulatory network.
Visualization of the gene regulatory network
Visualization of the gene regulatory network was performed using the software Cytoscape 2.8.3 (http://www.cytoscape.org/) [17].
GO term enrichment analysis
To find the significant biological processes in the gene regulatory network, we first annotated the GO terms for each gene via InterProScan tool [18]. Then, we conducted the GO term enrichment analysis using R package topGO (http://www.bioconductor.org/packages/2.12/bioc/html/topGO.html). The significant level for the enrichment is p-value < 0.05.
GO term annotations for the unknown genes based on Markov blanket
In a Bayesian network, the Markov blanket of node includes its parents, children and the other parents of all of its children. To annotate the function of an unknown gene, we first extracted the Markov blanket of the gene from the gene regulatory network, and then conducted the GO term enrichment analysis for the Markov blanket. Finally, we assigned the enriched GO term(s) to the unknown gene as its function(s).
ResultsGene regulatory network of D. radiodurans R1
We first reconstructed D. radiodurans R1 gene regulatory network using Bayesian network approach. The gene regulatory network includes 1938 nodes and 2635 edges (Figure 1). Each edge between two nodes has a bootstrap value greater than 0.85. The distribution of node degrees showed that only a minority of nodes have high degree of connectivity (Figure 2), and followed the power law (Figure S1). The result suggested that D. radiodurans R1 gene regulatory network is a scale-free network. The scale-free networks are remarkably resistant to accidental failures [19]. Since the hub nodes (i.e. nodes having high degree of connectivity) in a scale-free network dominate the overall connectivity of the network, they are of great importance [20]. Therefore, we next focused our analysis on the hub nodes in D. radiodurans R1 gene regulatory network, and expected to find out the key mechanisms of radiation resistance in D. radiodurans R1.
Hub node sub-network reveals a variety of radiation-resistant mechanisms in D. radiodurans R1
In this study, we defined the nodes with degree equal to or greater than 8 as hub nodes. We collected all of 74 hub nodes and 511 nodes directly connected with the hub nodes (Table S1). Figure 2 is the sub-network which hub nodes involved in. Next, we performed the GO term enrichment analysis for the hub node sub-network, and found that twenty-two biological processes were enriched (Table 1, Figure S2). The enriched biological processes could be classified into eight categories: (1) Arginine metabolic process; (2) GTP metabolic process; (3) metal ion homeostasis; (4) oxygen transport; (5) dicarboxylic acid transport; (6) protein transport; (7) protein oligomerization and (8)
Figure 2: The distribution of node degrees. In the gene regulatory network, only a minority of nodes have high degree of connectivity. On the whole, the distribution of node degrees follows the power law. However, the number of nodes with degree of seven is over-represented.
2 4 6 8 100
100
200
300
400
500
600
700
The distribution of node degrees
Node degree
Freq
uenc
y
Category GO.ID Term p-value
1GO:0006520 cellular amino acid metabolic process 0.034
GO:0006525 arginine metabolic process 0.043
2 GO:0046039 GTP metabolic process 0.036
3
GO:0048878 chemical homeostasis 0.031
GO:0006873 cellular ion homeostasis 0.031
GO:0006875 cellular metal ion homeostasis 0.031
GO:0006879 cellular iron ion homeostasis 0.031
GO:0030003 cellular cation homeostasis 0.031
GO:0050801 ion homeostasis 0.031
GO:0055065 metal ion homeostasis 0.031
GO:0055072 iron ion homeostasis 0.031
GO:0055080 cation homeostasis 0.031
4GO:0015669 gas transport 0.031
GO:0015671 oxygen transport 0.031
5 GO:0006835 dicarboxylic acid transport 0.031
6
GO:0033036 macromolecule localization 0.023
GO:0008104 protein localization 0.023
GO:0045184 establishment of protein localization 0.016
GO:0015031 protein transport 0.016
7 GO:0051259 protein oligomerization 0.031
8GO:0055082 cellular chemical homeostasis 0.031
GO:0071555 cell wall organization 0.031
Table 1: Significant biological processes in the hub node sub-network.
Citation: Wan P, Yue Z, Xie Z, Gao Q, Yu M, et al. (2013) Mechanisms of Radiation Resistance in Deinococcus radiodurans R1 Revealed by the Reconstruction of Gene Regulatory Network Using Bayesian Network Approach. J Proteomics Bioinform S6: 007. doi:10.4172/jpb.S6-007
Page 4 of 5
Microarray ProteomicsJ Proteomics Bioinform ISSN:0974-276X JPB, an open access journal
Figure 3: The sub-network of hub node in D. Radiodurans R1. The sub-network includes 74 hub nodes with degree of 8~10 and 563 nodes directly connected with the hub nodes. The node sized is proportion to the degree of the node. The sub-network reveals eight mechanisms of radiation-resistance in D. radiodurans R1 (shown in different colors).
Dicarboxylic acid transport
Protein transport
DR2043
DR1333
DR1844
DRA0065
DR0015
DR1578
DR0070 DR2213
DR1616 DR2116DRB0034DR1827DR0131
DR1395 DR1460
DR1258DR2311
DRA0323
DR2591
DRC0026
DRB0049
DR1795
DR0924
DR2490
DR0873
DR2334 DRA0093 DR0903
DR1470 DR1963
DR2308DR0956
DR0651 DR1630 DR1173 DRA0267 DR0125 DR1086
DR2305
DR0824
DR1842
DR1941 DR2292
DR0649
DR2242DR1725
DRB0140DR2623
DR1910
DR0988
DR0785
DRB0110
DR0656
DR0776DRA0265
DRA0103DR2633
DR0927
DR0678
DR1340
DR0383
DRA0020
DR2012
DRA0031
DR1937
DR1322
DR0578
DR1222
DR1079
DR0802
DR0428
DRB0104
DR1291
DR0286
DR1237
DR2240
DR1253DR2201
DR2281
DRA0230
DR2450
DR2262
DR0848
DR1263
DR2634
DRB0142DR1505
DR0040
DR2024
DR0559
DR0446DR0042
DR0783
DR1730
DR0434
DR0349DR2399
DR0169DR1006
DR0399
DR0358DR0665
DR1315
DR0513DR2500
DRA0328
DR2321
DR1712
DRA0184
DR0600
DRA0307
DR0935
DR0930
DR1863
DR1874
DR0067DRA0113
DR0059
DR1018
DR0864
DR2528
DR0194
DR1602
DR1683
DR0643
DR2356
DR0154DRA011
DR0176
DR0945
DR1449
DR1737DR1433
DR2246
DR0437DR1217
DR0980
DR0398
DRA0290
DRB0111
DR1199DR1035
DRA0203
DR2120
DR2229DRA0168
DR2268
DR0374
DR2587DR0470
DR1330
DR2550
DRA0035
DR1654
DR2536
DR2525
DRA0317
DR1814
DR0994
DR2530
DR0780
DR2263DR1792
DR0031
DR2447
DRC0024 DR0461DR1872
DRB0068
DR0570
DR0584
DR2016
DR0926
DR2398
DR1100
DR0589DR1901
DR1228
DR1713
DR1159
DR0654
DR0658
DR1989
DRB0144
DRA0211
DRA0204
DR1920
DR1700
DR1765
DR0252
DR1329
DR2110
DR0822
DR2054
DR2122
DR0405
DR1745
DRB0026
DR1823
DR1030
DR1125
DR1454 DR0778
DR1679DR2138
DR0569
DR1227
DRB0094
DRA0045
DR2020
DR1916DR2637
DR1047
DR2366
DR1904
DR1313
DRA0180
DR0017
DR0640
DR1281
DR2547
DR1982
DR1350
DR0292
DR1451DR1681
DR0105
DR0900
DR1055
DR0836
DR1060
DR0306
DR0231
DR1245
DR1143
DR1588
DR1124
DRB0124
DR2508
DRA0090
DRA0174
DR1002
DRA0262DR0052
DR0203DRA0251
DR0567
DR2405
DR1167
DRB0092
DR2208
DR0885
DRA0234
DR1900
DR0771
DR1985
DR0109
DR2085
DR0249
DR2283
DRA0194
DR1243DR0135
DRB0067
DR0157
DRA0001DRB0074DR2396DR1090
DRA0163
DR1743
DRA0330
DR0681
DR1024
DRA0243
DR0539
DR0635
DR1201
DR2214
DR1328
DR0469
DR0181
DR2325
DR0242
DR1574
DRC0021DR1033DRA0369
DR1226
DR1768
DR1276
DR0316
DR1650
DR2555
DR2499DR0954
DRC0028DRA0139
DR0719
DR1106
DR0742DR2137
DR2232DR2258
DR0177
DR0992
DR2083
DR2378
DR2541
DR0106DR1493
DR2199
DR2277
DR2197
DR1846
DR1053DR0875
DR1130
DR2196
DR1105
DR0133
DR0775
DR1750
DR2123
DRA0359
DR0858DR1183
DR0733
DR1150
DR1287DR0239
DRB0122DR0721 DR0061
DR2601
DR2047
DRC0022DR0474
DR0322
DR1715
DR2017DR1721
DR0353
DR2223
DR0767DR0012
DR2583
DR1239
DRA0105
DR2025
DR1585
DR1059
DR0325DR0949
DR2060
DR2241
DR0575
DR0403
DR2118
DR1810
DR0837
DRA0061
DR2549
DR1057
DRA0008
DRB0138
DRA0337
DR1257
DR1319DRB0095
DR0113
DR2558
DR1318
DR2162
DR1957
DR1617
DR1009
DR1459
DR0047
DRA0181
DR1735
DR2234
DRB0037
DRB0060
DR1386
DRA0033
DR0546
DR0940DR2059
DR2100
DR0429
DR1349
DR1876
DR0847
DR2314
DR0795
DR0069DR1860
DRA0145
DR1134
DR0989
DR0153
DR1185
DR0452
DR1865
DR2265
DR0655
DR1940
DR2442
DRB0069
DR2350
DR1267
DR0535
DRA0294
DRA0261
DR0946
DR0299DR0167
DR1776
DR1674
DRC0013
DRA0153
DR0846
DR1955
DR0037
DR1899DRB0002
DR2608
DR1482
DRC0010
DR0053 DR0253DR1548
DR0224DR1608
DR2336DR0629 DR0503
DR1591
DRA0030
DRA0201
DR0934
DRA0118
DR2069
DR2203
DR0260
DR1968DR2603
DR1668
DR1923
DRA0049
DR1371
DR0430
DR0079
DR0977
DR1338
DR1074DR1235
DR1873
DR1462
DR1425
DR2329
DR1072
DRB0118
DR2014DRA0167
DR1557
DR0588
DR1590
DR0192
DR0150
DR0737
DRA0097DR2621
DR1621
DR2438
DR1526
DR0591
DR1279
DR2112DR1450
DR0566
DR0604
DR0610
DR1580
DR2111
DR2565
DR0241
DR0637
DR2278
DR0686
DRB0054
DR0723
DR1547
DR1565
DR0350
DR2574
DR1360
DR1657
DR1642
DR0856
DR2146
DR2364
DR0736
DRA0155
DR2577DR1264
DRA0110
DR2534
DR0805
DRB0106
DR2250DR1993
DRA0057
DR2576
DR1417 DR2461
DRA0235
DRA0053
DR1988
DR0041
DR1832
DR1742DR1004
DR1766
DRB0029
DR1747
DR1104
DR0439
DR0127
DR1242
DR2337
DR0636DR1310
DRA0128
DR0118
DRA0237
DR0892
DRB0011
DR2384DR2236
DR1069
DR0327
DR0048
DR0884
DR1677
DR0018
DR0049
DR1362DR0019
DRA0080 DRA0363
DR0459
DR1801DR1919
DR1511
DR1950
DR1509
DR2563
DR1649
DR1479
DR1013
DRB0063
DR2055
DR0794
DR1348DRA0312
DR0759
DR0606
DRA0283
DR1809
DR0611
DR1101
DRB0083
DR0630
DR0919
DR0827
DRA0338
DR1949
DR1195
DR0601
DR1847
DR2600
DR0646
DRA0326
Arginine metabolic process
GTP metabolic process
Metal ion homeostasis
Oxygen transport
cell wall organization (Table 1). We found that some nodes involved in different categories simultaneously. For example, nodes DR0569, DR0778, DR0785, DR1454, DR1679 and DR2547 involved in the oxygen transport and the dicarboxylic acid transport at the same time. The node DR1910 participated the dicarboxylic acid transport as well as the cell wall organization (Table S1).
Nodes with degree of seven are over-represented in D. radiodurans R1 gene regulatory network
We observed that 131 nodes with degree of seven appeared in D. radiodurans R1 gene regulatory network (Figure 3). Theoretically, the number should be less than that of the node with degree of six (47 nodes). To understand the biological meaning behind the over-representation, we extracted the sub-network of the 131 nodes with the degree of seven from the whole gene regulatory network, and performed the GO term enrichment analysis for the sub-network. We found that thirteen biological processes were enriched (Table 2). The enriched biological processes could be classified into 4 categories: (1) DNA repair; (2) reactive oxygen species (ROS) metabolic process and superoxide metabolic process; (3) glycine catabolic process and (4) tRNA aminoacylation (Table 2).
DiscussionIn this study, we reconstructed the first gene regulatory network
for the extreme radiation-resistant bacteria D. radiodurans R1 using Bayesian network approach. Further analysis for the gene regulatory network revealed that twelve mechanisms involved in the radiation-
Category GO.ID Term p-value
1
GO:0006950 response to stress 0.048
GO:0033554 cellular response to stress 0.027
GO:0006974 response to DNA damage stimulus 0.041
GO:0006281 DNA repair 0.041
2GO:0072593 reactive oxygen species metabolic process 0.015
GO:0006801 superoxide metabolic process 0.015
3GO:0009071 serine family amino acid catabolic process 0.043
GO:0006546 glycine catabolic process 0.043
4
GO:0019538 protein metabolic process 0.011
GO:0044267 cellular protein metabolic process 0.042
GO:0043038 amino acid activation 0.041
GO:0043039 tRNA aminoacylation 0.041
GO:0006418 tRNA aminoacylation for protein translation 0.041
Table 2: Significant biological processes in the sub-network of 131 nodes with degree of 7.
resistant processes in D. radiodurans R1.
We find eight mechanisms of radiation-resistance in D. radiodurans R1: (1) Arginine metabolic process; (2) GTP metabolic process; (3) Dicarboxylic acid transport; (4) Protein transport; (5)
Citation: Wan P, Yue Z, Xie Z, Gao Q, Yu M, et al. (2013) Mechanisms of Radiation Resistance in Deinococcus radiodurans R1 Revealed by the Reconstruction of Gene Regulatory Network Using Bayesian Network Approach. J Proteomics Bioinform S6: 007. doi:10.4172/jpb.S6-007
Page 5 of 5
Microarray ProteomicsJ Proteomics Bioinform ISSN:0974-276X JPB, an open access journal
Protein oligomerization; (6) Cell wall organization; (7) Glycine catabolic process and (8) tRNA aminoacylation. Some mechanism has been proved to be radiation-resistant in other organisms. For example, arginine could protect hematopoietic progenitor cells against ionizing radiation in mammalian [21]. The existences of nodes involve different mechanisms (Table S1) suggest that different mechanisms may act in concert under the radiation stress.
Previous studies have found that DNA repair and reactive oxygen species (ROS) mechanism respond to radiation in all biological systems including mammalian [4]. In this study, we also found that DNA repair process and reactive oxygen species metabolic process are two significant radiation-resistant mechanisms in D. radiodurans R1 (Table 2). Therefore, our results are consistent with the known knowledge. Our finding of the over-representation of node with degree 7 in D. radiodurans R1 gene regulatory network suggests that D. radiodurans R1 may has a more complex DNA repair and reactive oxygen species (ROS) mechanism than other organisms.
In 2009, Daly proposed the manganese-based radiation protection hypothesis [9]. The hypothesis involves metal ion homeostasis and oxygen transport process. In this study, we also find that the two mechanisms are related to radiation resistance (Table 1). Therefore, our results support Daly’s manganese-based radiation protection hypothesis.
One limitation of our study is that Bayesian network is a directed acyclic graph (DAG). So our gene regulatory network did not include the relationship of negative feedback regulation. Nevertheless, our results are not only validated by the well-known mechanisms, and also support the recent hypothesis of radiation resistance. Thus, our findings uncover more radiation-resistant mechanisms in D. radiodurans R1.
In summary, using Bayesian network approach, we reconstruct the first gene regulatory network of the extreme radiation-resistant bacterium D. radiodurans R1. We find more radiation-resistant mechanisms in D. radiodurans R1. Our results are not only consistent with the known knowledge, but also support the current radiation-resistant hypothesis.Acknowledgement
The authors would like to thank Xiaoke Gui and Yubao Chen for their helpful discussions. This work was supported by Beijing Municipal Education Commission PHR Project (Grant No.PHR201008078). We appreciate the effort of the anonymous reviewer and his/her useful comments and suggestions for improving the manuscript.
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