The proteomics and gene expression data were obtained from radiation-treated AT5BIVA and ATCL8 cell lines. AT5BIVA was derived from human fibroblasts of ataxia teleangiectasis (AT) patient with mutated ATM (AT mutated) gene (Jung et al, 1995), while ATCL8 was derived by reintroducing the wild-type ATM gene into the AT5BIVA cells. The two cell lines were exposed to 10 Gy of ionizing radiation and analyzed at time intervals from 30 minutes to 24 hours. The proteomics data were obtained from two-dimensional gel electrophoresis (2D-gel) followed by MALDI-MS of the excised gel spots. The gene expression data were obtained using Affymetrix DNA microarray (U133A probe set of 14500 human genes) chip assays. The experimental procedures for cell culture and radiation treatment, 2D-gel, MALDIMS proteomics and microarray have been described elsewhere (Lee et al., 2001; Mewani et al, 2006). Protein identification from MALDI-MS was based on MASCOT search engine using UniProtKB/Swiss-Prot database. Lists of proteins were identified (with UniProtKB accession #) from differentially changed 2D-gel spots based on >=2-fold changes (p-value <=0.05), increased (including newly appeared spots after irradiation) or decreased (including spots only in control but disappeared after irradiation) for each time point and cell type. Lists of genes were identified (with Entrez Gene #) from differentially expressed mRNAs (increased or decreased) in microarray based on >= 1.5- fold changes (p-value <= 0.05).

We applied an integrated bioinformatics approach for the proteomics and gene expression data analysis. The iProXpress integrated protein expression analysis system http://pir.georgetown.edu/iproxpress/ was primarily used as a platform for the functional data analysis, coupled with the Ingenuity Pathway Analysis (IPA) tool for pathway and network analysis. A prototype of the iProXpress system has been applied to several previous high-throughput studies (Li et al., 2004; Chi et al., 2006, Hu et al., 2007). Below we briefly describe the bioinformatics analysis procedures.

1) Protein mapping: Gene or protein lists were mapped to UniProtKB protein entries primarily based on gene/protein identifiers. Genes with common identifiers such as GenBank, UniGene or Entrez Gene are mapped based on the PIR ID mapping service http://pir.georgetown.edu/pirwww/search/idmapping.shtml. For genes with no ID match, the mapping is based on sequence comparison, or name mapping if the sequence is not available. The protein and gene lists from AT5BIVA and ATCL8 cells were integrated into the iProXpress system after protein mapping.

2) Protein annotation: After protein mapping, rich annotations are described in a protein information matrix that captures salient features of proteins, such as functions and pathways, for given experimental data sets. These rich annotations are derived from comprehensive protein information that have been integrated into the UniProt and iProClass databases and from sequence analysis for homology-based inference.

3) Functional profiling: The gene and protein lists were divided into experimental groups based on cell types and time course for functional profiling using various functional attributes (i.e. annotation fields of the protein information matrix). Primarily used for functional profiling were GO slims (a subset of GO with high level terms at GO hierarchy) http://www.geneontology.org/GO.slims and pathway information (e.g. from KEGG database).

4) Pathway and network analysis: Pathway visualization was based on pathway diagrams provided in source pathway databases such as KEGG and the IPA tool. An ATM protein interaction pathway map was also used, which was curated by scientists who initially discovered the ATM gene (Savitsky et al., 1995) and reflects the current state of knowledge for ATM-mediated pathways available at http://www.cs.tau.ac.il/~spike/images/1.png. Network analysis was done using the IPA tool, which dynamically generates functional association networks based on curated literature information of protein-protein interaction, coexpression, and genetic regulation.

Figure 1 depicts genotypes the overview of an integrated bioinformatics approach to analyze and interpret the proteomics and gene expression data from irradiated cells with mutant or wild type ATM genotypes.

Figure 2 shows the iProXpress web interface for searching, browsing, and profiling the experimental groups of different cell types, time courses, and protein or mRNA level changes. The interactive graphical user interface provided several functionalities for data analysis, such as selecting data groups, browsing the proteins and associated annotations, and expression profiling using GO slims and pathways.

The 2D-gel/MS proteomics and DNA microarray data generated from radiation-treated AT5BIVA and ATCL8 cells are summarized in Table 1, which shows total numbers of UniProt protein entries mapped from proteomics and gene expression data. Most up-regulated proteins were observed at 3hr post-irradiation in both AT5BIVA and ATCL8 cells, and with many more up-regulated in ATCL8 than in AT5BIVA cells. In contrast, most downregulated proteins were seen at 30min in ATCL8 and at 24hr in AT5BIVA cells. At gene expression level, prominent responses to radiation at early time in ATCL8 cells were observed, for example, three times as many mRNAs were up-regulated at 30min in ATCL8 (33) as in AT5BIVA (11) cells, while up-regulation of most genes was only seen 1hr after radiation in AT5BIVA cells. These differences showed that ATCL8 was more radiation-responsive at both protein and mRNA levels at earlier time than the ATM-mutated AT5BIVA cells. Compared to AT5BIVA, ATCL8 cells were shown to quickly respond to irradiation at 30min by increasing more gene expressions and by decreasing the amounts and/or activities (presumably modification states) of more proteins, followed by increasing more at 3hr.

The profiling of the differentially changed proteins or genes from irradiated cells based on GO slims and the KEGG pathways provided global views of functional changes in these cells. Table 2 shows the major GO biological process categories of radiation induced protein changes. The total changed proteins (combined up- and down-) in the two cell lines generally showed similar profiles among top categories of GO biological processes. However, profiles based on up- or down-regulated proteins showed clear differences between the two cell lines. For example, in AT5BIVA cells, a higher percentage of proteins involved in cell cycle was down-regulated (8.3%) than up-regulated (4.8%), and more were up-regulated than down-regulated in RNA metabolism, transcription, and protein biosynthesis. In ATCL8 cells, a higher percentage of proteins were up-regulated in signal transduction and protein modification, while more were down-regulated in protein biosynthesis.

When profiling is performed using KEGG pathways for the total changed proteins, differences were observed in the percentages of proteins involved in purine metabolism, glycolysis/gluconeo-genesis, pyrimidine metabolism, and glutamate metabolism in the two cell lines. Pathway profiling based on the up- or downregulated proteins resulted in more differences between the AT5BIVA and ATCL8 cells. For example, higher percentages of down-regulated proteins in purine metabolism and of up-regulated proteins in starch and sucrose metabolism and folate biosynthesis were observed in AT5BIVA cells. Also consistent with GO process profiles, more cell cycle proteins were seen downregulated in AT5BIVA while more were up-regulated in ATCL8 cells. Overall, metabolic pathways were clearly affected, and purine metabolism was the most affected pathway in irradiated AT5BIVA and ATCL8 cells based on the expression profiling using iProXpress as well as from the Ingenuity pathway profiles (not shown).

Although the general profiles in Table 2 provided global views of major functional changes in the two cell lines without regard to specific time points, profiles based on more specific or focused data groups, such as at certain time points, offered more biological insights. We selected a proteomics data set at 3hr from both AT5BIVA and ATCL8 cells and a microarray data set at 30min from ATCL8 only for further analysis, when most differentially changed protein or gene expressions were observed or most upregulation of proteins or genes occurred (Table 1). The comparative pathways profiling of four data groups representing the upand down-regulated proteins from AT5BIVA and ATCL8 cells at 3hr post-irradiation showed that purine metabolism is the most predominant pathway with 10 differentially expressed proteins, and major differences exist between the four data groups (Figure 3).

Table 3 lists proteins of purine metabolism from all time points (30min to 24hr) in AT5BIVA and ATCL8 cells. Most enzyme changes in this pathway occurred at 3hr in both cell lines, and those changed at other time points were mostly down-regulated in both cells. Strikingly, while most changed enzymes were downregulated at 3hr in AT5BIVA cells, all changed enzymes were up-regulated at 3hr in ATCL8 cells. Two enzymes with opposite changes were identifiet from the two cell lines, adenylate kinase 2 (up in ATCl8 and down in AT5Cl8 at 30min), and IMP dehdrogenase 2 (up in ATCl8 at 3hr and down in AT5BIVA at 24hr).

Figure 4 shows a diagram of the purine metabolism pathway with differentially expressed enzymes listed in Table 3 superimposed onto the pathway map. Interestingly, most of these enzymes are located at the biochemical steps surrounding the ADP/ATP or GDP/GTP synthesis. For enzymes involved in these steps, most were down-regulated in AT5BIVA cells, while most were up-regulated in ATCL8. This strongly suggests that the ATCL8 cells were able to respond to irradiation by increasing the amount or activities of nucleotide synthesis enzymes to prepare for increased DNA synthesis and repair.

Because of the relatively low numbers of differentially expressed genes from the microarray experiment, expressing profiling using GO or KEGG pathways was usually not revealing for most of the experimental groups (Table 1). Instead we focused on the differentially expressed genes from ATCL8 cells at 30min postirradiation, when more genes were differentially expressed in ATCL8 than in AT5BIVA cells, and most up-regulated genes in ATCL8 occurred. Table 4 lists gene products from the top 3 GO biological process categories, signal transduction, protein modification, and transcription, from the microarray experiment. Among them, p53, BRCA1 and HDAC1 were all up-regulated at 30min in ATCL8 cells and are also well-known to be involved in DNA repair and cell cycle control.

Furthermore, despite the low numbers of differentially expressed genes from microarray experiment, it was interesting to correlate these genes with differentially changed proteins from proteomics data. A total of 103 proteins (UniProt entries) from AT5BIVA and 131 from ATCL8 cells were mapped from from the microarray data of both AT5BIVA and ATCL8 cells (Table 1).shows the common protein set of 13 proteins, namely the overlapping genes/proteins between the proteomics and microarray data, 10 were from ATCL8 and 3 from AT5BIVA cells.

Interestingly, from above proteomics and microarray data RRM2 was shown to be increased at both mRNA and protein levels in ATCL8 cells, with mRNA level increased at 30min, and protein level increased at 1hr and 3hr (Table 3 and Figure 4).

A critical rate-limiting enzyme in DNA synthesis, RRM2 expression increased in ATCL8 cells at 1hr and 3hr after irradiation, while no changes were detected in AT5BIVA cells. Since RRM2 is involved in DNA repair, we wanted to examine the functional association networks involving RRM2 in the context of current proteomic and gene expression data.

Figure 5 shows the network in which RRM2 is connected with several major DNA repair and cell cycle proteins, including HDAC1, p53, BRCA1, and CDKN2A, directly or indirectly. Except for CDKN2A, a negative regulator of cell cycle progression, the other three proteins were all differentially regulated in ATCL8 cells, suggesting that RRM2 play an important role in radiation-induced and ATM-mediated DNA repair processes and cell cycle control.

Since AT5BIVA and ATCL8 cell lines were specifically designed as models for examining ATM-mediated pathways, we used an ATM protein interaction pathway map to examine changed proteins or genes from proteomics and gene expression data. This pathway map (Figure 6, left) shows that two proteins directly interacted with and activated by ATM are p53 and BRCA1, which were up-regulated in ATCL8 cells. Based on the expression data and the network analysis, we hypothesize that RRM2 is involved in radiation induced ATM-p53-mediated DNA repair pathway in the ATCL8 cells (Figure 6, right). RRM2 directly binds p53 and upon irradiation dimerizes with RRM2 to form the ribonucleotide reductase (RR) holoenzyme complex. Increased RR activity will result in an increase in the pool of deoxyribonucleotide precursors for DNA synthesis which is required for DNA repair in response to radiation damage.