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TISSUE-SPECIFIC STEM CELLS

Stringent Regulation of DNA Repair During Human Hematopoietic Differentiation: A Gene Expression and Functional Analysis

^a Institut für Zellbiologie and
^b Innere Klinik (Tumorforschung), Universitätsklinikum Essen, Essen, Germany;
^c Institut für Transplantationsdiagnostik und Zelltherapeutika, Universitätsklinikum Düsseldorf, Düsseldorf, Germany

Key Words. Comet assay • Ethylnitrosourea • EtNU • Melphalan • Nucleotide excision repair • Base excision repair • Hematotoxicity

Correspondence: Jürgen Thomale, Ph.D., Institute of Cell Biology, University of Duisburg-Essen Medical School, Essen, Germany. Telephone: 49-201-723-4230; Fax: 49-201-723-3104; e-mail: juergen.thomale{at}uni-essen.de.

Received May 18, 2005; accepted for publication September 9, 2005.

	ABSTRACT

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 
For the lymphohematopoietic system, maturation-dependent alterations in DNA repair function have been demonstrated. Because little information is available on the regulatory mechanisms underlying these changes, we have correlated the expression of DNA damage response genes and the functional repair capacity of cells at distinct stages of human hematopoietic differentiation. Comparing fractions of mature (CD34^–), progenitor (CD34⁺38⁺), and stem cells (CD34⁺38^–) isolated from umbilical cord blood, we observed: 1) stringently regulated differentiation-dependent shifts in both the cellular processing of DNA lesions and the expression profiles of related genes and 2) considerable interindividual variability of DNA repair at transcriptional and functional levels. The respective repair phenotype was found to be constitutively regulated and not dominated by adaptive response to acute DNA damage. During blood cell development, the removal of DNA adducts, the resealing of repair gaps, the resistance to DNA-reactive drugs clearly increased in stem or mature compared with progenitor cells of the same individual. On the other hand, the vast majority of differentially expressed repair genes was consistently upregulated in the progenitor fraction. A positive correlation of repair function and transcript levels was found for a small number of genes such as RAD23 or ATM, which may serve as key regulators for DNA damage processing via specific pathways. These data indicate that the organism might aim to protect the small number of valuable slow dividing stem cells by extensive DNA repair, whereas fast-proliferating progenitor cells, once damaged, are rather eliminated by apoptosis.

	INTRODUCTION

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The cellular capacity to remove drug-induced lesions from the nuclear DNA strongly determines the sensitivity of normal and malignant hematopoietic cells to DNA-reactive agents, such as alkylator-type antineoplastic drugs [1–3]. Here, on the molecular level, a network of distinct and evolutionary, highly conserved pathways has been identified, that allows cells to repair their DNA when damaged by adducts, crosslinks, or strand breaks [4, 5]. Studies in animals defective for specific repair functions have underscored the role of the DNA repair machinery in the response of mammalian hematopoietic cells to DNA damage [6 – 8], and this notion is further supported by genetic or pharmacological manipulation of DNA repair function in primary blood cells [9 –14]. However, little information is available on the regulation of this network, the exact role of individual pathways, or crosstalk between pathways in the lymphohematopoietic system and other primary tissues.

In human leukocytes generated from peripheral blood or umbilical cord blood samples, a broad spectrum of individual DNA repair phenotypes has been observed regarding overall repair capacity and distinct repair functions [15–18]. These variations could be ascribed, at least partly, to polymorphisms [19] or other genetic variances in the corresponding structural or regulatory gene sequences [20]. In addition to the individual repair phenotype, we and others have demonstrated distinct shifts in functional DNA repair when comparing defined sub-populations in the lymphohematopoietic differentiation process such as CD34⁺ progenitor or mature CD34^– cells [18, 21, 22]. The functional impairment of progenitor cells to process DNA alkylation damage was not restricted to a specific function or component of the multipathway network [22] (Fig. 1), implying some sort of differentiation-dependent regulation of the complex DNA repair machinery during hematopoiesis. At present it is not known, however, whether the repair capacity of primary human cells is mainly determined by transcriptional regulation, for example, of rate-limiting gene products along a given pathway, or at subsequent steps like protein modification or cellular localization of critical components. Therefore, we have analyzed the expression profiles of DNA damage response genes at different stages of maturation in primary human hematopoietic cells, with a specific focus on genes directly involved in major repair pathways [23]. Additionally, we have correlated their regulatory pattern to the kinetics of DNA damage processing in these cells.

View larger version (20K): [in this window] [in a new window]   Figure 1. Schematic outline of major DNA damage repair pathways and functional assays. Primary adducts are detected by the immunocytological assay (ICA) and secondary lesions by the comet assay. Abbreviations: BER, base excision repair; NER, nucleotide excision repair; GGR, global genomic repair; TCR, transcription coupled repair; MMR, mismatch repair; DSBR, double-strand break repair; HR, homologous recombination; NHEJ, nonhomologous end joining; SSB, single-strand break; DSB, double-strand break; MX, methoxyamine (a specific inhibitor of early BER).

	MATERIALS AND METHODS

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For functional analysis the primitive, stem cell-enriched fraction of CD34⁺38^low cells and the progenitor-enriched CD34⁺38⁺ cell fraction were isolated from preselected CD34⁺ cells by fluorescence-activated cell sorting (FACS). After incubation with CD34-fluorescein isothiocyanate (FITC), CD38-PE, and CD45-PerCP-Cy5.5 antibodies (BD Pharmingen, San Diego, http://www.bdbiosciences.com/pharmingen; 15 minutes in phosphate-buffered saline (PBS)/1% FCS), cells were washed in PBS and sorted by using a FACSVantage (BD Biosciences). The purity of CD34⁺38^low and CD34⁺38⁺ fractions was >95%. During and after drug exposure, cells were kept in supplemented RPMI medium at 37°C in a humidified atmosphere containing 5% CO₂.

For comparative microarray expression analysis of primitive and progenitor cells, CD34⁺38^low and CD34⁺38⁺ cells were isolated from the CD34⁺-enriched fraction by immunostaining with CD3-FITC, CD14-FITC, CD16-FITC, CD19-FITC, CD20-FITC, and CD56-FITC (lin1 antibody cocktail; BD Biosciences), as well as glycophorin A (GA)-FITC, CD38-PE, and CD34-PeCy5 antibodies (BD Pharmingen). lin1^–GA^–CD34⁺CD38^low and lin1^–GA^–CD34⁺CD38⁺ cells were highly purified using a Coulter EPICS Elite ESP fluorescence cell-sorting system equipped with the Expo32 software (Beckmann Coulter) with lin1^–GA^–CD34⁺CD38^low comprising one-sixth of total lin1^–GA^–CD34⁺ cells. Separated cell fractions were frozen in TRIzol (Invitrogen, Carlsbad, CA, http://www.invitrogen.com) and stored at –80°C until RNA was prepared.

Exposure to Drugs and Apoptosis Assay
For the measurement of repair kinetics, cells were exposed to N-ethylnitrosourea (EtNU; Sigma, 100 µg/ml) for 30 minutes or to melphalan (Alkeran; 10 µg/ml; GlaxoSmithKline, Research Triangle Park, NC, http://www.gsk.com) in RPMI medium (10% FCS, 5 mM HEPES) for 2 hours at 37°C. Thereafter, cells were washed in PBS, resuspended in prewarmed RPMI, and incubated at 37°C. Cell aliquots were taken prior and at different time points after drug treatment. For expression profile analysis, EtNU-exposed cells were postincubated for 2 hours prior to RNA isolation. For repair inhibition studies, cells were preincubated with 1 mM methoxyamine (MX; Sigma) for 1 hour prior to EtNU exposure and throughout the experiment. Drug-induced apoptosis in cells was measured 24 hours after the addition of cisplatin (Platinex; Bristol-Meyers Squibb, New York, http://www.bms.com), EtNU, or melphalan to the medium. The fraction of apoptotic cells was determined by annexin V-FITC staining (Annexin V Detection Kit I; BD Pharmingen) and FACS analysis.

Comet Assay
DNA strand breaks in individual nuclei of small cell fractions were measured by single-cell gel electrophoresis ("comet assay") modified according to McNamee et al. [24]. In brief, from 8-well cell culture chamber slides (BD Falcon, Franklin Lakes, NJ, http://www.bdbiosciences.com) the glass bottom was removed and replaced by GelBond film (Cambrex, Walkersville, MD, http://www.cambrex.com; Biozym, Hess, Oldendorf, Germany, http://www.biozym.com). Aliquots of 10⁴ cells were suspended in 45 µl of low-melting point agarose (0.75% in PBS, prewarmed at 42°C; Metaphor; Biozym) and cast into the wells. After coagulation the frames were removed, and the gels on the film were soaked overnight at 4°C in lysis buffer (2.5 M NaCl, 100 mM EDTA, 10 mM Tris, 10% dimethyl sulfoxide, 1% Triton X-100, 1% n-laurylsarcosinate, pH 10). Nuclear DNA was denatured by alkaline treatment (300 mM NaOH, 1 mM EDTA, 10 mM Tris-HCl, pH 12.7) for 15 minutes, and GelBond films were subjected to alkaline electrophoresis in the same buffer (20 minutes, 4°C, 1.5 V/cm). After neutralization (30 minutes, 400 mM Tris-HCl, pH 7.5), gels were dehydrated in absolute ethanol (1 h) and air-dried. Before evaluation of comet formation, gel films were rehydrated, and the nuclear DNA was stained with SYBR-Green (dilution 1:10,000; Roche Diagnostics, Basel Switzerland, http://www.roche-applied-science.com).

Immunocytological Assay
Immunoanalytical measurement of melphalan-induced adducts in the nuclear DNA of individual cells was performed as described [22] with minor modifications: 10⁴ cells/sample were applied to precoated microscopic slides (ImmunoSelect; Squarix, Marl, Germany, http://www.squarix.de) and immuno-stained for melphalan-DNA adducts with rat monoclonal antibody Amp 4–42 (kindly provided by Dr. M. J. Tilby, University of Newcastle upon Tyne, Newcastle upon Tyne, U.K.). Binding of primary antibody was visualized by consecutive staining with rabbit anti-(rat Ig) and goat anti-(rabbit Ig), both labeled with Cy3 (Dianova).

Quantitative Image Analysis and Statistics
Comet assay and immunocytological assay (ICA) were evaluated by quantification of fluorescence signals using a photomicroscope (Axioplan; Zeiss, Jena, Germany, http://www.zeiss.de) and a multiparameter image analysis system (ACAS; Ahrens Electronics, Bargteheide, Germany). Melphalan adduct levels of individual cell nuclei were calculated by normalizing the antibody-derived fluorescence signals for the DNA content of the same cell. The relative amount of DNA strand breaks (comet assay) was determined using the olive tail moment [OTM = (migrated DNA) x(distance between the head and center of gravity of DNA in the tail)] [25]. Mean signal values (±SEM) were calculated from >100 individual cells per sample. Data of corresponding cell pairs from the same donor were analyzed by paired t test.

RNA Preparation
Cells were homogenized using a QIAShredder column (Qiagen, Hilden, Germany, http://www1.qiagen.com), and total RNA was isolated according to the manufacturer’s instructions. RNA concentrations were measured by fluorescence staining (Ribo-Green Kit; Molecular Probes) using a microplate reader, and RNA quality was verified by electrophoresis in 1% agarose gels. Due to the small number of cells in the CD34⁺38^low fraction, isolated RNA from four individual cord blood samples was pooled and compared with pooled RNA from the CD34⁺38⁺ fractions of the same four donors.

RNA Amplification
To obtain sufficient amounts of labeled material for the Gene-Chip hybridization, RNA samples from individual CD34⁺ or CD34^– cell fractions were subjected to a two-round amplification procedure according to Baugh et al. [26] with modifications. Briefly, total RNA (300 ng) was converted into cDNA using 0.5 µg of an oligodeoxythymidine primer containing the T7 RNA polymerase binding site (5'-GCATTAGCGGCCGCGAAATTAATACGACTCACTATAGGGAGA-(dT)₂₁V-3') (MWG Biotech, Ebersberg, Germany, http://www.mwg-biotech.com) for first-strand synthesis in a total volume of 15 µl of (1x First Strand Buffer [Invitrogen], 0.5 mM dNTPs, 10 mM dithiothreitol [DTT], 200 U of SuperScript II [Invitrogen], 0.5 µg of T4gp32 [GE Healthcare, Piscataway, NJ, http://www1.amershambiosciences.com], 30 U of RNasin [Promega, Mannheim, Germany, http://www.promega.com]) for 45 minutes at 42°C, 10 minutes at 45°C, and 10 minutes at 48°C. After heat inactivation for 15 minutes at 65°C, second-strand synthesis in 100-µl reactions [1x Second-strand buffer (Invitrogen), 0.2 mM dNTPs, 1 U of RNase H (Takara, Otsu, Japan, http://www.takara.co.jp), 20 U of Escherichia coli DNA polymerase I (Invitrogen), 6 U of E. coli DNA ligase (Takara)] was performed for 2 hours at 16°C. Subsequently, 8 U of T4 DNA polymerase (Invitrogen) was added, and incubation continued for 15 minutes at 16°C. Double-stranded cDNA was purified on spin columns (Microarray purification kit; Roche Diagnostics), precipitated with glycoblue (Ambion, Austin, TX, http://www.ambion.com) and transcribed in 40 µl of [1x T7 RNA polymerase buffer (Takara), 4 mM NTPs, 10 mM MgCl₂, 1% polyethylene glycol 20000, 6.25 mM DTT, 40 U of pyrophosphatase (USB), 40 U of RNasin (Promega), 1.5 µg of T7 RNA polymerase] for 16 hours at 37°C. Reactions were treated with 2 U of RNase-free DNase I (Ambion) for 30 minutes at 37°C before purification on spin columns (Roche) and quantitated by optical density measurement. For second-round cDNA synthesis, 500 ng of first-round amplification products was used in all cases. Reverse transcription with SuperScript II was performed with 0.5 µg of random hexamer primer (Stratagene) in 15-µl reactions without T4gp32 as described above. Following heat inactivation, RNA templates were removed by digestion with 2 U of RNase H for 30 minutes at 37°C. After annealing of T7-dT₂₁V primer (100 ng) at 42°C for 5 minutes, reactions were snap-cooled in ice water. Second-strand cDNA synthesis was performed in a final volume of 100-µl reactions (1x Second-strand buffer, 0.2 mM dNTPs, 1 U of RNase H, 20 U of E. coli DNA polymerase I) for 2 hours at 16°C and trimmed with 10 U of T4 DNA polymerase for another 15 minutes at 16°C. CDNA was purified, precipitated, and transcribed with T7 RNA polymerase as described above, except that ribonucleotide concentrations were 4 mM each for GTP and ATP, 1.4 mM each for CTP and UTP, and 0.6 mM each for biotin-11-CTP and biotin-11-UTP (PerkinElmer Life and Analytical Sciences, Boston, http://www.perkinelmer.com). Pooled samples of lin^–CD34⁺38⁺ or lin^–CD34⁺38^low-derived RNA (500 ng) were amplified by one round of cDNA synthesis using the MessageAmp II aRNA kit (Ambion) and in vitro transcription in the presence of biotinylated NTPs as described above.

Oligonucleotide Microarray Analysis
Biotin-labeled cRNA was purified on RNeasy columns (Qiagen), fragmented, and hybridized to HG-U133A GeneChips (Affymetrix, Santa Clara, CA, http://www.affymetrix.com) following the Affymetrix standard protocol. The arrays were washed and stained according to the manufacturer’s recommendation and finally scanned in a GeneArray scanner 2500 (Agilent, Palo Alto, CA, http://www.home.agilent.com). Array images were processed to determine signals and detection calls (present, absent, and marginal) for each probe set using the Affymetrix Microarray Suite 5.0 software. Scaling across all probe sets of a given array to an average intensity of 1,000 was performed to compensate for variations in the amount and quality of the cRNA samples and other experimental variables of nonbiological origin.

Analysis of Microarray Data
For unsupervised hierarchical clustering, signals of individual probe sets were normalized to the mean probe set signal of all included arrays and log transformed. Log transformed ratios were subjected to UPGMA clustering using correlation as similarity measure (Spotfire DecisionSite for functional genomics). As additional criteria we used the present calls in 30% of the samples and a ratio of means of 1.5 or 0.67. To compare corresponding pairs of CD34⁺/CD34^– or CD34⁺38⁺/CD34⁺38^low cells from the same donor for the magnitude and direction of change, we employed the signal log ratio (SLR) algorithm giving the differences as binary logarithmic values.

Quantitative Reverse Transcription-Polymerase Chain Reaction
For real-time polymerase chain reaction (PCR) analyses, total RNA was reverse-transcribed using random primers (High Capacity cDNA Archive Kit; Applied Biosystems). PCR was carried out in duplicate 20-µl reactions containing cDNA corresponding to 5 ng of total RNA, 1 µl of Taqman-based assay, and 1x master mix reagents (Applied Biosystems). PCR was performed on an ABI Prism 7900HT system as recommended by the manufacturer using the glyceraldehyde-3-phosphate dehydrogenase assay (Hs99999905_m1) as the endogenous reference and ATM (Hs00175892_m1), RAD23A (Hs00192541_m1), and RAD50 (Hs00194871_m1) as target assays. Differential expression was estimated by the comparative C_t method (ABI Prism 7700 Sequence Detection System User Bulletin #2: Relative Quantification of Gene Expression [P/N 4303859]).

	RESULTS

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 
Expression of Damage Response Genes in CD34⁺ and CD34^– Cells
To assess the transcriptional activity of genes involved in DNA damage response at different stages of lymphohematopoietic differentiation, CD34⁺ progenitor cells and their mature CD34^– counterparts were prepared from seven individual cord blood samples. Total RNA was isolated, and gene expression profiles were determined using Affymetrix HG_U133A GeneChips. Hybridization signals from 1418 probe sets, representing a total of 803 DNA damage response genes, were evaluated. By our criteria (present calls in 30% of the samples), transcripts for 633 (79%) of these genes were detected. This set comprised 296 of 366 genes related to cell-cycle control, 254 of 330 genes related to apoptosis, and 153 of 189 genes related to DNA repair functions with some genes listed in more than one subgroup. Pronounced interindividual variances in specific transcript levels of DNA repair genes were observed at both stages of differentiation. For instance, the amount of mRNA transcribed from the mismatch repair gene MSH2 varied at a maximum range of 7.5-fold (fluorescence signals: 286–2,145) among CD34⁺ and 4.6-fold (signals: 190–882) among CD34^– cell samples. The corresponding values for RAD23A, a gene involved in nucleotide excision repair, were 6.7-fold (signals: 764–5,142) and 4.1-fold (signals: 2,909–12,024), respectively. For the majority of genes, interindividual variations were found in a 2.5- to 3.5-fold range, with a tendency to broader variations in progenitor cells. On the other hand, a small number of genes was expressed more constantly, showing less than 2-fold inter-individual variations within either of the cell fractions. One member of this group was the XPA gene coding for a key component of both sub-pathways of nucleotide excision repair (NER), that is global genomic (GGR) and transcription-coupled repair (TCR).

Despite the pronounced interindividual variation at the level of specific transcripts, stringently regulated, differentiation-dependent shifts in gene expression profiles were observed. Unsupervised hierarchical cluster analyses employing the whole set of damage response genes revealed a clear-cut separation between progenitor and mature blood cells (Fig. 2A). A similar pattern was found when focusing on genes associated with DNA repair functions or apoptosis (Fig. 2B, 2C), indicating that these genes are stringently regulated during hematopoietic cell development and that this regulation dominates interindividual variability in gene expression.

View larger version (55K): [in this window] [in a new window]   Figure 2. Expression profiles of DNA damage response genes separate mature (CD34–) and progenitor (CD34+) cord blood cells. Fourteen RNA samples from seven corresponding pairs of hematopoietic cells were subjected to GeneChip analysis. Signals from individual probe sets were normalized to the mean and log-transformed, and ratios were analyzed by unsupervised hierarchical clustering (see Materials and Methods; relative expression: red [significantly higher], green [significantly lower], or black [mean]). The dendrograms and matrices represent the clustering of 962 probe sets (DNA damage response) (A), 102 probe sets (DNA repair) (B), and 219 probe sets (apoptosis) (C). Criteria for the depicted probe sets in (A): present call in 30% of the CD34+ or the CD34– samples; additional in (B), and (C): ratio of means 1.5 or 0.667.

View larger version (33K): [in this window] [in a new window]   Figure 3. Most differentially expressed genes contributing to major DNA repair pathways are consistently upregulated in progenitor compared with mature cells. SLRs of 37 differentially expressed genes with function in one or more of the major repair pathways: BER (A), NER (B), MMR (C), and DSBR (D). White bars show the SLRs of individual CD34+/CD34– cell pairs from the same donor; black bars represent the mean SLRs of all seven samples (criterion for significant up- or down-regulation: p .005 or .995 for at least 4/7 CD34+/CD34– cell pairs). Abbreviations: SLR, single log ratio; BER, base excision repair; NER, nucleotide excision repair; MMR, mismatch repair; DSBR, double-strand break repair.

Functional Analysis of Cellular DNA Repair and Correlation with Gene Expression Profiles
The overall capacity of hematopoietic cells to process DNA damage was measured by single-cell gel electrophoresis ("comet assay"), which determines repair-induced DNA strand breaks in individual cell nuclei and by ICA allowing the direct measurement of drug-induced DNA adducts (Fig. 1). To induce a set of structurally defined DNA adducts, CD34⁺ or CD34^– cell fractions in liquid holding were exposed to a short pulse of EtNU, a fast-reacting monofunctional alkylator (t_1/2 in cells: 7 minutes), which is not subject to active drug transportation. EtNU interacts with the cellular DNA to form about a dozen different ethylation products (among them 15% N⁷-guanine, 9% O⁶-guanine, 9% O²-/O⁴-thymine, 4% N³-adenine, and 3% O²-cytidine) [27], which simultaneously trigger repair responses via various pathways such as NER, BER, and MMR or direct removal by the alkyl-DNA alkyltransferase O⁶-methylguanine-DNA methyltransferase (MGMT).

For quantitative evaluation of the repair kinetics by the comet assay, two parameters were utilized: 1) the amount of DNA strand breaks present directly after a 30-minutes period of drug exposure (OTM, t₀: representing the efficiency of initial repair incision) and 2) the slope of the repair curve (OTM/t: depicting the efficiency of gap filling in religation steps) (Fig. 4A). Although analysis of both parameters confirmed the high interindividual variance in the DNA repair capacity of hematopoietic cells at the functional level, repair kinetics between mature and progenitor cells from the same donor differed markedly, too (Fig. 4B, 4C). Fewer early incisions into adducted DNA (8/8 samples, p = .004) and slower religation of repair gaps (7/8 samples, p = .018) both indicate less efficient repair processing of EtNU-induced DNA lesions in CD34⁺ progenitor cells.

View larger version (26K): [in this window] [in a new window]   Figure 4. Processing of DNA lesions in hematopoietic cells shows high interindividual variation and is impaired in progenitor compared with stem and mature cells. Following exposure to N-ethylnitrosourea (EtNU; 100 µg/ml; 30 minutes), the kinetics of repair-induced DNA strand breaks were determined by the comet assay (measurement of OTM) in CD34+ or CD34– cells isolated from eight cord blood samples, as well as in CD34+38low or CD34+38+ cells from four individual samples. (A): Two parameters for the cellular repair capacity, the efficiency of initial strand incision (OTM, t0), and the velocity of repair gap resealing (OTM/minutes) were determined. (B, C): Both parameters were significantly lower in the related CD34+ cell fractions (paired t test: p = 0.004 and 0.018, respectively). Statistical evaluation is given in the box (25–75 percentile) and whisker (5–95 percentile) plots. (D): Kinetics for CD34+38low and CD34+38+ cell fractions from an individual donor. (E, F): In addition to pronounced differences between four individual samples, the frequency of initial DNA strand breaks and repair velocity were consistently higher in the stem cell fraction. Abbreviation: OTM, olive tail moment.

To link the removal of primary and secondary DNA lesions to chemosensitivity, the onset of apoptosis after exposure to EtNU, melphalan, or cisplatin was investigated (Table 1). A consistently higher apoptotic response in progenitor versus mature cells was observed, thus backing up our earlier observation of accelerated induced cell death after treatment with DNA-damaging agents in progenitor cells [22].

To address the relative contribution of individual pathways to the overall repair activity, the pharmacological inhibitor MX was employed, which prevents the strand incision as an early step along the BER pathway [15] (Fig. 1). Thus, the proportion by which MX reduces the frequency of DNA strand breaks after drug treatment estimates the contribution of BER to the overall repair capacity of a cell. When comparing CD34⁺ and CD34^– cell pairs after exposure to EtNU alone or combined with MX, the relative contribution of BER was consistently (4/4 samples) higher in the CD34⁺ subset than in mature cells (mean ± SEM: 51 ± 7% and 21 ± 12%, respectively). This observation is in agreement with the augmented mRNA levels of all (10/10) differentially expressed BER genes in the progenitor cell compartment (Fig. 3A).

No Immediate Transcriptional Response to EtNU-Induced DNA Damage
It has been shown that exposure of human cell lines to DNA-damaging agents can induce a significant shift in the expression profile of DNA damage response genes [29]. Therefore, the functional differences in repair capacity, which we observed between CD34⁺ and CD34^– cells, could be due to cell type-specific rapid up- or downregulation of DNA damage-related genes shortly after drug exposure. To investigate this possibility, we have compared gene expression profiles in both cell fractions prior to and 2 h after exposure to EtNU. However, no major shifts in mRNA levels upon initial DNA damage were observed either in mature or in progenitor cells (Fig. 5A, 5B). The changes induced by EtNU treatment were by far less pronounced than those observed between cells of different maturation status (Fig. 5C).

View larger version (27K): [in this window] [in a new window]   Figure 5. Lack of transcriptional response in mature and progenitor hematopoietic cells early after DNA alkylation stress. Scatter plots of the hybridization signals from 1,418 probe sets (representing 803 DNA damage response genes); comparison of cord blood–derived cells prior to and 2 hours after ex vivo exposure to EtNU (100 µg/ml) CD34+ (A); CD34– (B); and CD34+ versus CD34–, both untreated (C). Abbreviation: EtNU, N-ethylnitrosourea.

View larger version (24K): [in this window] [in a new window]   Figure 6. Genes for major DNA repair functions are differentially expressed in primitive CD34+38low and CD34+38+ progenitor cells. Up- or downregulation of transcripts (single log ratio [SLR]; see Fig. 3) as measured in pooled RNA samples from four cord blood specimens (criterion for significance: p values of SLRs .005 or .995). Abbreviations: BER, base excision repair; NER, nucleotide excision repair; MMR, mismatch repair; DSBR, double-strand break repair.

	DISCUSSION

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

We now have employed gene array technology to allow a correlation of functional and gene expression analysis and have extended our studies to the hematopoietic stem cell compartment. We show that the differentiation-dependent alterations in DNA repair function and apoptotic response are accompanied by characteristic and consistent shifts in the expression profiles of related genes. Although genome-wide transcriptional signatures have been described for distinct stages of lymphohematopoietic differentiation [30, 31], very limited information is available on the regulation of the DNA repair machinery. For a small number of repair genes, such as XPG, XPD, MSH2, KU80, LIG3, or RAD23A, higher expression in bone marrow stem cells compared with terminally differentiated cells has been reported in mice [29, 30]. However, no comparable data are available on distinct developmental stages in the human system. The study presented here now reveals a strict differentiation-dependent regulation within the DNA damage response network of human hematopoietic cells. The uniform shift in transcript levels of regulated genes, up or down, in all seven cord blood specimens investigated implies a high biological relevance for this observation.

Despite this stringent regulation during development, intriguingly high interindividual differences were observed in repair gene expression, as well as functional repair capacity. Similar individual variations were detected for the induction of apoptosis following cytotoxic drug exposure (Table 1) or toxicity of chloroethylnitrosourea- or triazine-type alkylating agents for human clonogenic progenitor cells (personal observation). It can be speculated also that the substantial differences in antineoplastic response or hematotoxic side-effects observed with DNA-damaging agents in the clinical situation may be related to the individual DNA repair capacity of malignant or physiologic cells, respectively. Thus, dosage based on prior assessment of DNA repair capacity in tumor cells, as well as normal tissue, may represent a way to individualize antineoplastic therapy and improve results.

Rather surprising results were obtained when functional and expression profiling data were compared. Despite their significantly lower capacity to remove DNA adducts and secondary strand breaks, progenitor cells contained higher mRNA levels than their maturated progeny for 35/37 differentially expressed pathway-related repair genes. Comparing the progenitor and stem cell fractions, a similar discrepancy was noted. Here, reduced expression for 16/19 pathway-related genes in primitive cells was associated with higher repair efficiency. A possible explanation for this observation could be the impact of post-transcriptional control instances on the performance of the repair system such as ubiquitination-triggered protein turnover [32–34], stability modulation of protein complexes [35, 36], or intracellular/intranuclear localization of key components [37, 38]. In addition, low abundant gene products not detectable by oligonucleotide arrays may represent rate-limiting "bottleneck" positions along a given repair pathway and significantly determine its functional activity. Thus, important regulatory functions might be associated with the substantial number of repair genes not qualifying for present calls in our analyses (14/97 in mature vs. progenitor cell analysis, 21/97 in progenitor vs. stem cells).

On the other hand, the few pathway-related genes with shifts in transcript levels being conform to the alterations in functional repair may be essential for fine-tuning the cellular response to DNA damage. One of these genes encodes for ATM, a protein kinase that senses and signals the presence of DNA lesions, in particular double-strand breaks, to essential checkpoints and initiates rejoining [39]. Mammalian cells deficient for this protein are sensitive to radiation but also to DNA alkylation damage [40], most likely due to an essential role of ATM in stabilization and nuclear localization of mismatch repair complexes [41]. Recently, functional ATM was shown to be involved in counteracting oxidative stress in mouse bone marrow cells. In this model, ATM represented a crucial factor for the self-renewal capacity of hematopoietic stem cells but was less important for their differentiation into progenitor cells [42].

The other gene with significantly diminished transcript levels in progenitor versus mature cells is RAD23A. The RAD23 proteins are involved in the regulation protein turnover via the ubiquitin/proteasome pathway [43, 44] and recently were found to stabilize the XPC protein, which is the core damage recognition factor initiating global repair via the NER pathway [35]. Thereby, they are ideal candidates to regulate the NER activity by controlling the influx into the pathway without disrupting the balance of the complex interaction of the other components. Based on these findings, the RAD23 proteins have been suggested to play a central role in a novel, newly emerging DNA damage-dependent regulatory mechanism for DNA repair in mammalian cells [45]. Interestingly, RAD23A is among the repair genes with the broadest interindividual variation of transcript levels in the cord blood samples analyzed and thus may be a key factor in controlling the individual repair capacity. Its relevance for the handling of DNA alkylation products is further strengthened by our observation that human XPC-RAD23 complexes can recognize EtNU-induced adducts in DNA and are essential for their NER-mediated excision in human lymphoid cells (unpublished data). Also in line with the downregulation of RAD23A and the reduced NER activity in progenitor cells is the higher relative contribution of BER (no downregulated constituents) to their overall repair capacity.

Thus, in contrast to expression levels of the majority of genes involved, the least efficient DNA repair during hematopoietic differentiation resides within the progenitor cell compartment, whereas increased capacity is observed in more mature as well as more primitive cells. At first sight this may appear surprising, as an organism can be expected to equip its pool of particularly proliferation-competent cells with protective mechanisms to counteract DNA damage and the emergence of mutated daughter cells. From the perspective of the organism, however, eliminating damaged cells via apoptosis rather than attempting to restore their genomic integrity also represents an efficient defense mechanism against genotoxic stress in critical cell compartments. A well-known example of this principle is intrathymic T-cell development, where cells expressing nonfunctional T-cell receptors are eliminated via apoptosis [46]. Along a similar line, experiments with murine embryonic stem (ES) cells have revealed their limited capacity to remove UV photolesions from the genome [47, 48]. Interestingly, the relative repair deficiency of ES compared with fully differentiated cells was not accompanied by an increased mutation rate, and this was due to an effective induction of cell death programs even at low levels of DNA damage. These data suggest that apoptosis in stem cells is triggered preferentially by global genomic damage, whereas transcription-blocking lesions in active genes may represent the critical signals in maturated cells. The model is in agreement with our observations in the human lymphohematopoietic system, where the proliferation-competent progenitor cells exhibit reduced efficiency of global repair and increased apoptotic response upon exposure to DNA-damaging agents. Thus, this might be a general way to protect somatic "cell replenishment compartments" from the accumulation of genetic damage and thereby avoiding the expansion of mutated cells and their potential malignant transformation.

	DISCLOSURES

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The authors indicate no potential conflicts of interest.

	ACKNOWLEDGMENTS

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We thank S. Niesert (Elisabeth-Krankenhaus, Essen, Germany) and G. Kögler and P. Wernet (Universitätsklinikum Düsseldorf) for providing cord blood samples; M. J. Tilby (University of Newcastle upon Tyne) for the generous gift of anti-(melphalan-DNA adduct) antibodies; R. A. Hilger and M. Grubert (Universitätsklinikum Duisburg-Essen, Essen, Germany) for the measurement of intracellular melphalan levels; and A. Feldmann and M. Möllmann (Innere Klinik [Tumorforschung]) for excellent technical assistance. Research was supported by Wilhelm Sander-Stiftung Grant 1999.082.1 and in part by Bundesministerium für Bildung und Forschung-Nationales Genomforshung-snetz Grant KR S06T06 and Mildred Scheel-Stiftung Grant 10-2039 to J.T. and T.M.

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