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Retroviral Integration Sites Correlate with Expressed Genes in Hematopoietic Stem Cells

^a Department of Internal Medicine V, University of Heidelberg, Heidelberg, Germany;
^b German Cancer Research Center (DKFZ), Heidelberg, Germany;
^c Biochemical Instrumentation Programme, European Molecular Biology Laboratory, Heidelberg, Germany;
^d Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA

Key Words. Hematopoietic stem cell • Microarray • Retroviral vector integration • CD34⁺ • Gene expression • Gene targeting

Correspondence: Anthony D. Ho, M.D., Ph.D., Department of Internal Medicine V, University of Heidelberg, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany. Telephone: 49-6221-568001; Fax: 49-6221-565813; e-mail: anthony_dick.ho{at}urz.uni-heidelberg.de

	ABSTRACT

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In this study, we analyzed whether retroviral integration sites in repopulating hematopoietic cells correlate with genes expressed in fractions enriched in hematopoietic stem cells (HSCs). We have previously described microarray studies of two populations enriched in HSCs: CD34⁺/CD38^– and the slow dividing fraction of CD34⁺/CD38^– cells (SDF). Furthermore, we demonstrated that oncoretroviral integrations in severe combined immunodeficient repopulating cells are preferentially located near the transcription start. Here, we have identified 117 corresponding cDNA clones on our micro-array representing genes with retroviral integration sites. These genes revealed a higher mean signal intensity in comparison with either all genes on the array or a subset of control genes with retroviral integrations in HeLa cells. Furthermore, these genes demonstrated a higher expression in CD34⁺/CD38^– cells and SDF. The association of gene expression and retrovirally targeted genes observed here will help to elucidate the molecular characteristics of primitive repopulating hematopoietic cells.

	INTRODUCTION

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The molecular characteristics of hematopoietic stem cells (HSCs) are still largely unknown [1, 2]. Many authors have demonstrated that the CD34⁺/CD38^– cells were highly enriched in stem cells whereas the CD34⁺/CD38⁺ subset represents more committed progenitors [3–6]. We have demonstrated that division kinetics can be exploited as another parameter to further enrich HSCs. Asymmetric cell division and multipotency are found in the quiescent or slow dividing fraction of CD34⁺/CD38^– cells (SDF) and not in the fast dividing fraction (FDF) [5, 7–11]. Whereas immunophenotype, division kinetics, and colony assays such as long-term culture-initiating cells or multilineage-initiating cells all represent surrogate markers for primitive hematopoietic cells, the engraftment capacity is an additional feature of this cell population.

Various studies have determined genome-wide gene expression profiles of HSCs, but these efforts are limited by the heterogeneity of populations using the available methods for enrichment [12–17]. We have recently analyzed differential gene expression between CD34⁺/CD38^– versus CD34⁺/CD38⁺ cells as well as between the SDF versus FDF within the CD34⁺/CD38^– population [17]. The gene expression profiles of the SDF provided further evidence for their primitive function [17]. Combination with different published microarray datasets revealed that several candidate genes, including hoxa9, fzd6, mdr1, and jak3, are highly expressed in different murine and human stem cell fractions [13, 14, 17, 18]. Whereas these overlapping genes shed some light on the biology of the stem cell population, it would be desirable to establish a straightforward approach to highlight genes that are initially expressed in the small subset of HSCs. Integrations of retroviruses that have been used as vectors for gene delivery in different experimental studies and clinical trials may be suitable for this attempt. Other authors have reported that retroviral vector integration in primitive marrow repopulating cells occurred preferentially in actively transcribed genes in murine and nonhuman primate models [19–25]. After reverse transcription (RT) of viral RNA, this viral DNA is integrated into the host-cell DNA [26, 27], and several studies have demonstrated that this integration is not random but favors actively transcribed genomic regions [25, 28–32]. We have described 189 retroviral integration sites in human severe combined immunodeficient (SCID) repopulating cells (SRCs) [28]. Retroviral integration occurred preferably at the start of the transcription unit and in the first intron of genes in repopulating hematopoietic cells [28, 33]. Presuming that viral integration sites reflect actively transcribed genes in repopulating stem cells, this data might facilitate the understanding of gene expression in HSCs. To test this hypothesis, we have combined the microarray data with retroviral vector integration sites in SRCs.

	MATERIALS AND METHODS

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Microarray Analysis
Enrichment of HSCs and determination of their gene expression profiles have been described in detail elsewhere [17]. These studies were performed with the Human Genome Microarray developed at the European Molecular Biology Laboratory. It is comprised of 51,143 different cDNA clones of the UnigeneSet RZPD3. In brief, the CD34⁺/CD38^– cell fraction and the CD34⁺/CD38⁺ fraction were isolated from human umbilical cord blood. Gene expression profiles of these two fractions were compared in four cohybridization datasets. Furthermore, the CD34⁺/CD38^– fraction was subdivided according to division kinetics as described before [5, 17]. Cells were stained with the fluorescent membrane dye PKH26 and cultivated in a cytokine-containing medium for 7 days as described previously by Huang et al. [5]. The SDF that is enriched in primitive asymmetric dividing cells remained PKH26-positive after this cultivation period, while the dye was diluted on the progeny of the FDF. Gene expression profiles of the SDF and FDF were compared in six cohybridization datasets. For each spot, total intensity and local background were calculated by the ChipSkipper Microarray Data Evaluation Software (http://www.ansorge-group.embl.de/chipskipper/index.htm). Raw ratios were derived from background-reduced signals. Normalization was carried out by intensity-dependent windowed median ratio centering. To estimate transcriptional activation in CD34⁺/CD38^– cells, average signal intensity was calculated of corresponding Cy3 or Cy5 channels in four cohybridization datasets. The ratio of differential gene expression is presented as the mean of log₂ ratios of all replicate and color-flip hybridizations (log₂ ratio). Differential gene expression has been verified for a number of genes by RT–polymerase chain reaction (PCR) [17]. The complete microarray data are accessible at the public microarray database Array Express (http://www.ebi.ac.uk/arrayexpress; accession number: E-EMBL-1).

Retroviral Integration Sites
Retroviral transduction of human CD34⁺ cells and transplantation into mice have been described in detail before [28]. In brief, mobilized peripheral blood CD34⁺ cells were obtained from five healthy donors and exposed to retroviral supernatant after a 1-day cytokine-mediated prestimulation followed by a 3-day transduction procedure as previously described by Schilz et al. [34]. The hybrid vector SF91m3 is based on the Friend mink cell focus-forming/murine embryonic stem cell virus and contains the human multiple drug resistance gene (MDR1) as described before [35]. Female nonobese diabetic/LtSz-SCID (NOD/SCID) mice were conditioned by sublethal irradiation with a total dose of 3 Gy. Between 3 x 10⁶ and 4 x 10⁶ transduced CD34⁺ cells were transplanted per mouse [34, 36]. Six to eight weeks post-transplantation, the mice were killed and the bone marrow cells were harvested. DNA was extracted from 21 NOD/SCID mouse chimeric bone marrow preparations. Ligation-mediated PCR (LM-PCR) was performed as described before [28] to analyze the junction between provirus and human genomic DNA. The LM-PCR amplicons were then cloned and subsequently sequenced. Sequence and integration site analysis of these data has been reported before [28, 33].

Combination of Retroviral Integration Sites and Microarray Analysis
Two hundred seven retroviral integration sites in SRCs were sequenced and analyzed by the Basic Local Alignment Search Tool (BLAST) with the University of California at Santa Cruz (UCSC) Human Genome Project Working Draft (May 2004 freeze; http://genome.ucsc.edu). One hundred eighty-nine retroviral integration sites could be unambiguously matched with human DNA database sequences as described before (identity >97%) [28, 33]. Seventy-seven of these 189 retroviral integration sites (41% of the integration sites) mapped to 72 different reference sequence genes (RefSeq) [37]. In addition, we have analyzed the sequences with the ^projectEnsembl ContigViewer (February 2005 freeze; http://www.ensembl.org), and 89 retroviral integration sites (47% of the integration sites) mapped to 82 different Ensembl genes.

As controls, we have used a set of integration sites of murine leukemia virus (MLV) in HeLa cells [38], presuming that genes targeted in these cells should reveal less correlation with the gene expression profile of hematopoietic cells. Three hundred and thirty-two of 791 integration sites in HeLa cells (41% of the integration sites) could be mapped to RefSeq genes. Recently, it has been shown that different viruses have different integration patterns. Thus, the integration sites of the control HeLa infections are not a perfect control. However, both vector backbones (used for the HeLa cell and for human CD34 cells) belong to the same genus: murine leukemia–related viral group.

Data of retroviral integration sites and microarray data were compared as follows: Integration sites were designated in one of two ways, either by National Center for Biotechnology Information (NCBI) Refseq, or by Ensembl identifiers of genes at or near the insertion site. Similarly, either expressed sequence tags (ESTs) were matched to unigene and compared with the Refseq identifiers by unigene ID, or NCBI Refseq IDs were assigned to EST sequences by sequence BLAST. The Refseq IDs were matched to Ensembl genes according to the EnsMart assignments. The probability that the set of genes with retroviral integration was higher expressed in the CD34⁺/CD38^– fraction or in the SDF was estimated with the one-sided t-test versus either all ESTs presented on the Human Genome Microarray or the set of control genes.

	RESULTS

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We have previously demonstrated that retroviral integration in repopulating CD34⁺ cells of mobilized peripheral blood is not a random process and that transcriptional start regions of genes were preferred. Thus, retroviral vector integration might occur in genes that are actively transcribed in repopulating hematopoietic cells. To test this hypothesis, we have identified the ESTs on the Human Genome Microarray that correspond to genes targeted by retroviral integration. The differential expression in this set of genes was then analyzed (Fig. 1).

View larger version (29K): [in this window] [in a new window]   Figure 1. Combined analysis of retroviral integration sites and microarray data. Human CD34+ cells were transduced with retroviral vector supernatant and transplanted into NOD/SCID mice. After 6–8 weeks, the retroviral integration sites were analyzed by ligation-mediated polymerase chain reaction in repopulating cells. Under the presumption that genes with a retroviral integration site were activated in repopulating hematopoietic cells, these results were compared with microarray data. Abbreviations: FDF, fast dividing fraction; HSC, hematopoietic stem cell; NOD/SCID, nonobese diabetic/severe combined immunodeficient; SDF, slow dividing fraction of CD34+/CD38– cells.

View larger version (27K): [in this window] [in a new window]   Figure 2. Retroviral integration occurs preferentially in genes that are strongly expressed in CD34+/CD38– cells. Average signal intensity in cDNA spots on the microarray was determined of four cohybridization datasets with CD34+/CD38– cells. (A): Distribution of signal intensity (log10) of all ESTs of the UnigeneSet RZPD3 is demonstrated in the histogram (n = 51,143). By analogy, distribution of signal intensity is presented for the subset of genes with retroviral vector integration sites in HeLa cells (n = 446) and for the subset of genes that were targeted in SRCs (n = 117). Mean signal intensity was significantly higher in the set of genes with integration in SRCs, indicating that integration is favored in actively transcribed genes. (B): Signal intensity of cDNA spots was then analyzed in relation to distance of retroviral integration to transcription start. Retroviral integration occurred preferentially near the transcription start of genes. Signal intensity in microarray data was higher in genes in which integrations occurred in the transcribed region (median signal intensity = 51,701) and in which retroviral integrations were located upstream of the transcription start (distance in base pairs [bp] indicated in negative numbers; median signal intensity = 39,609). The gray dashed line indicates the median signal intensity of 20,569 of all genes on the microarray. Abbreviations: EST, expressed sequence tag; SRC, severe combined immunodeficient repopulating cell.

View larger version (29K): [in this window] [in a new window]   Figure 3. Retroviral vector integration is favored in genes upregulated in primitive fractions of hematopoietic cells (CD34+/CD38–; SDF). Differential expression (log2 ratio) of two microarray experiments is presented: (A) CD34+/CD38– versus CD34+/CD38+ and (B) SDF versus FDF. Analysis of all ESTs of the UnigeneSet RZPD3 reveals a symmetric Gaussian distribution of differential expression (mean is presented as gray). In contrast, the set of 117 cDNA clones representing genes with retroviral vector integration in SRCs revealed a higher expression in the stem cell fractions (CD34+/CD38– cells and SDF; mean is presented as black dashed line). On average, genes with retroviral vector integration sites in SRCs were significantly higher expressed in the fractions enriched in HSCs (* p = .0043, ** p = .0002). Abbreviations: EST, expressed sequence tag; FDF, fast dividing fraction; HSC, hematopoietic stem cell; SDF, slow dividing fraction of CD34+/CD38– cells; SRC, severe combined immunodeficient repopulating cell.

	DISCUSSION

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A number of authors have provided evidence that retroviral integration is favored in actively transcribed regions and should thus reflect gene expression [28–32]. Recent comparison of different retroviral vectors revealed that those derived from the HIV had an even higher preference for actively transcribed genes [32] whereas those derived from the MLV showed a stronger bias for integration near the transcription start sites [25, 28, 38]. Studies by Hematti et al. in nonhuman primate repopulating cells have shown that retroviral vectors with neomycin resistance gene or green fluorescent protein gene as transgene integrate preferentially in genes active in primitive hematopoietic cells [25]. Therefore, we do not consider that the similar effects observed here are due to a selection bias induced by the MDR1 transgene.

To estimate if retroviral integration in SRCs favored genes that are actively transcribed in hematopoietic cells, we have analyzed signal intensity in corresponding cDNA spots on microarrays hybridized with CD34⁺/CD38^– cells. Absolute gene expression can only roughly be estimated by signal intensity due to limitations of cDNA microarray technology resulting from variations in spot size, cDNA quantity, and different hybridization capability of different sequences. Various studies have demonstrated correlation of signal intensity in microarray data and absolute gene expression [39, 40]. However, interpretation of signal intensity should be cautious, and thus we did not focus on the absolute expression of individual genes but rather on the average expression level. Differential gene expression as observed by microarray analysis has been verified for a set of genes in our previous work [17]. Observations of this study indicate that retroviral integration in SRCs favored sequences located either upstream of the transcription start or within the transcribed region of genes actively transcribed in CD34⁺/CD38^– cells whereas genes with retroviral integration in nonhematopoietic HeLa cells were transcribed to a smaller extent. Thus, higher signal intensity in genes with retroviral integration sites in SRCs was not solely due to selection of characterized genes that are commonly expressed but also to specific transcriptional activity in hematopoietic cells. Furthermore, genes with retroviral integration in SRCs occurred preferably in genes that were higher expressed in primitive hematopoietic cell fractions of CD34⁺/CD38^– cells and SDF as compared with CD34⁺/CD38⁺ cells and FDF. Among the genes higher expressed in the stem cell fractions (CD34⁺/CD38^– or SDF) were several that might have impact in stem cell function (Table 1). Adhesion proteins that might play a role in the interaction of primitive hematopoietic cells with the microenvironment include galectin-9 [41], stromal interaction molecule 1 [42], and CD109 [43]. Notch homologue-2 is preferentially expressed in B cells and functions as a receptor for membrane-bound ligands Jagged1, Jagged2, and Delta1 to regulated cell-fate determination [44–46]. Transcription factors with implications in early hematopoiesis include early hematopoietic zinc finger protein (EHZF) [47] and pre–B cell leukemia transcription factor 3 (PBX3) [48]. Bruton agammaglobulinemia tyrosine kinase (BTK) and protein kinase C, beta 1 (PRKCB1) seem to play an important role in B-cell ontogeny [49, 50]. Although the information about retroviral integration sites in repopulating HSCs is today still very rudimentary, the results shown here provide evidence that those genes are preferably targeted by retroviral integration sites that are actively transcribed in early hematopoiesis. In the NOD/SCID repopulating cells investigated here are a mixed population of potential HSCs and committed progenitor cells. Because mature granulocytes have a half-life of a few days, detection of such cells 6 weeks after transplantation suggests continuous regeneration from a primitive cell pool. Detection of retroviral integrations in these progeny cells will therefore be informative with regard to the integration pattern into the highly proliferative precursor cells.

Retroviral integration sites were analyzed in repopulating hematopoietic cells and their differentiated daughter cells. This method has the capability of demonstrating active genes in this otherwise elusive primitive cell fraction. Criticisms can be raised that the culture conditions used to generate the data-sets of microarray analysis and retroviral integration site analysis were not identical. This issue will be corrected in further studies. Moreover, the number of well-characterized integration sites is still low. Further collection of data of retroviral vector integration sites is necessary to gain a more comprehensive picture of gene expression, and a far larger number of sequences needs to be analyzed to provide clear-cut insight in stem cell biology (e.g., microserial analysis of gene expression [SAGE]). Currently, the detection of retroviral integration sites is performed with PCR techniques that result in random amplification of a fraction of the integration sites. Collection of integration sites originating from the same vector, target cells, and transduction condition in a database will allow us to gain a more comprehensive picture on the representation of specific sites. Comparison of datasets directly after transduction and after long-term engraftment will allow us to address the question of differential survival of clones after retroviral gene transfer. Therefore, a collaborative RISC (retroviral integration site in chromosome) score database (CRSD) of the gene therapy safety group (http://www.gtsg.org) has been set up to allow comprehensive analysis as presented here. Further contribution of integration sites, including retroviral vector integration sites of large animals and patients and different cell sources, will allow us to further specify the gene expression pattern of long-term repopulating HSCs and their daughter cells.

	ACKNOWLEDGMENTS

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We wish to thank Wilhelm Ansorge, Alexandra Ansorge, and Ute Wirkner for providing the Human Genome Microarray and for their help in the microarray experiments. The technical assistance of Bernhard Berkus, Hans Jürgen Engel, Sigrid Heil, and Katrin Miesala and the support of the animal facility team of the German Cancer Research Center are gratefully acknowledged. We thank Klaus Kuehlcke and Sonja Naundorf for transduction of CD34⁺ cells (Fresenius-Biotech, Idar-Oberstein, Germany, http://www.fresenius-ag.com). We are grateful to Christopher Baum (Hannover Medical School, Hannover, Germany) for providing the SF91m3 vector. This work was supported by Deutsche Forschungsgemeinschaft (DFG) HO 914/2-3, Bundesministerium für Bil-dung und Forschung (BMBF) 01GN0107, NGFN2 EP-S19T01 and Siebeneicher Stiftung, Germany and in part by grant I0-2089-FlI of the Deutsche Krebshilfe and by grant M 20.4 of the H.W. & J. Hector-Stiftung. W.W. and S.L. contributed equally to this study.

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