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a Department of Internal Medicine V, University of Heidelberg, Heidelberg, Germany;8 }4 U' A, m0 \- Z! G
) L/ P8 S! {- }$ ub German Cancer Research Center (DKFZ), Heidelberg, Germany;, a, O4 _7 o+ v2 X) n# C8 x
& j- p. r* U) Gc Biochemical Instrumentation Programme, European Molecular Biology Laboratory, Heidelberg, Germany;* S& | b! m. R: v+ l, X
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d Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
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1 Z; g$ I5 O# ^/ f# Y* eKey Words. Hematopoietic stem cell ? Microarray ? Retroviral vector integration ? CD34 ? Gene expression ? Gene targeting2 J- c; X% O8 E& a5 n" E
7 ^# m2 j( A. D! t& {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@urz.uni-heidelberg.de
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ABSTRACT
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The molecular characteristics of hematopoietic stem cells (HSCs) are still largely unknown . Many authors have demonstrated that the CD34 /CD38– cells were highly enriched in stem cells whereas the CD34 /CD38 subset represents more committed progenitors . 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) . 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.1 _& [' l/ @( l
0 ]3 W2 q$ }1 k$ Z! pVarious 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 . 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 . The gene expression profiles of the SDF provided further evidence for their primitive function . 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 . 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 . After reverse transcription (RT) of viral RNA, this viral DNA is integrated into the host-cell DNA , and several studies have demonstrated that this integration is not random but favors actively transcribed genomic regions . We have described 189 retroviral integration sites in human severe combined immunodeficient (SCID) repopulating cells (SRCs) . Retroviral integration occurred preferably at the start of the transcription unit and in the first intron of genes in repopulating hematopoietic cells . 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.- x+ |; L" s4 I! @1 n, m
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MATERIALS AND METHODS; v! r& |: e9 d* R
8 _* R/ G6 _8 u0 z7 I9 tWe 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).
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, G1 z7 o' w( h! N q& \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.. P" Q. O/ R8 j. J3 O3 K
( D* W% S! y1 c& `Microarray data of two different studies were used: CD34 /CD38– cells versus CD34 /CD38 cells and SDF versus FDF . We have compared normalized signal intensity values and normalized ratios of 51,143 different ESTs of the UnigeneSet RZPD3 that is presented on the microarray with data of two subsets of genes targeted for integration: For the combination of 72 RefSeq genes and 82 Ensembl genes that were targeted by oncoretroviral vector integration in SRCs , we identified 76 genes that were represented by 117 different ESTs on the Human Genome Microarray (Table 1). For the 332 RefSeq genes that were targeted by retroviral integration in HeLa cells , we identified 268 different genes on the Human Genome Microarray represented by 446 different ESTs. In three different genes, retroviral integration sites were observed in both SRCs and HeLa cells (CD109 ; KIF13A ; FYB ).
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Table 1. Genes with SF91m3-vector integration in SRCs and corresponding microarray data
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To estimate whether integration site selection correlated to transcriptional activity, signal intensity values of corresponding spots on the microarray were analyzed. Signal intensity correlates roughly with abundance of corresponding transcripts. The average signal intensity was determined for those channels that represent CD34 /CD38– cells. Signal intensities of all ESTs of the UnigeneSet RZPD3 represented on the array revealed a median signal intensity of 20,569 (arbitrary units). In 446 spots representing the set of control genes with retroviral integration in HeLa cells, median signal intensity was 31,164. In the subset of 117 spots on the microarray representing ESTs with retroviral integration in SRCs, the median signal intensity was 51,701. One-sided t-test of log10 values of signal intensity demonstrated that signal intensity was significantly higher in genes targeted in SRCs as compared with all ESTs on the array (p = 2.6 x 10–9), as well as in comparison with genes that were targeted in HeLa cells (p = 1.9 x 10–3). Thus, genes with retroviral integration in repopulating hematopoietic cells correlate with transcriptional activity in CD34 /CD38– cells rather than genes with integration in nonhematopoietic HeLa cells (Fig. 2A). Analysis of retroviral integration sites located upstream of a gene revealed that integration occurred preferentially near the transcription start of genes and these insertions also correlate with higher expression data (median signal intensity 39,609; p = 9.6 x 10–3; Fig. 2B).1 U* v' }+ q! |* D1 p: h- U& w3 `
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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 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.( ~. v6 f. ?9 B! x7 S6 c& @
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We subsequently analyzed if retroviral integration in SRCs occurred preferably in genes with a higher differential expression in more primitive fractions of hematopoietic progenitor cells (CD34 /CD38– or SDF) as compared with the more committed progenitor cells (CD34 /CD38 or FDF). Differential expression ratios (log2 ratios) of all ESTs of the UnigeneSet RZPD3 revealed a symmetric Gaussian distribution in the two comparisons (CD34 /CD38– versus CD34 /CD38 : mean log2 ratio = 0.007, SD = 0.346; SDF versus FDF: mean log2 ratio = –0.011, SD = 0.418) (Fig. 3). In contrast, the set of ESTs representing genes with retroviral vector integration sites in repopulating hematopoietic cells revealed higher expression in the CD34 /CD38– fraction (CD34 /CD38– versus CD34 /CD38 : mean log2 ratio = 0.076, SD = 0.333) and in the SDF (SDF versus FDF: mean log2 ratio = 0.171, SD = 0.532; Table 1). Statistical analysis showed a significantly higher expression of genes that were targeted in SRCs in these fractions that are enriched in primitive HSCs as compared with all ESTs on the array (CD34 /CD38–: p = .0043; SDF: p = .0002)." \- R" [) w: h% b' N; j0 W2 b
2 R& O- }1 Z4 p& C1 {( NFigure 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.( B) }" S+ T2 x: j7 K8 ~- l( K' F2 X$ ~
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DISCUSSION
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0 E" v( R- D$ nWe 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.- u( b+ ~7 P$ F
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发表于 2015-5-23 13:54
