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First published online June 7, 2005
Stem Cells Vol. 23 No. 7 August 2005, pp. 946 -957
doi:10.1634/stemcells.2004-0311; www.StemCells.com
© 2005 AlphaMed Press

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Clonal Heterogeneity in Growth Kinetics of CD34+CD38– Human Cord Blood Cells In Vitro Is Correlated with Gene Expression Pattern and Telomere Length

Kerol Bartolovica, Stefan Balabanova, Birgit Bernera, Hans-Jörg Bühringa, Martina Komorb, Sven Beckerc, Dieter Hoelzerb, Lothar Kanza, Wolf-Karsten Hofmannb, Tim H. Brümmendorfa

a Departments of Hematology/Oncology and
c Obstetrics/Gynecology, University Medical Center, Tübingen, Germany;
b Department of Hematology/Oncology, University Medical Center, Frankfurt/Main, Germany

Key Words. CD34+ • Telomere • Telomerase • Cell-cycle heterogeneity • Gene expression • Cord blood • Hematopoietic progentitor cells

Correspondence: Tim H. Brümmendorf, M.D., Department of Oncology and Hematology, University Hospital Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany. Telephone: 49-40-42803-3552; Fax: 49-40-42803-3563; e-mail: t.bruemmendorf{at}uke.uni-hamburg.de


   ABSTRACT
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Human hematopoietic stem cells (HSCs) are characterized by an extensive proliferative capacity that decreases from fetal liver to cord blood (CB) to adult bone marrow. In previous studies, it was demonstrated that the proliferative capacity of individual CD34+CD38– HSC clones is correlated with their growth kinetics in vitro and that HSC turnover in vivo can be estimated by telomere-length measurements.

The present study was aimed at the characterization of the clonal composition of CD34+CD38– human umbilical CB cells in terms of growth kinetics, telomere length, and gene expression profile. For this purpose, individual CD34+CD38– CB cells were sorted into 96-well plates containing serum-free medium supplemented with six growth factors. During expansion, cell numbers in each individual well were scored in 3-day intervals. Once sufficient cell numbers were achieved, telomere length was measured by flow fluorescence in situ hybridization (flow FISH). In a second set of experiments, gene expression and colony-forming capacity were analyzed in slowly growing clones as compared with fast-growing clones, using linear amplification and oligonucleotide microarrays (HG-U133A; Affymetrix).

Individual CD34+CD38– cells from CB displayed an extensive functional heterogeneity in growth kinetics. Among highly proliferative clones, the most slowly growing clones were characterized by the longest telomeres. Furthermore, significant differences in gene expression were detected between slow- and fast-growing clones, whereas no significant difference in colony-forming capacity was observed. These data provide further evidence for a functional hierarchy in the human HSC compartment and suggest a link between telomere length and proliferation capacity of individual HSC clones.


   INTRODUCTION
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Hematopoietic stem cells (HSCs) are characterized by their ability to differentiate into all hematopoietic lineages while retaining their capacity for self-renewal [1] as well as by an extensive proliferation capacity that decreases during ontogeny [2]. The heterogeneous composition of the human HSC compartment is poorly understood due to the lack of experimental tools that allow the characterization of the developmental program of individual stem cells [3]. According to our current knowledge, the HSC pool may be separated into several distinct subpopulations based on both surface marker expression and retrospective identification of HSCs, using in vivo and in vitro stem cell assays. The CD34 antigen has become the major positive marker for human hematopoietic stem and progenitor cells [4]. In human fetal liver, umbilical cord blood (CB), and bone marrow, 0.5%–5% of hematopoietic cells express CD34 [5, 6], and cells with this phenotype harbor virtually all in vitro clonogenic potential [5–7]. However, the pool of human hematopoietic cells defined by CD34 expression is heterogeneous. A small fraction of CD34+ cells (1%–10%) that does not express mature lineage markers (or CD38) [8] contains cells with in vitro bilineage, lymphoid (B/NK), and myeloid differentiation potential [9–12]. Furthermore, CD34+CD38– cells and not CD34+CD38+ cells are highly enriched for long-term culture-initiating cells [13, 14] and contain severe combined immunodeficiency (SCID)-hu–repopulating [9] as well as nonobese diabetic SCID–repopulating cells [15, 16].

In previous studies, we analyzed the functional heterogeneity of single-sorted CD34+CD38– cells from human fetal liver in growth factor–supplemented serum-free medium in vitro [17]. The number of cells in primary cultures varied widely after 6–10 days. When CD34+CD38– cells derived from slowly growing clones were recloned, the number of cells in their respective sub-clones varied widely again. These results were indicative of a symmetric cell divisions in primitive hematopoietic cells in which proliferative potential and cell-cycle properties are unevenly distributed among daughter cells [17].

The aim of the present study was the characterization of the clonal composition of the CD34+CD38– compartment from an ontogenetically later but clinically more relevant HSC source, i.e., human umbilical CB. Slow growth kinetics in vitro were correlated with telomere length and gene expression profiling to potentially identify new parameters that might help to define immature subpopulations among CD34+CD38– candidate HSCs.


   MATERIALS AND METHODS
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Umbilical CB Samples
CB was obtained from normal full-term deliveries after informed consent was given. The protocol of the study was approved by the ethics review board of the medical faculty of the University of Tübingen. Samples of CB were collected in heparinized 200-ml tubes. Mononuclear cells were purified using Ficoll-Hypaque density gradient centrifugation (Biochrom AG, Berlin, http://www.biochrom.de) and cryopreserved in 10% dimethyl sulfoxide (Sigma Aldrich, Munich, Germany, http://www.sigmaaldrich.com). Cells were stored in liquid nitrogen until use.

Purification of Umbilical CB Stem Cell Candidates
Human CB cells were thawed, and CD34+ cells were enriched using a negative StemSep column system (StemCell Technologies Inc, Vancouver, British Columbia, Canada, http://www.stemcell.com) according to the supplier’s directions. For gene expression analysis and methylcellulose assays, human CB cells were selected using a Midi-MACS CD34 Isolation Kit (Miltenyi Biotec, Bergisch Gladbach, Germany, http://www.miltenyibiotec.com) according to the manufacturer’s instructions.

Single-Cell Sorting and Expansion Cultures
Enriched CD34+ cells were labeled with anti–CD34-fluorescein isothiocyanate (FITC), anti–CD38-phycoerythrin (Becton, Dickinson and Company, Oxford, U.K., http://www.bd.com), and 1 µg/ml propidium iodide (PI) (Sigma). Using a FACSVantage cell sorter equipped with a Clonecyte device (Becton, Dickinson and Company), CD34+CD38– PI– cells were individually sorted directly into round-bottomed tissue culture plates (Nunc, Roskilde, Denmark, http://www.nuncbrand.com) containing 100 µl of serum-free medium supplemented with 100 ng/ml of human stem cell factor (SCF) and human Flt-3 ligand, 50 ng/ml human thrombopoietin, and 20 ng/ml each of human interleukin (IL)-3, IL-6 (CellSystems, St. Katharinen, Germany, http://www.cellsystems.de), and G-CSF (Amgen, Munich, Germany, http://www.amgen.com) (Fig. 1Go). The cells were incubated at 37°C in a humidified atmosphere with 5% CO2 in air. After 5 days of culture, another 100 µl of growth factor–containing medium was added. In time intervals of 3 days, cell numbers of each individual well were estimated under an inverted microscope [17]. When clone size reached ≥ 1 x 105 cells per well (Fig. 1AGo), colonies were individually transferred in 1-ml cultures of 24-well plates for further expansion. Once sufficient cell numbers were achieved (minimum 2 x 105 cells/well), telomere length was measured by flow FISH. In a second independent set of experiments, colonies reaching 1 x 104 cells per well were split. Five thousand cells of each individual clone were frozen for gene expression analysis by DNA microarray technology. To assess the content of lineage-committed progenitors of the individual clone, 2 x 500 cells of each clone were directly transferred in a methylcellulose assay.



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  		Figure 1. Experimental design of the study. Abbreviations: GF, growth factor; SFM, serum-free medium.

 
Telomere FISH and Flow Cytometry
The average length of telomere repeats at chromosome ends in individual cells in clones derived from a total of four human CB samples was measured by flow FISH (Fig. 2Go). Analysis was performed in the presence or absence of FITC-labeled telomere-specific peptide nucleic acid probes (dark grey and light grey peaks in Fig. 2CGo, respectively) to allow subtraction of autofluorescence of cells in the same light-scatter window from telomere fluorescence (horizontal bar). FITC-labeled fluorescent calibration beads (Quantum 24 Premixed; Flow Cytometry Standards Corporation, Fishers, IN, http://www.bangslabs.com) were used to correct for shifts in the linearity of the flow cytometer as well as for fluctuations in the laser intensity and to allow the expression of results in standard fluorescence units as reported previously [18]. At the beginning of each experiment, the fluorescence signals from four different populations of FITC-labeled microbeads suspended in phosphate-buffered saline with 0.1% bovine serum albumin were acquired. Results were expressed in molecular equivalents of soluble fluorochrome units (kMESF), as shown in Figure 2CGo. Average telomere length in individual colonies was measured on different days. To control for day-to-day variation in hybridization efficiency, mononuclear cells from the same bully coat were analyzed in each experiment as reported previously [19]. Due to restrictions in cell numbers, only 17 clones were analyzed in doublets, whereas 10 clones could only be analyzed as single values.



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  		Figure 2. Experimental setup for flow fluorescence in situ hybridization analyses of clones derived from single-sorted CD34+CD38– cells from human umbilical cord blood. (A): The cells were gated on region 1 (diploid cells, R1) on the basis of propidium iodide (PI) fluorescence and forward light scatter (FSC). (B): Region 2 was selected within R1 from the forward-scatter (FSC) versus side-scatter (SSC) dot-plot diagram. (C): Telomere fluorescence of a clone was analyzed after hybridization with or without FITC-(C3TA2) peptide nucleic acid (dark gray and light gray histograms in panel C, respectively).

 
Methylcellulose Progenitor Assay for Colony-Forming Units
The content of lineage-committed progenitors of clones derived from single-sorted CD34+CD38– cells from three umbilical CB samples was assessed using a methylcellulose assay. Once individual clones reached ≥ 1 x 104 cells per well, cells were harvested. A total of 2 x 500 cells of an individual clone were plated in 1.1-ml semisolid methylcellulose progenitor culture medium (StemCell Technologies Inc) containing a cocktail of recombinant human cytokines: SCF (50 ng/ml), GM-CSF (10 ng/ml), IL-3 (10 ng/ml), and Epo (3 U/ml). After 16 days of culture at 37°C in a humidified atmosphere with 5% CO2, plates were assessed for the presence of erythroid (mainly burst-forming units-erythroid [BFU-E]) and myeloid colonies (colony-forming units-granulocyte/macrophage [CFU-G/M]).

Oligonucleotide Microarrays
Gene expression in clones (n = 134) derived from single-sorted CD34+CD38– cells (n = 1440) was analyzed by oligonucleotide microarrays (HG-U 133A; Affymetrix, Inc., Santa Clara, CA, http://www.affymetrix.com) in two independent experiments with three human CB samples each. Clones at a level of ≥ 1 x 104 cells per well were harvested and frozen down as dry pellet. In each of the two experiments, dry pellets from slowly growing clones and from fast-growing clones, respectively, were pooled together. Both genomic DNA and total RNA were extracted using TRIzol (Invitrogen, Karlsruhe, Germany, http://www.invitrogen.com) according to the manufacturer’s protocol with minor modifications. To ensure that the gene expression measured by microarray assay was not affected by degradation of the RNA extracted from the clones, we used the Bioanalyzer System (Agilent Technologies, Waldbronn, Germany, http://www.agilent.com) to evaluate the quality of the RNA. The detailed protocol for the sample preparation and microarray processing is available from Affymetrix, Inc. Because of the limited number of cells and the low RNA content in clones derived from single-sorted CD34+CD38– CB cells, a double in vitro transcription technique (nanogram-scale assay) was used. Purified RNA 50 ng was reverse transcribed by Superscript II reverse transcription (Invitrogen) using T7-(dT)24 primer containing a T7 RNA polymerase promoter. After synthesis of the second cDNA strand, this product was used in an in vitro transcription reaction to generate complementary cRNA. This cRNA was used for a second round of in vitro transcription for synthesis of the biotinylated cRNA. Fifteen micrograms of fragmented cRNA was hybridized to an HG-U133A microarray (Affymetrix) for 16 hours at 45°C with constant rotation at 60 rpm according to the Affymetrix protocol. After hybridization, the microarray was washed and stained on an Affymetrix fluidics station and scanned with an argon-ion confocal laser, with a 488-nm emission and detection at 570 nm. The image was processed by Affymetrix Microarray Suite Software 5.0, and individual arrays were analyzed with the MAS 5.0 algorithm for single-array analysis. Data analysis was performed with the GeneSpring software version 4.2 (Agilent Technologies, Palo Alto, CA, http://www.agilent.com/USeng/home.html). Data were normalized first by each sample to itself (making the median of all measurements within one sample to 1) and secondly by each gene to itself (making the median of all measurements of one gene within several samples to 1). To eliminate changes within the range of background noise and to select the most differentially expressed genes, upregulated genes were required to be called present by the Affymetrix data analysis. For differential gene expression, a minimum of twofold change was required. Hierarchical clustering analysis with Spearman’s confidence correlation was used to identify gene clusters. The separation ratio was set at 0.5.

Statistical Analysis
The mean difference in telomere length between fast-growing and slowly growing clones was statistically analyzed using the Student’s t-test (GraphPad Software, San Diego, http://www.graphpad.com). A value of p < .05 was considered significant. In colony-forming assay, the categories of fast-growing versus slowly growing clones were compared by an unpaired t-test according to the number of CFU-G/M and BFU-E (GraphPad Software).


   RESULTS
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Categorization of Primary Cultures Derived From Single CD34+CD38– Umbilical CB Cells
Five hundred ninety-five single CD34+CD38– CB candidate stem cells from four independent human CB samples were sorted in individual wells of round-bottomed tissue plates containing serum-free medium supplemented with human growth factors. Within 24 hours after sorting, a single viable cell was detected in 352 wells (plating efficiency, 59%) with the use of an inverted microscope. The cell number was analyzed in regular (mostly 3-day) time intervals. Two hundred ninety-six of the single-sorted cells proliferated to more than 50 cells per well (cloning efficiency, 50%). More than 11% of the single-sorted cells reached a clone size of > 1 x 105 cells and were transferred into 1-ml cultures of 24-well plates. A total of 27 transferred clones (5%) achieved a sufficient cell number (minimum 2 x 105 cells/well) for telomere-length analysis by flow FISH. Based on the time span it took the individual clone to reach 1 x 105 cells, the transferred clones were categorized into two groups. The median duration to expand to 1 x 105 cells was 36 days. Accordingly, clones that required ≤ 36 days were classified as fast, whereas the remaining ones were classified as slowly growing clones.

Growth Kinetics of Highly Proliferative CB Clones
The growth kinetics of 27 transferred clones that achieved a clone size of 1 x 105 cells between days 30 and 57 is graphed in Figure 3Go. After individual clones were transferred into 24-well plates, the cell number was not counted any more until the clones were harvested for flow FISH analysis. According to the median time span it took individual clones to reach 1 x 105 cells (i.e., 36 days), 20 of the transferred clones were classified as fast (≤36 days) and 7 as slowly growing clones (>36 days). After 12–15 days in culture, the number of cells per well varied over a wide range, indicating extensive heterogeneity among CB CD34+CD38– cells. On day 27, rapidly growing clones yielded an average cell number (mean ± standard error of mean [SEM]) of 48,000 ± 6,000, compared with 27,000 ± 10,000 found in slowly growing clones.



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  		Figure 3. Clonal heterogeneity in single-sorted CD34+CD38– human umbilical cord blood cells in growth factor–supplemented serum-free medium. At the indicated time intervals, the number of cells (mean ± standard error [SE]) in each well was scored under an inverted microscope. Here, clones that required less or equal as compared with more than 36 days to reach the level of 105 cells per well were classified as fast-growing (n = 20) or slowly growing (n = 7), respectively. The plot shows the growth kinetics from the day when single cells were sorted until the first time point, when individual clones were transferred into 24-well plates.

 
Telomere-Length Measurements of CB Clones
We could observe a substantial heterogeneity in telomere length between the 27 highly proliferative clones, ranging from 9 to 23 kMESF. A significant negative linear correlation between growth kinetics and telomere length was observed (not shown). Slowly growing clones (n = 7), which have previously been characterized by a high proliferative potential [17], showed significantly longer telomere length compared with the group of fast-growing clones (n = 20). The mean difference in telomere fluorescence between fast-growing (mean ± SEM, 13.7 ± 0.6 kMESF) and slowly growing (20.1 ± 0.6 kMESF) clones amounted to 6.4 kMESF (Fig. 4Go; p < .001), which is equivalent to approximately 3.2 kb.



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  		Figure 4. Telomere length analysis by flow fluorescence in situ hybridization in clones (n = 27) derived from CD34+CD38– human umbilical cord blood cells cultured in serum-free medium supplemented with stem cell factor, Flt-3, interleukin-3, interleukin-6, thrombopoietin, and G-CSF. Mean telomere length (black bar) was expressed for the category of slowly growing clones compared with the category of the fast-growing clones. Slowly growing clones (n = 7, including three single values) showed significantly (p < .001) longer telomeres compared with the fast-growing clones (n = 20, including seven single values).

 
Methylcellulose Progenitor Assay for Colony-Forming Units
To investigate the colony-forming capacity in fast compared with slowly growing clones, a methylcellulose colony assay was used. A total of 50 clones from three human umbilical CB specimens achieved a clone size of 1 x 104 cells per well between days 12 and 28. According to the median time span it took individual clones to reach 1 x 104 cells (i.e., 18 days), 25 of the clones were classified as fast-growing or slowly growing clones, respectively. When achieving the target cell number of ≥ 1 x 104 cells per well (Fig. 1BGo), respective cells were directly put in a methylcellulose assay. The average number of CFU-GM and BFU-E colonies of each clone is graphed in Figure 5Go. Colony-forming capacity was detected in 21 of 25 clones from the fast-growing category (84%) compared with 20 of 25 clones from the slowly growing category (80%). In the category of fast-growing clones, a total of 753 colonies were detected. Of these, 17 colonies (2.3%) were defined as erythroid and 736 colonies (97.7%) were defined as myeloid colonies. In the fraction of slowly growing clones, a total of 751 colonies were counted, 25 (3.3%) of which were classified as erythroid and 726 (96.7%) of which were defined as myeloid colonies. No significant difference in the median number of CFU-GM and BFU-E between fast-growing versus slowly growing clones was observed.



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  		Figure 5. Methylcellulose assay illustrating the median (black bar) of lineage-committed progenitor cell capacity in the category of slowly growing clones (n = 25) compared with the category of fast-growing clones (n = 25) in vitro.

 
Gene Expression Pattern in Clones Derived from Single CD34+CD38– Human CB Cells
We analyzed differential gene expression in a total of 134 clones derived from 1440 single-sorted CD34+CD38– cells in two independent experiments with three CB samples each. These 134 clones reached a clone size ≤ 1 x 104 per well between 12 and 30 days in culture. The median time to expand to ≥ 1 x 104 cells was 18 days in both independent experiments. Accordingly, clones that required less time than the median were classified as fast (a total of 79 clones), whereas the remaining clones were classified as slowly growing clones (a total of 55 clones). Clones of each category were pooled for gene expression analysis by oligonucleotide microarrays. For a first analysis, genes that are differentially expressed in fast-growing clones compared with slowly growing clones were required to pass the restrictions in all (three of three) paired samples analyzed. A twofold upregulation of 115 genes was detected in slowly growing clones (Table 1Go), whereas 43 genes showed a downregulation compared with fast-growing clones (Table 2Go). In further analyses, differentially expressed genes that were upregulated were required to have the Affymetrixcall present, and those that were downregulated were required to have the Affymetrixcall absent in all of the samples. This resulted in a selection of 10 genes that could be used to clearly separate fast-growing clones from slowly growing clones by hierarchical cluster analysis (Fig. 6Go). Among the five genes overexpressed in slowly growing clones, three seemed to be of particular interest. Pax4 (paired box gene 4) is involved in embryonal development, CD61 (platelet glycoprotein IIIa) is involved in megakaryopoesis, and ETB (endothelin receptor type B) is involved in cell signaling.


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  		Table 1. Genes upregulated in slowly growing clones compared with fast-growing clones derived from individual CD34+CD38– cells from human umbilical cord blood
 

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  		Table 2. Genes downregulated in slowly growing clones compared with fast-growing clones derived from individual CD34+CD38– cells from human umbilical cord blood
 


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  		Figure 6. Identification of clusters of gene expression in clones derived from CD34+CD38– side scatter from human umbilical cord blood. Increasing the level of statistical restrictions resulted in the selection of 10 genes (vertical list: gene and accession number) that subsequently could be used to clearly separate fast from slowly growing clones by hierarchical clustering with Spearman’s confidence correlation. Horizontal list is each of the samples. Vertical list displays the 10 genes. Color code: Blue, low expression; Red, high expression. The intensity of the color reflects the trust of the expression data.

 
Genes that are differentially expressed in the two categories and passed the restrictions were classified as either hematopoiesis- or nonhematopoiesis-affiliated genes according to their tissue-specific expression or functions (Fig. 7Go). Most of the non-hematopoiesis-affiliated genes are present in the group of slowly growing clones (21%) compared with fast-growing clones (7%). Furthermore, genes involved in embryonal development and early hematopoiesis are predominantly found in the slowly growing fraction. Representative candidate genes are Pax4, Meis (mouse) homologue 2, Ang-1, and SCL/tal-1 (Table 1Go).



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  		Figure 7. Gene expression profiles were analyzed in clones (n = 134) derived from single-sorted CD34+CD38– human umbilical cord blood cells. Categorization of informative sequences by function (A) or by tissue (B) that were upregulated in the category of slowly growing clones (n = 55) compared with the category of fast-growing clones (n = 79) derived from single-sorted CD34+CD38– cells from human umbilical cord blood (n = 3).

 

   DISCUSSION
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
In previous studies, we have shown that CD34+CD38– cells from fetal liver display an extensive functional heterogeneity when cultured as single cells in the presence of a mixture of stimulatory cytokines. Clones with the highest overall proliferative potential could be recognized by their slow growth kinetics [17].

The current follow-up study was aimed at the identification of genetic determinants that can be linked to the slow growth kinetics found in highly proliferative subclones of CD34+CD38– CB cells. In line with our previous observations in fetal liver [17], candidate CD34+CD38– HSCs from CB were found to display an extensive functional heterogeneity when cultured as single cells under defined cultured conditions. Interestingly, although considerable heterogeneity is detectable in fetal liver HSCs already at day 6, individually sorted CD34+CD38– cells from CB divided at a significantly lower rate, and marked differences in growth kinetics could only be assessed at days 12 through 15 in culture. Furthermore, in line with data showing that the proliferative capacity of human HSCs decreases from fetal liver to CB to adult bone marrow [2], the degree of expansion in vitro as well as the proportion of highly proliferative subclones was substantially reduced in CB HSCs compared with fetal liver. In fetal liver, highly proliferative clones were predominantly found in the slowly growing category of clones. In the present study, we could now demonstrate that among highly proliferative clones, the most slowly growing clones were characterized by significantly longer telomeres compared with fast-growing clones. These data support the hypothesis that slowly growing clones possess a higher replicative capacity compared with fast-growing clones. Furthermore, the data support the idea that despite low levels of telomerase activity found in CD34+ cells [20, 21], telomere shortening may be one potential factor that limits HSC replicative potential [4]. In line with this hypothesis, telomeres were found to undergo replicative shortening in vivo [18, 22–24]. These observations indicate that (although telomerase might provide added replicative capacity for HSCs [25]) the degree to which telomerase activity is present in normal HSCs is not sufficient to (completely) prevent replication-dependent telomere shortening. However, although ectopic (over)expression of telomerase led to stabilization of telomere length in mouse HSCs [26], it did not extend their replicative lifespan in a serial transplantation model [25, 27].

To identify potential yet-unknown factors involved in the regulation of stem cell fate and to compare gene expression in the clones studied here with published data on gene expression profiling in highly enriched human or murine HSCs [28–33], microarray analysis in pooled samples of slowly growing as compared with fast-growing clones was performed. We restricted clone sizes for gene-expression profiling to approximately 10,000 cells per well to reduce the impact of genes upregulated during differentiation in the individual wells as much as technically possible. Furthermore, to ensure that we could select differentially expressed genes specific for the fast-/slow-growing clones but not genes that were differentially expressed due to individual clone differences, we have used pooled RNA samples for microarray hybridization. The impact of selected genes was further increased by analyzing two independently pooled samples for each of the conditions. By cluster analysis, we could categorize each individual clone as slow- or fast-growing based on the expression of 10 differentially regulated genes (five upregulated and five downregulated).

Previous studies described promiscuous expression of non-hematopoietic genes to be most pronounced in the immature HSC compartment. In agreement with this assumption, we observed that most nonhematopoietic genes were expressed in the group of slowly growing clones (21%) compared with fast-growing clones (7%). The paired-homeodomain transcription factor Pax4 represents one such candidate nonhematopoietic gene that was found to be overexpressed in slowly growing clones. Pax4 activity appears essential for the initiation of differentiation from embryonic stem cells into functional insulin-producing pancreatic beta-cells [34]. However, this homeobox gene has also been shown to be expressed in very early murine HSCs recently [30]. Homeobox genes encode homeodomain proteins, which play an important role in early embryogenesis. Another homeobox protein, Meis (mouse) homologue 2, a three-amino acid extension loop (TALE) protein, represents a highly conserved transcriptional regulator [35]. Meis2 and Meis3 are Meis1-related genes [36]. Meis1 was reported to be expressed in early CD34+ but not in later CD34– hematopoietic cells. It was proposed that during normal myelopoiesis, Meis1a functions as a molecular switch that changes the response of a cell to both lineage-specific cytokines (e.g., G-CSF) and costimulatory cytokines (e.g., SCF), shifting that response from self-renewal (when Meis1 is expressed in CD34+ cells) to differentiation (when Meis1 is downregulated) [37]. Meis1 was predominantly expressed in HSCs and downregulated in multi-potential progenitors, common lymphoid progenitors, and common myeloid progenitors [30].

Moreover, several other genes involved in embryonal development and early hematopoiesis are predominantly found in the slowly growing fraction. We identified the angiogenesis-regulating gene angiopoietin (Ang-1), a ligand for the Tie-2 receptor, which is also highly expressed in CD34+/CD133+ human CB but not in the CD34–/CD133– fraction [38]. It has been suggested that an autocrine loop of Ang-1 is involved in self-renewal of HSCs and the Tie2/Ang-1 signaling pathway contributes to quiescence of HSCs in the bone marrow stem cell niche [39]. Angiopoietin may therefore play a critical role in keeping HSCs in an immature state [40]. Another gene selectively overexpressed in slowly growing clones was SCL/tal-1, which is known to be required in the specification of HSCs from mesoderm during embryonic development [41]. In the adult hematopoietic system, expression of the transcription factor SCL/tal-1 is increased in HSCs and multipotent progenitors [42].

No significant difference in colony-forming capacity or distribution of myeloid and erythroid colonies was observed between the two groups of slowly growing compared with fast-growing clones. These findings support the assumption that the differences in gene expression observed are not simply due to altered differentiation properties.

In summary, our retrospective analyses in growth kinetics, telomere biology, and gene-expression profiling provide further support for a functional hierarchy within CD34+CD38– candidate HSCs from CB. Within the 5% of clones with the highest proliferative capacity, we were able to discriminate between subpopulations based on growth kinetics, telomere length, and gene-expression pattern. Future studies will be aimed at the characterization and in vivo analysis of selected candidate genes to better define their functional importance for the mechanisms underlying both stem cell maintenance and asymmetric divisions of HSCs.


   ACKNOWLEDGMENTS
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
This study was supported by the Sonderforschungsbereich 510 (Teilprojekt A6) of the Deutsche Forschungsgemeinschaft (Bonn, Germany). We would like to thank Alexandra Wahl and Anke Marxer for excellent technical assistance and Dr. Martin Eichner (Department of Medical Biometry, Tübingen University, Tübingen, Germany) for help with statistical analysis of the data. Furthermore, we would like to thank Andreas M. Boehmler for critical reading of the manuscript.


   REFERENCES
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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Received November 9, 2004; accepted for publication March 30, 2005.




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